diff --git a/.gitattributes b/.gitattributes index 0ca48512d45a9923ee1696f7852bba8ea0172028..10d4e949dbaea816f316cb6efab4fe73559ef537 100644 --- a/.gitattributes +++ b/.gitattributes @@ -237,3 +237,4 @@ data_all_eng_slimpj/shuffled/split/split_finalaa/part-12.finalaa filter=lfs diff data_all_eng_slimpj/shuffled/split/split_finalaa/part-03.finalaa filter=lfs diff=lfs merge=lfs -text data_all_eng_slimpj/shuffled/split/split_finalaa/part-00.finalaa filter=lfs diff=lfs merge=lfs -text data_all_eng_slimpj/shuffled/split/split_finalaa/part-18.finalaa filter=lfs diff=lfs merge=lfs -text +data_all_eng_slimpj/shuffled/split/split_finalaa/part-17.finalaa filter=lfs diff=lfs merge=lfs -text diff --git a/data_all_eng_slimpj/shuffled/split/split_finalaa/part-17.finalaa b/data_all_eng_slimpj/shuffled/split/split_finalaa/part-17.finalaa new file mode 100644 index 0000000000000000000000000000000000000000..51f118c0f34f134525adb0939b1ac5d64768cca2 --- /dev/null +++ b/data_all_eng_slimpj/shuffled/split/split_finalaa/part-17.finalaa @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:84dacf56febad88c9582746f0a3e9e8c30a7f25748c4fc25c0fb8555d358fb24 +size 12576661867 diff --git a/data_all_eng_slimpj/shuffled/split2/finalzrcs b/data_all_eng_slimpj/shuffled/split2/finalzrcs new file mode 100644 index 0000000000000000000000000000000000000000..b6bf8bebc3c0449c4090477396e34608a9c3f311 --- /dev/null +++ b/data_all_eng_slimpj/shuffled/split2/finalzrcs @@ -0,0 +1,5 @@ +{"text":"\\section{Introduction}\n\nMost currently popular models for the formation of galaxies and larger\nstructures postulate that growth occurs hierarchically through\ngravitational clustering in such a way that small objects form first \nand then aggregate into larger systems (Frenk et al. 1988, Carlberg\nand Couchman 1989, Kauffman and White 1993, Lacey and Cole 1993). The \nobservational evidence seems to support these models since it is\npossible to trace the influence of merging both on galaxies and on\nclusters of galaxies. We can classify mergers roughly according to the\nmasses of the objects involved: (1) major mergers and (2) minor\nmergers. The first involve galaxies of comparable mass and are often \ninvoked as a mechanism to form elliptical galaxies\nfrom spiral systems (Toomre 1977, Negroponte and White 1983, Schweizer\n1990, Barnes 1992, Silk and Wyse 1993). Minor mergers involve a giant \ngalaxy accreting a small satellite. The Large Magellanic Cloud and our\nown Galaxy are a clear example of such an ongoing minor merger. In\nspite of a general consensus that minor mergers may drive internal \nevolution in galaxies, the consequences of these events are still not\nclear (Quinn and Goodman 1986, Quinn, Hernquist and Fullagar\n1993, Walker, Mihos and Hernquist 1994 and, Huang and Carlberg 1997; \nhereafter QG, QHF, WMH and HC, respectively).\\\\\n\nAn important constraint on the effects of minor mergers was raised\nby Ostriker (1990) and T\\'oth and Ostriker (1992, hereafter TO).\nIn a high density Universe dominated by cold dark matter (CDM) about \n$80$ per cent of the dark haloes have undergone a merger in the past $5$\nbillion years which increased their mass by 10 per cent or more\n(Frenk et al. 1988, Kauffman and White 1993, Navarro, Frenk and White \n1994). TO argued that such a merger rate is too high to be compatible\nwith the observed thinness and coldness of discs in spiral galaxies. \nUsing a semi-analytic treatment of the problem, they derived an \nuncomfortably low upper limit for the mass that could be accreted by \na disc like that of the Milky Way -- no more than $4$ per cent of the \npresent mass within the solar circle could have been accreted during \nthe last $5$ billion years, given the observed local values of Toomre's \nstability Q-parameter and of disc scale-height. They argued that this\nconstraint favours a low density universe (perhaps with a cosmological\nconstant) in which the expected merger rate is low.\\\\\n\nSeveral complementary lines of investigation have been used to\nevaluate the argument proposed by TO. One approach\nconcentrates on understanding the later stages of merging and the\ndynamical evolution of disc structure.\nSemi-restricted and full N-body simulations\nhave been employed to explore how infalling satellites perturb \ndiscs (QG, TO, QHF, WMH, HC). The most recent work by WMH and\nHC used full N-body simulations and incorporated a key\ningredient in the accretion process, the responsiveness of the\nhalo. A possible weakness of all these studies is that they \nfocussed on satellites on nearly\ncircular orbits. For instance, WMH followed their satellite only\nafter it was already within $21$ kpc of the galaxy centre; this choice\nwas imposed by their decision to use a very large number of particles \n(500,000) in order to reduce numerical noise and to delay the\ngrowth of a bar in their model disc. They found that accretion of a \nsatellite with $10$ per cent of the disc mass was already enough\nto provoke a 60 percent thickening of the stellar disc \nat the solar circle. In contrast, HC found that satellites with\nmasses between $10$-$30$ per cent of the disc mass could be put on\nnear-circular orbits at about $10$ disc half-mass radii,\nand would be sufficiently disrupted by tides before interacting\nstrongly with the disc that their effects on it are quite small.\nThe present paper is a continuation and extension of this line of\nresearch.\\\\\n\nA complementary approach concentrates on evaluating the rate at which\nsatellites are accreted as a function of mass and orbital parameters.\nObservation-based arguments can be used to\nestimate the current merger rate either for dark haloes or for \ngalaxies. Thus, signs of disturbance like tidal tails and shells \ncan be considered signs of a recent merger and thus allow the merger \nrate of luminous galaxies to be obtained. From a sample of\n$4000$ galaxies, 10 were identified by Toomre (1977) as results of a\nrecent merger. From this he was able to derive a lower limit of\n$0.005$ Gyr$^{-1}$ for the current merger rate. A higher merger rate \nof about $0.04$ Gyr$^{-1}$ was found by Carlberg, Pritchet \\& Infante\n(1994) based on the observed numbers of close galaxy pairs and\nthe assumption is that pairs will merge if their closest approach\ndistance and relative velocity are less than their characteristic \nradius and their internal velocity dispersion, respectively (Aarseth\nand Fall 1980). On larger scales it is clear that substructure is a \ncommon feature of clusters of galaxies, suggesting that many of them \nhave formed recently by the merging of several smaller systems\n(Dressler and Shectman 1988; Jones and Forman 1992; Richstone, Loeb \nand Turner 1992). Using another version of the TO argument, the\nobserved amount of substructure in clusters can give an estimate of\nthe current merging rate and so of the cosmic density parameter\n$\\Omega$ (Richstone, Loeb and Turner 1992; Lacey and Cole 1993;\nKauffman and White 1993; Evrard et al. 1994). Neither of these\narguments, however, can give the satellite accretion rates needed to\nevaluate the TO argument.\\\\\n\nSatellite accretion rates can be estimated from theoretical arguments\nbased either on the Press-Schechter model for hierarchical clustering\n(Lacey and Cole 1993) or on high resolution simulations. For example,\nNavarro, Frenk and White (1994, 1995) have carried out a series of\nsimulations of the formation of galaxy-satellite systems in an \n$\\Omega = 1$ CDM universe; their results suggest that the existence of\nthin discs may, perhaps, be reconciled with such a model, because\ndiscs are less efficient at accreting material than are their\nsurrounding dark haloes. In these simulations fewer than 30 per cent\nof the discs grew by more than 10 per cent in mass over the last 5 \nGyr, whereas about $80$ of the haloes grew by this much or more.\nThe distributions of orbital orientation and orbital eccentricity of\ntheir satellites were essentially uniform. Thus,\nLacey and Cole's (1993) suggestion that the TO constraint might be\navoided if satellites are primarily on near-circular orbits does not\nseem to be viable in a realistic hierarchical clustering model. Note\nthat while the simulations of Navarro et al. (1995) give useful \nindications about the rates\nof satellite accretion onto discs, their resolution is too low to\ngive information about how this accretion affects disc structure.\\\\\n\nIn the present paper we address the heating of the\nstellar disc by infalling satellites following the first approach \ndiscussed above. We consider satellites with a variety of internal \nstructures and on orbits with a variety of initial orientations and\neccentricities. We follow the evolution of the systems by using\nfull N-body simulations of all the components. Our paper is organized as\nfollows: section 2 contains brief descriptions of the models we adopt\nfor our primary and satellite galaxies, of our numerical methods, and\nof the parameters of the set of simulations we have carried out. \nSection 3 studies how the disc is heated and thickened by\ninfalling satellites and a comparison with TO's results is given in\nsection 4. We discuss the tilting and warping of the disc resulting\nfrom such events in section 5. Section 6 concentrates on the\ndisruption of the satellite and the evolution of its orbit. We show,\nin section 7, that the latter can be well reproduced by Chandrasekhar's local\nformulation of dynamical friction. In section 8 we replace our\n``live'' halo by a rigid one to demonstrate how halo response affects\nthe accretion and disc heating processes. Finally, in section 9, we\nsummarize our main conclusions.\\\\\n\n\n\n\\begin{table}\n\\begin{center}\n\\centering\n\\label {symbol1}\n\\caption{ Galactic parameters.}\n\\begin{tabular}{|l|c|l|} \\hline \n \t& Symbol & Value \\\\ \\hline \\hline\nDisc: \t& & \t\t\t \t\\\\\n\t& $N_D$ & $40\\,960$\t\t\t\t\t\\\\\n \t& $M_D$ & $ 5.6 \\times 10^{10}$ M$_\\odot$ \t\t\\\\\n \t& $R_D$ & $ 3.5$ kpc \\\\\n\t& $z_o$ & $ 700 $ pc\\\\\n\t& $Q_\\odot $ & $1.5$ \t\t\t\t\t\\\\\n\t& $R_\\odot $ & $8.5$ kpc \\\\\n\t&$\\epsilon_D$& $175$ pc \\\\ \\hline\nBulge: &\t &\t\t\t\t\t\t\\\\\n\t& $N_B$ & $4\\,096$\t\t\t\t\t\\\\\n\t& $M_B$ & $1.87 \\times 10^{10}$ M$_\\odot$\t\t\\\\\n\t& $a^*$ & $525$ pc\t\t\\\\\n\t&$\\epsilon_B$& $175$ pc \\\\ \\hline\nHalo:\t& \t & \t\t\t\t\t\t\\\\\n\t& $N_H$\t & $171\\,752$\t\t\t\t\t\\\\\n\t& $M_H$ & $7.84 \\times 10^{11}$ M$_\\odot$ \\\\\n\t& $\\gamma$ & $3.5$ kpc \\\\\n\t& $r_{cut}$ & $84$ kpc \\\\\n\t&$\\epsilon_H$& $175$ pc \\\\ \\hline\n\\end{tabular}\n\\end{center}\n\\medskip\n$^*$ The bulge half-mass radius is $1.27$ kpc. $N_D$, $N_B$ and $N_H$\ncorrespond to the number of particles used for each galaxy component. \nThe system of units is such that $G=M_D=R_D=1$.\n\n\\end{table}\n\n\\section{Numerical Preliminaries}\n\nIn this section we describe briefly the idealised models which we\nadopt to describe the primary disc galaxy and the satellites which\nmerge with it. We also describe the numerical tools employed to\nfollow the dynamical evolution of the primary\/satellite system, and\nthe parameters which define the specific set of simulations which we\nhave carried out.\n\n\\subsection{The Primary Galaxy Model}\n\nWe use the methods of Hernquist (1993) to set up a self-consistent \nN-body realization of a galaxy model consisting of three\ncomponents: a disc, a bulge and a halo. A detailed description of \nthe technique can be found in Hernquist's paper. The density\ndistributions of the three components are: \\\\ \n\n\\begin{equation}\n\\rho_D(R,z)\\,=\\,{{M_D}\\over{4 \\pi R_D^2 z_o}} \\exp(-R\/R_D)\n\\hbox{ sech}^2(z\/z_o),\n\\end{equation}\n\n\\begin{equation}\n\\rho_B(r)\\,=\\,{{M_B}\\over{2 \\pi}}{{a}\\over{r(a+r)^3}},\n\\end{equation}\n\n\\begin{equation}\n\\rho_H(r)\\,=\\,{{M_H \\alpha}\\over{2 \\pi^{3\/2}r_{cut}}}{{\\exp\n(-r^2\/r_{cut}^2)}\\over{r^2+\\gamma^2}}.\n\\end{equation}\n\nHere, $M_D$, $M_B$ and $M_H$ correspond to the masses of the disc, the\nbulge and the halo, repectively. $R_D$ and $z_o$ are the radial and vertical\nscale lengths of the disc. $a$ defines the scale length of the bulge\nand corresponds to a half-mass radius of $a(1+\\sqrt{2})$ (Hernquist\n1990). Finally, $\\gamma$ and $r_{cut}$ are the core and cut-off radii\nfor the halo and $\\alpha$ is a normalisation constant. Notice that we\nassume both the bulge and the halo to be spherical.\\\\ \n\nThe velocities are derived from the Jeans equations (e.g. Binney and\nTremaine 1987). Isotropic gaussians are assumed for the halo and\nbulge velocity distributions. For the disc, the square of the radial\nvelocity dispersion is taken to be proportional to the surface density\nof the disc, $\\sigma_R^2 \\propto \\exp(- R_D\/R)$ (Lewis and Freeman\n1989) and the vertical component of the velocity ellipsoid is\ndetermined from $\\sigma_z^2=\\pi G \\Sigma (R) z_o$ in agreement with an\nisothermal sheet (Spitzer 1942). The azimuthal component is obtained\nfrom the epicyclic approximation, $\\sigma_\\phi^2=\\sigma_R^2\n\\kappa^2\/(4 \\Omega^2)$. Finally, the constant of proportionality is\ndetermined by fixing the value of Toomre's stability Q-parameter to a\ngiven value. We select $Q_\\odot = Q( R_\\odot) =1.5$ at the Solar radius. \\\\\n\nWe have chosen a system of units such that $U_m=M_D=1$, $U_l=R_D=1$ and\n$G=1$. For a disc mass of $5.6 \\times 10^{10}$ M$_\\odot$ and a disc radial \nscale length of $3.5$ kpc (Bahcall, Schmidt and Soneira 1983) the units of \ntime and velocity are $1.3 \\times 10^7$ yr and $262$ kms$^{-1}$, \nrespectively. The half-mass radius of the disc is $\\sim 1.7\\,R_D$ with \na rotation period at this radius of about $13$ time units. The model can \nbe easily scaled through the following expressions for the time and velocity \nunits:\n\n\\begin{equation}\nU_t\\,=\\,4.709\\times 10^{11}\\,\\Big{(}{U_l^3\\over U_m}\\Big{)}^{1\/2}\\, \\hbox{yr}\n\\end{equation}\n \n\\begin{equation}\nU_v\\,=\\,2.076 \\times 10^{-3}\\,\\Big{(}{U_m\\over U_l}\\Big{)}^{1\/2}\\,\\hbox{kms}^{-1}\n\\end{equation}\n \n\\noindent where $U_m$ and $U_l$ are given in solar masses and \nkpc, respectively. In Table 1 we summarize the values of the \nparameters that define our primary galaxy model. \\\\\n\nWe should notice that \n(1) our halo is probably too small to be realistic.\nStudies of satellites in the Local Group and around external\ngalaxies show that galactic haloes extend to radii beyond $200$ kpc\nwith masses exceeding $2 \\times 10^{12}$ M$_\\odot$ (Zaritsky et al.\n1989, Zaritsky and White 1994). However, our halo is consistent with\nthe largest velocities observed for halo stars in the solar neighborhood\n(Carney and Lathman 1987) and should be massive enough to give\nrealistic orbital velocities for eccentric satellite orbits. (2) Our \nhalo is maybe too concentrated. Persic, Salucci and Stel (1996) argue for a \nhalo core radius of about $1-2\\,R_{opt}$ where $R_{opt}=3.2\\,R_D$ is the \noptical radius. However, a model with such a halo will be prone to \nform a bar which is an undesirable additional source of disc heating and \nto prevent its growth it will be necessary to increase the bulge \ncontribution. The values of the parameters listed in Table 1 guarantee \nstability against bar formation of the disc galaxy model in isolation (Vel\\'azquez \nand White, in preparation). \\\\\n \nThe rotation curve of our galaxy model (solid lines) is shown in figure 1. \nFor comparison, two other rotation curves are displayed for different bulge \nmasses but with the same disc and halo. The rotation curve for our galaxy \nmodel at the optical radius is $V_C(R_{opt})\\approx 243$ kms$^{-1}$ in model units while the \nmodels with a bulge mass of $M_B=0.2\\,M_D\\,(=1.12 \\times 10^{10}\\,\\hbox{M}_\\odot)$ and $M_B=2\/3\\,M_D\\,\n(=3.73 \\times 10^{10}\\,\\hbox{M}_\\odot)$ have values of \n$V_C(R_{opt})\\approx 236$ kms$^{-1}$ and $V_C(R_{opt})\\approx 257$ kms$^{-1}$, respectively. We can \nobserve that, at difference of the sample of rotation curves given by \nPersic et al. (1996), the rotation curve of our model shows a steeper rise \nin the inner region which is consistent with the observed nuclear rotation curves of galaxies in the CO-line emission and with the optical rotation \ncurves for large bright galaxies (Sofue et al. 1997, Courteau 1997). Furthermore, it peaks near $R_{opt}$ in agreement with the results of \nCourteau (1997). \\\\\n\n\n\\begin{figure}\n\\plotone{Fig01.ps}\n\\caption{ The rotation curve for our disc galaxy model \n(solid lines) has a value of $V_C(R_{opt})\\approx 243$ kms$^{-1}$ where \n$R_{opt}=3.2\\,R_D$. Dotted-lines and dashed-lines \ncorrespond to rotation curves for bulge masses of $0.2\\,M_D$ and $2\/3\\,M_D$ \nwith values of $V_C(R_{opt})\\approx 236$ kms$^{-1}$ and $V_C(R_{opt})\\approx 257$ kms$^{-1}$, \nrespectively. For clarity the contribution of the disc and halo are not \nshown. The arrow indicates the Solar position.}\n\\label{Fig. 1}\n\\end{figure}\n\nFinally, we should mention that for this galaxy model we have used a \ntotal number of $216\\,808$ particles. Most of these are in the halo \ncomponent $(171\\,752)$ where large numbers are required to reduce \nheating of the disc by two-body relaxation effects. \\\\\n\n\n\\begin{table}\n\\begin{center}\n\\centering\n\\label {symbol2}\n\\caption{ Satellite models.}\n\\begin{tabular}{|l|c|l|} \\hline\n Model & Symbol & Value \\\\ \\hline \\hline\n S1:\t& & \t\t\t \t\\\\\n \t& $M_S$ & $ 5.60 \\times 10^9$ M$_\\odot$ \t\t\\\\\n \t& $r_c$ & $1$ kpc \\\\\n\t& $c$ & $0.8$ \\\\ \n\t& $\\rho_c$ & $0.52$ M$_\\odot$\/pc$^3$ \\\\ \n\t& $\\sigma_c$& $52$ kms$^{-1}$\t\\\\\t\\hline\n S2: &\t &\t\t\t\t\t\t\\\\\n \t& $M_S$ & $ 5.60 \\times 10^9$ M$_\\odot$ \t\t\\\\\n \t& $r_c$ & $ 500$ pc \\\\\n\t& $c$ & $ 1.1$\t\t\t\t \t\\\\ \n\t& $\\rho_c$ & $0.84$ M$_\\odot$\/pc$^3$ \\\\ \n\t& $\\sigma_c$& $60$ kms$^{-1}$ \\\\ \\hline\n S3: &\t &\t\t\t\t\t\t\\\\\n \t& $M_S$ & $ 1.12 \\times 10^{10}$ M$_\\odot$\t\\\\\n \t& $r_c$ & $ 875$ pc \\\\\n\t& $c$ & $ 1$\t\t\t\t \t\\\\ \n\t& $\\rho_c$ & $ 1.36 $ M$_\\odot$\/pc$^3$ \\\\ \n\t& $\\sigma_c$& $ 71$ kms$^{-1}$ \\\\\t\t\\hline\n\\end{tabular}\n\\end{center}\n\\medskip\n$c$ defines the concentration of the satellite model and is given by\n$\\log_{10}(r_{t}\/r_c)$ where $r_c$ and $r_t$ are, respectively, the\ncore and tidal radii of a King model. $M_S$, $\\rho_c$ and $\\sigma_c$ denote \nthe satellite mass, the central density and the central one-dimensional \nvelocity dispersion, respectively.\n\\end{table}\n\n\n\\begin{figure}\n\\plotone{Fig02.ps}\n\\caption{ Rotation curve for our satellite models.}\n\\label{Fig. 2}\n\\end{figure}\n\n\\subsection{ Satellite Models}\n\nThe satellites are represented by self-consistent King models (King\n1966) which provide a reasonable fit to early-type and nucleated dwarf\ngalaxies (Vader and Chaboyer 1994). These models are a sequence of\ntruncated isothermal spheres parametrized by a concentration $c \\equiv\n\\log_{10}(r_t\/r_c)$, where $r_t$ and $r_c$ are the so-called tidal and\ncore radii, respectively. To specify completely a satellite model we\nprovide the satellite mass, $M_S$, its concentration and its tidal radius. \nThe latter is estimated from the density contrast\n$\\rho_S(r_t)\/\\overline{\\rho}_G(r_a) \\sim 3 $ at the apocentric\ndistance, $r_a$, of the orbit where the satellite is initially\nplaced. The parameters that characterize our satellite \nmodels, including the central density and the central one-dimensional \nvelocity dispersion, are listed in Table 2 which are within the observed \nvalues (Vader and Chaboyer 1994; Binggeli and Cameron 1991; Bender, Burstein \nand Faber 1992). The rotation curve for each satellite model is shown in \nfigure 2. We can notice that our satellite models are more concentrated than \nDD154-type dwarf galaxies (Moore 1994). In all cases, the \nsatellite consists of $8192$ particles. \\\\\n\n\\subsection{ Numerical Methods and Orbital Parameters}\n\nTo follow the evolution of the galaxy-satellite system we use a tree\nalgorithm with a tolerance parameter of \n$\\theta_{\\hbox{{\\footnotesize tol}}}=0.75$ and\nan integration timestep of $1.3 \\times 10^6$ yrs. Forces between particles are\ncomputed including the quadrupole components (see Barnes and Hut (1986)\nand Hernquist (1987) for details of this code). With these values, the\nconservation of global energy and angular momentum is better than $1$ \nper cent for all our models.\\\\ \n\nSince our initial galaxy and satellite models are not in a perfect\nequilibrium we allow them to relax separately before starting an\ninteraction simulation. The disc galaxy is relaxed for 20 time units, \nabout one and a half rotation periods at its half-mass radius, \nwhile the satellite\nis allowed to evolve for $40$ time units to reduce initial transient\neffects. These two configurations are then superposed to create\nour initial conditions. We have performed a set\nof experiments varying the parameters that are likely to\ninfluence the result of a galaxy-satellite interaction, for example, the\n`circularity' of the orbit, the angle between the angular momentum of\nthe satellite and the disc, and the satellite structure. In Table 3\nwe list the parameters\nof these simulations. Here, the `circularity' of the orbit has been\ndefined as $\\epsilon_J \\equiv J\/J_C(E)$, where $J$ is the\nangular momentum of the satellite and $J_C(E)$ is the corresponding\nangular momentum for a circular orbit of the same energy $E$ as the \nsatellite's orbit. Also, we\nhave followed the subsequent evolution of the galaxy model in\nisolation (our control model) to distinguish effects produced by\ntwo-body encounters from those provoked by the accretion of the\nsatellite. The discussion of the following sections all refers to\nsatellites on orbits which actually intersect the disc. \\\\\n\n\n\\begin{table}\n\\begin{center}\n\\centering\n\\label {symbol3}\n\\caption{ Simulations.}\n\\begin{tabular}{|l|c|c|c|c|c|} \\hline\n Name & Sat. model & $\\theta_i$ & $\\epsilon_J$ & $r_p\/R_D$ & $r_a\/R_D$ \\\\ \\hline \\hline\nG1S1 & S1\t & $45^{o}$ & $0.33$ & $1.5$ & $16.86$ \\\\\nG1S2 & S1\t & $0^{o}$ & $0.55$ & $3$ & $15.71$ \\\\\nG1S3 & S1\t & $45^{o}$ & $0.55$ & $3$ & $15.71$ \\\\\nG1S4 & S1\t & $90^{o}$ & $0.55$ & $3$ & $15.71$ \\\\\nG1S5 & S1\t & $135^{o}$ & $0.55$ & $3$ & $15.71$ \\\\ \nG1S6 & S1\t & $180^{o}$ & $0.55$ & $3$ & $15.71$ \\\\\nG1S7 & S1\t & $0^{o}$ & $0.82$ & $6$ & $13.29$ \\\\\nG1S8 & S1\t & $45^{o}$ & $0.82$ & $6$ & $13.29$ \\\\\nG1S9 & S2\t & $0^{o}$ & $0.55$ & $3$ & $15.71$ \\\\\nG1S10 & S2\t & $45^{o}$ & $0.55$ & $3$ & $15.71$ \\\\\nG1S11 & S2\t & $90^{o}$ & $0.55$ & $3$ & $15.71$ \\\\\nG1S12 & S2\t & $135^{o}$ & $0.55$ & $3$ & $15.71$ \\\\\nG1S13 & S2\t & $180^{o}$ & $0.55$ & $3$ & $15.71$ \\\\\nG1S14 & S3\t & $45^{o}$ & $0.55$ & $3$ & $15.71$ \\\\ \nG1S15 & S3\t & $135^{o}$ & $0.55$ & $3$ & $15.71$ \\\\\n\\hline\n\\end{tabular}\n\\end{center}\n\\medskip\n$\\theta_i$ refers to the angle between the initial angular momentum of\nthe satellite and the initial angular momentum of the disc. $\\epsilon_J$ \ndefines the circularity of the orbit, $r_p$ and $r_a$ correspond to\nthe initial pericentric and apocentric radii of the orbit, respectively. \n\\end{table}\n\n\n\n\n\\begin{figure*}\n\\vskip 16cm\n\\caption{ The evolution of the disc for model G1S10. A fourth of the \ntotal number of disc particles has been plotted. The satellite has \nbeen tidally disrupted at time 252. By this time, the disc has been \nslightly tilted and shows an asymmetric configuration (see text for \na discussion of some of these issues).}\n\\label{Fig. 3}\n\\end{figure*}\n\n\n\\begin{figure*}\n\\vskip 16cm\n\\caption{ The disc evolution for the retrograde counterpart of \nfigure 3 (see model G1S12 in Table 3). The disc looks thicker \nthan it really is because of tilting.}\n\\label{Fig. 4}\n\\end{figure*}\n\n\n\\begin{figure}\n\\plotone{Fig05.ps}\n\\caption{ The kinematical properties of the disc in our\nmodel G1S10. Solid lines give the kinematics of the disc in this \nmodel after $3.3$ Gyr, while short-dashed lines show corresponding \nquantities for our control model. Dotted lines show the \ndifference between the two, and so the part of the changes due purely \nto the interaction. In all plots the vertical long-dashed line indicates \nthe position at $R_\\odot$.}\n\\label{Fig. 5}\n\\end{figure}\n\n\\section{ Disc Heating and Thickening }\n\nIn figures 3 and 4 we show the evolution of the disc of our models \nG1S10 and G1S12 (see Table 3). At the end of these simulations the \nsatellite has been completely disrupted and the disc component has \nbeen altered in three different ways: (1) it is hotter and thicker; \n(2) it is no longer axisymmetric; and (3) it is tilted and warped. \nWe discuss some of these effects in this and the following sections. \\\\\n\n\n\\begin{figure}\n\\plotone{Fig06.ps}\n\\caption{ The response of the disc to the infall of\na satellite with an initial mass of $0.2\\,M_D$. The satellite at this\ntime ($2.34$ Gyr) has been completely destroyed. The solid lines\ncorrespond to a satellite following a prograde orbit with initial\nangle of $\\theta_i = 45^o$, (G1S14) while the long-dashed lines\ncorrespond to its retrograde counterpart (G1S15) with $\\theta_i =\n135^o$. For reference, the\nkinematical structure in our isolated control model is also\nshown (short-dashed lines). The kinematical changes for model G1S14 \nare indicated by dotted lines and for model G1S15 by dashed-dotted lines. \nThe vertical line again indicates the position at the Solar radius.}\n\\label{Fig. 6}\n\\end{figure}\n\nTo determine the kinematics of the disc we rotate to axes aligned with\nthe principal\naxes of the disc inertia tensor and then average particle properties in\nconcentric cylindrical annuli. These averages are a\ncrude measure of the disc kinematics since warping and\nazimuthal asymmetry are not taken into account. The heating and thickening of the disc can be described by the\nchanges of the velocity dispersions $(\\Delta \\sigma_R, \\Delta\n\\sigma_\\phi, \\Delta \\sigma_z)$ and by the increase of the vertical\nscale length, $\\Delta z_o$. Effects due to two-body relaxation can\nbe subtracted by comparing the final state to that of the control model.\nThe increase of Toomre's stability parameter, $Q$, is also shown.\nWe compute the vertical scale length in each annulus \nusing the following definition $z_o (R) \\equiv ^{1\/2}$. \\\\ \n\nIn figure 5 we show the disc kinematical properties of our model G1S10 (solid lines)\ntogether with the corresponding properties of the control model (short-dashed lines). It is evident \nfrom this figure that thickening of the stellar disc\ndoes not occur uniformly at all radii; regions beyond $R_\\odot$\nare much more susceptible to damage by the infalling satellite than\nthe inner disc. Given the complexity of the\nfinal disc structure we found it convenient to sample the kinematics at\nthree representative radii: near the centre (averaged out to $\\sim 2$ kpc), at $R_\\odot$, and at $14$ kpc. This is sufficient to provide us\nwith a global view of the heating and thickening. In Table 4 we give \nthe final disc structure at these radii for all our simulations listed in \nTable 3\\footnote{Satellite particles are not considered in computing the \nkinematical properties of the disc because, in most of the cases, their orbits \ndo not fall into the disc plane and so they would be separeted from disc \nparticles by their kinematics. Particles from satellites on prograde \ncoplanar orbits would be more difficult to distinguish, however, in these \nsimulations they form a disc-like structure with a hole of about $3-4$ kpc \nin the central region (see also Barnes 1996).}. For example, the velocity \nellipsoid of the disc in model \n(G1S10) grows by $(18,12,8)$ kms$^{-1}$, $(12,10,5)$ kms$^{-1}$ and\n$(19,14,8)$ kms$^{-1}$ (from inside to outside) resulting in \nincreases of\nToomre's $Q$ parameter by about $0.4$, $0.8$ and, $2.2$. Before the accretion event $Q$ was roughly constant between $3$ kpc \nand $9$ kpc with a value of $\\sim 1.5$ and after\nsatellite accretion it has risen to $Q \\sim 2$ between $3$ kpc and $7$ kpc. \nThe vertical scale length in this same case increases by $100$ pc, $275$ pc \nand $500$ pc, representing a thickening by about $14$, $39$\nand, $71$ per cent; while for its retrograde counterpart (model G1S11) is of $21$, $21$ and $43$ per cent. Disc thickening is even lower \nfor model G1S3 being of $7$, $14$ and $43$ per cent (see entries in Table 4). \nIn some of the models \n(G1S5, G1S10, G1S12 and G1S14) satellite accretion induces \nadditional heating and thickening by exciting a bar-like instability \nin the inner $5$ kpc. \\\\ \n\nThree main trends are observed in our simulations: (1) a mighty\ncorrelation between the change in disc structure and the relative\norientation of disc and satellite angular momenta. We find\nthat, in general, the disc is much more susceptible to damage by a satellite\non a prograde orbit than by its retrograde counterpart. This suggests\na resonant coupling between satellite orbit and disc. This difference\nis most clearly seen by comparing the entries in Table 4 for \nthe coplanar prograde case (model \nG1S9) and the corresponding polar case (model G1S11). In figure 6, we \nillustrate these effects using our two simulations with massive \nsatellites (G1S14 and G1S15 in Table\n3). Notice that for the retrograde case the disc is less strongly\naffected at all radii. (2) In general, the planar\ncomponents of the velocity ellipsoid\nrespond more strongly than the vertical component to the\naccretion of the satellite. Indeed, the ratio of the two planar components\nis fixed by epicyclic theory. The degree of anisotropy \nis correlated with both the inclination and the sense of motion of the\norbit, being greatest for prograde coplanar orbits.\nAs a result Toomre's stability parameter $Q$ responds more\nsensitively than the vertical scale length to the\naccretion event. This is largely a consequence of the fact (addressed\nin section 5) that\nvertical perturbations tend to tilt the disc rather than to heat it.\n(3) For our model G1S3 the effects of accretion on the disc are\nquite modest, but a more massive and compact satellite can have a very\nlarge effect (see entries of model G1S3 and G1S14 in Table 4). \\\\ \n\n\n\\begin{table*}\n\\begin{center}\n\\centering\n\\caption{Disc kinematical changes.}\n\\begin{tabular}{|l|c|c|c|c|c|c|c|c|c|} \\hline\n\\multicolumn{1}{|c|}{} & \\multicolumn{3}{|c|}{$R_{c}^{*}$} & \\multicolumn{3}{|c|}{$R_\\odot$} & \\multicolumn{3}{|c|}{$R_{4}^{\\dag}$} \\\\ \\hline\nModel & $\\scriptstyle{(\\Delta \\sigma_R,\\Delta \\sigma_\\phi,\\Delta \\sigma_z)}$ & $\\scriptstyle{\\Delta Q}$ & $\\scriptstyle{\\Delta z_o}$ & $\\scriptstyle{(\\Delta \\sigma_R,\\Delta \\sigma_\\phi,\\Delta \\sigma_z)}$ & $\\scriptstyle{\\Delta Q}$ & $\\scriptstyle{\\Delta z_o}$ & $\\scriptstyle{(\\Delta \\sigma_R,\\Delta \\sigma_\\phi,\\Delta \\sigma_z)}$ & $\\scriptstyle{\\Delta Q}$ & $\\scriptstyle{\\Delta z_o}$ \\\\ \n\t & (kms$^{-1}$) & & (pc)& (kms$^{-1}$)& & (pc)\n& (kms$^{-1}$) & & (pc) \\\\ \\hline \\hline\n{G1S1} & $(9,6,4)$ & $0.3$ & {$50$} & $(5,3,2)$ & $0.5$ & {$150$} & $(10,7,4)$ & $1.2$ & $225$ \t\\\\\n{G1S2} & $(16,8,4)$ & $0.4$ & {$75$} & $(16,10,4)$ & $1.1$ & {$200$} & $(32,21,6)$ & $2.6$ & $300$ \t\\\\\n& [$(16,7,5)$] & [$0.5$] & [{$100$}] & [$(31,12,4)$] & [$1.4$] & [{$200$}] & [$(47,26,9)$] & [$2.9$] & [$450$] \\\\\n{G1S3} & $(10,7,5)$ & $0.3$ & {$50$} & $(5,3,2)$ & $0.5$ & {$100$} & $(11,6,5)$ & $1.4$ & $300$ \t\\\\\n{G1S4} & $(12,6,4)$ & $0.5$ & {$100$} & $(4,3,2)$ & $0.4$ & {$100$} & $(6,5,4)$ & $0.9$ & $250$ \t\\\\\n{G1S5$^{\\ddag}$} & $(24,16,8)$ & $0.6$ & {$200$} & $(4,2,3)$ & $0.5$ & {$100$} & $(6,6,4)$ & $1.0$ & $150$ \t\\\\ \n{G1S6} & $(6,5,7)$ & $0.3$ & {$75$} & $(5,4,3)$ & $0.4$ & {$100$} & $(10,7,5)$ & $1.7$ & $275$ \t\\\\\n{G1S7} & $(38,18,8)$ & $0.4$ & {$100$} & $(16,12,5)$ & $1.2$ & {$250$} & $(27,14,7)$ & $3.4$ & $450$ \t\\\\\n & [$(38,17,9)$] & [$0.4$] & [{$100$}] & [$(15,12,6)$] & [$1.1$] & [{$250$}] & [$(29,16,8)$] & [$3.4$] & [$500$] \\\\\n{G1S8} & $(10,10,6)$ & $0.3$ & {$50$} & $(10,7,4)$ & $0.8$ & {$150$} & $(17,12,6)$ & $2.2$ & $350$ \t\\\\\n{G1S9} & $(19,13,11)$ & $0.5$ & {$100$} & $(22,15,7)$ & $1.5$ & {$300$} & $(37,23,9)$ & $2.6$ & $550$ \t\\\\\n & [$(19,13,11)$] & [$0.5$] & [{$100$}] & [$(25,15,8)$] & [$1.6$] & [{$350$}] & [$(43,28,12)$] & [$2.9$] & [$675$] \t\\\\\n{G1S10$^{\\ddag}$} & $(18,12,8)$ & $0.4$ & {$100$} & $(12,10,5)$ & $0.8$ & {$275$} & $(19,14,8)$ & $2.2$ & $500$ \t\\\\\n{G1S11} & $(11,10,6)$ & $0.4$ & {$100$} & $(7,4,4)$ & $0.5$ & {$150$} & $(11,8,5)$ & $1.0$ & $300$ \t\\\\\n{G1S12$^{\\ddag}$} & $(17,11,11)$ & $0.8$ & {$150$} & $(4,4,4)$ & $0.4$ & {$150$} & $(10,6,6)$ & $1.0$ & $300$ \t\\\\ \n{G1S13} & $(7,8,4)$ & $0.5$ & {$75$} & $(12,10,7)$ & $0.8$ & {$250$} & $(19,15,10)$ & $2.4$ & $700$ \t\\\\\n{G1S14$^{\\ddag}$} & $(32,20,12)$ & $0.6$ & {$150$} & $(22,15,12)$ & $1.2$ & {$550$} & $(27,18,16)$ & $2.9$ & $800$ \t\\\\\n{G1S15} & $(20,12,8)$ & $0.6$ & {$100$} & $(11,9,6)$ & $0.8$ & {$300$} & $(21,12,10)$ & $2.2$ & $525$ \t\\\\ \\hline\n\n\\end{tabular}\n\\end{center}\n\\medskip\nSymbols $*$ and $\\dag$ denote quantities at the centre and $4\\,R_D$,\nrespectively. Models forming a bar are indicated by the symbol\n$\\ddag$. Quantities in brackets are computed by taking into account satellite \nparticles.\n\\end{table*}\n\n\\subsection{ Disc Heating and the Bulge\/Disc Mass Ratio}\n\nTo address the effect of the bulge in the heating process of the stellar \ndisc we have repeated a few of our simulations but with two additional \ngalactic models. One of them has a bulge with a mass of $M_B=0.2\\,M_D$ and the other with a mass of $M_B=2\/3\\,M_D$. We did not pursue a larger reduction of \nthe bulge mass since it requires a huge number of particles $(> 5\\times 10^5)$ to keep stable the disc against bar formation during the \ndisruption times in our simulations; this would be prohibitive (e.g. Walker et al. 1996). In these models both the disc and halo are \nthe same as in our primary galaxy model of section 2. In figure 1 we \nshow the rotation curves for these new galactic models.\\\\\n\nIn Table 5 we summarize the disc kinematical changes for these new experiments. \nPrefix G2 and G3 refer to the galactic model with the less and more \nmassive bulge, respectively. We should mention that model `G2' develops a \nbar in isolation at time $\\sim 3.2$ Gyr inside $4$ kpc. Comparing the entries \nin tables 4 and 5 at the Solar radius we can see that the disc has \nbeen thickened by $39$, $39$ and $21$ per cent for models G1S10, G2S10 \nand G3S10, respectively, while for their retrograde counterparts (G1S12, G2S12 and G3S12) the corresponding values are only of $21$, $29$ and \n$14$ per cent. This suggest that a very \nmassive bulge would be more efficient in reducing the heating and \nthickening of the stellar disc. This effect can be more clearly appreciated in \nour models with the more massive satellite (models G1S14, G1S15, G3S14 \nand G3S15). Thus, the difference between the thickening found \nby Walker et al. (1996) ($\\sim 60$\\%) and that in our simulations can \nbe attributed \nto the fact that in the former case the satellite interacts strongly with \nthe disc because of the orbit chosen and because of the bulgeless galaxy \nmodel. The latter forms a bar during the early stages of the accretion. \\\\ \n\n\n\\begin{table*}\n\\begin{center}\n\\centering\n\\caption{Disc kinematical changes.}\n\\begin{tabular}{|l|c|c|c|c|c|c|c|c|c|} \\hline\n\\multicolumn{1}{|c|}{} & \\multicolumn{3}{|c|}{$R_{c}^{*}$} & \\multicolumn{3}{|c|}{$R_\\odot$} & \\multicolumn{3}{|c|}{$R_{4}^{\\dag}$} \\\\ \\hline\nModel & $\\scriptstyle{(\\Delta \\sigma_R,\\Delta \\sigma_\\phi,\\Delta \\sigma_z)}$ & $\\scriptstyle{\\Delta Q}$ & $\\scriptstyle{\\Delta z_o}$ & $\\scriptstyle{(\\Delta \\sigma_R,\\Delta \\sigma_\\phi,\\Delta \\sigma_z)}$ & $\\scriptstyle{\\Delta Q}$ & $\\scriptstyle{\\Delta z_o}$ & $\\scriptstyle{(\\Delta \\sigma_R,\\Delta \\sigma_\\phi,\\Delta \\sigma_z)}$ & $\\scriptstyle{\\Delta Q}$ & $\\scriptstyle{\\Delta z_o}$ \\\\ \n\t & (kms$^{-1}$) & & (pc)& (kms$^{-1}$)& & (pc)\n& (kms$^{-1}$) & & (pc) \\\\ \\hline \\hline\n{G2S10$^{\\ddag}$} & $(16,11,10)$ & $0.7$ & {$75$} & $(12,7,7)$ & $0.8$ & {$275$} & $(18,11,9)$ & $1.3$ & $600$ \t\\\\\n{G2S12$^{\\ddag}$} & $(9,10,5)$ & $0.3$ & {$100$} & $(7,5,4)$ & $0.7$ & {$200$} & $(11,6,9)$ & $0.7$ & $400$ \t\\\\ \\hline\n{G3S3} & $(5,6,6)$ & $0.6$ & {$50$} & $(4,3,3)$ & $0.4$ & {$100$} & $(7,6,4)$ & $0.8$ & $200$ \t\\\\\n{G3S10} & $(9,6,5)$ & $0.8$ & {$100$} & $(7,5,5)$ & $0.5$ & {$150$} & $(16,10,7)$ & $1.5$ & $400$ \t\\\\ \n{G3S12} & $(6,5,3)$ & $0.7$ & {$50$} & $(4,3,2)$ & $0.4$ & {$100$} & $(6,6,5)$ & $0.7$ & $275$ \t\\\\\n{G3S14} & $(16,6,9)$ & $0.8$ & {$75$} & $(10,8,8)$ & $0.8$ & {$325$} & $(26,14,13)$ & $2.5$ & $750$ \t\\\\\n{G3S15} & $(10,8,4)$ & $0.5$ & {$50$} & $(6,4,5)$ & $0.5$ & {$200$} & $(13,9,8)$ & $1.4$ & $425$ \t\\\\ \\hline\n\\end{tabular}\n\\end{center}\n\\medskip\nSymbols as in Table 4.\n\\end{table*}\n\n\n\\begin{figure*}\n\\ppplotone{Fig07.ps}\n\\caption {Disc kinematical changes in the Solar neighborhood. Here, we\nshow the changes in the parameter $Q$ (top-left), in the vertical\nscale length (top-right), and in the vertical (bottom-left) and radial\n(bottom-right) velocity dispersions as resulting by the accretion of a\nsatellite of mass $M_S$. Solid and dashed lines represent the\nkinematical changes as predicted by TO's formulae while starred \nsymbols represent the results from all our simulations (see text for details).}\n\\label{Fig. 7}\n\\end{figure*}\n\n\\section{ Comparison with TO's Results}\n\n\nIt is interesting to compare the size of the effects we find with\nthose predicted analytically by TO. They give formulae for the changes\nin the disc vertical scale length, velocity dispersions and stability\nparameter $Q$ (their equations 2.16, 2.21, 2.25 and 2.26). These can be\nused to estimate the quantities we list in Table 4 and 5. We apply\nthese formulae by inserting the properties of the unperturbed disc (as\nmeasured in our control model) at the Solar radius and the satellite\ntotal mass, and by averaging over the orbital inclination of the\nsatellite. In figure 7,\nwe show the resulting disc changes as predicted by TO\n(solid and dashed lines for two extreme cases) together with \nthose found in our simulations (denoted by starred symbols). The solid \nlines correspond to a vertical ($\\epsilon_\\perp$) and \nepicyclic ($\\epsilon_\\parallel$) efficiency heating assuming circular \norbits with random inclinations for the \nvelocity distribution of the satellites while the dashed lines refer to \nan isotropic Maxwellian distribution (see TO, Appendix A). Clearly, the \nanalytical predictions tend to\noverestimate the disruptive effects of satellite accretion by a\nnon-negligible factor; typically about $2-3$. These\ndifferences are more marked for the more massive satellite. Notice\nthat for models G1S2, G1S7 and G1S9 the change in\nthe stability parameter is closer to that predicted by TO. This is\nbecause the satellite in these models (which follows a prograde orbit\nnear the disc plane) induces substantial deviations in $\\Sigma_D(R)$. These\ndeviations were taken into account in determining the change in $Q$\nfor figure 7. If we ignore such variations,\nas TO did, then $\\Delta Q$ is entirely determined by $\\Delta\n\\sigma_R$; the difference is then more dramatic since\nthe change in $Q$ is reduced to $0.8$, $0.7$ and $1.0$ for models G1S2, \nG1S7 and G1S9, respectively. \\\\\n\nThe fact that we find substantially weaker effects than those\npredicted by TO suggests that their limits on the accretion rate of\nsatellites (based on the thinness of observed discs, and their\nsusceptibility to spiral instabilities) are likely to be too strict.\nThere are some additional effects which may result in our own results\nstill being a significant overestimate of the extent of the damage.\n\\begin{itemize}\n\\item The stellar dynamical heating of the disc in our \nsimulations may be partially compensated by dissipative effects in a\ngaseous component. N-body\/Hydrodynamical simulations carried out by Mihos and\nHernquist (1994) and the recent work by HC reveal that gas cooling can make\nan important contribution to sustaining spiral structure in galaxies.\n\\item Our simulations begin with the satellite already\nquite close to the disc and have relatively low mass halos. They are\nthus likely to underestimate disruptive effects on the satellite\nbefore it begins to interact strongly with the disc (see HC).\nProgress on this point will require larger simulations and properly\nrealistic ``cosmological'' initial conditions. Currently available \nresults suggest that discs may accrete material less efficiently\nthan haloes (NFW94, NFW95). \n\\item Damaging effects on disc structure will be\ndiminished whenever the satellite is less concentrated than those we\nhave considered and so can be disrupted before encountering the disc\n(again see HC). Although simulations from\ncosmological initial conditions show that the distribution of orbital \neccentricities should be almost uniform so that a significant\nfraction of satellites reach the disc essentially unperturbed on their first\npassage, such\nhigh velocity, near-radial encounters cause less damage than\nprograde encounters at lower velocities.\n\\end{itemize}\nIt is interesting that the properties of the most strongly perturbed\ndiscs in our simulations do seem to agree with those of the thick disc\ncomponent at the solar radius. This component has a velocity ellipsoid\nof about $(63,42,38)$ kms$^{-1}$, a vertical scale length of $1$ kpc\nand an asymmetric drift of about $25$ kms$^{-1}$ (Freeman\n1996). Similar structure can be seen in the\ngalaxy NGC $4565$ for which the vertical scale length is $\\approx \\,\n1.5$ kpc (Morrison 1996). \\\\\n\nThe difference between TO's analytical results and those of our\nsimulations may be due to one or a combination of the following\nfactors: \n\\begin{itemize}\n\\item A self-gravitating satellite has the capacity to absorb part of\nits orbital energy which can be carried away by the stripped\nmaterial. In this way, the deposition of energy onto the disc is diminished. \n\\item Another important ingredient in the galaxy-satellite interaction\nis the responsiveness of the halo. This regulates the transfer of\nangular momentum between the different components and may weaken the\nresonant response of the disc to the infalling satellite.\n\\item In addition, TO do not make any distinction between satellites\non prograde and retrograde orbits and this has important consequences \nfor the survival and evolution of the disc (see section 3 and 5).\n\\item Another controversial point in TO's derivation is their\nassumption that the deposition of a satellite's orbital energy in the\ndisc is a local process. They argued that the overall energy change in\nthe disc would be the same if the excitation of modes\nin the disc were taken into account, but the formation of spirals and\nwarps reveals that {\\sl global} modes are excited by\nthe infalling satellite before it crosses the main disc.\n\\end{itemize}\n\n\n\\begin{figure}\n\\plotone{Fig08.ps}\n\\caption{Evolution of the vertical kinetic energy of the\ndisc for several of our models.\nThe solid line represents the vertical heating\nproduced by numerical relaxation. The starred symbols refer to the\nvertical kinetic energy as measured from a frame that coincides with\nthe main axes of the inertia tensor while the open circles show its\nevolution in the initial reference frame.} \n\\label{Fig. 8}\n\\end{figure}\n\n\\section{ Disc Tilting and Warping}\n\nAs the satellite sinks to the galactic centre it transfers energy and\nangular momentum to its surroundings (QHF, HC). Part of this energy,\nas we saw in section 3, goes to the disc in random vertical motions\ngiving rise to the disc thickening. There is also, however, a coherent\nresponse of the disc to the satellite accretion which is associated\nwith the tilting observed in figures 3 and 4. Looking in figure 8 we can also\nappreciate the effect of the orbital type, compactness and mass of the \nsatellite and the mass of the bulge on the evolution of the vertical \nkinetic energy. The solid line corresponds to the\nvertical heating of the disc component coming from numerical\nrelaxation while the starred symbols refer to the vertical kinetic\nenergy as measured in a reference frame that coincides with the main\naxes of the inertia tensor and the open circles correspond to the\nvertical kinetic energy in the original reference frame. We can appreciate \nsome general trends: (i) In the prograde models most of the energy \ngoes to thickening \nthe disc which is best illustrated by models G1S2, G1S9 and G1S14. \nIn contrast, the \nretrograde models clearly show a coherent response of the disc (e.g. G1S12 and \nG1S15). Thus, a smaller fraction of the energy goes to thickening the disc in \nthis case which tell us that the disc is more robust to mergers with satellites \non retrograde orbits than on prograde ones. Notice that for satellites on \npolar and retrograde coplanar orbits all the energy goes to the disc, \nhowever, the \nthickening is lower than in their prograde counterparts suggesting that the \nvertical kinetic energy is distributed in the satellite remnants and \nhalo particles. (ii) As pointed out in section 3, a more massive bulge \nmay reduce the vertical heating of the disc which is more dramatic in models \nG1S10, G2S10 and G3S10 but this is not the case in their \nretrograde counterparts for which the coherent response of the disc seems to \nbe reduced (e.g. models G1S12, G2S12 and G3S12). \\\\\n\n\n\n\\begin{figure*}\n\\vskip 18cm\n\\caption{Representation of the disc by a set of rings equally spaced\nin the polar radius. Each ring has been displaced to the centre\ndefined by the centre of mass of the particles contained in it and\nthen rotated to the principal axes of its inertia tensor. The size of\nthe boxes are $56 \\times 56 \\times 3.5$ in kpc so the plotted distortions \nfrom planarity exaggerate the true distortions. The mean radii of the\nrings shown in this figure are: $4.37$, $7.88$, $11.38$, $14.87$, and\n$18.35$ kpc.}\n\\label{Fig. 9}\n\\end{figure*}\n\nIn the absence of a satellite there is a small exchange of angular\nmomentum between the disc and the halo resulting in a small tilt of the\ndisc, less than $3^o$ over $\\sim 4.5$ Gyr. When a satellite is\nintroduced in the galaxy, the transfer of angular momentum changes\ndramatically. By the end of the simulation, the disc of model G1S14 \nhas been tilted by $\\sim 11^o$ while the angle $\\theta_i$ (for both bound\nand unbound satellite particles) has fallen by $\\sim 26^o$ from \nits initial value. For model G1S15, the disc has been tilted by $\\sim\n15^o$, which, as noted above, is larger than for the corresponding\nprograde case. In this last model, the angle $\\theta_i$ remained\nalmost unchanged which tell us about the importance of the\ncoupling between disc stars and the satellite orbit. However, in both\ncases about $45$ per cent of the total initial angular momentum of the\nsatellite remains in the satellite debris, the rest going to the\ndisc and the halo. Less massive satellites experience less dramatic\nevolution since the sinking rate and, hence, \nthe loss of angular momentum is proportional to the square of the\nsatellite mass. Thus, in our models G1S3 and G1S5 about 61\\% and 68\\%,\nrespectively, of the angular momentum remains in the satellite \ndebris. Also the disc tilting is only about $6^o$ and $8^o$ in these\ncases. \\\\\n\nOn the other hand, observations of edge-on disc galaxies show that a\nconsiderable fraction of them have a conspicuous feature in the form of\nan `integral sign', commonly known as a warp. Most of these structures\ndevelop far beyond the optical disc and are very extended (Briggs\n1990). A typical example is our own Galaxy for which the HI warp,\ndetected at $21\\,$cm, is revealed beyond the solar circle (Henderson\net al. 1982). However, HI warps are observable mainly where the\noptical disc ends and the detection of stellar warps is harder. A\nsystemic attempt was made by S\\'anchez-Saavedra, Battaner and Florido\n(1990) by selecting a sample of $82$ edge-on disc galaxies from the\nPalomar Survey. They were able to identify $23$ cases of stellar warps\nin that sample. This study suggests that stellar warps are also a\ncommon feature, but their origin remains a puzzle.\\\\ \n\nFrom a theoretical perspective, several scenarios have been proposed to\ntry to explain the origin of the warping of disc galaxies (an\nexcellent review on the subject is found in Binney 1992). Among the\nmost frequently invoked is a cosmological origin reflecting the time when\nthe galaxy was built up. Current cosmological simulations suggest that\ndark haloes are highly flattened with mean axis ratios of $ \\sim\n0.5$ and $ \\sim 0.7$ (Dubinski and Carlberg 1991). As a\nconsequence, the disc angular momentum may not be in\nalignment with one of the main halo axes which may then induce \na warping mode in the disc. This tilting mode was studied\nby Sparke and Casertano (1988) for the case of a disc embedded in a\nflattened rigid halo; they found that it is consistent with observed \nwarps. However, recent self-consistent N-body simulations\ncarried out by Dubinski and Kuijken (1995) have shown that the\nresponse of the halo can not be ignored, since dynamical\nfriction can damp the warps in much less than a Hubble time. Nelson and\nTremaine (1995) used perturbation theory to arrive at a similar\nconclusion, suggesting that, in general, a primordial origin of\ngalactic warps may be ruled out.\\\\ \n\nAnother mechanism to excite and maintain warps resorts to the accretion\nof satellites (Binney 1992) which has been highlighted in a recent\npaper by Weinberg (1996). This last author has shown the importance\nof the response of the halo (assumed spherical) of our Galaxy to the\ninteraction with the LMC, and its subsequent effect on the formation of\nthe disc's HI warp. Since in all our simulations the halo is assumed \nspherical we can address the relevance of such events in the formation\nof stellar warps. For this, we proceeded by rotating our disc along\nthe main axes of the inertia tensor of the particles located inside\n$3\\,R_D$ and representing it by a system of initially concentric\nrings equally spaced and each containing a sufficient number of\nparticles. This done, each ring is displaced to a new centre\ndetermined by the centre of mass of the particles within it. Finally,\nwe compute the inertia tensor for each ring and \\mbox{rotate} to its principal \naxes. Figure 9 shows the result of this process for our isolated\ngalaxy model `G1' (upper panel) and for our models G1S3, G1S8 and G1S14,\nrespectively. The size of the each box is $56 \\times 56 \\times 3.5$ in\nkpc. We can see that model G1S3 produces no \ndistinguishable warp while a\nmore massive satellite (model G1S14) in the same orbit or a \nsatellite on\na more nearly circular orbit (model G1S8)\nproduces bigger changes. However, it is important to remark that even\nin the most favorable case the departure of the warp from the disc\nplane is less than $1.75$ kpc in the outer parts which \ncorrespond to an angle less than $7^o$.\\\\\n\n\n\\section{ Satellite Sinking and Disruption Times}\n\nIn order to verify the reliability of the decay rate and disruption\ntime of the satellites in our simulations we built up a self-consistent\nmodel called 'NEW' similar to our model G1S3 but with only a fourth\nof the number of particles in each of the components present in the\nmodel. The mass evolution and\ndisruption rate of the satellite for these models are shown in figure\n10(a)-(b) where the open circles represent model G1S3 and\nthe open squares joined by solid lines correspond to the 'NEW'\nmodel. Notice that the agreement is good with differences in the\ndisruption process of the satellite being more evident in the last\nstages of its evolution.\\\\ \n\n\n\\begin{figure}\n\\plotone{Fig10.ps}\n\\caption{(a) This figure shows the mass of the satellite as a function\nof time. In both models G1S3 (open circles) and NEW we obtained similar \ntimes for the total disruption of the satellite which occurs about $2.6-2.8$\nGyr. (b) The satellite position is presented as a function of\ntime. Notice that the satellite is completely destroyed before it\nreachs the centre of the galaxy. }\n\\label{Fig. 10}\n\\end{figure}\n\n\n\\begin{figure}\n\\plotone{Fig11.ps}\n\\caption{The disruption times of the satellites for most of our\nsimulations. Most of the damage to the satellites occurs at pericentre \nsince the tidal force due to the galactic potential is strongest there.}\n\\label{Fig. 11}\n\\end{figure}\n\n\n\\begin{figure}\n\\plotone{Fig12.ps}\n\\caption{The orbital decay rate for the satellites \nin most of our simulations.}\n\\label{Fig. 12}\n\\end{figure}\n\nAs the satellite is being accreted by the host galaxy, there are two main \nphysical \\mbox{mechanisms} that regulate its evolution: the tidal\ninteraction and dynamical friction. Figures 11 and 12 show the effects\nof these mechanisms in the overall evolution of the satellites for most of \nour simulations. These effects are illustrated by\nour model G1S1. Notice that the biggest `jumps' in the mass evolution\nof the satellite correspond to its passage through pericentre. This is\neasily understood since at that position the tidal interaction of the\nsatellite with the host galaxy is the strongest since the\ngradient of the galactic gravitational force reachs a maximimum at\npericentre. Comparison of the different models yields the following\nconclusions: \n(i) for a given circularity and satellite model, the disruption of the\nsatellite occurs faster for prograde orbits than for retrograde\nones being more evident for coplanar orbits. Furthermore, just from \nthe mass loss and disruption total times, it is\ndifficult to distinguish between polar and retrograde orbits. In the\ncase of prograde orbits, the satellites suffer a faster disruption and\nsinking if they follow orbits which are closer to coplanar. \n(ii) For a given orbit, the decay rate and disruption of our satellite \nwith an initial mass of $0.2\\,M_D$ are faster than for the satellite with an \ninitial mass of $0.1\\,M_D$ since the decay rate is proportional to the\nsatellite mass. (iii) For a given satellite mass and orbit a\nmore compact satellite survives for a longer time than a less\ncompact one since its binding energy is greater. (iv) Finally,\nalthough we do not have a large number of simulations, we note that, \nfor a given satellite, the disruption time scales roughly as \n$\\epsilon_J^{1\/3}$.\\\\\n\n\\section{ Chandrasekhar's Dynamical Friction Formula}\n\nIn this section we briefly address the reliability of Chandrasekhar's\ndynamical friction formula (Chandrasekhar 1960) for describing the decay\nrate of the satellites in our N-body simulations. To carry\nout this study, we built up a galaxy model similar to our fully\nself-consistent one but replacing the self-gravitating halo by a rigid\npotential which is free to move in response to the particle\ndistribution of the other components. For a Maxwellian distribution of\nvelocities with a dispersion velocity $\\sigma(r)$ we have that the\ndynamical friction on the satellite is given by (Binney and Tremaine\n1987): \n\n\\begin{equation}\n{\\bf F}_{df}\\,=\\,-{{4\\pi \\ln \\Lambda G^2 M_S^2 \\rho_H(r)}\\over{v_S^3}}[\\hbox{ erf}(X)-{{2 X}\\over{\\sqrt{\\pi}}}\\hbox{ e}^{-X^2}]\\,{\\bf v}_S,\n\\end{equation} \n\n\\noindent where $X \\equiv {v}_S\/(\\sqrt{2}\\sigma(r))$ and $\\ln \\Lambda$ is the\nCoulomb logarithm. The basic underlying assumption in the derivation\nof this equation \nis that a point particle of mass $M_S$ moves with a velocity ${\\bf\nv}_S$ in an homogeneous and infinite background of lighter\nparticles whose self-gravity is completely ignored. As this point\nparticle travels across the background it deflects particles\n(gravitational focusing) producing a density enhancement (a wake)\nbehind it which is responsible for the drag force expressed in equation\n(6) (Mulder 1983). Obviously, the manifestation of this force requires\na halo made of independent particles and hence, it will be not present in a\nrigid model. Since we want to check the reliability of equation (6) to\ndescribe the sinking rate in our self-consistent simulations we have\nintroduced it `by hand' in the case of the rigid halo models to\nemulate a drag force acting on the satellite. This will allow us to\ndetermine the importance of the self-gravity of the background particles of \nthe halo particles to the sinking process. We should remark that the\ndisc was kept alive and, hence, `disc friction' is included. \\\\ \n\n\n\n\\begin{figure}\n\\plotone{Fig13.ps}\n\\caption{Decay and disruption rates for a few of our models. Open\ncircles corresponds to our fully self-consistent simulations while\nsolid lines represent the same model but with a rigid halo free to\nmove instead. Dynamical friction has been computed using\nChandrasekhar's relation.} \n\\label{Fig. 13}\n\\end{figure}\n\nIn addition to the study of the orbital decay of satellites within\ntheir host galaxies (e.g. QG, QHF) dynamical friction has been invoked to \nexplain the evolution of cD galaxies in clusters \nof galaxies (Ostriker and Tremaine 1975, White 1976) as well as \nthe formation of galactic nuclei (Tremaine, Ostriker and\nSpitzer 1975). Despite numerous studies, there is\nstill disagreement about the applicability of Chandrasekhar's relation in \nsuch situations and the relevance of its inherent local character. \nThus, Lin and Tremaine (1983) using a semi-restricted N-body code found\nthat equation (6) provides accurate decay rates for satellites\nfollowing circular orbits for a large part of the parameter space\n(satellite mass, satellite size, and number density and mass of halo\nstars) suggesting that the self-gravity of the halo stars is\nunimportant. In contrast, White (1983) using fully self-consistent N-body\ncalculations based on a spherical harmonics expansion found that a\nlocal description of the dynamical friction was not enough to\ndetermine the sinking times in satellites. However, Bontekoe and van\nAlbada (1987) reached a conclusion more in agreement with Lin and\nTremaine (1987) since they found that higher order terms of the\nharmonic expansion had no discernible effect on their results. In an\nattempt to clarify this situation, Zaritsky and White (1988) carried\nout an exhaustive study using several codes and found that the\nself-gravity of the halo is not important for the sinking rate of the\nsatellite. Also, Hernquist and Weinberg (1989) used self-consistent\nand semi-restricted N-body algorithms to study this problem and to try\nto understand the discrepancy. They concluded that orbital decay is\nstrongly suppressed if self-gravity of the response is taken into\naccount in disagreement with Zaritsky and White (1988). Since most of\nthe previous work was restricted to satellites following circular\norbits, S\\'eguin and Dupraz (1994, 1996) employed a semi-restricted\nmethod to determine the applicability of Chandrasekhar's relation to\nhead-on encounters. They also conclude that the global response of the\ngalaxy cannot be ignored. \\\\ \n\n\\begin{table*}\n\\begin{center}\n\\centering\n\\caption{Disc kinematical changes. Rigid haloes}\n\\begin{tabular}{|l|c|c|c|c|c|c|c|c|c|} \\hline\n& \\multicolumn{3}{|c|}{$R_{c}^{*}$} & \\multicolumn{3}{|c|}{$R_\\bullet$} & \\multicolumn{3}{|c|}{$R_{4}^{\\dag}$} \\\\ \\hline\n{Model} & $\\scriptstyle{(\\Delta \\sigma_R,\\Delta \\sigma_\\phi,\\Delta \\sigma_z)}$ & $\\scriptstyle{\\Delta Q}$ & $\\scriptstyle{\\Delta z_o}$ & $\\scriptstyle{(\\Delta \\sigma_R,\\Delta \\sigma_\\phi,\\Delta \\sigma_z)}$ & $\\scriptstyle{\\Delta Q}$ & $\\scriptstyle{\\Delta z_o}$ & $\\scriptstyle{(\\Delta \\sigma_R,\\Delta \\sigma_\\phi,\\Delta \\sigma_z)}$ & $\\scriptstyle{\\Delta Q}$ & $\\scriptstyle{\\Delta z_o}$ \\\\ \\hline \\hline\nR-G1S1 & $(9,6,4)$ & $0.4$ & $50$ & $(5,4,5)$ & $0.4$ & $200$ & $(10,9,8)$ & $2.6$ & $550$ \t\\\\\nR-G1S3 & $(9,6,5)$ & $0.3$ & $50$ & $(5,4,5)$ & $0.4$ & $150$ & $(13,8,10)$ & $2.2$ & $750$ \t\\\\\nR-G1S8 & $(9,8,6)$ & $0.3$ & $50$ & $(10,5,5)$ & $0.6$ & $250$ & $(20,15,16)$ & $2.8$ & $1000$ \t\\\\\nR-G1S14 & $(27,16,13)$ & $0.5$ & $150$ & $(26,16,30)$ & $1.8$ & $1200$ & $(30,23,28)$ & $3.4$ & $1700$ \t\\\\ \\hline\n\\end{tabular}\n\\end{center}\n\\medskip\nAs in Table 4, symbols $*$ and $\\dag$ denote quantities at the centre\nand $4\\,R_D$, respectively. \n\\end{table*}\n\nDue to this confusion about the role played by the global response of\nthe halo in the sinking process of the satellite we have repeated four\nof our simulations (models G1S1, G1S3, G1S8 and G1S14) but replacing the\nself-consistent halo by a rigid one which is free to move. With these new\nsimulations we try to cover several situations (different\neccentricities and satellite masses) to see whether the expression\n(6) deviates from the results in our self-consistent N-body\ncalculations and from a satellite that does not follow a circular\norbit as is claimed by S\\'eguin and Dupraz (1994, 1996). Figure 13\nshows the sinking and disruption times for the satellites in the new\nsimulations. Open squares represent the fully self-consistent\nsimulations while solid lines correspond to the model with rigid\nhaloes. To quantify the sinking and distruption rates we have used\nequation (6) with $\\rho_H(r)=\\rho(r)$ representing the local halo\ndensity at the satellite position and the satellite mass $M_S=M_S(t)$\nas the particles that remain bound. ${\\bf F}_{df}$ is applied to all\nthe bound particles. Notice that the agreement is quite\nremarkable and it suggests that a local description, as is implicit\nin Chandrasekhar's formula, is adequate to determine the sinking\ntimes of satellites whenever the satellite is immersed in the halo provided \nwe choose the right value for $\\Lambda $ and we define the satellite\nmass $M_S$ as the total mass of bound particles. The values for\n$\\Lambda $ that appear in figure 13 were estimated initially from the \nexpression $\\Lambda=p_{max}\/p_{min}$ \\footnote{Here, $p_{max}$ and\n$p_{min}$ are the maximum and minimum impact parameter, respectively,\nand are defined by $p_{max}\\equiv \\simeq GM^2\/(2|W|)$ and\n$p_{min}\\equiv GM_S\/\\sigma_H^2(r_p)$ where $M$, $|W|$, $M_S$, \n$\\sigma_H(r_p)$ are the total mass of the spiral galaxy, the total\npotential energy of the spiral, the satellite's initial mass and the\none-dimensional dispersion velocity of the halo evaluated at the\npericentric radius $r_p$, respectively.} and afterwards were\nfine-tuned to get the `right' values. We must point out that to\ndetermine the dependence of $\\Lambda$ on the orbital parameters and\nthe satellite structure further work is necessary.\\\\\n\n\n\\begin{figure}\n\\plotone{Fig14.ps}\n\\caption{Disc kinematics for model R-GS3 (solid\nlines). Dashed lines represent the kinematics of the equivalent\nisolated galaxy model while dotted lines correspond to the changes\nsuffered by the disc as a consequence of the satellite accretion.}\n\\label{Fig. 14}\n\\end{figure}\n\n\\section{ Rigid Haloes and Disc Heating and Thickening}\n\nWe have carried out a detailed analysis of the simulations involving rigid\nhaloes in order to address the importance of the\nself-consistent \nrepresentation of the haloes in the accretion of a satellite. In\nfigure 14 we show the resulting disc kinematics (solid lines) for\nthe case equivalent to our model G1S3 but with a rigid halo\n(model R-G1S3). The kinematics of the corresponding isolated control\nmodel is displayed in the same figure\n(dashed lines) and the kinematical changes induced by the accretion\nevent are indicated by dotted lines. From comparison of figures 5 and\n14 we can notice that: (i) the disc thickening due purely to numerical\nrelaxation has been diminished by the introduction of a rigid halo;\nin an isolated model the disc heating is dominated by encounters\nbetween disc and halo particles. (ii)\nAfter completion of the accretion event, the radial and azimuthal\nchanges of the velocity ellipsoid induced by the satellite are\nroughly similar to those found in model G1S3. Thus, limits on\naccreted mass based only on the value of $\\Delta Q$ ($\\propto \\Delta\n\\sigma_R$) and ignoring any change of $\\Sigma_D(R)$ and any gas\ncooling will be essentially the same even if the spherical halo is \nrepresented by a rigid potential rather than by a distribution of\nparticles provided the decay and disruption rates of the satellite are\nconsidered adequately (in our case by equation 6). (iii) However, the\nresponse of the vertical structure\nof the disc seems to be strongly coupled to the responsiveness of the\nhalo. For example, for\nmodel R-G1S3 we found that the change of the vertical scale length at\n$14$ kpc is about a factor of $2$ bigger than in model G1S3 \nwhile at the solar radius the factor is $\\sim 1.5$. This difference is\nsubstantial despite the fact that we have mimicked the satellite's\norbital energy loss to the rigid halo through equation 6. This may be\nbecause the disc develops some other\ninstabilities, as satellite accretion proceeds, which can be damped\nby a self-gravitating halo. (iv) As the\nsatellite becomes more massive, the necessity of a self-consistent\ntreatment of the halo is more evident; see figure 15\nwhich is the equivalent of our model G1S14 (compare it with figure\n6). The kinematics of this set of simulations using \nrigid haloes is summarized in Table 6.\\\\ \n\n\n\\begin{figure}\n\\plotone{Fig15.ps}\n\\caption{The same as figure 14 but for a satellite \nwith $0.2$ M$_D$. }\n\\label{Fig. 15}\n\\end{figure}\n\n\\section{ Conclusions}\n\nWe can summarize our main conclusions as follows:\n\n\\begin{itemize}\n\\item A comparison of our results with those obtained using TO's\nformulae shows that the mass limits they derived are too strict. In\ngeneral, TO tend to\noverestimate the damaging effects of satellite accretion by a\nfactor of about $2-3$ at the Solar radius. The\ndamaging effects in our simulations may also be an overestimation since\nwe ignore any contribution of gas cooling during the accretion process. The\norigin of the discrepancy between TO's predictions and our results may\nlie in the fact that: (i) their analysis ignores the coherent response of\nthe disc and its interaction with the halo. (ii) Their assumption that\nthe satellite's orbital\nenergy is deposited locally in the disc is clearly unrealistic. (iii)\nA fully self-consistent treatment of the dynamics is needed to get reliable\nresults. A rigid halo (with dynamical friction introduced through\nequation (6) leads to a larger increase of the vertical scale length of\nthe disc by a factor of $1.5-2$. A self-consistent treatment is more\nimportant for more massive satellites.\n\n\\item The damaging\neffects (heating and thickening) on the disc are very different for \nsatellites on prograde and\nretrograde orbits. A satellite on a prograde orbit tends to heat the\nstellar disc while its retrograde counterpart induces a coherent\nresponse of the disc in a form of a tilt. A massive satellite on a \nretrograde orbit may be accreted by a spiral galaxy without destroying its\ndisc. Furthermore, a massive central bulge may reduce the vertical heating \nof the disc for prograde orbits (but weaker for retrograde) \nwhile it may slightly diminish the tilting of the disc for retrograde \nones (but not for prograde).\n\n\\item A satellite as massive as $0.1\\,M_D$ and moving in a roughly\nelongated orbit (e.g. our model G1S3) does not produce a\nstrong stellar warp. The\nmost noticeable case of warp formation occurs in our model G1S14 where\nwe see a departure from the disc plane of less than $7^o$ in the outer\nregions (at about $15$ kpc). \n\n\\item Chandrasekhar's dynamical \nfriction formula gives remarkably good estimates for the sinking and\ndisruption rates of satellites in a variety of situations provided\na suitable value is chosen for the Coulomb logarithm and the\nsatellite mass is taken to be the mass still bound to\nthe satellite at each moment.\n\n\\end{itemize}\n\n\\section{ACKNOWLEDGMENTS}\n\nWe thank L. Hernquist for provide us with his algorithms. We also thanks \nan anonymous referee for his helpful comments to improve this paper. HV \nacknowledges useful conversations with L. Aguilar and S. Levine. HV \nthanks CONACyT (Consejo Nacional de Ciencia y Tecnolog\\'{\\i}a) of M\\'exico \nfor a studentship and the Max-Planck f\\\"ur Astrophysik for a Stipendium for \nthe fulfillment of this research. Most of the simulations were run at the \nMax-Planck Society's Computer Centre at Garching, Germany. \n\n\n","meta":{"redpajama_set_name":"RedPajamaArXiv"}} +{"text":"\\section{Introduction}\n\n The beams of different kind of waves, such as electromagnetic or sonic, experience diffraction and broaden as they propagate in a homogeneous medium. This spreading of energy in space diminishes the wave amplitude of the beam in the axis along propagation, unless the spreading is balanced by some focusing mechanism. Still, it is possible to prevent this fundamental wave propagation property and create non-diverging beams. Among the beam patterns without divergence the most popular are the linear Bessel beams \\cite{Drunin87}, and the nonlinear solitonic or self-trapped beams \\cite{Stegeman99}. Recently, another method for creating linear non-diverging beam was proposed, for waves propagating in a periodic medium. Such beams have been named self-collimated beams, and were first proposed for light beams in photonic crystals \\cite{Kosaka1999}, and later extended to other type of waves. The phenomenon of self-collimation has attracted much attention, as a technique to propagate optical, acoustical or even matter wave beams at long distances without a sensible loss of amplitude. Self-collimation is highly sensitive to the frequency: the divergence of beams can be reduced or even suppressed only at particular frequencies, those presenting particular dispersion characteristics, namely flat regions in the isofrequency contours \\cite{Kosaka1999}. The size of the self-collimated beam is also limited by the extension of such flat region in angular space. \n Self-collimation of low amplitude (linear), monochromatic acoustic waves has been demonstrated in 2D \\cite{Espinosa2007} and 3D \\cite{Soliveres2009} sonic crystals. More recently, the simultaneous self-collimation of two beams of different frequencies was also demonstrated experimentally \\cite{Soliveres2011}. These results show that the conditions for self-collimation can be achieved also for non-monochromatic beams; in particular the case of the superposition of beams of one frequency and its second harmonic was considered in \\cite{Soliveres2011}. The latter results are valid in linear regime; actually in \\cite{Soliveres2011} both frequency components were present in the input beam, and the corresponding beams propagated in the crystal without nonlinear interaction between them. \n \n In the linear case, the propagation of light and sound beams obey similar equations, and similar propagation characteristics are expected. The similarities between photonic and sonic crystals are well established \\cite{Miyashita05}, and have motivated many studies, where analogous effects in both systems have been investigated. The analogy, however, breaks for high amplitude waves, where nonlinear effects appear. For example, second and higher harmonic generation processes may be essentially different in optics and acoustics. One reason is the absence of intrinsic dispersion for acoustic waves propagating in homogeneous media. Nonlinear acoustical waves in nondispersive media as homogeneous fluids, eventually generate shock waves, which are not observed in optics. Also, the type and strength of nonlinearity may be different. While most common optical nonlinearities are cubic (kerr-type), in fluids and homogeneous solids, quadratic nonlinearity is dominant in acoustics. Even, nontraditional acoustic nonlinearities (power-law, hysteretic,...) are typical of some complex or microstructured acoustic media. In this sense, nonlinear effects of acoustic waves in periodic media, and in particular the self-collimation problem considered here are not a direct extension of the same effects in the optical case. Furthermore, the propagation of nonlinear acoustic beams in sonic crystals has never been addressed before.\n\nThe basic effect in nonlinear acoustics is harmonic generation \\citep{Hamilton2008}. It is known that efficient harmonic generation is only possible under fulfilment of phase matching conditions. For acoustic waves in fluids, this condition is rather natural, being always fulfilled for all harmonics due to the absence of dispersion, however in optics this requires special materials and special phase matching techniques \\cite{Boyd2003}. \n\nAcoustic harmonic generation has been studied in a variety of highly-dispersive nonlinear media, as bubbly liquids, or acoustic waveguides \\cite{Hamilton2008}, and weakly dispersive media as elastic plates \\cite{DeLima2003, Muller2010}, nonlinear porous-elastic media \\cite{Donskoy1997} and in granular media \\cite{Legland2012}. It has been proven as a useful effect in different applications, as material characterization \\cite{Hirsekorn1994,Zheng1999}, ultrasound imaging and echography, \\cite{Humphrey2000}, biological tissue characterization \\cite{Law1981} and other medical ultrasound applications. \n\n\nThe purpose of this paper is to study nonlinear propagation of high intensity sound beams in periodic media, and in particular to demonstrate the formation of nonlinear self-collimated acoustic beams, and discuss the conditions under which this process occurs with maximal efficiency. A sonic crystal is designed, by using an iterative method, to fulfil the three conditions for optimal energy transfer between harmonics: flatness of isofrequency contour for each harmonic, phase matching and large overlap between distributions of the interacting Bloch modes. The predictions are checked by FDTD simulations of the nonlinear problem, that demonstrate the efficient generation of fundamental and second harmonic acoustic narrow beams. \n\n\\section{Nonlinear sound beam propagation model}\n\nSeveral models can be used to describe nonlinear sound wave propagation though a fluid medium, with different levels of accuracy. An accurate description, when thermal and viscous effects are negligible, follows from the conservation laws of mass and momentum, can be written, respectively, in a Eulerian form \\cite{Hamilton2008}: \n\\begin{eqnarray}\n\t\\frac{{\\partial \\rho }}{{\\partial t}} = - \\nabla \\cdot \\left( {\\rho {\\bf{v}}} \\right),\\label{eq_mass}\\\\\n\t\\rho \\left( {\\frac{{\\partial {\\bf{v}}}}{{\\partial t}} + {\\bf{v}} \\cdot \\nabla {\\bf{v}}} \\right) = - \\nabla p,\\label{eq_momentum}\n\\end{eqnarray}\nwhere $\\textbf{v}$ is the particle velocity vector, $p$ is the acoustic pressure, $\\rho$ is the total density field that can be expressed as $\\rho = \\rho_0 + \\rho'$, where $\\rho _0$ the ambient fluid density and $\\rho'$ is the acoustic density. The system is closed by the equation of state of the fluid, that under our assumptions is a pressure-density relation, $p=p(\\rho)$. A commonly used expression is obtained after Taylor expansion, keeping nonlinear terms up to second order. Then \n\\begin{equation}\\label{eq_state}\np = c_0^2 \\rho + \\frac{c_0^2}{\\rho_0}\\frac{B}{2A}\\rho^{2},\n\\end{equation}\nwhere $B\/A$ is the nonlinear parameter of the medium (which is known for most of materials, see e.g. \\citep{Naugolnykh1998}) and $c_0$ the sound speed in the medium.\nNote that Eqs. (\\ref{eq_mass}) and (\\ref{eq_momentum}) also contain nonlinearities related to (1) mass and momentum advection , or (2) geometrical nonlinearities. However, for the second harmonic generation they are of minor importance compared with the nonlinear terms in the equation of state, Eq. (\\ref{eq_state}). \n\n The above formulation of nonlinear propagation problem remains valid when the propagating medium is inhomogeneous, including the case of sonic crystals where inhomogeneity is periodically distributed in space. In such case, the medium parameters $c_0$ and $\\rho _0$ are space-dependent, represented by periodic functions. To our knowledge, the propagation of acoustic beams in periodic media has been only studied in the linear regime, and the corresponding nonlinear problem is addressed here for the first time.\n \n\\begin{figure}[t]\n\t\\includegraphics[width=8cm]{Figure1a.eps}\\\\\n\t\\includegraphics[width=4.1cm]{Figure1b.eps}\n\t\\includegraphics[width=4.1cm]{Figure1c.eps}\n\n\t\\caption{Top: Band structure (left) of a square lattice of rigid cylinders with $r = 0.11 a$, where $a$ is the lattice constant, immersed in water (right). Red and blue lines mark the bands (2nd and 8th) for which simultaneous self-collimation for both fundamental and second harmonic searched, along $\\Gamma-\\mathrm{X}$ direction. Bottom: Isofrequency contours for the 2nd (left) and 8th bands (right).Points denote the wavevectors for both waves, lying on flat segments respectively}\n\t\\label{FigDiagram}\n\\end{figure}\n\n\n\\section{Self-collimation of intense acoustic beams}\n\nWe consider a narrow, intense acoustic beam incident on a 2D sonic crystal made of cylindrical scatterers of radius $r$ embedded in a fluid, arranged in a square-lattice with lattice constant $a$. The corresponding filling fractio is $f=\\pi (r\/a)^2$. The beam width is roughly $6$ lattice periods. For the sake of simplicity the scatterers are considered perfectly rigid (the sound field is totally reflected from the wall of scatterer). Assuming water as a host fluid, the material parameters are $\\rho _0 = 1000$ kg\/m$^3$, $c_0 = 1490$ m\/s.\n\nThe special conditions required for a sound beam to propagate without diffraction are presented in this section. The problem of self-collimation has been already discussed for linear, monofrequency \\cite{Perez2007,Espinosa2007} and bi-frequency \\cite{Soliveres2011} beams. Since a nonlinear beam is composed by a fundamental frequency component and its high frequency harmonics, self-collimation of the nonlinear beam requires self-collimation of its constituent frequency components. We remind that in self-collimation regime the sonic beam does not spread diffractively because Bloch wave vectors lying on the flat segment of the spatial dispersion curve have equal longitudinal components and thus do not dephase mutually in propagation. In general, this flatness of the dispersion curve appears at a particular frequency, but as shown in \\cite{Soliveres2011} it can be also obtained for a wave and its second harmonic regarded they propagate in different propagation bands. \n\nTo illustrate this case, we show in Fig. \\ref{FigDiagram} the dispersion diagram of the sonic crystal for small-amplitude excitations, obtained using the Plane Wave Expansion (PWE) method on a linearized version of Eqs. (\\ref{eq_mass})-(\\ref{eq_state}). The conventional form of the band diagram is represented on the trajectory along the principal directions of the crystal, $\\Gamma-\\mathrm{X}-\\mathrm{M}-\\Gamma$, which are the boundary of the irreducible Brillouin zone (BZ). Figure~\\ref{FigDiagram} (top) shows the dispersion diagram for $\\Gamma-\\mathrm{X}$ direction. The red line in Fig.~\\ref{FigDiagram} denotes the 2nd propagation band. The fundamental (driving) field lies on this band. Its frequency $\\Omega$ is chosen such that the corresponding isofrequency contour contains flat regions. The blue line in Fig.~\\ref{FigDiagram} denotes the 8th propagation band. The second harmonic frequency, $2\\Omega$, lies in this band for the particular crystal parameters considered. \nAs shown in \\cite{Soliveres2011}, for a given crystal, it is possible to choose the fundamental frequency such that the isofrequency contours for both frequencies present flat regions. \nIn our particular crystal, this happens when $\\Omega$ = 0.125 [these are dimensionless frequencies, related to physical frequencies $\\omega$ as $\\omega=\\Omega (2 \\pi c_0\/a)]$. Similarly, a normalized Bloch wavevector is defined as $\\mathrm{K}=\\mathrm{k}_x(a\/\\pi)$\n\nSuch condition is necessary to achieve self-collimated propagation of the nonlinear beam. \nIn order to obtain an efficient generation of the second harmonic, together with simultaneous self-collimation for both waves two additional geometric conditions must be fulfilled, related to the wavenumber and spatial shape of the interacting beams. \nThese conditions have been discussed for photonic crystals \\cite{Nistor2008, Nistor2010}. \n\n\\subsection{Phase matching conditions}\n\n It is well known from nonlinear optics \\cite {Boyd2003} that a proper phase relationship between the fundamental and second harmonic waves must be satisfied for an efficient nonlinear frequency conversion along the propagation direction. In a dispersive medium, the wavenumbers of first harmonics do not combine to result precisely in wavevector of second harmonics, and a phase mismatch $\\Delta \\mathrm{K}=2\\mathrm{K}(\\Omega)-\\mathrm{K}(2\\Omega)$ occurs. As a consequence, the second harmonic field is limited in amplitude: it does not grow linearly but oscillates in propagation, with a characteristic period given by the coherence length $l_c=\\frac{\\pi}{\\Delta \\mathrm{k}}=\\frac{a}{\\Delta \\mathrm{K}}$ \\citep{Boyd2003}. \n \n The conversion efficiency into second harmonics generally is smaller in optics than in acoustics, because of the inherent material dispersion for light waves (absent for sound waves in fluids), that causes the fundamental and second harmonic waves to travel along the crystal with different phase velocities. Thus, the presence of the scatterers is the only important source of dispersion in the acoustic case. \n \n\n\\begin{figure}[tb]\n\t\\centering\n\t\\includegraphics [width=8cm]{Figure2.eps}\n\t\\caption{Dispersion curves involved in simultaneous self-collimation for the fundamental (red line) at the 2nd band and second harmonic (blue line) at the 8th band. The \"doubled\" dispersion curve is represented (dashed red line) to identify phase matching of harmonics. The intersection denotes the frequency presenting phase matching. A closest view (inset) shows that for the self-collimated second harmonic, two solutions (modes A and B, with distinct $\\mathrm{K}$) are found, phase and non-phase matched, respectively}\n\t\\label{SHmatch}\n\\end{figure}\n\nPhase matching corresponds to $\\Delta \\mathrm{K} = 0$. Figure ~\\ref{SHmatch} shows that it can be actually achieved for the pair of frequencies where self-collimation occurs, as follows from the previous analysis. There, we represent the dispersion branches involved in self-collimation, along $\\Gamma-\\mathrm{X}$ direction, as in Fig.~\\ref{FigDiagram}. Fundamental and second harmonic modes correspond to the crossings of the dotted horizontal lines with the corresponding dispersion branches. For a given fundamental frequency $\\Omega$, in order to check the fulfillment of the phase matching condition, the curve corresponding to the ''double'' of the 2nd band dispersion curve, $2\\Omega(2\\mathrm{K})$, has been represented in Fig.~\\ref{SHmatch} as a red dashed line. Phase matching is satisfied at the intersection between this curve with the corresponding curve at the 8th band. This corresponds to the mode labeled A in Fig.~\\ref{SHmatch}, which is phase-matched with the fundamental mode.\n\nNote that due to the concavity of the 8th band, at frequency 2$\\Omega$ a second mode labelled with B in Figure.~\\ref{SHmatch} can be also excited. This solution presents a large phase mismatch with the fundamental mode, and its contribution to the second harmonic field is negligible. \n\nThe simultaneous fulfillment of both conditions is obtained by an iterative procedure, which implies a re-design of the crystal parameters. The procedure is as follows: we start from a pair of frequencies $(\\Omega,2\\Omega)$ showing self-collimation for a given crystal parameters. Around this doublet, we seek the closest pair of frequencies $\\Omega'=\\Omega+\\delta \\Omega$ and 2$\\Omega'$ showing phase-matching. Then the isofrequency curves (Fig.~\\ref{FigDiagram}) are again calculated in order to evaluate the deviation of flatness in the isofrequency contours. The sonic crystal parameters are then modified, e.g. by a slight variation of the filling fraction, in order to tune the dispersion relations to get again self-collimation conditions. The process is repeated again until both conditions (flatness and phase matching) are simultaneously satisfied. We note that, despite this is out of the scope of this paper, optimization techniques as genetic algorithms can be applied here in order to find an optimal structure.\n\n\\subsection{Nonlinear coupling of Bloch modes}\n\n\\label{sec:Nonlinearcoupling}\nEfficient energy transfer between harmonics requires also a strong mode coupling, which depends on the spatial overlapping between the two interacting waves. For plane waves in a homogeneous medium a perfect spatial nonlinear coupling between first and second harmonic is assured, since mode overlapping is maximal. The propagation eigenmodes in a periodic medium are Bloch waves, whose amplitudes are spatially modulated and does not necessarily overlap. If two modes do not overlap in space, the energy transfer is less efficient even if they are phase matched. The amount of energy transfer can be estimated evaluating the spatial overlap between the envelopes of the corresponding Bloch modes. Let $B_{1}$ and $B_{2}$ be the spatial envelopes of the Bloch modes of the fundamental and and second harmonic waves, respectively. The nonlinear coupling coefficient is calculated as the cross-correlation between the functions $B_{1}^{2}$ and $B_{2}$ normalized in such a way that unity would correspond to the perfect matching of the modes \\cite{Nistor2008}. We define the coupling coefficient as\n\\begin{equation}\n\\kappa = \\frac{| \\int_{M} B_{1}^{2}\\,B_{2}^{*} \\mathrm{d}r |} { \\sqrt{ \\int_{C} \\, | B_{1}^{4}|\\,\\mathrm{d}r \\, \\int_{C} \\, | B_{2}|^{2}\\,\\mathrm{d}r }}\n\\end{equation}\nwhere the upper integral is calculated in the nonlinear medium from one unit cell, while the lower integrals are taken over the entire unit cell. \nTo calculate $B_{1}$ and $B_{2}$ we solve the eigenvalue problem for the pressure field by means of the PWE method, which converts the differential equation to an infinite matrix eigenvalue problem that can be truncated and solved numerically. For that, we follow the same procedure as in \\cite{Perez2007} however the problem is solved inversely, i.e. for a given frequency, the corresponding wave vectors, satisfying the phase matching condition, are obtained. Then $B_{1}$ and $B_{2}$ are obtained as the eigenvectors corresponding to fundamental and second harmonic frequencies, respectively. In Fig.~\\ref{BlochMode} we plot the spatial distributions of $B_{1}$ and $B_{2}$, respectively, for the selected final design where a coupling coefficient of $\\kappa = 0.85$ is obtained. This value is of the same order as the coupling in homogeneous media, $\\kappa = 1$, and therefore sufficiently large for an efficient harmonic generation.\n\n\\begin{figure}[t]\n\t\\centering\n\t\\includegraphics[width=4.1cm]{Figure3a.eps}\n\t\\includegraphics[width=4.1cm]{Figure3b.eps}\n\t\\caption{Spatial distribution of the pressure field for the Bloch modes of the findamental (left) and the second harmonic (right) waves. The coupling coefficient is estimated to be $\\kappa = 0.85$.}\n\t\\label{BlochMode}\n\\end{figure}\n\n\n\\subsection{Numerical simulation}\n\n\n\\begin{figure}[t]\n\t\\centering\n\t\\includegraphics[width=4cm]{Figure4a.eps}\n\t\\includegraphics[width=4cm]{Figure4b.eps}\\\\\n\t\\includegraphics[width=4cm]{Figure4c.eps}\n\t\\includegraphics[width=4cm]{Figure4d.eps}\\\\\n\t\\includegraphics[width=4cm]{Figure4e.eps}\n\t\\includegraphics[width=4cm]{Figure4f.eps}\n\t\\caption{Pressure distributions obtained by FDTD simulations. Normalized intensity cross section of fundamental (a) and second harmonic (b) at $x=80a$ propagating in the crystal (continuous line) and in a homogeneous (water) medium (dashed lines). Beam spatial distribution for simultaneously self-collimated harmonics in the sonic crystal (c-d) and in homogeneous fluid (e-f). Pressures are normalized to the maximum pressure.}\n\t\\label{figFDTD}\n\\end{figure}\n\nA full-wave nonlinear simulation was performed, using the FDTD method, to validate the efficiency of the second harmonic generation in the proposed structure. The crystal parameters, obtained after the iterative procedure describe above, are as in Figs. (\\ref{FigDiagram}) and (\\ref{SHmatch}). The source is a plane piston with a width of $6a$, located near the crystal, and radiating a harmonic wave with normalized frequency $\\Omega$ = 0.125. In order to minimize numerical dispersion a computational grid with $N_{\\lambda}=45$ elements per wavelength was used, and a Courant-Friedrich-Levy number of $S=0.95$. In Fig.~\\ref{figFDTD} we present the numerically obtained spatial distributions of the fundamental and its nonlinearly generated second harmonic. As predicted, both beams are nearly collimated. For comparison, the beam spatial distribution calculated for an homogeneous material (removing the crystal) are represented in Fig.~\\ref{figFDTD}~(e-f), where the diffractive broadening of the beams is visible. Transversal intensity distributions are shown in Fig.~\\ref{figFDTD}~(a-b) for a distance $80a$, where beam widths are compared with the reference beams in the homogeneous medium, broadened by diffraction. \n\nThe pressure amplitudes along the beam axis are shown in Fig.~\\ref{FWSHout} for each harmonic. Here, the analytic solution for a nonlinear plane wave propagating in a homogeneous (nondispersive) medium is plotted for reference (dashed lines) \\cite{Naugolnykh1998}, given by $p_n\/p_0=2 J_n(n\\sigma)\/n\\sigma$, where $J_n$ is the Bessel funcion of order $n$, $\\sigma=(\\varepsilon \\omega p_0\/\\rho_0 c_0^3) x$ is coordinate normalized to the shock formation distance, $p_0$ is the pressure at the source and $\\beta=1+ B\/2A$ the nonlinearity parameter. Such analytical solution is valid in the pre-shock region $\\sigma<1$. The growth rate of the self-collimated second harmonic beam propagating in the crystal matches well the growth rate of a plane wave in a homogeneous medium in such preshock region, which is a consequence of the weak divergence of the beam and the high degree of phase matching. Also, the second harmonic field can reach even higher amplitudes than those corresponding to nondispersive media (where harmonics decay beyond the shock formation distance). The latter effect can be understood in terms of phase mismatch of higher harmonics: in homogeneous media all harmonics are phase matched while in the crystal only the second harmonic is phase matched. In Fig. (\\ref{FWSHout}) the third harmonic is also plotted, where its small contribution to the beam is evident. The phase mismatch in third and higher harmonics decrease the energy flow into these components. Finally, the amplitude in Fig. (\\ref{FWSHout}) decays because non-perfect conditions for self-collimations, that makes the beam to start diverging after a long distance, or non-perfect phase matching, which results in a beating period with long coherence length.\n\n\\begin{figure}[t]\n\t\\includegraphics[width=8cm]{Figure5.eps}\n\t\\centering\n\t\\caption{Normalized field amplitude along the acoustical axis $y=0$, for the fundamental, second and third harmonic beams. The dashed lines represent the analytical solutions for harmonic evolution on a plane wave propagating in a nondispersive medium.}\n\t\\label{FWSHout}\n\\end{figure}\n\n\n\\section{Conclusions and Remarks}\n\nWe have demonstrated the possibility of efficient second harmonic generation of sound in a sonic crystal, by means of the formation of narrow, weakly diverging nonlinear acoustic beams. Three conditions must be simultaneously present for a efficient second harmonic generation, which are: 1) simultaneous self-collimation, 2) phase mathing and 3) high spatial coupling of interacting harmonics. The use of simultaneous self-collimation regime limits the diffraction of both harmonic beams, maintaining the amplitude at the axis and therefore the nonlinear interaction. Under ideal conditions (no divergence and losses), the decrease of the first harmonic beam is mainly attributed to the energy transfer to second and higher harmonics. The sonic crystal parameters can be chosen to fulfill phase matching with the second harmonic, maximizing second harmonic generation due to synchronous cumulative interaction. Finally, the spatial coupling (overlapping) between interacting modes is also analyzed by calculating a nonlinear coupling coefficient. It is shown that its value ($\\kappa=0.85$ for the case studied) is not far from the ideal case, revealing a strong spatial overlap between both Bloch modes that leads to high energy transfer. \n\n\n The study show that linear dispersion characteristics (band structures, isofrequency contours) can be used to predict the behaviour of nonlinear beams propagating in periodic media. This opens the possibility of extending the study of nonlinear sound beam propagation in sonic crystals to other cases of interest. For example, crystals with higher filling factors present full frequency bandgaps, that may be used to filter out the propagation of selected higher harmonics. In this sense, sonic crystals can be a way to control the spectrum of intense acoustic waves, using the strong dispersion properties introduced by the periodicity. \n\n\n\\bibliographystyle{apsrev}\n\n","meta":{"redpajama_set_name":"RedPajamaArXiv"}} +{"text":"\n\\section{Introduction}\nAn important feature of finite temperature QCD is the generation of an\nelectric and magnetic screening mass which play an important role in\ncontrolling\nthe infrared behaviour of the theory. The electric screening mass leads to\na Debye\nscreened static quark-antiquark potential and is given for SU(N) \nwith $N_{f}$ quark flavours, and for vanishing chemical potential and \nquark mass, in\nleading order\nperturbation theory by $m^{2}_{el} = \\frac{g^{2}}{3}(N+N_{f}\/2)T^{2}$ \n\\cite{kala}.\nRenormalization group improved perturbation\ntheory\ntells us that the effective coupling is a function of the temperature, and\ndecreases\nwith increasing temperature. This suggests that at sufficiently high\ntemperatures,\nabove the deconfining phase transition, the screening mass may be computed in\nperturbation theory. Because of the singular\ninfrared behaviour of the perturbative series, however, the computation\nof the next to leading order contribution requires a resummation of infrared\ndivergent diagrams which turns out to be sensitive to the magnetic\nscreening mass \\cite{rebh}.\nThis mass vanishes in lowest order perturbation theory and is expected to be\nof ${\\cal O}(g^{2}T)$. The coefficient multiplying $g^{2}T$ turns out however\nto be incalculable \\cite{lind}.\nMaking use\nof an improved perturbation theory proposed by Braaten and Pisarski \n\\cite{braa}, which\nresums hard thermal loops, and of a gauge invariant\ndefinition of the\nelectric screening mass \\cite{kobe}, Rebhan \nhas calculated the ${\\cal O}(g^{3}T^{2})$\ncorrections to the non-abelian screening mass-squared and has shown that\nnext to leading order contributions give rise to an enhancement \\cite{rebh}.\n\nThe lattice formulation of QCD allows one to\ndetermine the electric screening mass non-perturbatively.\nThe\nscreening mass is extracted from correlators of Polyakov loops\n[6--9], or\nfrom the long distance behaviour of the gluon propagator \n\\cite{hell}. For small\nquark-antiquark\nseparations lattice perturbation theory for the Polyakov loop correlation\nfunction\nis expected to describe the\nMonte Carlo data, since\nfor a finite lattice volume one is not confronted with the infrared\nproblems encountered in thermal perturbation theory. This has been checked\nin \\cite{pete} for the SU(3) gauge theory\nby taking careful account of finite size effects and, in particular,\nof the zero momentum modes which do not allow\none to take the thermodynamical limit for fixed coupling, as one would do in\nstandard perturbation theory. \nFor larger quark-antiquark separations, beyond the ``perturbative horizon'',\nthe colour averaged potential is expected to have a Debye screened form.\nMonte Carlo simulations confirm this screening picture [6--9].\nIn the case of pure SU(2) and SU(3) gauge theories the electric screening\nmass, when determined from Polyakov loop correlation functions, is found to\nbe about $10\\%$ larger \\cite{gao,irba} \nthan the leading order perturbative result \nif the temperature dependent coupling constant is \ndetermined from Polyakov loop correlators in the perturbative region.\nAs was pointed out by Rebhan, \\cite{rebh}, such an enhancement could also\nbe expected if next to leading order corrections to the continuum screening\nmass are taken into account through resummed perturbation theory. A\nquantitative comparison with the results obtained in the above simulations\nis however very difficult and has, to our knowledge, not been carried out\nso far. In contrast to the work of ref.\\ \\cite{gao,irba}, the electric\nscreening mass as extracted in ref.\\ \\cite{hell} from the gluon propagator\nin the Landau gauge was found to deviate strongly form the leading order\nperturbative result. \n\nIn comparing the Monte Carlo data for the electric screening mass with\nleading order, or resummed, perturbation theory it is important to have\nan estimate of the size of lattice artefacts to be expected from a finite\nlattice spacing.\nTo obtain such an estimate\nwe compute the electric screening\nmass in one-loop order on the lattice, at finite temperature and\nchemical potential, in the infinite volume\nlimit, and compare it with the continuum. \nFor the case of QED with {\\it naive} fermions the screening mass has been \ncalculated by Pietig \\cite{piet}.\nThe screening mass is calculated\nfrom the zero-momentum\nlimit of the 44-component of the vacuum polarization tensor\nevaluated for vanishing Matsubara\nfrequency.\nIn one-loop order this definition of the screening mass is gauge invariant,\nand consistent\nwith the more general gauge invariant definition given in ref.\\ \\cite{kobe},\nwhere\nthe screening mass is determined from the position of the\npole\nof the gluon propagator for vanishing Matsubara frequency.\n\nThe paper is organized as follows: In the following section we calculate the\nelectric screening mass for QCD in one-loop order for\nthe case of Wilson fermions. The Feynman\nrules and frequency summation formulae required for the computation are\nrelegated\nto two Appendices. As we shall see, the resulting integral expression has a\nvery transparent form. In section 3\nwe then evaluate the momentum integrals for the\nscreening mass numerically and compare the results with the\ncontinuum. We show that the lattice artefacts due to a finite\nlattice spacing give rise\nto an enhancement of the screening mass as compared to the continuum. We\ndiscuss the magnitude of this enhancement as a function of \nthe temperature and chemical potential\nfor lattices with different number of lattice sites in the\ntemporal direction which can be implemented in numerical simulations.\nMost of the enhancement\nis found to be due to the fermion\nloop contribution.\nSection\n4 contains a summary of our results.\n\\section{Electric Screening Mass in One Loop Order}\nIn this section we compute the electric screening mass in lattice QCD to\none loop order\nfrom the zero momentum limit of the 44-component of the vacuum polarization\ntensor evaluated for vanishing Matsubara frequency. The Feynman diagrams\ncontributing\nin this order are shown in fig.\\ 1. While diagrams (a,c,d,e) have a\ncontinuum analog, the\nremaining diagrams, required by gauge invariance on the lattice, do not\npossess a\ncontinuum counterpart.\n\\begin{figure}[ht]\n\\leavevmode\n\\centering\n\\epsfxsize10cm \\epsffile{loops.ps}\n\\caption{Feynman diagrams contributing to the vacuum polarization in\n one loop order on the lattice.}\n\\end{figure}\nThe finite temperature, finite chemical potential\nlattice Feynman\nrules are obtained from the $T=\\mu =0$ rules by replacing the fourth\ncomponent of\nthe fermion and boson momenta by $\\hat{\\omega}^{-}_{\\ell} +i\\hat{\\mu}$ and\n$\\hat{\\omega}^{+}_{\\ell}$,\nrespectively, where $\\hat{\\omega}^{+}_{\\ell} = \\frac{2\\pi}{\\hat{\\beta}}\\ell\n\\ (\\hat{\\omega}^{-}_{\\ell} = \\frac{(2\\ell+1)\\pi}{\\hat{\\beta}})$, with\n$\\ell \\in Z$, \nare the Matsubara\nfrequencies\nfor bosons (fermions), and $\\hat{\\beta}$ is the inverse temperature.\nQuantities with a\n\"hat\" are always understood to be measured in lattice units. Furthermore,\nintegrals over the\nfourth component of momenta at zero temperature are replaced at finite\ntemperature by\nsums over Matsubara frequencies in the interval $[-\\frac{\\hat{\\beta}}{2},\n\\frac{\\hat{\\beta}}{2}-1]$, \nwhere we have taken $\\hat{\\beta}$ to be even. The\nFeynman rules\nare collected in Appendix A. The relevant formulae for carrying out the sums\nover Matsubara frequencies are derived in Appendix B.\n\nThe contributions of diagrams (a-g) to the vacuum polarization tensor are\ndiagonal\nin colour space,\n\\begin{equation}\n\\hat{\\Pi}^{(\\beta,\\mu)AB}_{\\mu\\nu}(\\hat{\\omega}^{+}_{\\ell},\\vec{\\hat{k}}) =\n\\delta_{AB}\\hat{\\Pi}^{(\\beta,\\mu)}_{\\mu\\nu}(\\hat{\\omega}^{+}_{\\ell},\\vec{\\hat{\nk}})\\ . \\label{diag:col}\n\\end{equation}\nThe electric screening mass (in lattice units) is then defined by\n\\begin{equation}\n\\hat{m}_{el}^{2} = \\lim_{\\vec{\\hat{k}}\\rightarrow 0}\n\\hat{\\Pi}^{(\\beta,\\mu)}_{44}(0,\\vec{\\hat{k}})\\ . \n\\end{equation}\nIn the following we first consider the contributions to\n$\\hat{\\Pi}^{(\\beta,\\mu)}_{44}(0,\\vec{\\hat{k}})$ coming from the fermion\nloops, i.e.,\ndiagrams (a) and (b).\\\\ \\\\\n{\\it i) Contribution of diagram (a)}\\\\ \n\nA straight forward application of the finite temperature, finite chemical\npotential\nlattice Feynman rules yields\n\\alpheqn\n\\begin{equation}\n\\hat{\\Pi}^{(\\beta,\\mu)}_{44}(0,\\vec{\\hat{k}})_{(a)}\n=-\\frac{N_{f}}{2}g^{2}\\frac{1}{\\hat{\\beta}}\n \\sum^{\\frac{\\hat{\\beta}}{2}-1}_{\\ell=-\\frac{\\hat{\\beta}}{\n 2}}\\int^{\\pi}_{-\\pi}\\frac{d^{3}\\hat{p}}{(2\\pi)^{3}}f^{(a)}\n(e^{i(\\hat{\\omega}_{\\ell}^{-}+i\\hat{\\mu})};\\vec{\\hat{p}},\n \\vec{\\hat{k}})\\ , \\label{pi:a}\n\\end{equation}\nwhere\n\\begin{equation}\nf^{(a)}(z;\\vec{\\hat{p}},\\vec{\\hat{k}})=\n\\frac{2(z^{4}+1)-2\\eta(z^{3}+z)+4\\xi{\\cal G}z^{2}}{\\Pi^{4}_{i=1}(z-z_i)}\n\\end{equation}\nwith\n\\begin{eqnarray}\n\\eta &=& \\frac{1}{[1+\\hat{M}(\\vec{\\hat{p}})]} + \\frac{1}{[1+\\hat{M}\n (\\vec{\\hat{p}}+\\vec{\\hat{k}})]} \\ , \\\\\n\\xi &=& \\frac{1}{[1+\\hat{M}(\\vec{\\hat{p}})][1+\\hat{M}(\\vec{\\hat{p}}+\n \\vec{\\hat{k}})]} \\ , \\\\\n{\\cal G} &=& 1+\\sum_{j}\\sin\\hat{p}_{j}\\sin(\\hat{p}+\\hat{k})_{j} \\ , \\\\\n\\hat{M}(\\vec{\\hat{p}}) &=& \\hat{m} +2 \\sum_{j} \\sin^{2}\\frac{\\hat{p}_{j}}{2}\\ ,\n\\end{eqnarray}\n\\reseteqn\nand $N_{f}$ is the number of quark-flavours.\nThe position of the poles of $f^{(a)}(z;\\vec{\\hat{p}},\\vec{\\hat{k}})$ \nare given by\n\\alpheqn\n\\begin{eqnarray}\nz_{1} &=& e^{\\phi};\\ \\ \\ z_{2}=e^{-\\phi} \\ , \\nonumber \\\\\nz_{3} &=& e^{\\psi};\\ \\ \\ z_{4}=e^{-\\psi} \\ ,\n\\end{eqnarray}\nwith\n\\begin{eqnarray}\n\\phi &=& \\tilde{\\cal E}(\\vec{\\hat{p}}) \\ , \\nonumber \\\\\n\\psi &=& \\tilde{\\cal E}(\\vec{\\hat{p}}+\\vec{\\hat{k}})\\ ,\n\\end{eqnarray}\nwhere\n\\begin{equation}\n\\tilde{\\cal E}(\\vec{\\hat{q}}) = \\ln\\left[ K(\\vec{\\hat{q}}) +\n \\sqrt{K^{2}(\\vec{\\hat{q}})-1}\\, \\right]\n = \\mbox{arcosh} K(\\vec{\\hat{q}})\n\\end{equation}\nand\n\\begin{equation}\nK(\\vec{\\hat{q}}) = 1 + \\frac{\\bar{E}^{2}(\\vec{\\hat{q}})}{2[1+\n \\hat{M}(\\vec{\\hat{q}})]}\\ , \\ \\\n\\bar{E}(\\vec{\\hat{q}}) = \\sqrt{\\sum_{j} \\sin^{2} \\hat{q}_{j} +\n \\hat{M}^{2}(\\vec{\\hat{q}})}\\ .\n\\end{equation}\n\\reseteqn\nNote that\n\\begin{equation}\n\\phi \\stackrel{\\vec{\\hat{p}} \\rightarrow\n-\\vec{\\hat{p}}-\\vec{\\hat{k}}}{\\longleftrightarrow} \\psi \\ , \\label{subst}\n\\end{equation}\nwhile $\\eta$, $\\xi$ and ${\\cal G}$ are invariant under the\ntransformation $\\vec{p} \\rightarrow -\\vec{p}-\\vec{k}$. \nThis will be important further\nbelow.\nThe frequency sum can be performed making use of eq.\\ (\\ref{sum:fermg}) \nderived in\nAppendix B. One\nfinds that\n\\alpheqn\n\\begin{eqnarray}\n\\frac{1}{\\hat{\\beta}}\\sum^{\\frac{\\hat{\\beta}}{2}-1}_\n{\\ell=-\\frac{\\hat{\\beta}}{2}}f^{(a)}\n (e^{i(\\hat{\\omega}_{\\ell}^{-}+i\\hat{\\mu})};\n\\vec{\\hat{p}},\\vec{\\hat{k}}) &=& 2 + h(\\phi,\\psi,\\eta,\\xi,{\\cal G})\n\\left[ \\frac{1}{e^{\\hat{\\beta}(\\phi+\\hat{\\mu})}+1} -\n \\frac{1}{e^{-\\hat{\\beta}(\\phi-\\hat{\\mu})}+1} \\right] \\nonumber \\\\\n& & \\mbox{} + h(\\psi,\\phi,\\eta,\\xi,{\\cal G})\n\\left[ \\frac{1}{e^{\\hat{\\beta}(\\psi+\\hat{\\mu})}+1} -\n \\frac{1}{e^{-\\hat{\\beta}(\\psi-\\hat{\\mu})}+1} \\right]\\ , \n \\nonumber \\\\ \\label{eq:aa}\n\\end{eqnarray}\nwhere\n\\begin{equation}\nh(\\phi,\\psi,\\eta,\\xi,{\\cal G})= \\frac{\\cosh 2\\phi-\\eta\\cosh\\phi\n+\\xi{\\cal G}}{\\sinh\\phi(\\cosh\\phi-\\cosh\\psi)}\\ . \\label{eq:ab}\n\\end{equation}\n\\reseteqn\nTo obtain $\\hat{\\Pi}^{(\\beta,\\mu)}_{44}(0;\\vec{\\hat{k}})_{(a)}$, \nwe must integrate\nthis expression over $\\vec{\\hat{p}}$, with $\\hat{p}_{j}\n\\in [-\\pi,\\pi]$. Noting that $\\eta$, $\\xi$ and\n${\\cal G}$ are invariant under the transformation $\\vec{\\hat{p}}\n\\rightarrow -\\vec{\\hat{p}}-\\vec{\\hat{k}}$,\nand making use of (\\ref{subst}), \nas well as of the fact that the integrand in (\\ref{pi:a})\nis a periodic function in $\\hat{p}_{j}$ and $\\hat{k}_{j}$, we\ncan combine the last two contributions on the r.h.s. of (\\ref{eq:aa}) \nand obtain\n\\alpheqn\n\\begin{eqnarray}\n\\hat{\\Pi}^{(\\beta,\\mu)}_{44}(0,\\vec{\\hat k})_{(a)} &=&\n N_{f}g^{2}\\int^{\\pi}_{-\\pi}\\frac{d^3\\hat{p}}{(2\\pi)^{3}}\n [h(\\phi,\\psi,\\eta,\\xi,\n {\\cal G})-1] \\nonumber \\\\\n& &\\mbox{} -N_{f}g^{2}\\int^{\\pi}_{-\\pi}\\frac{d^3\\hat{p}}{(2\\pi)^{3}}\n h(\\phi,\\psi,\n \\eta,\\xi,{\\cal G})[\\hat{\\eta}_{FD}(\\phi)+\\bar{\\hat{\\eta}}_{FD}\n (\\phi)]\\ . \\label{erg:a}\n\\end{eqnarray}\nwhere\n\\begin{equation}\n\\hat{\\eta}_{FD}(\\phi)=\\frac{1}{e^{\\hat{\\beta}(\\phi-\\hat{\\mu})}+1}\\ ,\\ \\\n\\bar{\\hat{\\eta}}_{FD}(\\phi)=\\frac{1}{e^{\\hat{\\beta}\n (\\phi+\\hat{\\mu})}+1}\\ ,\n\\end{equation}\n\\reseteqn\nare the lattice Fermi-Dirac distribution functions\nfor particles and antiparticles.\\\\ \\\\\n{\\it ii) Contribution of diagram (b)} \\\\\n\nWe next compute the contribution to $\\hat{\\Pi}^{(\\beta,\\mu)}_{44}(0,\n\\vec{\\hat{k}})$ of the Feynman diagram (b) depicted in Fig.\\ 1. \nThis diagram has\nno analog in the continuum and is given by\n\\alpheqn\n\\begin{equation}\n\\hat{\\Pi}^{(\\beta,\\mu)}_{44}(0,\\vec{\\hat{k}})_{(b)} = - N_{f} g^{2}\n \\frac{1}{\\hat{\\beta}}\n\\sum^{\\frac{\\hat{\\beta}}{2}-1}_{\\ell=\\frac{\\hat{\\beta}}{2}}\\int^{\\pi}_{-\\pi}\n \\frac{d^{3}\\hat{p}}{(2\\pi)^{3}} f^{(b)}(e^{i(\\hat{\\omega}_{\\ell}^{-}+i\n \\hat{\\mu})},\\vec{\\hat{p}} )\n\\end{equation}\nwhere\n\\begin{eqnarray}\n f^{(b)}(z;\\vec{\\hat{p}}) &=& -\\frac{z^2-2\\rho z+1}{(z-z_1)(z-z_2)}\\ , \\\\\n \\rho &=& \\frac{1}{1+\\hat{M}(\\vec{\\hat{p}})}\\ ,\n\\end{eqnarray}\n\\reseteqn\nand where $z_{1}$ and $z_{2}$ have been defined\nin (2.4a-d). Making again use of the frequency summation formula\n(\\ref{sum:fermg}), one verifies that\n\\begin{eqnarray}\n\\lefteqn{\n \\hat{\\Pi}^{(\\beta,\\mu)}_{44}(0,\\vec{\\hat{k}})_{(b)}=-N_{f}g^{2}\n \\int^{\\pi}_{-\\pi}\n \\frac{d^{3}\\hat{p}}{(2\\pi)^{3}} \\left(\\coth \\phi- \\frac{\\rho}{\\sinh\n \\phi}-1 \\right) } \\nonumber \\\\\n& & \\mbox{} + N_{f} g^{2} \\int^{\\pi}_{-\\pi}\n \\frac{d^{3}\\hat{p}}{(2\\pi)^{3}} \\left(\\coth \\phi- \\frac{\\rho}{\\sinh\n \\phi} \\right)[\\hat{\\eta}_{FD}(\\phi)\n +\\bar{\\hat{\\eta}}_{FD}(\\phi)]\\ .\n\\end{eqnarray}\nCombining this expression with (\\ref{erg:a}) one finds that\n\\alpheqn\n\\begin{equation}\n\\hat{\\Pi}^{(\\beta,\\mu)}_{44}(0,\\vec{\\hat{k}})\n =\\hat{\\Pi}^{(vac)}_{44}(0,\\vec{\\hat{k}}) +\n N_{f} g^{2} \\int^{\\pi}_{-\\pi}\n \\frac{d^{3}\\hat{p}}{(2\\pi)^{3}}H(\\phi,\\psi,\\rho,\\eta,\\xi,{\\cal G})\n [ \\hat{\\eta}_{FD}(\\phi)+\\bar{\\hat{\\eta}}_{FD}(\\phi) ]\\ , \\label{eq:bc}\n\\end{equation}\nwhere\n\\begin{equation}\n H(\\phi,\\psi,\\rho,\\eta,\\xi,{\\cal G}) = \\coth \\phi - \\frac{\\rho}{\\sinh\\phi}-\n h(\\phi,\\psi,\\eta,\\xi,{\\cal G})\n\\end{equation}\nand\n\\begin{equation}\n \\hat{\\Pi}^{(vac)}_{44}(0,\\vec{\\hat{k}}) = -N_{f}g^{2} \\int^{\\pi}_{-\\pi}\n \\frac{d^{3}\\hat{p}}{(2\\pi)^{3}}H(\\phi,\\psi,\\rho,\\eta,\\xi,{\\cal G}\n ) \\label{eq:ba}\n\\end{equation}\n\\reseteqn\nis the $T = \\mu = 0$ contribution.\nAs we now show, $\\hat{\\Pi}^{(vac)}_{44}(0,\\vec{\\hat{k}})$ vanishes in the limit\n$\\vec{\\hat{k}} \\rightarrow 0$, and hence does not contribute to\nthe screening mass.\n\nConsider the function $h(\\phi,\\psi,\\eta,\\xi,{\\cal G})$ defined in\n(\\ref{eq:ab}). It is singular for $\\vec{\\hat{k}} \\rightarrow 0$, \nsince in this\nlimit $\\psi \\rightarrow \\phi$. \nThe singularity is however integrable.\\footnote{We\nfollow here\nand in the following a technique used in ref. \\cite{piet}, where the author\nhas calculated the screening mass for naive\nfermions in lattice QED to one loop order}\nThis can be seen as follows. Since according to (\\ref{subst}), \nand the statement\nfollowing it\n\\begin{equation}\n h(\\phi,\\psi,\\eta,\\xi,{\\cal G}) \n \\stackrel{\n \\vec{\\hat{p}}\\rightarrow -\\vec{\\hat{p}}-\\vec{\\hat{k}}}{\\longrightarrow}\n h(\\psi,\\phi,\\eta,\\xi,{\\cal G})\n\\end{equation}\nwe can also write (\\ref{eq:ba}) in the form\n\\alpheqn\n\\begin{eqnarray}\n \\hat{\\Pi}^{(vac)}_{44}(0,\\vec{\\hat{k}})\n&=& -N_{f}g^{2}\\int^{\\pi}_{-\\pi}\n \\frac{d^{3}\\hat{p}}{(2\\pi)^{3}}\\left(\\coth\\phi-\\frac{\\rho}{\n \\sinh\\phi}\\right) \\nonumber \\\\\n& &\\mbox{}+\\frac{1}{2}N_{f}g^{2}\\int^{\\pi}_{-\\pi}\\frac{d^{3}\\hat{p}}{\n (2\\pi)^{3}}\n \\tilde{h}(\\phi,\\psi,\\eta,\\xi,{\\cal G}) \\ , \\label{eq:bb}\n\\end{eqnarray}\nwhere\n\\begin{equation}\n \\tilde{h}(\\phi,\\psi,\\eta,\\xi,{\\cal G})=h(\\phi,\\psi,\\eta,\\xi,{\\cal G})\n +h(\\psi,\\phi,\\eta,\\xi,{\\cal G}) \\ . \\label{eq:bd}\n\\end{equation}\n\\reseteqn\nAlthough each term on the rhs of (\\ref{eq:bd}) is singular for \n$\\vec{\\hat{k}} \\rightarrow 0$\n$(\\psi \\rightarrow \\phi)$, the sum possesses a finite\nlimit.\nThus setting $\\psi=\\phi+\\epsilon$ and taking the limit \n$\\vec{\\hat{k}} \\rightarrow 0$\n($\\epsilon \\rightarrow 0$),\none verifies that\n\\begin{equation}\n \\lim_{\\vec{\\hat{k}} \\rightarrow 0}\\tilde{h}(\\phi,\\psi,\\eta,\\xi,{\\cal G})\n = 2\\left( \\coth\\phi-\\frac{\\rho}{\\sinh\\phi} \\right) \\ . \\label{eq:be}\n\\end{equation}\nFrom (\\ref{eq:bb}) we therefore conclude that\n\\[ \\lim_{\\vec{\\hat k}\\to 0}\\hat\\Pi^{(vac)}_{44}(0,\\vec{\\hat k})\n=0 \\ . \\]\nThis result is not unexpected, since for vanishing temperature and chemical\npotential it is\nwell known in the continuum formulation, that Lorentz and gauge invariance\nprotects the gluon from acquiring a mass. The screening mass is therefore\ndetermined by the\nfinite temperature (f.T.), finite chemical potential contribution, given by the\nintegral in (\\ref{eq:bc}). By making again use of the fact that\n$\\phi\\leftrightarrow\\psi$, when $\\vec{\\hat{p}} \\rightarrow -\n\\vec{\\hat{p}}-\\vec{\\hat{k}}$, while $\\eta$, $\\xi$ and ${\\cal G}$\nremain invariant under this change of variables, we can write this\ncontribution in\nthe form\n\\begin{eqnarray}\n \\hat{\\Pi}^{(\\beta,\\mu)}_{44}(0,\\vec{\\hat{k}})_{f.T.} &=& N_{f}g^{2}\n \\int^{\\pi}_{-\\pi}\n \\frac{d^{3}\\hat{p}}{(2\\pi)^{3}}\\left( \\coth\\phi-\\frac{\\rho}{\n \\sinh\\phi} \\right) [ \\hat{\\eta}_{FD}(\\phi)+\\bar{\\hat{\\eta}}_{FD}\n(\\phi) ] \\nonumber \\\\\n& &\\mbox{} -\\frac{1}{2}N_{f}g^{2}\\int^{\\pi}_{-\\pi}\n \\frac{d^{3}\\hat{p}}{(2\\pi)^{3}} \\left\\{ h(\\phi,\\psi,\\eta,\\xi,{\\cal G})\n[ \\hat{\\eta}_{FD}(\\phi)+\\bar{\\hat{\\eta}}_{FD}(\\phi) ]\\right. \\nonumber \\\\\n& &\\mbox{}+ \\left. h(\\psi,\\phi,\\eta,\\xi,{\\cal G})[ \\hat{\\eta}_{FD}(\\psi)\n+\\bar{\\hat{\\eta}}_{FD}(\\psi)] \\right\\} \\ . \\label{pi:fft}\n\\end{eqnarray}\nConsider the second integral. It can be rewritten as follows\n\\[ \\int^{\\pi}_{-\\pi}\n \\frac{d^{3}\\hat{p}}{(2\\pi)^{3}} \\{ \\tilde{h}(\\phi,\\psi,\\eta,\\xi,{\\cal G})\n[\\hat{\\eta}_{FD}(\\psi)+\\bar{\\hat{\\eta}}_{FD}(\\psi)]+\n h(\\phi,\\psi,\\eta,\\xi,{\\cal G})\n \\bigtriangleup\\hat{\\eta}_{FD}(\\phi,\\psi) \\} \\ , \\]\nwhere $\\tilde{h}$ has been defined in (\\ref{eq:bd}), and\n\\[ \\bigtriangleup\\hat{\\eta}_{FD}(\\phi,\\psi) =\n [\\hat{\\eta}_{FD}(\\phi)-\\hat{\\eta}_{FD}(\\psi)]+\n [\\bar{\\hat{\\eta}}_{FD}(\\phi)-\\bar{\\hat{\\eta}}_{FD}(\\psi)]\\ . \\]\nAccording to (\\ref{eq:be}), $\\tilde{h}$ approaches a finite limit for\n$\\vec{\\hat{k}} \\rightarrow 0$. \nUpon making the change of variables \n$\\vec{\\hat{p}} \\rightarrow -\\vec{\\hat{p}}-\\vec{\\hat{k}}$\nthe contribution proportional to $\\tilde{h}$ is seen to be\ncancelled by\nthe first integral in (\\ref{pi:fft}). We therefore conclude that\n\\begin{equation}\n \\lim_{\\vec{\\hat{k}} \\rightarrow 0}\\hat{\\Pi}^{(\\beta,\\mu)}_{44}\n (0,\\vec{\\hat{k}})=\n -\\frac{1}{2}N_{f}g^{2}\\lim_{\\vec{\\hat{k}}\\rightarrow 0}\\int^{\\pi}_{-\\pi}\n \\frac{d^{3}\\hat{p}}{(2\\pi)^{3}}\n h(\\phi,\\psi,\\eta,\\xi,{\\cal G})\\bigtriangleup\\hat{\\eta}_{FD}\n (\\phi,\\psi)\\ .\n\\end{equation}\nWe have now dropped the subscript \"f.T.\", since in this\nlimit only (\\ref{pi:fft}) contributes to the screening mass. To calculate\nthis limit we proceed as before and set $\\psi=\\phi+\\epsilon$.\nOne then verifies that for $\\epsilon \\rightarrow 0$ \n(or $\\vec{\\hat{k}} \\rightarrow 0$) the\nfermionic\ncontribution to the screening mass squared is given by\n\\begin{equation}\n [\\hat{m}_{el}^{2}(\\hat{\\beta},\\hat{\\mu},\\hat{\nm})]_{ferm}=N_{f}g^{2}\\hat{\\beta}\\int^{\\pi}_{-\\pi}\n \\frac{d^{3}\\hat{p}}{(2\\pi)^{3}}\n \\left\\{ \\frac{e^{\\hat{\\beta}(\\phi+\\hat{\\mu})}}{\n [e^{\\hat{\\beta}(\\phi+\\hat{\\mu})}+1]^2}+\n \\frac{e^{\\hat{\\beta}(\\phi-\\hat{\\mu})}}{\n [e^{\\hat{\\beta}(\\phi-\\hat{\\mu})}+1]^2}\\right\\} \\ . \\label{mel:fermg}\n\\end{equation}\nIn the continuum limit the electric screening mass is given by\n\\begin{equation}\n m^{2}_{el} = \\lim_{a\\rightarrow 0}\\frac{1}{a^{2}} \\hat{m}_{el}^{2} \n (\\frac{\\beta}{a},\\mu a,ma)\\ . \\label{mel:lim}\n\\end{equation}\nFor Wilson fermions, only momenta $\\vec{\\hat{p}}$ in the immediate\nneighbourhood of\n$\\vec{\\hat{p}} = 0$ contribute to the integral (\\ref{mel:fermg}) for \n$\\hat{\\beta} \\rightarrow \\infty$,\n$\\hat{\\beta}\\hat{\\mu} = \\beta\\mu$, $\\hat{\\beta}\\hat{m} = \\beta m$ fixed.\nBut in this\nlimit $\\hat{\\beta}\\phi(\\vec{\\hat{p}}) \\rightarrow \n\\beta\\sqrt{\\vec{p}^{\\, 2}+m^{2}}$.\nIntroducing in (\\ref{mel:fermg}) the dimensioned\nmomenta $\\vec{p} = \\vec{\\hat{p}}\/a$ as new integration variables, with $a$\nthe lattice\nspacing, one then verifies, after performing\nthe angular integration, and a partial integration that\n\\begin{equation}\n [m^{2}_{el}]_{ferm}=N_{f}\\frac{g^{2}}{2\\pi^{2}}\\int^{\\infty}_{0}dp\n \\frac{2p^{2}+m^{2}}{\\sqrt{p^{2}+m^{2}}}\\left[\\eta_{FD}(E,\\mu) +\n \\bar{\\eta}_{FD}(E,\\mu)\\right]\\ ,\n\\end{equation}\nwhere $E = \\sqrt{\\vec{p}^{\\, 2}+m^{2}}$, and\n\\begin{equation}\n \\eta_{FD}(E,\\mu) = \\frac{1}{e^{\\beta (E-\\mu)}+1}\\ ; \\ \\\n \\bar{\\eta}_{FD}(E,\\mu) = \\frac{1}{e^{\\beta (E+\\mu)}+1} \n\\end{equation}\nare the Fermi-Dirac distribution functions for particles and antiparticles.\n\nWe next consider the contribution to the electric screening mass arising\nfrom diagrams\n(c-g) in fig.\\ 1.\nThey only involve sums over Matsubara frequencies\nof the bosonic type. Since in the continuum limit the only dimensioned\nscale is the temperature, their contribution to the screening mass will be\nof the form $const \\times g T$. For finite lattice spacing, however, the\ntemperature dependence will be modified by lattice artefacts. In\nthe following we first consider diagrams (c-e) which have an analog\nin the continuum.\\\\ \\\\\n{\\it iii) Contribution of diagram (c)}\\\\\n\nUsing the lattice Feynman rules given in Appendix A one finds after some\nalgebra that\nthis diagram contributes as follows to\n$\\hat{\\Pi}^{(\\beta,\\mu)}_{44}(0,\\vec{\\hat{k}})$,\ndefined in (\\ref{diag:col}),\n\\alpheqn\n\\begin{equation}\n\\hat{\\Pi}^{(\\beta,\\mu)}_{44}(0,\\vec{\\hat{k}})_{(c)}=\\frac{3}{2}\n g^{2}\\frac{1}{\\hat{\\beta}}\\sum^{\\frac{\\hat{\\beta}}{2}-1}_{\\ell=\n -\\frac{\\hat{\\beta}}{2}} \\int^{\\pi}_{-\\pi}\\frac{d^{3}\\hat{q}}{\n (2\\pi)^{3}}f^{(c)}(e^{i\\hat{\\omega}^{+}_{\\ell}};\\vec{\\hat{q}},\n \\vec{\\hat{k}})\\ ,\n\\end{equation}\nwhere\n\\begin{equation}\n f^{(c)}(z;\\vec{\\hat{q}},\\vec{\\hat{k}})=\\frac{a(\\vec{\\hat{k}})(z^{2}-1)^{2}-b\n (\\vec{\\hat{q}},\\vec{\\hat{k}})z(z+1)^{2}}{\n \\Pi^{4}_{i=1}[z-\\bar{z}_i]} \\label{eq:ca}\n\\end{equation}\nand\n\\begin{eqnarray}\n a(\\vec{\\hat{k}}) &=& \\sum_{j}\\cos^{2}\\frac{\\hat{k}_{j}}{2}\\ , \\\\\n b(\\vec{\\hat{q}},\\vec{\\hat{k}}) &=& \\frac{1}{4} \\left[ \\sum_{j}\n \\widetilde{(\\hat{q}-\\hat{k})}^{2}_{j} +\n \\sum_{j}\\widetilde{(\\hat{q}+2\\hat{k})}^{2}_{j} \\right] \\ .\n\\end{eqnarray}\n\\reseteqn\nHere $\\tilde{\\hat{p}}$ is generically defined by\n$\\tilde{\\hat{p}}_{\\mu}=2\\sin\\frac{\\hat{p}_{\\mu}}{2}$.\nThe zeros of the denominator in (\\ref{eq:ca}) are located at\n\\alpheqn\n\\begin{eqnarray}\n \\bar{z}_{1} &=& e^{\\tilde{\\phi}}\\ ;\\ \\bar{z}_{2}=e^{-\\tilde{\\phi}}\\ ,\n \\nonumber \\\\\n \\bar{z}_{3} &=& e^{\\tilde{\\psi}}\\ ;\\ \\bar{z}_{4}=e^{-\\tilde{\\psi}}\\ ,\n\\end{eqnarray}\nwhere\n\\begin{eqnarray}\n \\tilde{\\phi} &=& \\mbox{arcosh} H(\\vec{\\hat{q}})\\ , \\nonumber \\\\\n \\tilde{\\psi} &=& \\mbox{arcosh} H(\\vec{\\hat{q}}+\\vec{\\hat{k}})\\ , \\\\\n H(\\vec{\\hat{p}}) &=& 1+2\\sum_{j}\\sin^{2}\\frac{\\hat{p}_{j}}{2}\\ . \\nonumber\n\\end{eqnarray}\n\\reseteqn\nThe frequency sum can be calculated by making use of \n(\\ref{sum:bosg}). After some\nstraight forward algebra one finds that\n\\alpheqn\n\\begin{eqnarray}\n\\lefteqn{\n \\hat{\\Pi}^{(\\beta,\\mu)}_{44}(0,\\vec{\\hat{k}})_{(c)}= 6g^2\n \\int^{\\pi}_{-\\pi}\\frac{d^{3}\\hat{q}}{(2\\pi)^{3}}\n h(\\tilde{\\phi},\\tilde{\\psi},\n a,b)\\hat{\\eta}_{BE}(\\tilde{\\phi}) } \\nonumber \\\\\n& &\\mbox{}+\\frac{3}{2} g^{2} \\left\\{ a(\\vec{\\hat{k}})+\\int^{\\pi}_{-\\pi}\n \\frac{d^{3}\\hat{q}}{(2\\pi)^{3}}[h(\\tilde{\\phi},\\tilde{\\psi},a,b)+h\n (\\tilde{\\psi},\\tilde{\\phi},a,b)] \\right\\}\\ , \\label{eq:cb}\n\\end{eqnarray}\nwhere\n\\begin{equation}\n h(\\tilde{\\phi},\\tilde{\\psi},a,b)=\\frac{-a\\, \\sinh^{2}\\tilde{\\phi}\n +\\frac{1}{2} b[\\cosh\\tilde{\\phi}+1]}{\\sinh\\tilde{\\phi}\n [\\cosh\\tilde{\\phi}-\\cosh\\tilde{\\psi}]} \\label{eq:cc}\n\\end{equation}\nand\n\\begin{equation}\n \\hat{\\eta}_{BE}(\\tilde{\\phi}) = \\frac{1}{e^{\\hat{\\beta}\\tilde{\\phi}}-1}\n\\end{equation}\n\\reseteqn\nis the lattice version of the Bose-Einstein distribution function.\n\nIn obtaining this result we have made use of the fact that\n\\begin{equation}\n \\tilde{\\phi} \\stackrel{\\vec{\\hat{q}} \\rightarrow\n -\\vec{\\hat{q}}-\\vec{\\hat{k}}}{\\longleftrightarrow} \\tilde{\\psi} \\label{substb}\n\\end{equation}\nwhile $a(\\vec{\\hat{k}})$ and $b(\\vec{\\hat{q}},\\vec{\\hat{k}})$ are invariant\nunder the\ntransformation \n$\\vec{\\hat{q}} \\rightarrow -\\vec{\\hat{q}}-\\vec{\\hat{k}}$. Note that the\nfunction\n(\\ref{eq:cc}) is singular for $\\vec{\\hat{k}} \\rightarrow 0$,\nsince in this limit $\\tilde{\\phi} \\rightarrow \\tilde{\\psi}$. \nThe singularity is however\nintegrable as can be seen by making use of (\\ref{substb}) to write\n(\\ref{eq:cb}) in the form\n\\alpheqn\n\\begin{eqnarray}\n\\lefteqn{\n \\hat{\\Pi}^{(\\beta,\\mu)}_{44}(0,\\vec{\\hat{k}})_{(c)}=3g^2\n \\int^{\\pi}_{-\\pi}\\frac{d^{3}\\hat{q}}{(2\\pi)^{3}}\n h(\\tilde{\\phi},\\tilde{\\psi},a,b)\n \\bigtriangleup\\hat{\\eta}_{BE}(\\tilde{\\phi},\\tilde{\\psi}) } \\\\\n& &\\mbox{}+\\frac{3}{2}g^{2} \\left\\{ a(\\vec{\\hat{k}})+\\int^{\\pi}_{-\\pi}\n \\frac{d^{3}\\hat{q}}{(2\\pi)^{3}}[h(\\tilde{\\phi},\\tilde{\\psi},a,b)+\n h(\\tilde{\\psi},\n \\tilde{\\phi},a,b)][1+2\\hat{\\eta}_{BE}(\\tilde{\\phi})] \\right\\}\\ , \\nonumber\n\\end{eqnarray}\nwhere\n\\begin{equation}\n \\bigtriangleup\\hat{\\eta}_{BE}(\\tilde{\\phi},\\tilde{\\psi}) = \n \\hat{\\eta}_{BE}(\\tilde{\\phi})\n -\\hat{\\eta}_{BE}(\\tilde{\\psi}) \\ . \\label{def:delbe}\n\\end{equation}\n\\reseteqn\nThe limit $\\vec{\\hat{k}} \\rightarrow 0$ \ncan now be easily taken and one obtains the\nfollowing contribution to the electric screening mass\n\\begin{eqnarray}\n (\\hat{m}^{2}_{el})_{(c)} &=& \\frac{3}{2} g^{2} \\left\\{ 3-\\int^{\\pi}_{-\\pi}\n \\frac{d^{3}\\hat{q}}{(2\\pi)^{3}} \\left[\n 3\\coth\\tilde{\\phi}+\\frac{1}{2\\sinh\n \\tilde{\\phi}} \\right] [1+2\\hat{\\eta}_{BE}(\\tilde{\\phi})] \\right\\} \\nonumber \\\\\n& &\\mbox{}+\\frac{15}{2} g^{2}\\hat{\\beta}\\int^{\\pi}_{-\\pi}\n \\frac{d^{3}\\hat{q}}{(2\\pi)^{3}}\n \\frac{e^{\\hat{\\beta}\\tilde{\\phi}}}{[e^{\\hat{\\beta}\\tilde{\\phi}}-1]^{2}}\n \\ . \\label{mel:c}\n\\end{eqnarray} \\pagebreak \\\\\n{\\it iv) Contribution of diagram (d)}\\\\\n\nThis diagram involves the 4-gluon vertex, which consists of types of terms\ndiffering in the colour structure: terms involving the structure constants\n$f_{ABC}$,\nand terms involving the completely symmetric colour couplings $d_{ABC}$. We\ndenote\nthe corresponding contributions to $\\hat{\\Pi}^{(\\beta,\\mu)}_{44}(\\hat{k})$\nby $[\\hat{\\Pi}^{(\\beta,\\mu)}_{44}(\\hat{k})]_{[f]}$ and\n$[\\hat{\\Pi}^{(\\beta,\\mu)}_{44}(\\hat{k})]_{[d]}$,\nrespectively.\nConsider first $[\\hat{\\Pi}^{(\\beta,\\mu)}_{44}(0,\\vec{\\hat{k}})_{(d)}]_{[f]}$.\nAfter some algebra one finds that\n\\alpheqn\n\\begin{equation}\n \\left[\\hat{\\Pi}^{(\\beta,\\mu)}_{44}(0,\\vec{\\hat{k}})_{(d)}\\right]_{[f]}=\n \\frac{3}{4} g^{2}\\frac{1}{\\hat{\\beta}}\\sum^{\\frac{\\hat{\\beta}}{2}-1}_{\n \\ell=-\\frac{\\hat{\\beta}}{2}}\\int^{\\pi}_{-\\pi}\n \\frac{d^{3}\\hat{q}}{(2\\pi)^{3}}\n \\left[ f^{(d)}(e^{i\\hat{\\omega}^{+}_{\\ell}};\\hat{q},\\hat{k})\\right]_{\n [f]}\\ , \\label{eq:da}\n\\end{equation}\nwhere\n\\begin{equation}\n \\left[ f^{(d)}(z;\\vec{\\hat{q}},\\vec{\\hat{k}})\\right]_{[f]}=\n \\frac{-c(\\vec{\\hat{k}})(z^{2}+1)+d(\\vec{\\hat{k}})(z-1)^{2}+\n P(\\vec{\\hat{q}},\\vec{\\hat{k}})z}{\n [z-\\bar{z}_{1}][z-\\bar{z}_{2}]}\n\\end{equation}\nand\n\\begin{eqnarray}\n c(\\vec{\\hat{k}}) &=& 1+2\\sum_{j}\\cos \\hat{k}_{j} \\ , \\nonumber \\\\\n d(\\vec{\\hat{k}}) &=& 1-\\frac{1}{3}\\sum_{j} \\tilde{\\hat{k}}_{j}^{2} \\ , \\\\\n P(\\vec{\\hat{q}},\\vec{\\hat{k}}) &=& 2+\\frac{1}{6}\\sum_{j}\n [\\widetilde{(\\hat{q}+\\hat{k})}_{j}^{2} +\n \\widetilde{(\\hat{q}-\\hat{k})}_{j}^{2}] \\ . \\nonumber\n\\end{eqnarray}\n\\reseteqn\nPerforming the frequency sum in (\\ref{eq:da}) one obtains\n\\begin{eqnarray}\n\\lefteqn{\n \\left[ \\hat{\\Pi}^{(\\beta,\\mu)}_{44}(0,\\vec{\\hat{k}})_{(d)} \\right]_{[f]}=\n \\frac{3}{4} g^{2} \\left\\{ -c(\\vec{\\hat{k}})+\n d(\\vec{\\hat{k}}) \\right. } \\nonumber \\\\\n& &\\mbox{}+\\int^{\\pi}_{-\\pi}\\frac{d^{3}\\hat{q}}{(2\\pi)^{3}}\n \\left. \\left[ (c-d)\n \\coth\\tilde{\\phi}+(d-\\frac{1}{2}P)\\frac{1}{\\sinh\\tilde{\\phi}} \\right]\n [1+2\\hat{\\eta}_{BE}(\\tilde{\\phi})] \\right\\} \\ .\n\\end{eqnarray}\nTaking the limit $\\vec{\\hat{k}} \\rightarrow 0$ one finds the following\ncontribution to\nthe screening mass\n\\begin{equation}\n (\\hat{m}^{2}_{el})^{(d)}_{[f]}=\\frac{1}{2}g^{2} \\left\\{ -9+\\frac{1}{\n 2}\\int^{\\pi}_{-\\pi}\n \\frac{d^{3}\\hat{q}}{(2\\pi)^{3}} \\left[ 17\\coth\n \\tilde{\\phi}+\\frac{1}{\\sinh\n \\tilde{\\phi}} \\right] [1+2\\hat{\\eta}_{BE}(\\tilde{\\phi})] \\right\\}\n \\ . \\label{mel:df}\n\\end{equation}\nNext consider the contribution \n$[\\hat{\\Pi}_{44}^{(\\beta,\\mu)}(0,\\vec{\\hat{k}})_{(d)}]_{[d]}$.\nIt is given by\n\\alpheqn\n\\begin{equation}\n \\left[\\hat{\\Pi}^{(\\beta,\\mu)}_{44}(0,\\vec{\\hat{k}})_{\n (d)}\\right]_{[d]}=-\\frac{1}{2}\n g^{2}\\frac{1}{\\hat{\\beta}}\\sum^{\\frac{\\hat{\\beta}}{2}-1}_{\\ell=-\n \\frac{\\hat{\\beta}}{2}}\\int^{\\pi}_{-\\pi}\\frac{d^{3}\\hat{q}}{(2\\pi)^{3}}\n \\left[ f^{(c)}(e^{i\\hat{\\omega}^{+}_{\\ell}};\\vec{\\hat{q}},\\vec{\\hat{k}})\n \\right]_{[d]}\\ ,\n\\end{equation}\nwhere\n\\begin{eqnarray}\n \\left[ f^{(d)}(z;\\vec{\\hat{q}},\\vec{\\hat{k}})\\right]_{[d]} &=&\\frac{1}{12}\n \\left(\\frac{20}{3}+d(A)\\right) \\frac{ K(\\vec{\\hat{k}})(z-1)^{2}-L(\\vec{\\hat{\n q}},\\vec{\\hat{k}})z}{\n [z-\\bar{z}_{1}][z-\\bar{z}_{2}]}\\ , \\\\\n K(\\vec{\\hat{k}}) &=& \\sum_{j}\\tilde{\\hat{k}}^{2}_{j}\\ , \\\\\n L(\\vec{\\hat{q}},\\vec{\\hat{k}}) &=& \\sum_{j}\\tilde{\\hat{q}}_{j}^{2}\n \\tilde{\\hat{k}}^{2}_{j}\\ ,\n\\end{eqnarray}\nand where $d(A)$ is defined by\n\\begin{equation}\n \\sum^{8}_{E,F=1}[2d_{AFE} d_{BFE}+d_{FFE}d_{ABE}]=d(A)\\delta_{AB}\\ .\n\\end{equation}\n\\reseteqn\nPerforming the frequency sum one finds\n\\begin{eqnarray*}\n\\lefteqn{\n \\left[\\hat{\\Pi}^{(\\beta,\\mu)}_{44}(0,\\vec{\\hat{k}}\n )_{(d)}\\right]_{[d]} = g^{2}\n \\frac{1}{24}\\left(\\frac{20}{3}+d(A)\\right) } \\\\\n& &\\times\\left\\{ -K+\\int^{\\pi}_{-\\pi}\n \\frac{d^{3}\\hat{q}}{(2\\pi)^{3}}\\left[ K \\coth\\tilde{\\phi}-\n \\frac{ K+\\frac{1}{2} L}{\\sinh\\tilde{\\phi}} \\right]\n [1+\\hat{\\eta}_{BE}\n (\\tilde{\\phi})] \\right\\}\\ .\n\\end{eqnarray*}\nSince $K(\\vec{\\hat{k}})$ and $L(\\vec{\\hat{q}},\\vec{\\hat{k}})$ vanish for\n$\\vec{\\hat{k}} \\rightarrow 0$, it does not contribute\nto the screening mass, i.e.,\n\\begin{equation}\n [(\\hat{m}_{el})_{(d)}]_{[d]} = 0 \\ . \\label{mel:dd}\n\\end{equation}\\\\\n{\\it v) Contribution of diagram (e)}\\\\\n\nThe only other diagram possessing a continuum analog is the ghost\nloop shown\nin fig.\\ 1e. Its contribution is given by\n\\alpheqn\n\\begin{equation}\n\\hat{\\Pi}^{(\\beta,\\mu)}_{44}(0,\\vec{\\hat{k}})_{(e)} = \\frac{3}{2}\n g^{2}\\frac{1}{\\hat{\\beta}}\n \\sum^{\\frac{\\hat{\\beta}}{2}-1}_{\\ell=-\n \\frac{\\hat{\\beta}}{2}}\\int^{\\pi}_{-\\pi}\\frac{d^{3}\\hat{q}}{(2\\pi)^{3}}\n f^{(d)}(e^{i\\hat{\\omega}^{+}_{\\ell}};\\vec{\\hat{q}},\\vec{\\hat{k}})\\ ,\n\\end{equation}\nwhere\n\\begin{equation}\n f^{(e)}(z;\\vec{\\hat{q}},\\vec{\\hat{k}}) = -\\frac{1}{2}\n \\frac{(z^{2}-1)^{2}}{\\Pi^{4}_{i=1}[z-\\bar{z}_{i}]} \\ .\n\\end{equation}\n\\reseteqn\nPerforming the frequency sum one finds that\n\\alpheqn\n\\begin{eqnarray}\n \\hat{\\Pi}^{(\\beta,\\mu)}_{44}(0,\\vec{\\hat{k}})_{(e)} &=& \\frac{3}{4}g^{2}\n \\left\\{ -1+\\int^{\\pi}_{-\\pi}\n \\frac{d^{3}\\hat{q}}{\n (2\\pi)^{3}}[g(\\tilde{\\phi},\\tilde{\\psi})+g(\\tilde{\\psi},\\tilde{\\phi})]\n \\right. \\nonumber \\\\\n& &\\mbox{}+ \\left. 4\\int^{\\pi}_{-\\pi}\n \\frac{d^{3}\\hat{q}}{(2\\pi)^{3}}g(\\tilde{\\phi},\\tilde{\\psi})\n \\hat{\\eta}_{BE}(\\tilde{\\phi}) \\right\\} \\ , \\label{eq:ea}\n\\end{eqnarray}\nwhere\n\\begin{equation}\n g(\\tilde{\\phi},\\tilde{\\psi}) = \\frac{\\sinh \\tilde{\\phi}}{\\cosh\\tilde{\\phi} -\n \\cosh\\tilde{\\psi}}\\ .\n\\end{equation}\n\\reseteqn\nThis function is again singular for $\\vec{\\hat{k}} \\rightarrow 0$. \nTo compute the\nlimit we\nproceed as discussed earlier and write (\\ref{eq:ea}) in the form\n\\begin{eqnarray*}\n \\hat{\\Pi}^{(\\beta,\\mu)}_{44}(0,\\vec{\\hat{k}})_{(e)} &=& \\frac{3}{4}g^{2}\n \\left\\{ -1+\\int^{\\pi}_{-\\pi}\n \\frac{d^{3}\\hat{q}}{(2\\pi)^{3}}[g(\\tilde{\\phi},\\tilde{\\psi})+\n g(\\tilde{\\psi},\\tilde{\\phi})]\n [1+2\\hat{\\eta}_{BE}(\\tilde{\\phi})]\\right. \\\\\n& &\\mbox{}+ \\left. 2\\int^{\\pi}_{-\\pi}\n \\frac{d^{3}\\hat{q}}{\n (2\\pi)^{3}}g(\\tilde{\\phi},\\tilde{\\psi})\\bigtriangleup\n \\hat{\\eta}_{BE}(\\tilde{\\phi},\n \\tilde{\\psi}) \\right\\}\\ ,\n\\end{eqnarray*}\nwhere $\\bigtriangleup\\hat{\\eta}_{BE}(\\tilde{\\phi},\\tilde{\\psi})$ \nhas been defined in (\\ref{def:delbe}).\nTaking the limit $\\vec{\\hat{k}} \\rightarrow 0$ \none obtains\n\\begin{eqnarray}\n(\\hat{m}^{2}_{el})_{(e)} &=& \\frac{3}{4}g^{2}\\left\\{ -1 +\n \\int^{\\pi}_{-\\pi}\n \\frac{d^{3}\\hat{q}}{(2\\pi)^{3}}[1+2\\hat{\\eta}_{BE}(\\tilde{\\phi})]\n \\coth\\tilde{\\phi} \\right. \\nonumber \\\\\n& &\\mbox{} \\left. -2\\hat{\\beta}\\int^{\\pi}_{-\\pi}\n \\frac{d^{3}\\hat{q}}{\n (2\\pi)^{3}}\\frac{e^{\\hat{\\beta}\\tilde{\\phi}}}{[e^{\\hat{\\beta}\\tilde{\\phi}}-1\n ]^{2}} \\right\\} \\ . \\label{mel:e}\n\\end{eqnarray}\nCombining the results (\\ref{mel:c}), (\\ref{mel:df}), (\\ref{mel:dd}) \nand (\\ref{mel:e}), we therefore\nfind that\nthose diagrams possessing\na continuum analog yield the following contribution to the electric screening\nmass in the gluonic sector\n\\begin{eqnarray}\n(\\hat{m}^{2}_{el})_{(c+d+e)} &=& g^{2}\\left\\{ -\\frac{3}{4}\n +\\frac{1}{2}\\int_{-\\pi}^{\\pi}\\frac{d^{3}\\hat{q}}{(2\\pi)^{3}} \n \\left( \\coth\\tilde{\\phi} -\n \\frac{1}{\\sinh\\tilde{\\phi}}\\right)[1+2\\hat{\\eta}_{BE}(\\tilde{\\phi})]\n \\right\\} \\nonumber \\\\\n& &\\mbox{}+6g^{2}\\hat{\\beta}\\int_{-\\pi}^{\\pi}\\frac{d^{3}\\hat{q}}{(2\\pi)^{3}}\n \\frac{e^{\\hat{\\beta}\\tilde{\\phi}}}{[e^{\\hat{\\beta}\\tilde{\\phi}}-1]^{2}}\n \\ . \\label{mel:cde}\n\\end{eqnarray}\n\nThe computation of the remaining contributions arising from diagrams (f)\nand (g),\nwhich are a consequence of the lattice regularization, is\nstraight forward. One finds that they cancel the first term in\n(\\ref{mel:cde}).\nHence the gluonic sector (G) contributes as follows to the screening\nmass\n\\begin{equation}\n [\\hat{m}_{el}^{2}(\\hat{\\beta},\\hat{\\mu},\\hat{m})]_{G}=\n 6g^{2}\\hat{\\beta}\\int^{\\pi}_{-\\pi}\\frac{d^{3}\\hat{q}}{(2\\pi)^{3}}\n \\frac{e^{\\hat{\\beta}\\tilde{\\phi}}}{[e^{\\hat{\\beta}\\tilde{\\phi}}-1]^{2}}\\ .\n\\end{equation}\nIn the continuum limit (\\ref{mel:lim}) the corresponding expression for the\n(dimensioned)\nscreening mass squared is given by\n\\begin{eqnarray*}\n (m^{2}_{el})_{G} &=& \\lim_{a\\rightarrow 0}6g^{2}\\beta\\int^{\\frac{\\pi}{a}}_{\n -\\frac{\\pi}{a}}\n \\frac{d^{3}q}{(2\\pi)^{3}}\\frac{e^{\\frac{1}{a}\\beta\\tilde{\\phi}\n (a\\vec{q}\\, )}}{\n [e^{\\frac{1}{a}\\beta\\tilde{\\phi}(a\\vec{q}\\, )}-1]^{2}} \\\\\n&=& \\frac{3}{\\pi^{2}}g^{2}\\beta\\int^{\\infty}_{0} dq\\, q^{2} \n \\frac{e^{\\beta q}}{[e^{\\beta q} -1]^{2}}\\ ,\n\\end{eqnarray*}\nwhere $q = |\\vec{q}\\, |$.\nAfter a partial integration this expression takes the form\n\\[ (m^{2}_{el})_{G} = \\frac{6}{\\pi^{2}}g^{2} T^{2}\\int^{\\infty}_{0} dx \n \\frac{x}{e^{x}-1}\\ . \\]\nMaking use of\n\\[ \\int^{\\infty}_{0} dx \\frac{x^{\\alpha-1}}{e^x-1} =\n \\Gamma(\\alpha)\\zeta(\\alpha)\\ , \\ \\ \\alpha > 1 \\ , \\]\nwhere $\\Gamma(\\alpha)$ is the Euler Gamma function, and $\\zeta(\\alpha)$ the\nRiemann\nZeta-function, we recover the well known result:\\ \n$(m^{2}_{el})_{G} = g^{2}T^{2}$.\n\\section{Lattice Artefacts in the Screening Mass}\n\\setcounter{equation}{0}\nIn this section we compare the one loop result for the electric screening mass\non the lattice with the continuum. This will provide us with an estimate of the\nmagnitude of the lattice artefacts to be expected in numerical simulations.\nThe numerical data we present is for two mass-degenerate quarks.\n\nOn a lattice the temperature can be varied by either keeping the lattice\nspacing fixed and varying the number $N_{\\tau}$ of temporal lattice sites, or\nby varying the lattice spacing (or equivalently the coupling) keeping\n$N_{\\tau}$ fixed. For fixed lattice spacing the dependence of the screening\nmass on the temperature, fermion mass and chemical potential is given by\n(see eq. (\\ref{mel:lim}))\n\\begin{equation}\n [m_{el}(T,m,\\mu,a)]_{latt} = \\frac{1}{a}\\hat{m}_{el}(\\frac{1}{Ta},\\mu a,\n ma)\n\\end{equation}\n\\begin{figure}[htb]\n\\leavevmode\n\\centering\n\\epsfxsize10cm \\epsffile{art2.eps} \n\\caption{Dependence of $[m_{el}]_{latt}\/[m_{el}]_{cont}$ on $\\frac{T}{m}$\n for $\\mu=0$ and different lattice spacings measured in units of $m^{-1}$.\n Open squares (filled stars) correspond to lattices with $N_{\\tau}=8$\n ($N_{\\tau}=16$).}\n\\end{figure}\nIf the lattice expression is to\napproximate the continuum, then the lattice spacing must be small compared\nto all\nphysical length scales in the problem. Hence we must have that\n$a \\ll \\frac{1}{T}$,\n$a \\ll \\frac{1}{m}$ and $a \\ll \\frac{1}{\\mu}$. We therefore expect that\nfor temperatures $T \\ll \\frac{1}{a}$ the continuum is well approximated for\n$ma \\ll 1$ and\n$\\mu a \\ll 1$. \nThis is shown in figs. 2 and 3 where we have plotted\n$[m_{el}]_{latt}\/[m_{el}]_{cont}$ as a function of $T\/m$ at $\\mu = 0$ and\n$\\mu\/m =1.5$\nfor various lattice spacings measured\nin units of $m^{-1}$. For $\\mu = 0$ and $ma \\equiv \\tilde{a} \\in [0, .3]$,\nthe deviation of this ratio from\nunity is seen to be at most\n$1.75\\%$ for $\\frac{T}{m} \\leq \\frac{1}{16\\tilde{a}}$. The rhs of this\ninequality is the temperature associated with a lattice with 16 sites\nin the temporal direction. \nFor $\\frac{T}{m} \\approx \\frac{1}{8\\tilde{a}}$ the deviation is already\n$7.5\\%$.\nThe endpoint of the curves\nfor $\\tilde{a} = 0.05$, $0.1$ and $0.3$ correspond to the minimal number\nof temporal lattice\nsites, i.e. $N_{\\tau} =2$, and the open squares (filled stars) to\n$N_{\\tau} =8$ ($N_{\\tau} =16$).\n\\begin{figure}[htb]\n\\leavevmode\n\\centering\n\\epsfxsize10cm \\epsffile{art3.eps}\n\\caption{Dependence of $[m_{el}]_{latt}\/[m_{el}]_{cont}$ on $\\frac{T}{m}$\n for $\\frac{\\mu}{m}=1.5$ and different lattice spacings measured in units \n of $m^{-1}$.\n Open squares (filled stars) correspond to lattices with $N_{\\tau}=8$\n ($N_{\\tau}=16$). The dashed-dotted (dashed) lines show the temperature\n dependence for a fixed number of temporal lattice sites, $N_{\\tau}=8$\n ($N_{\\tau}=16$). }\n\\end{figure}\n\nFor $\\mu\/m = 1.5$ we must also ensure that $\\mu a \\ll 1$. We therefore\nexpect that the allowed range of lattice spacings for achieving an accuracy\nof $2\\%$ for $T \\leq \\frac{1}{16 a}$ is now restricted to a smaller interval.\nFig.\\ 3 shows that the continuum screening mass is well approximated for\n$\\tilde{a} < 0.1$ in this temperature range.\n\nIn lattice simulations one is interested in determining the electric screening\nmass above the deconfining phase transition. It is\nextracted from correlators of Polyakov loops [6--9],\nor from the long distance behaviour of\nthe gluon propagator \\cite{hell}. \nIn these simulations the number of lattice sites\n$N_{\\tau} \\equiv \\hat{\\beta}$ is\nfixed. The electric screening mass in physical units, divided by\nthe temperature, is then given by\n\\begin{equation}\n [m_{el}]_{latt}\/T = N_{\\tau} \\hat{m}_{el}(N_{\\tau},(\\mu\/T)N^{-1}_{\\tau},\n (m\/T)N^{-1}_{\\tau})\\ ,\n\\end{equation}\nwhile in the continuum limit ($N_{\\tau} \\rightarrow \\infty$) \nthis ratio is just a\nfunction of\n$m\/T$ and $\\mu\/T$.\nThe above conditions for approximating the continuuum now read\n(a) $N_{\\tau} \\gg 1$; (b) $ma = (\\frac{m}{T})\\frac{1}{N_{\\tau}} \\ll 1$;\n(c) $\\mu a = (\\frac{\\mu}{T})\\frac{1}{N_{\\tau}} \\ll 1$.\nWe therefore expect that for fixed $N_{\\tau}$ the continuum is best\napproximated for high temperatures. \nFor $\\frac{\\mu}{m}=1.5$ this is shown in fig.\\ 3, where\nthe temperature dependence of $[m_{el}]_{latt}\/[m_{el}]_{cont}$ for\n$N_{\\tau}=8$ and $N_{\\tau}=16$ is given by the dash-dotted and dashed curves\nrespectively. The strong deviation of this ratio at\nlow temperatures is due to the fermion loop contribution. \n\\begin{figure}[htb]\n\\leavevmode\n\\centering\n\\epsfxsize10cm \\epsffile{art4.eps} \\\\\n\\caption{Dependence of the pure gluonic contribution to\n $[m_{el}]_{latt}\/[m_{el}]_{cont}$ on the number of lattice sites $N_{\\tau}$.\n The solid line interpolates between different numbers of lattice sites,\n $N_{\\tau}$.}\n\\end{figure}\nThis is evident\nfrom fig.\\ 4, where we have plotted \n$[m_{el}]_{latt}\/[m_{el}]_{cont}$ for the pure SU(3) gauge theory for various\nvalues of $N_{\\tau}$. This ratio only depends on the number of lattice sites,\n$N_{\\tau}$. The solid line interpolates between different numbers of\ntemporal lattice sites. \nThe deviation from the continuum is seen to be small already\nfor $N_{\\tau}=8$. For $N_{\\tau}=8$, and $N_{\\tau}=16$, it is about $2\\%$,\nand $0.4\\%$, respectively.\n\n\\begin{figure}[htb]\n\\leavevmode\n\\centering\n\\begin{tabular}{cc}\n\\epsfxsize7.5cm \\epsffile{art5.eps} & \n\\epsfxsize7.5cm \\epsffile{art6.eps} \\\\\n\\end{tabular}\n\\caption{Dependence of $[m_{el}]_{latt}\/[m_{el}]_{cont}$ on $\\frac{m}{T}$\n and $\\frac{\\mu}{T}$ for (a) $N_{\\tau}=8$, and (b) $N_{\\tau}=16$.}\n\\end{figure}\nFinally, in fig.\\ 5\nwe have plotted the ratio $[m_{el}]_{latt}\/[m_{el}]_{cont}$ as a function\nof $\\frac{m}{T}$ and $\\frac{\\mu}{T}$ for \n$N_{\\tau} = 8, 16$. In the parameter\nrange\nconsidered the above inequalities are well satisfied and the\ndeviation of this ratio from unity is seen to be at most\n$1.7\\%$ for $N_{\\tau} = 16$,\nand $10\\%$ for $N_{\\tau} = 8$.\nThe range of values $m\/T$ and $\\mu\/T$ for which the continuum is\nwell approximated will of course increase with increasing $N_{\\tau}$.\n\\section{Conclusions}\n\\setcounter{equation}{0}\nIn this paper we have have computed the electric screening mass for\nWilson fermions in the infinite volume limit for lattice QCD at finite\ntemperature and chemical potential in one\nloop order. The expression we obtained had a very transparent structure in\nwhich the artefacts arising from a finite lattice spacing were concentrated\nin two functions which in the naive continuum limit reduced to the\non shell energies of a free quark and gluon. We then studied the\ndependence of the lattice\nscreening mass on the temperature and chemical potential for fixed values of\nthe lattice spacing. It was found that lattice artefacts\ngive rise to an enhancement of the screening mass. For $\\mu =0$\nand lattice spacings $a < .3m^{-1}$ the deviation\nof $[m_{el}]_{latt}\/[m_{el}]_{cont}$ from the continuum was found to\nbe less than $1.75\\%$ for $\\frac{T}{m} \\leq \\frac{1}{16\\tilde{a}}$,\nwhere $\\tilde{a}=ma$. For\n$\\frac{\\mu}{m} = 1.5$ a substantially smaller lattice spacing was\nrequired to approximate the continuum. Most of the deviation was found to\nbe due to the fermion loop contribution.\n\nSince in numerical simulations the temperature dependence of the screening\nmass is extracted from a given lattice by varying the coupling\n(lattice spacing), we have also studied the dependence of the lattice\nscreening mass on the temperature and chemical potential for \nfixed $N_{\\tau}$. It\nwas found that for $N_{\\tau} =16$, and temperatures larger than the fermion\nmass and chemical potential, the continuum screening mass was approximated\nto within $1.75\\%$. The corresponding\ndeviation for $N_{\\tau} = 8$ was found to be\nat most $10\\%$ and to be due to the fermion loop contribution.\nIn the pure SU(3) gauge theory the continuum\nwas already approximated to $2\\%$ for only 8 lattice sites in\nthe temporal direction.\n\nOur analysis was carried out for infinite lattice volume.\nFor finite spatial volume the momentum spectrum becomes\ndiscrete and zero momentum modes must be treated separately in a\nperturbative expansion. In comparing the data for the electric\nscreening mass obtained in Monte Carlo simulations with continuum\nperturbation theory, finite volume effects need to be\nincluded, while finite lattice spacing effects may, as our analysis\nsuggests, be negligible\nfor those couplings and lattice sizes at which the simulations have been\nperformed.\\\\ \\\\\n\\begin{center} {\\bf ACKNOWLEDGEMENTS} \\end{center}\nWe are very grateful to T. Reisz for several discussions and constructive\ncomments.\n","meta":{"redpajama_set_name":"RedPajamaArXiv"}} +{"text":"\\section{Introduction}\n\nWe investigate algorithmic computability of a particular class of coalitional games (cooperative games), \ncalled \\emph{simple games} (voting games). \nOne can think of simple games as representing voting methods; alternatively,\nas representing ``manuals'' or ``contracts.'' \nWe give a characterization of computable simple games; it implies that a computable simple game uses\ninformation about only finitely many players, but how much information it uses depends on each coalition.\nWe also apply the characterization to the theory of the core.\nFor the latter application, we extend Nakamura's \ntheorem (\\citeyear{nakamura79}) regarding the core of simple games to the framework\nwhere not all subsets of players are deemed to be a coalition.\n\n\\subsection{Computability analysis of social choice}\n\nMost of the paper (except the part on the theory of the core) \ncan be viewed as a contribution to the foundations of \n\\emph{computability analysis of social choice}, \nwhich studies algorithmic properties of social decision-making. \nThis literature includes \\citet{kelly88}, \n\\citet{lewis88}, \\citet{bartholdi-tt89vs,bartholdi-tt89cd},\nand \\citet{mihara97et,mihara99jme,mihara04mss},\nwho study issues in social choice using \\emph{recursion theory} \n(the theory of computability and complexity).\\footnote\nThese works, which are mainly concerned with the complexity of rules or cooperative games in themselves,\ncan be distinguished from the closely related studies of the complexity of \\emph{solutions} for cooperative games, \nsuch as \\citet{deng-p94} and \\citet{fang-zcd02}; %\nthey are also distinguished from the studies, such as \\citet{takamiya-t0701}, of the complexity of deciding\nwhether a given cooperative game has a certain property.\n(More generally, applications of recursion \ntheory to economic theory and game theory include\n\\citet{spear89}, \\citet{canning92}, \\citet{anderlini-f94},\n\\citet{anderlini-s95}, \\citet{prasad97},\n\\citet{richter-w99jme, richter-w99et}, and \\citet{evans-t01}.\nSee also \\citet{lipman95} and \\citet{rubinstein98} for surveys of the literature on \nbounded rationality in these areas.)}\n\nThe importance of computability in social choice theory would be unarguable.\nFirst, the use of the language by social choice theorists suggests the importance.\nFor example, Arrow defined a social welfare function to be \na ``\\emph{process or rule}'' which, for each profile of \nindividual preferences, ``states'' a corresponding social \npreference \\citep[p.~23]{arrow63}, and called the function a \n``\\emph{procedure}'' \\citep[p.~2]{arrow63}. Indeed, he later \nwrote \\citep[p.~S398]{arrow86} in a slightly different context, ``The next \nstep in analysis, I would conjecture, is a more consistent assumption of \n\\emph{computability} in the formulation of economic hypotheses'' (emphasis added).\nSecond, there is a normative reason. Algorithmic \nsocial choice rules specify the procedures in such a way that the same \nresults are obtained irrespective of who carries out a computation, leaving \nno room for personal judgments. In this sense, \ncomputability of social choice rules formalizes the notion of ``due \nprocess.''\\footnote\n\\citet{richter-w99jme} give reasons for studying \ncomputability-based economic theories from the viewpoints of \nbounded rationality, computational economics, and complexity analysis.\nThese reasons partially apply to studying computable rules in social choice.}\n\n\\subsection{Simple games with countably many players}\\label{Intro2}\n\nSimple games have been central to the study of social choice \n\\citep[e.g.,][]{banks95,austensmith-b99,peleg02hbscw}.\n\\emph{Simple games} on an algebra of coalitions of players assign either 0 or~1 to each coalition\n(member of the algebra).\nIn the setting of players who face a yes\/no question, \na coalition intuitively describes those players who vote yes.\nA simple game is characterized by its \\emph{winning} coalitions---those assigned the value~1.\n(The other coalitions are \\emph{losing}.)\nWinning coalitions are understood to be those coalitions whose unanimous votes are decisive.\n\n\nWhen there are only \\emph{finitely} many players, we can construct a finite table listing \nall winning coalitions. Computability is automatically satisfied, since such a table gives an \nalgorithm for computing the game.\nThe same argument does not hold when there are \\emph{infinitely} many players.\nIndeed, some simple games are noncomputable,\nsince there are uncountably many simple games but only countably many computable ones\n (because each computable game is associated with an algorithm).\n \nTaking the ``fixed population'' approach,\\footnote\nThere are two typical approaches to introducing infinite population to a social choice model.\nIn the ``variable population'' approach, \nplayers are potentially infinite, but each problem (or society) involves only finitely many\nplayers. Indeed, well-known schemes, such as simple majority rule, \nunanimity rule, and the Condorcet and the Borda rules, are all algorithms that \napply to problems of any finite size.\n\\citet{kelly88} adopts this approach, giving examples of noncomputable social choice rules.\nIn the ``fixed population'' approach, which we adopt, each problem involves the whole set of \ninfinitely many players. This approach dates back to \\citet{downs57}, who\nconsider continuous voter distributions.\nThe paper by \\citet{banks-dl06} is a recent example of this approach to political theory.} %\nwe consider a fixed infinite set of players in this study of simple games.\nRoughly speaking, a simple game is \\emph{computable} if there is a Turing program (finite algorithm) that can decide\nfrom a description (by integer) of each coalition whether it is winning or losing.\nTo be more precise, we have to be more specific about what we mean by a ``description'' of a coalition.\nThis suggests the following:\nFirst, since each member of a coalition should be describable in words (in English), it is natural to assume that the\nset $N$ of (the names of) players is countable, say, $N=\\mathbb{N}=\\{0,1,2, \\dots \\}$.\nSecond, since one can describe only countably many coalitions, we have to restrict coalitions.\nFinite or cofinite coalitions can be described by listing their members or nonmembers completely.\nBut restricting coalitions to these excludes too many coalitions of interest---such as the set of even numbers.\nA natural solution is to describe coalitions by a Turing program that can decide for the name of each player whether\nshe is in the coalition. Since each Turing program has its code number (G\\\"{o}del number),\nthe coalitions describable in this manner are describable by an integer, as desired.\nOur notion of computability (\\emph{$\\delta$-computability}) focuses on this\nclass of coalitions---\\emph{recursive} coalitions---as well as the method (characteristic index) of describing them.\n\nA fixed population of countably many \\emph{players} arises not only in voting but in other contexts, \nsuch as a special class of multi-criterion decision making---depending on how we interpret a ``player'':\n\\begin{description}\n\\item [Simulating future generations] \nOne may consider countably many \\emph{players} (people) extending into the indefinite future.\n\n\\item [Uncertainty]\nOne may consider finitely many \\emph{persons} facing countably many states of the world~\\citep{mihara97et}:\neach \\emph{player} can be interpreted as a particular \\emph{person} in a particular \\emph{state}.\nThe decision has to be made before a state is realized and identified.\n(This idea is formalized by \\citet{gomberg-mt05}, who introduce\n``$n$-period coalition space,'' where $n$ is the number of persons.)\n\n\\item [Team management]\nPutting the right people (and equipment) in the right places is basic to team management.\\footnote{In line with much of \ncooperative game theory, we put aside the important problems of economics of organization, such as coordinating the\nactivities of the team members by giving the right incentives.}\nTo ensure ``due process'' (which is sometimes called for), can a manager of a company write \na ``manual'' (computable simple game\\footnote{Like \\citet{anderlini-f94}, who view contracts as algorithms, we view ``manuals'' as algorithms. They derive contract incompleteness through computability analysis.}) elaborating the conditions that a team must meet?\n\nFix a particular task such as operating an exclusive agency of the company.%\n\\footnote{Extension to finitely or countably many tasks is straightforward.\nRedefine a \\emph{team} as consisting of members, equipment, \\emph{and} tasks.\nThen introduce a player for each task. \nSince a task can be regarded as a negative input, it will be more natural to assign\n$0$ to those tasks undertaken and $1$ to those not undertaken (think of the monotonicity condition).}\nA \\emph{team} consists of members (people) and equipment.\nThe manager's job is to organize or give a licence to a team that satisfactorily performs the task.\nEach member (or equipment) is described by attributes such as skills, position, availability at a particular time and place (in case of equipment such as a computer, the attributes may be the kind of operating system, the combination of software that may run at the same time, as well as hardware and network specifications).\nEach such \\emph{attribute} can be thought of as a particular yes\/no question, \nand there are countably many such questions.\\footnote{According to a certain approach \\citep[e.g.,][]{gilboa90}\nto modeling scientific inquiry, \na ``state'' is an infinite sequence of $0$'s and $1$'s (answers to countably many questions) \nand a ``theory'' is a Turing program describing a state.\nThis team management example is inspired by this approach in philosophy of science.\nIf we go beyond the realm of social choice, we can indeed find many other interpretations\nhaving a structure similar to this example, such as elaborating the conditions for a certain medicine to take the \ndesired effects and deciding whether a certain act is legal or not.}\n\n\nHere, each \\emph{player} can be interpreted as a particular attribute of a particular member (or equipment).%\n\\footnote{From the viewpoint of ``due process,'' it would be reasonable to define a simple game not for the \nset of (the names of) members but for the set of attributes. \n(This is particularly important where games cannot meet anonymity.) \nConsidering characteristic games for the set of attributes \n(``skills'') can make it easy to express certain allocation problems and give solutions to them \n\\citep[see][]{yokoo-05aaai}.}\nIn other words, each \\emph{coalition} is identified with a $0$-$1$ ``matrix'' of \nfinitely many rows (each row specifying a member) and \ncountably many columns (each column specifying a particular attribute).\\footnote{Since different \nquestions may be interrelated,\nsome ``matrix'' may not make much sense. One might thus want to restrict admissible ``matrices.'' \nThis point is not crucial to our discussion, provided that there are infinitely many \nadmissible ``matrices'' consisting of infinitely many $0$'s and infinitely many $1$'s (in such cases\ncharacteristic indices are the only reasonable way of naming coalitions).}\n\n\\end{description}\n\n\n\\subsection{Overview of the results}\n\n\nAdopting the above notion of computability for simple games, \n\\citet{mihara04mss} gives a sufficient condition and necessary conditions \nfor computability. The sufficient condition \\citep[Proposition~5]{mihara04mss} is intuitively plausible: \nsimple games with a \\emph{finite carrier} (such games are in effect finite, ignoring all except finitely many,\nfixed players' votes) are computable.\nA necessary condition \\citep[Corollary~10]{mihara04mss} in the paper seems to exclude ``nice'' \n(in the voting context) infinite games:\ncomputable simple games have both finite winning coalitions and cofinite losing coalitions.\nHe leaves open the questions (i)~whether there exists a computable simple game that has no finite carrier and\n(ii)~whether there exists a noncomputable simple game that has both finite winning coalitions and cofinite \nlosing coalitions. \nThe first of these questions is particularly important since if the answer were no, then\nonly the games that are in effect finite would be computable, a rather uninteresting result.\nThe answers to these questions (i) and~(ii) are affirmative. \nWe construct examples in Section~\\ref{examples} to show their existence.\nThe construction of these examples depends in essential ways on Proposition~\\ref{cutprop}\n(which gives a necessary condition for a simple game to be computable) or on\nthe easier direction of Theorem~\\ref{delta0det} (which gives a sufficient condition).\nIn contrast, the results in \\citet{mihara04mss} are not useful enough for \nus to construct such examples.\n\n\nTheorem~\\ref{delta0det} gives a necessary and sufficient condition for simple games to be computable.\nThe condition roughly states that ``finitely many, unnecessarily fixed players matter.'' \n\nTo explain the condition, let us introduce the notion of a ``determining string.'' \nGiven a coalition~$S$, its \\emph{$k$-initial segment} is the string of $0$'s and $1$'s of length $k$\nwhose $j$th element (counting from zero) is $1$ if $j\\in S$ and is $0$~if $j\\notin S$. \nFor example, if $S=\\{0,2,4\\}$, \nits $0$-initial segment, $1$-initial segment, \\ldots, $8$-initial segment, \\ldots are, respectively, the empty string,\nthe string~$1$, the string $10$, the string~$101$, the string $1010$, the string $10101$,\nthe string $101010$, the string $1010100$, the string $10101000$, \\ldots.\nWe say that a (finite) string $\\tau$ is \\emph{winning determining} if any coalition~$G$ extending $\\tau$\n(i.e., $\\tau$ is an initial segment of~$G$) is winning. We define \\emph{losing determining} strings similarly.\n\nThe necessary and sufficient condition for computability according to Theorem~\\ref{delta0det}\nis the following: there are computably listable sets \n$T_0$ of losing determining strings and $T_1$ of winning determining strings such that \nany coalition has an initial segment in one of these sets. \nIn the above example, the condition \nimplies that at least one string from among the empty string, $1$, $10$, \\ldots, $10101000$, \n\\ldots is in $T_0$ or in $T_1$---say, $1010$ is in $T_1$.\nThen any coalition of which $0$ and $2$ are members but $1$ or $3$ is not, is winning.\nIn this sense, \\emph{one can determine whether a coalition is winning or losing\nby examining only finitely many players' membership}. \nIn general, however, \\emph{one cannot do so by picking finitely many players before a coalition is given}.\n\nTheorem~\\ref{delta0det} has an interesting implication for the nature of ``manuals'' or ``contracts,'' \nif we regard them as being composed of computable simple games\n (e.g., the team management example in Section~\\ref{Intro2}).\nConsider how many ``criteria'' (players; e.g., member-attribute pairs) are needed for a ``manual'' to determine \nwhether a given ``situation'' (coalition; e.g., team) is ``acceptable'' (winning; e.g., satisfactorily performs a given task).\n\\emph{While increasingly complex situations may require increasingly many criteria, \nno situation (however complex) requires infinitely many criteria.}\nThe conditions (such as ``infinitely many of the prime-numbered criteria must be met'') \nbased on infinitely many criteria are ruled out.\n\nThe proof of Theorem~\\ref{delta0det} uses the \\emph{recursion theorem}.\nIt involves much more intricate arguments of recursion theory\nthan those in \\citet{mihara04mss} giving only a partial characterization of the computable \ngames.\\footnote{Theorem~\\ref{delta0det} can also be derived from results in \\citet{kreisel-ls59}\nand \\citet{ceitin59}. See Remark~\\ref{kreisel59}.}\n\nA natural characterization result might relate computability to well-known properties of simple games, \nsuch as monotonicity, properness, strongness, and nonweakness.\nUnfortunately, we are not likely to obtain such a result: as we clarify in a companion paper~\\citep{kumabe-m06csg64}, \ncomputability is ``unrelated to'' the four properties just mentioned.\n\n\nThe earlier results~\\citep{mihara04mss} are easily obtained from Theorem~\\ref{delta0det}.\nFor example, if a computable game has a winning coalition, then,\nan initial segment of that coalition is winning determining, implying that (Proposition~\\ref{d0neg1cor}) \nthe game has a finite winning coalition and a cofinite winning coalition.\nWe give simple proofs to some of these results in Section~\\ref{applications}.\nIn particular, Proposition~\\ref{nonfinanonymous} strengthens the earlier result \\citep[Corollary~12]{mihara04mss} \nthat computable games violate anonymity.\\footnote\nDetailed studies of anonymous rules based on infinite simple games include\n\\citet{mihara97scw}, \\citet{fey04}, and \\citet{gomberg-mt05}.}\n\n\\subsection{Application to the theory of the core}\n\nMost cooperative game theorists are more interested in the properties of a \\emph{solution} (or value) \nfor games than in the properties of a game itself.\nIn this sense, Section~\\ref{core} deals with more interesting applications of Theorem~\\ref{delta0det}.\n(Most of the section is of independent interest, and can be read without a knowledge of recursion theory.)\n\nTheorem~\\ref{nakamura-thm} is our main contribution to the study of \nacyclic preference aggregation rules in the spirit of \nNakamura's theorem (\\citeyear{nakamura79}) on the core of simple games.\\footnote\n\\citet{banks95}, \\citet{truchon95}, and \\citet{andjiga-m00} are recent contributions\nto this literature.\n(Earlier papers on acyclic rules can be found in \\citet{truchon95} \nand \\citet{austensmith-b99}.)\nMost works in this literature (including those just mentioned) consider finite sets of players.\n\\citet{nakamura79} considers arbitrary (possibly infinite) sets of players and the algebra of all subsets of players.\nIn contrast, we consider arbitrary sets of players and \\emph{arbitrary algebras} of coalitions.}\n\n\nCombining a simple game with a set of alternatives and a profile of individual preferences, we define a \n\\emph{simple game with (ordinal) preferences}.\nNakamura's theorem (\\citeyear{nakamura79}) gives a necessary and sufficient condition for a simple game with\npreferences to have a nonempty core for all profiles: \nthe number of alternatives is below a certain number, called the \\emph{Nakamura number} of the simple game.\nWe extend (Theorem~\\ref{nakamura-thm}) Nakamura's theorem to the framework \nwhere simple games are defined on an arbitrary algebra of coalitions\n(so that not all subsets of players are coalitions).\n\\emph{It turns out that our proof for the generalized result is more elementary than Nakamura's original proof;\nthe latter is more complex than need be.}\n\nSince computable (nonweak) simple games have a finite winning coalition, \nwe can easily prove that they have a finite Nakamura number (Corollary~\\ref{nakamura-finite}).\nTheorem~\\ref{nakamura-thm} in turn implies (Corollary~\\ref{core-nakamura}) that \nif a game is computable, \nthe number of alternatives that the set of players can deal with rationally is restricted by this number.\nWe conclude Section~\\ref{core} with Proposition~\\ref{filter-nakamura}, which suggests the fundamental \ndifficulty of obtaining computable aggregation rules in Arrow's setting (\\citeyear{arrow63}),\neven after relaxing the transitivity requirement for (weak) social preferences.\\footnote\n\\citet{mihara97et,mihara99jme} studies computable aggregation rules \\emph{without} relaxing the\ntransitivity requirement; these papers build on \\citet{armstrong80,armstrong85}, who generalizes\n\\citet{kirman-s72}.}\n\n\n\n\\section{Framework}\n\n\\subsection{Simple games}\\label{notions}\n\nLet $N=\\mathbb{N}=\\{0,1,2, \\dots \\}$ be a countable set of (the names of) \nplayers. Any \\textbf{recursive} (algorithmically decidable) \nsubset of~$N$ is called a \\textbf{(recursive) coalition}.\n\nIntuitively, a simple game describes in a crude manner the power \ndistribution among \\emph{observable} (or describable) subsets of players. Since the cognitive \nability of a human (or machine) is limited, it is not natural to \nassume that all subsets of players are observable when there are \ninfinitely many players. We therefore assume that only \n\\textbf{recursive} subsets are \nobservable. This is a natural assumption in the present context, \nwhere algorithmic properties of simple games are investigated. \nAccording to \\emph{Church's thesis} \\citep[see][]{soare87,odifreddi92}, the recursive coalitions \nare the sets of players for which there is an algorithm that can decide for \nthe name of each player whether she is in the set.\\footnote{\\citet{soare87} and \\citet{odifreddi92}\ngive a more precise definition of \\emph{recursive sets} as well as detailed discussion of recursion theory.\n\\citet{mihara97et,mihara99jme} contain short reviews of recursion theory.}\nNote that \\textbf{the class~$\\mathrm{REC}$ of recursive \ncoalitions} forms a \\textbf{Boolean algebra}; that is, it includes $N$ \nand is closed under union, intersection, and complementation.\n(We assume that observable coalitions are recursive, not just r.e.\\ (\\emph{recursively enumerable}). \n\\citet[Remarks~1 and 16]{mihara04mss} gives three reasons: \nnonrecursive r.e.\\ sets are observable in a very limited sense; \nthe r.e.\\ sets do not form a Boolean algebra;\nno satisfactory notion of computability can be defined if a simple game is \ndefined on the domain of all r.e.\\ sets.)\n\n\nFormally, a \\textbf{(simple) game} is a collection~$\\omega\\subseteq\\mathrm{REC}$ of (recursive) coalitions.\nWe will be explicit when we require that $N\\in \\omega$.\nThe coalitions in $\\omega$ are said to be \\textbf{winning}. \nThe coalitions not in $\\omega$ are said to be \\textbf{losing}. \nOne can regard a simple game as a function from~REC to $\\{0,1\\}$, assigning the value 1 or 0 to each \ncoalition, depending on whether it is winning or losing.\n\nWe introduce from the theory of cooperative games a few basic \nnotions of simple games~\\citep{peleg02hbscw,weber94}.\\footnote{The desirability of these properties depends, \nof course, on the context. Consider the team management example in Section~\\ref{Intro2}, for example.\nMonotonicity makes sense, but may be too optimistic (adding a member may turn an acceptable team into an\nunacceptable one). Properness may be irrelevant or even undesirable \n(ensuring that a given task can be performed by \ntwo non-overlapping teams may be important from the viewpoint of reliability).\nThis observation does not diminish the contribution of the main theorem (Theorem~\\ref{delta0det}),\nwhich does not refer to these properties.\nIn fact, one can show~\\citep{kumabe-m06csg64}\n that computability is ``unrelated to'' monotonicity, properness, strongness, and weakness.}\nA simple game $\\omega$ is said to be \n\\textbf{monotonic} if for all coalitions $S$ and $T$, the \nconditions $S\\in \\omega$ and $T\\supseteq S$ imply $T\\in\\omega$. \n$\\omega$ is \\textbf{proper} if for all recursive coalitions~$S$, \n$S\\in\\omega$ implies $S^c:=N\\setminus S\\notin\\omega$. $\\omega$ is \n\\textbf{strong} if for all coalitions~$S$, $S\\notin\\omega$ \nimplies $S^c\\in\\omega$. $\\omega$ is \\textbf{weak} if \n$\\omega=\\emptyset$ or\nthe intersection~$\\bigcap\\omega=\\bigcap_{S\\in\\omega}S$ of the winning coalitions is nonempty. \nThe members of $\\bigcap\\omega$ are called \\textbf{veto players}; they \nare the players that belong to all winning coalitions. \n(The set $\\bigcap\\omega$ of veto players may or may not be observable.)\n$\\omega$ is \\textbf{dictatorial} if there exists some~$i_0$ (called a \n\\textbf{dictator}) in~$N$ such that $\\omega=\\{\\,S\\in\\mathrm{REC}: i_0\\in \nS\\,\\}$. Note that a dictator is a veto player, but a veto player is \nnot necessarily a dictator.\n\nWe say that a simple game $\\omega$ is \\textbf{finitely anonymous} if for any finite permutation $\\pi: N\\to N$ \n(which permutes only finitely many players) and for \nany coalition $S$, we have \n$S\\in \\omega \\iff \\pi(S) \\in \\omega$. \nIn particular, finitely anonymous games treat any two coalitions with the same finite number of players equally.\nFinite anonymity is a notion much weaker than \nthe version of anonymity that allows any (measurable) permutation $\\pi: N\\to N$.\nFor example, free ultrafilters (nondictatorial ultrafilters) defined below are finitely anonymous. \n\nA \\textbf{carrier} of a simple game~$\\omega$ is a coalition $S\\subset N$ \nsuch that\n\\[ \nT\\in\\omega \\iff S\\cap T\\in \\omega\n\\]\nfor all coalitions~$T$.\nWe observe that if $S$ is a carrier, then so is any coalition $S'\\supseteq S$.\n\nFinally, we introduce a few notions from the theory of Boolean \nalgebras~\\citep{koppelberg89}; they can be regarded as properties of \nsimple games. \nA monotonic simple game~$\\omega$ satisfying\n$N\\in \\omega$ and $\\emptyset\\notin\\omega$\nis called a \\textbf{prefilter} if it has the finite intersection property:\nif $\\omega'\\subseteq \\omega$ is finite, then $\\bigcap\\omega'\\neq \\emptyset$.\nIntuitively, a prefilter consists of ``large'' coalitions.\nA prefilter is \\textbf{free} if and only if it is nonweak (i.e., it has no veto players).\nA free prefilter does not contain any finite coalitions (Lemma~\\ref{nakamura-ceiling}).\nA prefilter~$\\omega$ is a \\textbf{filter} if it is closed with respect to finite intersection: \nif $S$, $S'\\in\\omega$, then $S\\cap S'\\in \\omega$.\nThe \\textbf{principal filter generated by $S$} is\n$\\omega=\\{T\\in \\mathrm{REC}: S\\subseteq T\\}$. It is a typical example of a filter that is\nnot free; it has a carrier, namely, $S$. A filter is a \\textbf{principal filter} if it is \nthe principal filter generated by some~$S$.\nA filter~$\\omega$ is called an \\textbf{ultrafilter} if it is a \nstrong simple game. If $\\omega$ is an ultrafilter, then $S\\cup \nS'\\in\\omega$ implies that $S\\in\\omega$ or $S'\\in\\omega$.\nAn ultrafilter is free if and only if it is not dictatorial.\n\n\\subsection{An indicator for simple games}\\label{indicators}\n\nTo define the notion of computability for simple games, we introduce below \nan indicator for them. In order to do that, \nwe first represent each recursive coalition by a characteristic index ($\\Delta_0$-index).\nHere, a number $e$~is a \\textbf{characteristic index} for a coalition~$S$\nif $\\varphi_e$ (the partial function computed by the Turing program with code number~$e$)\nis the characteristic function for~$S$. \nIntuitively, a characteristic index for a coalition describes\nthe coalition by a Turing program that can decide its membership.\nThe indicator then assigns the value 0 or 1 to each \nnumber representing a coalition, depending on whether the \ncoalition is winning or losing. When a number does not represent a \nrecursive coalition, the value is undefined.\n\nGiven a simple game $\\omega$, its \\textbf{$\\delta$-indicator} is the partial \nfunction~$\\delta_\\omega$ on~$\\mathbb{N}$ defined by\n\\begin{equation}\n\t\\label{d:eq}\n\t\\delta_\\omega(e)=\\left\\{\n\t \\begin{array}{ll}\n\t\t1 & \\mbox{if $e$ is a characteristic index for a recursive\n\tset in $\\omega$}, \\\\\n\t\t0 & \\mbox{if $e$ is a characteristic index for a recursive\n\tset not in $\\omega$}, \\\\\n\t\t\\uparrow & \\mbox{if $e$ is not a characteristic\n\tindex for any recursive set}.\n\t\\end{array}\n\t\\right.\n\\end{equation}\nNote that $\\delta_\\omega$ is well-defined since each $e\\in\\mathbb{N}$ can be a \ncharacteristic index for at most one set.\n\n\\subsection{The computability notion}\n\\label{comp:notions}\n\nWe now introduce the notion of \\emph{$\\delta$-computable} simple games.\nWe start by giving a scenario or intuition underlying the notion of $\\delta$-computability.\nA number (characteristic index) representing a coalition\n(equivalently, a Turing program that can decide the membership of a coalition)\nis presented by an inquirer to the aggregator (planner), \nwho will compute whether the coalition is winning or not.\nThough there is no effective (algorithmic) procedure to decide whether a number given by the \ninquirer is legitimate (i.e., represents some recursive coalition),\na human can often check manually (non-algorithmically) if such a number is a legitimate representation.\nWe assume that the inquirer gives the aggregator only those indices that he has checked and proved its legitimacy.\nThis assumption is justified if we assume that the aggregator always demands such proofs.\nThe aggregator, however, cannot know a priori which indices will possibly be presented to her.\n(There are, of course, indices unlikely to be used by humans. \nBut the aggregator cannot a priori rule out some of the indices.)\nSo, \\emph{the aggregator should be ready to compute whenever a legitimate representation\n is presented to her}.\\footnote\nAn alternative notion of computability might use a ``multiple-choice format,''\n in which the aggregator gives possible indices that the inquirer can choose from. \nUnfortunately, such a ``multiple-choice format'' would not work as one might wish\n\\citep[Appendix~A.1]{kumabe-m07csgcc}.} \nThis intuition justifies the following condition of computability.\\footnote\n\\citet{mihara04mss} also proposes a stronger condition, \\emph{$\\sigma$-computability}.\nWe discard that condition since it is too strong a notion of computability (Proposition~3 of that paper;\nfor example, even \\emph{dictatorial} games are not $\\sigma$-computable).} %\n\n\\begin{description} \\item[$\\delta$-computability] $\\delta_\\omega$ has \nan extension to a partial recursive function. \n\\end{description}\n\nInstead of, say, $\\delta$-computability, one might want to require the indicator~$\\delta_\\omega$ \\emph{itself} \n(or its extension that gives a number different from $0$ or~$1$ whenever $\\delta_\\omega(e)$ is undefined)\nto be partial recursive \\citep[Appendix~A]{mihara04mss}. \nSuch a condition cannot be satisfied, however, since the domain of~$\\delta_\\omega$ is\nnot r.e. \\citep[Lemma~2]{mihara97et}.\n\n\\section{A Characterization Result}\\label{mainresult}\n\n\n\\subsection{Determining strings}\n\nThe next lemma states that for any coalition~$S$ of a \n$\\delta$-computable simple game, \nthere is a cutting number~$k$ such \nthat any \\emph{finite} coalition~$G$ having the same $k$-players \nas~$S$ (that is, $G$ and $S$ are equal if players~$i\\geq k$ are \nignored) is winning (losing) if $S$ is winning (losing). Note that \nif $k$ is such a cutting number, then so is any $k'$ greater than~$k$.\n\n\\medskip\n\n\\textbf{Notation}. We identify a natural number~$k$ with the finite \nset $\\{0,1,2,\\ldots,k-1\\}$, which is an initial segment of~$\\mathbb{N}$. \nGiven a coalition $S\\subseteq N$, we write $S\\cap k$ to represent the \ncoalition $\\{i\\in S: iz$.} %\nNote that if $(e,y)\\in Q_1$, then \n$s_0=s_0(y)$ is defined and $\\delta'_{s_0}(y)\\in \\{0,1\\}$. We can \neasily check that $Q_1$ is r.e. Given $(e,y)\\in Q_1$, let $s_1$ be the \nleast $s'\\geq s_0$ such that conditions (ii.a) and (ii.b) hold for \nsome $e'\\in\\mathbf{F}_{s'}$. Let $e_0$ be the least $e'\\in\\mathbf{F}_{s'}$ such that \nconditions (ii.a) and (ii.b) hold for $s'=s_1$. We can view $e_0$ as \na p.r.\\ function $e_0(e,y)$, which converges for $(e,y)\\in Q_1$.\n\nDefine a partial function~$\\psi$ by \n\\[\n\\psi(e,y,z) =\\left\\{ \n\t\\begin{array}{ll}\n\t\t\\varphi_{e_0}(z) & \\mbox{if $y\\in Q_0$ and $(e,y)\\in Q_1$},\\\\\n\t\t\\varphi_{e,s_0-1}(z) & \\mbox{if $y\\in Q_0$ and $(e,y)\\notin Q_1$},\\\\\n\t\t\\varphi_e(z) & \\mbox{if $y\\notin Q_0$}.\n\t\\end{array}\n\t\\right.\n\\]\n\n\\begin{lemma}\n$\\psi$ is p.r.\n\\end{lemma}\n\n\\begin{subproof}\nWe show there is a sequence of p.r.\\ functions~$\\psi^s$\nsuch that $\\psi=\\bigcup_s \\psi^s$. We then apply the Graph Theorem to conclude $\\psi$ is p.r.\n\n\\medskip\n\nFor each $s\\in \\mathbb{N}$, define a recursive set $Q_0^s\\subseteq\\mathbb{N}$ by\n$y\\in Q_0^s$ iff there exists~$s'\\leq s$ such that\n$\\delta'_{s'}(y)=0$ or $\\delta'_{s'}(y)=1$. We have $y\\in Q_0$ iff $y\\in Q_0^s$ for some~$s$.\nNote that if $y\\in Q_0^s$, then $s\\ge s_0=s_0(y)$.\n\nFor each $s\\in \\mathbb{N}$, define a recursive set $Q_1^s\\subseteq\\mathbb{N}\\times\\mathbb{N}$ by \n$(e,y)\\in Q_1^s$ iff (i)~$y\\in Q_0^s$ and \n(ii)~there exist $s'$ such that $s_0:=s_0(y)\\le s' \\le s$ and $e'\\in\\mathbf{F}_{s'}$ such \nthat (ii.a)~$\\delta'_{s'}(e')=1-\\delta'_{s_0}(y)$ and that \n(ii.b)~$\\varphi_{e',s'}$ is an extension of $\\varphi_{e,s_0-1}$. \n(Conditions (ii.a) and~(ii.b) are the same as those in the definition of~$Q_1$.)\nWe have $(e,y)\\in Q_1$ iff $(e,y)\\in Q_1^s$ for some $s$.\nNote that if $(e,y)\\in Q_1^s$, then $s_0\\le s_1 \\le s$.\n\nFor each $s\\in \\mathbb{N}$, define a p.r.\\ function~$\\psi^s$ by \n\\[\n\\psi^s(e,y,z) =\\left\\{ \n\t\\begin{array}{ll}\n\t\t\\varphi_{e_0,s}(z) & \\mbox{if $y\\in Q_0^s$ and $(e,y)\\in Q_1^s$},\\\\\n\t\t\\varphi_{e,s_0-1}(z) & \\mbox{if $y\\in Q_0^s$ and $(e,y)\\notin Q_1^s$},\\\\\n\t\t\\varphi_{e,s}(z) & \\mbox{if $y\\notin Q_0^s$}.\n\t\\end{array}\n\t\\right.\n\\]\n\n\\emph{We claim that $\\bigcup_s \\psi^s$ is a partial function \n(i.e., $\\bigcup_s \\psi^s(e,y,z)$ does not take more than one value)\nand that $\\psi=\\bigcup_s \\psi^s$}:\n\n\\begin{itemize}\n\\item Suppose $y\\notin Q_0$. Then $y\\notin Q_0^s$ for any~$s$. So, for all $s$, $\\psi^s(e,y,z)=\\varphi_{e,s}(z)$.\nHence $\\bigcup_s \\psi^s(e,y,z)=\\varphi_{e}(z)=\\psi(e,y,z)$ as desired.\n\n\\item Suppose ($y\\in Q_0$ and) $(e,y)\\in Q_1$. Then $s_0$, $s_1$, and $e_0$ are defined and $s_1\\ge s_0$.\nIf $s1$, it is nonweak, but any finite intersection of winning coalitions is nonempty\n (i.e., has an infinite Nakamura number, to be defined in Section~\\ref{core}).\nNote that if $1\\#X$.\n\nThe following useful lemma \\citep[Lemma~2.1]{nakamura79} states that the Nakamura number of\na $\\mathcal{B}$-simple game cannot exceed the size of a winning coalition by more than one.\n\n\\begin{lemma}\\label{nakamura-ceiling}\nLet $\\omega$ be a nonweak $\\mathcal{B}$-simple game. \nThen $\\nu(\\omega)\\leq \\min \\{\\#S: S\\in\\omega\\}+1$.\n\\end{lemma}\n\n\\begin{proof}\nChoose a coalition $S\\in \\omega$ such that $\\#S=\\min \\{\\#S: S\\in\\omega\\}$.\nSince $\\bigcap\\omega=\\emptyset$, for each $i\\in S$, there is some $S^i\\in \\omega$ with $i\\notin S^i$.\nSo, $S\\cap (\\bigcap_{i\\in S} S^i)=\\emptyset$. Therefore, $\\nu(\\omega)\\leq \\#S+1$.\\end{proof}\n\nIt is easy to prove \\citep[Corollary~2.2]{nakamura79} that the Nakamura number of a nonweak $\\mathcal{B}$-simple game is at \nmost equal to the cardinal number~$\\#N$ of the set of players and that this maximum is attainable if $\\mathcal{B}$ \ncontains all finite coalitions.\nIn fact, one can easily construct a computable, nonweak simple game with any given Nakamura number:\n\n\\begin{prop}\\label{nakamura-any}\nFor any integer $k\\geq 2$, there exists a $\\delta$-computable, nonweak simple game~$\\omega$\nwith Nakamura number $\\nu(\\omega)=k$.\n\\end{prop}\n\n\\begin{proof}\nGiven an integer $k\\geq 2$, \nlet $S=\\{0,1, \\ldots, k-1\\}$ be a carrier and define $T\\in \\omega$ iff $\\#(S\\cap T) \\geq k-1$. \nThen $\\nu(\\omega)=k$.\\end{proof}\n\nSince computable, nonweak simple games have winning coalitions, \nit has \\emph{finite} winning coalitions by Proposition~\\ref{d0neg1cor}.\nAn immediate corollary of Lemma~\\ref{nakamura-ceiling} is the following:\n\\begin{cor}\\label{nakamura-finite}\nLet $\\omega$ be a $\\delta$-computable, nonweak simple game. \nThen its Nakamura number~$\\nu(\\omega)$ is finite.\n\\end{cor}\n\n\\citet{nakamura79} proves the following theorem for $\\mathcal{B}=2^{N'}$:\n\n\\begin{theorem} \\label{nakamura-thm}\nLet $\\mathcal{B}$ be a Boolean algebra of sets of $N'$.\nSuppose that $\\emptyset \\notin \\omega$ and $\\omega\\neq \\emptyset$.\nThen the core $C(\\omega, X, \\mathbf{p})$ of a $\\mathcal{B}$-simple game $(\\omega, X, \\mathbf{p})$ with preferences is nonempty for all (measurable) profiles $\\mathbf{p}\\in \\A^{N'}_\\B$\nif and only if $X$ is finite and $\\#X<\\nu(\\omega)$.\\end{theorem}\n\n\\begin{remark}\nAt first glance, Nakamura's proof \\citep[Theorem~2.3]{nakamura79} of the necessary condition~$\\#X<\\nu(\\omega)$,\ndoes not appear to generalize to an arbitrary Boolean algebra~$\\mathcal{B}$:\nhe constructs certain coalitions from winning coalitions by taking possibly\n\\emph{infinite unions and intersections}, as well as complements;\na difficulty is that the resulting set of players may not belong to the Boolean algebra~$\\mathcal{B}$.\nHowever, it turns out that once we make use of the other necessary condition \n(disregarded by Nakamura) that $X$~is finite, \nwe only need to consider \\emph{finite} unions and intersections, and his proof actually works.\nSince accessible proofs are readily available in the literature \\citep[e.g.,][Theorem~3.2]{austensmith-b99}\nfor $\\mathcal{B}=2^{N'}$ and finite sets~$N'$ of players, we choose to relegate the proof to\nthe working paper \\citep[Appendix~A.3]{kumabe-m07csgcc}. \nUnlike others', our proof treats the \\emph{measurability} condition ($\\mathbf{p}\\in \\A^{N'}_\\B$) particularly carefully.\\end{remark}\n\nIt follows from Theorem~\\ref{nakamura-thm} that if a $\\mathcal{B}$-simple game $\\omega$ is \\emph{weak} \n(and satisfies $\\emptyset \\notin \\omega$ and $\\omega\\neq \\emptyset$), \nthen the core $C(\\omega, X, \\mathbf{p})$ is nonempty for all profiles $\\mathbf{p}\\in \\A^{N'}_\\B$ \nif and only if $X$~is finite.\nThe more interesting case is where $\\omega$ is nonweak.\nCombined with Corollary~\\ref{nakamura-finite}, Theorem~\\ref{nakamura-thm} has a consequence\nfor nonweak, computable simple games:\n\n\\begin{cor}\\label{core-nakamura}\nLet $\\omega$ be a $\\delta$-computable, nonweak simple game satisfying\n$\\emptyset \\notin \\omega$.\nThen there exists a finite number $\\nu$ (the Nakamura number~$\\nu(\\omega)$) such that\nthe core $C(\\omega, X, \\mathbf{p})$ is nonempty for all profiles $\\mathbf{p}\\in \\mathcal{A}^{N}_\\mathrm{REC}$\nif and only if $\\#X<\\nu$.\\end{cor}\n\nIf we drop the computability condition, the above conclusion no longer holds.\nAn example of $\\omega$ that has no such restriction on the size of the set~$X$ of alternatives\nis a nonweak prefilter (e.g., the $q$-complement rule of Example~\\ref{q-compl}, for $q>1$),\nwhich has an infinite Nakamura number.\n\nIn fact, we can say more, if we shift our attention from the core---the set of undominated \nalternatives with respect to the dominance relation~$\\succ^\\mathbf{p}_\\omega$---to the \ndominance relation itself. \n(The proof of the following proposition is in the working paper \\citep[Appendix~A.4]{kumabe-m07csgcc}.)\n\n\\begin{prop}\\label{filter-nakamura}\nLet $\\omega$ be a nonweak simple game\nsatisfying $\\emptyset \\notin \\omega$.\n\\textup{(i)}~$\\omega$ cannot be a $\\delta$-computable prefilter.\n\\textup{(ii)}~If $\\omega$ is $\\delta$-computable; then $\\nu(\\omega)$ is finite, and\n$\\succ^\\mathbf{p}_\\omega$ is acyclic for all $\\mathbf{p}\\in\\mathcal{A}^N_\\mathrm{REC}$ if and only if $\\#X<\\nu(\\omega)$.\n\\textup{(iii)}~If $\\omega$ is a prefilter,\nthen $\\succ^\\mathbf{p}_\\omega$ is acyclic for all $\\mathbf{p}\\in\\mathcal{A}^N_\\mathrm{REC}$, regardless \nof the cardinal number $\\#X$ of~$X$.\\end{prop}\n\n\n\nWe can strengthen the acyclicity of the dominance relation~$\\succ^\\mathbf{p}_\\omega$ in statement~(iii)\nof Proposition~\\ref{filter-nakamura} by replacing the statement with one of the following:\n(iv)~if $\\omega$ is a \\emph{filter},\nthen $\\succ^\\mathbf{p}_\\omega$ is transitive for all $\\mathbf{p}$ such that all individuals have transitive preferences~$\\succ_i^\\p$;\n(v)~if $\\omega$ is an \\emph{ultrafilter},\nthen $\\succ^\\mathbf{p}_\\omega$ is asymmetric and negatively transitive for all $\\mathbf{p}$ \nsuch that all individuals have asymmetric, negatively transitive preferences~$\\succ_i^\\p$.\nIn fact, statements (iii), (iv), and (v) each gives an aggregation rule $\\succ_\\omega\\colon \\mathbf{p}\\mapsto \\, \\succ^\\mathbf{p}$ that satisfies Arrow's conditions of ``Unanimity'' and ``Independence of irrelevant alternatives.''\nThese results are immediate from the relevant definitions \n(\\citet[Proposition~3.2]{armstrong80} gives a proof).\nAccording to Arrow's Theorem (\\citeyear{arrow63}), however, if the set $N$ of players were \nreplaced by a \\emph{finite} set, then social welfare functions given by statement~(v) \nwould be dictatorial (and $\\omega$ would be weak).\n\nIn an attempt to escape from Arrow's impossibility, many authors have investigated the consequences of\nrelaxing the rationality requirement (negative transitivity of $\\succ^\\mathbf{p}_\\omega$)\nfor social preferences.\nIn view of the close connection \\citep[Theorems 2.6 and 2.7]{austensmith-b99} \nbetween the rationality properties of an aggregation rule and preflters \n\\citep[also][]{kirman-s72,armstrong80,armstrong85},\nProposition~\\ref{filter-nakamura} has a significant implication for this investigation.\n\n\n\\section{Examples}\\label{examples}\n\nPropositions~\\ref{d0pos}, \\ref{d0neg1cor}, and \\ref{d0neg2cor} show that the class of computable games\n(i)~includes the class of games that have finite carriers and \n(ii)~is included in the class of games that have both finite winning coalitions and cofinite losing coalitions.\nIn this section, we construct examples showing that these inclusions are strict.\n\nWe can find such examples without sacrificing the voting-theoretically desirable properties of simple games.\nWe pursue this task thoroughly in a companion paper~\\citep{kumabe-m06csg64}.\nThe \\emph{noncomputable} simple game example in Section \\ref{ex:noncomp} \nthat has both finite winning coalitions and cofinite losing coalitions is a sample of that work.\nIt is monotonic, proper, strong, and nonweak.\nExamples of a \\emph{computable} simple game that is monotonic, proper, strong, nonweak, \nand has no finite carrier is given in \\citet{kumabe-m06csg64,kumabe-m07nc}.\n\n\n\\subsection{A noncomputable game with finite winning coalitions} \n\\label{ex:noncomp}\n\nWe exhibit here a noncomputable simple game\nthat is monotonic, proper, strong, nonweak, \nand have both finite winning coalitions and cofinite losing coalitions.\nIt shows in particular that the class of computable games is strictly smaller than the class \n of games that have both finite winning coalitions and cofinite losing coalitions.\nIn this respect, the game is unlike nonweak prefilters\n(such as the $q$-complement rules in Example~\\ref{q-compl}); \nthose examples do not have any finite winning coalitions.\nFurthermore, unlike nonprincipal ultrafilters---which are also \nmonotonic, proper, strong, and nonweak noncomputable simple games---the \ngame is nonweak in a stronger sense: it violates the finite intersection property.\n\n\nLet $A=N\\setminus \\{0\\}=\\{1,2,3,\\ldots\\}$. We define the simple game~$\\omega$ as follows:\nAny coalition except $A^c=\\{0\\}$ extending the string 1 of length~1 (i.e., any coalition containing~0) is winning; \nany coalition except $A$ extending the string 0 is losing; $A$ is winning and $A^c$ is losing.\nIn other words, for all $S\\in \\mathrm{REC}$,\n\\[ \nS\\in \\omega \\iff [\\textrm{$S=A$ or ($0\\in S$ \\& $S\\neq A^c$)}].\n\\]\n\n\\begin{remark}\nThe reader familiar with the notion of repeated games (or binary rooted trees) may find the following visualization helpful.\nThink of the extensive form of an infinitely repeated game played by you, \nwith the stage game consisting of two moves 0 and~1. \nIf you choose~1 in the first stage, you will win unless you keep choosing 0 indefinitely thereafter; \nif you choose~0 in the first stage, you will lose unless you keep choosing 1 indefinitely thereafter.\nNow, you ``represent'' a certain coalition and play 1 in stage $i$ if $i$ is in the coalition; \nyou play~0 in that stage otherwise.\nThen the coalition that you represent is winning if you win; it is losing if you lose.\n\\end{remark}\n\n\\begin{lemma}\n$\\omega$ is not $\\delta$-computable.\n\\end{lemma}\n\nThe following proof demonstrates the power of Theorem~\\ref{delta0det},\nalthough its full force is not used (Proposition~\\ref{cutprop} suffices).\nProposition~\\ref{d0neg1}, which appeared earlier in \\citet{mihara04mss}, does not have this power.\n\n\\bigskip\n\n\\begin{proof}\nIf $\\omega$ is $\\delta$-computable, then by Theorem~\\ref{delta0det} (or by Proposition~\\ref{cutprop}),\n$A$ has an initial segment $A\\cap k$ that is a winning determining string.\nBut $A\\cap k$ itself is not winning (though it extends the string trivially).\n\\end{proof}\n\n\\begin{lemma}\n$\\omega$ has both finite winning coalitions and cofinite losing coalitions.\n\\end{lemma}\n\n\\begin{proof}\nFor instance, $\\{0,1\\}$ is finite and winning.\n$N\\setminus \\{0,1\\}=\\{2, 3, 4, \\ldots\\}$ is cofinite and losing.\n\\end{proof}\n\n\\begin{lemma}\n$\\omega$ is monotonic.\n\\end{lemma}\n\n\\begin{proof}\nSuppose $S\\in \\omega$ and $S\\subsetneq T$. There are two possibilities.\nIf $S=A$, then $T=N$, and we have $N\\in \\omega$ by the definition of $\\omega$.\nOtherwise, $S$ contains 0 and some other number $i$. The same is true of $T$, \nimplying that $T\\in \\omega$.\n\\end{proof}\n\n\\begin{lemma}\n$\\omega$ is proper and strong.\n\\end{lemma}\n\n\\begin{proof}\nIt suffices to show that $S^c\\in\\omega \\iff S\\notin\\omega$.\nFrom the definition of $\\omega$, we have\n\\begin{eqnarray*}\nS \\notin\\omega & \\iff & \\textrm{$S\\neq A$ \\& ($0\\notin S$ or $S=A^c$)} \\\\\n\t\t\t\t\t\t& \\iff & \\textrm{$S^c \\neq A^c$ \\& ($0\\in S^c$ or $S^c= A$)} \\\\\n\t\t\t\t\t\t& \\iff & \\textrm{($0\\in S^c$ \\& $S^c \\neq A^c$) or $S^c= A$} \\\\\n\t\t\t\t\t\t& \\iff & S^c\\in\\omega.\n\\end{eqnarray*}\\end{proof}\n\n\\begin{lemma}\n$\\omega$ is not a prefilter. In particular, it is not weak. \n\\end{lemma}\n\n\\begin{proof}\nWe show that the intersection of some finite family of winning coalitions is empty.\nThe coalitions $\\{0,1\\}$, $\\{0,2\\}$, and~$A$ form such a family.\n(Incidentally, this shows that the Nakamura number of $\\omega$ is three, since $\\omega$ is proper.)\\end{proof}\n \n\n\n\\subsection{A computable game without a finite carrier}\\label{ex:nocarrier}\n\n\nWe exhibit here a computable simple game that does not have a finite carrier. \nIt shows that the class of computable games is strictly larger than \nthe class of games that have finite carriers.\n\nOur approach is to construct r.e.\\ (in fact, recursive) sets $T_0$ and $T_1$ \nof determining strings (of 0's and 1's) satisfying the conditions of Theorem~\\ref{delta0det} \n(the full force of the theorem is not needed; the easier direction suffices).\nWe first give a condition that any string in $T_0\\cup T_1$ must satisfy. \nWe then specify each of $T_0$ and $T_1$, and construct the simple game by means of these sets.\nWe conclude that the game is computable by checking (Lemmas~\\ref{ex:nocarrier-rec}, \\ref{ex:nocarrier-string1},\nand \\ref{ex:nocarrier-det}) \nthat $T_0$ and $T_1$ satisfy the conditions of the theorem.\nFinally, we show (Lemma~\\ref{ex:nocarrier-none}) that the game does not have a finite carrier.\n\n\\bigskip\n\nLet $\\{k_s\\}_{s=0}^\\infty$ be an effective listing (recursive enumeration) of the members of \nthe r.e.\\ set $\\{k : \\varphi_k(k)\\in \\{0,1\\}\\}$, \nwhere $\\varphi_k(\\cdot)$ is the $k$th p.r.\\ function of one variable.\nWe can assume that all elements $k_s$ are distinct.\n(Such a listing $\\{k_s\\}_{s=0}^\\infty$ exists by the Listing Theorem~\\citep[Theorem~II.1.8 and Exercise II.1.20]{soare87}.)\nThus, \n\\[ \\mathrm{CRec} \\subset \\{k : \\varphi_k(k)\\in \\{0,1\\}\\} = \\{k_0, k_1, k_2, \\ldots\\}, \\]\nwhere $\\mathrm{CRec}$ is the set of characteristic indices for recursive sets.\n\nLet $l_{0}=k_0+1$, and for $s>0$, let $l_{s}=\\max \\{l_{s-1}, k_{s}+1\\}$.\nWe have $l_s\\geq l_{s-1}$ (that is, $\\{l_s\\}$ is an nondecreasing sequence of numbers) and \n$l_s>k_s$ for each $s$. Note also that $l_s\\geq l_{s-1}>k_{s-1}$, and $l_s\\geq l_{s-2}>k_{s-2}$, etc.\\ \nimply that $l_s> k_s$, $k_{s-1}$, $k_{s-2}$, \\ldots.\n\nFor each $s$, let $F_s$ be the set of strings $\\alpha=\\alpha(0)\\alpha(1)\\cdots\\alpha(l_s-1)$ \n(the *'s denoting the concatenation are omitted)\nof length $l_s$ such that \n\\begin{equation} \\label{ex:nocarrier1}\n\\textrm{$\\alpha(k_{s})=\\varphi_{k_{s}}(k_{s})$ and for each $s's$ and \nno constraints on $\\alpha(k)$ for $k\\notin\\{k_0,k_1,k_2, \\ldots\\}$, \nwhile it imposes real constraints for $s'\\leq s$,\nsince $|\\alpha|=l_s> k_{s'}$ for such $s'$.\nWe observe that if $\\alpha\\in F_s\\cap F_{s'}$, then $s=s'$.\n \nLet $F=\\bigcup_{s}F_s$. ($F$ will be the union of $T_0$ and $T_1$ defined below.)\nWe claim that for any two distinct elements $\\alpha$ and $\\beta$ in $F$\nwe have neither $\\alpha\\subseteq \\beta$ ($\\alpha$ is an initial segment of~$\\beta$)\nnor $\\beta\\subseteq\\alpha$ \n(i.e., there is $k< \\min\\{|\\alpha|,|\\beta|\\}$ such that $\\alpha(k)\\neq \\beta(k)$).\n To see this, let $|\\alpha|\\leq |\\beta|$, without loss of generality. \n If $\\alpha$ and $\\beta$ have the same length, then the \n conclusion follows since otherwise they become identical strings.\n If $l_s=|\\alpha|< |\\beta|=l_{s'}$, then $s |\\sigma|$, then $\\sigma\\notin F_s$.\nSince $l_s$ is nondecreasing in $s$ and $F_s$ consists of strings of length~$l_s$, \nit follows that $\\sigma\\notin F$, implying $\\sigma\\notin T_0$.\n\nIf $l_s= |\\sigma|$, then check whether $\\sigma \\in F_s$; this can be \ndone since the values of $\\varphi_{k_{s'}}(k_{s'})$ for $s'\\leq s$ in (\\ref{ex:nocarrier1})\nare available and $F_s$ determined by time $s$.\nIf $\\sigma\\notin F_s$ and $l_{s+1}>l_s$, then $\\sigma \\notin T_0$ as before.\nOtherwise check whether $\\sigma \\in F_{s+1}$. \nIf $\\sigma \\notin F_{s+1}$ and $l_{s+2}>l_{s+1}=l_s$, then $\\sigma \\notin T_0$ as before.\nRepeating this process, we either get $\\sigma\\in F_{s'}$ for some $s'$ or \n$\\sigma\\notin F_{s'}$ for all $s'\\in \\{s': l_{s'}=l_s\\}$.\nIn the latter case, we have $\\sigma \\notin T_0$.\nIn the former case, if $\\sigma(k_{s'})=\\varphi_{k_{s'}}(k_{s'})=1$, \nthen $\\sigma \\in T_1$ by the definition of $T_1$; hence it is not in $T_0$.\nOtherwise $\\sigma(k_{s'})=\\varphi_{k_{s'}}(k_{s'})=0$, \nand we have $\\sigma \\in T_0$.\\end{proof}\n\n\\begin{lemma}\\label{ex:nocarrier-string1}\n$T_1$ consists only of winning determining strings for $\\omega$;\n$T_0$ consists only of losing determining strings for $\\omega$.\n\\end{lemma}\n\n\\begin{proof}\nLet $\\alpha\\in T_1$. If a coalition~$S$ extends $\\alpha$, then by the definition of~$\\omega$,\n$S$~is winning. This proves that $\\alpha$~is a winning determining string.\n\nLet $\\alpha\\in T_0$. Suppose a coalition~$S$ extends $\\alpha\\in T_0\\subset T_0\\cup T_1=F$.\nIf $\\beta\\in F$ and $\\beta\\neq \\alpha$, \nwe have, as shown before, $\\alpha \\not \\subseteq \\beta$ and $\\beta\\not \\subseteq\\alpha$,\nwhich implies that $S$~does not extend~$\\beta$. So, in particular, $S$ does not extend any\nstring in~$T_1$. It follows from the definition of~$\\omega$ that $S$~is losing.\nThis proves that $\\alpha$~is a losing determining string.\\end{proof}\n\n\\begin{lemma} \\label{ex:nocarrier-string}\nFor each $s$, any string $\\alpha$ of length $l_s$ such that $\\alpha(k_s)=\\varphi_{k_s}(k_s)$ \nextends a string in $\\bigcup_{t\\leq s}F_t$.\n\\end{lemma}\n\n\\begin{proof}\nWe proceed by induction on $s$.\nLet $\\alpha$ be a string of length $l_s$ such that $\\alpha(k_s)=\\varphi_{k_s}(k_s)$. \nIf $s=0$, we have $\\alpha\\in F_0$; hence the lemma holds for $s=0$. \nSuppose the lemma holds for $s'0$ and $i \\in \\{0,1\\}$, there is an $s>s'$ such that $k_s> l_{s'}$ and $\\varphi_{k_s}(k_s)=i$.\n\nFor a temporarily chosen $s'$, fix $i$ and fix such $s$. Then choose the greatest $s'$ satisfying these conditions.\nSince $l_s>k_s>l_{s'}$, there is a string $\\alpha$ of length~$l_s$ extending (as a string) $A\\cap l_{s'}$ \nsuch that $\\alpha\\in F_s$. \nSince $\\alpha(k_s)=\\varphi_{k_s}(k_s)=i$, we have $\\alpha\\in T_i$. \n\nThere are infinitely many such $s$, so there are infinitely many such $s'$. \nIt follows that for infinitely many $l_{s'}$, the initial segment $A\\cap l_{s'}$ is a substring \nof some string~$\\alpha$ in $T_1$ (by Lemma~\\ref{ex:nocarrier-string1}, $\\alpha$ is winning in this case), \nand for infinitely many $l_{s'}$, $A\\cap l_{s'}$ is a substring of some (losing) string~$\\alpha$ in $T_0$.\\end{proof}\n\n\\section*{Acknowledgements}\n\nWe would like to thank an anonymous referee for useful suggestions. %\nThis is an outcome of a long-term collaboration started in 1998. \nIt could not have been produced without a lack of grants for shorter-term projects.\n\n\n\n\n\n","meta":{"redpajama_set_name":"RedPajamaArXiv"}} +{"text":"\\section{Introduction}\n\nSuppose $X$ is a compact oriented manifold acted on by a compact\nconnected Lie group $K$ of dimension $s$; one may\nthen define the equivariant\ncohomology $\\hk(X)$.\nThroughout this paper we shall consider only cohomology\nwith complex coefficients.\nIf $X$ is a symplectic manifold\nwith symplectic form $\\om$ and the action of $K$ is Hamiltonian\n(in other words, there is a moment map $\\mu: X \\to \\lieks$), then we\nmay form the symplectic quotient $\\xred = \\mu^{-1}(0)\/K$. The restriction\nmap $i_0: X \\to \\mu^{-1}(0)$ gives a ring homomorphism\n$i_0^*: \\hk(X) \\to \\hk (\\mu^{-1}(0) ) $. Using Morse theory and the gradient\nflow of the function $|\\mu|^2: X \\to {\\Bbb R }$, it is proved\nin \\cite{Ki1}\nthat the map\n$i_0^*$ is surjective.\n\nSuppose in addition that $0$ is a {\\em regular value} of the\nmoment map $\\mu$. This assumption is equivalent to the assumption\nthat the stabilizer $K_x$ of $x$ under\n the action of $K$ on\n$X$ is {\\em finite } for every $x \\in \\mu^{-1} (0)$, and\nit implies that $\\xred$ is an orbifold, or $V$-manifold, which inherits\na symplectic form $\\omega_0$ from the symplectic form\n$\\omega$ on $X$. In this situation there is a canonical isomorphism\n$\\pi_0^*: H^*(\\mu^{-1}(0)\/K) \\to \\hk (\\zloc)$.\\footnote{This\nisomorphism is induced by the map $\\pi_0: \\zloc \\times_K EK \\to \\zloc\/K$.\nRecall that we are only considering cohomology with complex coefficients.}\nHence we have a surjective ring homomorphism\n\\begin{equation} \\label{0.1}\n\\kappa_0 = (\\pi_0^*)^{-1} \\circ i_0^*: \\hk(X) \\to\nH^*(\\xred). \\end{equation}\n\n\nHenceforth, if $\\eta \\in \\hk(X)$ we shall denote $\\kappa_0(\\eta)$ by\n$\\eta_0$.\nPrevious work \\cite{Brion,Ki2} on determining the ring structure\nof $\\hk(X)$ has presented methods which in some situations\npermit the direct determination of the kernel of the\nmap $\\kappa_0$, and hence of generators and relations\nin $H^*(\\xred)$ in terms of generators\nand relations in $\\hk(X)$. (Note that the generators of $\\hk(X)$\ngive generators of $H^*(\\xred)$ via the surjective map $\\kappa_0$, and also that\ngenerators of $H^*(BK)$ together with extensions to\n$\\hk(X)$ of generators of $H^*(X)$ give generators of\n$\\hk(X)$ because the spectral sequence\nof the fibration\n$X \\times_K EK \\to BK$ degenerates \\cite{Ki1}.)\n Here we present\nan alternative approach to determining the ring structure of\n$H^*(\\xred)$ when $0$ is a regular value of $\\mu$, which complements\nthe results obtained by directly studying the kernel\nof $\\kappa_0$. Our approach is based on the observation that since\n$H^*(\\xred) $ satisfies Poincar\\'e duality, a class\n$\\eta \\in \\hk(X)$ is in the kernel of $\\kappa_0$ if and only if for all\n$\\zeta \\in \\hk(X)$ we have\n\\begin{equation} \\eta_0 \\zeta_0 [\\xred]\n= (\\eta \\zeta)_0 [\\xred] = 0 . \\end{equation}\nHence to determine the kernel of $\\kappa_0$ (in other words the\nrelations in the ring $H^*(\\xred)$) given\nthe ring structure of $\\hk(X)$, it suffices to know\nthe {\\em intersection pairings}, in other words the evaluations\non the fundamental class $[\\xred]$ of all possible classes $\n\\xi_0 = \\kappa_0 (\\xi)$.\nIn principle the intersection pairings thus determine generators\nand relations for the cohomology ring $H^*(\\xred)$, given\ngenerators and relations for $\\hk(X)$.\n\n\n There is a natural\npushforward map $\\pisk: \\hk(X) \\to \\hk $ $ = \\hk({\\rm pt} )$\n$ \\cong S(\\lieks)^K$, where we have identified\n$\\hk$ with the space of $K$-invariant polynomials on the\nLie algebra $\\liek$. This map can be thought of as integration\nover $X$ and will sometimes be denoted by\n$\\int_X$.\nIf $T$ is a compact {\\em abelian} group\n(i.e. a torus) and $\\zeta \\in \\hht(X)$,\nthere is a formula\\footnote{Atiyah and Bott\n\\cite{abmm} give\na cohomological proof of this formula, which was first proved by\nBerline and Vergne \\cite{BV1}.} (the {\\em abelian localization\ntheorem})\nfor $\\pist \\zeta$ in terms of\nthe restriction of $\\zeta$ to the components of the\nfixed point set for the action of $T$. In particular, for a general\ncompact Lie group $K$ with maximal torus $T$ there\nis a canonical map\n$\\tau_X: \\hk(X) \\to \\hht(X)$, and we may apply the\nabelian localization theorem to $\\tau_X (\\zeta)$ where\n$\\zeta \\in \\hk(X)$.\n\n\n\n\n\n\n\n\n\n\nIn terms of the components $F$ of the fixed point set\nof $T$ on $X$, we obtain a\nformula (the residue formula, Theorem \\ref{t8.1})\nfor the evaluation\n of a class $\\eta_0 \\in H^*(\\xred) $ on the\nfundamental class $[\\xred]$, when $\\eta_0$ comes\nfrom a class $\\eta \\in \\hk(X)$. There are two main\ningredients in the proof\nof Theorem \\ref{t8.1}. One is the abelian localization\ntheorem \\cite{abmm,BV1}, while\nthe other is an equivariant normal\nform for $\\om$ in a neighbourhood of $\\zloc$,\ngiven in \\cite{STP}\nas a consequence of the coisotropic embedding theorem.\nThe result is the following:\n\n\\noindent{\\bf Theorem 8.1} {\\em\nLet $\\eta \\in \\hk(X)$ induce $\\eta_0 \\in H^*(\\xred)$.\nThen we have\n$$\n\\eta_0 e^{i\\omega_0} [\\xred] =\n \\frac{(-1)^{n_+} }{(2 \\pi)^{s-l} |W| \\,{\\rm vol}\\, (T) }\n\\treso\n\\Biggl ( \\: \\nusym^2 (\\psi)\n \\sum_{F \\in {\\mbox{$\\cal F$}}} e^{i \\mu_T(F) (\\psi) }\n\\int_F \\frac{i_F^* (\\eta(\\psi) e^{i \\omega} ) }{e_F(\\mar \\psi) }\n[d \\psi] \\Biggr ). $$\nIn this formula, $n_+$ is the number of\npositive roots of $K$, and\n$\\nusym(\\psi) = \\prod_{\\gamma > 0} \\gamma(\\psi)$ is the product of the\n positive roots, while\n${\\mbox{$\\cal F$}}$ is the set of components of the fixed point\nset of the maximal torus $T$ on $X$. If $F \\in\n{\\mbox{$\\cal F$}}$ then $i_F$ is the inclusion of $F$ in $ X$ and\n$e_F$ is the equivariant Euler class of the normal\nbundle to $F$ in $X$.}\n\n\\noindent Here, via the {\\em Cartan model},\nthe class $\\tau_X ( \\eta )\\in \\hht(X)$\nhas been identified with a family of differential\nforms $\\eta (\\psi)$ on $X$\nparametrized by $\\psi \\in \\liet$. The definition of the\nresidue map $\\treso$ (whose domain is a suitable class of\nmeromorphic differential forms on\n$\\liet \\otimes {\\Bbb C }$)\n will be given in Section\n8 (Definition \\ref{d8.5n}). It is a linear map, but\nin order to apply it to the individual terms\nin the statement of Theorem 8.1 some\nchoices must be made. The choices do not affect the\nresidue of the whole sum. When $\\liet$ has dimension one the\nformula becomes\n\n\n\n\n\n$$\n\\eta_0 e^{i\\omega_0} [\\xred] =\n -\\frac{1}{2}\n{\\rm Res}_0\n\\Biggl ( \\psi^2 \\:\n \\sum_{F \\in {\\mbox{$\\cal F$}}_+} e^{i \\mu_T(F) (\\psi) }\n\\int_F \\frac{i_F^* (\\eta(\\psi) e^{i \\omega} ) }{e_F(\\mar \\psi) }\n \\Biggr ), $$\nwhere ${\\rm Res}_0$ denotes the coefficient of\n$1\/\\psi$, and ${\\mbox{$\\cal F$}}_+$ is the subset of the\nfixed point set of $T = U(1)$ consisting of those\ncomponents $F$ of the $T$ fixed point set for which\n$\\mu_T(F) > 0 $.\n\n\nWe note that if $\\dim \\eta_0 = \\dim \\xred$ then the\nleft hand side of the equation in Theorem \\ref{t8.1}\nis just $\\eta_0 [\\xred]$. More generally one may obtain\na formula for $\\eta_0[\\xred]$ by replacing the\nsymplectic form $\\omega$ by $\\delta \\omega$\n(where $\\delta > 0 $ is a small parameter), and taking\nthe limit as $\\delta \\to 0$. This has the\neffect of replacing the moment map $\\mu$ by $\\delta \\mu$.\nIn the limit $\\delta \\to 0$, the Residue Formula (Theorem \\ref{t8.1})\nbecomes a sum of terms corresponding to the components $F$ of the\nfixed point set, where the term corresponding to $F$ is (up to a constant)\nthe residue (in the sense of Section 8) of\n$\\nusym^2(\\psi) \\int_F {i_F^* (\\eta(\\psi) ) }\/{e_F(\\mar \\psi) } $, and\nthe only role played by the symplectic form and the moment\nmap is in determining which\n $F$\ngive a nonzero\ncontribution to the residue of the sum and the signs with which\nindividual terms enter.\n\n\n\n\n\n\n\n\nResults for the case when $K = S^1$, which are\nrelated to our Theorem \\ref{t8.1}, may\nbe found in the papers of Kalkman \\cite{Kalk} and\nWu \\cite{wu}.\n\n\nWitten in Section 2 of \\cite{tdg} gives a related result, the\n{\\em nonabelian localization theorem}, which also interprets\nevaluations $\\eta_0[\\xred]$ of classes on the\nfundamental class $[\\xred]$ in terms of appropriate\ndata on $X$. For $\\epsilon > 0$ and $\\zeta \\in \\hk(X)$,\nhe defines\\footnote{The normalization of the measure in\n$\\ie(\\zeta)$ will be described at the beginning of\nSection 3. As above, $\\pis: \\hk(X) \\to \\hk \\cong S(\\lieks)^K$ is the\nnatural pushforward map, where $S(\\lieks)^K$ is the space of\n$K$-invariant polynomials on $\\liek$. }\n\\begin{equation} \\label{1.1}\n\\ie(\\zeta) = \\frac{1}{(2 \\pi i)^s \\,{\\rm vol}\\, K}\n\\intk [d \\phi] e^{- \\epsilon \\inpr{\\phi, \\phi}\/2 }\n\\pisk \\zeta (\\phi) \\end{equation}\n(where $\\inpr{\\cdot,\\cdot} $ is a fixed invariant inner\nproduct on $\\liek$, which we shall use throughout to identify\n$\\lieks$ with $\\liek$)\n and expresses it as a sum\nof local contributions.\n\n\n\n\nWitten's theorem tells us that just as $\\pisk \\zeta$ would have\ncontributions from\nthe components of the fixed point set of $K$ if $K $ were\nabelian, the quantity $\\ie(\\zeta)$ (if $K$ is not necessarily\nabelian) reduces to a sum of integrals\nlocalized around the critical set of the function\n$\\rho = |\\mu|^2,$\ni.e. the set of points $x$ where $(d |\\mu|^2)_x = 0$.\n(Of course $d |\\mu|^2 = 2\\inpr{\\mu, d \\mu}$, so the\nfixed point set of the $K$ action, where $d \\mu = 0$,\nis a subset of the critical set of $d|\\mu|^2$.)\nMore precisely the critical set of $\\rho = |\\mu|^2$\ncan be expressed as a disjoint union of closed subsets\n$C_\\beta$ of $X$ indexed by a finite subset\n${\\mbox{$\\cal B$}}$ of the Lie algebra $\\liet$ of the maximal\ntorus $T$ of $K$ which is explicitly\nknown in terms of the moment map\n$\\mu_T$ for the action of $T$ on $X$ \\cite{Ki1}. If\n$\\beta \\in {\\mbox{$\\cal B$}}$ then the critical subset\n$C_\\beta$ is of the form $C_\\beta = K (Z_\\beta \\cap\n\\mu^{-1}(\\beta))$ where $Z_\\beta$ is a union of\nconnected components of the fixed point set of the\nsubtorus of $T$ generated by $\\beta$. The subset\n$\\mu^{-1}(0)$ on which $\\rho = |\\mu|^2$ takes its\nminimum value is $C_0$.\nThere is a natural map\\footnote{This map\nis induced by the projection ${\\rm pr}:\\zloc \\to {\\rm pt}.$}\n${\\rm pr}^*: \\hk \\to \\hk(\\zloc)$\n so that the distinguished class $f(\\phi) = -\\inpr{\\phi, \\phi}\/2$\nin $H^4_K$\ngives rise to a distinguished class\n$\\Theta \\in H^4(\\zloc\/K) \\cong H^4_K(\\zloc).$\nWitten's result can then be expressed in the form\n\\begin{theorem} \\label{t1.1}\n$$ \\ie(\\zeta) = \\zeta_0e^{\\epsilon \\Theta} [\\xred] + \\sum_{\\beta \\in\n{\\mbox{$\\cal B$}} - \\{0\\} } \\int_{U_\\beta}\n{\\zeta'}_\\beta. $$\nHere,\nthe $U_\\beta$ are\nopen neighbourhoods in $X$ of\n the nonminimal critical subsets $C_\\beta$ of the function\n$\\rho$.\nThe $\\zeb$ are\ncertain differential forms on $U_\\beta$ obtained from $\\zeta$.\n\\end{theorem}\n\nIn the special case $\\zeta = \\eta \\exp \\iins \\bar{\\om} $ (where $\\bar{\\om}(\\phi)\n = \\om + \\evab{\\phi}{ \\mu} $ is the standard extension of the symplectic\nform $\\om$\nto an element of $H^2_K(X)$, and\n$\\eta$ has polynomial dependence\\footnote{The equivariant\ncohomology $\\hk(X) $ is defined to consist of classes which have\npolynomial dependence on the generators of $\\hk$, but we shall\nalso make use of formal classes such as $\\exp \\iins \\bom$ which\nare formal power series in these generators.}\non the generators of $\\hk$),\n Witten's results give us the following\n estimate\non the growth of the terms $\\int_{U_\\beta} \\zeb$\nas $\\epsilon \\to 0$:\n\\begin{theorem} \\label{t1.2}\nSuppose $\\zeta = \\eta \\exp i \\bar{\\om}$ for some $\\eta \\in \\hk(X)$. If\n$\\beta \\in {\\mbox{$\\cal B$}} - \\{0\\}$ then\n$\\int_{U_\\beta} \\zeb = e^{- \\rho_\\beta\/{2 \\epsilon} } \\:\nh_\\beta(\\epsilon)$, where $\\rho_\\beta = |\\beta|^2$\n is the value of $|\\mu|^2$\non the critical set $C_\\beta$ and $|h_\\beta(\\epsilon)|$ is bounded by a polynomial\nin $\\epsilon^{-1}$.\n\\end{theorem}\n\nThus one should think of $\\epsilon > 0$ as a small parameter,\nand one may use the asymptotics of the integral $\\ie$\nover $X$ to calculate the intersection pairings\n$\\eta_0 e^{\\epsilon \\Theta} e^{i\\om_0} [\\xred],$ since the terms in\nTheorem \\ref{t1.2} corresponding to the other critical subsets\nof $\\rho$ vanish exponentially fast as $\\epsilon \\to 0$.\nNotice that when $\\zeta = \\exp i\\bom$, the vanishing of\n$\\mu$ on $\\zloc$ means that $\\zeta_0 = \\exp i\\om_0$, where\n$\\omega_0$ is the symplectic form induced\nby $\\omega$ on $\\xred = \\mu^{-1}(0)\/K$.\n\n\n\n\n\nIn this paper we shall give a proof of a variant of\nTheorems \\ref{t1.1} and \\ref{t1.2}, for the case\n$\\zeta = \\eta \\exp i \\bom $ where $\\eta \\in \\hk(X)$.\n Before outlining our proof, it will\nbe useful to briefly recall Witten's argument.\nWitten introduces a $K$-invariant 1-form $\\lambda$ on\n$X$, and shows that $\\ie(\\zeta) = \\ie(\\zeta \\exp s D \\lambda)$,\nwhere $D $ is the differential in equivariant\ncohomology and $s \\in {\\Bbb R }^+$. He then does the\nintegral over $\\phi \\in \\liek$ and shows that in the limit\nas $s \\to \\infty$,\nthis\nintegral vanishes over any region of\n$X$ where $\\lambda(\\va) \\ne 0$ for at least one of the vector fields\n$\\va, j = 1, \\dots, s$ given by the infinitesimal action of a basis of\n$\\liek$ on $X$ indexed by $j$.\n Thus, after integrating\nover $\\phi \\in \\liek$, the limit as $s \\to \\infty$\nof $\\ie(\\zeta)$ reduces to a sum of contributions\nfrom sets where $\\lambda(\\va) = 0$ for all the $\\va$.\n\nIn our case, when $X$ is a symplectic manifold and the action\nof $K$ is Hamiltonian, Witten chooses $\\lambda(Y) = d|\\mu|^2(JY)$,\nwhere $J$ is a $K$-invariant almost complex structure on\n$X$. Thus $\\lambda(\\va)(x) = 0$ for all $j$\nif and only if $(d|\\mu|^2)_x = 0$,\nso $\\ie(\\zeta)$ reduces to a sum of contributions from the critical sets\nof $\\rho = |\\mu|^2$.\nFurther, he obtains the contribution from $ \\zloc$\nas $e^{\\epsilon \\Theta} \\zeta_0 [\\xred] $. If $\\zeta = \\eta e^{\\iins \\bom} $\nhe also obtains the estimates in Theorem \\ref{t1.2}\non the contributions from the neighbourhoods $U_\\beta$.\n\nIn general,\nthe contributions to the localization theorem depend\n on the choice of $\\lambda$. In the symplectic\ncase, with $\\lambda = J d |\\mu|^2$, the contribution\nfrom $\\mu^{-1}(0)$ is canonical but the contributions\nfrom the other critical sets $C_\\beta$ depend in principle\non the choice of $J$. Further, the properties of these\nother terms are difficult to study. Ideally they\nshould reduce to integrals over the critical sets\n$C_\\beta$, and indeed when proving Theorem \\ref{t1.2} Witten\nmakes the assumption (before (2.52)) that the $C_\\beta$\nare nondegenerate critical manifolds in the sense of Bott\n\\cite{bnd}.\nIn general the $C_\\beta$ are not manifolds; and\neven when they are manifolds, they are not necessarily nondegenerate. They\n satisfy only a weaker condition called {\\em minimal\ndegeneracy} \\cite{Ki1}.\\footnote{However, minimal degeneracy\nmay be sufficient for Witten's argument.} We shall treat the\nintegrals over neighbourhoods of the $C_\\beta$ in a future paper.\n\n\nIn the case when $X$ is a symplectic manifold and\n$\\zeta = \\eta \\exp \\bom$ for any $\\eta \\in\n\\hk(X)$,\nwe have been able to use our methods\nto prove a variant\nof Theorems \\ref{t1.1} and \\ref{t1.2}\n(see Theorems \\ref{t4.1}, \\ref{t4.3} and \\ref{t7.1} below)\nwhich\nbypasses these analytical difficulties and reduces the result\nto fairly well known results on Hamiltonian group actions on\nsymplectic manifolds. We assume that $0$ is\na regular value of $\\mu$, or equivalently\nthat $K$ acts on $\\mu^{-1}(0)$ with finite\nstabilizers.\\footnote{Witten assumes that $K$ acts\nfreely on $\\mu^{-1}(0)$.} By treating the pushforward\n$\\pisk \\zeta$ as a function on $\\liek$, we\nmay use the abelian\nlocalization formula \\cite{abmm,BV1} for the\npushforward in equivariant cohomology of\ntorus actions to find an explicit expression for\n$\\pisk \\zeta$ as a function on $\\liek$.\nThus, analytical problems relating to\nintegrals over neighbourhoods of $C_\\beta$ are circumvented,\nand localization reduces to studying the image of the moment\nmap and the pushforward of the symplectic or Liouville\nmeasure under the moment map.\\footnote{If $K$ is\nabelian, this pushforward measure is equal (at $\\phi \\in \\liek$)\nto Lebesgue measure multiplied by a function which gives\nthe symplectic volume of the reduced space\n$\\mu^{-1}(\\phi)\/K$; this function is sometimes called the\n Duistermaat-Heckman polynomial \\cite{DH}.}\nSeen in this light, the nonabelian localization\ntheorem is a consequence of the same results that\nunderlie the residue formula:\nthe abelian localization formula for torus\n actions \\cite{abmm,BV1} and the normal\nform for $\\om$ in a neighbourhood of $\\zloc$.\n\n\nWe now summarize the key steps in our proof. Having replaced\nintegrals over $X$ by integrals over $\\liek$,\nwe observe that in turn these may be replaced by integrals over the\nLie algebra\n$\\liet$ of the maximal torus. Then, applying properties of\nthe Fourier transform, we rewrite $\\ie$ as the\nintegral over\n$\\liets$ of a Gaussian $\\gtsoe(y) $ $\\sim e^{- |y|^2\/(2 \\epsilon) } $\n multiplied by a\nfunction $Q = D_\\nusym R$ where $R$ is piecewise\npolynomial and $D_\\nusym$ is a differential operator on $\\liets$:\n\\begin{equation} \\label{0.2}\\ie =i^{-s} \\tintt \\widetilde{\\gsoe} (y) Q(y), \\end{equation}\nwhere $s$ is the dimension of $K$.\n The function $Q$ is obtained by combining the\nabelian localization theorem (Theorem \\ref{t2.1})\nwith a result\n(Proposition \\ref{p3.5}) on Fourier transforms of a certain class of\nfunctions which arise in the\n formula for the pushforward.\n\nThe\nfunction $Q$ is smooth in a neighbourhood of the origin when\n$0$ is a regular value of $\\mu$:\nthus there is a polynomial $Q_0\n = D_\\nusym R_0 $ which is equal to $Q$ near\n$0$. It turns out that the cohomological expression\n$\\eeth[\\xred]$ is obtained as the integral over $\\liets$\nof a Gaussian multiplied not\nby $Q$ but by the polynomial $Q_0$:\n\\begin{equation} \\eeth [\\xred] = i^{-s} \\tintt \\widetilde{\\gsoe} (y) Q_0(y). \\end{equation}\nThis result follows from a normal form for $\\om$ near\n$\\zloc$.\\footnote{This\nnormal form is a key tool in the original proof \\cite{DH} of\nthe Duistermaat-Heckman theorem; this theorem\nmotivated the proof by Atiyah and Bott \\cite{abmm} of the\nabelian localization theorem.}\n\nTo obtain our analogue of Witten's estimate (Theorem\n\\ref{t1.2}) for the asymptotics of\n$\\ie - \\eeth [\\xred]$ as $\\epsilon \\to 0$,\nwe then write\n\\begin{equation} \\ie - \\eeth [\\xred] =\ni^{-s} \\tintt \\widetilde{\\gsoe}(y)\nD_\\nusym (R - R_0) (y). \\end{equation}\nHere, $R - R_0$ is piecewise polynomial and\nsupported {\\em away} from $0$.\nBy studying\nthe minimum distances from $0$\nin the support of $R - R_0$\nwe obtain an estimate (Theorem \\ref{t4.1}) similar to\nWitten's estimate (Theorem \\ref{t1.2}). In our estimate,\nthe terms in the sum are indexed by\nthe set ${\\mbox{$\\cal B$}} - \\{0\\}$; however, our estimate is\nweaker than Witten's estimate since some of the subsets\n$C_\\beta$ indexed by\n$\\beta \\in {\\mbox{$\\cal B$}} - \\{0\\}$ (which a priori\ncontribute to our sum\\footnote{In a future paper\nwe hope to prove that the nonzero contributions\nto our estimate (Theorem \\ref{t4.1}) come only\nfrom those $|\\beta|^2$ which are nonzero critical values\nof $|\\mu|^2$.}\n)\nmay be empty in which case $\\rho_\\beta\n= |\\beta|^2$ may not be a critical value\nof $|\\mu|^2$.\n\n\n\nTo summarize, the following related quantities appear in this paper:\n\\begin{enumerate}\n\\item The cohomological quantity $\\eta_0 e^{i \\om_0}\n[\\xred]$.\n\\item The integral ${\\mbox{$\\cal I$}}^\\epsilon $ (\\ref{1.1}) coming from\nthe pushforward of an equivariant cohomology class\n$\\eta \\in \\hk(X)$ to $\\hk$.\n\\item Sums of terms of the form\n$$\\int_F \\frac{i_F^* \\eta}{e_F}$$\nwhere\n$F$ is a connected component of\nthe fixed point set of the maximal torus $T$ acting\non $X$.\nSuch sums appear after mapping $\\eta \\in\n\\hk(X)$ into $\\hht(X) $ and then applying the abelian\nlocalization theorem.\n\\end{enumerate}\nWitten's work relates (1) and (2), while our\nTheorem \\ref{t8.1} relates (1) and (3).\n\n\n\n\n\n\n\n\n\nThis paper is organized as follows. Section 2 contains\nbackground material on equivariant cohomology\nand the abelian localization formula.\nIn Section 3 we collect a number of preliminary results\nwhich we use in Section 4 to reduce our integral\n$\\ie$ to an integral over $\\liets$ of a piecewise\npolynomial function multiplied by a Gaussian.\nSection 4 also contains the statement of two of\nour main results,\nTheorems \\ref{t4.1} and \\ref{t4.3}; Theorem\n\\ref{t4.3} is proved in Section 5, and Theorem \\ref{t4.1}\nin Section 6. In Section 7, Theorems \\ref{t4.1}\nand \\ref{t4.3} (which are for the case $\\zeta = \\exp \\bom$)\nare extended to the case $\\zeta = \\eta \\exp \\bom $ for\n$\\eta \\in \\hk(X)$: the result is\nTheorem \\ref{t7.1}. Finally, in Section 8 we\nprove the residue\n formula (Theorem \\ref{t8.1}) for the evaluation of cohomology\nclasses from $\\hk(X)$ on the fundamental class of $\\xred$, and\nin Section 9 we\napply it when $K = SU(2)$ to specific examples.\nThis formula may be related to an unpublished\nformula due to Donaldson.\n\nIn future papers we shall treat the case when\n$\\xred$ is singular using intersection homology; we shall also\napply the nonabelian localization formula to moduli spaces of\nbundles over Riemann surfaces regarded as finite\ndimensional symplectic quotients, in singular as\nwell as nonsingular cases.\n\n\\noindent{\\em Acknowledgement:}\nWe are most grateful to H. Duistermaat and M. Vergne for\nhelpful suggestions and careful readings of the paper.\n\nIn addition, one\n of us (L.C.J.) wishes\nto thank E. Lerman and E. Prato for explaining their work,\nand also to thank E. Witten for discussions about\nthe nonabelian localization formula while the paper\n\\cite{tdg} was being written.\n\n\n\n\n\n{ \\setcounter{equation}{0} }\n\\section{Equivariant cohomology and pushforwards}\n\nIn this section we recall the localization formula for torus\nactions (Theorem\n\\ref{t2.1}) and express it in a form convenient\nfor our later use (Lemma \\ref{l2.2}).\n\nLet $X$ be a compact manifold equipped with the action of\na compact Lie group $K$ of dimension $s$ with\nmaximal torus $T$ of dimension $l$. We denote the Lie algebras\nof $K$ and $T$ by $\\liek$ and $\\liet$ respectively, and\nthe Weyl group by $W$.\nWe assume an invariant inner product\n$\\inpr{\\cdot, \\cdot} $ on $\\liek$ has\nbeen chosen (for example, the Killing form): we shall use\nthis to identify $\\liek$ with its dual. The orthocomplement\nof $\\liet$ in $\\liek$ will be denoted $\\lietp$.\n\nThroughout this paper all cohomology groups are assumed to have\ncoefficients in\nthe field ${\\Bbb C }$.\nThe $K$-equivariant cohomology of a point is $\\hk = H^*(BK)$,\nand similarly the $T$-equivariant cohomology is $\\hht\n= H^*(BT)$. We identify $\\hk $ with\n$S(\\liek^*)^K$, the $K$-invariant polynomial functions on $\\liek$,\nand $\\hht$ with $S(\\liets)$.\nHence we have a bijective map (obtained from the restriction from\n$\\lieks$ to $\\liets$) which identifies $\\hk$ with the subset of\n$\\hht$ fixed by the action of the Weyl group $W$:\n\\begin{equation} \\label{2.1}\n\\hk \\cong S(\\lieks)^K\n\\cong S(\\liets)^W \\subseteq S(\\liets) \\cong \\hht \\end{equation}\nThis natural map $\\hk \\to \\hht$ will be denoted $\\tau$ or\n$\\tau_X$.\nWe shall use the symbol $\\phi$ to denote a point in\n$\\liek$, and $\\psi$ to denote a\npoint in $\\liet$. For $f \\in \\hk$ we shall write\n$f = f (\\phi)$ as a function of $\\phi$.\n\nThe $K$-equivariant cohomology of $X$ is the cohomology\nof a certain chain complex (see, for instance, Chapter 7 of\n\\cite{BGV} or Section 5\nof \\cite{MQ}; the construction is due to Cartan\n\\cite{cartan}) which\ncan be expressed as\n\\begin{equation} \\label{2.0}\n\\Om^*_K(X) = \\Bigl ( S(\\lieks) \\otimes \\Om^*(X) \\Bigr )^K \\end{equation}\n(where $\\Om^*(X)$ denotes differential forms on $X$).\nAn element in $\\Om^*_K(X)$ may be thought of as a\n$K$-equivariant polynomial function\nfrom $\\liek$ to $\\Om^*(X)$.\nFor\n $ \\alpha \\in \\Om^*(X)$ and $f \\in S(\\lieks)$,\nwe write $(\\alpha \\otimes f) (\\phi) = f(\\phi) \\alpha$.\nIn this notation, the differential $D$ on the\ncomplex $\\Om^*_K(X)$ is then defined by\\footnote{This definition and\nthe definition (\\ref{2.0''}) of the extension $\\bom(\\phi)\n= \\omega + \\mu(\\phi)$\nof the\nsymplectic form $\\omega$ to an equivariant cohomology\nclass are different from the conventions\nused by Witten \\cite{tdg}: a factor $\\phi$ appears in the\nour definitions where $i \\phi$ appears in Witten's definition.\nIn other words Witten's definition is\n$D(\\alpha \\otimes f) (\\phi) =\nf(\\phi) (d \\alpha - i \\iota_{ \\tilde{\\phi} } \\alpha)$\nand $\\bom(\\phi)\n= \\omega + i \\mu(\\phi)$.\nWitten makes this substitution\nso that the oscillatory\nintegral $ \\int_X \\exp (\\om + i \\evab{\\phi}{ \\mu} ) $ will appear\nas the integral of an equivariant cohomology class.}\n\\begin{equation} \\label{2.0'}\nD(\\alpha \\otimes f) (\\phi) =\nf(\\phi) (d \\alpha - \\iota_{ \\tilde{\\phi} } \\alpha)\n= \\, f (\\phi) d \\alpha\n- \\sum_{j= 1}^s \\phi_j f(\\phi) \\: \\iota_{\\va} \\alpha . \\end{equation}\nHere, $\\tilde{\\phi}$ is the vector\nfield on $X$ given by the action\nof $\\phi \\in \\liek$, and $\\iota_{\\tilde{\\phi} }$ is the interior\nproduct with the vector field $\\tilde{\\phi}$.\nWe have introduced an orthonormal basis $\\{ \\hat{e}^j,\n\\: j = 1, \\dots, s \\} $ for $\\liek$, and the $\\phi_j$ $ \\in \\lieks$\nare\nsimply the coordinate functions $\\phi_j = \\inpr{\\hat{e}^j, \\phi},\n $ while the $\\va$ are the vector fields on $X$ generated by\nthe action of $\\hat{e}^j$. The $\\phi_j $ are assigned\ndegree $2$, so that the differential $D$ increases degrees by $1$.\n\n\nOne may define the pushforward\n$\\pis^K: \\hk(X) \\to \\hk$, which\ncorresponds to integration over the fibre\nof the map $X \\times_K EK \\to BK $ (see Section 2\nof \\cite{abmm}). The pushforward satisfies\n$\\pis^T = \\tau \\circ \\pisk$. Because of this identification,\nwe shall usually simply write $\\pis$ for $\\pis^K$ or\n$\\pis^T$.\nA localization formula for $\\pist$ was given by\nBerline and Vergne in \\cite{BV1}; a more topological\nproof of this formula is given in Section 3 of\n\\cite{abmm}.\n\\begin{theorem} \\label{t2.1} {\\bf \\cite{BV1} }\nIf $\\si \\in \\hht(X)$ and $\\psi \\in \\liet$ then\n$$(\\pist \\si) (\\psi) = \\sum_{F \\in {\\mbox{$\\cal F$}}}\n\\int_F\n\\frac{i_F^* \\si(\\psi) }{e_F( \\psi) }. $$\nHere we sum over the set ${\\mbox{$\\cal F$}}$ of components $F$ of the fixed point\nset of $T$, and $e_F $ is the $T$-equivariant\nEuler class of the normal bundle of $F$; this Euler class\nis an element of $H^*_T(F) \\cong H^*(F) \\otimes \\hht$,\nas is $i_F^* \\si$. The map $i_F: F \\to X$ is the inclusion map.\nThe right hand side of the above expression is to be interpreted as\na rational function of $\\psi$.\n\\end{theorem}\n\n\nWe shall now prove a lemma about the image of the pushforward,\nwhich will be applied in Section 4.\n\\begin{lemma}\\label{l2.2}\nIf $\\si \\in \\hht(X) $ then $(\\pist \\si)(\\psi)$ is a sum of terms\n\\begin{equation} \\label{2.m0} (\\pist \\si)(\\psi) =\n\\sum_{F \\in {\\mbox{$\\cal F$}}, \\;\\alpha \\in {\\mbox{$\\cal A$}}_F}\\tau_{F,\\alpha} \\end{equation}\nsuch that each term $\\tau_{F,\\alpha}$ is of the form\n\\begin{equation} \\label{2.m1}\n\\tau_{F,\\alpha} =\n\\frac{\\int_F c_{F, \\alpha}(\\psi) }{ \\efo(\\mar \\psi) \\prod_j\n\\beta_{F,j}(\\mar \\psi)^{n_{F,j}(\\alpha)} } \\end{equation}\nfor some component $F$ of the fixed point set of the\n$T$ action. Here, the $\\beta_{F,j}$ are the weights of\nthe $T$ action on the normal bundle $\\nu_F$, and\n$\\efo (\\mar \\psi) = \\prod_j \\beta_{F,j}(\\mar \\psi)$ is the product of all the\nweights, while $n_{F,j}(\\alpha)$ are some nonnegative integers. The class\n$c_{F,\\alpha}$ is in $H^*(F) \\otimes H^*_T$, and is equal to\n$i_F^* \\si \\in H^* (F) \\otimes H^*_T$ times some\ncharacteristic\nclasses of subbundles of $\\nu_F$.\n\\end{lemma}\n\n\\Proof\nThe normal bundle $\\nu_F$ to $F$ decomposes as a direct sum of\nweight spaces $\\nu_F =\n\\oplus_{j = 1}^r \\nu_F^{(j)}$, on each of which\n$T$ acts with weight $\\bfj$. All these weights must be nonzero.\nBy passing to a split manifold if necessary (see section 21 of\n\\cite{BT}), we may assume without loss of generality\nthat the subbundle on which $T$ acts with a given weight decomposes\ninto a direct sum of $T$-invariant real subbundles\nof rank $2$.\nIn other words, we may assume that the $\n\\nu_F^{(j)}$ are rank $2$ real bundles, and the\n$T$ action enables one to identify them in a\nstandard way with complex line bundles.\n\nThen the equivariant\nEuler class $e_F(\\psi)$ is given for $\\psi \\in \\liet$\n by\n\\begin{equation} \\label{2.3}\ne_F(\\psi) = \\prod_{j = 1}^r \\Bigl (c_1(\\nu_F^{(j)}) + \\beta_{F,j}(\\psi)\n\\Bigr ). \\end{equation}\nThus we have\n$$\n\\frac{1}{e_F (\\mar \\psi)} = \\frac{1}{\\efo(\\mar \\psi) } \\,\n\\prod_j (1 + \\frac{c_1 (\\nu_F^{(j)} )}{\\beta_{F,j}(\\mar \\psi) } )^{-1} $$\n\\begin{equation} \\label{2.4}\n= \\frac{1}{\\efo(\\mar \\psi) } \\: \\prod_j \\sum_{r_j \\ge 0 }\n\\: \\, (-1)^{r_j} \\Bigl ( \\frac{c_1 (\\nu_F^{(j)} )}\n{\\beta_{F,j}(\\mar \\psi) } \\Bigr )^{r_j}\n. \\end{equation}\nHere, $c_1(\\nu_F^{(j)} ) \\in H^2(F)$, so that\n$c_1(\\nu_F^{(j)} )\/\\beta_{F,j}(\\mar \\psi)$ is {\\em nilpotent} and the inverse\nmakes sense in $H^*(F) \\otimes {\\Bbb C }(\\psi_1, \\dots, \\psi_l)$,\nwhere ${\\Bbb C } (\\psi_1, \\dots, \\psi_l)$ denotes the complex\nvalued rational functions\non $\\liet$.\n$\\square$\n\n\nLet us now assume that $X$ is a symplectic manifold\nand the action of $K$ is Hamiltonian with moment map\n$\\mu: X \\to \\lieks$. Denote by $\\mu_T $\nthe moment map for the action of $T$ given by the composition\nof $\\mu$ with the restriction map $\\lieks \\to \\liets$.\nWe shall be interested in one particular (formal)\nequivariant cohomology\nclass $\\si $, defined by\n\\begin{equation} \\label{2.0''}\\si(\\phi) =\n\\exp \\iins \\bom(\\phi), \\phantom{bbbbb} \\bom(\\phi)\n = \\omega + \\mu( \\phi ) . \\end{equation}\n For this\nclass the localization formula gives\n\\begin{equation} \\label{2.2}\n (\\pist \\si) (\\psi) = \\sum_F \\rf(\\psi), \\phantom{bbbbb}\n\\rf (\\psi) = \\int_F \\frac{ e^{i \\mu_T(F)(\\psi )\n } e^\\om } {e_F(\\mar \\psi) }. \\end{equation}\n(This formula does not require the fixed point set\nof $T$ to consist of\n isolated fixed points.)\n\n\\noindent{\\em Remark:} For any\n$\\eta \\in \\hk(X) $ the function $\\pisk \\eta \\in \\hk$ is\n a polynomial on $\\liek$, and in particular is smooth. However,\n$\\sigma = e^{\\iins \\bom} $ does not have\npolynomial dependence on $\\phi$.\nAlthough it is not immediately obvious\nfrom the formula (\\ref{2.2}), the\nfunction $\\pisk (\\eta e^{\\iins \\bom}) $ is still a\n{ smooth}\nfunction on $\\liek$ (for any $\\eta \\in \\hk(X)$ represented\nby an element $\\tilde{\\eta} \\in \\Om^*_K (X)$): this\nfollows from its description as\n$$ \\pisk (\\eta e^{\\iins \\bom}) (\\phi) = \\int_{x \\in X} e^{i \\om}\n \\tilde{\\eta} (\\phi)\ne^{i \\mu(x) (\\phi) }. $$\n\n\n\n{ \\setcounter{equation}{0} }\n\\section{Preliminaries}\n\nThis section contains results which will be applied in the\nnext section to reduce the integral $\\ie$ to an integral over $\\liets$\nof a Gaussian multiplied by a piecewise polynomial function. The\nfirst, Lemma \\ref{l3.1}, reduces integrals over $\\liek$ to\nintegrals over $\\liet$. Lemma \\ref{l3.2} enables\nus to replace the $L^2$ inner product of two functions by\nthe $L^2$ inner product of their Fourier transforms. Lemma\n\\ref{l3.3} relates Fourier transforms on $\\liek$ to\nFourier transforms on $\\liet$. Finally Proposition \\ref{p3.5}\ndescribes certain functions\nwhose Fourier transforms are the terms\nappearing\nin the localization formula (\\ref{2.4}).\n\nWe would like to study a certain integral that arises out\nof equivariant cohomology:\n\\begin{equation} \\label{3.1}\n{\\mbox{$\\cal I$}}^\\epsilon = \\frac{1}{(2 \\pi i )^s \\,{\\rm vol}\\, K} \\int_{\\phi \\in \\liek}\n[d\\phi] \\, e^{- \\epsilon \\inpr {\\phi, \\phi } \/2 } \\int_X \\si(\\mar \\phi). \\end{equation}\nHere, $\\si \\in \\Om^*_K(X) $\n(see (\\ref{2.0})); we are mainly interested in the\nclass $\\si$ defined by (\\ref{2.0''}).\nAlso,\n $\\epsilon > 0 $ and we shall consider the behaviour of ${\\mbox{$\\cal I$}}^\\epsilon$\nas $\\epsilon \\to 0^+$.\nThe measure $[d \\phi]$ is a measure on $\\liek$ which\ncorresponds to a choice of invariant metric on $\\liek$\n(for instance, the metric given by the Killing form): such\na metric induces a volume form on $K$, and\n$ \\,{\\rm vol}\\, K$ is the integral of this volume form over $K$. Thus\n$[d \\phi]\/ \\,{\\rm vol}\\, K$ is independent of the choice of metric on\n$\\liek$. The metric also gives a measure $[d \\psi] $\non $\\liet$ and a volume form on $T$: it is\nimplicit in our notation that the measures on $T$ and $\\liet$\ncome from the same invariant metric as those on $K$ and $\\liek$.\n\nIt will be convenient to recast integrals over $\\liek$ in terms\nof integrals over $\\liet$. For this we use\n a function $\\nusym: \\liet \\to {\\Bbb R }$,\nsatisfying $\\nusym(w \\psi) = (\\det w) \\nusym(\\psi)$ for\nall elements $w$ of the Weyl group $ W$, and\ndefined by\n\\begin{equation} \\label{3.2}\n\\nusym(\\psi) = \\prod_{\\gamma > 0} \\gamma(\\psi), \\end{equation}\nwhere $\\gamma$ runs over the positive roots.\nUsing the inner product to identify $\\liet$ with\n$\\liets$, $\\nusym$ also defines a function $\\liets \\to {\\Bbb R }$.\nWe have\n\\begin{lemma} \\label{l3.1}[Weyl Integration Formula]\nIf $f: \\liek \\to {\\Bbb R }$ is $K$-invariant, then\n$$\\int_{\\phi \\in \\liek} f (\\phi) [d \\phi]\n= \\ck^{-1} \\intt f (\\psi) \\nusym(\\psi)^2\n[d \\psi], $$\nwhere $s$ and $l$ are the dimensions of $K$ and $T$, and\n$ \\ck = { \\wn \\,{\\rm vol}\\, T}\/ \\,{\\rm vol}\\, K $.\n\\end{lemma}\n\\Proof There is an orthonormal basis $\\{X_\\gamma, Y_\\gamma | $\n$\\gamma $ a positive root$\\}$ for $\\lietp$ such that\n$$[X_\\gamma, \\psi] = \\gamma(\\psi) Y_\\gamma, $$\n$$ [Y_\\gamma, \\psi] = - \\gamma(\\psi) X_\\gamma$$\nfor all $\\psi \\in \\liet$. The Riemannian volume form of the\ncoadjoint orbit\nthrough $\\psi \\in \\liet \\cong \\liets$ (with the metric\non the orbit pulled back from the metric on $\\lieks$\ninduced by the inner product $\\inpr{\\cdot, \\cdot}$)\nevaluated on the tangent vectors $[X_\\gamma, \\psi]$ and $[ Y_\\gamma, \\psi]$\nis thus $ \\prod_{\\gamma> 0} \\gamma(\\psi)^2$, while the volume\nform\nof the homogeneous space $K\/T$ (induced by\nthe chosen metric on $\\liek$) evaluated on the tangent vectors\ncorresponding to\n$X_\\gamma, Y_\\gamma \\in \\liek $ is $1$. Hence\n the Riemannian volume of the orbit\nthrough $\\psi \\in \\liet$ is $ \\nusym(\\psi)^2$ times the\nvolume of the homogeneous space $K\/T$.\n$\\square$\n\n\\newcommand{\\lamax}{\\Lambda^{\\rm max} }\n\\newcommand{\\dist}{{\\mbox{$\\cal D$}}'}\n\nIt will be convenient also to work with the Fourier transform. Given\n$f: \\liek \\to {\\Bbb R }$ we define $F_K f: \\lieks \\to {\\Bbb R }$,\n$F_T f: \\liets \\to {\\Bbb R }$\nby\n\\begin{equation} \\label{3.3}\n(F_K f) (z) = \\frac{1}{(2 \\pi)^{s\/2} } \\intk f (\\phi)\ne^{-i \\evab{\\phi}{z} } \\, [d \\phi], \\end{equation}\n\\begin{equation} \\label{3.4}\n(F_T f) (y) = \\frac{1}{(2 \\pi)^{l\/2} } \\intt f (\\psi)\ne^{-i \\evab{\\psi}{y} } \\, [d \\psi]. \\end{equation}\nMore invariantly, the Fourier transform\nis defined on a vector space $V$ of dimension $n$ with\ndual space $V^*$ as a map\n$F: \\Omega^{\\rm max}(V) \\to \\Omega^{\\rm max} (V^*)$\nwhere\n$\\Omega^{\\rm max} (V) = \\Lambda^{\\rm max} (V^*) \\otimes \\dist (V)$,\n$\\Lambda^{\\rm max}(V^*) $\n is the top exterior power of\n$V^*$ and $\\dist (V) $ are the tempered distributions\non $V$ (see \\cite{hor}).\nIndeed for $z \\in V^*$, $f \\in \\dist(V) $ and $u \\in \\lamax(V^*)$\nwe define\n\\begin{equation} \\Bigl ( F (u \\otimes f )\\Bigr ) (z) = \\frac{v}{(2 \\pi)^{n\/2}}\n\\int_{\\phi \\in V} f(\\phi) e^{- i z(\\phi)} u , \\end{equation}\nwhere the element\n$v\\in \\lamax (V) $ satisfies $u(v) = 1 $ under the\nnatural pairing $\\lamax(V^*) \\cong \\Bigl (\\lamax (V) \\Bigr)^*.$\n(The normalization has been chosen so that\n$$ \\tilde{f} (\\phi) = F (F \\tilde{f}) (- \\phi) $$\nfor any $\\tilde{f} \\in \\Omega^{\\rm max}(V)$.)\nFor notational convenience\nwe shall often ignore this subtlety\nand identify $\\liek, \\liet$ with $\\lieks, \\liets$\nunder the invariant inner product $\\inpr{\\cdot, \\cdot}$:\nwe shall also suppress the exterior powers of\n$\\liek$ and $\\liet$ and write $\\fk: \\dist(\\liek) \\to\n\\dist (\\lieks)$, $\\ft: \\dist(\\liet) \\to \\dist(\\liets)$.\nFurther, although we shall work with functions whose definition\ndepends on the choice of the element $[d \\phi] \\in \\lamax(\\lieks)$\n(associated to the inner product), some of our end results\ndo not depend on this choice\\footnote{The statement of\nTheorem \\ref{t8.1},\nfor instance, does not depend on\nthe invariant\ninner product $\\inpr{\\cdot, \\cdot}$.}\nand the use of such\nfunctions is just a notational convenience.\n\n\nA fundamental property of the Fourier transform\nis that it preserves the $L^2$ inner product:\n\\begin{lemma} \\label{l3.2} {\\bf [Parseval's Theorem]}(\\cite{hor},\nSection 7.1)\nIf $f: \\liek \\to {\\Bbb C }$ is a tempered distribution\nand $g: \\liek \\to {\\Bbb C }$ is a Schwartz function then\n$F_K f: \\liek \\to {\\Bbb C }$ is also a tempered distribution and\n$F_K g: \\liek \\to {\\Bbb C }$ a Schwartz function, and we have\n$$ \\intk \\overline{g(\\phi)}\n f (\\phi) [d \\phi] = \\tintk \\overline{(F_K g)(z) }\n(F_K f)(z) \\, [d z], $$\n$$ \\intt \\overline{g(\\psi)}\n f (\\psi) [d \\psi] = \\tintt \\overline{(F_Tg)(y) }\n(F_T f)(y) \\, [d y]. $$\n\\end{lemma}\nWe note also that if\n$g_\\epsilon: \\liek \\to {\\Bbb R }$ is the\nGaussian defined by $g_\\epsilon(\\phi) = e^{-\\epsilon \\inpr{\\phi, \\phi}\/2 }\n$, then\n\\begin{equation} \\label{3.5} (F_K g_\\epsilon) (z) = \\frac{1}{\\epsilon^{s\/2} } e^{- \\inpr{z,z}\n\/{2 \\epsilon}\n} = \\frac{1}{\\epsilon^{s\/2} } \\gsoe(z), \\phantom{bbbbb}\n(F_T g_\\epsilon ) (y) = \\frac{1}{\\epsilon^{l\/2} } e^{- \\inpr{y,y} \/{2 \\epsilon}\n} = \\frac{1}{\\epsilon^{l\/2} } \\gsoe(y). \\end{equation}\n\nWe have also that\n\\begin{lemma} \\label{l3.2'} The symplectic volume form\n$d \\Om^S_\\phi$ at a point $\\phi$ in the\norbit $K \\cdot \\psi$\n through $\\psi \\in \\liek$\nis related to the Riemannian volume form\n$d \\Om^R_\\phi$ (induced by\nthe metric on $\\liek$)\nby\n$$d \\Om^R_\\phi = \\nusym(\\psi) d \\Om^S_\\phi.$$\n\\end{lemma}\n\\Proof The symplectic form is\n $K$-invariant\nand is given at the point $\\psi \\in \\liet_+$ in the orbit\n$K \\cdot \\psi$\n(for $\\xi, \\eta \\in \\lietp$ giving rise to tangent\nvectors $[\\xi,\\psi], $ $[\\eta, \\psi]$ to the orbit) by\n\\begin{equation} \\label{3.7}\n\\om([\\xi,\\psi], [ \\eta,\\psi]) = \\inpr{[ \\xi,\\psi], \\eta }\n= \\inpr{\\psi, [ \\eta,\\xi] }. \\end{equation}\nIn the notation of Lemma \\ref{l3.1}, the symplectic\nvolume form evaluated on the tangent vectors\n$[ X_\\gamma,\\psi], $ $[ Y_\\gamma,\\psi]$ is given by\n$\\prod_{\\gamma > 0} \\om ([ X_\\gamma,\\psi], [ Y_\\gamma,\\psi] ).$\nBut $\\om ([X_\\gamma,\\psi], [ Y_\\gamma,\\psi] ) = \\inpr{[ X_\\gamma,\\psi], Y_\\gamma} $\n$ = \\gamma(\\psi)$, from which (comparing with the proof of\nLemma \\ref{l3.1}) the Lemma follows. $\\square$\n\nWe shall use this Lemma to prove the following\nLemma relating Fourier\ntransforms on $\\liek$ to those on $\\liet$:\n\\begin{lemma} \\label{l3.3}\nLet $f \\in \\dist(\\liek)$ be $K$-invariant,\nand let $\\nusym$ be defined\nby (\\ref{3.2}). Then\n$$\\ft(\\nusym f) = \\nusym \\fk(f)$$\nas distributions on $\\liet$.\n\\end{lemma}\n\\Proof $$(\\fk f) (z) = \\frac{1}{(2 \\pi)^{s\/2} } \\intk e^{-i\n\\evab{\\phi}{z} } \\, f(\\phi) [d \\phi] $$\n\\begin{equation} \\label{3.6}\n= \\frac{1} {(2 \\pi)^{s\/2} } \\int_{\\psi \\in \\liet_+}\n\\int [d \\psi] f(\\psi) \\: \\int_{\\phi \\in K \\cdot \\psi}\ne^{- i \\evab{\\phi}{z} } d \\Om^R_\\phi \\end{equation}\n(where $\\liet_+$ denotes the fundamental Weyl chamber).\n\nWe have from Lemma \\ref{l3.2'} that\n$d \\Om^R_\\phi = \\nusym(\\psi) d \\Om^S_\\phi$.\nThus we have\n\\begin{equation} \\label{3.8}(F_K f)(z) = (2 \\pi)^{-s\/2} \\int_{\\psi \\in \\liet_+}\n[d \\psi] f (\\psi) \\nusym(\\psi) \\int_{\\phi \\in K \\cdot \\psi}\ne^{- i \\evab{\\phi}{ z} } d \\Om^S_\\phi. \\end{equation}\n\nNow the integral over the coadjoint orbit may be computed\nby the Duistermaat-Heckman theorem \\cite{DH} applied to the\naction of $T$ on the orbit $K \\cdot \\psi$\n(or equivalently as a consequence\nof the\nabelian localization theorem, Theorem \\ref{t2.1}): we have\n(see e.g. \\cite{BGV} Theorem 7.24)\n\\begin{equation} \\label{3.9}\n\\int_{\\phi \\in K \\cdot \\psi} e^{- i \\evab{\\phi}{ z} }\n\\, d \\Om^S_\\phi =\n\\frac{(2 \\pi)^{(s-l)\/2} } {\\nusym(z) } \\sum_{w \\in W} e^{- i \\evab{w \\psi}{ z}\n}\n(\\det w). \\end{equation}\nThis is a well known formula due originally to Harish-Chandra\n(\\cite{Harish}, Lemma 15).\n(Notice that the $z$ in (\\ref{3.9}) plays the role of the\n$\\psi$ in Theorem \\ref{t2.1}, while the $\\psi$ in\n(\\ref{3.9}) specifies the orbit.)\nNow since $\\nusym(w \\psi) = (\\det w) \\nusym(\\psi), $ we may replace\nthe integral over $\\liet_+$ by an integral over $\\liet$: in other\nwords we have\n\\begin{equation} \\label{3.10}\n\\nusym(z) (F_K f) (z) = (2 \\pi)^{- l\/2} \\int_{\\psi \\in \\liet}\n[d \\psi] \\, f(\\psi) \\nusym(\\psi) \\eminevb{\\psi}{ z} = F_T(\\nusym f) (z).\n\\phantom{bbbbb} \\square \\end{equation}\n\n\\newcommand{\\ims}{i^{-s} }\n\nApplying this to the Gaussian\n$\\gse(\\psi) = e^{-\\epsilon \\inpr{\\psi, \\psi}\/2 } $ we have\n\\begin{corollary} \\label{c3.4}\n$$\nF_T(\\gse \\nusym) (y) = \\frac{1}{\\epsilon^{s\/2} } \\nusym(y) e^{- \\inpr{y,y} \/{2 \\epsilon} }\n= \\frac{1}{\\epsilon^{s\/2} } \\nusym(y) \\gsoe(y). $$\n\\end{corollary}\n\nWe shall also need\nthe following result which occurs\nin the work of Guillemin, Lerman, Prato\nand Sternberg\n concerning Fourier transforms of\na class of functions on\n$\\liets$. This result will be applied to functions\nappearing in the abelian localization formula (\\ref{2.4}).\n\\begin{prop} \\label{p3.5}\n{\\bf (a)} (see \\cite{JGP}, section 3.2 of \\cite{GLS},\nand \\cite{GP})\nDefine $h(y) = H_{\\bar{\\beta} }(y + \\tau)$ for some\n$\\tau \\in \\liet$,\nwhere $H_{\\bar{\\beta} } (y) = \\,{\\rm vol}\\, \\{ (s_1, \\dots,\ns_N): s_i \\ge 0, \\phantom{a} y = \\sum_j s_j \\beta_j \\}$ for\nsome $N$-tuple $\\bar{\\beta} = $\n$\\{ \\beta_1, \\dots, \\beta_N \\}$ , $\\beta_j \\in \\liets$,\nsuch that\nthe $\\beta_j$ all lie in the interior of\n some half-space of $\\liets$.\nThus $H_{\\bar{\\beta} } $ is a piecewise polynomial\nfunction supported on the cone $C_\\barb =\n\\{ \\sum_j s_j \\beta_j \\, | \\, s_j \\ge 0 \\}. $\nThen the Fourier transform of $h$ is given for\n$\\psi$ in the complement of the hyperplanes\n$\\{ \\psi \\in \\liet| {\\beta_j}({ \\psi}) = 0 \\}$ by\nthe formula\n\\begin{equation} \\label{3.10'} F_T h(\\psi) = \\frac{\\epinev{\\tau}{ \\psi} }\n{i^N \\prod_{j = 1}^N \\beta_j (\\mar \\psi) }. \\end{equation}\n\n\\noindent{\\bf(b)} (see Section 2 of \\cite{JGP}\nand (2.15) of \\cite{GP}) The function $H_{\\bar{\\beta}} (y) $ is also given\nas\n$$H_{\\bar{\\beta}} (y) = H_{\\beta_1} * H_{\\beta_2} * \\dots\n* H_{\\beta_r}, $$\nwhere for $\\beta \\in {\\rm Hom}({\\Bbb R }^l,{\\Bbb R })$ we have $H_\\beta = (i_\\beta)_* dt$,\ni.e. $H_\\beta$ is the pushforward of the Euclidean\nmeasure $dt$ on ${\\Bbb R }^+$ under the map $i_\\beta: {\\Bbb R }^+ \\to {\\Bbb R }^l$\ngiven by $i_\\beta(t) = \\beta t$. Here, $*$ denotes convolution.\n\n\\noindent{\\bf (c)} (see Section 2 of \\cite{JGP}) The function\n$H_\\barb $ satisfies the differential equation\n$$ \\prod_{j = 1}^N \\beta_j (\\partial\/\\partial y) H_\\barb(y) =\n\\delta_0(y) $$\nwhere $\\delta_0$ is the Dirac delta distribution.\n\n\\noindent{\\bf (d)} (see Proposition 2.6 of \\cite{JGP})\nThe function $H_\\barb$ is smooth at any\n$y \\in U_\\barb$, where $U_\\barb$ are the\npoints in $\\liets$ which are not in any cone\nspanned by a subset of $\\{\\beta_1, \\dots, \\beta_N \\} $ containing\nfewer than $l$ elements.\n\n\n\\end{prop}\n\n{ \\setcounter{equation}{0} }\n\\section{Reduction to a piecewise polynomial function}\n\n\tIn this section we apply the results stated in\nSection 3 to reduce $\\ie$ to the form given in Proposition \\ref{p4.2},\nas the integral over $y \\in \\liets$ of a\nGaussian $\\gtsoe(y) = \\gsoe(y)\/((2 \\pi)^s \\wn \\,{\\rm vol}\\, ( T) \\epsilon^{s\/2} ) $\ntimes a function\n$Q(y)$ which is $D_\\nusym R(y)$\nwhere $D_\\nusym$ is a differential operator\nand $R$ is a piecewise polynomial function.\nAs a byproduct we obtain also a generalization of\nTheorem 2.16 of \\cite{GP}: we may relax the hypothesis of \\cite{GP}\nthat\nthe action of the maximal torus $T$ have isolated fixed points.\n\n Two of our main results related to Witten's work in\n\\cite{tdg}\nare Theorem \\ref{t4.1} and \\ref{t4.3}: these are stated in this section.\nThe proof of Theorem \\ref{t4.3} will be given in Section 5. It\ntells us that the cohomological contribution $\\eeth[\\xred]$\ngiven in Witten's Theorem \\ref{t1.2} for the zero locus\nof the moment map is given by the integral\nover $y \\in \\liets$ of $\\gtsoe(y)$ times a polynomial\n$Q_0(y)$ which is equal to $Q$ near $y = 0$.\nTheorem \\ref{t4.1} is our version of the asymptotic\nestimates given in Witten's Theorem \\ref{t1.1}, and will be\nproved in Section 6 below. Theorem \\ref{t7.1} in Section 7\nextends Theorems \\ref{t4.1} and \\ref{t4.3} to more general\nequivariant cohomology classes.\n\n\n\nWe assume throughout the rest of the\npaper that $K$ acts on $X$ in a Hamiltonian fashion,\nand that $0$ is a regular value of the moment map\n$\\mu$ for the $K$ action.\nThis is equivalent to the assumption that\n $K$ acts on $\\mu^{-1}(0)$ with finite stabilizers, and it\n implies that $\\mu^{-1}(0)$ is a smooth manifold.\n Under these\nhypotheses, the space $\\xred = \\mu^{-1}(0)\/K$ is a $V$-manifold or\norbifold\n(see \\cite{kaw}) and $P = \\mu^{-1}(0) \\to\n\\mu^{-1}(0)\/K $ is a $V$-bundle: we have a class\n$\\Theta \\in H^4 (\\xred) $ which represents the class\n$-\\inpr{\\phi, \\phi}\/2 \\in H^4_K(\\mu^{-1}(0) ) $\n$\\cong H^4(\\zloc\/K)$,\nand which is a four-dimensional characteristic class\nof the bundle $P \\to \\xred$.\n\nIn \\cite{Ki1} it is proved that the set of\ncritical points of the function $\\rho = |\\mu|^2: X \\to {\\Bbb R }$\nis a disjoint union of closed subsets $C_\\beta$ in\n$X$ indexed by a finite subset ${\\mbox{$\\cal B$}}$ of $\\liet$.\nIn fact if $\\liet_+$ is a fixed positive Weyl\nchamber for $K$ in $\\liet$ then $\\beta \\in {\\mbox{$\\cal B$}}$ if and only\nif $\\beta \\in \\liet_+$ and $\\beta$ is the closest point to $0$\nof the convex hull in $\\liet$ of some nonempty\nsubset of the finite set $\\{ \\mu_T(F): F \\in {\\mbox{$\\cal F$}}\\}$,\ni.e. the image under $\\mu_T$ of the set of fixed\npoints of $T$ in $X$. Moreover if $\\beta \\in {\\mbox{$\\cal B$}}$\nthen $$C_\\beta = K(Z_\\beta \\cap \\mu^{-1}(\\beta))$$\nwhere $Z_\\beta$ is the union of those connected components\nof the set of critical points of the function $\\mu_\\beta$\ndefined by $\\mu_\\beta (x) = \\eva{\\mu(x)}{ \\beta} $\non which $\\mu_\\beta$ takes the value $|\\beta|^2$. Note that\n$C_0 = \\mu^{-1}(0) $ and in general the value\ntaken by the function $\\rho = |\\mu|^2$\non the critical set $C_\\beta$ is just $|\\beta|^2$.\n\n\n\n\nWe shall prove the following version\nof Witten's nonabelian localization theorem, for\nthe integral $\\ie$ defined in (\\ref{3.1}) with\nthe\nclass $\\si = e^{\\iins \\bom} $ defined by (\\ref{2.0''}):\n\\begin{theorem}\n\\label{t4.1} For each $\\beta \\in {\\mbox{$\\cal B$}}$ let $\\rho_\\beta = |\\beta|^2$\n(this is the critical value\nof the function $\\rho = |\\mu|^2: X \\to {\\Bbb R }$ on the critical\nset $C_\\beta$ when this set is nonempty).\nThen\nthere exist functions $h_\\beta: {\\Bbb R }^+ \\to {\\Bbb R } $ such that\nfor some $N_\\beta \\ge 0$,\n$\\epsilon^{N_\\beta} h_\\beta(\\epsilon)$ remains bounded as $\\epsilon \\to 0^+$, and\nfor which\n$$|\\ie - e^{\\epsilon \\Theta} e^\\om [\\xred] | \\le\n\\sum_{\\beta \\in {\\mbox{$\\cal B$}} - \\{0\\} }\n e^{- \\rho_\\beta \/{2 \\epsilon} } \\, h_\\beta(\\epsilon). $$\n\n\\end{theorem}\n\n\\noindent{\\em Remark:} The estimate given in Theorem\n\\ref{t4.1} is {\\em weaker} than Witten's estimate\n(Theorem 1.2) since $|\\beta|^2 $ is not in fact a\ncritical value of $|\\mu|^2 $ when $C_\\beta$ is\nempty.\nNevertheless in many interesting cases all the $C_\\beta$\nare nonempty, and our estimate then coincides with Witten's.\n\n\nTo prove this result, we shall rewrite $\\ie$ using Lemma\n\\ref{l3.1}:\n\\begin{equation} \\label{4.1} \\ie = \\frac{1}{(2 \\pi i)^s \\wn \\,{\\rm vol}\\, (T) }\n \\: \\intt [d \\psi] \\, \\Bigl (\n\\gse(\\psi) \\: \\nusym(\\psi) \\Bigr ) \\:\n\\Bigl ( \\: \\nusym(\\psi) (\\pist \\sigma ) (\\psi) \\Bigr ). \\end{equation}\nNow we apply Lemma \\ref{l3.2} to get\n\\begin{equation} \\label{4.2}\n\\ie = \\frac{1}{(2 \\pi i)^s \\wn \\,{\\rm vol}\\, (T) }\n\\tintt [dy] \\Bigl ( F_T (g_\\epsilon \\nusym) (y) \\Bigr )\n\\Bigl ( F_T (\\nusym \\, \\pist \\si ) (y) \\Bigr ). \\end{equation}\nApplying Corollary \\ref{c3.4} we have\n\\begin{equation} \\label{4.3}\n\\ie = \\frac{1}{(2 \\pi i)^s \\wn \\,{\\rm vol}\\, (T) \\epsilon^{s\/2} }\n\\tintt [dy] \\nusym(y) e^{- \\inpr{y,y}\/{2 \\epsilon} } \\,\nF_T ( \\nusym \\pist \\si) (y). \\end{equation}\n\n\\newcommand{\\bwd}{\\lasub}\n\\newcommand{\\cf}{C_F}\n\\newcommand{\\cfl}{C_{F,\\lasub } }\n\\newcommand{\\dcf}{\\check{C}_{F,\\lasub} }\n\n\nFollowing Guillemin, Lerman and Sternberg \\cite{JGP},\nwe may use the abelian localization formula (Theorem\n\\ref{t2.1})\nto give a formula for $F_T ( \\pist \\si)$ where $\\si = e^{\\iins \\bom}$,\nand from it obtain a formula\nfor $F_T (\\nusym \\pist \\si)$.\nIn terms of the notation of Lemma \\ref{l2.2}, we choose\na component $\\bwd$ of the set $\\cap_{F,j} \\Bigl \\{\n\\psi \\in \\liet:$ $ \\bfj(\\psi) \\ne 0 \\Bigr \\}, $\nwhere $\\beta_{F, j}$ are the weights of the action\nof $T$ on the normal bundle to a component $F$ of the\nfixed point set. Thus $\\bwd$\nis a cone in $\\liet$. If we denote by $\\cf = \\cfl$\nthe component of $\\cap_j \\{ \\psi \\in \\liet:\n$ $ \\bfj (\\psi) \\ne 0 \\} $ containing $\\bwd$, then\n$\\bwd = \\cap_F \\cfl$. Also, $\\bfj \\in \\liets$ lies\nin the dual cone $\\dcf$ of $\\cfl$: indeed, this dual\ncone is simply the cone $\\dcf = \\{\n\\sum_j s_j \\bfj: s_j \\ge 0 \\}. $\nWe then define\n$\\sigma_\\fj = {\\rm sign} \\bfj(\\xi) $ for any\n$\\xi \\in \\bwd$, and $\\bfjw =\n\\sigma_\\fj \\bfj$. Then we set $k_F(\\alpha) =\n\\sum_{j, \\sigma_\\fj = - 1} n_\\fj(\\alpha)$.\n\nWe define a function $\\hh: \\liets \\to {\\Bbb C }$\nby\n\\begin{equation} \\label{4.g}\n\\hh(y) = \\sum_{F \\in {\\mbox{$\\cal F$}}} \\sum_{\\alpha \\in {\\mbox{$\\cal A$}}_F}\n(-1)^{k_F(\\alpha) } H_{\\bar{\\gamma_F}(\\alpha) } (-y + \\mu_T(F) )\n\\int_F (e^{i\\om} \\tilde{c}_{F,\\alpha}) . \\end{equation}\nHere as before ${\\mbox{$\\cal F$}}$ is the set of components\n$F$ of the fixed point set of $T$ and\nthe ${\\mbox{$\\cal A$}}_F$ are the indexing sets which appeared\nin Lemma \\ref{l2.2}. If $\\alpha \\in {\\mbox{$\\cal A$}}_F$ then\n$\\bar{\\gamma_F}(\\alpha)$ consists of the elements\n$\\bfjw$ where each $\\bfjw$ appears with multiplicity\n$n_\\fj(\\alpha) $.\nThen\n$H_{\\bar{\\gamma_F}(\\alpha) } $ is as defined in Proposition \\ref{p3.5}.\nThe $\\tilde{c}_{F,\\alpha} \\in H^*(F) $ are related to\nthe $c_{F,\\alpha} $ in (\\ref{2.m1}), in that\n\\begin{equation} \\label{4.004} c_{F, \\alpha}(\\psi) = e^{i\\om} e^{i \\eva{\\mu_T(F)}{ \\psi} }\n\\tilde{c}_{F,\\alpha}. \\end{equation}\n\n\nWe then have the following Theorem, which in the case\nwhen the action of $T$ has isolated fixed points is the main\ntheorem\nof Section 3 of the paper \\cite{JGP}\nof Guillemin, Lerman and Sternberg.\nFor the most part our proof is a direct extension\nof the proof given in that paper; the major difference is in\nthe use of the abelian localization theorem rather than\nstationary phase.\n\n\n\\begin{theorem} \\label{t4.1'} The (piecewise polynomial)\nfunction\n$\\hh$ given in (\\ref{4.g}) is identical\nto the distribution $ \\ggh = F_T ( \\pist e^{\\iins \\bom}) $.\n\\end{theorem}\n\\Proof We first\n apply the abelian localization formula (\\ref{2.2})\nto $\\pist \\si$.\n Then\nthe formula obtained from Lemma \\ref{l2.2} for\n$\\pist \\si$ is\n\\begin{equation} \\label{4.3p} \\pist \\si =\n\\sum_{F \\in {\\mbox{$\\cal F$}}} \\rf, \\phantom{bbbbb} \\rf = \\sum_{\\alpha \\in {\\mbox{$\\cal A$}}_F} \\tau_{F, \\alpha} , \\end{equation}\n\\begin{equation} \\label{4.03p}\\tau_{F, \\alpha} =\n (-1)^{k_F(\\alpha) } \\frac{ \\epinevb{\\psi}{ \\mu_T(F)}\n\\int_F (e^{\\iins\\om} \\tilde{c}_{F,\\alpha} ) }\n{\\prod_j \\Bigl ( \\bfjw (\\mar \\psi) \\Bigr )^{{n}_\\fj(\\alpha)} } , \\end{equation}\nwhere $\\mu_T $, the moment map for the $T$ action, is simply\nthe projection of $\\mu$ onto $\\liet$\nand the $ \\bfj $ are the weights of the $T$ action. Recall that\nthe quantity $\\bfjw$ is $\\bfj$ if $\\bfj (\\xi) > 0 $\nand $- \\bfj$ if $\\bfj (\\xi) < 0 $.\nThe class $\\tilde{c}_{F, \\alpha} \\in H^*(F)$ is equal to\nsome characteristic classes of\nsubbundles of the normal bundle $\\nu_F$; it is independent\nof $\\psi$.\n\nNotice that each $\\bfjw$ $\\in \\liets$\nlies in the half space\n$\\{ y \\in \\liets \\, | y( \\xi) > 0 \\}$, for any $\\xi \\in \\bwd$.\nThe expression (\\ref{4.03p}) is hence\nof the form appearing on the right hand side\nof (\\ref{3.10'}), up to multiplication by a\nfactor independent of $\\psi$.\nThe conclusion of the proof goes, as in Section 3 of \\cite{JGP},\nby applying a lemma about distributions (see Appendix A of \\cite{GP}):\n\\begin{lemma} \\label{l4} Suppose $\\gggh$ and $\\hhh$ are\ntwo tempered distributions on ${\\Bbb R }^l$ such that:\n\\begin{enumerate}\n\\item $F_T \\gggh - F_T \\hhh$ is supported on a finite union\nof hyperplanes.\n\\item There is a half space $\\{ y \\, | \\, \\inpr{y,\\zeta} > k_0 \\}$\ncontaining the support of $\\hhh - \\gggh$.\n\\end{enumerate}\nThen $\\gggh = \\hhh$.\n\\end{lemma}\nHere we apply the lemma to $\\hhh$ as given in\n(\\ref{4.g}) and $\\gggh = F_T ( \\pist e^{\\iins \\bom} ) $.\nThe first hypothesis is satisfied because we know from Proposition\n\\ref{p3.5} that $F_T \\hh$ is given by the formula (\\ref{4.3p})\non the complement of the hyperplanes\n$\\{ \\psi \\, | \\, \\bfjw ( \\psi) = 0 \\}$; but this\nis just the formula for $F_T \\ggh = \\pist e^{\\iins \\bom}$.\nFurther, $\\hh$ is supported in a half space since all the\nweights $\\bfjw$ satisfy $\\bfjw(\\xi) > 0$ for any $\\xi \\in \\bwd$, while\nthe support of $\\ggh$ is\ncontained in the compact set $\\mu_T(X)$ (see Section 5 below).\nTherefore the support of $H-G$ is contained\nin a half space of the form $\\{ y: \\inpr{y,\\xi} > k_0 \\}$\nfor some $k_0$.\nThis completes the proof of Theorem \\ref{t4.1'}. $\\square$\n\n\n\n\nDefine\n\\begin{equation} \\label{4.3pp}\nR(y) = F_T ( \\pist \\si) (y), \\end{equation}\nwhere $\\si = \\exp \\iins \\bom$.\nThen\n (\\ref{4.3}) and (\\ref{4.g}) give us the following\n\\begin{prop} \\label{p4.2}\nThe function $R$ is a piecewise polynomial function supported on\ncones each of which has apex at $\\mu_T(F)$ for some component\n$F$ of the fixed point set of $T$.\nLet $Q$ be the distribution defined by\n$$ Q(y) = \\nusym(y) D_\\nusym R(y) $$\nwhere\nthe differential operator $D_\\nusym$ is given by\n$$D_\\nusym = \\prod_{\\gamma> 0} (i \\gamma(\\partial\/\\partial y) )$$\nand $\\gamma$ runs over the positive roots (cf. (\\ref{3.2})).\nThen\n\\begin{equation} \\label{4.3ppp}\n\\ie = \\frac{1}{(2 \\pi i )^s \\wn \\,{\\rm vol}\\, ( T) \\epsilon^{s\/2} }\n\\tintt [dy] e^{- \\inpr{y,y}\/{2 \\epsilon} } Q(y). \\end{equation}\n\\end{prop}\n\\Proof It only remains\nto note that $\\ft (\\nusym \\pist \\si) = D_\\nusym \\ft (\\pist \\si), $\nwhere $D_\\nusym$ is defined above. $\\square$\n\n\\noindent{\\em Remark:} The formulas for $Q(y)$ obtained\nfrom (\\ref{4.3p}) will in general be different for\ndifferent choices of $\\bwd$.\n\n\n\nIn addition, certain formulas simplify if we impose\nthe additional assumption that at any point $x$ in a component\n$F$ of the fixed point set of the $T$ action,\nthe orthocomplement $\\lietp$ of $\\liet$ in $\\liek$\ninjects into the tangent space $T_x X$ under the infinitesimal\naction of $K$: in other words, that the stabilizer ${\\rm Stab} (x)$\nof $x$ is such that ${\\rm Stab}(x)\/T$ is a finite group.\nUnder this additional hypothesis,\nwe may indeed prove a somewhat stronger result.\n Notice that by Lemma \\ref{l2.2},\neach term (corresponding to a component $F$ in the fixed point\nset of $T$) in the localization\nformula for $\\pist \\si$ has a factor $\\efo(\\mar \\psi)$ in the denominator.\nNow\nfor $x \\in F$, the fibre $(\\nu_F)_x$ over $x$ of the normal bundle\nto $F$\nwill contain $ \\lietp \\cdot x$, the image of $\\lietp$\nunder the infinitesimal action of $K$. Under the additional assumption\nthat $\\lietp$ injects into $T_x X$,\nthe set of weights for $\\nu_F$ contains for each root $\\gamma > 0$\neither the root $\\gamma$ or the root $- \\gamma$: in other words,\n$\\efo (\\mar \\psi)$ is divisible by $\\nusym(\\psi)$. Thus from Lemma\n\\ref{l2.2} we obtain\nthe formula for\n$\\nusym(\\psi) \\pist \\si$:\n\\begin{equation} \\label{4.3pinj}\n\\nusym(\\psi) \\pist \\si = \\sum_{F \\in {\\mbox{$\\cal F$}}, \\alpha \\in {\\mbox{$\\cal A$}}_F}\n\\ttfa, \\end{equation}\n\\begin{equation} \\label{4.03pinj} \\ttfa =\n (-1)^{k_F(\\alpha) } \\frac{ \\epinevb{\\psi}{ \\mu_T(F)}\n }\n{\\prod_j \\Bigl ( \\bfjw (\\mar \\psi) \\Bigr )^{\\tilde{n}_\\fj(\\alpha)} }\n\\int_F ( e^{i \\om} \\tilde{c}_{F,\\alpha} ) . \\end{equation}\nHere, the notation is as in (\\ref{4.3p})\nand (\\ref{4.03p}) except that\n$\\tilde{n}_\\fj(\\alpha) = n_\\fj(\\alpha) $ if $\\bfj$ is not a\nroot, while $\\tilde{n}_\\fj(\\alpha) = n_\\fj(\\alpha) - 1$ if $\\bfj$ is a root.\n\n\n\n We may then use the abelian localization formula\nto give a formula for $F_T (\\nusym \\pist \\si)$ where $\\si = e^{\\iins \\bom}$.\nAs in (\\ref{4.g}),\nwe define a function $\\hh^\\nusym(y) $ for $y \\in \\liets$\nby\n\\begin{equation} \\label{4.ginj}\n\\hh^\\nusym(y) = \\sum_{F \\in {\\mbox{$\\cal F$}}} \\sum_{\\alpha \\in {\\mbox{$\\cal A$}}_F}\n(-1)^{k_F(\\alpha) } H_{\\hat{\\gamma_F}(\\alpha) } (-y +\\mu_T(F) )\n\\int_F e^\\omega \\tilde{c}_{F,\\alpha} . \\end{equation}\nThe notation is as in ({\\ref{4.g}) except that\neach $\\bfjw$ appears in $\\hat{\\gamma}_F(\\alpha)$ with multiplicity\n$n_\\fj(\\alpha) $ if it is not a root and $n_\\fj(\\alpha) - 1 $ if it is a\nroot. The function\n$H_{\\hat{\\gamma_F}(\\alpha) } $ is then as defined in Proposition \\ref{p3.5}.\n\n\n\nIn the case\nwhen the action of $T$ has isolated fixed points, the theorem\n\\ref{t4.1'inj} below\nis the main\nresult\n(Theorem 2.16) of Part I of the paper \\cite{GP} of Guillemin\nand Prato. For the most part our proof translates directly from\nthe proof given in that paper, except that we use\nthe abelian localization theorem in place of\nstationary phase.\n\n\n\\begin{theorem} \\label{t4.1'inj}\nSuppose\nthat $\\lietp$ injects into $T_x X$ for all fixed points\n$x$ of the action of $T$.\nThen the distribution\n$\\hh^\\nusym$ given in (\\ref{4.ginj}) is identical\nto the distribution $ \\ggh = F_T (\\nusym \\pist e^{\\iins \\bom}) $.\n\\end{theorem}\n\\Proof This theorem is proved in exactly\nthe same way as Theorem \\ref{t4.1'}.\nThe conclusion of the proof goes, as in the\nproof of Theorem 2.16 of \\cite{GP}, by applying\nLemma \\ref{l4} directly to\n$\\hh^\\nusym$ as given in\n(\\ref{4.ginj}) and $\\gggh = F_T (\\nusym \\pist e^{\\iins \\bom} ) $.\n $\\square$\n\n\n\n\n\nIn particular we have the following\n\\begin{prop} \\label{p4.2inj}\nSuppose\nthat $\\lietp$ injects into $T_x X$ for all fixed points\n$x$ of the action of $T$.\nDefine\n\\begin{equation} \\label{4.3ppinj}\nQ(y) = \\nusym(y) F_T (\\nusym \\pist \\si) (y), \\end{equation}\nso that\n\\begin{equation} \\label{4.3pppinj}\n\\ie = \\frac{1}{(2 \\pi i )^s \\wn \\,{\\rm vol}\\, ( T) \\epsilon^{s\/2} }\n\\tintt [dy] e^{- \\inpr{y,y}\/{2 \\epsilon} } Q(y). \\end{equation}\nThen $Q$ is a piecewise polynomial function supported on\ncones each of which has apex at $\\mu_T(F)$ for some component\n$F$ of the fixed point set of $T$.\n\\end{prop}\n\n\n\nWe now drop the hypothesis that $\\lietp$ injects into $T_x X$\nat the fixed points $x$ of the action of $T$, and\nreturn to the general situation described in\nProposition \\ref{p4.2}.\nIt will follow from (\\ref{5.6}) that $Q$ is smooth near\n$y = 0$: thus in particular there is a polynomial $Q_0$ which\nis equal to $Q$ near $y = 0$. Of course $Q_0 = D_\\nusym R_0$ where\n$R_0$ is the polynomial which is equal to $\\ft (\\pist \\si)$ near\n$y = 0$.\nIn the next section we shall provide an alternative\ndescription of $Q_0$ and prove\n\\begin{theorem}\n\\label{t4.3}\n$$\n\\ie_0 \\;\\: {\\stackrel{ {\\rm def} }{=} } \\;\\:\n\\frac{1}{ (2 \\pi i)^s \\wn \\,{\\rm vol}\\, ( T) \\epsilon^{s\/2} }\n \\tintt [dy] e^{- \\inpr{y,y}\/{2 \\epsilon} }\n\\: Q_0(y) = e^{\\epsilon \\Theta} e^{i \\om_0} [\\xred]. $$\n\\end{theorem}\nThis tells us that the contribution to\n$\\ie$ from $\\mu^{-1}(0)\/K$ is obtained by integrating\n$Q_0$ rather than $Q$ (weighted by the Gaussian $\\tilde{g}_{\\epsilon^{-1}}$\ndefined in the first paragraph of this Section)\nover $y \\in \\liets$.\n\n\n\n\n{ \\setcounter{equation}{0} }\n\\section{The proof of Theorem 4.7}\n\nThis section gives the proof of Theorem \\ref{t4.3}, which\nidentifies $\\eeth [\\xred]$ with the integral of\na Gaussian $\\gtsoe$ times a polynomial $Q_0$.\nThe key step in the proof is\nthe well known result Proposition \\ref{p5.2} below, which\ngives a normal form for the symplectic form, the $K$ action\nand the moment map in a neighbourhood ${\\mbox{$\\cal O$}}$ of $\\zloc$.\nWe first recast the distribution $Q$ in terms of an integral\nover $X$ (Proposition \\ref{p5.1}), so that\n$Q(y)$ is given by the integral over $X$ of a distribution\nsupported where $\\mu$ takes the value $y$. (This step occurs\nalso in the proof \\cite{DH} of the Duistermaat-Heckman theorem.)\nHence, for sufficiently small $y$, this distribution\nis supported in ${\\mbox{$\\cal O$}}$ and we may do the integral over\n$X$ to obtain the value of the polynomial $Q_0 $ which\nis equal to $Q $ near $0$.\nThis turns out to be given by an integral over $\\xred$ involving\nthe symplectic form and the curvature of a bundle\nover $\\xred$ (see (\\ref{5.6})).\nFinally, we multiply $Q_0$\nby the Gaussian $\\gtsoe$ and integrate over $\\liet$\nto see that the result is\n $\\eeth [\\xred]$.\n\n\n\\begin{prop} \\label{p5.1}\n$Q(y) = \\nusym^2(y) (2 \\pi)^{s\/2} \\int_{x \\in X}\ne^{i \\om} \\delta (y - \\mu(x) ) $,\nwhere $\\delta$ denotes the (Dirac) delta distribution.\n\\end{prop}\n\\Proof We have by Lemma \\ref{l3.3} that\n$$Q = \\nusym F_T (\\nusym \\pist \\si ) =\n\\nusym^2 F_K(\\pisk \\si) ,$$\nso that\n$$ Q(y) = \\frac{\\nusym^2 (y) }{(2 \\pi)^{s\/2} }\n \\intk [d \\phi] \\, e^{-i \\evab{\\phi}{ y} }\n\\int_{x \\in X} e^{i \\om} e^{ i \\eva{\\mu(x)}{ \\phi} } \\, $$\n \\begin{equation} \\label{5.1}\n= \\nusym^2 (y) (2 \\pi)^{s\/2} \\int_X e^{i \\om} \\delta(\\mu - y). \\square \\end{equation}\n\nWe would like to study this for $|y| < h $ for sufficiently\nsmall $h > 0$. Now there is a neighbourhood of $\\mu^{-1}(0)$\non which the symplectic form is given in a standard way\nrelated to the symplectic form $\\om_0$ on $\\xred$: this\nfollows from the coisotropic embedding theorem\n(see sections 39-41 of \\cite{STP}).\n\\begin{prop} \\label{p5.2} {\\bf (Gotay\\cite{gotay}, Guillemin-Sternberg\n\\cite{STP}, Marle \\cite{marle})}\nAssume $0$ is a regular value of $\\mu$ (so that $\\mu^{-1}(0) $\nis a smooth manifold and $K$ acts on $\\mu^{-1}(0) $\nwith finite stabilizers).\nThen there is a neighbourhood ${\\mbox{$\\cal O$}} \\cong \\mu^{-1}(0) \\times\n\\{ z \\in \\lieks, |z| \\le h \\} $\n$\\subseteq \\mu^{-1}(0) \\times \\lieks$ of $\\mu^{-1} (0)$ on which the\nsymplectic form is given as follows. Let\n$P \\;\\: {\\stackrel{ {\\rm def} }{=} } \\;\\: \\mu^{-1}(0) \\stackrel{q}{\\to} \\xred $\nbe the orbifold principal $K$-bundle given by\nthe projection map $q: \\zloc \\to \\zloc\/K$,\n and let $\\theta$ $ \\in \\Om^1(P) \\otimes \\liek$\nbe a connection\nfor it. Let $\\omr$ denote the induced symplectic form on\n$\\xred$, in other\nwords $q^* \\om_0 = i_0^* \\om$.\nThen if we define a 1-form\n$\\tau$ on ${\\mbox{$\\cal O$}}\\subset P \\times \\lieks$ by\n$\\tau_{p,z} = z(\\theta)$ (for $p \\in P$ and $z \\in \\lieks$),\n the symplectic form on ${\\mbox{$\\cal O$}}$\nis given by\n\\begin{equation} \\label{5.2} \\om = q^* \\omr + d \\tau. \\end{equation}\nFurther, the moment map on ${\\mbox{$\\cal O$}} $\nis given by $\\mu (p, z) = z$.\n\\end{prop}\n\n\\noindent{\\em Proof of Theorem \\ref{t4.3}:}~\nWe assume for simplicity of notation that $K$\nacts freely on $\\mu^{-1}(0)$, but all of the following\nmay be transferred to the case when $K$ acts with finite\nstabilizers by introducing $V$-manifolds or orbifolds (see \\cite{kaw}).\nIn other words, we work locally on finite covers\nof subsets of $\\mu^{-1}(0)$ and $\\mu^{-1}(0)\/K$, where the\ncovering group is the stabilizer of the $K$ action at a\npoint $x \\in \\mu^{-1}(0)$.\n\n\nWhen $|y| < h$ and $h$ is sufficiently small,\nthe distribution $\\delta(\\mu(x) - y)$\nis supported in ${\\mbox{$\\cal O$}}$, so we may compute\n$Q_0(y)$ from (\\ref{5.1}) by restricting to ${\\mbox{$\\cal O$}}$.\nWe have\n\\begin{equation} \\label{5.3}\nQ_0(y) = (2 \\pi)^{s\/2} \\nusym^2(y) \\int_{(p, z') \\in P \\times \\lieks}\ne^{i \\om} \\delta(y - z') \\end{equation}\n\\begin{equation} \\label{5.4}\n \\phantom{a} = (2 \\pi)^{s\/2} \\nusym^2(y)\n\\int_{(p, z') \\in P \\times \\lieks}\n\\exp i(q^* \\om_0 + \\evab{d \\theta}{ z'}) \\exp i\\evab{\\theta}{ dz'} \\delta(y - z')\n\\end{equation}\nNow the term in $\\exp i \\evab{\\theta}{ dz'} $ which contributes\nto the integral (\\ref{5.4}) is $i^s \\Om \\,[dz'] $\nwhere $[dz'] $ is the volume form on $\\liek$\n(since all factors $d z'_1 \\dots {dz'}_l$ must appear in\norder to get a contribution to the integral).\nHere, $\\Om = \\prod_{j = 1}^s \\theta^j$ (for $j$ indexing an\northonormal basis of $\\liek$ and $\\theta^j$ the\ncorresponding components of the connection\n$\\theta$) is a form integrating to $ \\,{\\rm vol}\\, (K)$\nover each fibre of $P \\to \\xred$.\n\nDoing the integral over $z' \\in \\lieks$, we get\n\\begin{equation} \\label{5.5}\nQ_0(y) = i^s \\nusym^2(y) (2 \\pi)^{s\/2}\n\\: \\int_P \\exp\ti (q^* \\omr + \\evab{d \\theta +\n[\\theta, \\theta]\/2 }{ y }\n ) \\: \\Om \\end{equation}\n\\begin{equation} \\label{5.6}\n\\phantom{bbbbb} = i^s \\nusym^2 (y) (2 \\pi)^{s\/2} \\: \\int_{\\zloc} \\exp\ni\n(q^* \\omr + \\evab{F_\\theta }{ y } ) \\, \\Om.\n\\end{equation}\nHere, $F_\\theta = d \\theta + {\\frac{1}{2} } [\\theta, \\theta]$ is the curvature\nassociated to the connection $\\theta$;\nwe may introduce the term $[\\theta, \\theta]$ into the\nexponential in (\\ref{5.5}) since\nthe additional factors $\\theta$ will give zero under\nthe wedge product with $\\Om$. Formula (\\ref{5.6})\nshows that $Q_0$ is a polynomial in $y$.\n\nNow we were interested in\n$$\\ie_0 = \\frac{1}{(2 \\pi i )^s \\wn \\,{\\rm vol}\\, ( T) \\epsilon^{s\/2} }\n\\tintt [dy] e^{- \\inpr{y,y}\/{2 \\epsilon} } Q_0(y) $$\n\\begin{equation} \\label{5.7}\n= \\frac{1 }\n{ (2 \\pi)^{s\/2} \\wn \\,{\\rm vol}\\, ( T) \\epsilon^{s\/2} }\n\\tintt [dy] \\nusym^2 (y) \\: e^{- \\inpr{y,y}\/{2 \\epsilon} } \\:\n\\int_{P} \\exp (q^* \\omr + \\evab{F_\\theta}{ y} ) \\, \\Om, \\end{equation}\n\\begin{equation} \\label{5.9}\n= \\frac{1}{ (2 \\pi \\epsilon)^{s\/2} \\,{\\rm vol}\\, (K) } \\int_{z \\in \\lieks}\n\\, [dz] \\, e^{- \\inpr{z,z}\/{2\\epsilon} } \\: \\int_{P}\n\\exp (q^* \\omr + \\evab{F_\\theta}{z} ) \\, \\Om, \\end{equation}\nwhere the last step uses Lemma \\ref{l3.1} and the\nfact that $\\int_{P} \\exp (q^* \\omr + \\evab{F_\\theta}{ z} ) \\Om$\nis an invariant function of $z$.\n\n\n\n\nWe now regard $F_\\theta$ as a formal parameter and complete the\nsquare to do the integral over $z$: we have\n(identifying $z(F_\\theta)$ with $\\inpr{F_\\theta, z}$ using the invariant\ninner product $\\inpr{\\cdot, \\cdot}$)\n\\begin{equation} \\label{5.10}\n\\int_{z \\in \\lieks} [dz] e^{- \\inpr{z,z}\/{2 \\epsilon} }\n\\: \\exp \\inpr{F_\\theta, z}\n = (2 \\pi \\epsilon)^{s\/2} \\exp \\epsilon \\inpr{F_\\theta, F_\\theta}\/2. \\end{equation}\nBut $\\inpr{F_\\theta, F_\\theta}\/2$ is just the class\n$\\pi^* \\Theta$ on $P$, for $\\Theta \\in H^4 (\\xred)$.\nHence we obtain (integrating over the fibre of\n$P \\to \\xred$ and using the fact that the\nintegral of $\\Om$ over the fibre is $ \\,{\\rm vol}\\, (K)$)\n\\begin{equation} \\label{5.11}\n\\ie_0 = \\int_{\\xred} \\exp i\\om_0 \\: \\exp \\epsilon \\Theta, \\end{equation}\ncompleting the proof of Theorem \\ref{t4.3}. $\\square$\n\n{ \\setcounter{equation}{0} }\n\\section{The proof of Theorem 4.1 }\n\nIn this section we complete the proof of Theorem\n\\ref{t4.1}. This is done by observing\nthat $\\ie - \\eeth[\\xred]$ is of the\nform $\\ims \\int_{\\liet} \\gtsoe (Q - Q_0) = $\n$\\int_{\\liet} \\gtsoe D_\\nusym ( R - R_0)$ =\n$\\int_{\\liet} (D_\\nusym^* \\gtsoe) (R-R_0)$, where\n$R - R_0$ is piecewise polynomial and\nsupported away from $0$. (Here,\n$D_\\nusym^* = (-1)^{(s-l)\/2} D_\\nusym.$)\nThe results of \\cite{Ki1}\nestablish that the distance\nof any point of Supp($Q - Q_0$) from $0$\nis at least $|\\beta|$ for some nonzero $\\beta$\nin the indexing set ${\\mbox{$\\cal B$}}$ defined in Section 4.\nHence we obtain the estimates in Theorem \\ref{t4.1}.\n\nIn fact the function $R - R_0$ is known explicitly\nin terms of the values of $\\mu_T(F)$ (where $F$ are\nthe components of the fixed point set), the\nintegrals over $F$ of characteristic classes of subbundles\nof the normal bundle $\\nu_F$, and the weights of\nthe action of $T$ on $\\nu_F$ (see (\\ref{2.4}) and\nProposition\\ \\ref{p3.5}). The function $R - R_0$ is\npolynomial on polyhedral regions of $\\liet$,\nso that the quantity $\\ie - \\eeth [\\xred]$ can in principle\nbe computed from the integral of a polynomial times a Gaussian\nover these polyhedral regions.\nWe shall study these integrals in another paper and\nrelate them to the cohomology of the higher strata\nin the stratification of $X$ according to the gradient\nflow of $|\\mu|^2$ given in \\cite{Ki1}.\n\n\n\n\n\n\n\n\n\n\n\nWe now examine $\\ie - \\ie_0$ and prove Theorem \\ref{t4.1}.\nRecall from section 4 that the indexing\nset ${\\mbox{$\\cal B$}}$ of the critical\nsets $C_\\beta$ for the\nfunction $\\rho = |\\mu|^2$ is\n ${\\mbox{$\\cal B$}} = \\liet_+ \\cap W{\\mbox{$\\cal B$}}$ where\n$W {\\mbox{$\\cal B$}} = \\{ w \\beta: \\; \\beta \\in {\\mbox{$\\cal B$}}, \\phantom{a} \nw \\in W \\}$ is the\nset of closest points to $0$\nof convex hulls of nonempty subsets\nof the set $\\{ \\mu_T (F): F \\in {\\mbox{$\\cal F$}}\\}$\nof images under $\\mu_T$ of the connected\ncomponents of the fixed point set of $T$ in $X$.\nWe shall refer to $\\{ \\mu_T (F): F \\in {\\mbox{$\\cal F$}}\\}$ as the\nset of {\\em weights}\\footnote{The motivation for this is\nthat if $X$ is a nonsingular subvariety of complex\nprojective space ${ \\Bbb P}_n$ and $T$ acts\non $X$ via a linear action on ${\\Bbb C }^{n+1} $\nthen each $\\mu_T(F)$ is a weight of this action\nwhen appropriate identifications are made.} associated to $X$ equipped with\nthe\naction of $T$.\n\nLet ${\\mbox{$\\cal J$}}$ denote the locus\n$${\\mbox{$\\cal J$}} = \\{ y \\in \\liets : \\, Q \\phantom{a} \n\\mbox{is not smooth at} \\phantom{a} y\\}. $$\nThen we have\n\\begin{prop}\n${\\mbox{$\\cal J$}} \\subset \\caljab, $ where\n$\\caljab = \\{ y \\in \\liets : \\, \\ft\n(\\pis e^{\\iins \\bom}) $ is not smooth at $y \\}. $\n\\end{prop}\n\\Proof $Q = \\nusym \\ft (\\nusym \\pis e^{\\iins \\bom})$\n$ = \\nusym D_\\nusym\n\\ft(\\pis e^{\\iins \\bom})$.\nHence if $\\ft (\\pis e^{\\iins \\bom})$ is smooth at $y$ then so is\n$Q$. $\\square$\n\nNow it follows from \\cite{JGP} (Section 5) that\n$\\caljab = \\cup_{\\gamma \\in \\Gamma} \\mu_T (V_\\gamma)$ where\n$V_\\gamma$ is a component of the fixed point set of a one parameter subgroup\n$T_\\gamma$ of $T$ and $\\Gamma$ indexes all such one parameter subgroups and\ncomponents of their fixed point sets.\nLet $$D = \\cap \\{ D_\\beta: \\; \\beta \\in W{\\mbox{$\\cal B$}} - \\{0\\}\n \\}$$\nwhere $D_\\beta$ denotes the open half-space\n$$ D_\\beta = \\{ y \\in \\liets: \\; y(\\beta)\n< |\\beta|^2 \\}. $$\nNote that if $\\beta \\in {\\mbox{$\\cal B$}} - \\{0\\}$\nthen $D_\\beta$ contains $0$ and its boundary\nis the hyperplane\n$$H_\\beta = \\{ y \\in \\liets: \\; y(\\beta) = |\\beta|^2 \\}.$$\n\\begin{lemma} \\label{l6.2}The support of $Q - Q_0$ is contained in\nthe complement of $D$ (or equivalently\n$Q = Q_0$ on $D$).\n\\end{lemma}\n\\Proof\nSuppose $V_\\gamma$ is a component of the fixed point set of a one\nparameter subgroup $T_\\gamma$.\nBy the Atiyah-Guillemin-Sternberg convexity theorem\n\\cite{aam,gsconv},\n$\\mu_T(V_\\gamma)$ is the convex hull of some subset of the\nweights. Hence the closest point to $0$ in\n$\\mu_T(V_\\gamma)$ is in $W {\\mbox{$\\cal B$}}$.\nNow either this closest point is $0$,\nor else the closest point is a point\n$\\beta \\in\nW{\\mbox{$\\cal B$}} - \\{0\\}$ (in which case $\\mu_T(V_\\gamma) \\subset \\liet - D_\\beta\n\\subset \\liet - D$).\n\nNow if $x$ is a point in Supp($Q - Q_0$) then the ray from\n$0$ to $x$ must pass through at least one point in ${\\mbox{$\\cal J$}}$: hence\nit suffices to prove ${\\mbox{$\\cal J$}} \\subset \\liet - D$ since $D$ is\nthe intersection of a number of\nopen half spaces all of which contain $0$.\n\nBut ${\\mbox{$\\cal J$}} \\subset \\cup_\\gamma \\mu_T (V_\\gamma)$ and every\npoint in $\\mu_T(V_\\gamma)$ is in $\\liet - D$ unless $0$ is\nin $\\mu_T(V_\\gamma)$. Moreover if $x \\in \\mu_T(V_\\gamma) \\cap {\\mbox{$\\cal J$}}$\nand $0 \\in \\mu_T(V_\\gamma)$, we may consider the function\n$Q - Q_0$ restricted to a small neighbourhood of the ray\nfrom $0$ through $x$. This ray lies in the hyperplane\n$\\tilde{H}_\\gamma$ which\nis the orthocomplement in\n$\\liet$ to the Lie algebra $\\liet_\\gamma$\nof $T_\\gamma$. (Since the component of\n$\\mu_T$ in the direction of $\\liet_\\gamma$ is\nconstant along $V_\\gamma$ and since\n$0 \\in \\mu_T(V_\\gamma)$, it follows\nthat $\\mu_T(V_\\gamma)$ is contained in\n$\\tilde{H}_\\gamma$.) Since\n$Q - Q_0$ is identically zero near $0$ but not near $x$,\nthe ray from $0$ to $x$ must contain a point $x'$ in\n${\\mbox{$\\cal J$}}$ which is contained in some $\\mu_T(V_{\\gamma'})$\nwith $t_\\gamma \\ne t_{\\gamma'}. $ If $0 \\notin\n\\mu_T(V_{\\gamma'})$\n then $\\mu_T(V_{\\gamma'} ) \\subset \\liet - D$\nand so $x \\in \\liet - D$. If $0 \\in\n\\mu_T(V_{\\gamma'}) $ then we simply\nrepeat the argument, considering the restriction\nof $Q - Q_0$ to a neigbourhood\nof $\\tilde{H}_\\gamma \\cap \\tilde{H}_{\\gamma'}$.\nSince $0 \\notin {\\mbox{$\\cal J$}}$, after finitely many repetitions of\nthis argument we get the required result.\n Hence the Lemma is proved. $\\square$\n\n\n\n\n\n\n\n\n\n\nTo complete the proof of Theorem \\ref{t4.3},\nwe then use Lemma \\ref{l6.2} to express $\\ie - \\ie_0 $ as\n\\begin{equation} \\label{6.3}\n\\ie - \\ie_0\n = \\frac{1}{(2 \\pi i)^s |W| \\,{\\rm vol}\\, T \\epsilon^{s\/2} }\n\\int_{\\liets - D} [dy] (Q - Q_0) e^{- |y|^2\/{2 \\epsilon} } . \\end{equation}\nDenote by $C$ the set\n$\\{ y \\in \\liets - D \\: : \\: |Q(y) - Q_0(y) | \\le 1 \\}. $\nThen $$(2 \\pi)^s |W| \\,{\\rm vol}\\, (T) \\epsilon^{s\/2}\n|\\ie - \\ie_0| \\le \\int_C [dy]\\stg +\n\\int_{\\liets - D}[dy] |Q - Q_0|^2 \\stg. $$\nIf $b $ is the minimum value of $|\\beta | $\nover all $\\beta \\in {\\mbox{$\\cal B$}} - \\{0\\}$, then\n$$\\int_C [dy]\\stg \\le \\int_{|y| \\ge b } [dy] \\stg\n\\le e^{- b^2\/{2 \\epsilon} } q(\\epsilon), $$\nwhere $q(\\epsilon) $ is a polynomial in $\\epsilon^ {\\frac{1}{2} } $.\n\nFurther, denote by $p$ the function $|Q - Q_0|^2$.\nThen\n\\begin{equation} \\label{6.4}\\int_{\\liets - D} [dy] p(y) \\stg\n \\le \\sum_{\\beta \\in W{\\mbox{$\\cal B$}} - \\{0\\}}\n\\int_{y \\in D_\\beta}[dy] \\stg p(y). \\end{equation}\nFor each $\\beta \\in W {\\mbox{$\\cal B$}} - \\{0\\} $ one can now decompose\n$y \\in \\liets$ into $y = w_0 \\hatb + w, w \\in \\beta^\\perp$, $w_0 \\in {\\Bbb R }$\n(where $\\hatb = \\beta\/|\\beta|$).\nHence each of\nthe integrals (\\ref{6.4}) is of the form\n$$ \\int_{w_0 \\ge |\\beta| } \\int_{w \\in \\beta^\\perp}\ne^{- w_0^2\/{2 \\epsilon} } e^{ - |w|^2\/{2 \\epsilon} } p(w_0, w), $$\nand this is clearly bounded by $e^{- |\\beta|^2\/{2 \\epsilon} } $ times\na polynomial in $\\epsilon$. This completes the proof of Theorem 4.1.\n$\\square$\n\n\n\n\n\n\n\n\n{ \\setcounter{equation}{0} }\n\\section{Extension of Theorems 4.1 and 4.7 to other classes}\n\nIn this section we extend Theorems \\ref{t4.1} and \\ref{t4.3}\nto equivariant cohomology classes of the form $\\zeta = \\eta e^{\\iins \\bom} $\nwhere $\\eta \\in \\hk(X)$.\n More precisely\nwe shall show the following\n\\begin{theorem} \\label{t7.1}\n Suppose $\\eta \\in \\hk(X)$\nand suppose\nthat\n$i_0^* \\eta \\in \\hk (\\zloc)$ is represented by $\\eta_0 \\in H^*(\\zloc\/K)$\n(where $i_0: \\zloc \\to X$ is the inclusion map). Then\n\n{\\bf(a)} We have that\n$$ \\eta_0 e^{\\epsilon \\Theta} e^{i \\om_0}\n[\\xred] = \\frac{1}{(2 \\pi i )^s |W| \\,{\\rm vol}\\, (T) \\epsilon^{s\/2} }\n\\tintt [dy] e^{- |y|^2\/{2 \\epsilon} } \\, Q_0^\\eta (y), $$\nwhere $Q^\\eta(y) = \\nusym(y) \\ft (\\nusym \\pist (\\eta \\exp \\iins \\bom) ) $\nand $Q_0^\\eta(y) $ is a polynomial\nwhich is equal to $Q^\\eta(y) $ near $y = 0$.\n\n{\\bf (b)}\nLet\n$ \\rho_\\beta = |\\beta|^2$ be the\nvalue of the function $|\\mu|^2: X \\to {\\Bbb R }$ on the\ncritical set $C_\\beta$. Then\nthere exist functions $h_\\beta: {\\Bbb R }^+ \\to {\\Bbb R } $ such that\nfor some $N_\\beta \\ge 0$,\n$\\epsilon^{N_\\beta} h_\\beta(\\epsilon)$ remains bounded as $\\epsilon \\to 0^+$, and\nfor which\n$$\\Bigl | \\, \\frac{1}{(2 \\pi i )^s \\,{\\rm vol}\\, (K) } \\intk [d \\phi]\ne^{-\\epsilon |\\phi|^2\/2} \\pisk \\eta e^{\\iins \\bom}\n - \\eta_0 e^{\\epsilon \\Theta} e^{i \\om_0} [\\xred] \\, \\Bigr | \\le\n\\sum_{\\beta \\in {\\mbox{$\\cal B$}} - \\{0\\} }\n e^{- \\rho_\\beta \/{2 \\epsilon} } \\, h_\\beta(\\epsilon). $$\n\n{\\bf (c)} Suppose $\\eta$ is represented by\n$\\tilde{\\eta} = \\sum_J \\eta_J \\phi^J $ $ \\in \\Om^*_K(X)$\nfor\n$\\eta_J \\in \\Om^*(X)$. Then $Q^\\eta$ is of the form\n$Q^\\eta (y) = \\sum_J D_J R_J(y)$, where $D_J$ are\ndifferential operators on $\\liets$ and $R_J$ are piecewise\npolynomial functions on $\\liets$.\n\\end{theorem}\n\\noindent{\\em Proof of } {\\bf(a)}: We examine the function $ \\qeta(y) $ near\n$y = 0$. We have from Lemma \\ref{l3.3} and the paragraph before\nTheorem \\ref{t2.1} that\n$$ \\nusym \\ft (\\nusym \\pist (\\eta e^{\\iins \\bom} ) ) (y)\n = \\Bigl (\\nusym^2 \\fk \\pisk (\\eta e^{\\iins \\bom} ) \\Bigr ) (y)$$\n$$ = \\frac{\\nusym^2 (y)}{(2 \\pi)^{s\/2} } \\intk [d \\phi] \\int_{x \\in X }\ne^{- i \\eva{y}{ \\phi} } e^{i \\om} e^{ i \\eva{\\mu(x)}{ \\phi} } \\eta (\\phi). $$\nNow since $\\eta (\\phi) = \\sum_I \\phi^I \\eta_I$ for $\n\\eta_I \\in \\Om^*(X)$ (where the $I$ are multi-indices), we may\ndefine for any $x \\in X$ a distribution ${\\mbox{$\\cal S$}}_x$ with\nvalues in $\\Lambda^* T^*_x X$ as follows: for any $y \\in \\liets$ we have\n$${\\mbox{$\\cal S$}}_x(y) = \\intk [d \\phi] \\eminev{y}{ \\phi } e^{i \\om}\n\\epinev{\\mu(x)}{ \\phi} \\sum_I \\eta_I \\phi^I $$\n\\begin{equation} = \\sum_I (i \\partial\/\\partial y)^I \\intk [d \\phi]\n\\epinev{ (\\mu(x) - y)}{ \\phi} e^{i \\om} \\eta_I \\end{equation}\n$$ = (2 \\pi)^s\n\\sum_I (i \\partial\/\\partial y)^I \\delta(\\mu(x) - y) e^{i \\om} \\eta_I. $$\nThus the distribution ${\\mbox{$\\cal S$}}_x(y)$, viewed as\na distribution $ {\\mbox{$\\cal S$}} (x,y) $ on $X \\times \\liets$,\n is supported on $\\{ (x , y) \\in X \\times \\liets \\, | \\,\n\\mu(x) = y \\}. $ Hence for sufficiently small $y$,\n${\\mbox{$\\cal S$}}(x,y) $ (viewed now\nas a function of $x$) is supported on $ {\\mbox{$\\cal O$}}$ (in the notation\nof Section 5) and we find that\n\\begin{equation} \\qeta(y) = \\frac{\\nusym^2(y)}{\\htps}\n\\int_{x \\in X} {\\mbox{$\\cal S$}}(x, y) \\end{equation}\n$$ = \\frac{\\nusym^2(y)}{ (2 \\pi)^{s\/2} } \\intk [d \\phi] \\int_{P \\times\n\\lieks}\n\\epinev{(\\mu(x) - y)}{ \\phi} e^{i \\om} \\eta(\\phi) . $$\n\nNow consider the restriction of $\\eta$ to $\\hk(P \\times \\lieks) \\cong\n\\hk(P)$ (where $P = \\mu^{-1}(0)$ as in Section\n5). Recall that there exists $\\eta_0 \\in\n\\Om^*(P\/K)$ such that $\\eta - \\pi^* q^*\\eta_0 = D \\gamma$ for some\n$\\gamma$, where $D$ is the equivariant cohomology differential on\n$P \\times \\lieks$ and $\\pi: P \\times \\lieks \\to P \\times \\{0\\}$ and\n $q: P \\to \\to P\/K$ are the\nprojection maps.\\footnote{This is because the map\n$i \\circ \\pi: P \\times \\lieks \\to P \\times \\lieks$ is homotopic\nto the identity by a homotopy through equivariant maps, where\n $i: P \\times \\{ 0 \\} \\to\nP \\times \\lieks$ is the inclusion map. Hence\n$i$ induces an isomorphism $i^*: \\hk (P \\times \\lieks)\n\\to \\hk(P \\times \\{0\\}). $}\n We then have that\n\\begin{equation} \\label{7.d3}\nQ^\\eta (y) - \\frac{\\nusym^2(y)}{(2 \\pi)^{s\/2} } \\intk [d \\phi]\n\\int_{x \\in\nP \\times \\lieks} \\epinev{(\\mu(x) - y)}{\\phi} e^{i \\om} \\pi^* q^*\\eta_0 \\end{equation}\n$$ \\phantom{a} \\phantom{a} = \\frac{\\nusym^2(y)}{(2 \\pi)^{s\/2} } \\intk [d \\phi]\n\\int_{x \\in P \\times \\lieks} \\epinev{(\\mu(x) - y)}{ \\phi} e^{i \\om}\nD \\gamma \\;\\: {\\stackrel{ {\\rm def} }{=} } \\;\\: \\frac{\\nusym^2(y)}{(2 \\pi)^{s\/2}} \\bigtriangleup. $$\nBut also\n$$ \\epinev{(\\mu(x) - y)}{ \\phi} e^{i \\om} D \\gamma = D (\n\\epinev{(\\mu(x) - y)}{ \\phi}\ne^{i \\om} \\gamma ) $$\n(since $D \\phi_j = 0 $ and $D \\bom = 0$). Hence\n$\\bigtriangleup = \\intk [ d \\phi] \\int_{P \\times \\lieks}\nd (\\epinev{(\\mu(x) - y)}{ \\phi} e^{i \\om} \\gamma) $ (since for any\ndifferential form $\\Psi$, the term\n$\\iota_{\\tilde{\\phi}} \\Psi$ in $D \\Psi$\ncannot contain differential forms of top degree in $x$).\nUsing Stokes' Theorem and replacing $P \\times \\lieks$ by\n$P \\times B(\\lieks) $ where $B(\\lieks)$ is a large ball in\n$\\lieks$ with boundary $S(\\lieks)$, we have that\n$$ \\bigtriangleup =\n\\intk [d \\phi] \\int_{P \\times S(\\lieks) }\n\\epinev{(\\mu(x) - y)}{ \\phi} e^{i \\om} \\sum_I \\gamma_I \\phi^I$$\nfor $\\gamma_I \\in \\Om^*(P \\times \\lieks)$. Thus we have\n$ \\bigtriangleup = \\sum_I (i \\partial\/\\partial y)^I S_I(y) $ where\n$$ S_I (y) =\n\\intk [d \\phi] \\int_{x \\in P \\times S(\\lieks) }\n\\epinev{(\\mu(x) - y)}{ \\phi} e^{i \\om} \\gamma_I. $$\nNow we do the integral\nover $\\phi$ to obtain\n$$ S_I(y) = (2 \\pi)^{s} \\int_{x \\in P \\times S(\\lieks)} \\delta (\\mu(x) - y)\ne^{i \\om} \\gamma_I. $$\nThis is zero since the delta distribution is supported\noff $S(\\lieks)$ (recall that $\\mu(p, z) = z$ for\n$(p, z) \\in P \\times \\lieks$). Hence we have that\n$\\bigtriangleup = 0$, and so\n\\begin{equation} \\qeta(y) = \\frac{\\nusym^2(y)}{(2 \\pi)^{s\/2} } \\intk [d \\phi]\n\\int_{(p, z) \\in P \\times \\lieks} \\epinev{(z - y)}{ \\phi}\ne^{i \\om} \\pi^* \\eta_0, \\end{equation}\nand the rest of the proof is exactly the same as the proof of\nTheorem \\ref{t4.3} which was for the case $\\eta_0 = 1$.\nIn particular the analogue of (\\ref{5.6}) is\n\\begin{equation} \\label{5.6ext}\nQ^\\eta_0(y) = i^s \\nusym^2 (y) (2 \\pi)^{s\/2} \\: \\int_{\\zloc}\n\\eta_0 \\exp\n(q^*\\omr + \\evab{F_\\theta}{ y } ) \\, \\Om \\, ;\n\\end{equation} this equation\nshows that $Q_0^\\eta$ is a polynomial (and in\nparticular smooth) in $y$.\n\n\\noindent{\\em Proof of }{\\bf(b):} This is a direct extension of the\nproof of Theorem \\ref{t4.1}, with $Q$ and $Q_0$ replaced by\n$\\qeta$ and $Q^\\eta_0$.\n\n\\noindent{\\em Proof of }{\\bf (c):} Since $\\eta = \\sum_J \\eta_J \\phi^J$,\nthe abelian localization formula for\n$\\pis (\\eta e^{\\iins \\bom})$ yields\n\\begin{equation} \\label{7.6n}\n\\nusym(\\phi) \\pis (\\eta e^{\\iins \\bom}) (\\phi) = \\nusym(\\phi)\n\\sum_{F \\in {\\mbox{$\\cal F$}}} \\rfe(\\phi), \\phantom{bbbbb}\n\\rfe(\\phi) = \\int_F \\frac{i_F^* \\eta( \\phi) e^{i \\bom(\\phi)} }{e_F(\\phi)},\n\\end{equation} $$ \\phantom{bbbbb} =\n\\sum_J \\phi^J\ne^ {i \\eva{\\mu_T(F)}{ \\phi} }\n \\int_F \\frac{i_F^* \\eta_J e^{i \\om}\n }{e_F(\\mar \\phi) } $$\n$$ \\phantom{a} = \\nusym(\\phi) \\sum_J \\phi^J\n\\sum_{F \\in {\\mbox{$\\cal F$}}, \\alpha \\in {\\mbox{$\\cal A$}}_F} \\tfaj(\\phi) , $$\n\\begin{equation} \\label{7.06}\\mbox{where} \\phantom{a} \\phantom{a} \\tfaj(\\phi) =\n (-1)^{k_F(\\alpha) }\n\\int_F i_F^* \\eta_J\ne^{i \\om}\n\\tilde{c}_{F,\\alpha}\n \\frac{ \\epinev{ \\mu_T(F)}{ \\phi } }\n{\\prod_j \\Bigl ( \\bfjw (\\mar \\phi) \\Bigr )^{{n}_\\fj(\\alpha)} }\n \\end{equation}\n(and the $\\tilde{c}_{F,\\alpha}$ are as in\n(\\ref{4.004})).\nHere, as in Section 4, we may form a distribution\n\\begin{equation} \\label{7.07}H(y) = D_\\nusym \\tilde{H},\n\\phantom{a} \\tilde{H} = \\sum_J (i \\partial\/\\partial y)^J\n\\sum_{F \\in {\\mbox{$\\cal F$}}, \\alpha \\in {\\mbox{$\\cal A$}}_F} (-1)^{k_F(\\alpha)}\n\\Bigl ( \\int_F i_F^* \\eta_J\ne^{i \\om}\n\\tilde{c}_{F,\\alpha} \\Bigr ) H_{\\bar{\\gamma}_F(\\alpha) } ( \\mu_T(F) - y ), \\end{equation}\nwhere the piecewise polynomial function\n$H_{\\bar{\\beta} }$ is as in Proposition \\ref{p3.5}. Thus $\\tilde{H}$ is of\nthe form $\\tilde{H}(y) = \\sum_J D_J R_J (y)$ where\nthe $R_J(y)$ are piecewise polynomial and\nthe $D_J$ are differential operators.\n\nWe also define the distribution\n\\begin{equation} \\label{7.07'}\nG(y) = \\ft( \\nusym \\pis \\eta e^{\\iins \\bom}) . \\end{equation}\nThus $\\nusym(y) G(y) = Q^\\eta (y)$.\n\nThen we may show\nthat the distributions $G$ and $H$ are identical.\nFor we apply Lemma \\ref{l4} as before. We find by Proposition\n\\ref{p3.5}(a) that $(\\ft G)(\\psi) $ and $(\\ft H)(\\psi) $ are identical\noff the hyperplanes $\\bfj( \\psi) = 0$, so the first\nhypothesis of Lemma \\ref{l4} is satisfied. Moreover,\n$H$ is supported in a half space and\n\\begin{equation} G(y) = \\nusym(y) \\fk (\\pis \\sum_J \\eta_J \\phi^J e^{\\iins \\bom} ) (y) \\end{equation}\n$$ = (2 \\pi)^s \\nusym(y) \\sum_J (i \\partial\/\\partial y)^J \\int_{x \\in X}\n\\eta_J \\delta(\\mu(x) - y) e^{i \\om}, $$\nso $G$ is supported in the compact set $\\mu(X) \\cap \\liets$ and hence\n$H - G$ is supported in a half space. Thus the second\nhypothesis of Lemma \\ref{l4} is also satisfied and\nwe may conclude that $G = H$, which completes the proof.\n$\\square$\n\n\n\n\n\n\n\n\n\n\n\n\n{ \\setcounter{equation}{0} }\n\\section{Relations in the cohomology ring of symplectic quotients}\nIn this section we shall prove a formula\nfor the evaluation of cohomology\nclasses from $\\hk(X) $ on the fundamental\nclass of $\\xred$, and apply\nit to study the cohomology\nring $H^*(\\xred)$ in two examples.\n\n\\newcommand{\\gamp}{\\Gamma(P) }\n\\newcommand{\\npl}{ {n_+} }\n\nWe shall prove the following theorem:\n\n\\begin{theorem}\\label{t8.1}\nLet $\\eta \\in \\hk(X)$ induce $\\eta_0 \\in H^*(\\xred)$. Then we have\n\\begin{equation} \\label{8.00}\n\\eta_0 e^{i \\om_0} [\\xred] =\n\\frac{(-1)^\\npl }{ (2 \\pi)^{s-l} |W| \\,{\\rm vol}\\, (T) }\n\\treso\n\\Biggl ( \\: \\nusym^2 (\\psi)\n \\sum_{F \\in {\\mbox{$\\cal F$}}} \\rfe(\\psi) [d \\psi] \\Biggr ), \\end{equation}\nwhere\n$$ \\phantom{a} \\rfe(\\psi) = e^{i \\mu_T(F) (\\psi) }\n\\int_F \\frac{i_F^* (\\eta(\\psi) e^{i \\omega}) }{e_F(\\mar \\psi) }\n . $$\n\\end{theorem}\nHere $s$ and $l$ are the dimensions of $K$ and\nits maximal torus $T$,\nand $\\nusym(\\psi) = \\prod_{\\gamma > 0 }\n\\gamma(\\psi)$ where $\\gamma$ runs over the positive roots of $K$;\nthe number of positive roots\n$(s - l)\/2$ is denoted by $\\npl$.\nIf $F \\in {\\mbox{$\\cal F$}}$ (where ${\\mbox{$\\cal F$}}$ denotes the set\nof components of the $T$ fixed point set) then\n$i_F: F \\to X$ is the inclusion of $F$ in $X$ and\n$e_F $ is the equivariant Euler class of the\nnormal bundle to $F$ in $X$.\nThe quantity $\\treso (\\Omega)$\nwill be defined\nbelow (Definition \\ref{d8.5n}).\nThe definition of $\\treso (\\Omega)$\n will depend on the choice of a cone $\\lasub$, a test function\n$\\testf$, and\n a ray in $\\liets$ specified by\na parameter $ \\zray \\in \\liets$ -- but in fact if the form $\\Omega$\nis sufficiently well behaved\n(as is the case in (\\ref{8.00})) then the\nquantity $\\treso (\\Omega) $ will turn out to be\nindependent of these choices. (See Propositions\n\\ref{p8.6n}, \\ref{p8.7n} and \\ref{p8.8n}.)\n\n\n\n\n\nIn the case of $K = SU(2) $ the result of\nTheorem \\ref{t8.1} is as follows:\n\n\n\n\n\\begin{corollary} \\label{c8.2}\nLet $K = SU(2)$, and let $\\eta \\in \\hk(X)$ induce\n$\\eta_0 \\in H^*(\\xred)$.\nThen\nthe cohomology class $\\eta_0 e^{i \\om_0} $ evaluated on\nthe fundamental class of $\\xred$ is given by the\nfollowing formula:\n$$ \\eta_0 e^{i \\om_0} [\\xred] =\n-\\frac{ 1}{2} {\\rm Res}_0\n\\Biggl ( \\psi^2\n\\sum_{F \\in {\\mbox{$\\cal F$}}_+ } \\rfe(\\psi) \\Biggr ), \\phantom{a} \n{\\rm where} \\phantom{a} \\rfe (\\psi) =\ne^{i \\mu_T(F)(\\psi) }\n\\int_F\n\\frac{i_F^* \\eta(\\psi) e^{i \\omega} }{e_F( \\psi) }.\n$$ Here,\n${\\rm Res_0}$ denotes the coefficient of $1\/\\psi$, and\n${\\mbox{$\\cal F$}}_+$ is the subset of the fixed point set of $T = U(1)$\nconsisting of those components $F$ of the $T$ fixed point set\nfor which $\\mu_T(F) > 0 $.\n\\end{corollary}\nAn important special case (cf. Witten \\cite{tdg}, Section 2.4) is as follows:\n\\begin{corollary} \\label{c8.00}\nLet $\\eta \\in \\hk(X)$ induce $\\eta_0 \\in H^*(\\xred)$,\nand let $\\Theta \\in H^4(\\xred)$ be induced by the\npolynomial function $- \\inpr{\\phi, \\phi}\/2$\nof $\\phi$, regarded as an element of $H^4_K$.\nThen if $\\epsilon > 0$ we have\n\\begin{equation} \\label{8.010}\n\\eta_0 e^{\\epsilon \\Theta} e^{i \\om_0} [\\xred] =\n \\frac{(-1)^\\npl }{(2 \\pi)^{(s-l)} |W| \\,{\\rm vol}\\, (T) }\n\\sum_{m \\ge 0} \\frac{1}{m!} \\treso\n\\Biggl ( (- \\epsilon |\\psi|^2\/2)^m \\: \\nusym^2 (\\psi)\n \\sum_{F \\in {\\mbox{$\\cal F$}}} \\rfe(\\psi) [d \\psi] \\Biggr ), \\end{equation}\n$$ \\phantom{bbbbb} {\\rm where} \\phantom{bbbbb} \\rfe (\\psi) = e^{i \\mu_T(F) (\\psi) }\n\\int_F \\frac{i_F^* (\\eta(\\psi) e^{i \\om}) }{e_F(\\mar \\psi) }\n. $$\n\\end{corollary}\n\n\nWe now give a general definition (Definition\n\\ref{d8.5n}) of $\\ress h [d \\psi]$\nwhen $h $ is a meromorphic function on an open\nsubset of $\\liet \\otimes {\\Bbb C }$ satisfying\ncertain growth conditions at infinity. For the restricted class of\nmeromorphic forms of the form\n$e^{i \\lambda(\\psi)} [d \\psi]\/\\prod_j \\beta_j (\\psi), $ Definition \\ref{d8.5n}\nimplies\nthe existence of an explicit procedure for computing these residues\nby successive contour integrations, which is outlined in\nProposition \\ref{p8.4}.\n\nOur definition of the residue will be based on the following\nwell-known result (\\cite{hor}, Theorem 7.4.2 and Remark following\nTheorem 7.4.3):\n\\begin{prop} \\label{cty}\n(i) Suppose $u$ is a distribution on $\\liets$. Then\nthe set $\\gu = \\{ \\xi \\in \\liet: \\: e^{(\\cdot, \\xi) } u $\nis a tempered distribution$\\}$ is convex. (Here, $(\\cdot, \\cdot)$\ndenotes the pairing between $\\liet$ and $\\liets$.)\n\n\\noindent (ii) If the interior $\\guo$ of $\\gu$ is nonempty,\nthen there is an analytic function $\\hat{u} $ in\n$\\liet + i \\guo$ such that the Fourier transform\nof $e^{(\\cdot, \\xi) } u $ is $\\hat{u} (\\cdot + i \\xi)$\nfor all $\\xi \\in \\guo$.\n\n\\noindent (iii) For every compact subset $M$ of $\\guo$\nthere is an estimate\n\\begin{equation} \\label{bds} | \\hat{u} (\\zeta) | \\le C (1 + |\\zeta|)^N, \\phantom{a} \n{\\rm Im} (\\zeta) \\in M. \\end{equation}\n\n\\noindent (iv) Conversely if $\\Gamma$ is an open convex set\nin $\\liet$ and $h$ is a holomorphic function on $\\liet + i \\Gamma$\nwith bounds of the form (\\ref{bds}) for every compact\n$M \\subset \\Gamma$, then there is a distribution\n$u$ on $\\liets$ such that $e^{(\\cdot, \\xi)} u $ is a tempered distribution\nand has Fourier transform\n$h (\\cdot + i \\xi)$ for all $\\xi \\in \\Gamma$.\n\n\\noindent (v) Finally, if $u$ itself is tempered then the Fourier transform\n$\\hat{u}$\n is the limit (in the space ${\\mbox{$\\cal S$}}'$\nof tempered distributions)\nof the distribution $ \\psi \\mapsto\n\\hat{u} (\\psi + i t \\theta)$\nas $t \\to 0^+$, for any $\\theta \\in \\guo$.\n\\end{prop}\n\n\n\n\\begin{definition} \\label{d8.5n}\nLet $\\lasub$ be a (proper) cone in $\\liet$. Let $h$ be a holomorphic\nfunction on $\\liet - i {\\rm Int} (\\Lambda) \\subseteq \\liet \\otimes {\\Bbb C } $\n such that\nfor any compact subset $M$ of $\\liet - i {\\rm Int} (\\lasub) $ there\nis an integer $N \\ge 0 $ and a constant $C$ such that\n$|h (\\zeta)| \\le C (1 + |\\zeta|)^N$\n for all $\\zeta \\in M$.\nLet $\\testf: \\lieks \\to {\\Bbb R }$ be a smooth invariant function with\ncompact support and strictly positive in some neighbourhood of $0$,\n and let $\\htestf =\n\\fk \\testf: $ $\\liek\n\\to {\\Bbb C }$ be its Fourier transform. Let $\\htestfe(\\phi) =\n\\htestf (\\epsilon \\phi)$ so that $(\\fk \\htestfe)(z) = \\testfe (z) =\n\\epsilon^{-s} \\testf (z\/\\epsilon). $ Assume $\\htestf(0) = 1. $\nThen we define\n\\begin{equation} \\label{8.1n} \\reslch (h [d \\psi])\n = \\lim_{\\epsilon \\to 0^+} \\frac{1}{(2 \\pi i )^l }\n\\int_{\\psi \\in \\liet - i \\xi} \\htestf (\\epsilon \\psi) h (\\psi) [ d\\psi] \\end{equation}\nwhere $\\xi$ is any element of $\\Lambda$.\n \\end{definition}\n\nBy the Paley-Wiener theorem (\\cite{hor}, Theorem 7.3.1), for any\nfixed $\\xi \\in \\liek$ the function $\\htestf (\\psi - i \\xi) =\n\\fk(e^{- \\inpr{\\xi, \\cdot} } \\testf)(\\psi) $ is rapidly decreasing\nsince $\\fk \\htestf = \\testf$ is smooth and compactly supported. Hence\nthe integral (\\ref{8.1n}) converges. Now the function $\\htestf$ extends\nto a holomorphic function on $\\liek \\otimes {\\Bbb C }$ and in\nparticular on $\\liet \\otimes {\\Bbb C }$ (Proposition \\ref{cty}), and\nby assumption $h$ extends\nto a holomorphic function on\n$\\liet - i \\, {\\rm Int} (\\lasub)$;\n hence, by Cauchy's theorem, the integral\n(\\ref{8.1n}) is independent of $\\xi \\in {\\rm Int} (\\lasub)$.\n\n\nThe independence of $\\reslch (\\Omega)$ of the\nchoices of $\\lasub$ and $\\testf$ when $\\Omega$ is sufficiently\nwell behaved is established by the next results.\n\\begin{prop} \\label{p8.6n}\n Let $h: \\liek \\to {\\Bbb C }$ be a\n$K$-invariant function. Assume that\n$\\fk h$ is compactly supported; it then follows that $h: \\liek \\to {\\Bbb C }$\nis smooth (\\cite{hor}, Lemma 7.1.3) and extends to a\nholomorphic function on $\\liek \\otimes {\\Bbb C }$ (Proposition \\ref{cty}).\n Then $\\reslch ( h [d \\psi] ) $\nis independent of the cone $\\lasub$.\n\\end{prop}\n\n\n\\Proof As above, define $\\testfe (z) = \\epsilon^{-s} \\testf (z\/\\epsilon),$\nso that $\\htestfe (\\phi) = \\htestf(\\epsilon \\phi). $\nThe function $h$ extends in particular to a holomorphic\nfunction on $\\liet \\otimes {\\Bbb C }$, and by the remarks after\nDefinition \\ref{d8.5n}, the function $\\htestfe$ also extends to a\nholomorphic function on $\\liet \\otimes {\\Bbb C }$.\nHence Cauchy's theorem shows that\nfor any choice of the cone $\\lasub$,\n\\begin{equation} \\label{8.4n}\n\\reslch ( h(\\psi) \\dps ) = \\lim_{\\epsilon \\to 0^+}\n\\frac{1}{(2 \\pi i)^l}\n \\intt \\htestf (\\epsilon\\psi) h(\\psi) [d \\psi]. \\phantom{bbbbb} \\square \\end{equation}\n\\noindent{\\em Remark:} If $h$ is as in the statement of\nProposition \\ref{p8.6n}, then $\\nusym^2 h$ also satisfies the hypotheses\nof the Proposition, so\n$\\reslch(\\nusym^2 h [d \\psi] ) $ is also independent of the cone\n$\\lasub$.\n\n\nThe following is a consequence of Proposition \\ref{cty}:\n\n\n\\begin{prop} \\label{p8.7n}\n Let $u: \\liets \\to {\\Bbb C }$ be a distribution,\nand assume the set $\\gu$ defined in Proposition \\ref{cty} contains\n$- {\\rm Int} (\\Lambda)$. Thus $h = \\ft u$ is a holomorphic\nfunction on $\\liet - i {\\rm Int} \\Lambda$, satisfying the\nhypotheses in Definition \\ref{d8.5n}. Suppose in addition\nthat $u$ is smooth at $0$. Then\n$\\reslch (h \\dps) $ is independent of the test function $\\chi$, and\nequals $i^{-l} u(0)\/(2 \\pi)^{l\/2} $.\n\\end{prop}\n\n\nWe shall be dealing with functions $h: \\liek \\to {\\Bbb C }$ whose Fourier\ntransforms are smooth at $0$ but which are sums of other\nfunctions not all of whose Fourier transforms need be smooth\nat $0$. For this reason we must introduce a small generic parameter\n$\\zray \\in \\liets$ where all the functions in this sum are smooth.\nMore precisely we make the following\n\\begin{definition} \\label{d8.7n} Let $\\lasub, $ $\\testf$ and $h$ be as in\nDefinition \\ref{d8.5n}. Let $\\zray \\in \\liets$ be such that the\ndistribution $\\ft h$ is smooth on the ray $t \\zray$ for $t \\in (0, \\delta)$\nfor some $\\delta > 0 $,\nand suppose $(\\ft h)(t \\rho) $ tends to a well defined limit\nas $t \\to 0^+$. Then we\ndefine\n\\begin{equation} \\label{8.6n} \\resrlch (h \\dps)\n= \\lim_{t \\to 0^+} \\reslch \\Bigl ( h (\\psi )\ne^{i t \\zray (\\psi) } \\dps \\Bigr ). \\end{equation}\n\\end{definition}\nUnder these hypotheses, $\\resrlch ( h \\dps) $ is independent of $\\testf$\n(by Proposition \\ref{p8.7n}), but it may depend on the\nray $\\{ t \\zray: t \\in {\\Bbb R }^+ \\}. $ However\nwe have by Proposition \\ref{p8.7n}\n\\begin{prop} \\label{p8.8n} Suppose $\\ft h $ is smooth at $0$. Then\nthe quantity $\\resrlch ( h \\dps)$ satisfies\n$\\resrlch (h \\dps) = \\reslch ( h \\dps) $.\n\\end{prop}\n\n\\noindent{\\em Remark:} In the light of Propositions \\ref{p8.6n},\n\\ref{p8.7n} and \\ref{p8.8n}, it makes sense to write\n${\\rm Res} (\\Omega) $ for $\\resrlch (\\Omega) $ when\n$\\Omega = \\nusym^2 h \\dps $ for a\n$K$-invariant function $h: \\liek \\to {\\Bbb C }$ for which $\\fk h$ is compactly\nsupported and $\\ft (\\nusym^2 h)$ is smooth at $0$. In the proof of\nTheorem \\ref{t8.1} which we are about to give, we shall check\nthe validity\nof these hypotheses for the form $\\Omega$ which appears in\nthe statement of the Theorem.\n\nWe now give the proof of Theorem \\ref{t8.1}. We shall first show\n\n\n\n\\begin{prop} \\label{p7.6}\n\n{\\noindent (a)} The distribution\n$\\fk(\\pisk \\eta e^{i \\bom} ) (\\zp) $ defined for\n$\\zp \\in \\liek$ is represented by a smooth\nfunction for $\\zp$ in a sufficiently small neighbourhood of $0$.\n\n{\\noindent (b) } We have\n\\begin{equation} \\label{7.001} \\eta_0 e^{i \\om_0}\n[\\xred] = \\frac{1}{(2 \\pi)^{s\/2}i^s\n \\,{\\rm vol}\\, (K) } F_K (\\pis \\eta e^{\\iins \\bom}) (0), \\end{equation}\n\n\\begin{equation} \\label{7.002} \\phantom{ \\eta_0 e^{i \\om}\n[\\xred]} = \\frac{(2 \\pi)^{l\/2} }{(2 \\pi)^{s}\n|W| \\,{\\rm vol}\\, (T)i^s } F_T (\\nusym^2 \\pis \\eta e^{\\iins \\bom}) (0). \\end{equation}\n\\end{prop}\n\n\\noindent{\\em Proof of (a):}\n To evaluate $\\fk(\\pis \\eta e^{i \\bom} ) (0)$, we introduce\na test function $\\testf: \\lieks \\to {\\Bbb R }^+$ which is smooth and\nof compact support, and for which $(\\fk \\testf) (0) = 1\/(2 \\pi)^{s\/2}. $\nWe define $\\testfe(z) = \\epsilon^{-s} \\testf(z\/\\epsilon) $; as $\\epsilon \\to 0 $,\nthe functions $\\testfe $ tend to the Dirac delta distribution on $\\lieks$\n(in the space ${\\mbox{$\\cal D$}}'$ of distributions on $\\lieks$).\nThen we have\n\\begin{equation} (\\fk \\testfe) (\\phi) = (\\fk \\testf) (\\epsilon \\phi). \\end{equation}\nNow to evaluate $\\fk (\\pis \\eta e^{i \\bom} ) (\\zp)$, we integrate it against\nthe sequence of test functions $\\testfe$:\n\\begin{equation} \\fk ( \\pis \\eta e^{i \\bom} ) (\\zp) = \\lim_{\\epsilon \\to 0^+}\ni^s \\je (\\zp) \\end{equation}\nwhere\n\\begin{equation} i^s \\je (\\zp)= \\tintk [d z] \\fk (\\pis \\eta\ne^{i \\bom} ) (z) \\chi_\\epsilon (z - \\zp) \\end{equation}\n$$ \\phantom{bbbbb} = \\intk [d \\phi] \\int_{x \\in X} \\eta(\\phi) e^{i \\om}\ne^{i (\\mu(x) - \\zp) (\\phi) } \\htestfe(\\phi) $$\n(by Parseval's Theorem).\nNow because $\\testfe$ is smooth and of compact support, the Paley-Wiener\nTheorem (Theorem 7.3.1 of \\cite{hor}) implies that $\\htestfe$ is rapidly\ndecreasing. So we may use Fubini's theorem to interchange the order\nof integration and get\n\\begin{equation} \\label{7.t1} i^s \\je(\\zp) = \\int_{x \\in X } e^{i \\om} \\int_{ \\phi \\in\n\\liek}\n[d \\phi] \\eta(\\phi) \\htestfe(\\phi) e^{i (\\mu(x) - \\zp) (\\phi)} \\end{equation}\n\\begin{equation} \\label{7.t2} \\phantom{bbbbb} = (2 \\pi)^{s\/2}\n\\int_{x \\in X} e^{i \\om} \\eta( - i \\partial\/\\partial z) \\testfe(z)|_{z =\n\\mu(x) - \\zp}. \\end{equation}\nAs $\\epsilon \\to 0$, $\\testfe$ is supported on an arbitrarily\nsmall neighbourhood of $\\mu^{-1}(0)$. Thus, because of\nProposition \\ref{p5.2},\nthe integral may be replaced by an integral over $P \\times \\lieks$:\n\\begin{equation} i^s \\je(z') = (2 \\pi)^{s\/2} \\int_{(p,z) \\in P \\times \\lieks}\ne^{i \\om} \\eta( - i \\frac{ \\partial }{\\partial z}) \\testfe(z - \\zp)\n\\end{equation}\nNow by the same argument as given in the proof of Theorem \\ref{t7.1}(a),\nthere is $\\eta_0 \\in \\Omega^*(P\/K) $ such that\n\\begin{equation} \\eta - \\pi^* \\eta_0 = D \\gamma \\phantom{a} \\mbox{for some $\\gamma$, } \\end{equation}\nwhere $D$ is the equivariant cohomology differential on $P \\times \\lieks$\nand $\\pi: P \\times \\lieks \\to P \\to P\/K$ is the projection map.\nBy the argument given after (\\ref{7.d3}), we have\n\\begin{equation} i^s \\je(\\zp) - (2 \\pi)^{s\/2} \\int_{(p,z) \\in P \\times \\lieks}\ne^{i \\om} (\\pi^* \\eta_0) \\testfe(z - \\zp) \\end{equation}\n$$ \\phantom{bbbbb} = \\int_{(p,z) \\in P \\times \\lieks} e^{i \\om}\n\\int_{ \\phi \\in \\liek} [d \\phi] D \\gamma(\\phi) \\htestfe(\\phi)\ne^{i (z - \\zp)( \\phi) } $$\n$$ = \\int_{ \\phi \\in \\liek} [d \\phi] \\htestfe( \\phi)\n\\int_{ (p,z) \\in P \\times \\lieks } e^{i \\om} D \\gamma (\\phi)\ne^{i (z - \\zp) (\\phi) } \\;\\: {\\stackrel{ {\\rm def} }{=} } \\;\\: \\deleps. $$\nBut\n\\begin{equation} e^{i \\om} e^{i (z-\\zp)(\\phi) }\nD \\gamma = D (e^{i \\om} e^{i (z - \\zp) (\\phi) }\n\\gamma(\\phi) ). \\end{equation}\nHence\n\\begin{equation} \\deleps = \\intk [d \\phi] \\htestfe (\\phi)\n\\int_{(p,z) \\in P \\times \\lieks}\nd ( e^{i \\om} e^{i (z - \\zp) (\\phi) } \\gamma(\\phi) ) \\end{equation}\n(since for any differential form $\\Psi$, the term\n$\\iota_{\\tilde{\\phi}} \\Psi$ in $D \\Psi$\ncannot contain differential forms of top degree in $x$).\nReplacing $P \\times \\lieks$ by\n$P \\times B_R(\\lieks)$ where $B_R (\\lieks)$ is a large ball in $\\lieks$\nwith boundary $S_R (\\lieks)$, we have that\n\\begin{equation} \\deleps = \\lim_{R \\to \\infty}\n\\intk [d \\phi] \\htestfe( \\phi)\n\\int_{(p,z) \\in P \\times B_R (\\lieks) } d \\Bigl (\ne^{i \\om} e^{i (z - \\zp) (\\phi) }\n\\gamma( \\phi) \\Bigr ) . \\end{equation}\nWe then interchange the order of integration to get\n\\begin{equation} \\deleps = \\lim_{R \\to \\infty}\n\\int_{(p,z) \\in P \\times B_R (\\lieks) } d \\left (\ne^{i \\om} \\intk [d \\phi] \\htestfe ( \\phi) e^{i (z - \\zp) (\\phi) }\n\\gamma( \\phi) \\right ) \\end{equation}\n$$ \\phantom{bbbbb} = \\lim_{R \\to \\infty}\n\\int_{(p,z) \\in P \\times B_R(\\lieks) } d\n\\Bigl (e^{i \\om}\n\\gamma( \\frac{\\partial}{\\partial z}) \\testfe (z - \\zp) \\Bigr ) . $$\n$$ \\phantom{bbbbb} = \\lim_{R \\to \\infty}\n\\int_{(p,z) \\in P \\times S_R(\\lieks) }\n\\Bigl (e^{i \\om}\n\\gamma( \\frac{\\partial}{\\partial z}) \\testfe (z - \\zp) \\Bigr )\n\\phantom{a} \\mbox{by Stokes' Theorem}. $$\nThis limit\nequals $0$ for sufficiently\nsmall $\\zp$ since $\\testfe$ is\ncompactly supported on $\\lieks$. Hence $\\deleps = 0 $.\n\nFinally we obtain using the expression for $\\omega$\ngiven in Proposition \\ref{p5.2}\n\\begin{equation} i^s \\je(\\zp) = (2 \\pi)^{s\/2} \\int_{(p,z) \\in P \\times \\lieks} e^{i \\om}\n(\\pi^* \\eta_0) \\testfe (z - \\zp), \\end{equation}\n\\begin{equation} \\phantom{bbbbb} = ( 2 \\pi)^{s\/2} \\int_{ (p,z) \\in P \\times \\lieks}\ne^{i \\pi^* \\om_0} (\\pi^* \\eta_0) e^{i \\theta(dz)} e^{i d \\theta(z) }\n\\testfe (z - \\zp). \\end{equation}\nThus we have as in Section 5\n\\begin{equation} \\label{8.26}\n \\lim_{\\epsilon \\to 0 } \\je (\\zp) = ( 2 \\pi)^{s\/2} \\int_{(p,z) \\in\nP \\times \\lieks} e^{i \\pi^* \\om_0} (\\pi^* \\eta_0)\n\\Om [dz] e^{i F_\\theta (z)} \\delta(z - \\zp) \\end{equation}\n$$ = ( 2\\pi)^{s\/2} \\int_P e^{i \\pi^* \\om_0}\n (\\pi^* \\eta_0)\ne^{i F_\\theta(\\zp) }\n\\Om $$\nwhere $\\Omega$ is the differential form introduced after (\\ref{5.4}).\nThis shows in particular that $(\\fk \\rbare)(\\zp)$\n (where $\\rbare (\\phi) = \\pis (\\eta e^{i \\bom})( \\phi) $)\nis a\npolynomial in $\\zp$ for small $\\zp$, and hence is smooth in\n$\\zp$ for $\\zp$ sufficiently close to $0$. This completes the\nproof of (a).\n\nWhen $\\zp = 0 $, equation (\\ref{8.26})\nbecomes\n$$\\lim_{\\epsilon \\to 0}\n\\je (0) =\ni^{-s} F_K (\\pis \\eta e^{\\iins \\bom})(0) = {(2 \\pi)^{s\/2} \\,{\\rm vol}\\, (K) }\n\\eta_0 e^{i \\om_0} [\\xred], $$\nwhich proves (\\ref{7.001}).\nUsing Lemma \\ref{l3.1} again, we have for any\n$K$-invariant function $f$ on $\\liek$ that\n\\begin{equation} \\label{7.003}\n\\frac{(2 \\pi)^{s\/2} }{ \\,{\\rm vol}\\, (K) }\n(F_K f) (0) =\n\\frac{( 2 \\pi)^{l\/2} }{|W| \\,{\\rm vol}\\, (T) }\nF_T(f \\nusym^2) (0). \\end{equation}\nCombining this with (\\ref{7.001}) we obtain\n$$\n\\eta_0 e^{i \\om_0}[\\xred]\n = \\frac{(2 \\pi)^{l\/2} }{(2 \\pi)^{s}\n|W| \\,{\\rm vol}\\, (T) i^s } F_T (\\nusym^2 \\pis \\eta e^{\\iins \\bom}) (0), $$\nwhich is (\\ref{7.002}). $\\square$\n\nTheorem \\ref{t8.1} follows from Proposition \\ref{p7.6} and\nProposition \\ref{p8.7n}\nby applying\nTheorem \\ref{t2.1} to decompose $r^{{\\eta}} =\n\\pis (\\eta e^{i \\bom} ) $ as a sum\nof meromorphic functions $\\rfe$ on $\\liet \\otimes {\\Bbb C } $ corresponding\nto the components $F$ of the fixed point set of $T$. We now\ncomplete the proof of this theorem.\n\n\\noindent{\\em Proof of Theorem \\ref{t8.1}:} As in (\\ref{7.6n}),\nthe abelian localization formula yields\n$ r^{{\\eta} } (\\psi) = \\sum_{F \\in {\\mbox{$\\cal F$}}} \\rfe (\\psi), $\nwhere\n$$ \\rfe(\\psi) = e^{i \\mu_T(F) (\\psi) } \\int_F\n\\frac{i_F^* \\eta(\\psi) e^{i \\om} } {e_F(\\psi) }. $$\nNow the distribution $(\\fk r^{{\\eta} } ) (\\phi) $ is represented\nby a smooth function near $0$ (Proposition \\ref{p7.6} (a));\nalso, the distribution $\\ft(\\nusym^2 r^{{\\eta} } ) $\n$ = D_{\\nusym} \\ft (\\nusym \\rbare) $ is represented\nby a smooth function near $0$ since $\\ft (\\nusym r^{{\\eta} } ) =\n\\nusym \\fk r^{{\\eta} } $ (Lemma\n\\ref{l3.3}) and $\\fk r^{{\\eta} } $ is smooth near $0$ (Proposition\n\\ref{p7.6}(a)).\nWe choose $ \\zray \\in \\liets$ so that the distribution\n$\\ft \\rfe$ is smooth along the ray $t \\zray, t \\in (0, \\delta) $, for all\n$F$ and sufficiently small $\\delta > 0 $, and that this distribution\ntends to a well defined limit as $t \\to 0^+$:\nthis is possible because the $\\rfe (\\psi)$ are sums of\nterms of the form $e^{i \\mu_T(F) (\\psi) } \/ \\prod_j \\bfj(\\psi)^{n_j} $\nso their Fourier transforms $\\ft \\rfe$ are piecewise polynomial\nfunctions of the form $H_\\barb (y) $ (see Proposition \\ref{p3.5}).\nThese functions are smooth on the set $U_\\barb$ consisting of all points\n$y$ where $y$ is not in the cone spanned by any subset of the\n$\\bfjw$ containing less than $l$ elements. Thus\n$$\\lim_{t \\to 0^+} (2 \\pi)^{-l\/2} i^{-l} \\ft \\rfe(t \\zray) =\n \\resrlch (\\rfe \\dps) $$ by\nDefinition \\ref{d8.5n} and Proposition \\ref{p8.7n}. It follows that\n\\begin{equation} \\label{8.7n}\n(2 \\pi)^{-l\/2} i^{-l} \\ft (\\nusym^2 \\rbare) (0) =\n\\resrlch (\\nusym^2 \\rbare \\dps ) \\end{equation}\n\\begin{equation} \\label{8.8n} \\phantom{bbbbb} = \\sum_{F \\in {\\mbox{$\\cal F$}}} \\resrlch (\\nusym^2 \\rfe). \\end{equation}\nThe residue in (\\ref{8.7n}) is independent of $\\testf$, $\\lasub$ and $\\zray$\nby Propositions \\ref{p8.6n}, \\ref{p8.7n} and\n\\ref{p8.8n}. The residues in (\\ref{8.8n}) are independent of $\\testf$ by\nProposition \\ref{p8.7n}, but they may depend on $\\zray$\nand $\\lasub$.\n\nTo conclude the proof of Theorem \\ref{t8.1} we note that (\\ref{7.002})\ngives\n\\begin{equation}\n \\eta_0 e^{i \\om}\n[\\xred] = \\frac{(2 \\pi)^{l\/2} }{(2 \\pi)^{s}\n|W| \\,{\\rm vol}\\, (T)i^s } F_T (\\nusym^2 \\pis \\eta e^{\\iins \\bom}) (0), \\end{equation}\n$$ = \\frac{i^l }{(2 \\pi)^{s-l}\n|W| \\,{\\rm vol}\\, (T)i^s } \\reso(\\rbare(\\psi) \\nusym^2(\\psi) [ d\\psi]) \\phantom{a} \n\\mbox{(by Proposition \\ref{p8.7n})} $$\n$$ = \\frac{-1)^\\npl }{ (2 \\pi)^{s-l} |W| \\,{\\rm vol}\\, (T) } \\reso\n\\Biggl ( \\sum_{F \\in {\\mbox{$\\cal F$}}} \\rfe(\\psi) \\nusym^2 (\\psi) [d \\psi]\n\\Biggr ) $$\nas claimed. $\\square$\n\n\\noindent{\\em Proof of Corollary 8.2:} In a normalization\nwhere $ \\,{\\rm vol}\\, (T) = 1$, the factor $\\nusym(\\psi) $ becomes $2 \\pi \\psi$.\nThis gives\n$$ \\frac{1}{(2 \\pi)^{s-l}}\\treso\n\\Biggl ( \\: \\nusym^2 (\\psi)\n \\sum_{F \\in {\\mbox{$\\cal F$}}} \\rfe(\\psi) \\dps \\Biggr )\n= \\reslch ( \\psi^2\n \\sum_{F \\in {\\mbox{$\\cal F$}}} \\rfe(\\psi) [d \\psi] ). $$\nEach term $\\rfe (\\psi) $ is a sum of terms of the form\n$\\tau_\\alpha (\\psi) = c_{\\alpha} \\psi^{-n_\\alpha} e^{i \\mu(F) \\psi} $ for some constants\n$c_\\alpha$ and integers $n_\\alpha$.\nBy (\\ref{8.1n}), the residue is given by\n\\begin{equation} \\label{8.001} \\reslch (h \\dps) =\n\\lim_{ \\epsilon \\to 0^+ }\n\\frac{1} {2 \\pi i} \\int_{ \\psi \\in {\\Bbb R } - i \\xi}\n\\htestf (\\epsilon \\psi) h(\\psi) \\dps, \\end{equation}\nwhere we choose $\\xi$ to be in the cone $\\lasub = {\\Bbb R }^+$.\nProposition \\ref{cty} (i), (ii) shows that\nthe function $\\htestf: {\\Bbb R } \\to {\\Bbb C }$ extends to an entire\nfunction on ${\\Bbb C }$.\n\n\n\nWe may now decompose the integral\n in (\\ref{8.001}) into terms corresponding to the $\\tau_\\alpha$. If\n$n_\\alpha > 0 $, we\ncomplete each such integral over ${\\Bbb R } - i \\xi$ to a\ncontour integral by adding a semicircular curve at infinity, which\nis in the upper half plane if $\\mu(F) > 0 $ and in the lower half\nplane if $\\mu(F) < 0 $. This choice of contour is made so that\nthe function\n$\\tau_\\alpha (\\psi) $ is bounded on the added\ncontours, so the added semicircular curves do not contribute to\nthe integral. Since only the contours corresponding to values\nof $F$ for which $\\mu(F) > 0 $ enclose the pole at $0$, application\n of Cauchy's residue formula now gives the result.\nA similar argument establishes that the terms $\\tau_\\alpha $ for which\n$n_\\alpha \\le 0 $ contribute $0$ to the sum.\\footnote{The\nformula obtained by choosing $\\lasub = {\\Bbb R }^-$ is in fact\nequivalent to the formula we have\nobtained using the choice $\\lasub = {\\Bbb R }^+$.\n This can be seen directly from the Weyl invariance\nof the function $\\rbare$, where the action of the Weyl group takes\n$\\psi$ to $- \\psi$ and so converts terms with $\\mu(F) > 0 $ to\nterms with $\\mu(F) < 0 $.}\n$\\square$\n\n\n\n\n\\noindent{\\em Remarks:}\n\n (a) The quantity $\\resrlch (\\nusym^2 \\rfe \\dps ) $ depends on\nthe cone $\\lasub$ for each $F$;\nhowever, it follows from Proposition\n\\ref{p8.6n} that the sum $\\sum_{F \\in {\\mbox{$\\cal F$}}}\n\\resrlch ( \\nusym^2 \\rfe \\dps ) $ is independent of $\\lasub$. }\n\n\\noindent (b) Let ${\\mbox{$\\cal F$}}_\\lasub$ be the set of those $F \\in {\\mbox{$\\cal F$}}$ for which\n$\\mu_T(F)$ lies in the cone $\\dcf =\n\\{ \\sum_j s_j \\bfjw: s_j \\ge 0 \\} $ (defined in Section 4) spanned\nby the $\\bfjw$. Then by\nProposition \\ref{p8.4} (iii), $\\resrlch ( \\nusym^2 \\rfe ) = 0 $ if\n $F \\notin {\\mbox{$\\cal F$}}_\\lasub$,\nso in fact $\\resrlch (\\nusym^2 \\rbare \\dps) =\n\\resrlch \\sum_{F \\in {\\mbox{$\\cal F$}}_\\lasub} ( \\nusym^2 \\rfe \\dps ) $.\n\n\n\\noindent (c) Finally, it follows from Proposition \\ref{p8.4} that\nif we replace the symplectic form\n$\\omega$ and the moment map $\\mu$ by $\\delta \\omega$ and $\\delta \\mu$\n(where $\\delta > 0 $) and then let $\\delta $ tend to $0$, we obtain\nan expression where $\\mu$ and $\\omega $ appear only in determining the\nset ${\\mbox{$\\cal F$}}_\\lasub$ indexing terms which yield a nonzero contribution.\n\n\nWe now restrict ourselves to the special case when $\\Omega$ is of the\nform $$\\Omega_\\lambda(\\psi) = e^{i \\lambda(\\psi)}\n[d \\psi]\/\\prod_{j = 1}^N \\beta_j (\\psi).$$\nIf $\\beta_j \\in \\lasub $ then the distribution\n$\\resrlch (\\Omega_\\lambda) $ is just (up to multiplication by a\nconstant) the piecewise polynomial function $H_\\barb(\\lambda)$ from Proposition\n\\ref{p3.5}.\nWe shall now give a Proposition\n which gives a list of properties satisfied\nby the residues $\\reso (\\Oma{\\lambda})$: these properties in fact characterize the\nresidues uniquely and enable one to compute them.\n\n\n\\newcommand{\\pee}{P}\n\\begin{prop} \\label{p8.4} Let $\\xi \\in \\liet$ and\nsuppose\n $\\beta_1, \\dots, \\beta_N \\in \\liets$ are\nall in the dual cone of a cone $\\lasub \\in\n\\liet$.\nDenote by $\\pee: \\liet \\to {\\Bbb R } $ the\nfunction $\\pee(\\psi) = \\prod_j \\beta_j(\\psi)$.\nSuppose $\\lambda \\in U_\\barb \\subset \\liets$ (see\nProposition \\ref{p3.5}), and\ndefine $\\Oma{\\lambda}(\\psi) =\ne^{i \\lambda(\\psi)}[d \\psi]\/\\pee(\\psi) $.\n\n\n\nThen we have\n\\begin{description}\n\\item[(i)]\n $\\reso (\\psi_k \\psi^J \\Oma{\\lambda})\n= (- i \\partial\/\\partial \\lambda_k) \\reso (\\psi^J \\Oma{\\lambda}).\n$\n\\item[(ii)] $(2 \\pi i)^l \\reso (\\Oma{\\lambda})\n= i^N H_\\barb (\\lambda)$, where $H_\\barb$ is\nthe distribution given in Proposition \\ref{p3.5}. (Recall we have assumed\nthat\n$\\beta_j $ is in the dual cone of\n$ \\lasub $ for all $j$.)\n\\item[(iii)] $\\reso (\\Oma{\\lambda}) = 0 $ unless $\\lambda$ is in the cone\n$C_\\barb$ spanned\nby the $\\beta_j$.\n\\item[(iv)] $$\\lim_{s \\to 0^+} \\reso \\Bigl (\n\\Oma{s \\lambda} \\psi^J\n\\Bigr ) = 0$$\nunless $ N - |J| = l$.\n\\item[(v)]\n$$\\lim_{s \\to 0^+} \\reso \\Bigl (\n\\Oma{s \\lambda} \\psi^J\n\\Bigr ) = 0 $$\nif the monomials $\\beta_j$ do not span $\\liets$.\n\\item[(vi)] If\n$\\beta_1, \\dots, \\beta_l$ span $\\liets$ and\n$\\lambda = \\sum_j \\lambda^j \\beta_j$\nwith all $\\lambda^j > 0$,\n then\n$$ \\lim_{s \\to 0^+} \\reso\n\\Bigl ( \\frac{ e^{i s \\lambda(\\psi) } [d \\psi] }{\\beta_1(\\psi) \\dots\n\\beta_l(\\psi)\n} \\Bigr )\n= \\frac{1}{\\det \\barb } , $$\nwhere $\\det \\barb $ is the determinant of the $l $ by $l$\nmatrix whose columns are the coordinates of $\\beta_1, \\dots,\n\\beta_l$ written in terms of any orthonormal\nbasis of $\\liet$.\n\\item[(vii)] $$ \\reso \\Bigl (\n\\frac{e^{i \\lambda(\\psi) } \\psi^J }\n{\\pee(\\psi)}\n[d \\psi]\n\\Bigr ) = \\sum_{m \\ge 0} \\lim_{s \\to 0^+}\n\\reso \\Bigl ( \\frac{ (i \\lambda(\\psi))^m e^{i s \\lambda(\\psi) } \\psi^J }\n{m! \\pee(\\psi)}\n [d \\psi]\\Bigr ). $$\n\n\\end{description}\n\\end{prop}\n\n\\noindent{\\em Remark:} The limits in Proposition\n\\ref{p8.4} are not part of the\ndefinition of the residue map: rather these limits\nare described in order to specify a procedure\nfor computing the piecewise polynomial function\n$H_\\barb (\\lambda) = (2 \\pi i)^l i^{-N}\n\\reso (\\Om_\\lambda). $ (See the example below.)\nProposition \\ref{p8.4} (ii)\nidentifies\n$H_\\barb (\\lambda)$ with an integral over $\\liet$,\nwhich may be completed to an appropriate\ncontour integral: the choice of contour is\ndetermined by the value of $\\lambda$,\nand requires $\\lambda$ to be a nonzero point in\n$U_\\barb$. Proposition \\ref{p8.4}\n(vii) says that one may compute $H_\\barb$ by\nexpanding the numerator $e^{i \\lambda(\\psi)}$ in\na power series, but only provided one keeps\na factor $e^{is \\lambda(\\psi)}$ in the\nintegrand (for small $s > 0$) in order to\nspecify the contour. The limits in\nProposition \\ref{p8.4} (iv)-(vii) exist because\naccording to Proposition \\ref{p8.4}\n(i) and (ii), they specify limits\nof derivatives of polynomials on subdomains of\n$U_\\barb$, as one approaches the point $0$\nin the boundary of $U_\\barb$ along the fixed\ndirection $s \\lambda$ as $s \\to 0$ in ${\\Bbb R }^+$.\n\n\n\\noindent{\\em Proof of (i):} This\nfollows directly from Definition \\ref{d8.5n}.\n\n\n\n\\noindent{\\em Proof of (ii):}\nThis follows because $(2 \\pi i)^l i^{- N} \\reso(\\Oma{\\lambda})$\nis the fundamental solution $E(\\lambda)$ of the differential\nequation $P(\\partial\/\\partial \\lambda)E(\\lambda) = \\delta_0$\nwith support in a half space containing the $\\beta_j$.\n(See\n\\cite{abg} Theorem 4.1 or \\cite{hor2} Theorem 12.5.1.)\nBut this fundamental solution is given\nby $H_\\barb$ (see Proposition \\ref{p3.5}(c)).\n\n\n\n\n\\noindent{\\em Proof of (iii):}\nThis is an immediate consequence of (i) and (ii), in view\nof Proposition \\ref{p3.5}(a).\\footnote{Alternatively there is the\nfollowing direct argument, which was pointed out to us\nby J.J. Duistermaat. We recall that\n$$\n \\reso (\\Omega_\\lambda) = \\frac{1}{(2 \\pi i)^l} \\intt\n\\frac{ e^{i \\lambda(\\psi - i \\xi) }}{P(\\psi - i \\xi) } \\, [d \\psi], $$\nwhich is defined and independent of $\\xi$ for $\\xi \\in (C_\\barb)^* $\n(see the discussion after\nDefinition \\ref{d8.5n}). Hence we may replace $\\xi $ by $t \\xi $\nfor any $t \\in {\\Bbb R }^+$:\n\\begin{equation} \\label{resrec}\n \\reso (\\Omega_\\lambda) = \\frac{1}{(2 \\pi i)^l} \\intt\n\\frac{ e^{i \\lambda(\\psi - i t\\xi) }}{P(\\psi - i t \\xi) } \\, [d \\psi]. \\end{equation}\nTaking the limit as $t \\to \\infty$, we\nsee that $\\reso (\\Omega_\\lambda) = 0 $ if $ \\lambda(\\xi) < 0 $,\nbecause of the factor $e^{ t \\lambda(\\xi) } $ that appears\nin the numerator of (\\ref{resrec}). Since this holds\nfor all $\\xi \\in (C_\\barb)^*$,\n$\\reso (\\Omega_\\lambda)$ is only nonzero when $\\lambda(\\xi) \\ge 0 $\nfor all $\\xi \\in (C_\\barb)^*$, in other words when\n$\\lambda \\in C_\\barb$.}\n\n\n\\noindent{\\em Proof of (iv):} By (i),\n$$\n\\limpl \\reso \\Bigl ( \\Oma{s \\lambda_0} \\psi^J\n \\Bigr ) = \\limpl (- i \\partial\/\\partial \\lambda)^J\nH_\\barb (\\lambda)|_{\\lambda = s\\lambda_0}, $$\nbut $H_\\barb$ is a homogeneous piecewise polynomial function\nof degree $N-l$, so the conclusion holds for $|J| > N - l.$\nIf $|J| < N - l$, we find that $(\\partial\/\\partial \\lambda)^J\nH_\\barb(\\lambda)$ is homogeneous of order $N - l - |J|$ (on any\nopen subset of\n$\\liets$ where $H_\\barb$ is smooth). Hence it\nis of order $s^{N - l - |J|} $ at $\\lambda = s \\lambda_0$ as $s \\to 0^+$,\nand the conclusion also holds in this case.\n\n\\noindent{\\em Proof of (v):} By (ii), we know that\n$\\reso \\Bigl ( \\Oma{\\lambda}\n \\Bigr )\n = 0$ for $\\lambda$ in a neighbourhood of $s \\lambda_0$ (since $s \\lambda_0$\nis not in the support of $H_\\barb$). Applying\n(i), $\\reso \\Bigl (\n\\Oma{\\lambda} \\psi^J\n\\Bigr ) $\nmust also be zero.\n\n\\noindent{\\em Proof of (vi):} If $\\beta = \\{\\beta_1, \\dots,\n\\beta_l \\} $ span $\\liets$, and $\\lambda = \\sum_j \\lambda^j \\beta_j$\nwith all $\\lambda^j > 0$, we have\n$$\\reso \\Bigl ( \\Oma{\\lambda} \\Bigr ) = \\frac{1}{(2 \\pi i)^l}\n\\intt \\frac{ [d \\psi] e^{i \\sum_j \\lambda^j (\\psi_j - i \\vt_j) } }\n{\\prod_{k = 1}^l (\\psi_k - i \\vt_k ) } , $$\nwhere the $\\vt_k = \\beta_k (\\vt) > 0$.\nBut $ [d \\psi] = d \\psi_1 \\dots d \\psi_l\/(\\det \\barb)$,\nwhere $\\psi_j = \\beta_j(\\psi)$.\nSince the integrals over $\\psi_1, \\dots, \\psi_l$ may be\ncompleted to integrals over semicircular contours\n$C_+(R) $ in the\nupper half plane, for each of which the contour integral\nmay be evaluated by the Residue Theorem to give the\ncontribution $ 2 \\pi i$, we obtain the result.\n\n\n\\noindent{\\em Proof of (vii):} We have\n$$ \\int_{\\psi + i \\vt \\in {\\Bbb R }^l} \\frac{ e^{i \\lambda(\\psi)} }{P(i\\psi)} [d \\psi]\n= (2 \\pi i)^l i^{-N} \\reso(\\Oma{\\lambda}) =\nH_\\barb (\\lambda). $$\nAlso, by (i),\n$$\\sum_{m_1, \\dots,\nm_l \\ge 0} \\frac{(2 \\pi i)^l i^{-N} }{m_1!\\dots m_l! }\n\\limpl\n\\reso \\Bigl (\n(i \\lambda^1\\psi_1)^{m_1}\n\\dots (i \\lambda^l\\psi_l)^{m_l} \\Oma{s \\lambda_0} \\Bigr ) $$\n$$ = \\sum_{m_1, \\dots,\nm_l \\ge 0} \\frac{(2 \\pi i)^l i^{-N}\n(\\lambda^1)^{m_1} \\dots\n(\\lambda^l)^{m_l}}\n{m_1!\\dots m_l! }\n\\limpl ( \\partial\/\\partial \\lambda^1)^{m_1} \\dots\n( \\partial\/\\partial \\lambda^l)^{m_l} \\reso (\\Oma{\\lambda} )\n|_{\\lambda = s \\lambda_0} $$\n$$ = \\sum_{m_1, \\dots,\nm_l \\ge 0} \\frac{\n(\\lambda^1)^{m_1} \\dots\n(\\lambda^l)^{m_l}}\n{m_1!\\dots m_l! }\n\\limpl ( \\partial\/\\partial \\lambda^1)^{m_1} \\dots\n( \\partial\/\\partial \\lambda^l)^{m_l} H_\\barb(\\lambda)\n|_{\\lambda = s \\lambda_0} $$\nwhich is equal to $H_\\barb(\\lambda)$ since $H_\\barb$ is\na polynomial on certain conical subregions\nof $\\liets$, and there is such\na subregion containing the ray $\\lambda = s \\lambda_0$.$\\square$\n\n\n\n\\noindent{\\underline{ Example.}}\nIn the following simple example, the explicit formula\n for $H_\\barb$ follows immediately from the definition of $H_\\barb$ in\nProposition \\ref{p3.5}(a). The example is included to show how\nthis result may alternatively be derived by successive contour\nintegrations.\n\nSuppose $l = 2$ and\n$N = 3$, and $\\beta_1(\\psi) = \\psi_1$, $\\beta_2(\\psi) = \\psi_2$,\n$\\beta_3(\\psi) = \\psi_1 + \\psi_2$. We compute\n\\begin{equation} \\label{10.6}{\\mbox{$\\cal R$}} = \\reso \\Bigl ( \\frac{e^{i \\lambda(\\psi)} }\n{\\psi_1 \\psi_2 (\\psi_1 + \\psi_2)} \\Bigr ) \\end{equation}\nwhere $\\lambda(\\psi) = \\lambda^1 \\psi_1 + \\lambda^2 \\psi_2. $\nWe assume $\\lambda^1, \\lambda^2 > 0$, and $\\vt_1, \\vt_2 > 0 $.\nThe quantity (\\ref{10.6}) is given by\n\\begin{equation} {\\mbox{$\\cal R$}} =\n\\frac{1}{(2 \\pi i)^2}\n\\int_{\\psi_2 + i \\vt_2 \\in {\\Bbb R }} d \\psi_2 \\frac{e^{i \\lambda^2 \\psi_2}}{\\psi_2}\n\\int_{\\psi_1+ i \\vt_1\\in {\\Bbb R }}\n \\frac{e^{i \\lambda^1 \\psi_1}}{(\\psi_1 + \\psi_2)\\psi_1} . \\end{equation}\n(This integral in fact gives the Duistermaat-Heckman\npolynomial $F_T (\\pist e^{\\iins \\bom}) (\\lambda)$ near $\\mu_T(F) $ where\n$F$ is\n a fixed point of the action of\n$T$ on $X$, when $X$ is a\ncoadjoint orbit of $SU(3)$ and $T\\cong (S^1)^2$ is the\nmaximal torus : see \\cite{JGP}.)\nWe compute this by first integrating over $\\psi_1$: since $\\lambda^1 > 0 $,\nthe integral may be completed to a contour integral over a semicircular\ncontour in the upper half plane. We obtain contributions\nfrom the two residues $\\psi_1 = 0 $ and $\\psi_1 = - \\psi_2$.\nHence we have\n\\begin{equation} {\\mbox{$\\cal R$}} =\n\\frac{1}{(2 \\pi i)}\n\\int_{\\psi_2 + i \\vt_2 \\in {\\Bbb R }} d \\psi_2 \\frac{e^{i \\lambda^2 \\psi_2}}{\\psi_2^2}\n-\\frac{1}{(2 \\pi i)}\n\\int_{\\psi_2 + i \\vt_2 \\in {\\Bbb R }} d \\psi_2 \\frac{e^{i (\\lambda^2-\n\\lambda^1) \\psi_2}}{\\psi_2^2} . \\end{equation}\nSince $\\lambda^2 > 0 $, the first of these integrals may\nbe completed to a contour integral over a semicircular\ncontour in the upper half plane, and the residue\nat $0$ yields the value $i \\lambda^2$. If $\\lambda^2 - \\lambda^1 > 0 $, the second\nintegral likewise yields $- i (\\lambda^2 - \\lambda^1)$.\nHowever if $\\lambda^2 - \\lambda^1 < 0 $ the second integral\nis instead equal to a contour integral over a semicircular\ncontour in the {\\em lower} half plane, which\ndoes not enclose the pole at $0$, and hence the second integral gives $0$.\nThus we have\n\\begin{equation} \\label{9.009}(2 \\pi i)^2 \\reso(\\Oma{\\lambda}) = \\cases{i \\lambda^2, &\n$\\lambda^1 > \\lambda^2$ \\cr\ni \\lambda^1, &\n$\\lambda^2 > \\lambda^1$. \\cr } \\end{equation}\n\nAccording to (iv) and (vii), the quantity ${\\mbox{$\\cal R$}}$ is\nalso given by\n\\begin{equation} {\\mbox{$\\cal R$}} = \\limpl \\int_{\\psi+ i \\vt\\in {\\Bbb R }^2}\n\\frac{ e^{i s (\\lambda^1 \\psi_1 + \\lambda^2 \\psi_2)} (i \\lambda^1 \\psi_1\n+ i \\lambda^2 \\psi_2)[d \\psi]}{\\psi_1 \\psi_2 (\\psi_1 + \\psi_2)} \\end{equation}\n$$ =\n \\limpl (i \\lambda^1) \\int_{\\psi+ i \\vt\\in {\\Bbb R }^2}\n\\frac{ e^{i s [\\lambda^1 (\\psi_1 + \\psi_2) + (\\lambda^2 - \\lambda^1)\\psi_2]}\n[d \\psi] }{(\\psi_1 + \\psi_2) \\psi_2}\n+\n \\limpl (i \\lambda^2) \\int_{\\psi+ i \\vt\\in {\\Bbb R }^2}\n\\frac{ e^{i s [(\\lambda^1 - \\lambda^2)\\psi_1 + \\lambda^2 (\\psi_1 + \\psi_2)]}\n[d \\psi] }{\\psi_1 (\\psi_1 + \\psi_2) }\n. $$\nThis clearly gives the result (\\ref{9.009}).\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n{ \\setcounter{equation}{0} }\n\\section{Examples}\n\nIn this section we shall show\nin the case $K = SU(2)$ how Corollary \\ref{c8.2} may\nbe used to prove relations in the cohomology\nring $H^*(\\xred)$ for two specific $X$.\nThese $X$ are the examples treated at the end of\nSection 6 of \\cite{Ki2}. There, all the relations\nin the cohomology ring are determined, which is equivalent\nto exhibiting\nall the vanishing intersection\npairings. We shall show how the results\nof the present paper may be used to show these are indeed vanishing\n intersection pairings, although we shall not\nbe able to rederive the result that there are no others.\n\n\n\\noindent\\underline{\\em Example 1: $X = ({\\Bbb P}_1)^N, $ $N$ odd.}\nConsider the action of $K = SU(2)$ on the space\n$X = ( {\\Bbb P } _1)^N$ of ordered $N$-tuples\nof points on the complex projective line\n$ {\\Bbb P } _1$, defined by the $N$th tensor\npower of the standard representation of $K$ on\n${\\Bbb C }^2$.\nEquivalently when $ {\\Bbb P } _1$ is identified with\nthe unit sphere $S^2$ in ${\\Bbb R }^3$ then $K$ acts\non $X = (S^2)^N$ by rotations of the sphere. When\nthe dual of the Lie algebra of $K$ is identified\nsuitably with ${\\Bbb R }^3$ then the moment map\n$\\mu$ is given (up to a constant scalar\nfactor depending on the conventions used)\nby $$\\mu(x_1, \\dots, x_N) = x_1 + \\dots + x_N$$\nfor $x_1 , \\dots, x_N \\in S^2$. We assume\nthat $0$ is a regular value for $\\mu$; this happens\nif and only if there is no $N$-tuple\nin $\\mu^{-1}(0)$ containing a pair of antipodal\npoints in $S^2$ each with multiplicity $N\/2$,\nand so $0$ is a regular value if and only\nif $N$ is odd.\n\nIn order to apply Corollary \\ref{c8.2} we note that\nthe fixed points of the action of the standard\nmaximal torus $T$ of $K$ are the $N$-tuples\n$(x_1, \\dots, x_N)$ of points in\n$ {\\Bbb P } _1$ such that each\n$x_j$ is either $0$ or $\\infty$. We shall index these\nby sequences $n = (n_1, \\dots, n_N)$ where\n$n_j = + 1$ if $x_j = 0$ and $n_j = - 1$\nif $x_j = \\infty$.\nDenote by $e_n$ the fixed point indexed\nby $n$. Then\n$$ \\mu_T(e_n) = \\sum_{j = 1}^N n_j $$\nand the weights of the action of $T$\nat $e_n$ are just $\\{ n_1, \\dots, n_N\\}$.\nHence the sign of the product of weights\nat $e_n$ is $\\prod_j n_j$ and its\nabsolute value is $1$.\n\nThe cohomology ring $H^*(X)$ has $N$\ngenerators $\\xi_1, \\dots, \\xi_N$ say, of degree two,\nsatisfying $\\xi_j^2 = 0$\nfor $1 \\le j \\le N$. The equivariant cohomology\nring $H^*_T(X)$ with respect to the torus $T$\nhas generators\n$\\xi_1, \\dots, \\xi_N$ and $\\alpha$ of\ndegree two subject to the relations\n$$(\\xi_j)^2 = \\alpha^2$$\nfor $1 \\le j \\le N$. The Weyl group action sends $\\alpha$\nto $-\\alpha$ so $\\hk(X)$ has generators\n$\\xi_1, \\dots, \\xi_n, \\alpha^2$ subject to the\nsame relations.\n\nAccording to the last example of section 6 of\n\\cite{Ki2}, the kernel of the map $\\hk(X) \\to H^*(\\xred)$\nis spanned by elements of the form\n\\begin{equation} \\label{8.beta} (1\/\\alpha) \\Bigl ( q(\n\\xi_1, \\dots, \\xi_N, \\alpha) \\prod_{i \\in Q} (\\xi_i + \\alpha)\n- q(\n\\xi_1, \\dots, \\xi_N, -\\alpha) \\prod_{i \\in Q} (\\xi_i - \\alpha) \\Bigr ) \\end{equation}\nfor some $Q \\subset \\{ 1, \\dots, N\\} $ containing\nat least $(N+1)\/2$ elements\nand some polynomial $q$ in $N + 1$ variables\nwith complex coefficients.\nWe can use Corollary \\ref{c8.2}\nto give an alternative proof that the evaluation against the\nfundamental class $[\\xred]$ of the image in\n$H^*(\\xred)$ of any element\nof this form of degree $N-3$ is zero. This amounts\nto showing that\n\\begin{equation} {\\rm Res}_0 \\frac{1}{\\psi^{N-1} }\n\\sum_{\\stackrel{\\indd_j = \\pm 1,}{ \\sum_j \\indd_j > 0} } \\Bigl ( \\prod_j\n\\indd_j \\Bigr )\n\\Bigl \\{ q(\\psi \\indd_1, \\dots, \\psi \\indd_N, \\psi) \\prod_{i \\in Q}\n\\psi(\\indd_i + 1)\n- q(\\psi \\indd_1, \\dots, \\psi \\indd_N, -\\psi) \\prod_{i \\in Q}\n\\psi(\\indd_i - 1) \\Bigr \\} \\end{equation}\nis zero when $q$ is homogeneous of degree $N - 2 - |Q|$.\nIn other words it amounts to showing\nthat $\\dell = 0$ for any $\\dell$ of the form\n\\begin{equation} \\dell =\n\\sum_{\\stackrel{\\indd_j = \\pm 1,}{ \\sum_j \\indd_j > 0}}\n\\Bigl ( \\prod_j \\indd_j \\Bigr )\n\\Bigl \\{\nq( \\indd_1, \\dots, \\indd_N, 1) \\prod_{i \\in Q}\n(\\indd_i + 1)\n- q( \\indd_1, \\dots, \\indd_N, -1) \\prod_{i \\in Q}\n(\\indd_i - 1) \\Bigr \\} \\end{equation}\nwhere $q$ is homogeneous of degree $N - 2 - |Q|$.\nLet us assume without loss of generality that\n$q (\\xi_1, \\dots, \\xi_N, \\alpha) = \\prod_i \\xi_i^{r_i} \\alpha^p$\nwhere $p + \\sum_i r_i + |Q| = N-2$.\nThus $p - 1 = |Q| + \\sum_i r_i $ (mod $2$) since\n$N$ is odd. Hence we have that\n\\begin{equation} \\dell =\n \\sum_{\\stackrel{\\indd_j = \\pm 1,} {\\sum_j \\indd_j > 0}\n}\n\\prod_j (\\indd_j^{r_j + 1} ) \\Bigl \\{\n\\prod_{i \\in Q} (\\indd_i + 1) +\n(-1)^{|Q|} \\prod_k (-1)^{r_k} \\prod_{i \\in Q} (\\indd_i - 1) \\:\n\\Bigr \\} \\end{equation}\n\\begin{equation} \\phantom{a} = \\sum_{\\stackrel{\\indd_j = \\pm 1,} {\\sum_j \\indd_j > 0}\n}\n\\prod_j (\\indd_j^{r_j + 1} )\n\\prod_{k \\in Q} (\\indd_k + 1)\n-\n \\sum_{\\stackrel{\\Indd_j = \\pm 1,}{ \\sum_j \\Indd_j < 0} }\n\\prod_j (\\Indd_j^{r_j + 1} )\n\\prod_{k \\in Q} (\\Indd_k + 1) \\end{equation}\nwhere we have introduced $\\Indd_j = - \\indd_j$.\n\nNow the second sum vanishes, for if $\\Indd_j = 1$\nfor all $j \\in Q$ then we must have $\\sum_j \\Indd_j > 0$\nsince $|Q|> N\/2$.\nHence we are reduced to proving the vanishing of\n$$ \\sum_{ \\indd\\in \\Gamma}\n\\prod_j \\indd_j^{r_j + 1} $$\nwhere\n$$\\Gamma = \\{ \\indd \\: | \\: \\sum_j \\indd_j > 0, \\;\n\\indd_j = 1 \\; \\mbox{for $j \\in Q$} \\}. $$\nHence we have to prove the vanishing\nof $$\\dell = \\sum_{\\indd_j = \\pm 1, j \\notin Q}\n\\prod_{j \\in S} n_j$$\nwhere $S$ is the set $\\{ j \\notin Q \\, | \\,\nr_j = 0 \\pmod{2} \\}. $\nThe sum thus vanishes by cancellation in pairs provided $S$ is\nnonempty. However if $S$ were empty then\n$r_j = 1 \\pmod{2}$ for all $j \\notin Q$,\nso $r_j \\ge 1$ for all $j \\notin Q$,\nwhich is impossible since $\\sum_j r_j + |Q| \\le N-2$.\nThis proves the desired result.\n\n\n\\noindent\\underline{\\em Example 2: $X = {\\Bbb P } _N$, $N$ odd.}\n A closely related example\nis given by the action of $K = SU(2)$ on the complex projective\nspace\n$X = {\\Bbb P}^N $ defined by the $N$th symmetric\npower of the standard representation of $K$ on\n${\\Bbb C }^2$. Equivalently we can identify $X$ with\nthe space of\nof {\\em unordered}\n$N$-tuples of points in the complex\nprojective line $ {\\Bbb P } _1$ or the sphere $S^2$, and\nthen $K$ acts by rotations as in example $1$.\nWe take the symplectic form $\\om$ on $X$\nto be the Fubini-Study form on $ {\\Bbb P } _N$.\nThe moment map is given by the composition\nof the restriction map ${\\bf u}(N+1)^* \\to \\lieks$\nwith the map\n$\\mu: {\\Bbb P } _N \\to {\\bf u}(N+1)^* $ defined for\n$a \\in {\\bf u}(N+1)$ by\n$$ \\inpr{\\mu(x) , a} = (2 \\pi i |x^*|^2 )^{-1}\n\\bar{x^*}^t a x^*, $$\nwhere $x^* = (x^*_0, \\dots, x^*_N)$ is\nany point\nin ${\\Bbb C }^{N+1}$ lying over the point $x \\in {\\Bbb P } _N$.\nThe restriction of this moment map\nto $\\liets$ is\n$\\mu_T (x) = (2 \\pi i |x^*|^2 )^{-1} )\n\\sum_{j = 0}^N (N - 2j)|x^*_j|^2 $.\nAgain we assume that $N$ is odd in order\nto ensure that $0$ is a regular value of\nthe moment map $\\mu$.\n\nAgain the fixed points of the action of $T$ are\nthe $N$-tuples of points in $ {\\Bbb P } _1$ consisting\nentirely of copies of $0$ and $\\infty$. Equivalently\nthey are the points\n$e_0 = [1, 0, \\dots, 0]$,\n$e_1 = [0, 1, \\dots, 0]$,\n$\\dots, e_N = [0, \\dots, 0, 1]$ of\n$ {\\Bbb P } _N$. The image of $e_k$ under $\\mu_T$ is\n$\\mu_T(e_k) = N - 2 k = \\mu_k$ say. Since\n$\\diag (t, t^{-1} ) \\in T$ acts on $ {\\Bbb P } _N$\nby sending $[x_0, \\dots, x_j, \\dots, x_N]$\nto $[t^{-N} x_0, \\dots, t^{2j-N} x_j, \\dots, t^N x_N]$\nthe weights at $e_k$ are\n$$\\{ 2 (j - k): \\: 0 \\le j \\le N, \\; j \\ne k \\}$$\nThe number of negative weights at $e_k$ is equal to $k$\n(modulo $2$), and the absolute value of the product\nof weights at $e_k$ is\n$v_k = \\prod_{j \\ne k } |j - k| = 2^N k! (N-k)! $\n\n\n\nThe cohomology ring $H^*( {\\Bbb P } _N)$ is generated\nby $\\xi$ of degree two subject to the relation\n$\\xi^{N+1} = 0$.\nThe equivariant cohomology ring $H^*_T ( {\\Bbb P } _N)$\nis generated by $\\xi$ and $\\alpha$ of degree two\nsubject to the\nrelation $\\prod_{0 \\le j \\le N} (\\xi - (2j-N) \\alpha) = 0, $\nand the equivariant cohomology ring $\\hk( {\\Bbb P } _N)$\nis generated by $\\xi$ and $\\alpha^2$ subject to the\nsame relation.\n\nAccording to section 6 of \\cite{Ki2} the kernel\nof the natural map $\\hk(X) \\to H^*(\\xred)$\nis generated as an ideal in $\\hk(X) $ by $P_+(\\xi, \\alpha)$\nand $P_-(\\xi,\n\\alpha)\/\\alpha$ where\n$$P(\\xi, \\alpha) = \\prod_{k > N\/2} (\\xi + \\mu_k \\alpha) $$\nand\n$$P_\\pm(\\xi, \\alpha) = P (\\xi, \\alpha) \\pm P(\\xi, - \\alpha). $$\n(Note that $P_+ (\\xi, \\alpha)$ and $P_-(\\xi, \\alpha)\/\\alpha$\nare actually polynomials in $\\xi$ and $\\alpha^2$.)\nWe would like to check that the evaluation against the\nfundamental class $[\\xred]$\nof the image of $R_+(\\xi, \\alpha^2) P_+(\\xi, \\alpha) $\nand $R_-(\\xi, \\alpha^2) P_-(\\xi, \\alpha)\/\\alpha$ in\n$H^*(\\xred)$ is zero for any $R_\\pm(\\xi, \\alpha^2)$\n$\\in \\hk(X)$ of the appropriate degree.\n\nNow we have from the abelian fixed point formula that for any\n$S(\\gnx, \\gna^2)$,\n$$\\Pi^+_* (S(\\gnx, \\gna^2) ) =\n\\sum_{k < N\/2} (-1)^k\n\\frac{S(\\mu_k \\psi, \\psi^2) }{\\veee_k }\n\\psi^{-N}. $$\n(Here, if $\\zeta \\in \\hk(X)$, the notation $\\Pi^+(\\zeta)$\nmeans the portion of the abelian formula (\\ref{2.1})\nfor $\\pis(\\zeta)$\ncorresponding to fixed points $F$ for which $\\mu_T(F) > 0$.)\nTo evaluate this on the fundamental class of $\\xred$\nwe must then find the term of degree $-1$ in\n$\\nusym^2(\\psi) \\Pi^+_* (S(\\gnx, \\gna^2 ) )(\\psi) $, or in other words\nthe term of degree $N - 3$ in\n$\\sum_{k < N\/2}(-1)^k S(\\mu_k \\psi, \\psi^2) \/(\\veee_k )\n$.\nHaving found the term of degree $N-3$ in $\\psi$, we evaluate\nit at $\\psi = 1$ to get the residue.\nIn the case when $S(\\mu_k \\psi, \\psi^2) = R_+(\\mu_k \\psi, \\psi^2)\nP_+(\\mu_k \\psi, \\psi) $ or\n$S(\\mu_k \\psi, \\psi^2) = R_-(\\mu_k \\psi, \\psi^2)\nP_-(\\mu_k \\psi, \\psi)\/\\psi $\nis homogeneous of degree $N - 3$ in $\\psi$, we need to show that\n$$ \\sum_{k = 0 }^{(N-1)\/2} \\: (-1)^k\n\\frac{1}{\\veee_k } \\Bigl ( \\,\nR_\\pm (\\mu_k, 1) \\prod_{j \\ge N\/2} (\\mu_k + \\mu_j)\n\\pm R_\\pm(\\mu_k, -1) \\prod_{j \\ge N\/2} (\\mu_k - \\mu_j) \\: \\Bigr ) = 0. $$\nSince $\\mu_k = - \\mu_{N-k} $, we have $\\prod_{j \\ge N\/2}\n (\\mu_k + \\mu_j ) = 0$\nfor all $k < N\/2$, so we just have to prove the vanishing of\n$$\\sum_{k \\le N\/2} \\: (-1)^k\n\\frac{1}{ \\veee_k }\nR(\\mu_k) \\prod_{j \\ge N\/2} (\\mu_k - \\mu_j)\n $$\nfor every polynomial $R$ of degree at most $(N-1)\/2 - 2$,\nor without loss of generality the vanishing of\n$$ \\sum_{k \\le N\/2} (\\mu_k)^s \\frac{(-1)^k}{ \\prod_{l \\ne k}\n|l - k| } \\prod_{j \\ge N\/2} (\\mu_k - \\mu_j), $$\nwhere $s \\le (N-1)\/2 - 2$.\nSince $ \\prod_{l \\ne k}\n|l - k| = k! (N-k)!$ and $\\mu_k - \\mu_j = 2(j - k), $\nwe have that\n$$ \\prod_{j \\ge N\/2} |\\mu_k - \\mu_j | = 2^{(N+1)\/2} \\frac{(N - k)!}\n{( (N-1)\/2 - k )! } $$\nDefine $r = (N-1)\/2$.\nWe need to show the vanishing of\n$$\\sum_{k = 0}^r (N-2k)^s \\frac{(-1)^k (N-k)!}{k! (N-k)! (r - k)! }\n$$ for $s \\le r - 2$.\nIt then suffices to show the vanishing of\n$$\\sum_{k = 0}^r k^s (-1)^k \\colvec{r}{k} , \\phantom{bbbbb} \\mbox{\n$s \\le r - 2$.}$$\nThis follows since one may expand $(1- e^\\lambda)^r$ as a power series\nin $e^\\lambda$ using the binomial theorem: we have\n$$ (1 - e^\\lambda)^r = \\sum_{j= 0}^r (-1)^j \\colvec{r}{j}\n\\exp j \\lambda \\: = \\sum_{s \\ge 0} \\lambda^s\/s!\n\\sum_{j= 0}^r (-1)^j j^s \\colvec{r}{j}\n, $$\nbut the terms in this expansion corresponding to $s < r$ must vanish\nsince $1 - e^\\lambda = \\lambda h(\\lambda)$ for some function\n$h$ of $\\lambda$ which is analytic at $\\lambda = 0$.\n\n\n\n","meta":{"redpajama_set_name":"RedPajamaArXiv"}} diff --git a/data_all_eng_slimpj/shuffled/split2/finalztif b/data_all_eng_slimpj/shuffled/split2/finalztif new file mode 100644 index 0000000000000000000000000000000000000000..40a2616c03bfe1c4e6e655ef7c0b773bacccb976 --- /dev/null +++ b/data_all_eng_slimpj/shuffled/split2/finalztif @@ -0,0 +1,5 @@ +{"text":"\\section{Introduction}\n\\label{sec:intro}\n\nAs a fundamental task for video understanding, video action recognition has drawn much attention from the community and industry~\\cite{tran2015learning, carreira2017quo, tran2018closer, feichtenhofer2019slowfast}. Unlike image-related tasks, networks for video-related tasks are normally easier to overfit due to the complexity of the tasks~\\cite{tran2017convnet, tran2015learning, kataoka2020would}. The common practice is to firstly pre-train the network on large-scale datasets (\\eg, Kinetics~\\cite{carreira2019short} of up to $650,000$ video clips) and then finetune on downstream small datasets to obtain better performance~\\cite{feichtenhofer2019slowfast,qian2021spatiotemporal,pan2021videomoco,han2020self}.\n\nHowever, since annotating large-scale video datasets is time-consuming and expensive, training models on a large dataset collected with complete annotations is impeded. To utilize large-scale datasets with acceptable costs, some researchers have turned to designing semi-supervised learning models which have good generalization ability with limited annotations~\\cite{jing2021videossl,singh2021semi,zou2021learning,xiong2021multiview}. As pseudo-label based methods (\\eg, FixMatch~\\cite{sohn2020fixmatch} and MixMatch~\\cite{ berthelot2019mixmatch}) have shown outstanding performance on semi-supervised image classification, most previous video-based methods are heavily built on them to utilize the unlabeled data. Although these preliminary attempts have obtained acceptable results, most methods ~\\cite{jing2021videossl,zou2021learning} are just taking video clips as `images' in 3D without further consideration of the video properties. \n\n\nVideos are significantly different from images, and the key differences are the temporal information span in multiple frames and the inherent multimodal property. The temporal information refers to the motion signal between frames, and usually the features of contiguous frames from the same video change smoothly. \\zzrevise{The multimodal consistency refers to the features of multiple modalities in the same video clip should be consistent since they are encoding the same content.}{The multimodal consistency expects the features extracted from the same video clip to be consistent, as they encode identical content.} Without special designs to specifically focus on temporal information and multimodal consistency, the potential of semi-supervised action recognition is not fully unleashed.\n\n\nSome previous studies\\cite{wang2016temporal, zhao2018recognize} introduce temporal gradient\\footnote{The difference between two RGB video frames with a short interval.} as an additional modality to better utilize the temporal information encoded in videos as it is rich in motion signals. The temporal gradient can be formulated as:\n$TG = x_t^{RGB} - x_{t+n}^{RGB}$,\nwhere $x$ represents a video, $t$ denotes the frame index and $n$ denotes the interval for calculating temporal gradient. \n\n\nInspired by these studies, we made a trial with temporal gradient under the semi-supervised settings and found that a much better performance could be generated when the input frames in RGB are replaced with temporal gradient. As shown in~\\Cref{fig:motivation}, the Top-1 accuracy of temporal gradient is $\\sim$25\\% higher than using the RGB as input on the UCF-101 dataset with only $20$\\% of labeled data for training.\n\n\n\nWhy is the temporal gradient so much better than the RGB frames when the training data are limited? We hypothesize that the key is in the detailed and fine-grained motion signals encoded in the temporal gradient. The gradient along the temporal dimension is color-invariant and explicitly encodes the representative motion information of the actions in the video. This helps models generalize much easier when the labels are extremely limited. Therefore, in this paper, we propose to train a semi-supervised action recognition RGB based model to mimic both the fine-grained and high-level features from the temporal gradient. \n\n\nWe start from FixMatch~\\cite{sohn2020fixmatch}, a typical pseudo-label based semi-supervised model, as the baseline framework. However, without any further constraints in the feature level, pseudo-label based methods perform poorly in the case of very limited labels, as many generated pseudo-labels are inaccurate.\nTherefore, we propose two constraints to help the model extract temporal information in video with multiple modalities and improve the consistency between the multimodal representations. To leverage the detailed and fine-grained motion signals from temporal gradient, we propose a knowledge distillation strategy using block-wise dense alignment. It helps the student RGB model learn from the teacher temporal gradient model efficiently and effectively. To further improve high-level representation space across different modalities, we perform contrastive learning between the features from RGB and temporal gradient sequences to enforce the high-order similarity. Given the two constraints at the feature level, our proposed model is able to achieve much better performance.\n\nUnlike the existing methods, our model has two unique advantages. First, our model requires no additional computation or parameters for inference. In the training, we distill the knowledge from temporal gradient to the RGB-based network; in the testing, only the RGB model is required. Second, our model is simple, yet effective. We conducted experiments on multiple public action recognition benchmarks including UCF-101, HMDB-51, and Kinetics-400. Our proposed method significantly outperforms all the state-of-the-art methods by a large margin.\n\n\n\\section{Related Work}\n\\noindent\\textbf{Semi-supervised learning in images.} The semi-supervised image classification task has been well studied and many methods have been proposed including Pseudo-Label~\\cite{lee2013pseudo}, S4L~\\cite{zhai2019s4l}, MeanTeacher~\\cite{tarvainen2017mean}, MixMatch~\\cite{berthelot2019mixmatch}, UDA~\\cite{xie2020unsupervised}, FixMatch~\\cite{sohn2020fixmatch}, UPS~\\cite{rizve2020defense}, etc. The Pseudo-Label~\\cite{lee2013pseudo} is an early method which uses the confidence (softmax probabilities) of the unlabeled data as labels and to train the network jointly with a small ratio labeled data and much more unlabeled data. Many improved versions of Pseudo-Label have been proposed while the key is to improve the quality of the labels~\\cite{sohn2020fixmatch, rizve2020defense}. Following a state-of-the-art method on image classification---FixMatch~\\cite{sohn2020fixmatch}, many FixMatch-alike methods achieve the state-of-the-art performance on many other tasks including detection~\\cite{wang20213dioumatch}, segmentation~\\cite{zou2020pseudoseg}, etc. Although these methods achieve remarkable performance on image-based tasks, some recent studies show that the performances are not satisfying when directly applying these methods to video semi-supervised tasks~\\cite{jing2021videossl, singh2021semi}.\n\n\\smallskip\\noindent\\textbf{Semi-supervised learning in videos.} Although there have been a few semi-supervised video action recognition methods~\\cite{jing2021videossl,singh2021semi,zou2021learning, xiong2021multiview} proposed, most of them directly apply the image-based methods to videos with less focus on the temporal dynamics of videos. VideoSSL~\\cite{jing2021videossl} made the first attempt to build a benchmark for the video semi-supervised learning task by training the network with ImageNet pre-trained models, which explicitly guides the model to learn the appearance information in each video. It also shows that the existing image-based methods (\\eg Pseudo-Label~\\cite{lee2013pseudo}, Mean-Teacher~\\cite{tarvainen2017mean}) have inferior performance on video semi-supervised benchmarks. TCL~\\cite{singh2021semi} is a recently proposed method that jointly optimizes the network by employing a self-supervised auxiliary task and a group contrastive learning. By using multimodal data, MvPL~\\cite{xiong2021multiview} achieved the state-of-the-art performance by sharing the same model with different input modalities (RGB, temporal gradient, and optical flow) and generating pseudo labels with the ``confidence'' of multiple modalities. Compared with these methods, our method specifically focuses on learning the temporal information from Temporal Gradient with our proposed constraints and significantly outperforms the state-of-the-art methods on multiple public benchmarks.\n\n\\smallskip\\noindent\\textbf{Multimodal Video Feature Learning.} Videos could be viewed from different modalities while each modality encodes information from a unique perspective. For example, a video in general RGB couples both spatial and temporal information, the temporal gradient is color invariant which mainly encodes the difference between frames, and the optical flow explicitly encodes the motion information for each pixel. The features from different modalities are normally complementary to each other, and therefore the feature fusions are normally performed for better performance. The pioneer work is the Two-Stream~\\cite{simonyan2014two, feichtenhofer2016convolutional} model which fuses features from both RGB video clips and optical flow clips. With the complementary information from different modalities, the multimodal network is able to achieve better performance~\\cite{simonyan2014two, feichtenhofer2016convolutional, wang2015towards,wang2020makes,alwassel2019self}. However, there are additional computation and latency during inference. Unlike the normal multimodal feature fusion model, our model distills the motion-related representation from the temporal gradient to the base RGB model, while only the base model and RGB frames are needed during the inference stage. Moreover, our model outperforms the teacher model with only RGB as input during the inference.\n\n\\smallskip\\noindent\\textbf{Contrastive learning.} Contrastive learning methods have achieved remarkable performance on downstream image classification~\\cite{tian2020contrastive, chen2020simple,misra2020self, he2020momentum,grill2020bootstrap,caron2020unsupervised}. The key idea is that the representation can be learned by minimizing the distance of features of positive pairs (two views of the same data sample) and maximizing the distance of features of negative pairs (two different data samples). Recently, many researchers proposed to use temporal contrastive learning for video self-supervised learning~\\cite{han2020self, feichtenhofer2021large,qian2021spatiotemporal,pan2021videomoco,huang2021self}. In this paper, to better utilize the unlabeled data for semi-supervised action recognition, we propose to use the cross-modal contrastive loss to enforce the consistency of features from RGB clips and temporal gradient clips. We demonstrate that the cross-modal contrastive method is very effective for the proposed semi-supervised learning.\n\n\\section{Method}\nThe objective of our method is to improve the performance on the semi-supervised action recognition task by introducing and utilizing an effective view of videos: Temporal Gradient. The overview of our proposed framework is shown in \\Cref{fig:overview}, which consists of three main components: (1) the FixMatch framework with weak-strong augmentation strategy to generate better pseudo-labels for unlabeled data (2) cross-modal dense feature alignment between the features from RGB clips and TG clips for network to learn the fine-grained motion signals, and (3) cross-modal contrastive learning to learn high-level consistency feature across RGB and TG clips. The formulation for each component is introduced in the following subsections.\n\n\\subsection{FixMatch}\n\nConsidering a multi-class classification problem, we denote $\\mathcal{X} = \\{(x_i, y_i)\\}_{i=1}^{N_l}$ as the \\emph{labeled} training set, where $x_i \\in \\mathcal{R}^{T\\times H\\times W\\times 3}$ is the $i$-th sampled video clip, $y_i$ is the corresponding one-hot ground truth label, and $N_l$ is the number of data points in the labeled set.\nSimilarly, we denote $\\mathcal{U} = \\{x_j\\}_{j=1}^{N_u}$ as the \\emph{unlabeled} set, where $N_u$ is the number of data points in the unlabeled set. We use $f_{\\theta}$ to denote a classification model with trainable parameters $\\theta$. We use $\\alpha(\\cdot)$ to represent the weak (standard) augmentation (\\ie, random horizontal flip, random scaling, and random crop in video action recognition), and $\\mathcal{A}(\\cdot)$ to represent the strong data augmentation strategies (i.e., Randaugment~\\cite{cubuk2020randaugment}).\n\nThe network $f_{\\theta}$ is optimized with each video clip consisting of $T$ frames as $x_i$. \nFor a mini-batch of \\emph{labeled} data $\\{(x_i, y_i)\\}_{i=1}^{B_l}$, the network is optimized by minimizing the cross-entropy loss $\\mathcal{L}_l$ as\n\\begin{equation}\n\\small\n \\mathcal{L}_l = -\\frac{1}{B_l} \\sum_{i=1}^{B_l} \n y_i \\log f_{\\theta}(\\alpha(x_i)),\n \\label{eq:loss_l}\n\\end{equation} \nwhere $B_l$ is the number of labeled samples in a batch.\n\nFor a mini-batch of \\emph{unlabeled} data $\\{x_j\\}_{j=1}^{B_u}$, FixMatch enforces the model to produce consistent predictions of the same unlabeled data sample with different extent of augmentations. Specifically, pseudo labels $\\hat{y}$ for the unlabeled data are usually generated via confidence thresholding as: \n\\begin{equation}\n\\label{eq:pseudo_label}\n\\small\n \\mathcal{C} = \\{x_j | \\text{max} f_{\\theta}(\\alpha(x_j)) \\geq \\gamma\\},\n\\end{equation}\nwhere $\\gamma$ denotes a pre-defined threshold and $\\mathcal{C}$ is the confident example set from a mini-batch. The confident predictions $f_{\\theta}(\\alpha(x_j))$ in the set $\\mathcal{C}$ are then transformed into one-hot labels $\\hat{y}_j$ by taking the \\textit{argmax} operation. Then a cross-entropy loss $\\mathcal{L}_u$ will be optimized over the samples in $\\mathcal{C}$ and its generated one-hot labels as: \n\\begin{equation}\n\\small\n \\mathcal{L}_u = -\\frac{1}{B_u} \\sum_{x_j \\in \\mathcal{C}}\n \\hat{y}_j \\log f_{\\theta}(\\mathcal{A}(x_j)),\n \\label{eq:loss_u}\n\\end{equation}\nwhere $B_u$ is the number of unlabeled samples in a batch.\n\nWith the loss over both labeled and unlabeled data, the entire FixMatch is optimized with the objective function as: \n\\begin{equation}\n\\small\n \\mathcal{L}_{fm} = \\mathcal{L}_l + \\mathcal{L}_u.\n\\end{equation}\n\n\n\\begin{figure*}[t]\n\\centering\n\\includegraphics[width=\\textwidth]{figures\/main.pdf}\n\\caption{\\textbf{An overview of our proposed framework.} Our method consists of two parallel models with different input modalities (\\ie, RGB and TG) of video clips. The entire framework is jointly optimized with (1) two parallel FixMatch frameworks with pseudo-labeling, (2) cross-modal dense feature alignment, and (3) cross-modal contrastive learning. }\n\\label{fig:overview}\n\\vspace{-2mm}\n\\end{figure*}\n\\subsection{Parallel Framework for Temporal Gradient}\n\\label{sec:parallel}\n\n\nTemporal gradient (TG) $(\\frac{\\partial V}{\\partial t})$ between two RGB frames in a video encodes the appearance change and corresponds to the temporal information that changes dynamically. Therefore, the response is accentuated by the moving objects, especially the boundaries. FixMatch\\cite{sohn2020fixmatch} is originally designed for the image classification task and pays little attention to the temporal information of videos, therefore, we extend it to jointly train with RGB and TG to explicitly focus more on capturing the temporal information. To avoid additional computation and delays for processing temporal gradients during model inference on unseen videos, we propose to distill fine-grained motion signals from TG to RGB without introducing extra input or parameters for inference.\n\n\nThe RGB and temporal gradient information are complementary with each other. The RGB encodes spatial and temporal information in a general way, while the temporal gradient has a focus on the motion signals, as illustrated in \\Cref{fig:motivation}. Therefore, for each video clip, the predictions from both RGB network and TG network are averaged and then used to generate the pseudo labels. In this way, the fused pseudo-label generation is reformulated as:\n\\begin{equation}\n\\label{eq:pseudo_label_avg}\n\\small\n \\mathcal{C} = \\{x_j | \\text{max} (\\frac{f_{\\theta_{R}}(\\alpha(x_j^{RGB})) + f_{\\theta_{T}}(\\alpha(x_j^{TG}))}{2} ) \\geq \\gamma\\}.\n\\end{equation}\n\n\nHaving access to both features from RGB and TG, the quality of the fused pseudo labels are more accurate than the predictions from each model alone, and a more detailed ablation study is provided in \\Cref{sec:Abla}. The fused pseudo labels will be jointly used with unlabeled data to train both the TG and RGB model. For the temporal gradient model, the training objective is also a summation of \\Cref{eq:loss_l} and \\Cref{eq:loss_u} but for TG.\n\\begin{equation}\n\\small\n \\mathcal{L}_{fm}^{TG} = \\mathcal{L}_{l}^{TG} + \\lambda_u \\mathcal{L}_u^{TG}.\n\\end{equation}\n\n\n\\subsection{Cross-modal Dense Feature Alignment}\n\\label{sec:alignemnt}\n\nTo learn detailed fine-grained motions from temporal gradient, we propose to distill the knowledge from temporal gradient model to the RGB model. The similarities between the features from both temporal gradient and RGB clips are minimized by the cross-model dense feature alignment module as: \n\\begin{equation}\n\\label{eq:alignment obj}\n\\small\n\\min \\left[\\mathcal{D}\\left(\\mathcal{F}^{RGB}_i, \\mathcal{F}^{TG}_i\\right)\\right],\n\\end{equation} where $\\mathcal{F}^{RGB}_i , \\mathcal{F}^{TG}_i\\in \\mathbb{R}^{C_i \\times T_i \\times H_i \\times W_i}$ denote the output features of the $i$-th block in the RGB and TG models, and $\\mathcal{D}$ represents a pairwise function evaluating the representation differences. There are many choices for $\\mathcal{D}$ and we experiment with three different functions: L1, L2 and Cosine Similarity losses (shown in \\Cref{eq:alignment func}, where $\\|\\cdot\\|_{1}$ and $\\|\\cdot\\|_{2}$ are $\\ell_{1}\/\\ell_{2}$-norm). A more detailed discussion is provided in \\Cref{sec:Abla}.\n\\begin{align}\n\\label{eq:alignment func}\n\\small\n\\begin{split}\n\\mathcal{D}_{L1}\\left(\\mathcal{F}_{1}, \\mathcal{F}_{2}\\right)&={\\left\\|\\mathcal{F}_{1}-\\mathcal{F}_{2}\\right\\|_{1}},\n\\\\\n\\mathcal{D}_{L2}\\left(\\mathcal{F}_{1}, \\mathcal{F}_{2}\\right)&={\\left\\|\\mathcal{F}_{1}-\\mathcal{F}_{2}\\right\\|_{2}},\n\\\\\n\\mathcal{D}_{cos}\\left(\\mathcal{F}_{1}, \\mathcal{F}_{2}\\right)&=-\\frac{\\mathcal{F}_{1}}{\\left\\|\\mathcal{F}_{1}\\right\\|_{2}} \\cdot \\frac{\\mathcal{F}_{2}}{\\left\\|\\mathcal{F}_{2}\\right\\|_{2}}.\n\\end{split}\n\\end{align}\n\n\nAn key setting in our online knowledge distillation method is the stop-gradient $(stopgrad)$ operation on the temporal gradient side, which means the teacher model would not receive any gradient from the alignment loss. This helps the TG model avoid degeneration by the alignment with the RGB student model. As shown in \\Cref{eq:alignment loss}, the alignment loss term for learning fine-grained motion features is:\n\\begin{equation}\n\\label{eq:alignment loss}\n\\small\n\\mathcal{L}_{kd} = \\left[\\mathcal{D}\\left(\\mathcal{F}^{RGB}_i, stopgrad(\\mathcal{F}^{TG}_i)\\right)\\right].\n\\end{equation}\n\n\\subsection{Cross-modal Contrastive Learning}\n\\label{sec:contrastive}\n\nThe dense feature alignment explicitly enables the RGB network to mimic the fine-grained motion signals from temporal gradient. We hypothesize that the global high-level representations across different modalities are also valuable and crucial. Therefore, cross-modal contrastive learning is employed as another module to discover the mutual information that coexists in both TG and RGB clips.\n Following the principle of SimCLR\\cite{chen2020simple} and CMC\\cite{tian2020contrastive}, we form the contrastive learning with positive pairs and negative pairs. Specifically, we consider the two modalities of the same video clip as a positive pair $\\{k^{+}\\}$ and the two modalities of different video clips as negative pairs $\\{k^{-}\\}$. The learning objective is to maximize the similarity of positive pairs and minimize the similarity of negative ones. We adopt \\mbox{InfoNCE} loss \\cite{oord2018representation} as the objective function over the features extracted from RGB and TG:\n\\begin{equation}\\label{eq:infonce} \t\\small\n\t\\mathcal{L}_{clr} = -\\log{\\frac{ {\\sum_{k \\in \\{k^+\\}}} \\exp\\left({\\mathrm{sim}(q, k) \/ \\tau}\\right)}{ {\\sum_{k \\in \\{k^+, k^-\\}}} {\\exp\\left({\\mathrm{sim}(q, k) \/ \\tau}\\right)} }},\n\\end{equation} with $\\tau$ being a temperature hyper-parameter for scaling.\nAll embeddings are $\\ell_2$ normalized and dot product (cosine) similarity is used to compare them $\\mathrm{sim}(q, k) = q^\\top k \/ \\lVert q\\rVert \\lVert k\\rVert$.\n\t\nIt is worth noting that this cross-modal contrastive learning directly uses all weakly augmented samples of the two modalities ($\\alpha(x^{RGB\/TG}_i)$) in the FixMatch, including both labeled (the labels are not used) and unlabeled data. Therefore, there is no additional computation for the data loading and preprocessing.\n\n\n\\smallskip\\noindent\\textbf{Total Loss}:\nOur entire model based is jointly trained with cross-entropy loss over labeled data,cross-entropy loss over the unlabeled data with pseudo-labels, the dense alignment over both labeled and unlabeled data, and the cross-modal contrastive loss over both labeled and unlabeled data. Overall, the final objective function of our method is:\n\\begin{equation}\n\\small\n \\mathcal{L}_{total} =w_{fm} (\\mathcal{L}_{fm}^{RGB} + \\mathcal{L}_{fm}^{TG}) + w_{kd}\\mathcal{L}_{kd} + w_{clr}\\mathcal{L}_{clr}.\n\\end{equation}\n\n\n\\begin{table*}[htbp]\n\t\t\\centering\n\t\t\\tablestyle{6pt}{1.1}\n\t\t\\small\n \\begin{tabular}{cc|cc|cc|cc|cc|cc}\n \\shline\n && \\multicolumn{4}{c|}{Kinetics-400} & \\multicolumn{4}{c|}{UCF-101} & \\multicolumn{2}{c}{HMDB-51}\n \\\\ \\hline\n & & \\multicolumn{2}{c|}{1\\%} & \\multicolumn{2}{c|}{10\\%} & \\multicolumn{2}{c|}{10\\%} & \\multicolumn{2}{c|}{20\\%}\n & \\multicolumn{2}{c}{50\\%}\n \\\\ \\shline\n Alignment & Contrast & Top-1 & Top-5 & Top-1 & Top-5 & Top-1 & Top-5 & Top-1 & Top-5\n & Top-1 & Top-5 \n \\\\ \\shline\n \\xmark & \\xmark & 5.4 & 17.0 & 40.2 & 65.4 & {38.4} & {64.8} & {54.1} & {78.1} \n & 37.8 &\t68.6\n \\\\\n \\cmark & \\xmark & 9.4 & 25.5 & 43.5 & 68.8 & 60.4 & 84.4 & 74.6 & 91.7 &47.3 &74.8 \\\\\n \\xmark & \\cmark & 5.2 & 23.1 & 42.6 & 67.4 & 58.0 & 82.5 & 68.6 & 89.2\n & 46.1 & 73.8\n \\\\\n \\cmark & \\cmark &\\textbf{9.8} & \\textbf{26.0} & \\textbf{43.8} & \\textbf{69.2} & \\textbf{62.4} & \\textbf{84.9} & \\textbf{76.1} & \\textbf{92.1}\n & \\textbf{48.4}\t& \\textbf{75.9}\n \\\\ \n \\shline \n \\end{tabular}\n\t\t\\centering\n\t\t\\caption{\\textbf{Effectiveness of the cross-modal alignment and contrastive learning.} The results are evaluated on the validation sets. The first row shows the results of the FixMatch baseline model without any proposed modules.}\n\t\t\\label{tab:abla_major}\n\t\t\\vspace{-4mm}\n\t\\end{table*}\n\t\n\t\n\n\n\n\\section{Experimental Results}\n\\subsection{Datasets and Evaluation}\n\\noindent\\textbf{Datasets.} Following previous state-of-the-art semi-supervised video action recognition methods~\\cite{jing2021videossl,zou2021learning, xiong2021multiview}, we evaluate our method on three public action recognition benchmarks: UCF-101~\\cite{soomro2012ucf101}, HMDB-51~\\cite{kuehne2011hmdb}, and Kinetics-400~\\cite{kay2017kinetics}. UCF-101 is a widely used dataset which consists of $13,320$ videos belonging to $101$ classes. HMDB-51 is a smaller dataset which consists of $6,766$ videos with $51$ classes. For UCF-101 and HMDB-51, we follow the data splits that released by VideoSSL\\cite{jing2021videossl}. The Kinetics-400 dataset is a large-scale dataset\nconsisting of $\\sim$235k training videos and $\\sim$20k validation videos belonging to 400 classes. For Kinetics-400, we follow the most recent state-of-the-art method MvPL~\\cite{xiong2021multiview} by forming two balanced labeled subsets by randomly sampling 6 and 60 videos per class for 1\\% and 10\\% settings.\n\n\\smallskip\\noindent\\textbf{Evaluation.}\nWe report Top-1 accuracy for major comparisons and Top-5 accuracy for some ablation studies.\n\n\\subsection{Implementation Details}\n\\label{sec:implementation}\n\\noindent\\textbf{Network architecture.} For a fair comparison with the state-of-the-art methods~\\cite{jing2021videossl, xiong2021multiview}, the FixMatch~\\cite{sohn2020fixmatch} framework is used as the backbone model while the 3D ResNet-18~\\cite{tran2018closer, he2016deep} is adopted as feature extractors for both RGB and TG (\\Cref{sec:parallel}) modalities. For each feature extractor, two individual contrastive heads with 3-layer non-linear MLP architecture are added for the cross-modal contrastive learning (\\Cref{sec:contrastive}).\n\n\\smallskip\\noindent\\textbf{Video augmentations.} There are two types of data augmentations: weak augmentation and strong augmentation. For the weak augmentation, the random horizontal flipping, random scaling, and random cropping following \\cite{zou2021learning}. To be specific, given a video clip, we firstly resize the video making the short side be $256$, and then a randomly resized crop operation is performed. The cropped clips are then resized to 224$\\times$224 pixels and flipped horizontally with a $50$\\% probability. For strong augmentation, the RandAugment~\\cite{cubuk2020randaugment} is chosen which randomly selects a small set of transformations from a large augmentation pools (\\eg, rotation, color inversion, translation, contrast adjustment, etc.) for each sample and then performs the selected data augmentation over the samples. It is worth noting that both the teacher (TG) and student (RGB) share the same weak augmentation (\\ie, the inputs are identically cropped in the same area and both flipped or not). This provides a direct positional information matching, which plays a crucial role for the dense alignment in \\Cref{sec:parallel}. \n\n\n\\smallskip\\noindent\\textbf{Training details.} All experiments are done with an initial learning rate of 0.2 on 8 GPUs by following the settings in~\\cite{feichtenhofer2019slowfast,zou2021learning, xiong2021multiview} using the cosine learning rate decaying scheduler~\\cite{loshchilov2016sgdr} and also a linear warm-up strategy \\cite{goyal2017accurate}. We use momentum of 0.9 and weight decay of 10$^\\text{-4}$. Dropout \\cite{srivastava2014dropout} of 0.5 is used before the final classifier layer to reduce the over-fitting. Following~\\cite{zou2021learning}, each mini-batch consists of 5 labeled data clips and 5 unlabeled data clips, while each input clip consists of 8 frames with a sampling stride of 8, which covers 64 frames of the raw video. We consistently train our models with 180 and 360 epochs for all experiments on UCF-101 and HMDB-51, while 45 (1\\%) and 90 (10\\%) epochs are trained for Kinetics-400. More training details are provided in the supplementary material. For the pseudo-label threshold, we follow~\\cite{xiong2021multiview} which sets it to 0.3 for getting more training samples.\nFor the loss weights, $w_{fm}$ is set to 0.5 while $w_{kd}$ and $w_{clr}$ are set to 1.\n\n\\smallskip\\noindent\\textbf{Inference.} \nFollowing the recent state-of-the-art methods \\cite{feichtenhofer2019slowfast, zou2021learning, xiong2021multiview}, 10 clips are uniformly sampled for each video along its temporal axis and each clip is taken 3 crops of 256$\\times$256. A total of 3x10 crops are evaluated for each video.\n\n\n\n\n\\subsection{Effectiveness of the Cross-modal Dense Alignment and Contrastive Learning}\n\n\n\nWe begin with a direct comparison to examine our hypothesis:\n\\emph{multimodal constraints on local and global features can serve as two complementary extensions to existing semi-supervised methods} (FixMatch~\\cite{sohn2020fixmatch} as the baseline).\nTo this end, our dense alignment (\\Cref{sec:alignemnt}) is devised to regularize the local features, and our contrastive loss (\\Cref{sec:contrastive}) is developed to distinguish global features. \nFor a fair comparison, we have ablated four experimental settings (detailed in \\Cref{tab:abla_major}): (1) none, (2) alignment-only, (3) contrast-only, and (4) both.\nKinetics-400, UCF-101, and HMDB-51 with different labeled data ratios (\\ie, 1\\%, 10\\%, 20\\%, and 50\\%) are used to ensure the generalizability of the following observations. \\textit{First}, FixMatch (none) exhibits acceptable but worse performance than its three counterparts, suggesting that pseudo labeling only is inadequate when using very limited labeled data. \n\\textit{Second}, dense alignment significantly elevates the performance (more than contrast-only), indicating that the fine-grained motion signal across multimodal plays an essential role in semi-supervised action recognition. \\textit{Third}, introducing contrastive loss across RGB and TG modalities improves Top-1\/Top-5 accuracy, revealing that global consistency in different modalities is advantageous.\n\\textit{Finally}, dense alignment and contrastive loss enforce the model learning from complementary perspectives because implementing both on top of FixMatch surpasses either one of them.\nWe hope that our discovery on multimodal constraints can shed new light on semi-supervised action recognition in video analysis.\n\n\\zzrevise{}{\n\\smallskip\\noindent\\textbf{Overfitting is alleviated.} \\Cref{tab:overfitting} (Suppl.) presents a significant accuracy gap between the training and testing set, showing that FixMatch severely overfits to the training set. Our method effectively reduces the gap by imposing additional regularization on models with RGB as input.\n}\n\n\n\\begin{table*}[!t]\n\\centering\n\n\\begin{threeparttable}\n\\resizebox{\\textwidth}{!}{\n\\begin{tabular}{lccccccccccccc}\n\\toprule\n & w\/ ImageNet & & \\multicolumn{2}{c}{Kinetics-400} & & \\multicolumn{4}{c}{UCF-101} & & \\multicolumn{3}{c}{HMDB-51} \\\\\n\\cmidrule{4-5}\n\\cmidrule{7-10}\n\\cmidrule{12-14}\nMethod & distillation & Backbone & 1\\% & 10\\% & & 5\\% & 10\\% & 20\\% & 50\\% & & 40\\% & 50\\% & 60\\% \\\\ \\midrule\nPseudo-Label~\\cite{lee2013pseudo} (ICMLW 2013) & \\xmark & R3D-18 & 6.3 & - & & 17.6 & 24.7 & 37.0 & 47.5 & & 27.3 & 32.4 & 33.5 \\\\\nMeanTeacher~\\cite{tarvainen2017mean} (NIPS 2017) & \\xmark & R3D-18 & 6.8 & 19.5 & & 17.5 & 25.6 & 36.3 & 45.8 & & 27.2 & 30.4 & 32.2 \\\\\nS4L~\\cite{zhai2019s4l} (ICCV 2019) & \\xmark & R3D-18 & 6.3 & - & & 22.7 & 29.1 & 37.7 & 47.9 & & 29.8 & 31.0 & 35.6 \\\\\nUPS~\\cite{rizve2020defense} (ICLR 2021) & \\xmark & R3D-18 & - & - & & - & - & 39.4 & 50.2 & & - & - & - \\\\ \\midrule\nVideoSSL~\\cite{jing2021videossl} (WACV 2021) & \\cmark & R3D-18 & - & 33.8 & & 32.4 & 42.0 & 48.7 & 54.3 & & 32.7 & 36.2 & 37.0 \\\\\nTCL~\\cite{singh2021semi} (CVPR 2021) & \\xmark & R3D(TSM)-18 & 7.7 & - & & - & - & - & - & & - & - & - \\\\\nActorCutMix~\\cite{zou2021learning} (arXiv 2021) & \\xmark & R(2+1)D-34 & - & - & & 27.0 & 40.2 & 51.7 & 59.9 & & 32.9 & 38.2 & 38.9 \\\\\nMvPL*~\\cite{xiong2021multiview} (arXiv 2021) & \\xmark & R3D-18 & 5.0 & 36.9 & & 41.2 & 55.5 & 64.7 & 65.6 & & 30.5 & 33.9 & 35.8 \\\\\n\\textbf{Ours} & \\xmark & R3D-18 & \\textbf{9.8} & \\textbf{43.8} & \\textbf{} & \\textbf{44.8} & \\textbf{62.4} & \\textbf{76.1} & \\textbf{79.3} & & \\textbf{46.5} & \\textbf{48.4} & \\textbf{49.7}\n\n\\\\\n\\bottomrule\n\\end{tabular}\n}\n\\begin{tablenotes}\n \\small\n \\item * indicates the method is reimplemented by ourselves. The input modalities are RGB and TG.\n \\end{tablenotes}\n\\end{threeparttable}\n\\caption{\\textbf{Comparison with the state-of-the-arts methods.}\nThe results are reported with Top-1 accuracy (\\%) on the validation sets.\nThe best performance of each setting is in \\textbf{bold}.\n}\n\\vspace{-5mm}\n\\label{tab:main_all}\n\\end{table*}\n\\subsection{Comparison with State-of-the-art Methods}\n\nTo demonstrate the capability and potential of our proposed method, we compared with the most recent state-of-the-art methods for the semi-supervised action recognition task on public datasets including Kinetics-400, UCF-101 and HMDB-51. As shown in \\Cref{tab:main_all}, we mainly compare with two types of methods including image-based methods~\\cite{lee2013pseudo, tarvainen2017mean, zhai2019s4l} which were originally designed for image classification and then simply adopted to video tasks and video based methods ~\\cite{jing2021videossl, singh2021semi, zou2021learning, xiong2021multiview} which were specifically designed for video action recognition task. \n\n\n\\smallskip\\noindent\\textbf{Comparison with image-based methods.}\nThe first three rows in \\Cref{tab:main_all} show the results of image-based methods including \\ie, Pseudo-Label\\cite{lee2013pseudo}, MeanTeacher\\cite{tarvainen2017mean} and S4L\\cite{zhai2019s4l}. In general, the results of all the three image-based methods across over the three datasets with all different labeled percentages are much lower than the results of all video-based based methods. This confirms that it is necessary to propose methods specifically designed based on the video temporal and multimodal attributes.\n\n\n\\smallskip\\noindent\\textbf{Comparison with video-based methods.} The overall performance of the video-based performance are much higher. VideoSSL surpasses all the image-based methods by using Imagenet pre-trained model to guide the learning, and TCL~\\cite{singh2021semi} use self-supervised learning task as auxiliary task and the group contrastive for the video semi-supervised learning. Both the ActorCutMix~\\cite{zou2021learning} and MvPL~\\cite{xiong2021multiview} are adapted from FixMatch~\\cite{sohn2020fixmatch}. Benefited by our proposed cross-modal dense alignment and cross-modal contrastive, our method outperforms all these methods by a significant margin on three datasets under all the experimental settings (different ratio of labels).\n\n\n\n\\subsection{Ablation Studies}\n\\label{sec:Abla}\n\nTo understand the impact of each part of the design in our method, we conduct extensive ablation studies on the UCF-101 dataset with 20\\% labeled setting.\n\n\n\\begin{figure}[t]\n\t\\centering\n \\hspace*{-0.5cm} \n\t\\includegraphics[width=1\\columnwidth]{figures\/compare_slowfast_tg.pdf}\n\t\\caption{\\textbf{Visualization of the slow and fast temporal gradient.} Slow temporal gradient contains a more noisy background of the shooting environment while fast temporal gradient focuses more on the activity-related moving objects.} \n\t\\label{fig:compare_slowfast_tg}\n\t\\vspace{-5mm}\n\\end{figure}\n\n\\smallskip\\noindent\\textbf{Fast temporal gradient is better.}\nTemporal gradient (TG) is calculated by differing two RGB frames and the stride of them could be small or large to generate either fast or slow TG. To delve deeper into the effect of different strides, we conduct experiments with fast TG (calculation stride = 1) and slow TG (calculation stride = 7), and the results are shown in \\Cref{tab:abla_fast}. The first group compare the performance with the baseline FixMatch framework with different modalities of data as input. The results confirm that both the slow TG and fast TG perform much better than RGB (more than 25\\% higher), and also demonstrate that the Fast TG is better than the slower TG for the semi-supervised setting. The second group of \\Cref{tab:abla_fast} compares the final performance of our model with different temporal gradients. When the pseudo-labels are generated by the fast TG, the model beats the performance with slow TG with a large margin (74.1\\% vs. 68.2\\%). To figure out the reason why the performance of fast TG is much higher than slower TG, we visualized the two types of temporal gradient for three video clips and the visualization are shown in \\Cref{fig:compare_slowfast_tg}. The comparison shows that the slow TG has much noisy background information especially when the cameras have significant movement while the fast temporal gradient information focuses more on the boundary of the fast moving objects (\\eg, people, balls). Both the quantitative and qualitative results \nverify the advantages of the fast TG over the slower TG for semi-supervised action recognition. \n\n\\begin{table*}[t]\n \\captionsetup[subtable]{font=normalsize}\n\n\t\\begin{subtable}[t]{0.25\\textwidth}\n\t\t\\centering\n\t\t\\tablestyle{2pt}{1.02}\n\t\t\\small\n\t\t\\begin{tabular}{cc|c}\nStudent & Teacher & Top-1 \\\\ \\shline\nRGB & - & 52.9 \\\\\nSlow TG & - & 67.3 \\\\\nFast TG & - & \\textbf{68.3} \\\\ \\hline\nRGB & Slow TG & 68.2 \\\\\nRGB & Fast TG & \\textbf{74.1}\n\\end{tabular}\n\t\t\\caption{\\textbf{Fast temporal gradient is better.} \n\t}\n\t\t\\label{tab:abla_fast}\n\t\\end{subtable}\n\t\\begin{subtable}[t]{0.25\\textwidth}\n\t\t\\tablestyle{2pt}{1.02}\n\t\t\\small\n\t\t\\begin{tabular}{c|cc}\n Align. Loss & Top-1 & Top-5 \\\\ \\shline\n \n- & 54.1 & 78.1 \\\\ \\hline\nL1 & 74.0 & 91.3 \\\\\nL2 & 74.4 & 91.4 \\\\\nCosine & \\textbf{74.6} & \\textbf{91.7}\n\\end{tabular}\n\\vspace{6pt}\n\t\t\\caption{\\textbf{Dense alignment functions.}}\n\t\t\\label{tab:abla_alignloss}\n\t\\end{subtable}\n\t\\begin{subtable}[t]{0.2\\textwidth}\n\t\t\\tablestyle{2pt}{1.02}\n\t\t\\small\n\t\t\\begin{tabular}{c|cc}\n Stopgrad & Top-1 & Top-5 \\\\ \\shline\n \\xmark & 60.0 & 84.4 \\\\\n \\cmark & \\textbf{74.6} & \\textbf{91.7}\n \\end{tabular}\n \\vspace{17pt}\n\t\t\\caption{\\textbf{Stop gradient in knowledge distillation.}}\n\t\t\\label{tab:abla_stopgrad}\n\t\\end{subtable}\n\t\\begin{subtable}[t]{0.3\\textwidth}\n\t\t\\tablestyle{2pt}{1.02}\n\t\t\\small\n\t\t\\begin{tabular}{c|cc}\n Pseudo-label Metric & Top-1 & Top-5 \\\\ \\shline\n RGB & 73.6 & 91.0 \\\\\n TG & 74.1 & 91.3 \\\\\n Self & 72.8 & 91.6 \\\\\n Average & \\textbf{74.6} & \\textbf{91.7}\n \\end{tabular}\n \\vspace{6pt}\n\t\t\\caption{\\textbf{Metrics for the pseudo-labels.}}\n\t\t\\label{tab:abla_pl_metric}\n\t\\end{subtable}\n\t\n\t\n\t\n\t\\begin{subtable}[t]{0.35\\textwidth}\n\t\t\\centering\n\t\t\\tablestyle{2pt}{1.02}\n\t\t\\small\n\t\t\\begin{tabular}{cccc|cc}\n\\multicolumn{4}{c|}{Aligned Block Index} & \\multicolumn{2}{c}{Accuracy} \\\\ \\hline\n1st & 2nd & 3rd & 4th & Top-1 & Top-5 \\\\ \\shline\n\\xmark & \\xmark & \\xmark & \\cmark & 71.4 & 90.2 \\\\\n\\xmark & \\xmark & \\cmark & \\cmark & 74.0 & 91.4 \\\\\n\\xmark & \\cmark & \\cmark & \\cmark & 74.4 & \\textbf{91.8} \\\\\n\\cmark & \\cmark & \\cmark & \\cmark & \\textbf{74.6} & 91.7 \n\\end{tabular}\n\t\t\\caption{\\textbf{Align them in block-wise.} }\n\t\t\\label{tab:abla_blockwise}\n\t\\end{subtable}\n\t\\begin{subtable}[t]{0.3\\textwidth}\n\t\\centering\n\t\t\\tablestyle{2pt}{1.02}\n\t\t\\small\n\t\t\\begin{tabular}{l|cc}\n & Top-1 & Top-5 \\\\ \\shline\n Plain & 71.1 & 90.0 \\\\\n + LR warm-up & 71.9 & 91.1 \\\\\n + Sup. warm-up & 74.1 & 91.0 \\\\\n + PreciseBN & \\textbf{74.6} & \\textbf{91.7}\n \\end{tabular}\n \\vspace{5pt}\n \\caption{\\textbf{The crucial training tricks.} \n\t}\n\t\\label{tab:abla_tricks}\n\t\\end{subtable}\n\t\\begin{subtable}[t]{0.35\\textwidth}\n\t\\centering\n\t\t\\tablestyle{2pt}{1.02}\n\t\t\\small\n\t\t\\begin{tabular}{c|cc}\n Tempature $\\tau$ & Top-1 & Top-5 \\\\ \\shline\n 0.1 & 74.8 & 91.8 \\\\\n 0.2 & 75.2 & \\textbf{92.4} \\\\\n 0.5 & \\textbf{76.1} & 92.1 \\\\\n 1.0 & 74.3 & 92.2\n \\end{tabular}\n \\vspace{5pt}\n \\caption{\\textbf{Ablation on contrastive temperature.}}\n \\label{tab:abla_temperature}\n\t\\end{subtable}\n\t\n\t\n\t\\caption{\\textbf{Ablation studies} on UCF101 split-1 under 20\\% semi-supervised setting (only use 20\\% labeled data). The results are reported with Top-1 and Top-5 accuracy on the validation set. Backbone: 3D ResNet-18~\\cite{he2016deep,tran2018closer}, each input clip consists of 8 frames sampled from a single video with the inter-frame interval of 8. Except for the study (a), all the other results are evaluated with PreciseBN. Except for the study (g), all the other experiments are without cross-modal contrastive learning for better comparisons.}\n\t\\vspace{-2mm}\n\t\\vspace{-5pt}\n\t\\label{tab:ablations}\n\\end{table*}\n\n\\smallskip\\noindent\\textbf{The choice of alignment functions.} As discussed in \\Cref{sec:alignemnt}, there are many possible choices for the alignment loss function as long as it can effectively enforce the similarity between the two features. Here we studied the performance of three different alignment functions including L1, L2 and Cosine Similarity loss. As shown in \\Cref{fig:compare_slowfast_tg} (b), all the three loss functions in alignment achieve high performance while Cosine Similarity (74.6\\%) outperforms the other two functions (74.0\\% \\& 74.4\\%). A possible explanation is that L1 and L2 have more strict constraints on the scale of two representations, while the Cosine Similarity loss focuses on the vector orientation (\\eg, L1 and L2 losses of $\\Vec{v_1}$=(10,10,10) and $\\Vec{v_2}$=(1,1,1) are large while the Cosine Similarity loss is 0). Although TG is normalized to the 0-255 range during training, there is still a gap in the scales between the representations of RGB and TG. A strict constraint like L1 or L2 would have negative effects on the model for learning motion features.\n\n\\smallskip\\noindent\\textbf{Stop gradient in knowledge distillation.} The stop-gradient operation on the TG side stated in \\Cref{sec:alignemnt} is one of the keys to the successful knowledge distillation with dense alignment. However, as the student RGB has much appearance information which TG does not have, directly training with the dense alignment strategy would make the teacher TG model degenerate greatly and hard to focus on extracting the fine-grained motion features. The stop-gradient avoids the fine-grained motion-related representations in TG model can be disturbed by the RGB model. As shown in \\Cref{tab:abla_stopgrad}, there is a 14.6\\% performance drop on Top-1 accuracy (60.0\\% vs. 74.6\\%) when stop gradient is taken off. \n\n\n\\smallskip\\noindent\\textbf{How to generate pseudo-labels?} There are multiple ways to generate pseudo-labels since our model takes two input modalities. We compare the performance of four settings: 1) use the prediction from RGB model as pseudo-labels, 2) use the prediction from TG model as pseudo-labels, 3) each model uses the probabilities of its self-modality, and 4) fuse the results from both RGB and TG as pseudo-labels. \\Cref{tab:abla_pl_metric} shows that the fused pseudo-labels are more reliable and achieve the best performance benefiting from comprehensive information of both RGB and TB.\n\n\\smallskip\\noindent\\textbf{Dense alignment in block-wise.} An intuitive question about our knowledge distillation framework is that which block or blocks should be densely aligned. Therefore, we conduct this ablation study by adding dense alignment to different positions (\\ie, blocks) and the results are shown in \\Cref{tab:abla_blockwise}. As the common practice of previous knowledge distillation methods \\cite{hinton2015distilling,thoker2019cross,stroud2020d3d} is to align the high-level features of the last layers. Therefore, we start to add the dense alignment module over the features from the last (4-th) block (ResNet basic block) and then experiment with more blocks. Their performances are consistently improved when more blocks are densely aligned and the best Top-1 accuracy is achieved with all blocks aligned. Compared with the baseline, our block-wise dense alignment strategy gains a considerable improvement of 20.5\\% (54.1\\% to 74.6\\%) which demonstrates that fine-grained motion signals are better at semi-supervised model generalization.\n\n\\smallskip\\noindent\\textbf{Crucial training tricks.} Through the extensive experiments, we identified several training tricks which are essential to lead to the high performance. \\Cref{tab:abla_tricks} shows the impact of learning rate warm-up \\cite{goyal2017accurate}, supervised warm-up\\cite{xiong2021multiview} and PreciseBN\\cite{wu2021rethinking}. All the three tricks could make a decent improvement, while the supervised warm-up (training with only the labeled data at the first several epochs) is the most effective one which gains an improvement of 2.7\\% (71.9\\% to 74.6\\%). This shows that the supervised warm-up can alleviate the cold-start issue that low-quality pseudo-labels would be generated at the beginning. The performance of the semi-supervised learning model could easily have large variations~\\cite{singh2021semi,oliver2018realistic,wang20213dioumatch}. These three tricks can solidly improve the performance while in the meantime make the training more stable.\n\n\\smallskip\\noindent\\textbf{Contrastive temperature.}\nAn appropriate temperature is important to the good performance of contrastive learning~\\cite{chen2020simple}, we ablate the contrastive loss temperature in \\Cref{eq:infonce}. As shown in \\Cref{tab:abla_temperature}, a modest temperature (e.g., 0.2 or 0.5) could help the proposed cross-modal contrastive learning work better while a large (1.0) or small (0.1) temperature is not that optimal.\n\n\n\n\n\\section{Conclusion}\n\n\nThis paper has presented a novel semi-supervised learning method which introduces temporal gradient for the fruitful motion-related information and extra representation consistency crossing multiple modalities. Our proposed method uses the block-wise dense alignment strategy and cross-modal contrastive learning. Without additional computation or delay during inference, our method substantially outperforms all prior methods while achieving state-of-the-art performance on UCF-101, HMDB-51, and Kinetics-400 datasets with all the experimented settings (different labeled ratios). In the future, we plan to study the effectiveness of temporal gradient on other video-based tasks and to automatically search or generate powerful modalities.\n\n\\smallskip\\noindent\\textbf{Acknowledgments:} This work was supported by the National Science Foundation under Grant No. NSF-1763705.\n\n\n{\\small\n\\bibliographystyle{ieee_fullname}\n\n","meta":{"redpajama_set_name":"RedPajamaArXiv"}} +{"text":"\\section{Introduction}\\label{INTRO}\n\nCondensation and fragmentation are basic and widely-studied concepts of Bose-Einstein condensate\nemanating from the properties of the reduced one-particle density matrix \\cite{RDM1,RDM2,RDM3,RDM4,RDM5}.\nThe bosons are said to be condensed if there is a single macroscopic eigenvalue of the\nreduced one-particle density matrix \\cite{PEN_ONS} and fragmented if there\nare two or more such macroscopic eigenvalues \\cite{FRAG_REV}. \nThese eigenvalues are commonly called natural occupation numbers and\nthe respective eigenfunctions of the reduced one-particle density matrix are referred to as natural orbitals.\nFragmentation of Bose-Einstein condensate has been investigated, e.g.,\nin \\cite{FRAG1,FRAG2,FRAG3,FRAG4,FRAG5,FRAG6,FRAG7,FRAG8,FRAG9,FRAG10,FRAG11,FRAG12,\nFRAG13,FRAG14,FRAG15,FRAG16,FRAG17,FRAG18,FRAG19,FRAG20}.\n\nThe condensation and especially fragmentation of\nthe reduced two-particle density matrix of interacting identical bosons is less studied, see, e.g., \\cite{RDMs_FRAG}.\nHere, the analysis of the reduced two-particle density matrix\nwould determine whether pairs of bosons are condensed or fragmented.\nThe respective eigenfunctions of the reduced two-particle density matrix\nare often called natural geminals.\nWe note that natural geminals in electronic systems have long been explored, see, e.g.,\n\\cite{GEM1,GEM2,GEM3,GEM4,GEM5,GEM6,GEM7,GEM8,GEM9,GEM10,GEM11,GEM12}.\n\nConsider now a mixture of two kinds of identical bosons,\nwhich are labeled species $1$ and species $2$.\nMixtures of Bose-Einstein condensate is a highly investigated topic, see, e.g., \\cite{MIX1,MIX2,MIX3,MIX4,MIX5,MIX6,MIX7,MIX8,MIX9,MIX10,MIX11,MIX12,MIX13,\nMIX14,MIX15,MIX16,MIX17,MIX18,MIX19,MIX20,MIX21,MIX22,MIX23,MIX24,MIX25,MIX26,\nMIX27,MIX28,MIX29,MIX30}. \nOne may ask,\njust like for single-species bosons,\nabout condensation or fragmentation of each of the species\nand how, for instance,\none species is affected by the presence of the other species and vice versa.\nTo answer this question the intra-species reduced one-particle density matrices\nof species $1$ and $2$ are required, i.e.,\nanalyzing the intra-species occupation numbers and natural orbitals.\nFollowing the above line,\none could also investigate fragmentation of higher-order intra-species reduced density matrices in the mixture.\nFor instance, to investigate whether pairs of identical bosons,\nof either species $1$ or species $2$, are fragmented,\ndiagonalizing of the intra-species reduced two-particle density matrices is needed.\nSummarizing, fragmentation of identical bosons and its manifestation\nin higher-order reduced density matrices stem from the properties of intra-species quantities.\n\nBut, a mixture of Bose-Einstein condensates\noffers a degree-of-freedom or many-particle construction\nwhich do not exist for single-species bosons, namely, inter-species reduced density matrices.\nNow, if fragmentation of identical bosons and pairs is defined as the macroscopic occupation\nof respective eigenvalues following the diagonalization of intra-species reduced density matrices,\nwe may analogously define fragmentation of distinguishable bosons' pairs as\nmacroscopic occupation of the eigenvalues of the inter-species reduced two-particle density matrix.\nObviously, the later is the lowest-order inter-species quantity,\nsince at least one particle of each species is needed to build an\ninter-species entity.\n\nThe above discussion defines the goals of the present work which are:\n(i) To investigate fragmentation of pairs of identical bosons and establish fragmentation of pairs of \ndistinguishable bosons in a mixture of Bose-Einstein condensates;\n(ii) To construct the respective natural geminals of the mixture, for identical pairs and for distinguishable pairs;\n(iii) To show that fragmentation of distinguishable bosons' pairs in the mixture persists with\nhigher-order inter-species reduced density matrices;\n(iv) To construct the Schmidt decomposition of the mixture's wavefunction and discuss\nsome of its properties at the limit of an infinite-number of particles where the mixture is $100\\%$ condensed;\nand\n(v) Achieving the first four goals analytically, using an exactly solvable model.\n\nTo this end we recruit the harmonic-interaction model for mixtures\n\\cite{HIM_MIX1,HIM_MIX_ENTANGLE,HIM_MIX2,HIM_MIX_RDM,HIM_MIX_VAR,HIM_MIX_FLOQUET},\nor, more precisely here, a symmetric version of which \\cite{HIM_MIX_CP}.\nThe harmonic-interaction model for single-species bosons (and fermions)\nhas been used extensively in the literature including for investigating properties of Bose-Einstein condensates\n\\cite{HIM_RDM,HIM_DIAG1,HIM_DIAG2,HIM_JCP,HIM_SCH,HIM1,HIM2,HIM3,HIM4,HIM5,HIM6,HIM7,HIM8,HIM9,HIM10}.\nIn our work\nwe build on results obtained and techniques used \nfor the reduced density matrices of single-species bosons within the harmonic-interaction model\n\\cite{HIM_RDM,HIM_DIAG1,HIM_DIAG2,HIM_JCP,HIM_SCH},\nand, among others, generalize and extend them for \nthe intra-species and particularly the inter-species reduced density matrices of mixtures \\cite{HIM_MIX_RDM}.\n\nThe structure of the paper is as follows.\nIn Sec.~\\ref{PAIR} we construct and investigate fragmentation of\nintra-species and inter-species pair functions in the mixture.\nIn Sec.~\\ref{MORE} we extend the results and explore fragmentation of\npairs of distinguishable pairs.\nFurthermore, a complementary result for the Schmidt decomposition\nof the mixture's wavefucntion at the limit of an infinite number of particles is offered.\nIn Sec.~\\ref{SUM_OUT} a summary of the results and an outlook of some prospected research topics are provided. \nFinally, appendix \\ref{APP} collects for comparison with the mixture \nthe details of fragmentation of bosons and pairs in the single-species system.\n\n\\section{Intra-species and inter-species natural pair functions}\\label{PAIR}\n\n\\subsection{The symmetric two-species harmonic-interaction model}\\label{PAIR_1}\n\nWe consider a mixture of two Bose-Einstein condensates\ndescribed by the Hamiltonian of the symmetric two-species harmonic-interaction model\n\\cite{HIM_MIX_CP,HIM_MIX_RDM}:\n\\begin{eqnarray}\\label{HIM_MIX}\n& & \\hat H(x_1,\\ldots,x_N,y_1,\\ldots,x_N) =\n\\sum_{j=1}^{N} \\left( -\\frac{1}{2m}\\frac{\\partial^2}{\\partial x_j^2} + \\frac{1}{2}m\\omega^2 x_j^2 \\right)\n+ \\lambda \\sum_{1\\le j - \\frac{m\\omega^2}{2N}$ and\n$\\lambda_{12} > - \\frac{m\\omega^2}{4N}$, respectively, on the interactions.\nIn other words, the inter-species interaction $\\lambda_{12}$ is bound from below,\nimplying that the mutual repulsion between the two species cannot be too strong,\nbut is not bound from above,\nmeaning that the mutual attraction between the two species can be unlimitedly strong.\nFurthermore,\nthe intra-species interaction $\\lambda$ can take\nany value as long as the inter-species interaction is sufficiently attractive, i.e.,\n$\\lambda > - \\frac{m\\omega^2}{2N} - \\lambda_{12}$.\nWe shall return to the dressed\nfrequencies $\\Omega$ and $\\Omega_{12}$ below.\n\n\\subsection{Intra-species natural pair functions}\\label{PAIR_2}\n\nThe intra-species reduced density matrices are defined when all bosons of the other type are integrated out.\nWe concentrate in what follows on the reduced one-particle\nand in particular the two-particle density matrices of species $1$,\n\\begin{eqnarray}\\label{RDMs_1_2}\n& & \\rho_1^{(1)}(x,x') = N \\int dx_2 \\cdots dx_N dy_1 \\cdots dy_N \n\\Psi(x,x_2,\\ldots,x_N,y_1,\\ldots,y_N) \\times \\nonumber \\\\\n& &\n\\times \\Psi^\\ast(x',x_2,\\ldots,x_N,y_1,\\ldots,y_N), \\nonumber \\\\\n& & \\rho_1^{(2)}(x_1,x_2,x'_1,x'_2) = N(N-1) \\int dx_3 \\cdots dx_N dy_1 \\cdots dy_N \n\\Psi(x_1,x_2,x_3,\\ldots,x_N,y_1,\\ldots,y_N) \\times \\nonumber \\\\\n& &\n\\times \\Psi^\\ast(x'_1,x'_2,x_3,\\ldots,x_N,y_1,\\ldots,y_N). \\\n\\end{eqnarray}\nIn a symmetric mixture, the corresponding reduced density matrices of species $2$, \n$\\rho_2^{(1)}(y,y')$ and\n$\\rho_2^{(2)}(y_1,y_2,y'_1,y'_2)$,\nare the same and need not be repeated.\n\nThe reduction of the many-particle density (\\ref{HIM_MIX_WF_DEN_MAT2})\nto its finite-order reduced density matrices is\nsomewhat lengthly and given in \\cite{HIM_MIX_RDM}.\nWe start from the final expression for the intra-species reduced one-particle density matrix\nwhich is given by\n\\begin{eqnarray}\\label{1_RDM}\n& & \\rho_1^{(1)}(x,x') = N \\left(\\frac{\\alpha+C_{1,0}}{\\pi}\\right)^{\\frac{1}{2}}\ne^{-\\frac{\\alpha}{2}\\left(x^2+{x'}^2\\right)} \ne^{- \\frac{1}{4} C_{1,0} \\left(x+x'\\right)^2} = \\nonumber \\\\\n& &\n= N \\left(\\frac{\\alpha+C_{1,0}}{\\pi}\\right)^{\\frac{1}{2}}\ne^{-\\frac{\\alpha+\\frac{C_{1,0}}{2}}{2}\\left(x^2+{x'}^2\\right)} \ne^{- \\frac{1}{2} C_{1,0} xx'}, \\nonumber \\\\\n& &\n\\alpha + C_{1,0} =\n(\\alpha-\\beta)\n\\frac{\\left[(\\alpha-\\beta) + N\\beta\\right]^2 - N^2\\gamma^2}\n{\\left[(\\alpha-\\beta) + N\\beta\\right]\\left[(\\alpha-\\beta) + (N-1)\\beta\\right] - N(N-1)\\gamma^2}.\n\\end{eqnarray}\nThe coefficient $C_{1,0}$ governs the properties of the intra-species reduced one-particle density matrix\nand reminds one that all bosons of type $2$ and all but a single boson of type $1$ are integrated out.\nAs might be expected, $\\rho_1^{(1)}(x,x')$\ndepends on the three parts of the many-boson wavefunction,\ni.e., on the $\\alpha$, $\\beta$, and $\\gamma$ terms (\\ref{HIM_MIX_WF_DEN_MAT1}).\nIn the absence of inter-species interaction, i.e., for $\\gamma=0$,\nthe coefficient $C_{1,0}$\nboils down to that of the single-species harmonic-interaction model,\nsee appendix \\ref{APP} for further discussion.\n\nJust as for the case of single-species bosons \\cite{HIM_JCP,HIM_SCH},\nthe intra-species reduced one-particle density matrix (\\ref{1_RDM}) can be diagonalized using Mehler's formula.\nMehler's formula can be written as follows\n\\begin{eqnarray}\\label{MEHLER}\n& & \\left[\\frac{(1-\\rho)s}{(1+\\rho)\\pi}\\right]^{\\frac{1}{2}}\ne^{-\\frac{1}{2}\\frac{(1+\\rho^2)s}{1-\\rho^2}\\left(x^2+{x'}^2\\right)} \\,\ne^{+\\frac{2\\rho s}{1-\\rho^2}xx'}\n= \\nonumber \\\\\n& & \n\\quad = \\sum_{n=0}^\\infty (1-\\rho)\\rho^n \\frac{1}{\\sqrt{2^n n!}} \\left(\\frac{s}{\\pi}\\right)^{\\frac{1}{4}} H_n(\\sqrt{s}x) e^{-\\frac{1}{2}s x^2}\n\\frac{1}{\\sqrt{2^n n!}} \\left(\\frac{s}{\\pi}\\right)^{\\frac{1}{4}} H_n(\\sqrt{s}x') e^{-\\frac{1}{2}s {x'}^2}, \\\n\\end{eqnarray}\nwith $s>0$ and, generally, for intra-species and inter-species\nreduced density matrices as well as later on for\nSchmidt decomposition of the wavefunction,\n$1 > \\rho \\ge 0$.\n$H_n$ are the Hermite polynomials.\n\nComparing the structure of the intra-species reduced\none-particle density matrix $\\rho_1^{(1)}(x,x')$\nwith that of Mehler's formula one readily has\n\\begin{eqnarray}\\label{S_1_1}\n& & s_1^{(1)} = \\sqrt{\\alpha\\left(\\alpha+C_{1,0}\\right)} =\n\\sqrt{\\frac{\\alpha(\\alpha-\\beta)\\left\\{\\left[(\\alpha-\\beta) + N\\beta\\right]^2 - N^2\\gamma^2\\right\\}}\n{\\left[(\\alpha-\\beta) + N\\beta\\right]\\left[(\\alpha-\\beta) + (N-1)\\beta\\right] - N(N-1)\\gamma^2}},\n\\nonumber \\\\ \\nonumber \\\\\n& & \\rho_1^{(1)} = \\frac{\\alpha - s_1^{(1)}}{\\alpha + s_1^{(1)}} =\n\\frac{\\sqrt{\\frac{\\alpha\\left\\{\\left[(\\alpha-\\beta) + N\\beta\\right]\\left[(\\alpha-\\beta) + (N-1)\\beta\\right] - N(N-1)\\gamma^2\\right\\}}{(\\alpha-\\beta)\\left\\{\\left[(\\alpha-\\beta) + N\\beta\\right]^2 - N^2\\gamma^2\\right\\}}}-1}\n{\\sqrt{\\frac{\\alpha\\left\\{\\left[(\\alpha-\\beta) + N\\beta\\right]\\left[(\\alpha-\\beta) + (N-1)\\beta\\right] - N(N-1)\\gamma^2\\right\\}}{(\\alpha-\\beta)\\left\\{\\left[(\\alpha-\\beta) + N\\beta\\right]^2 - N^2\\gamma^2\\right\\}}}+1},\n\\nonumber \\\\\n& & 1 - \\rho_1^{(1)} = \\frac{2s_1^{(1)}}{\\alpha + s_1^{(1)}}. \\\n\\end{eqnarray}\nHere, $1 - \\rho_1^{(1)}$ is the condensate fraction of species $1$ (and of species $2$),\ni.e., the fraction of condensed bosons,\nand $\\rho_1^{(1)}$ is the depleted fraction,\nnamely, the fraction of bosons residing outside the lowest, condensed mode.\n$s_1^{(1)}$ is the scaling, or effective frequency, of the intra-species\nnatural orbitals.\nThe condensate fraction, depleted fraction, and scaling of the natural orbitals\nare all given in closed form as a function of the number of bosons $N$, and the intra-species $\\lambda$\nand inter-species $\\lambda_{12}$ interaction strengths.\nA specific application of the general expressions\n(\\ref{S_1_1}) for the mixture appears below.\n\nFor the intra-species two-particle reduced density matrix we have:\n\\begin{eqnarray}\\label{2_RDM}\n& &\n\\rho_1^{(2)}(x_1,x_2,x'_1,x'_2) = \nN(N-1) \\left(\\frac{\\alpha+C_{1,0}}{\\pi}\\right)^{\\frac{1}{2}} \\left(\\frac{\\alpha+C_{2,0}}{\\pi}\\right)^{\\frac{1}{2}} \\times \\nonumber \\\\\n& & \n\\times e^{-\\frac{\\alpha}{2}\\left(x_1^2+x_2^2+{x'_1}^2+{x'_2}^2\\right)} e^{-\\beta\\left(x_1x_2 + x'_1x'_2\\right)}\ne^{-\\frac{1}{4} C_{2,0} \\left(x_1+x_2+x'_1+x'_2\\right)^2}, \\nonumber \\\\\n& &\n\\alpha+\\beta+2C_{2,0} =\n(\\alpha-\\beta)\n\\frac{\\left[(\\alpha-\\beta) + N\\beta\\right]^2 - N^2\\gamma^2}\n{\\left[(\\alpha-\\beta) + N\\beta\\right]\\left[(\\alpha-\\beta) + (N-2)\\beta\\right] - N(N-2)\\gamma^2}, \\\n\\end{eqnarray}\nwhere $C_{1,0}$ is the coefficient of the intra-species reduced one-particle density matrix (\\ref{1_RDM})\nand the combination $\\left(\\alpha+\\beta+2C_{2,0}\\right)$ would appear shortly after.\n\nTo obtain the natural geminals of $\\rho_1^{(2)}(x_1,x_2,x'_1,x'_2)$ we \ndefine the variables $q_1 = \\frac{1}{\\sqrt{2}}\\left(x_1+x_2\\right)$, $q_2 = \\frac{1}{\\sqrt{2}}\\left(x_1-x_2\\right)$\nand $q'_1 = \\frac{1}{\\sqrt{2}}\\left(x'_1+x'_2\\right)$, $q'_2 = \\frac{1}{\\sqrt{2}}\\left(x'_1-x'_2\\right)$,\ni.e., the center-of-mass and relative coordinate of\ntwo identical bosons.\nWith this rotation of coordinates we have for the different terms in (\\ref{2_RDM}): \n\\begin{eqnarray}\\label{TRAS1}\n& & x_1^2+x_2^2+{x'_1}^2+{x'_2}^2 = q_1^2 + {q'_1}^2 + q_2^2 + {q'_2}^2, \\nonumber \\\\\n& & x_1x_2+x'_1x'_2 = \\frac{1}{2}\\left(q_1^2 + {q'_1}^2 - q_2^2 - {q'_2}^2\\right), \\nonumber \\\\\n& & \\left(x_1+x_2+x'_1+x'_2\\right)^2 = 2 \\left(q_1^2 + {q'_1}^2 + 2q_1q'_1\\right). \\\n\\end{eqnarray} \nConsequently, one readily finds the diagonal form\n\\begin{eqnarray}\\label{2_RDM_DIAG}\n& &\n\\rho_1^{(2)}(q_1,q'_1,q_2,q'_2) = \nN(N-1)\n\\left(\\frac{\\alpha-\\beta}{\\pi}\\right)^{\\frac{1}{2}}\ne^{-\\frac{\\alpha-\\beta}{2}\\left(q_2^2 + {q'_2}^2\\right)} \\times \\nonumber \\\\\n& & \\times\n\\left(\\frac{\\alpha+\\beta+2C_{2,0}}{\\pi}\\right)^{\\frac{1}{2}}\ne^{-\\frac{\\alpha+\\beta+C_{2,0}}{2}\\left(q_1^2 + {q'_1}^2\\right)}\ne^{-C_{2,0} q_1q'_1},\n\\end{eqnarray}\nwhere\nthe normalization coefficients before and after diagonalization are, of course, equal and satisfy\n$\\left(\\alpha+C_{1,0}\\right)\\left(\\alpha+C_{2,0}\\right)=\\left(\\alpha-\\beta\\right)\\left(\\alpha+\\beta+2C_{2,0}\\right)$.\n\nAfter the transformation (\\ref{TRAS1}),\nthe first term of $\\rho_1^{(2)}(q_1,q'_1,q_2,q'_2)$ is separable as a function of $q_2$ and $q'_2$ whereas,\nusing Mehler's formula onto the variables $q_1$ and $q'_1$,\nthe second term can be diagonalized. \nThus, comparing the second term in (\\ref{2_RDM_DIAG}) and Eq.~(\\ref{MEHLER}) we find\n\\begin{eqnarray}\\label{S_1_2}\n& & s_1^{(2)} = \\sqrt{\\left(\\alpha+\\beta\\right)\\left(\\alpha+\\beta+2C_{2,0}\\right)} =\n\\sqrt{\\frac{(\\alpha^2-\\beta^2)\\left\\{\\left[(\\alpha-\\beta) + N\\beta\\right]^2 - N^2\\gamma^2\\right\\}}\n{\\left[(\\alpha-\\beta) + N\\beta\\right]\\left[(\\alpha-\\beta) + (N-2)\\beta\\right] - N(N-2)\\gamma^2}},\n\\nonumber \\\\ \\nonumber \\\\\n& & \\rho_1^{(2)} = \\frac{\\left(\\alpha + \\beta\\right) - s_1^{(2)}}{\\left(\\alpha +\\beta\\right) + s_1^{(2)}} =\n\\frac{\\sqrt{\\frac{\\left(\\alpha+\\beta\\right)\\left\\{\\left[(\\alpha-\\beta) + N\\beta\\right]\\left[(\\alpha-\\beta) + (N-2)\\beta\\right] - N(N-2)\\gamma^2\\right\\}}{(\\alpha-\\beta)\\left\\{\\left[(\\alpha-\\beta) + N\\beta\\right]^2 - N^2\\gamma^2\\right\\}}}-1}\n{\\sqrt{\\frac{\\left(\\alpha+\\beta\\right)\\left\\{\\left[(\\alpha-\\beta) + N\\beta\\right]\\left[(\\alpha-\\beta) + (N-2)\\beta\\right] - N(N-2)\\gamma^2\\right\\}}{(\\alpha-\\beta)\\left\\{\\left[(\\alpha-\\beta) + N\\beta\\right]^2 - N^2\\gamma^2\\right\\}}}+1},\n\\nonumber \\\\\n& & 1 - \\rho_1^{(2)} = \\frac{2s_1^{(2)}}{\\alpha + s_1^{(2)}}. \\\n\\end{eqnarray}\nWith expressions (\\ref{S_1_2}),\nthe decomposition of the intra-species reduced two-particle density matrix in terms of its natural\ngeminals is explicitly given by\n\\begin{eqnarray}\\label{2_RDM_NAT_GEM}\n& &\n\\rho_1^{(2)}(x_1,x_2,x'_1,x'_2) = \nN(N-1) \\sum_{n=0}^\\infty \\left(1-\\rho_1^{(2)}\\right)\\left(\\rho_1^{(2)}\\right)^n\n\\Phi^{(2)}_{1,n}(x_1,x_2) \\Phi^{(2),\\ast}_{1,n}(x'_1,x'_2), \\nonumber \\\\\n& & \\Phi^{(2)}_{1,n}(x_1,x_2) =\n\\frac{1}{\\sqrt{2^n n!}}\n\\left(\\frac{s_1^{(2)}}{\\pi}\\right)^{\\frac{1}{4}}\nH_n\\left(\\sqrt{\\frac{s_1^{(2)}}{2}}\\left(x_1+x_2\\right)\\right)\ne^{-\\frac{1}{4}s_1^{(2)}\\left(x_1+x_2\\right)^2} \\times \\nonumber \\\\\n& & \\times\n\\left(\\frac{\\alpha-\\beta}{\\pi}\\right)^{\\frac{1}{4}}\ne^{-\\frac{1}{4}\\left(\\alpha-\\beta\\right)\\left(x_1-x_2\\right)^2}.\\\n\\end{eqnarray}\nEquation (\\ref{2_RDM_NAT_GEM}) is a general result on\nthe inter-species natural geminals of the mixture.\nTogether with (\\ref{S_1_2}) they imply\nthat\n$1 - \\rho_2^{(1)}$ is the fraction of condensed pairs of species $1$ (and of species $2$),\n$\\rho_1^{(2)}$ is the fraction of depleted pairs,\ni.e., the fraction of pairs residing outside the lowest, condensed natural geminal,\nand \n$s_1^{(2)}$ is the scaling, or effective frequency, of the intra-species\nnatural pair functions.\nThe intra-species natural geminals along with their condensate and depleted fractions\nare prescribed as explicit functions of the number of bosons $N$, and the intra-species $\\lambda$\nand inter-species $\\lambda_{12}$ interactions.\nA specific application of the general decomposition\n(\\ref{S_1_2}),\n(\\ref{2_RDM_NAT_GEM})\nto natural geminals of the mixture is provided below.\nFinally, we point out that \nthe generalization to higher-order intra-species reduced density matrices and corresponding natural\nfunctions follows the above pattern\nand will not be discussed further here.\n\nLet us work out an explicit application\nwhere we shall find and analyze fragmentation of identical bosons' pairs.\nConsider the specific scenario where $\\lambda+\\lambda_{12}=0$,\ni.e., that the intra-species interaction is inverse to and `compensates'\nthe effect of the inter-species interaction on each of the species\nin the manner that the intra-species frequency is that of non-interacting particles,\n$\\Omega=m\\omega$.\nThen, the coefficients of the three parts of the wavefunction simplify and one has\n$\\alpha=m\\omega+\\beta = m\\omega \\left[1 + \\frac{1}{2N}\\left(\\frac{\\Omega_{12}}{\\omega}-1\\right)\\right]$\nand\n$\\beta=\\gamma=\\frac{m}{2N}\\left(\\Omega_{12}-\\omega\\right)$.\nConsequently, expressions (\\ref{S_1_1}) and (\\ref{S_1_2}) simplify and the intra-species reduced\none-particle and two-particle density matrices can be evaluated further.\nThus we readily find\n\\begin{subequations}\\label{S_INTRA_EXAM}\n\\begin{eqnarray}\\label{S_1_1_EXAM}\n& & s_1^{(1)} = m\\omega \\sqrt{\\frac{1 + \\frac{1}{2N}\\left(\\frac{\\Omega_{12}}{\\omega}-1\\right)}\n{1 + \\frac{1}{2N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)}},\n\\nonumber \\\\ \\nonumber \\\\\n& & \\rho_1^{(1)} = \\frac{\\sqrt{\\left[1 + \\frac{1}{2N}\\left(\\frac{\\Omega_{12}}{\\omega}-1\\right)\\right]\n\\left[1 + \\frac{1}{2N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)\\right]}-1}\n{\\sqrt{\\left[1 + \\frac{1}{2N}\\left(\\frac{\\Omega_{12}}{\\omega}-1\\right)\\right]\n\\left[1 + \\frac{1}{2N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)\\right]}+1},\n\\nonumber \\\\\n& & 1 - \\rho_1^{(1)} = \\frac{2}\n{\\sqrt{\\left[1 + \\frac{1}{2N}\\left(\\frac{\\Omega_{12}}{\\omega}-1\\right)\\right]\n\\left[1 + \\frac{1}{2N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)\\right]}+1}\\\n\\end{eqnarray}\nfor the intra-species reduced one-particle density matrix,\nwhere $\\alpha+C_{1,0} = m\\omega \\frac{1}{1 + \\frac{1}{2N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)}$ is used,\nand\n\\begin{eqnarray}\\label{S_1_2_EXAM}\n& & s_1^{(2)} = m\\omega \\sqrt{\\frac{1 + \\frac{1}{N}\\left(\\frac{\\Omega_{12}}{\\omega}-1\\right)}\n{1 + \\frac{1}{N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)}},\n\\nonumber \\\\ \\nonumber \\\\\n& & \\rho_1^{(2)} = \\frac{\\sqrt{\\left[1 + \\frac{1}{N}\\left(\\frac{\\Omega_{12}}{\\omega}-1\\right)\\right]\n\\left[1 + \\frac{1}{N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)\\right]}-1}\n{\\sqrt{\\left[1 + \\frac{1}{N}\\left(\\frac{\\Omega_{12}}{\\omega}-1\\right)\\right]\n\\left[1 + \\frac{1}{N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)\\right]}+1},\n\\nonumber \\\\\n& & 1 - \\rho_1^{(2)} = \\frac{2}\n{\\sqrt{\\left[1 + \\frac{1}{N}\\left(\\frac{\\Omega_{12}}{\\omega}-1\\right)\\right]\n\\left[1 + \\frac{1}{N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)\\right]}+1} \\\n\\end{eqnarray}\n\\end{subequations}\nfor the intra-species reduced two-particle density matrix,\nwhere \n$\\alpha+\\beta = m\\omega \\left[1 + \\frac{1}{N}\\left(\\frac{\\Omega_{12}}{\\omega}-1\\right)\\right]$ and\n$\\alpha+\\beta+2C_{2,0} = m\\omega \\frac{1}{1 + \\frac{1}{N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)}$ are utilized.\nWe see that fragmentation of identical pairs and bosons\nis governed by the ratio $\\frac{\\Omega_{12}}{\\omega}$ and its inverse $\\frac{\\omega}{\\Omega_{12}}$,\nmeaning that it takes place both at the attractive and repulsive sectors of interactions.\nMoreover, the condensed and depleted fractions\nof the pairs and bosons are symmetric to interchanging $\\frac{\\Omega_{12}}{\\omega}$ and \n$\\frac{\\omega}{\\Omega_{12}}$, see discussion below.\n\nLet us analyze explicitly macroscopic fragmentation of geminals, i.e.,\nwhen there is macroscopic occupation of more than a single\nintra-species natural pair function of\\break\\hfill $\\rho_1^{(2)}(x_1,x_2,x'_1,x'_2)$.\nAs a reference, we also refer to the corresponding and standardly defined\nmacroscopic fragmentation of the intra-species natural orbitals of $\\rho_1^{(1)}(x,x')$. \nThe structure of the eigenvalues,\nemanating from Mehler's formula and its applicability to the various reduced density matrices,\nsuggests that, say, the `middle' value $\\rho=1-\\rho=\\frac{1}{2}$, i.e., when the condensed and depleted fractions are equal,\nis a convenient manifestation of macroscopic fragmentation.\nIndeed, for this value the first few natural occupation fractions $(1-\\rho)\\rho^n$, $n=0,1,2,3,4,\\ldots$ are\n\\begin{equation}\\label{rho_half}\n\\frac{1}{2}, \\quad \\frac{1}{4}, \\quad \\frac{1}{8}, \\quad \\frac{1}{16}, \\quad \\frac{1}{32}, \\ldots,\n\\end{equation}\nnamely,\nthere is $50\\%$ occupation of the first natural geminal,\n$25\\%$ occupation of the second,\n$12.5\\%$ of the third,\n$6.25\\%$ of the fourth,\n$3.125\\%$ of the fifth,\nand so on.\nFor brevity,\nwe refer to the fragmentation values in (\\ref{rho_half}) as $50\\%$ fragmentation. \n\nNow, one can compute for which ratio $\\frac{\\Omega_{12}}{\\omega}$,\nor, equivalently, for which inter-species interaction\n$\\lambda_{12} = \\frac{m\\omega^2}{4N}\\left[\\left(\\frac{\\Omega_{12}}{\\omega}\\right)^2-1\\right]$,\nthe intra-species reduced\ntwo-particle and one-particle density matrices are macroscopically fragmented as in (\\ref{rho_half}).\nThus, solving (\\ref{S_1_1_EXAM}) for $50\\%$ natural-orbital fragmentation we find\n\\begin{eqnarray}\\label{FRAG_INTRA_1}\n \\rho_1^{(1)}=\\frac{1}{2} \\quad\n\\Longrightarrow \\quad\n\\frac{\\Omega_{12}}{\\omega} =\n\\left(1 + \\frac{8N^2}{N-\\frac{1}{2}}\\right) \\pm \\sqrt{\\left(1 + \\frac{8N^2}{N-\\frac{1}{2}}\\right)^2 - 1},\n\\end{eqnarray}\nand working out (\\ref{S_1_2_EXAM}) for $50\\%$ natural-geminal fragmentation we get\n\\begin{eqnarray}\\label{FRAG_INTRA_2}\n \\rho_1^{(2)}=\\frac{1}{2} \\quad\n\\Longrightarrow \\quad\n\\frac{\\Omega_{12}}{\\omega} = \n\\sqrt{1+\\frac{4N}{m\\omega^2}\\lambda_{12}} = \n\\left(1 + \\frac{4N^2}{N-1}\\right) \\pm \\sqrt{\\left(1 + \\frac{4N^2}{N-1}\\right)^2 - 1}.\n\\end{eqnarray}\nThere are two `reciprocate' solutions for both\nthe natural geminals and natural orbitals:\nWe see that $50\\%$ fragmentation occurs for strong attractions,\ni.e., when $\\frac{\\Omega_{12}}{\\omega}$ is large,\nor near the border of stability for repulsions, that is when $\\frac{\\Omega_{12}}{\\omega}$ is close to zero.\nAlso, to achieve the same degree of $50\\%$ with a larger number $N$ of species $1$ (and species $2$) bosons,\na stronger attraction or repulsion is needed.\nFinally, comparing natural-geminal with natural-orbital fragmentation at the same $50\\%$ value,\none sees from (\\ref{FRAG_INTRA_2}) and (\\ref{FRAG_INTRA_1}) that slightly weaker\ninteractions, attractions or repulsions, are needed for the former.\n\nIt is also useful to register the one-particle and two-particle densities, i.e.,\nthe diagonal parts $\\rho_1^{(1)}(x)=\\rho_1^{(1)}(x,x'=x)$ and $\\rho_1^{(2)}(x_1,x_2)=\\rho_1^{(2)}(x_1,x_2,x'_1=x_1,x'_2=x_2)$,\nwhich read\n\\begin{eqnarray}\\label{DENSITIES_1_2_EXAM}\n& & \\rho_1^{(1)}(x) =\nN \\left(\\frac{\\alpha+C_{1,0}}{\\pi}\\right)^{\\frac{1}{2}} e^{-\\left(\\alpha+C_{1,0}\\right)x^2} = \nN \\left(\\frac{m\\omega}{\\pi\\left[1 + \\frac{1}{2N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)\\right]}\\right)^{\\frac{1}{2}}\ne^{-\\frac{m\\omega}{1 + \\frac{1}{2N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)}x^2},\n\\nonumber \\\\\n& & \\rho_1^{(2)}(x_1,x_2) = \nN(N-1)\n\\left(\\frac{\\alpha-\\beta}{\\pi}\\right)^{\\frac{1}{2}}\ne^{-\\frac{\\alpha-\\beta}{2}\\left(x_1-x_2\\right)^2}\n\\left(\\frac{\\alpha+\\beta+2C_{2,0}}{\\pi}\\right)^{\\frac{1}{2}}\ne^{-\\frac{\\alpha+\\beta+2C_{2,0}}{2}\\left(x_1+x_2\\right)^2} = \\nonumber \\\\\n& &\n= N(N-1)\n\\left(\\frac{m\\omega}{\\pi}\\right)^{\\frac{1}{2}}\ne^{-\\frac{m\\omega}{2}\\left(x_1-x_2\\right)^2}\n\\left(\\frac{m\\omega}{\\pi\\left[1 + \\frac{1}{N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)\\right]}\\right)^{\\frac{1}{2}}\ne^{-\\frac{m\\omega}{2\\left[1 + \\frac{1}{N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)\\right]}\\left(x_1+x_2\\right)^2}.\n\\end{eqnarray}\nFrom the densities (\\ref{DENSITIES_1_2_EXAM}) we can infer a measure for the size\nof identical pairs' and bosons' clouds using the widths of the respective Gaussian functions therein.\nThus, we have\n\\begin{subequations}\\label{WIDTH_INTRA}\n\\begin{eqnarray}\\label{WIDTH_INTRA_GEN}\n& &\n\\sigma_{1,x}^{(1)} = \\sqrt{\\frac{1 + \\frac{1}{2N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)}{2m\\omega}}, \\nonumber \\\\\n& &\n\\sigma_{1,\\frac{x_1+x_2}{\\sqrt{2}}}^{(2)} = \\sqrt{\\frac{1 + \\frac{1}{N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)}{2m\\omega}},\n\\quad\n\\sigma_{1,\\frac{x_1-x_2}{\\sqrt{2}}}^{(2)} = \\sqrt{\\frac{1}{2m\\omega}}. \\\n\\end{eqnarray}\nTo assess the combined impact of the intra-species and inter-species interactions\natop the fragmentation of the reduced density matrices,\nit is useful to compute the sizes (\\ref{WIDTH_INTRA_GEN}) for large inter-species attractions or \ninter-species repulsions at the border of stability.\nOne finds, respectively,\n\\begin{eqnarray}\\label{WIDTH_INTRA_LIM}\n& & \\lim_{\\frac{\\Omega_{12}}{\\omega} \\to \\infty} \\sigma_{1,x}^{(1)} = \n\\sqrt{\\frac{1 - \\frac{1}{2N}}{2m\\omega}}, \\qquad\n\\sigma_{1,x}^{(1)} \\longrightarrow \\infty \\quad \\mathrm{for} \\quad \\frac{\\Omega_{12}}{\\omega} \\to 0^+, \\nonumber \\\\\n& & \\lim_{\\frac{\\Omega_{12}}{\\omega} \\to \\infty} \\sigma_{1,\\frac{x_1+x_2}{\\sqrt{2}}}^{(2)} = \n\\sqrt{\\frac{1 - \\frac{1}{N}}{2m\\omega}}, \\qquad\n\\sigma_{1,\\frac{x_1+x_2}{\\sqrt{2}}}^{(2)} \\longrightarrow \\infty \\quad \\mathrm{for} \\quad \\frac{\\Omega_{12}}{\\omega} \\to 0^+,\n\\\n\\end{eqnarray}\n\\end{subequations}\nwhere $\\sigma_{1,\\frac{x_1-x_2}{\\sqrt{2}}}^{(2)}$ is independent of the interactions.\nInterestingly, the size of the densities \nfor strong inter-species attractions, which is accompanied by strong intra-species repulsions because $\\lambda+\\lambda_{12}=0$,\nsaturates at about the trap's size and does not depend on the strengths of interactions.\nIn other words, a high degree of fragmentation is possible in the mixture without shrinking of the density due to strong inter-species\nattractive interaction or expansion of the intra-species densities due to strong intra-species repulsive interaction. \nFor the sake of comparative analysis, it is instructive to make contact with\nfragmentation of single-species bosons in the harmonic-interaction model,\nsee appendix \\ref{APP}.\n\n\\subsection{Inter-species natural pair functions}\\label{PAIR_3}\n\nAs mentioned above,\nin a mixture of two types of identical bosons there are other kinds of pairs, namely,\npairs of distinguishable particles.\nIf we are to examine the lowest-order inter-species reduced density matrix,\nwe can ask regarding distinguishable pairs questions analogous to those asked concerning identical pairs.\nThe purpose of this subsection is to\nderive the relevant tools and answer such questions.\n\nThe inter-species reduced two-particle density matrix,\ni.e., the lowest-oder inter-species quantity, is defined from the all-particle density as\n\\begin{eqnarray}\\label{2_RDM_12_SYM_GEN}\n& & \\rho_{12}^{(2)}(x,x',y,y') = N^2 \\int dx_2 \\cdots dx_N dy_2 \\cdots dy_N \n\\Psi(x,x_2,\\ldots,x_N,y,y_2,\\ldots,y_N) \\times \\nonumber \\\\\n& &\n\\times \\Psi^\\ast(x',x_2,\\ldots,x_N,y',y_2,\\ldots,y_N). \\\n\\end{eqnarray}\nFor the harmonic-interaction model of the symmetric mixture it\ncan be computed analytically and, starting from (\\ref{HIM_MIX_WF_DEN_MAT2}),\nis given by \\cite{HIM_MIX_RDM}\n\\begin{subequations}\\label{2_RDM_12_SYM}\n\\begin{eqnarray}\\label{2_RDM_12_SYM_DEN}\n& & \\rho_{12}^{(2)}(x,x',y,y') = N^2\n\\left[\\frac{(\\alpha_1+C_{1,1})^2-D_{1,1}^2}{\\pi^2}\\right]^\\frac{1}{2} \\times \\nonumber \\\\\n& & \\times e^{-\\frac{\\alpha_1}{2} \\left(x^2+{x'}^2+y^2+{y'}^2\\right)}\ne^{-\\frac{1}{4}C_{1,1}\\left[\\left(x+x'\\right)^2+\\left(y+y'\\right)^2\\right]}\ne^{+\\frac{1}{2}D_{1,1} \\left(x+x'\\right)\\left(y+y'\\right)} \ne^{+\\frac{1}{2}D'_{1,1} \\left(x-x'\\right)\\left(y-y'\\right)}, \\\n\\end{eqnarray}\nwhere\n\\begin{eqnarray}\\label{2_RDM_12_SYM_COEFF}\n& & \\alpha + C_{1,1} \\mp D_{1,1} =\n(\\alpha-\\beta)\n\\frac{(\\alpha-\\beta) + N(\\beta\\mp \\gamma)}\n{(\\alpha-\\beta) + (N-1)(\\beta\\mp \\gamma)},\n\\nonumber \\\\\n& & D'_{1,1} = \\gamma.\n\\end{eqnarray}\n\\end{subequations}\nWe see that the structure of the inter-species reduced two-particle density matrix\nis more involved than that of the intra-species reduced two-particle density matrix\nas well as that of the product of the two, species $1$ and species $2$ intra-species reduced one-particle density matrices.\nNonetheless, it can be diagonalized.\n\nTo diagonalize\n$\\rho_{12}^{(2)}(x,x',y,y')$\none must couple and make linear combinations of\ncoordinates associated with distinguishable bosons.\nDefining $u = \\frac{1}{\\sqrt{2}}\\left(x+y\\right)$, $v = \\frac{1}{\\sqrt{2}}\\left(x-y\\right)$\nand \n$u'= \\frac{1}{\\sqrt{2}}\\left(x'+y'\\right)$, $v'= \\frac{1}{\\sqrt{2}}\\left(x'-y'\\right)$\nwe have for the different terms in (\\ref{2_RDM_12_SYM}):\n\\begin{eqnarray}\\label{TRAS3}\n& & x^2+y^2+{x'}^2+{y'}^2 = u^2 + {u'}^2 + v^2 + {v'}^2, \\\\\n& & \\left(x+x'\\right)^2+\\left(y+y'\\right)^2 = \\left(u+u'\\right)^2 + \\left(v+v'\\right)^2 =\nu^2 + {u'}^2 + v^2 + {v'}^2 + 2\\left(uu'+vv'\\right), \\nonumber \\\\\n& & \\left(x \\pm x'\\right)\\left(y \\pm y'\\right) = \\frac{1}{2}\\left[\\left(u\\pm u'\\right)^2 - \\left(v\\pm v'\\right)^2\\right] =\n\\frac{1}{2}\\left(u^2 + {u'}^2 - v^2 - {v'}^2\\right) \\pm \\left(uu'-vv'\\right). \\nonumber \\\n\\end{eqnarray}\nConsequently, we readily find the decomposition\n\\begin{eqnarray}\\label{2_RDM_12_SYM_DIAG}\n& &\n\\rho_{12}^{(2)}(u,u',v,v') = N^2\n\\left(\\frac{\\alpha_1+C_{1,1}-D_{1,1}}{\\pi}\\right)^\\frac{1}{2}\ne^{-\\frac{\\alpha_1+\\frac{C_{1,1}}{2}-\\frac{D_{1,1}+D'_{1,1}}{2}}{2}\\left(u^2 + {u'}^2\\right)}\ne^{-\\frac{1}{2}\\left[C_{1,1}-\\left(D_{1,1}-D'_{1,1}\\right)\\right]uu'} \\times \\nonumber \\\\\n& & \\times \n\\left(\\frac{\\alpha_1+C_{1,1}+D_{1,1}}{\\pi}\\right)^\\frac{1}{2}\ne^{-\\frac{\\alpha_1+\\frac{C_{1,1}}{2}+\\frac{D_{1,1}+D'_{1,1}}{2}}{2}\\left(v^2 + {v'}^2\\right)}\ne^{-\\frac{1}{2}\\left[C_{1,1}+\\left(D_{1,1}-D'_{1,1}\\right)\\right]vv'},\n\\end{eqnarray}\nwhere the normalizations after and before diagonalization are, of course, equal.\nAs might be expected,\nsince the structure of $\\rho_{12}^{(2)}(x,x',y,y')$ is more involved than that\nof $\\rho_1^{(2)}(x_1,x_2,x'_1,x'_2)$ the diagonalization of the former is more intricate.\nFortunately, we can do that using the application of Mehler's formula twice,\non the appropriately-constructed inter-species `mixed' coordinates $u, u'$ and $v, v'$.\nWe thus get\n\\begin{eqnarray}\\label{S_12_2}\n& & s_{12,\\pm}^{(2)} = \\sqrt{\\left(\\alpha \\mp D'_{1,1}\\right)\\left(\\alpha+C_{1,1} \\mp D_{1,1}\\right)} =\n\\sqrt{(\\alpha\\mp \\gamma)(\\alpha-\\beta)\n\\frac{(\\alpha-\\beta) + N(\\beta\\mp \\gamma)}\n{(\\alpha-\\beta) + (N-1)(\\beta\\mp \\gamma)}},\n\\nonumber \\\\\n& & \\rho_{12,\\pm}^{(2)} = \\frac{\\left(\\alpha \\mp D'_{1,1}\\right) - s_{12,\\pm}^{(2)}}{\\left(\\alpha \\mp D'_{1,1}\\right) + s_{12,\\pm}^{(2)}} =\n\\frac{\\frac{(\\alpha\\mp \\gamma)\\left[(\\alpha-\\beta) + (N-1)(\\beta\\mp \\gamma)\\right]}{(\\alpha-\\beta)\\left[(\\alpha-\\beta) + N(\\beta\\mp \\gamma)\\right]}-1}{\\frac{(\\alpha\\mp \\gamma)\\left[(\\alpha-\\beta) + (N-1)(\\beta\\mp \\gamma)\\right]}{(\\alpha-\\beta)\\left[(\\alpha-\\beta) + N(\\beta\\mp \\gamma)\\right]}+1},\n\\nonumber \\\\\n& & 1 - \\rho_{12,\\pm}^{(2)} = \\frac{2s_{12,\\pm}^{(2)}}{\\left(\\alpha \\mp D'_{1,1}\\right) + s_{12,\\pm}^{(2)}}, \\\n\\end{eqnarray}\nwhere the ``$+$'' terms quantify the fragmentation in the $u,u'$ part of the intra-species reduced two-particle density matrix and\nthe ``$-$'' terms quantify the fragmentation in the $v,v'$ part of the intra-species reduced two-particle density matrix,\nalso see below.\nEquation (\\ref{S_12_2}) is one of the main results of the present work and bears\na clear and appealing physical meaning,\nthat pairs made of distinguishable bosons can be fragmented,\nand that this fragmentation is governed\nby the center-of-mass and \nby a relative coordinate of distinguishable bosons.\nWe shall return to this point in what follows.\n\nWe can now prescribe the decomposition of the\ninter-species reduced two-particle density matrix\nto its distinguishable natural pair functions which is given by\n\\begin{eqnarray}\\label{12_2_RDM_NAT_DIS_GEM}\n& &\n\\rho_{12}^{(2)}(x,x',y,y') = \\nonumber \\\\\n& & = N^2 \n\\sum_{n_+=0}^\\infty \\sum_{n_-=0}^\\infty\n\\left(1-\\rho_{12,+}^{(2)}\\right)\n\\left(1-\\rho_{12,-}^{(2)}\\right)\n\\left(\\rho_{12,+}^{(2)}\\right)^{\\!n_+}\n\\left(\\rho_{12,-}^{(2)}\\right)^{\\!n_-}\n\\Phi^{(2)}_{12,n_+,n_-}(x,y) \\Phi^{(2),\\ast}_{12,n_+,n_-}(x',y'), \\nonumber \\\\\n& & \\Phi^{(2)}_{12,n_+,n_-}(x,y) =\n\\frac{1}{\\sqrt{2^{n_+} {n_+}!}}\n\\left(\\frac{s_{12,+}^{(2)}}{\\pi}\\right)^{\\frac{1}{4}}\nH_{n_+}\\left(\\sqrt{\\frac{s_{12,+}^{(2)}}{2}}\\left(x+y\\right)\\right)\ne^{-\\frac{1}{4}s_{12,+}^{(2)}\\left(x+y\\right)^2} \\times \\nonumber \\\\\n& & \\times\n\\frac{1}{\\sqrt{2^{n_-} {n_-}!}}\n\\left(\\frac{s_{12,-}^{(2)}}{\\pi}\\right)^{\\frac{1}{4}}\nH_{n_-}\\left(\\sqrt{\\frac{s_{12,-}^{(2)}}{2}}\\left(x-y\\right)\\right)\ne^{-\\frac{1}{4}s_{12,-}^{(2)}\\left(x-y\\right)^2}.\\\n\\end{eqnarray}\nAll in all,\n(\\ref{12_2_RDM_NAT_DIS_GEM}) implies\nthat the distinguishable-pair `condensed fraction' is given by\\break\\hfill\n$\\left(1-\\rho_{12,+}^{(2)}\\right)\\left(1-\\rho_{12,-}^{(2)}\\right)$ \nand the respective depleted fraction by\n$1-\\left(1-\\rho_{12,+}^{(2)}\\right)\\left(1-\\rho_{12,-}^{(2)}\\right)=\n\\rho_{12,+}^{(2)}+\\rho_{12,-}^{(2)}-\\rho_{12,+}^{(2)}\\rho_{12,-}^{(2)}$. \nEach of the inter-species `mixed' coordinates $\\frac{x\\pm y}{\\sqrt{2}}$\ncarry its own scaling, $s_{12,\\pm}^{(2)}$.\nThe distinguishable natural geminals \n$ \\Phi^{(2)}_{12,n_+,n_-}(x,y)$\nare, needless to say, orthonormal to each other. \n\nWe proceed now for an application.\nWe considered above the specific case of $\\lambda+\\lambda_{12}=0$\nwhich leads to \n$\\Omega=m\\omega$,\n$\\alpha=m\\omega \\left[1 + \\frac{1}{2N}\\left(\\frac{\\Omega_{12}}{\\omega}-1\\right)\\right]$, and\n$\\beta=\\gamma=\\frac{m}{2N}\\left(\\Omega_{12}-\\omega\\right)$.\nTo evaluate $\\rho_{12}^{(2)}(x,x',y,y')$\nwe also need the combinations\n$\\left(\\alpha + C_{1,1} - D_{1,1}\\right) = m \\omega$\nand\n$\\left(\\alpha - D'_{1,1}\\right) = m\\omega$ for the ``$+$'' branch\nas well as\n$\\left(\\alpha + C_{1,1} + D_{1,1}\\right) =\nm\\omega \\frac{1}{1 + \\frac{1}{N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)}$\nand\n$\\left(\\alpha + D'_{1,1}\\right) =\nm\\omega \\left[1 + \\frac{1}{N}\\left(\\frac{\\Omega_{12}}{\\omega}-1\\right)\\right]$\nfor the ``$-$'' branch.\n\nThus, expressions (\\ref{S_12_2}) can readily be evaluated and the following picture\nof inter-species fragmentation is found:\n\\begin{subequations}\\label{S2_INTER_EXAM}\n\\begin{eqnarray}\\label{S2_12_+_EXAM}\n& & s_{12,+}^{(2)} = m\\omega,\n\\qquad\n\\rho_{12,+}^{(2)} = 0,\n\\qquad\n1 - \\rho_{12,+}^{(2)} = 1, \\\n\\end{eqnarray}\nindicating that there is no contribution to fragmentation from the symmetric `mixed' coordinate $u, u'$.\nOn the other end,\n\\begin{eqnarray}\\label{S2_12_-_EXAM}\n& & s_{12,-}^{(2)} = m\\omega \\sqrt{\\frac{1 + \\frac{1}{N}\\left(\\frac{\\Omega_{12}}{\\omega}-1\\right)}\n{1 + \\frac{1}{N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)}},\n\\nonumber \\\\ \\nonumber \\\\\n& & \\rho_{12,-}^{(2)} = \\frac{\\sqrt{\\left[1 + \\frac{1}{N}\\left(\\frac{\\Omega_{12}}{\\omega}-1\\right)\\right]\n\\left[1 + \\frac{1}{N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)\\right]}-1}\n{\\sqrt{\\left[1 + \\frac{1}{N}\\left(\\frac{\\Omega_{12}}{\\omega}-1\\right)\\right]\n\\left[1 + \\frac{1}{N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)\\right]}+1},\n\\nonumber \\\\\n& & 1 - \\rho_{12,-}^{(2)} = \\frac{2}\n{\\sqrt{\\left[1 + \\frac{1}{N}\\left(\\frac{\\Omega_{12}}{\\omega}-1\\right)\\right]\n\\left[1 + \\frac{1}{N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)\\right]}+1}, \\\n\\end{eqnarray}\n\\end{subequations}\nnamely, that the fragmentation fully originates from the asymmetric `mixed' coordinate $v, v'$.\nWe conclude that,\nwhereas fragmentation of identical pairs is associated with their center-of-mass coordinate,\nfragmentation of distinguishable pairs is linked, in this explicit case, only with a relative coordinate between\ntwo distinguishable bosons. \nInterestingly,\nthe degree of intra-species and inter-species pair fragmentation is the same\nin the specific case considered,\ndespite pertaining to different parts of the mixtures' many-boson wavefunction.\nFurthermore,\nthere are different numbers of pairs:\n$\\frac{N}{2}$ intra-species identical pairs (for each of the species)\nand $N$ inter-species pairs of distinguishable bosons.\n\nNow, one can compute the ratio $\\frac{\\Omega_{12}}{\\omega}=\\sqrt{1+\\frac{4N}{m\\omega^2}\\lambda_{12}}$\nfor which the inter-species reduced two-particle density matrix is $50\\%$ fragmented as in (\\ref{rho_half}).\nSince $\\rho_{12,+}^{(2)}=0$ does not contribute,\nthe only contribution to fragmentation comes from\n$\\rho_{12,-}^{(2)}$.\nThus, solving (\\ref{S2_12_-_EXAM}) for $50\\%$ distinguishable-pair-function fragmentation we obtain\n\\begin{eqnarray}\\label{FRAG_INTER_2}\n\\rho_{12,-}^{(2)}=\\frac{1}{2} \\quad\n\\Longrightarrow \\quad\n\\frac{\\Omega_{12}}{\\omega} =\n\\left(1 + \\frac{4N^2}{N-1}\\right) \\pm \\sqrt{\\left(1 + \\frac{4N^2}{N-1}\\right)^2 - 1}.\n\\end{eqnarray}\nAs above, there are two `reciprocate' solutions,\none for strong inter-species attraction and the second close to the border of stability for intermediate-strength\ninter-species repulsion.\nWe remind that since $\\lambda+\\lambda_{12}=0$ in our example,\nthe respective intra-species interaction is opposite in sign.\nAlso, to achieve the same degree of $50\\%$ fragmentation\nwith a larger number $N$ of\ndistinguishable pairs,\na stronger inter-species attraction or repulsion is needed.\nFurthermore, as discussed above,\ncomparing distinguishable-pair and identical-pair fragmentation at the same $50\\%$ value\nin this example,\none sees from (\\ref{FRAG_INTER_2}) and (\\ref{FRAG_INTRA_2}) that the same interaction\nis needed.\n\nFinally, we prescribe the inter-species two-particle density,\nnamely,\nthe diagonal part $\\rho_{12}^{(2)}(x,y)=\\rho_{12}^{(2)}(x,x'=x,y,y'=y)$,\nwhich is given by\n\\begin{eqnarray}\\label{DENSITY_2_12_EXAM}\n& &\n\\rho_{12}^{(2)}(x,y) = N^2\n\\left(\\frac{\\alpha_1+C_{1,1}-D_{1,1}}{\\pi}\\right)^\\frac{1}{2}\ne^{-\\frac{\\alpha_1+C_{1,1}-D_{1,1}}{2}\\left(x+y\\right)^2}\n\\times \\nonumber \\\\\n& & \\times \n\\left(\\frac{\\alpha_1+C_{1,1}+D_{1,1}}{\\pi}\\right)^\\frac{1}{2}\ne^{-\\frac{\\alpha_1+C_{1,1}+D_{1,1}}{2}\\left(x-y\\right)^2} = \\nonumber \\\\\n& &\n= N^2\n\\left(\\frac{m\\omega}{\\pi}\\right)^{\\frac{1}{2}}\ne^{-\\frac{m\\omega}{2}\\left(x+y\\right)^2}\n\\left(\\frac{m\\omega}{\\pi\\left[1 + \\frac{1}{N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)\\right]}\\right)^{\\frac{1}{2}}\ne^{-\\frac{m\\omega}{2\\left[1 + \\frac{1}{N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)\\right]}\\left(x-y\\right)^2}.\n\\end{eqnarray}\nNext, the size of the distinguishable pairs' cloud can be assessed \nfrom the density (\\ref{DENSITY_2_12_EXAM})\nusing the widths of the respective Gaussian functions.\nAccordingly, we find\n\\begin{subequations}\\label{WIDTH_INTER}\n\\begin{eqnarray}\\label{WIDTH_INTER_GEN}\n& & \\sigma_{12,\\frac{x+y}{\\sqrt{2}}}^{(2)} = \\sqrt{\\frac{1}{2m\\omega}}, \\quad\n\\sigma_{12,\\frac{x-y}{\\sqrt{2}}}^{(2)} = \\sqrt{\\frac{1 + \\frac{1}{N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)}{2m\\omega}}. \\\n\\end{eqnarray}\nTo show the combined effect of the intra-species and inter-species interactions\naccompanying\nfragmentation of $\\rho_{12}^{(2)}(x,x',y,y')$,\nit is useful to compute the sizes (\\ref{WIDTH_INTER_GEN}) for large inter-species attractions or \ninter-species repulsions at the border of stability.\nWe obtain, respectively,\n\\begin{eqnarray}\\label{WIDTH_INTER_LIM}\n& & \\lim_{\\frac{\\Omega_{12}}{\\omega} \\to \\infty} \\sigma_{12,\\frac{x-y}{\\sqrt{2}}}^{(2)} = \n\\sqrt{\\frac{1 - \\frac{1}{N}}{2m\\omega}}, \\qquad\n\\sigma_{12,\\frac{x-y}{\\sqrt{2}}}^{(2)} \\longrightarrow \\infty \\quad \\mathrm{for} \\quad \\frac{\\Omega_{12}}{\\omega} \\to 0^+,\n\\\n\\end{eqnarray}\n\\end{subequations}\nwhere $\\sigma_{12,\\frac{x+y}{\\sqrt{2}}}^{(2)}$ is independent of the interactions.\nWe see that the size of the inter-species density\nsaturates as well at about the trap's size and does not depend on the strengths of interactions\nin the limit of strong inter-species attractions.\nAnalogously to identical pairs,\na strong fragmentation of distinguishable pairs\nis possible in the mixture without shrinking of the inter-species \ndensity due to strong inter-species\nattractive interaction.\nAt the other end,\nwhen the inter-species repulsion is close to the border of stability,\nthe inter-species density expands boundlessly.\nSummarizing, inter-species fragmentation is governed by the ratio $\\frac{\\Omega_{12}}{\\omega}$\nand takes place both at the attractive and repulsive sectors of interactions.\nFor the sake of analysis, we compared the results for inter-species pair fragmentation with intra-species pair fragmentation\nand discussed the similarity and differences between the respective two-particle densities\n(\\ref{DENSITY_2_12_EXAM}) and (\\ref{DENSITIES_1_2_EXAM}).\n\n\\section{Pair of distinguishable pairs and Schmidt decomposition of the wavefunction}\\label{MORE}\n\nFollowing the results of the previous section\non fragmentation of distinguishable pairs,\nthere are two questions that warrant answers.\nThe first is whether inter-species fragmentation persists beyond distinguishable pairs,\nsay, to pairs of distinguishable pairs?\nIn as much as single-species and intra-species fragmentations\ntake place at the lowest-level reduced one-particle density matrix,\nand persist at higher-level single-species reduced density matrices,\nwe wish to establish the result of inter-species fragmentation at the level of\nhigher-order reduced density matrices.\nAfter all, the reduced two-particle density matrix is the lowest-order inter-species one.\nThe second question deals with the nature of the inter-species coordinates governing fragmentation.\nAt the level of distinguishable-pair fragmentation,\ni.e., within the inter-species reduced two-particle density matrix,\none cannot unambiguously tell whether the relative center-of-mass\ncoordinate of the two species is involved or whether other relative inter-species coordinates govern fragmentation.\nThis is because for a pair of distinguishable particles one cannot\ndistinguish between the two types of coordinates.\n\nAs seen in the previous section,\nthe inter-species reduced two-particle density matrix is more intricate\nthan the intra-species ones, \nand consequently its diagonalization is more involved.\nWe derive now the inter-species reduced four-particle density matrix\nand examine which `normal coordinates' govern its diagonalization.\nThen, the natural four-particle functions are obtained explicitly and investigated.\n\nFinally and as a complementary result of the techniques\nused for inter-species fragmentation,\nwe carry the connection between inter-species and intra-species center-of-mass coordinates,\nin conjunction with the usage of Mehler's formula within a mixture, further.\nThis is done\nby constructing the Schmidt decomposition of the mixture's wavefunction\nand discussing consequences of this decomposition at the limit of an infinite number of particles.\n\n\\subsection{Inter-species fragmentation in higher-order reduced density matrices}\\label{MORE_FRAG}\n\nThe inter-species reduced four-particle density matrix is defined as\n\\begin{eqnarray}\\label{4_RDM_12_SYM_GEN}\n& & \\rho_{12}^{(4)}(x_1,x_2,x'_1,x'_2,y_1,y_2,y'_1,y'_2) = N^2 \\left(N-1\\right)^2\n\\int dx_3 \\cdots dx_N dy_3 \\cdots dy_N \\times \\nonumber \\\\\n& & \\times \\Psi(x_1,x_2,x_3,\\ldots,x_N,y_1,y_2,y_3,\\ldots,y_N)\n\\Psi^\\ast(x'_1,x'_2,x_3,\\ldots,x_N,y'_1,y'_2,y_3,\\ldots,y_N). \\\n\\end{eqnarray}\nNote that here we only treat the four-particle quantity with two identical bosons per each species.\nIntegrating the harmonic interaction-model for symmetric mixtures we find the final expression explicitly\n\\begin{subequations}\\label{4_RDM_12_SYM}\n\\begin{eqnarray}\\label{4_RDM_12_SYM_DEN}\n& & \\rho_{12}^{(4)}(x_1,x_2,x'_1,x'_2,y_1,y_2,y'_1,y'_2) = N^2 \\left(N-1\\right)^2\n\\left[\\frac{(\\alpha+C_{1,1})^2-D_{1,1}^2}{\\pi^2}\\right]^\\frac{1}{2}\n\\left[\\frac{(\\alpha+C_{2,2})^2-D_{2,2}^2}{\\pi^2}\\right]^\\frac{1}{2} \\times \\nonumber \\\\\n& & \\times e^{-\\frac{\\alpha}{2} \\left(x_1^2+x_2^2+{x'_1}^2+{x'_2}^2+y_1^2+y_2^2+{y'_1}^2+{y'_2}^2\\right)}\ne^{-\\beta\\left(x_1x_2+x'_1x'_2+y_1y_2+y'_1y'_2\\right)} \\times \\nonumber \\\\\n& & \\times\ne^{-\\frac{1}{4}C_{2,2}\\left[\\left(x_1+x_2+x'_1+x'_2\\right)^2+\\left(y_1+y_2+y'_1+y'_2\\right)^2\\right]} \\times \\nonumber \\\\\n& & \\times e^{+\\frac{1}{2}D_{2,2} \\left(x_1+x_2+x'_1+x'_2\\right)\\left(y_1+y_2+y'_1+y'_2\\right)} \ne^{+\\frac{1}{2}D'_{2,2} \\left(x_1+x_2-x'_1-x'_2\\right)\\left(y_1+y_2-y'_1-y'_2\\right)}, \\\n\\end{eqnarray}\nwhere\n\\begin{eqnarray}\\label{4_RDM_12_SYM_COEFF}\n& & \\alpha + \\beta +2\\left(C_{2,2} \\mp D_{2,2}\\right) =\n(\\alpha-\\beta)\n\\frac{(\\alpha-\\beta) + N(\\beta\\mp \\gamma)}\n{(\\alpha-\\beta) + (N-2)(\\beta\\mp \\gamma)},\n\\nonumber \\\\\n& & D'_{2,2} = \\gamma,\n\\end{eqnarray}\n\\end{subequations}\nand $\\alpha+C_{1,1}\\mp D_{1,1}$ are given in (\\ref{2_RDM_12_SYM_COEFF}).\nThe combinations of parameters $\\alpha + \\beta +2\\left(C_{2,2} \\mp D_{2,2}\\right)$\nwould appear below shortly.\n\nTo diagonalize \n$\\rho_{12}^{(4)}(x_1,x_2,x'_1,x'_2,y_1,y_2,y'_1,y'_2)$\nwe need to mix and rotate the coordinates of the two species\ninto new coordinates appropriately.\nThus, defining the new coordinates as the center-of-mass, relative center-of-mass,\nand relative coordinates of two identical pairs, one for each of the species,\n$u_1 = \\frac{1}{2}\\left[\\left(x_1+x_2\\right)+\\left(y_1+y_2\\right)\\right]$,\n$v_1 = \\frac{1}{2}\\left[\\left(x_1+x_2\\right)-\\left(y_1+y_2\\right)\\right]$,\n$u_2 = \\frac{1}{\\sqrt{2}}\\left(x_1-x_2\\right)$,\n$v_2 = \\frac{1}{\\sqrt{2}}\\left(y_1-y_2\\right)$\nand\n$u'_1 = \\frac{1}{2}\\left[\\left(x'_1+x'_2\\right)\\right.+\\left.\\left(y'_1+y'_2\\right)\\right]$,\n$v'_1 = \\frac{1}{2}\\left[\\left(x'_1+x'_2\\right)-\\left(y'_1+y'_2\\right)\\right]$,\n$u'_2 = \\frac{1}{\\sqrt{2}}\\left(x'_1-x'_2\\right)$,\n$v'_2 = \\frac{1}{\\sqrt{2}}\\left(y'_1-y'_2\\right)$,\nwe have for the different terms in (\\ref{4_RDM_12_SYM_DEN}): \n\\begin{eqnarray}\\label{TRAS4}\n& & x_1^2+x_2^2+y_1^2+y_2^2+{x'_1}^2+{x'_2}^2+{y'_1}^2+{y'_2}^2 =\nu_1^2+{u'_1}^2+v_1^2+{v'_1}^2+u_2^2+{u'_2}^2+v_2^2+{v'_2}^2, \\nonumber \\\\\n& & x_1x_2+x'_1x'_2+y_1y_2+y'_1y'_2 =\n\\frac{1}{2}\\left(u_1^2+{u'_1}^2+v_1^2+{v'_1}^2-u_2^2-{u'_2}^2-v_2^2-{v'_2}^2\\right), \\nonumber \\\\\n& & \\left(x_1+x_2+x'_1+x'_2\\right)^2+\\left(y_1+y_2+y'_1+y'_2\\right)^2 =\n2\\left[\\left(u_1+u'_1\\right)^2 + \\left(v_1+v'_1\\right)^2\\right], \\nonumber \\\\\n& & \\left[\\left(x_1+x_2\\right)\\pm\\left(x'_1+x'_2\\right)\\right]\\left[\\left(y_1+y_2\\right)\\pm\\left(y'_1+y'_2\\right)\\right] = \n\\left(u_1 \\pm u'_1\\right)^2 - \\left(v_1 \\pm v'_1\\right)^2. \\\n\\end{eqnarray}\nRelations (\\ref{TRAS4}) imply that\none could equally define inter-species linear combinations of the relative coordinates,\nsince\n$u_2^2+v_2^2 = \\left[\\frac{\\left(x_1-x_2\\right)+\\left(y_1-y_2\\right)}{2}\\right]^2 + \n\\left[\\frac{\\left(x_1-x_2\\right)-\\left(y_1-y_2\\right)}{2}\\right]^2$ and\n${u'_2}^2+{v'_2}^2 = \\left[\\frac{\\left(x'_1-x'_2\\right)+\\left(y'_1-y'_2\\right)}{2}\\right]^2 + \n\\left[\\frac{\\left(x'_1-x'_2\\right)-\\left(y'_1-y'_2\\right)}{2}\\right]^2$.\nWe\nchose the former combinations.\n\nPlugging (\\ref{TRAS4}) into (\\ref{4_RDM_12_SYM}) we readily find for the transformed\ninter-species reduced four-particle density matrix\n\\begin{eqnarray}\\label{4_RDM_12_SYM_DIAG}\n& &\n\\rho_{12}^{(4)}(u_1,u'_1,v_1,v'_1,u_2,u'_2,v_2,v'_2) = N^2 \\left(N-1\\right)^2\n\\times \\nonumber \\\\\n& & \\times \n\\left(\\frac{\\alpha-\\beta}{\\pi}\\right)^{\\frac{1}{2}} e^{-\\frac{\\alpha-\\beta}{2}\\left(u_2^2 + {u'_2}^2\\right)}\n\\left(\\frac{\\alpha-\\beta}{\\pi}\\right)^{\\frac{1}{2}} e^{-\\frac{\\alpha-\\beta}{2}\\left(v_2^2 + {v'_2}^2\\right)} \\times \\nonumber \\\\\n& & \\times \n\\left[\\frac{\\alpha+\\beta+2\\left(C_{2,2}-D_{2,2}\\right)}{\\pi}\\right]^\\frac{1}{2}\ne^{-\\frac{\\alpha+\\beta+C_{2,2}-\\left(D_{2,2}+D'_{2,2}\\right)}{2}\\left(u_1^2 + {u'_1}^2\\right)}\ne^{-\\left[C_{2,2}-\\left(D_{2,2}-D'_{2,2}\\right)\\right]u_1u'_1} \\times \\nonumber \\\\\n& & \\times \n\\left[\\frac{\\alpha+\\beta+2\\left(C_{2,2}+D_{2,2}\\right)}{\\pi}\\right]^\\frac{1}{2}\ne^{-\\frac{\\alpha+\\beta+C_{2,2}+\\left(D_{2,2}+D'_{2,2}\\right)}{2}\\left(v_1^2 + {v'_1}^2\\right)}\ne^{-\\left[C_{2,2}+\\left(D_{2,2}-D'_{2,2}\\right)\\right]v_1v'_1}, \\\n\\end{eqnarray}\nwhere\nthe normalization coefficients before and after diagonalization are, naturally, equal and fulfill\n$\\left[\\alpha+\\left(C_{1,1}\\mp D_{1,1}\\right)\\right]\\left[\\alpha+\\left(C_{2,2}\\mp D_{2,2}\\right)\\right]=\n\\left(\\alpha-\\beta\\right)\\left[\\alpha+\\beta+2\\left(C_{2,2}\\pm D_{2,2}\\right)\\right]$.\n\nAs can be seen in (\\ref{4_RDM_12_SYM_DIAG}) and (\\ref{2_RDM_12_SYM_DIAG}),\nthe similarities and differences between the structures\nof $\\rho_{12}^{(4)}(u_1,u'_1,v_1,v'_1,u_2,u'_2,v_2,v'_2)$ and $\\rho_{12}^{(2)}(u,u',v,v')$ \nclarify the issue of which coordinates are coupled and identify the coordinates that are not.\nIn particular, just like for the two-particle quantity,\nwe can apply Mehler's formula twice,\non the appropriately-constructed inter-species `mixed coordinates' $u_1, u'_1$ and $v_1, v'_1$,\nto diagonalize the inter-species reduced four-particle density matrix.\nWhen this is done one obtains\n\\begin{eqnarray}\\label{S_12_4}\n& & s_{12,\\pm}^{(4)} = \\sqrt{\\left(\\alpha+\\beta\\mp 2D'_{2,2}\\right)\n\\left[\\alpha+\\beta+2\\left(C_{2,2} \\mp D_{2,2}\\right)\\right]} = \\nonumber \\\\\n& & = \\sqrt{(\\alpha+\\beta\\mp 2\\gamma)(\\alpha-\\beta)\n\\frac{(\\alpha-\\beta) + N(\\beta\\mp \\gamma)}\n{(\\alpha-\\beta) + (N-2)(\\beta\\mp \\gamma)}},\n\\nonumber \\\\\n& & \\rho_{12,\\pm}^{(4)} = \\frac{\\left(\\alpha+\\beta \\mp 2D'_{2,2}\\right) - s_{12,\\pm}^{(4)}}{\\left(\\alpha+\\beta \\mp 2D'_{2,2}\\right) + s_{12,\\pm}^{(4)}} =\n\\frac{\\frac{(\\alpha+\\beta\\mp 2\\gamma)\\left[(\\alpha-\\beta) + (N-2)(\\beta\\mp \\gamma)\\right]}{(\\alpha-\\beta)\\left[(\\alpha-\\beta) + N(\\beta\\mp \\gamma)\\right]}-1}\n{\\frac{(\\alpha+\\beta\\mp 2\\gamma)\\left[(\\alpha-\\beta) + (N-2)(\\beta\\mp \\gamma)\\right]}{(\\alpha-\\beta)\\left[(\\alpha-\\beta) + N(\\beta\\mp \\gamma)\\right]}+1},\n\\nonumber \\\\\n& & 1 - \\rho_{12,\\pm}^{(4)} = \\frac{2s_{12,\\pm}^{(4)}}{\\left(\\alpha+\\beta \\mp 2D'_{2,2}\\right) + s_{12,\\pm}^{(4)}}, \\\n\\end{eqnarray}\nwhere the ``$+$'' terms quantify the fragmentation in the $u_1, u'_1$ part of the inter-species reduced four-particle density matrix and\nthe ``$-$'' terms determine\nthe fragmentation in the $v_1, v'_1$ part of the inter-species reduced four-particle density matrix.\nAs found and shown in (\\ref{4_RDM_12_SYM_DIAG}),\nthere is no fragmentation due to the relative-coordinate parts $u_2, u'_2$ and $v_2, v'_2$.\nEquation (\\ref{S_12_4}) adds to the main results of the present work and bears\na transparent and appealing physical meaning:\nIn the mixture inter-species fragmentation is quantified by\nthe eigenvalues obtained from Mehler's formula when the latter\nis applied to the mixture's center-of-mass and relative center-of-mass coordinates\nof distinguishable pairs of pairs.\nExtensions to larger distinguishable aggregates of species $1$ and species $2$ identical bosons in the mixture is possible along the above lines,\nand will not be pursued further here.\n\nWe can now prescribe the decomposition of the intra-species reduced four-particle density matrix,\nin as much as the reduced two-particle density matrix was decomposed, \ninto its natural four-particle functions made of distinguishable particles which is given by\n\\begin{eqnarray}\\label{12_4_RDM_NAT_DIS_GEM}\n& &\n\\rho_{12}^{(4)}(x_1,x_2,x'_1,x'_2,y_1,y_2,y'_1,y'_2) = N^2(N-1)^2 \n\\sum_{n_+=0}^\\infty \\sum_{n_-=0}^\\infty\n\\left(1-\\rho_{12,+}^{(4)}\\right)\n\\left(1-\\rho_{12,-}^{(4)}\\right) \\times \\nonumber \\\\\n& & \\times \\left(\\rho_{12,+}^{(4)}\\right)^{\\!n_+}\n\\left(\\rho_{12,-}^{(4)}\\right)^{\\!n_-}\n\\Phi^{(4)}_{12,n_+,n_-}(x_1,x_2,y_1,y_2) \\Phi^{(4),\\ast}_{12,n_+,n_-}(x'_1,x'_2,y'_1,y'_2), \\nonumber \\\\\n& & \\Phi^{(4)}_{12,n_+,n_-}(x_1,x_2,y_1,y_2) = \\nonumber \\\\\n& & =\n\\frac{1}{\\sqrt{2^{n_+} {n_+}!}}\n\\left(\\frac{s_{12,+}^{(4)}}{\\pi}\\right)^{\\frac{1}{4}}\nH_{n_+}\\left(\\frac{\\sqrt{s_{12,+}^{(4)}}}{2}\\left[\\left(x_1+x_2\\right)+\\left(y_1+y_2\\right)\\right]\\right)\ne^{-\\frac{1}{8}s_{12,+}^{(4)}\\left[\\left(x_1+x_2\\right)+\\left(y_1+y_2\\right)\\right]^2} \\times \\nonumber \\\\\n& & \\times\n\\frac{1}{\\sqrt{2^{n_-} {n_-}!}}\n\\left(\\frac{s_{12,-}^{(4)}}{\\pi}\\right)^{\\frac{1}{4}}\nH_{n_-}\\left(\\frac{\\sqrt{s_{12,-}^{(4)}}}{2}\\left[\\left(x_1+x_2\\right)-\\left(y_1+y_2\\right)\\right]\\right)\ne^{-\\frac{1}{8}s_{12,-}^{(4)}\\left[\\left(x_1+x_2\\right)-\\left(y_1+y_2\\right)\\right]^2} \\times \\nonumber \\\\\n& & \n\\times \\left(\\frac{\\alpha-\\beta}{\\pi}\\right)^{\\frac{1}{4}}\ne^{-\\frac{\\alpha-\\beta}{4}\\left(x_1-x_2\\right)^2}\n\\left(\\frac{\\alpha-\\beta}{\\pi}\\right)^{\\frac{1}{4}}\ne^{-\\frac{\\alpha-\\beta}{4}\\left(y_1-y_2\\right)^2}. \\\n\\end{eqnarray}\nEquation (\\ref{12_4_RDM_NAT_DIS_GEM}) means\nthat the pair-of-distinguishable-pairs `condensed fraction' is given by\nthe product\n$\\left(1-\\rho_{12,+}^{(4)}\\right)\\left(1-\\rho_{12,-}^{(4)}\\right)$ \nand the respective depleted fraction is\\break\\hfill\n$1-\\left(1-\\rho_{12,+}^{(4)}\\right)\\left(1-\\rho_{12,-}^{(4)}\\right)=\n\\rho_{12,+}^{(4)}+\\rho_{12,-}^{(4)}-\\rho_{12,+}^{(4)}\\rho_{12,-}^{(4)}$.\nThe center-of-mass and relative center-of-mass coordinates of the two pairs,\n$\\frac{\\left(x_1+x_2\\right)\\pm\\left(y_1+y_2\\right)}{2}$,\ncarry the respective scalings $s_{12,\\pm}^{(4)}$.\nThe natural four-particle functions $\\Phi^{(4)}_{12,n_+,n_-}(x_1,x_2,y_1,y_2)$\nare enumerated by the two quantum numbers $n_+$, $n_-$ and\nare obviously orthonormal to each other. \n\nWe proceed now to examine fragmentation in this higher-order inter-species reduced density matrix.\nWe investigate as above the specific case of $\\lambda+\\lambda_{12}=0$.\nTo compute $\\rho_{12}^{(4)}(x_1,x_2,x'_1,x'_2,y_1,y_2,y'_1,y'_2)$\nwe require the quantities\n$\\left[\\alpha+\\beta+2\\left(C_{2,2} - D_{2,2}\\right)\\right] = m \\omega$\nand\n$\\left(\\alpha+\\beta-2D'_{2,2}\\right) = m\\omega$\nfor the ``$+$'' branch as well as\n$\\left[\\alpha+\\beta+2\\left(C_{2,2} + D_{2,2}\\right)\\right] =\nm\\omega \\frac{1}{1 + \\frac{2}{N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)}$\nand\n$\\left(\\alpha+\\beta+2D'_{2,2}\\right) =\nm\\omega \\left[1 + \\frac{2}{N}\\left(\\frac{\\Omega_{12}}{\\omega}-1\\right)\\right]$\nfor the ``$-$'' branch.\n\nNow, expressions (\\ref{S_12_4}) can readily be evaluated and the following picture\nof higher-order inter-species fragmentation is found:\n\\begin{subequations}\\label{S4_INTER_EXAM}\n\\begin{eqnarray}\\label{S4_12_+_EXAM}\n& & s_{12,+}^{(4)} = m\\omega,\n\\qquad\n\\rho_{12,+}^{(4)} = 0,\n\\qquad\n1 - \\rho_{12,+}^{(4)} = 1, \\\n\\end{eqnarray}\nindicating that there is no contribution to fragmentation from the center-of-mass `mixed coordinate' $u_1, u'_1$.\nThis is additional to the no contribution to fragmentation coming from the relative coordinates\n$u_2, u'_2$ and $v_2, v'_2$,\nsee (\\ref{4_RDM_12_SYM_DIAG}).\nFor the relative center-of-mass `mixed coordinate' $v_1, v'_1$,\non the other end,\none finds\n\\begin{eqnarray}\\label{S4_12_-_EXAM}\n& & s_{12,-}^{(4)} = m\\omega \\sqrt{\\frac{1 + \\frac{2}{N}\\left(\\frac{\\Omega_{12}}{\\omega}-1\\right)}\n{1 + \\frac{2}{N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)}},\n\\nonumber \\\\ \\nonumber \\\\\n& & \\rho_{12,-}^{(4)} = \\frac{\\sqrt{\\left[1 + \\frac{2}{N}\\left(\\frac{\\Omega_{12}}{\\omega}-1\\right)\\right]\n\\left[1 + \\frac{2}{N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)\\right]}-1}\n{\\sqrt{\\left[1 + \\frac{2}{N}\\left(\\frac{\\Omega_{12}}{\\omega}-1\\right)\\right]\n\\left[1 + \\frac{2}{N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)\\right]}+1},\n\\nonumber \\\\\n& & 1 - \\rho_{12,-}^{(4)} = \\frac{2}\n{\\sqrt{\\left[1 + \\frac{2}{N}\\left(\\frac{\\Omega_{12}}{\\omega}-1\\right)\\right]\n\\left[1 + \\frac{2}{N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)\\right]}+1}, \\\n\\end{eqnarray}\n\\end{subequations}\nnamely, that the fragmentation of pairs of distinguishable pairs \nfully originates from the relative center-of-mass `mixed coordinate' $v_1, v'_1$.\nWe see that also the higher-order inter-species fragmentation is governed by the ratio $\\frac{\\Omega_{12}}{\\omega}$\nand takes place both at the attractive and repulsive sectors of interactions.\nConcluding, higher-order inter-species fragmentation is proved.\n\nNow, one can compute the ratio $\\frac{\\Omega_{12}}{\\omega}=\\sqrt{1+\\frac{4N}{m\\omega^2}\\lambda_{12}}$\nfor which the inter-species reduced four-particle density matrix is $50\\%$ fragmented as in (\\ref{rho_half}).\nSince $\\rho_{12,+}^{(4)}=0$ does not contribute in this specific case,\nthe only contribution to fragmentation comes from\n$\\rho_{12,-}^{(4)}$.\nThus, solving (\\ref{S4_12_-_EXAM}) for $50\\%$ distinguishable-four-particle-function fragmentation we obtain\n\\begin{eqnarray}\\label{FRAG_INTER_4}\n\\rho_{12,-}^{(4)}=\\frac{1}{2} \\quad\n\\Longrightarrow \\quad\n\\frac{\\Omega_{12}}{\\omega} =\n\\left(1 + \\frac{2N^2}{N-2}\\right) \\pm \\sqrt{\\left(1 + \\frac{2N^2}{N-2}\\right)^2 - 1}.\n\\end{eqnarray}\nAs for distinguishable pairs,\nthere are two `reciprocate' solutions,\none for strong attractions and the second close to the border of stability for repulsions.\nAlso, to achieve the same degree of $50\\%$\nwith a larger number $\\frac{N}{2}$ of distinguishable four-boson aggregates,\na stronger attraction or repulsion is needed.\nFurthermore,\ncomparing distinguishable-four-boson and distinguishable-two-boson fragmentation at the same $50\\%$ value,\none sees from (\\ref{FRAG_INTER_4}) and (\\ref{FRAG_INTER_2}) that \nslightly weaker interactions, attractions or repulsions, are needed for the former.\nThis behavior of fragmentation of increasing orders of inter-species reduced density matrices\nis analogous to and generalizes\nthat of intra-species and single-species reduced density matrices,\nsee the previous section and the appendix, respectively.\n\nFinally, we present for completeness\nthe inter-species four-particle density,\ni.e., the diagonal part\n$\\rho_{12}^{(4)}(x_1,x_2,y_1,y_2)=\n\\rho_{12}^{(4)}(x_1,x_2,x'_1=x_1,x'_2=x_2,y_1,y_2,y'_1=y_1,y'_2=y_2)$,\nwhich is given by\n\\begin{eqnarray}\\label{DENSITY_4_12_EXAM}\n& &\n\\rho_{12}^{(4)}(x_1,x_2,y_1,y_2) = N^2 \\left(N-1\\right)^2\n\\left(\\frac{\\alpha-\\beta}{\\pi}\\right)\ne^{-\\frac{\\alpha-\\beta}{2}\\left(x_1-x_2\\right)^2}\ne^{-\\frac{\\alpha-\\beta}{2}\\left(y_1-y_2\\right)^2} \\times \\nonumber \\\\\n& & \\times \n\\left[\\frac{\\alpha+\\beta+2\\left(C_{2,2}-D_{2,2}\\right)}{\\pi}\\right]^\\frac{1}{2}\ne^{-\\frac{\\alpha+\\beta+2\\left(C_{2,2}-D_{2,2}\\right)}{4}\\left[\\left(x_1+x_2\\right)+\\left(y_1+y_2\\right)\\right]^2}\n\\times \\nonumber \\\\\n& & \\times \n\\left[\\frac{\\alpha+\\beta+2\\left(C_{2,2}+D_{2,2}\\right)}{\\pi}\\right]^\\frac{1}{2}\ne^{-\\frac{\\alpha+\\beta+2\\left(C_{2,2}+D_{2,2}\\right)}{4}\\left[\\left(x_1+x_2\\right)-\\left(y_1+y_2\\right)\\right]^2} = \\nonumber \\\\\n& & \n= N^2 \\left(N-1\\right)^2 \\left(\\frac{m\\omega}{\\pi}\\right)^{\\frac{3}{2}}\ne^{-\\frac{m\\omega}{2}\\left(x_1-x_2\\right)^2} e^{-\\frac{m\\omega}{2}\\left(y_1-y_2\\right)^2} \ne^{-\\frac{m\\omega}{4}\\left[\\left(x_1+x_2\\right)+\\left(y_1+y_2\\right)\\right]^2} \\times \\nonumber \\\\\n& & \\times \\left(\\frac{m\\omega}{\\pi\\left[1 + \\frac{2}{N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)\\right]}\\right)^{\\frac{1}{2}}\ne^{-\\frac{m\\omega}{4\\left[1 + \\frac{2}{N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)\\right]}\n\\left[\\left(x_1+x_2\\right)-\\left(y_1+y_2\\right)\\right]^2}.\n\\end{eqnarray}\nTo proceed,\nthe size of the distinguishable four-boson cloud can be estimated \nfrom the widths of the respective Gaussian functions in the density (\\ref{DENSITY_4_12_EXAM}).\nThus, we obtain\n\\begin{subequations}\\label{WIDTH_4_INTER}\n\\begin{eqnarray}\\label{WIDTH_4_INTER_GEN}\n& & \\sigma_{12,\\frac{x_1-x_2}{\\sqrt{2}}}^{(4)} = \\sqrt{\\frac{1}{2m\\omega}}, \\quad\n\\sigma_{12,\\frac{y_1-y_2}{\\sqrt{2}}}^{(4)} = \\sqrt{\\frac{1}{2m\\omega}}, \\quad\n\\sigma_{12,\\frac{\\left(x_1+x_2\\right)+\\left(y_1+y_2\\right)}{2}}^{(4)} =\n\\sqrt{\\frac{1}{2m\\omega}}, \\nonumber \\\\\n& & \n\\sigma_{12,\\frac{\\left(x_1+x_2\\right)-\\left(y_1+y_2\\right)}{2}}^{(4)} = \\sqrt{\\frac{1 + \\frac{2}{N}\\left(\\frac{\\omega}{\\Omega_{12}}-1\\right)}{2m\\omega}}. \\\n\\end{eqnarray}\nTo show the combined effect of the inter-species and intra-species interactions\naccompanying\nfragmentation of $\\rho_{12}^{(4)}(x_1,x_2,x'_1,x'_2,y_1,y_2,y'_1,y'_2)$,\nit is instrumental to compute the sizes (\\ref{WIDTH_4_INTER_GEN}) for large inter-species attractions or \ninter-species repulsions at the border of stability.\nWe obtain, respectively,\n\\begin{eqnarray}\\label{WIDTH_4_INTER_LIM}\n& & \\!\\!\\!\\!\\!\\!\\!\\! \\lim_{\\frac{\\Omega_{12}}{\\omega} \\to \\infty} \\sigma_{12,\\frac{\\left(x_1+x_2\\right)-\\left(y_1+y_2\\right)}{2}}^{(4)} = \n\\sqrt{\\frac{1 - \\frac{2}{N}}{2m\\omega}}, \\qquad\n\\sigma_{12,\\frac{\\left(x_1+x_2\\right)-\\left(y_1+y_2\\right)}{2}}^{(4)}\n\\longrightarrow \\infty \\quad \\mathrm{for} \\quad \\frac{\\Omega_{12}}{\\omega} \\to 0^+,\n\\\n\\end{eqnarray}\n\\end{subequations}\nwhere\n$\\sigma_{12,\\frac{x_1-x_2}{\\sqrt{2}}}^{(4)}$,\n$\\sigma_{12,\\frac{y_1-y_2}{\\sqrt{2}}}^{(4)}$, and\n$\\sigma_{12,\\frac{\\left(x_1+x_2\\right)+\\left(y_1+y_2\\right)}{2}}^{(4)}$\ndo not depend on the interactions.\nWe see that the size of the inter-species four-boson density\nsaturates as well at about the trap's size and does not depend on the strengths of interactions\nin the limit of strong inter-species attractions.\nAs for the pair of distinguishable bosons,\na strong fragmentation is possible in the mixture with\nhardy any shrinking of the density in comparison with the bare trap\ndue to the condition $\\lambda+\\lambda_{12}=0$,\ni.e., that strong inter-species attractive interaction is accompanied by \nstrong intra-species repulsion of equal magnitude.\nSummarizing, inter-species fragmentation in higher-order reduced density matrices\nis also governed by the ratio $\\frac{\\Omega_{12}}{\\omega}$\nand takes place both at the attractive and repulsive sectors of interactions.\n\n\\subsection{Inter-species entanglement and the limit of an infinite number of particles}\\label{MORE_Schmidt}\n\nIn the previous sections the reduced density matrices \nfor identical and distinguishable pairs of bosons were diagonalized and\nthe intra-species and inter-species fragmentations explored.\nBoth kinds of fragmentations are critical phenomena in the sense that,\ngoing to the limit of an infinite number of particles while keeping the interaction parameters \n(products of the number of particles times the interaction strengths) constant,\nthe respective reduced density matrix per particle becomes $100\\%$ condensed \\cite{HIM_MIX_RDM}.\nThis can be easily obtained from the leading natural eigenvalues of the natural functions\nexplicitly obtained above,\nsee the general (\\ref{S_1_1}), (\\ref{S_1_2}), (\\ref{S_12_2}), (\\ref{S_12_4})\nand specific (\\ref{S_INTRA_EXAM}), (\\ref{S2_INTER_EXAM}), (\\ref{S4_INTER_EXAM}) expressions,\nwhich are all equal to $1$ in this limit.\n\nIn the present, concluding subsection we touch upon a property of the mixture which does not diminish at the limit\nof an infinite number of particles.\nClassifying properties of Bose-Einstein condensates and their mixtures\nat the limit of an infinite number of particles,\nand especially when many-body and mean-field theories do not coincide,\nis an active field of research,\nwhere variances and the overlap between the many-body and mean-field\nwavefunctions are discussed elsewhere,\nsee \\cite{HIM_MIX_VAR,HIM_MIX_FLOQUET,HIM_MIX_CP,INF1,INF2,INF3,INF4,INF5,INF6,INF7,INF8,INF9}.\nHere, combining the techniques used in the previous sections,\nwe apply Mehler's formula to perform the Schmidt decomposition of the wavefunction.\n\nLet us examine the mixture's wavefunction,\nfor which the coordinates of the two species are coupled to each other owing to the inter-species interaction,\nsee the last term in (\\ref{HIM_MIX_WF_DEN_MAT1}).\nTo remind, the wavefunction is obtained by representing the Hamiltonian (\\ref{HIM_MIX}) with the mixture's Jacoby coordinates,\nfor which it is fully diagonalized, and translating back to the laboratory frame.\nTo decouple the coordinates of each species, in the sense of prescribing the Schmidt decomposition of the wavefunction,\nit is useful to go `half a step' backward,\nand express (\\ref{HIM_MIX_WF_DEN_MAT1}) using the individual species' Jacoby coordinates.\n\nThe Jacoby coordinates of each species are given by\n\\begin{eqnarray}\\label{JACOBY_12}\n& & X_k = \\frac{1}{\\sqrt{k(k+1)}} \\sum_{j=1}^k \\left(x_{k+1}-x_j\\right), \\quad 1\\le k \\le N-1, \\qquad\nX_{N} = \\frac{1}{\\sqrt{N}} \\sum_{j=1}^{N} x_j, \\nonumber \\\\\n& & Y_k = \\frac{1}{\\sqrt{k(k+1)}} \\sum_{j=1}^k \\left(y_{k+1}-y_j\\right), \\quad 1\\le k \\le N-1, \\qquad\nY_{N} = \\pm \\frac{1}{\\sqrt{N}} \\sum_{j=1}^{N} y_j, \\\n\\end{eqnarray}\nwhere, for the derivation given below,\nit is useful to distinguish between the two cases for the definition of, say, $Y_N$:\nThe plus sign is assigned to positive $\\gamma$, namely,\nto attractive inter-species interactions for which $\\Omega_{12} > \\omega$,\nand the minus sign is assigned to negative $\\gamma$, i.e.,\nto repulsive inter-species interactions where $\\Omega_{12} < \\omega$.\n\nFor the symmetric mixture,\ngiven the above Jacobi coordinates of each species, Eq.~(\\ref{JACOBY_12}),\nthe wavefunction reads\n\\begin{subequations}\\label{WF_MIX}\n\\begin{eqnarray}\\label{WF_MIX_JACOBY}\n& & \\Psi(X_1,\\ldots,X_{N},Y_1,\\ldots,Y_{N}) =\n\\left(\\frac{m\\Omega}{\\pi}\\right)^{\\frac{N-1}{2}}\n\\left(\\frac{M_{12}\\Omega_{12}}{\\pi}\\right)^{\\frac{1}{4}}\n\\left(\\frac{M\\omega}{\\pi}\\right)^{\\frac{1}{4}} \\times \\nonumber \\\\\n& & \\times e^{-\\frac{1}{2} m \\Omega \\sum_{k=1}^{N-1} \\left(X_k^2 + Y_k^2\\right)}\ne^{-\\frac{\\frac{1}{2}m\\left(\\Omega_{12}+\\omega\\right)}{2}\\left(X_{N}^2 + Y_{N}^2\\right)}\ne^{\\pm\\frac{1}{2}m\\left(\\Omega_{12}-\\omega\\right)X_{N}Y_{N}}. \\\n\\end{eqnarray}\nIndeed, all relative coordinates are decoupled and the only coupling due to the inter-species interaction\nis between the center-of-mass\n$X_N$ of species $1$ bosons\nand the center-of-mass\n$Y_N$ of species $2$ bosons.\nConsequently, applying Mehler's formula to the intra-species\ncenter-of-mass Jacoby coordinates $X_{N}$ and $Y_{N}$\nthe Schmidt decomposition of (\\ref{WF_MIX_JACOBY}) is readily performed and given by\n\\begin{eqnarray}\\label{WF_MIX_SCHMIDT}\n& & \\Psi(X_1,\\ldots,X_{N},Y_1,\\ldots,Y_{N})\n= \\sum_{n=0}^{\\infty} \\sqrt{1-\\rho^2_{SD}} \\rho_{SD}^n \\Phi_{1,n}(X_1,\\ldots,X_N) \\Phi_{2,n}(Y_1,\\ldots,Y_N), \\nonumber \\\\\n& & \\Phi_{1,n}(X_1,\\ldots,X_N) = \\left(\\frac{m\\Omega}{\\pi}\\right)^{\\frac{N-1}{4}}\ne^{-\\frac{1}{2} m \\Omega \\sum_{k=1}^{N-1} X_k^2}\n\\frac{1}{\\sqrt{2^n n!}} \\left(\\frac{s_{SD}}{\\pi}\\right)^{\\frac{1}{4}} H_n\\left(\\sqrt{s_{SD}}X_N\\right) e^{-\\frac{1}{2}s_{SD} X_N^2}, \\nonumber \\\\\n& & \\Phi_{2,n}(Y_1,\\ldots,Y_N) = \\left(\\frac{m\\Omega}{\\pi}\\right)^{\\frac{N-1}{4}}\ne^{-\\frac{1}{2} m \\Omega \\sum_{k=1}^{N-1} Y_k^2}\n\\frac{1}{\\sqrt{2^n n!}} \\left(\\frac{s_{SD}}{\\pi}\\right)^{\\frac{1}{4}} H_n\\left(\\sqrt{s_{SD}}Y_N\\right) e^{-\\frac{1}{2}s_{SD} Y_N^2}, \\nonumber \\\\\n& & \\sqrt{1-\\rho^2_{SD}} =\n\\frac{2\\sqrt{\\frac{\\Omega_{12}}{\\omega}}}{1+\\frac{\\Omega_{12}}{\\omega}}, \\qquad\n\\rho_{SD} =\n\\frac{\\left(\\frac{\\Omega_{12}}{\\omega}\\right)^{\\pm 1}-1}{\\left(\\frac{\\Omega_{12}}{\\omega}\\right)^{\\pm 1}+1}, \\qquad\ns_{SD} = m\\sqrt{\\omega\\Omega_{12}}.\n\\\n\\end{eqnarray}\n\\end{subequations}\nWe remind that the plus sign is for attraction and the minus for repulsion,\nwhich is what guarantees that $\\rho_{SD}$ \nand consequently the Schmidt coefficients $\\sqrt{1-\\rho^2_{SD}} \\rho_{SD}^n$, $n=0,1,2,3,\\ldots$\nare always positive.\n$s_{SD}$ defines the inverse width of the individual species' center-of-mass Gaussians in\nthe Schmidt basis $\\Phi_{1,n}(X_1,\\ldots,X_N)$ and $\\Phi_{2,n}(Y_1,\\ldots,Y_N)$. \n\nLet us concisely discuss properties of the Schmidt decomposition of the mixture, Eq.~(\\ref{WF_MIX_SCHMIDT}). \nClearly and interestingly,\nthe Schmidt coefficients are independent of the intra-species dressed frequency $\\Omega$,\nwhich only appears in conjunction with intra-species relative coordinates, \ni.e., the Schmidt coefficients depend solely on the\ninter-species interaction.\nFurthermore,\nthere is a kind of symmetry between respective attractive and repulsive inter-species interactions,\nas one gets the\nsame Schmidt coefficients for the inter-species frequency $\\frac{\\Omega_{12}}{\\omega}=\\sqrt{1+\\frac{4N\\lambda_{12}}{m\\omega^2}}$ and\ninverse frequency $\\frac{\\omega}{\\Omega_{12}}=\\frac{1}{\\sqrt{1+\\frac{4N\\lambda_{12}}{m\\omega^2}}}$.\n\nLast but not least,\nthe same Schmidt coefficients are obtained when the product\nof the number of bosons in each species times the inter-species interaction strength, $N\\lambda_{12}$, is held fixed,\nand $N$ is increased to infinity.\nIn other words,\nwhereas identical and distinguishable bosons, pairs, four-particle aggregates, etc.\nare $100\\%$ condensed at the limit of an infinite number of particles, \ni.e., the leading eigenvalue of \nall finite-order intra-species and inter-species reduced density matrices per particle is $1$,\nthe mixture's wavefunction exhibits a fixed amount of entanglement at the infinite-particle-number limit.\nThis is a good place to bring the present study to an end. \n\n\\subsection{Summary and Outlook}\\label{SUM_OUT}\n\nThe present work aims at developing and combining concepts from quantum theory\nof many-particle systems with novel results on the physics\nof trapped mixtures of Bose-Einstein condensates.\nThe notions of natural orbitals and\nnatural geminals are fundamental to many-particle systems\nmade of identical particles.\nThese natural functions entail the diagonalization of the reduced one-particle and two-particle density matrices, respectively.\nIn a mixture of two kinds of identical particles,\nhere explicitly two types of bosons,\nthere are, naturally, identical bosons and pairs made of indistinguishable bosons of either species.\nTo find their natural orbitals and natural geminals,\nthe construction and subsequent diagonalization of\nrespective intra-species reduced density matrices is in need.\nIn the mixture there are, additionally, pairs made of distinguishable bosons.\nAnalogously, their theoretical description would require\nassembling, diagonalizing, and analyzing the inter-species\nreduced two-particle density matrix. \nIn the present work we have investigated pairs made of identical or distinguishable\nbosons in a mixture of Bose-Einstein condensates,\ncovering both the structure of the respective natural pair functions,\non the more formal theoretical side,\nand the exploration of pairs' fragmentation.\nLike identical bosons,\nwhich can, depending on whether the reduced one-particle density matrix has\none or more macroscopic eigenvalues,\nbe condensed or fragmented,\nso do pairs of bosons.\nWe showed in the present work that,\nin the mixture, both pairs made of identical bosons\nand pairs consisting of distinguishable bosons\ncan be condensed and more so fragmented.\n\nTo tackle the above and other questions,\nwe employed a solvable model,\nthe symmetric harmonic-interaction model for mixtures.\nThe natural geminals for pairs made of identical or distinguishable bosons\nwere explicitly contracted as a function of the inter-species and intra-species interactions.\nThis was done\nby diagonalizing the corresponding intra-species and inter-species reduced two-particle density matrices\nusing applications of Mehler's formula on appropriately-constructed linear combinations of intra-species and inter-species coordinates.\nHere, the role of the mixture's center-of-mass and relative center-of-mass coordinates was identified and explained.\nThe structure of identical and distinguishable pairs in the mixture was discussed,\nand a generalization to pairs of distinguishable pairs using the inter-species reduced four-body density matrix was made.\nA particular case, where attractive and repulsive inter-species and intra-species interactions are opposite in magnitude,\nhas been worked out explicitly.\nFragmentation of bosons, pairs, and pairs of pairs in the mixture has been proven,\nand the size of the respective densities analyzed.\nLast but not least,\nas a complementary investigation,\nthe exact Schmidt decomposition of the mixture's wavefunction was performed.\nThe entanglement between the two species was shown to be governed by the coupling of their individual center-of-mass coordinates\nand, consequently, not to vanish at the limit of an infinite number of particles where\nany finite-order intra-species and inter-species reduced density matrix per particle is 100\\% condensed.\n\nThe present investigations suggest several directions for further developments.\nWe have treated the symmetric mixture\nand an anticipated extension to\ngeneric trapped mixtures, with different numbers of bosons, masses, and interaction strengths for each species, would be in place.\nIn what capacity the fragmentation of identical pairs in the different species can be made to differ,\nand to what extent the fragmentation of distinguishable pairs would become more complex? \nDo the center-of-mass and relative center-of-mass coordinates keep their\nrole in the diagonalization of inter-species reduced density matrices for a generic mixture?\nIt also makes sense, in a generic mixture,\nto investigate fragmentation of\naggregates with unequal numbers of bosons from each species,\nlike, for instance, the analysis of inter-species reduced three-particle density matrices.\nAnother extension foreseen is to mixtures with more species and, if feasible,\nto generic multi-species mixtures where, e.g., one species could serve as a bridge between two baths.\nFinally, one could forecast that the topic of Bose-Einstein condensates and mixtures in the limit of an infinite number of particles\nwould be enriched by exploring the Schmidt decomposition of the wavefunction.\nRecall that at the infinite-particle-number limit any finite-order intra-species and inter-species reduced\ndensity matrix per particle is $100\\%$ condensed.\nHere, observables' variances and wavefunctions' overlaps\nhave deepened our understanding of the\ndifferences between many-body and mean-field theories of Bose-Einstein condensates and mixtures\nat limit of an infinite number of particles,\nbut are properties already defined for single-species bosons.\nThe Schmidt decomposition, on the other hand, is a property that\nenters the topic of the infinite-particle-number limit starting, obviously,\nonly from a two-species mixture.\nAll of which paves the way for further intriguing investigations to come.\n \n\\section*{Acknowledgements}\n\nThis research was supported by the Israel Science Foundation \n(Grant No. 1516\/19). \n\n","meta":{"redpajama_set_name":"RedPajamaArXiv"}} +{"text":"\n\n\n\n\\section{Introduction}\n\n\\subsection{Objective}\n\nDesigning computing environments consuming a limited amount of energy while achieving computationally complex tasks is an objective of utmost importance, especially in distributed systems involving a large number of computing entities. In this paper, we aim at designing energy-efficient algorithms for the standard LOCAL and CONGEST models of distributed computing in networks~\\cite{peleg2000}. Both models assume a network modeled as an $n$-node graph $G=(V,E)$, where each node is provided with an identifier, i.e., an integer that is unique in the network, which can be stored on $O(\\log n)$ bits. All nodes are assumed to run the same algorithm, and computation proceeds as a series of synchronous rounds (all nodes start simultaneously at round~1). During a round, every node sends a message to each of its neighbors, receives the messages sent by its neighbors, and performs some individual computation. The two models LOCAL and CONGEST differ only in the amount of information that can be exchanged between nodes at each round. \n\nThe LOCAL model does not bound the size of the messages, whereas the CONGEST model allows only messages of size $O(\\log n)$ bits. Initially, every node~$v\\in V$ knows solely its identifier~$\\mathsf{id}(v)$, an upper bound of the number~$n$ of nodes, which is assumed to be polynomial in~$n$ and to be the same for all nodes, plus possibly some input bit-string $x(v)$ depending on the task to be solved by the nodes. In this paper, we denote by $N$ the maximum between the largest identifier and the upper bound on~$n$ given to all nodes. Hence $N=O(\\mbox{poly}(n))$, and is supposed to be known by all nodes. After a certain number of rounds, every node outputs a bit-string~$y(v)$, where the correctness of the collection of outputs $y=\\{y(v):v\\in V\\}$ is defined with respect to the specification of the task to be solved, and may depend on the collection of inputs $x=\\{x(v):v\\in V\\}$ given to the nodes, as well as on the graph~$G$ (but not on the identifiers assigned to the nodes, nor on the upper bound~$N$). \n\n\\paragraph{Activation complexity.} \n\nWe measure the energy consumption of an algorithm~$A$ by counting how many times each node and each edge is activated during the execution of the algorithm. More specifically, a node~$v$ (resp., an edge~$e$) is said to be \\emph{active} at a given round~$r$ if $v$ is sending a message to at least one of its neighbors at round~$r$ (resp., if a message traverses $e$ at round~$r$). The \\emph{node-activation} and the \\emph{edge-activation} of an algorithm~$A$ running in a graph $G=(V,E)$ are respectively defined as \n\\[\n\\mathsf{nact}(A):=\\max_{v\\in V}\\#\\mbox{activation}(v),\n\\;\\; \\mbox{and} \\;\\;\n\\mathsf{eact}(A):=\\max_{e\\in E}\\#\\mbox{activation}(e),\n\\]\nwhere $\\#\\mbox{activation}(v)$ (resp., $\\#\\mbox{activation}(e)$) denotes the number of rounds during which node~$v$ (resp., edge~$e$) is active along the execution of the algorithm~$A$.\nBy definition, we have that, in any graph of maximum degree~$\\Delta$, \n\\begin{equation}\\label{eq:ineq-activation}\n\\mathsf{eact}(A)\\leq 2\\cdot \\mathsf{nact}(A), ~\\textrm{ and }~ \\mathsf{nact}(A) \\leq \\Delta\\cdot\\mathsf{eact}(A).\n\\end{equation}\n\n\\paragraph{Objective.} \n\nOur goal is to design \\emph{frugal} algorithms, that is, algorithms with \\emph{constant} node-activation, or to the least \\emph{constant} edge-activation, independent of the number~$n$ of nodes and of the number~$m$ of edges. Indeed, such algorithms can be viewed as consuming the least possible energy for solving a given task. Moreover, even if the energy requirement for solving the task naturally grows with the number of components (nodes or edges) of the network, it grows \\emph{linearly} with this number whenever using frugal algorithms. We refer to \\emph{node-frugality} or \\emph{edge-frugality} depending on whether we focus on node-activation or edge-activation, respectively. \n\n\\subsection{Our Results}\n\nWe first show that every Turing-computable problem\\footnote{A problem is Turing-computable if there exists a Turing machine that, given any graph with identifiers and inputs assigned to the nodes, computes the output of each node in the graph.} can thus be solved by a node-frugal algorithm in the LOCAL model as well as in the CONGEST model. It follows from Eq.~\\ref{eq:ineq-activation} that every Turing-computable problem can be solved by an edge-frugal algorithm in both models. In other words, every problem can be solved by an energy-efficient distributed algorithm. One important question remains: what is the round complexity of frugal algorithms? \n\nIn the LOCAL model, our node-frugal algorithms run in $O(\\mbox{poly}(n))$ rounds. However, they may run in exponentially many rounds in the CONGEST model. We show that this cannot be avoided. Indeed, even if many symmetry-breaking problems such as computing a maximal-independent set ({\\sc mis}) and computing a $(\\Delta+1)$-coloring can be solved by a node-frugal algorithm performing in $O(\\mbox{poly}(n))$ rounds, we show that there exist problems (e.g., deciding $C_4$-freeness or deciding the presence of symmetries in the graph) that cannot be solved in $O(\\mbox{poly}(n))$ rounds in the CONGEST model by any edge-frugal algorithm. \n\nFinally, we discuss the relation between node-activation complexity and edge-activation complexity. We show that the bounds given by Eq.~\\ref{eq:ineq-activation} are essentially the best that can be achieved in general. Precisely, we identify a problem, namely \\textsc{Depth First Pointer Chasing}{} (\\textsc{dfpc}), which has edge-activation complexity $O(1)$ for all graphs with an algorithm running in $O(\\mbox{poly}(n))$ rounds in the CONGEST model, but satisfying that, for every $\\Delta =O\\left(\\frac{n^{1\/4}}{\\sqrt{\\log n}}\\right)$, its node-activation complexity in graphs with maximum degree $\\Delta$ is $\\Omega(\\Delta)$ whenever solved by an algorithm bounded to run in $O(\\mbox{poly}(n))$ rounds in the CONGEST model. In particular, \\textsc{Depth First Pointer Chasing}{} has constant edge-activation complexity but node-activation complexity $\\tilde{\\Omega}(n^{1\/4})$ in the CONGEST model (for $O(\\mbox{poly}(n))$-round algorithms). \n\nOur main results are summarized in Table~\\ref{tab:summary}. \n\n\\begin{table}\n\\begin{center} \n\\begin{tabular}{l|l|l|l|}\n& \\hspace{1cm} \\textbf{Awakeness}\n& \\hspace{.1cm} \\textbf{Node-Activation}\n& \\hspace{.3cm} \\textbf{Edge-Activation} \\\\\n\\hline\nLOCAL \n& $\\bullet \\;\\forall \\Pi, \\Pi \\in O(\\log n)$ with \n& $\\bullet \\;\\forall \\Pi, \\Pi \\in O(1)$ with \n& $\\bullet \\; \\forall \\Pi, \\Pi \\in O(1)$ with\\\\\n& $\\;\\; O(\\mbox{poly}(n))$ rounds \\cite{BarenboimM21} \n& $\\;\\; O(\\mbox{poly}(n))$ rounds \n& $\\;\\; O(\\mbox{poly}(n))$ rounds\\\\\n& $\\bullet \\; \\mbox{\\sc st}\\in \\Omega(\\log n)$ \\cite{BarenboimM21} \n& & \\\\\n\\hline \nCONGEST \n& $\\bullet \\; \\mbox{\\sc mis}\\in O(\\mbox{polyloglog}(n))$ \n& $\\bullet \\; \\forall \\Pi, \\Pi\\in O(1)$ \n& $\\bullet \\; \\forall \\Pi, \\Pi \\in O(1)$\\\\\n& \\;\\; with $O(\\mbox{polylog}(n))$ \n& $\\bullet \\;\\mbox{poly}(n)$ rounds \n& $\\bullet \\; \\mbox{poly}(n) $ rounds \\\\\n& \\;\\; rounds \\cite{DufoulonMP22} (randomized)\n& $\\;\\; \\Rightarrow \\exists \\Pi \\in \\Omega(\\mbox{poly}(n)) $ \n& $\\;\\; \\Rightarrow \\exists \\Pi \\in \\Omega(\\mbox{poly}(n)) $ \\\\\n& $\\bullet \\; \\mbox{\\sc mst} \\in O(\\log n)$\n& $\\bullet \\;\\mbox{poly}(n)$ rounds \n& $\\bullet \\;\\mbox{\\sc dfpc}\\in O(1)$ with \\\\\n& \\;\\; with $O(\\mbox{poly}(n))$\n& $\\;\\; \\Rightarrow \\mbox{\\sc dfpc}\\in \\tilde{\\Omega}(n^{1\/4})$\n& $\\; \\; O(\\mbox{poly}(n))$ rounds \\\\\n& \\;\\; rounds \\cite{AugustineMP22}\n&\n& $\\bullet \\;\\Pi\\in \\mbox{FO and}\\; \\Delta=O(1) $\\\\\n&\n&\n& $\\;\\; \\Rightarrow \\Pi\\in O(1) \\; \\mbox{with}$ \\\\\n&\n&\n& $\\;\\; O(\\mbox{poly}(n))$ rounds~\\cite{GrumbachW09} \\\\\n\\hline\n\\end{tabular}\n\\end{center}\n\\caption{\\sl Summary of our results where, for a problem $\\Pi$, $\\Pi\\in O(f(n))$ means that the corresponding complexity of $\\Pi$ is $O(f(n))$ (same shortcut for $\\Omega$).}\n\\label{tab:summary}\n\\end{table}\n\n\\paragraph{Our Techniques.} \n\nOur upper bounds are mostly based on similar types of upper bounds techniques used in the sleeping model~\\cite{BarenboimM21,ChatterjeeGP20} (cf. Section~\\ref{subsec:related-work}), based on constructing spanning trees along with\ngathered and broadcasted information. However, the models considered in this paper do not suffer from the same limitations as the sleeping model (cf. Section~\\ref{sec:preliminaries}), and thus one can achieve activation complexity $O(1)$ in scenarios where the sleeping model limits the awake complexity to $\\Omega(\\log n)$. \n\nOur lower bounds for CONGEST are based on reductions from 2-party communication complexity. However, as opposed to the standard CONGEST model in which the simulation of a distributed algorithm by two players is straightforward (each player performs the rounds sequentially, one by one, and exchanges the messages sent across the cut between the two subsets of nodes handled by the players at each round), the simulation of distributed algorithms in which only subsets of nodes are active at various rounds requires more care. This is especially the case when the simulation must not only control the amount of information exchanged between these players, but also the number of communication steps performed by the two players. Indeed, there are 2-party communication complexity problems that are hard for $k$ steps, but trivial for $k+1$ steps~\\cite{NisanW93}, and some of our lower bounds rely on this fact. \n\n\n\n\\subsection{Related Work}\n\\label{subsec:related-work}\n\nThe study of frugal algorithms has been initiated in~\\cite{GrumbachW09}, which focuses on the edge-frugality in the CONGEST model. It is shown that for {\\emph{bounded-degree graphs}}, any problem expressible in first-order logic (e.g., $C_4$-freeness) can be solved by an edge-frugal algorithm running in $O(\\mbox{poly}(n))$ rounds in the CONGEST model. This also holds for planar graphs with no bounds on the maximum degree, whenever the nodes are provided with their local combinatorial embedding. Our results show that these statements cannot be extended to arbitrary graphs as we prove that any algorithm solving $C_4$-freeness in $O(\\mbox{poly}(n))$ rounds in the CONGEST model has edge-activation $\\tilde{\\Omega}(\\sqrt{n})$. \n\nMore generally, the study of energy-efficient algorithms in the context of distributed computing in networks has been previously considered in the framework of the \\emph{sleeping} model, introduced in~\\cite{ChatterjeeGP20}. This model assumes that nodes can be in two states: \\emph{awake} and \\emph{asleep}. A node in the awake state performs as in the LOCAL and CONGEST models, but may also decide to fall asleep, for a prescribed amount of rounds, controlled by each node, and depending on the algorithm executed at the nodes. A sleeping node is totally inactive in the sense that it does not send messages, it cannot receive messages (i.e., if a message is sent to a sleeping node by an awake neighbor, then the message is lost), and it is computationally idle (apart from counting rounds). The main measure of interest in the sleeping model is the \\emph{awake complexity}, defined as the maximum, taken over all nodes, of the number of rounds at which each node is awake during the execution of the algorithm. \n\nIn the LOCAL model, it is known~\\cite{BarenboimM21} that all problems have awake complexity $O(\\log n)$, using algorithms running in $O(\\mbox{poly}(n))$ rounds. This bound is tight in the sense that there are problems (e.g., spanning tree construction) with awake complexity $\\Omega(\\log n)$ \\cite{BarenboimM21,ChangDHHLP18}. \n\nIn the CONGEST model, It was first shown~\\cite{ChatterjeeGP20} that {\\sc mis} has constant \\emph{average} awake complexity, thanks to a \\emph{randomized} algorithm running in $O(\\mbox{polylog}(n))$ rounds. The round complexity was improved in~\\cite{GhaffariP22} with a \\emph{randomized} algorithm running in $O(\\log n)$ rounds. The (worst-case) awake complexity of {\\sc mis} was proved to be $O(\\log\\log n)$ using a \\emph{randomized} Monte-Carlo algorithm running in $O(\\mbox{poly}(n))$ rounds~\\cite{DufoulonMP22}. This (randomized) round complexity can even be reduced to $O(\\log^3n \\cdot \\log\\log n \\cdot \\log^\\star n)$, to the cost of slightly increasing the awake complexity to $O(\\log\\log n \\cdot \\log^\\star n)$. {\\sc mst} has also been considered, and it was proved~\\cite{AugustineMP22} that its (worst-case) awake complexity is $O(\\log n)$ thanks to a (deterministic) algorithm running in $O(\\mbox{poly}(n))$ rounds. The upper bound on the awake complexity of {\\sc mst} is tight, thank to the lower bound for spanning tree ({\\sc st}) in~\\cite{BarenboimM21}. \n\n\\section{Preliminaries}\n\\label{sec:preliminaries}\n\nIn this section, we illustrate the difference between the standard LOCAL and CONGEST models, their sleeping variants, and our node- and edge-activation variants. Fig.~\\ref{fig:1}(a) displays the automaton corresponding to the behavior of a node in the standard models. A node is either \\emph{active}~(A) or \\emph{terminated}~(T). At each clock tick (i.e., round) a node is subject to message events corresponding to sending and receiving messages to\/from neighbors. A node remains active until it terminates. \n\n\\begin{figure}[!h]\n \\centering\n \\scalebox{0.8}{\n \\input{Figure1.tex}}\n \\caption{(a) Classical model (b) Sleeping model, (c) Activation model. }\n \\label{fig:1}\n\\end{figure}\n\n\nFig.~\\ref{fig:1}(b) displays the automaton corresponding to the behavior of a node in the sleeping variant. In this variant, a node can also be in a \\emph{passive} (P) state. In this state, the clock event can either leave the node passive, or awake the node, which then moves back to the active state. \n\nFinally, Fig.~\\ref{fig:1}(c) displays the automaton corresponding to the behavior of a node in our activation variants. It differs from the sleeping variant in that a passive node is also subject to message events, which can leave the node passive, but may also move the node to the active state. In particular, a node does not need to be active for receiving messages, and incoming messages may not trigger an immediate response from the node (e.g., forwarding information). Instead, a node can remain passive while collecting information from each of its neighbors, and eventually react by becoming active. \n\n\\paragraph{Example 1: Broadcast.} \n\nAssume that one node of the $n$-node cycle~$C_n$ has a token to be broadcast to all the nodes. Initially, all nodes are active. However, all nodes but the one with the token become immediately passive when the clock ticks for entering the second round. The node with the token sends the token to one of its neighbors, and becomes passive at the next clock tick. Upon reception of the token, a passive node becomes active, forwards the token, and terminates. When the source node receives the token back, it becomes active, and terminates. The node-activation complexity of broadcast is therefore~$O(1)$, whereas it is known that broadcasting has awake complexity $\\Omega(\\log n)$ in the sleeping model~\\cite{BarenboimM21}. \n\n\\paragraph{Example 2: At-least-one-leader.} \n\nAssume that each node of the cycle~$C_n$ has an input-bit specifying whether the node is leader or not, and the nodes must collectively check that there is at least one leader. Every leader broadcasts a token, outputs accept, and terminates. Non-leader nodes become passive immediately after the beginning of the algorithm, and start waiting for $N$~rounds (recall that $N$ is an upper bound on the number~$n$ of nodes). Whenever the ``sleep'' of a (passive) non-leader is interrupted by the reception of a token, it becomes active, forwards the token, outputs accept, and terminates. After $N$ rounds, a passive node that has not been ``awaken'' by a token becomes active, outputs reject, and terminates. This guarantees that there is at least one leader if and only if all nodes accept. The node-activation complexity of this algorithm is $O(1)$, while the awake complexity of at-least-one-leader is $\\Omega(\\log n)$ in the sleeping model, by reduction to broadcast. \n\n\\medskip \n\nThe following observation holds for LOCAL and CONGEST, by noticing that every algorithm for the sleeping model can be implemented with no overheads in terms of node-activation. \n\n\n\\begin{observation}\\label{obs:sleep-vs-activation}\nIn $n$-node graphs, every algorithm with awake complexity~$a(n)$ and round complexity~$r(n)$ has node-activation complexity~$a(n)$ and round complexity~$r(n)$. \n\\end{observation}\n\nIt follows from Observation~\\ref{obs:sleep-vs-activation} that all upper bound results for the awake complexity directly transfer to the node-activation complexity. However, as we shall show in this paper, in contrast to the sleeping model in which some problems (e.g., spanning tree) have awake complexity $\\Omega(\\log n)$, even in the LOCAL model, all problems admit a frugal algorithm in the CONGEST model, i.e., an algorithm with node-activation~$O(1)$. \n\n\\begin{definition}\nA LOCAL or CONGEST algorithm is \\emph{node-frugal} (resp., \\emph{edge-frugal}) if the activation of every node (resp., edge) is upper-bounded by a constant independent of the graph, and of the identifiers and inputs given to the nodes. \n\\end{definition}\n\n\\section{Universality of Frugal Algorithms}\n\nIn this section we show that every Turing-computable problem can be solved by frugal algorithms, both in the LOCAL and CONGEST models. Thanks to Eq.~\\ref{eq:ineq-activation}, it is sufficient to prove that this holds for node-frugality.\n\n\\begin{lemma} \\label{lemm:leader}\nThere exists a CONGEST algorithm electing a leader, and constructing a BFS tree rooted at the leader, with node-activation complexity~$O(1)$, and performing in $O(N^2) = O(\\mbox{\\rm poly}(n))$ rounds.\n\\end{lemma}\n\n\\begin{proof}\nThe algorithm elects as leader the node with smallest identifier, and initiates a breadth-first search from that node. At every node~$v$, the protocol performs as follows. \n\n\\begin{itemize}\n\\item If $v$ has received no messages until round $\\mathsf{id}(v) \\cdot N$, then $v$ elects itself as leader, and starts a BFS by sending message $(\\mathsf{id}(v),0)$ to all its neighbors. Locally, $v$~sets its parent in the BFS tree to \\(\\bot\\), and the distance to the root to~$0$.\n\n\\item Otherwise, let $r$ be the first round at which vertex~$v$ receives a message. Such a message is of type $(\\mathsf{id}(u),d)$ where $u$ is the neighbor of $v$ which sent the message to~$v$, and $d$ is the distance from $u$ to the leader in the graph. Node $v$ sets its parent in the BFS tree to $\\mathsf{id}(u)$, its distance to the root to $d+1$, and, at round $r+1$, it sends the message $(\\mathsf{id}(v),d+1)$ to all its neighbors. (If $v$ receives several messages at round~$r$, from different neighbors, then $v$ selects the messages coming from the neighobors with smallest identifier).\n\\end{itemize}\n\nThe node $v$ with smallest identifier is indeed the node initiating the BFS, as the whole BFS is constructed between\nrounds ${\\mathsf{id}(v)\\cdot N}$ and ${\\mathsf{id}(v)\\cdot N + N - 1}$, and $N\\geq n$. The algorithm terminates at round at most~$O(N^2)$. \n\\qed\n\\end{proof}\n\nAn instance of a problem is a triple $(G,\\mathsf{id},x)$ where $G=(V,E)$ is an $n$-node graph, $\\mathsf{id}:V\\to [1,N]$ with $N=O(\\mbox{poly}(n))$, and $x:V\\to [1,\\nu]$ is the input assignment to the nodes. Note that the input range $\\nu$ may depend on~$n$, and even be exponential in~$n$, even for classical problems, e.g., whenever weights assigned to the edges are part of the input. A solution to a graph problem is an output assignment $y:V\\to [1,\\mu]$, and the correctness of~$y$ depends on $G$ and $x$ only, with respect to the specification of the problem. We assume that $\\mu$ and $\\nu$ are initially known to the nodes, as it is the case for, e.g., {\\sc mst}, in which the weights of the edges can be encoded on $O(\\log n)$ bits.\n\n\\begin{theorem}\\label{theo:all-in-LOCAL}\nEvery Turing-computable problem\nhas a LOCAL algorithm with $O(1)$ node-activation complexity, and running in $O(N^2) = O(\\mbox{\\rm poly}(n))$ rounds.\n\\end{theorem}\n\n\\begin{proof}\nOnce the BFS tree~$T$ of Lemma \\ref{lemm:leader} is constructed, the root can (1)~gather the whole instance $(G,\\mathsf{id},x)$, (2)~compute a solution~$y$, and (3)~broadcast~$y$ to all nodes. Specifically, every leaf~$v$ of~$T$ sends the set \n\\[\nE(v)=\\big\\{\\{(\\mathsf{id}(v),x(v)),(\\mathsf{id}(w),x(w))\\}:w\\in N(v)\\big\\}\n\\]\nto its parent in~$T$. An internal node~$v$ waits for receiving a set of edges $S(u)$ from each of its children~$u$ in~$T$, and then forwards the set \n\\[\nS(v)=E(v)\\cup(\\cup_{u\\in \\mbox{\\tiny child}(v)}S(u))\n\\]\nto its parent. Each node of $T$ is activated once during this phase, and thus the node-activation complexity of gathering is~1. Broadcasting the solution~$y$ from the leader to all the nodes is achieved along the edges of~$T$, again with node-activation~1.\n\\qed\n\\end{proof}\n\nThe algorithm used in the proof of Theorem~\\ref{theo:all-in-LOCAL} cannot be implemented in CONGEST due to the size of the messages, which may require each node to be activated more than a constant number of times. To keep the node-activation constant, we increased the round complexity of the algorithm. \n\n\\begin{lemma}\\label{lem:simulation-local-congest}\nEvery node-frugal algorithm $\\mathcal{A}$ performing in $R$ rounds in the LOCAL model with messages of size at most~$M$ bits can be implemented by a node-frugal algorithm $\\mathcal{B}$ performing in $R\\,2^M$ rounds in the CONGEST model.\n\\end{lemma} \n\n\\begin{proof}\nLet $v$ be a node sending a message~$m$ through an incident edge~$e$ at round~$r$ of~$\\mathcal{A}$. Then, in~$\\mathcal{B}$, $v$ sends one ``beep'' through edge~$e$ at round $r\\,2^M+t$ where $t$ is lexicographic rank of $m$ among the at most $2^M$ messages generated by~$\\mathcal{A}$. \n\\qed\n\\end{proof}\n\n\\begin{theorem}\\label{theo:all-in-CONGEST}\nEvery Turing-computable problem\nhas a CONGEST algorithm with $O(1)$ node-activation complexity, and \n running in \n$2^{\\mbox{\\rm\\scriptsize poly}(n)+O((\\nu+\\mu)\\log n)}$ rounds for inputs in the range $[1,\\nu]$ and outputs in the range $[1,\\mu]$. \n\\end{theorem}\n\n\\begin{proof}\nThe algorithm used in the proof of Theorem~\\ref{theo:all-in-LOCAL} used messages of size at most $2N^2+\\nu\\log N$ bits during the gathering phase, and of size at most $\\mu\\log N$ bits during the broadcast phase. The result follows from Lemma~\\ref{lem:simulation-local-congest}.\\qed\n\\end{proof}\n\n\nOf course, there are many problems that can be solved in the CONGEST model by a frugal algorithm much faster than the bound from Theorem~\\ref{theo:all-in-CONGEST}. This is typically the case of all problems that can be solved by a sequential greedy algorithm visiting the nodes in arbitrary order, and producing a solution at the currently visited node based only on the partial solution in the neighborhood of the node. Examples of such problems are {\\sc mis}, $\\Delta + 1$-coloring, etc. We call such problem \\emph{sequential-greedy}. \n\n\\begin{theorem}\nEvery sequential-greedy problem whose solution at every node can be encoded on $O(\\log n)$ bits has a node-frugal CONGEST algorithm running in $O(N) = O({\\mbox{\\rm poly}(n)})$ rounds.\n\\end{theorem}\n\n\\begin{proof}\nEvery node $v \\in V$ generates its output at round~$\\mathsf{id}(v)$ according to its current knowledge about its neighborhood, and sends this output to all its neighbors. \n\\qed\n\\end{proof}\n\n\\section{Limits of CONGEST Algorithms with Polynomially Many Rounds}\n\nGiven a graph \\(G = (V,E)\\) such that \\(V\\) is partitioned in two sets \\(V_A, V_B\\), the set of edges with one endpoint in \\(V_A\\) and the other in \\(V_B\\) is called the \\emph{cut}. We denote by \\(e(V_A,V_B)\\) the number of edges in the cut, and by \\(n(V_A,V_B)\\) the number of nodes incident to an edge of the cut. Consider the situation where there are two players, namely Alice and Bob. We say that a player controls a node \\(v\\) if it knows all its incident edges and its input. For a CONGEST algorithm \\(\\mathcal{A}\\), we denote \\(\\mathcal{A}(\\mathcal{I})\\) the output of \\(\\mathcal{A}\\) on input \\(\\mathcal{I} = (G,\\mathsf{id}, x)\\). We denote \\(R_\\mathcal{A}(n)\\) the round complexity of \\(\\mathcal{A}\\) on inputs of size \\(n\\).\n\n\\begin{lemma}[Simulation lemma]\\label{lem:simu}\n Let \\(\\mathcal{A}\\) be an algorithm in the CONGEST model, let \\(\\mathcal{I} = (G,\\mathsf{id},x)\\) be an input for $\\mathcal{A}$, and let \\(V_A, V_B\\) be a partition of \\(V(G)\\). Suppose that Alice controls all the nodes in \\(V_A\\), and Bob controls all the nodes in \\(V_B\\). Then, there exists a communication protocol \\(\\mathcal{P}\\) between Alice and Bob with at most \\(2\\cdot\\min(n(V_A,V_B)\\cdot \\mathsf{nact}(\\mathcal{A}), e(V_A,V_B)\\cdot \\mathsf{eact}(\\mathcal{A}))\\) rounds and using total communication \\(\\mathcal{O}(\\min(n(V_A,V_B)\\cdot \\mathsf{nact}(\\mathcal{A}), e(V_A,V_B)\\cdot \\mathsf{eact}(\\mathcal{A}))\\cdot \\log n \\cdot \\log(R_{\\mathcal{A}}(n))\\), such that each player computes the value of \\(\\mathcal{A}(\\mathcal{I})\\) at all nodes he or she controls. \n\\end{lemma}\n\n\\begin{proof}\n\n\nIn protocol \\(\\mathcal{P}\\), Alice and Bob simulate the rounds of algorithm \\(\\mathcal{A}\\) in all the nodes they control. The simulation run in phases. Each phase is used to simulate up to a certain number of rounds \\(t\\) of algorithm \\(\\mathcal{A}\\), and takes two rounds of protocol \\(\\mathcal{P}\\) (one round for Alice, and one round for Bob). By simulating \\(\\mathcal{A}\\) up to \\(t\\) rounds, we mean that Alice and Bob know all the states of all the nodes they control, on every round up to round \\(t\\). \n\nIn the first phase, players start simulating \\(\\mathcal{A}\\) from the initial state. Let us suppose that both Alice and Bob have already executed \\(p\\geq 0\\) phases, meaning that they had correctly simulated \\(\\mathcal{A}\\) up to round \\(t = t(p)\\geq 0\\). Let us explain phase \\(p+1\\) (see also Figure~\\ref{fig:simulationphase}). \n\n\n\\begin{figure}[!h]\n \\centering\n \\input{Figure3.tex}\n \\caption{Illustration of one phase of the simulation protocol. Assuming that the players agree on the simulation of algorithm \\(\\mathcal{A}\\) up to round \\(t\\), each player runs an oblivious simulation at the nodes they control. In the example of the figure, the next message corresponds to a node controlled by Bob, who sends a message to a node in \\(V_A\\) at round \\(r_b\\). The oblivious simulation of Alice is not aware of this message, and incorrectly considers that a message is sent from \\(V_A\\) to \\(V_B\\) at round \\(r_a > r_b\\). Using the communication rounds in this phase, the players agree that the message of Bob was correct. Thus the simulation is correct up to round \\(r_b\\), for both players. }\n \\label{fig:simulationphase}\n\\end{figure}\n\n\nStarting from round \\(t\\), Alice runs an \\emph{oblivious simulation} of algorithm \\(\\mathcal{A}\\) over all nodes that she controls. By oblivious, we mean that Alice assumes that no node of \\(V_B\\) communicates a message to a node in \\(V_A\\) in any round at least \\(t\\). The oblivious simulation of Alice stops in one of the following two possible scenarios:\n\n\\begin{itemize}\n\\item[(1)] All nodes that she controls either terminate or enter into a passive state that quits only on an incoming message from \\(V_B\\). \n\\item[(2)] The simulation reaches a round \\(r_a\\) where a message is sent from a node in \\(V_A\\) to a node in \\(V_B\\).\n\\end{itemize}\n\nAt the same time, Bob runs and oblivious simulation of \\(\\mathcal{A}\\) starting from round \\(t\\) (i.e. assuming that no node of \\(V_A\\) sends a message to a node in \\(V_B\\) in any round at least \\(t\\)). The oblivious simulation of Bob stops in one of the same two scenarios analogous to the ones above. In this case, we call \\(r_b\\) the round reached by Bob in his version of scenario~(2). \n\nAt the beginning of a phase, it is the turn of Alice to speak. Once the oblivious simulation of Alice stops, she is ready to send a message to Bob. If the simulation stops in the scenario (1), Alice sends a message \"\\emph{scenario 1}\" to Bob. Otherwise, Alice sends \\(r_a\\) together with all the messages sent from nodes in \\(V_A\\) to nodes in \\(V_B\\) at round \\(r_a\\), to Bob. When Bob receives the message from Alice, one of the following situations holds:\\\\\n\n\\noindent{Case 1:} the oblivious simulation of both Alice and Bob stopped in the first scenario. In this case, since \\(\\mathcal{A}\\) is correct, there are no deadlocks. Therefore, all vertices of \\(G\\) reached a terminal state, meaning that the oblivious simulation of both players was in fact a real simulation of \\(\\mathcal{A}\\), and the obtained states are the output states. Therefore, Bob sends a message to Alice indicating that the simulation is finished, and indeed Alice and Bob have correctly computed the output of \\(\\mathcal{A}\\) for all the nodes they control. \\\\\n\n\\noindent{Case 2:} the oblivious simulation of Alice stopped in scenario (1), and the one of Bob stopped in the scenario (2). In this case, Bob infers that his oblivious simulation was correct. He sends \\(r_b\\) and all the messages communicated in round \\(r_b\\) through the cut to Alice. When Alice receives the message of Bob, she updates the state of the nodes she controls up to round \\(r_b\\). It follows that both players have correctly simulated algorithm \\(\\mathcal{A}\\) up to round \\(r_b > t\\).\\\\ \n\n\\noindent{Case 3:} the oblivious simulation of Alice stopped in scenario (2), and the one of Bob stopped in scenario (1). In this case, Bob infres that the simulation of Alice was correct up to round \\(r_a\\). He sends a message to Alice indicating that she has correctly simulated \\(\\mathcal{A}\\) up to round \\(r_a\\), and he updates the states of all the nodes he controls up to round \\(r_a\\). It follows that both players have correctly simulated \\(\\mathcal{A}\\) up to round \\(r_a > t\\). \\\\\n\n\\noindent{Case 4:} the oblivious simulation of both players stopped in scenario (2), and \\(r_a > r_b\\). Bob infers that his oblivious simulation was correct up to \\(r_b\\), and that the one of Alice was not correct after round \\(r_b\\). Then, the players act in the same way as described in Case 2. Thus, both players have correctly simulated \\(\\mathcal{A}\\) up to round~\\(r_b\\).\\\\\n\n\\noindent{Case 5:} the oblivious simulation of both players stopped in scenario (2), and \\(r_b > r_a\\). Bob infers that his oblivious simulation was incorrect after round \\(r_a\\), and that the one of Alice was correct up to round \\(r_a\\). Then, the players act in the same way as described in Case 3. Thus, both players have correctly simulated \\(\\mathcal{A}\\) up to round~\\(r_a\\). \\\\\n\n\\noindent{Case 6:} the oblivious simulation of both players stopped in scenario (2), and \\(r_b = r_a\\). Bob assumes that both oblivious simulations were correct. He sends \\(r_b\\) together with all the messages communicated from his nodes at round \\(r_b\\) through the cut. Then, he updates the states of all the nodes he controls up to round \\(r_b\\). When Alice receives the message from Bob, she updates the states of the nodes she controls up to round \\(r_b\\).\nIt follows that both players have correctly simulated \\(\\mathcal{A}\\) up to round \\(r_b > t\\). \\\\\n\nObserve that, except when the algorithm terminates, on each phase of the protocol, at least one node controlled by Alice or Bob is activated. Since the number of rounds of \\(\\mathcal{P}\\) is twice the number of phases, we deduce that the total number of rounds is at most\n\\[ 2\\cdot \\min(n(V_A,V_B)\\cdot\\mathsf{nact}(\\mathcal{A}), e(V_A,V_B)\\cdot \\mathsf{eact}(\\mathcal{A})). \\]\nMoreover, on each round of $\\mathcal{P}$, the players communicate \\(O(\\log(R_{\\mathcal{A}}(n)) \\cdot \\log n \\cdot e(V_A,V_B))\\) bits. As a consequence, the total communication cost of $\\mathcal{P}$ is \\[O(\\log(R_{\\mathcal{A}}(n)) \\cdot \\log n \\cdot e(V_A,V_B)) \\cdot \\min(n(V_A,V_B)\\cdot \\mathsf{nact}(\\mathcal{A}), e(V_A,V_B)\\cdot \\mathsf{eact}(\\mathcal{A})) ),\\]\nwhich completes the proof. \\qed \\end{proof}\n\nWe use the simulation lemma to show that there are problems that cannot be solved by a frugal algorithm in a polynomial number of rounds. In problem \\textsc{C4-free\\-ness}{}, all nodes of the input graph $G$ must accept if $G$ has no cycle of 4 vertices, and at least one node must reject if such a cycle exists. Observe that this problem is expressible in first-order logic, in particular it has en edge-frugal algorithm with a polynomial number of rounds in graphs of bounded degree~\\cite{GrumbachW09}. We show that, in graphs of unbounded degree, this does not hold anymore.\nWe shall also consider problem \\textsc{Symmetry}{}, where the input is a graph $G$ with $2n$ nodes indexed from $1$ to $2n$, and with a unique edge $\\{1,n+1\\}$ between $G_A = G[\\{1,\\dots,n\\}]$ and $G_B = G[\\{n+1,\\dots,2n\\}]$. Our lower bounds holds even if every node is identified by its index. All nodes must output \\emph{accept} if the function $f:\\{1,\\dots,n\\} \\to \\{n+1,\\dots,2n\\}$ defined by $f(x)=x+n$ is an isomorphism from $G_A$ to $G_B$, otherwise at least one node must output \\emph{reject}.\n\n The proof of the following theorem is based on classic reductions from communication complexity problems \\textsc{Equality} and \\textsc{Set Disjointness} (see, e.g., \\cite{KushilevitzNisan}), combined with Lemma~\\ref{lem:simu}.\n\n \n\\begin{theorem}\\label{th:limits}\nAny CONGEST algorithm solving \\textsc{Symmetry}{} (resp., \\textsc{C4-free\\-ness}{}) in polynomially many rounds has node-activation and edge-activation at least $\\Omega\\left(\\frac{n^2}{\\log^2 n}\\right)$ (resp., $\\Omega\\left(\\frac{\\sqrt{n}}{\\log^2 n}\\right)$).\n\\end{theorem}\n\n\n\\begin{proof}\nIn problem \\textsc{Equality}, two players Alice and Bob have a boolean vector of size $k$, $x_A$ for Alice and $x_B$ for Bob. Their goal is to answer \\emph{true} if $x_A = x_B$, and \\emph{false} otherwise. The communication complexity of this problem is known to be~$\\Theta(k)$~\\cite{KushilevitzNisan}.\nLet $k = n^2$. We can interpret $x_A$ and $x_B$ as the adjacency matrix of two graphs $G_A$ and $G_B$ in an instance of $\\textsc{Symmetry}$. It is a mere technicality to \"shift\" $G_B$ as if its vertices were indexed from $1$ to~$n$, such that \\textsc{Symmetry}{} is true for $G$ iff $x_A = x_B$. Moreover, Alice can construct $G_A$ from its input $x_A$, and Bob can construct $G_B$ from $x_B$. Both can simulate the unique edge joining the two graphs in $G$. Therefore, by Lemma~\\ref{lem:simu} applied to $G$, if Alice controls the vertices of $G_A$, and Bob controls the vertices of $G_B$, then any CONGEST algorithm $\\mathcal{A}$ solving \\textsc{Symmetry}{} in polynomially many rounds yields a two-party protocol for \\textsc{Equality} on $n^2$ bits. Since graphs $G_A$ and $G_B$ are linked by a unique edge, the total communication of the protocol is $O(\\mathsf{eact}(\\mathcal{A}) \\cdot \\log^2 n)$ and $O(\\mathsf{nact}(\\mathcal{A})\\cdot \\log^2 n)$. The result follows.\n\n\\medskip \n\nIn \\textsc{Set Disjointness}, each of the two players Alice and Bob has a Boolean vector of size $k$, $x_A$ for Alice, and $x_B$ for Bob. Their goal is to answer \\emph{true} if there is no index $i \\in [k]$ such that both $x_A[i]$ and $x_B[i]$ are true (in which case, $x_A$ and $x_B$ are disjoint), and \\emph{false} otherwise. The communication complexity of this problem is known to be~$\\Theta(k)$~\\cite{KushilevitzNisan}.\nWe use the technique in~\\cite{DruckerKO14} to construct an instance $G$ for $C_4$ freeness, with a small cut, from two Boolean vectors $x_A, x_B$ of size $k = \\Theta(n^{3\/2})$. Consider a $C_4$-free $n$-vertex graph~$H$ with a maximum number of edges. Such a graph has $k = \\Theta(n^{3\/2})$ edges, as recalled in~\\cite{DruckerKO14}. We can consider the edges $E(H)$ as indexed from $1$ to~$k$, and $V(H)$ as $[n]$. Let now $x_A$ and $x_B$ be two Boolean vectors of size~$k$. These vectors can be interpreted as edge subsets $E(x_A)$ and $E(x_B)$ of~$H$, in the sense that the edge indexed $i$ in $E(H)$ appears in $E(x_A)$ (resp. $E(x_B)$) iff $x_A[i]$ (resp. $x_B[i]$) is true. Graph $G$ is constructed to have $2n$ vertices, formed by two sub-graphs $G_A = G[\\{1,\\dots, n\\}]$ and $G_B = G[\\{n+1,\\dots, 2n\\}]$. \nThe edges of $E(G_A)$ are exactly the ones of $E(x_A)$. Similarly, the edges of $E(G_B)$ correspond to $E(x_A)$, modulo the fact that the vertex indexes are shifted by~$n$, i.e., for each edge $\\{u,v\\} \\in E(x_B)$, we add edge $\\{u+n,v+n\\}$ to~$G_B$. Moreover we add a perfect matching to $G$, between $V(G_A)$ and $V(G_B)$, by adding all edges $\\{i,i+n\\}$, for all $i \\in [n]$. Note that $G$ is $C_4$-free if and only if vectors $x_A$ and $x_B$ are disjoint. Indeed, since $G_A, G_B$ are isomorphic to sub-graphs of $H$, they are $C_4$-free. Thus any $C_4$ of $G$ must contain two vertices in $G_A$ and two in $G_B$, in which case the corresponding edges in $G_A$ and $G_B$ designate the same bit of $x_A$ and $x_B$ respectively.\nMoreover Alice and Bob can construct $G_A$ and $G_B$, as well as the edges in the matching, from their respective inputs $x_A$ and~$x_B$. Therefore, thanks to Lemma~\\ref{lem:simu}, a CONGEST algorithm $\\mathcal{A}$ for \\textsc{C4-free\\-ness}{} running in a polynomial number of rounds can be used to design a protocol $\\mathcal{P}$ solving \\textsc{Set Disjointness} on $k = \\Theta(n^{3\/2})$ bits, where Alice controls $V(G_A)$ and Bob controls $V(G_B)$. The communication complexity of the protocol is $O(\\mathsf{eact}(\\mathcal{A})\\cdot n\\cdot \\log^2 n)$, and $O(\\mathsf{nact}(\\mathcal{A}) \\cdot n\\cdot \\log^2 n)$, since the cut between $G_A$ and $G_B$ is a matching. The result follows. \n\\qed \n\\end{proof}\n\n\n\\section{Node versus Edge Activation}\n\nIn this section we exhibit a problem that admits an edge-frugal CONGEST algorithm running in a polynomial number of rounds, for which any algorithm running in a polynomial number of rounds has large node-activation complexity.\n\nWe proceed by reduction from a two-party communication complexity problem. However, unlike the previous section, we are now also interested in the number of rounds of the two-party protocols. We consider protocols in which the two players Alice and Bob do not communicate simultaneously. For such a protocol~$\\mathcal{P}$, a \\emph{round} is defined as a maximal contiguous sequence of messages emitted by a same player. We denote by $R(\\mathcal{P})$ the number of rounds of~$\\mathcal{P}$. \n\nLet \\(G\\) be a graph, and \\(S\\) be a subset of nodes of~$G$. We denote by \\(\\partial S\\) the number of vertices in \\(S\\) with a neighbor in \\(V\\setminus S\\). \n\n\\begin{lemma}[Round-Efficient Simulation lemma]\\label{lem:simu2}\n Let \\(\\mathcal{A}\\) be an algorithm in the CONGEST model, let \\(\\mathcal{I} = (G,\\mathsf{id},x)\\) be an input for~$\\mathcal{A}$, and let \\(V_A, V_B\\) be a partition of~\\(V(G)\\). Let us assume that Alice controls all the nodes in~\\(V_A\\), and Bob controls all the nodes in \\(V_B\\), and both players know the value of \\(\\mathsf{nact}(\\mathcal{A})\\). Then, there exists a communication protocol \\(\\mathcal{P}\\) between Alice and Bob such that, in at most \\(\\min(\\partial V_A, \\partial V_B)\\cdot \\mathsf{nact}(\\mathcal{A})\\) rounds, and using total communication \\(O(((\\partial(V_A) + \\partial(V_B)) \\cdot \\mathsf{nact}(\\mathcal{A})))^2 \\cdot \\log n \\cdot \\log R_{\\mathcal{A}}(n)) \\) bits, each player computes the value of \\(\\mathcal{A}(\\mathcal{I})\\) at all the nodes he or she controls. \n\\end{lemma}\n\n\\begin{proof}\nIn protocol \\(\\mathcal{P}\\), Alice and Bob simulate the rounds of algorithm \\(\\mathcal{A}\\) at all the nodes each player controls. Without loss of generality, we assume that algorithm \\(\\mathcal{A}\\) satisfies that the nodes send messages at different rounds, by merely multiplying by \\(N\\) the number of rounds. \n\nInitially, Alice runs a oblivious simulation of \\(\\mathcal{A}\\) that stops when every node in \\(V_A\\) either has terminated, or entered into the passive state that it may leave only after having received a message from a node in~\\(V_B\\) (this corresponds to what we call the first scenario in the proof of Lemma~\\ref{lem:simu}). Then, Alice sends to Bob the integer \\(t_1 = 0\\), and the set \\(M^1_A\\) of all messages sent from nodes in \\(V_A\\) to nodes in \\(V_B\\) in the communication rounds that she simulated, together with their corresponding timestamps. If the number of messages communicated by Alice exceeds \\(\\mathsf{nact}(\\mathcal{A})\\cdot \\partial A\\), we trim the list up to this threshold.\n\nLet us suppose that the protocol \\(\\mathcal{P}\\) has run for \\(p\\) rounds, and let us assume that it is the turn of Bob to speak at round \\(p+1\\) --- the case where Alice speaks at round \\(p+1\\) can be treated in the same way. Moreover, we assume that \\(\\mathcal{P}\\) satisfies the following two conditions:\n\\begin{enumerate}\n\\item At round \\(p\\), Alice sents an integer \\(t_p\\geq 0\\), and a list of timestamped messages \\(M^p_A\\) corresponding to messages sent from nodes in \\(V_A\\) to nodes in \\(V_B\\) in an oblivious simulation of \\(\\mathcal{A}\\) starting from a round \\(t_p\\). \n\\item Bob had correctly simulated \\(\\mathcal{A}\\) at all the nodes he controls, up to round \\(t_p\\). \n\\end{enumerate}\n\n\n\n\\begin{figure}[!h]\n \\centering\n \\input{Figure4.tex}\n \\caption{Illustration of the round-efficient simulation protocol for algorithm \\(\\mathcal{A}\\). After round \\(p\\), Alice has correctly simulated the algorithm up to round \\(t_p\\). It is the turn of Bob to speak in round \\(p+1\\). In round \\(p\\), Alice sent to Bob the set of messages \\(M^p_A\\), obtained from an oblivious simulation of \\(\\mathcal{A}\\) starting from \\(t_p\\). Only the first three messages are correct, since at round \\(t_{p+1}\\) Bob communicates a message to Alice. Then, Bob runs an oblivious simulation of \\(\\mathcal{A}\\) starting from \\(t_{p+1}\\), and communicates all the messages sent from nodes \\(V_B\\) to nodes in \\(V_A\\). In this case the two first messages are correct. }\n \\label{fig:efficientsimulationround}\n\\end{figure}\n\n\nWe now describe round \\(p+1\\) (see also Figure~\\ref{fig:efficientsimulationround}). \nBob initiates a simulation of \\(\\mathcal{A}\\) at all the nodes he controls. However, this simulation is \\emph{not} oblivious. Specifically, Bob simulates \\(\\mathcal{A}\\) from round \\(t_p\\) taking into account all the messages sent from nodes in \\(V_A\\) to nodes in \\(V_B\\), as listed in the messages~\\(M^{p}_A\\). The simulation stops when Bob reaches a round \\(t_{p+1}>t_p\\) at which a node in \\(V_B\\) sends a message to a node in \\(V_A\\). Observe that, up to round \\(t_{p+1}\\), the oblivious simulation of Alice was correct. At this point, Bob initiates an oblivious simulation of \\(\\mathcal{A}\\) at all the nodes he controls, starting from \\(t_{p+1}\\). Finally, Bob sends to Alice \\(t_{p+1}\\), and the list \\(M^{p+1}_B\\) of all timestamped messages sent from nodes in \\(V_B\\) to nodes in \\(V_A\\) resulting from the oblivious simulation of the nodes he controls during rounds at least \\(t_{p+1}\\). Using this information, Alice infers that her simulation was correct up to round \\(t_{p+1}\\), and she starts the next round for protocol~$\\mathcal{P}$. \n\nThe simulation carries on until one of the two players runs an oblivious simulation in which all the nodes he or she controls terminate, and no messages were sent through the cut in at any intermediate round. In this case, this player sends a message \"\\emph{finish}\" to the other player, and both infer that their current simulations are correct. As a consequence, each player has correctly computed the output of \\(\\mathcal{A}\\) at all the nodes he or she controls.\n\nAt every communication round during which Alice speaks, at least one vertex of \\(V_A\\) which has a neighbor in \\(V_B\\) is activated. Therefore, the number of rounds of Alice is at most \\(\\partial V_A \\cdot \\mathsf{nact}(\\mathcal{A})\\). By the same argument, we have that the number of rounds of Bob is at most \\(\\partial V_B \\cdot \\mathsf{nact}(\\mathcal{A})\\). It follows that \n\\[\nR(\\mathcal{P}) = \\min(\\partial V_A,\\partial V_B) \\cdot \\mathsf{nact}(\\mathcal{A}).\n\\]\nAt each communication round, Alice sends at most \\(\\partial(V_A) \\cdot \\mathsf{nact}(\\mathcal{A})\\) timestamped messages, which can be encoded using \\(O(\\partial(V_A) \\cdot \\mathsf{nact}(\\mathcal{A})) \\cdot \\log n \\cdot \\log R_{\\mathcal{A}}(n)) \\) bits. Similarly, Bob sends \\(O(\\partial(V_B) \\cdot \\mathsf{nact}(\\mathcal{A})) \\cdot \\log n \\cdot \\log R_{\\mathcal{A}}(n)) \\) bits. It follows that\n\\[\nC(\\mathcal{P}) = O(((\\partial(V_A) + \\partial(V_B)) \\cdot \\mathsf{nact}(\\mathcal{A})))^2 \\cdot \\log n \\cdot \\log R_{\\mathcal{A}}(n)),\n\\]\nwhich completes the proof. \n\\qed\n\\end{proof}\n\nIn order to separate the node-activation complexity from the edge-activation complexity, we consider a problem called \\textsc{Depth First Pointer Chasing}, and we show that this problem can be solved by an edge-frugal CONGEST algorithm running in $O(\\mbox{poly}(n))$ rounds, whereas the node-activation complexity of any algorithm running in $O(\\mbox{poly}(n))$ rounds for this problem is $\\Omega(\\Delta)$, for any $\\Delta \\in O(\\frac{\\sqrt{n}}{\\log n})$. The lower bound is proved thanks to the Round-Efficient Simulation Lemma (Lemma~\\ref{lem:simu}), by reduction from the two-party communication complexity problem \\textsc{Pointer Chasing}{}, for which too few rounds imply large communication complexity~\\cite{NisanW93}.\n\nIn the \\textsc{Depth First Pointer Chasing}, each node $v$ of the graph is given as input its index $\\mbox{DFS}(v)\\in [n]$ in a depth-first search ordering (as usual we denote $[n]=\\{1,\\dots,n\\}$). Moreover the vertex indexed~$i$ is given a function $f_i:[n] \\to [n]$, and the root (i.e., the node indexed~1) is given a value $x \\in [n]$ as part of its input. The goal is to compute the value of $f_n \\circ f_{n-1} \\circ \\dots \\circ f_1(x)$ at the root. \n\n\\begin{lemma}\\label{lem:algoforDFPC}\nThere exists an edge-frugal CONGEST algorithm for problem \\textsc{Depth First Pointer Chasing}, with polynomial number of rounds.\n\\end{lemma}\n\n\n\\begin{proof}\nThe lemma is established using an algorithm that essentially traverses the DFS tree encoded by the indices of the nodes, and performs the due partial computation of the function at every node, that is, the node with index~$i$ computes $f_i \\circ f_{i-1} \\dots f_1 (x)$, and forwards the result to the node with index~$i+1$.\n\nAt round 1, each node $v$ transmits its depth-first search index $\\mbox{DFS}(v)$ to its neighbors. Therefore, after this round, every node knows its parent, and its children in the DFS tree. Then the algorithm merely forwards messages of type $m(i) = f_i \\circ f_{i-1} \\dots f_1 (x)$, corresponding to iterated computations for increasing values~$i$, along the DFS tree, using the DFS ordering. That is, for any node $v$, let $\\mbox{MaxDFS}(v)$ denote the maximum DFS index appearing in the subtree of the DFS tree rooted at $v$. We will not explicitly compute this quantity but it will ease the notations. At some round, vertex $v$ of DFS index $i$ will receive a message $m(i-1)$ from its parent (of index $i-1$). Then node $v$ will be in charge of computing message $m(\\mbox{MaxDFS}(v))$, by ``calling'' its children in the tree, and sending this message back to its parent. In this process, each edge in the subtree rooted at $v$ is activated twice.\n\nThe vertex of DFS index~1 initiates the process at round~2, sending $f_1(x)$ to its child of DFS index~$2$. Any other node~$v$ waits until it receives a message from its parent, at a round that we denote~$r(v)$. This message is precisely $m(i-1) = f_{i-1} \\circ f_{i-2} \\dots f_1 (x)$, for $i = \\mbox{DFS}(v)$. Then $v$ computes message \n$m(i) = f_{i} \\circ f_{i-1} \\dots f_1 (x)$ using its local function $f_i$. If it has no children, then it sends this message $m(i)$ to its parent at round $r(v)+1$. Assume now that $v$ has $j$ children in the DFS tree, denoted $u_1,u_2,\\dots,u_j$, sorted by increasing DFS index. Observe that, by definition of DFS trees, $\\mbox{DFS}(u_k) = \\mbox{MaxDFS}(u_{k-1})+1$ for each $k \\in \\{2,\\dots,j\\}$. \nNode~$v$ will be activated $j$ times, once for each edge $\\{v,u_k\\}$, $1 \\leq k \\leq j$, as follows. \nAt round $r(v)+1$ (right after receiving the message from its parent), $v$~sends message $m(i)$ to its child $u_1$, then it awaits until round $r^1(v)$ when it gets back a message from $u_1$. \n\nThe process is repeated for $k=2,\\dots,j$: at round $r^{k-1}(v)+1$, node $v$ sends the message $m(\\mbox{DFS}(u_{k})-1)$ received from $u_{k-1}$ to $u_k$, and waits until it gets back a message from $u_k$, at round $r^k(v)$. Note that if $k$ wafer) by co-evaporation of iron from an electron beam source and germanium from an effusion cell in a chamber with base pressure below $8 \\times 10^{-9}$ Torr. \nGrowth rates were monitored using separate quartz crystal microbalances and were, for each deposition, maintained at a constant value between $0.23$ \\AA\/s and $0.27$ \\AA\/s. Immediately following film growth, a capping layer (3-5 nm thickness) which prevents sample oxidation was deposited \\emph{in situ} by sublimation of Al$_2$O$_3$ from an electron beam source.\n\n\n\nFilm thickness was measured in a KLA-Tencor Alpha-Step IQ surface profiler. Compositions and atomic number densities were determined from Rutherford backscattering spectra measured at the Pelletron at Lawrence Berkeley National Laboratory; a spectrum corresponding to each measurement was simulated and iterated to fit the measured spectrum to obtain the sample composition and density. \nSample amorphicity was verified using x-ray and electron diffraction [Fig.~\\ref{fStruct}(a)], while high-resolution energy dispersive X-ray spectrometry [Fig.~\\ref{fStruct}(b) and (c)] demonstrates the films' nanoscale elemental homogeneity. \nTaken together, these data rule out the possibility of precipitation, percolation, or nanocrystallization of the \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace films.\nFurthermore, the amorphous quality of \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace films grown by identical techniques has been previously shown using high-resolution cross-sectional transmission electron microscopy.~\\cite{Gray2011} \nGiven that silicon and germanium are both well-known glass formers, it is unsurprising that both \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace and \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace readily condense into an amorphous phase in the studied range of $x$.\n\n\nMagnetization and magnetoelectrical transport were measured in a Quantum Design Magnetic Property Measurement System (MPMS XL) equipped with a 7 T superconducting magnet. The reciprocating sample option (RSO) was used for all magnetization measurements, with four distinct SQUID voltage curves averaged for each magnetic moment data point. To isolate the magnetic signal from the film, a diamagnetic background due to the substrate was calculated from the sample mass, measured in a microbalance, and substrate susceptibility, known from previous magnetization measurements of virgin substrates. This calculated background was used to verify the accuracy of a linear fit to the high-field regions of a $T = 300$ K $M(H)$ measurement on each sample, and a straight line with the slope of this fit was subtracted from the total measured magnetization. \n\nLongitudinal and transverse resistivities were obtained using the van der Pauw method,~\\cite{VanderPauw1958} in which each rectangular film (side length $3-5$ mm) is mounted onto a specialized MPMS sample rod, with four evenly spaced pointlike (diameter $< 0.5$ mm) electrical contacts attached to the film perimeter by indium soldering. Individual four-point resistances used to calculate the film resistivity were measured using standard AC lock-in techniques, with currents of amplitude $2\\; \\mu$A and frequency 16 Hz. The transverse and longitudinal resistivities were then calculated following the procedures detailed by van der Pauw, with the aid of a numerical solver to find roots of the transcendental equation defining the longitudinal resistivity.\n\n\\subsection{Density Functional Theory Calculations}\nDensity functional theory (DFT) calculations were performed using the projector augmented wave (PAW) method~\\cite{Blochl1994, Kresse1999} and a plane wave basis set, as implemented in the Vienna \\textit{ab initio} simulation package (VASP);~\\cite{Kresse1993, Kresse1996} an energy cutoff of 350 eV was used for the plane wave basis expansion.\nThe exchange-correlation interactions were described by the generalized-gradient approximation (GGA) with the Perdew-Burke-Ernzerhof (PBE) functional,~\\cite{Perdew1996} taking spin polarization into account.\nTwo separate sets of amorphous Fe$_x$Ge$_{1-x}$ structures were simulated, with one set using a 64-atom supercell (with 29, 31, 35, and 39 Fe atoms) and the other using a 128-atom supercell (with 58, 61, 69, and 78 Fe atoms), corresponding to $x \\simeq 0.45$, 0.48, 0.54, and 0.61, matching the experimental compositions. The similarity of the results of these calculations indicates that both supercell sizes capture the patterns of amorphous systems. \n\nFor each value of $x$ and each supercell size, 20 different independent amorphous structures were simulated using \\textit{ab initio} molecular dynamics (AIMD).\nInitial configurations were created by randomly substituting Fe and Ge atoms onto zincblende crystal structure sites. \nTo randomize the atomic structural positions, the systems underwent a melting step (2000 K for the 64-atom systems; 3000 K followed by a 4 ps anneal to ensure a fully molten state for the 128-atom systems) and a quenching step (2000 K to 200 K at $3 \\times 10^{14}$ K\/s for the 64-atom systems; 3000 K to 300 K at $4.5 \\times 10^{14}$ K\/s for the 128-atom systems); the 64-atom systems underwent a subsequent annealing step (200 K for 4.5 ps) in a canonical ensemble. \nThe structures were then further relaxed using the conjugate gradient method until the forces on each atom were less than 0.01 eV\/\\AA. Only the $\\Gamma$-point was used to sample the Brillouin zone during the melting, quenching, and annealing processes; however, a $3 \\times 3 \\times 3$ Monkhorst-Pack (MP) $k$-point mesh was used for the atomic geometry relaxation of all structures. \nThis mesh was also used for the 128-atom electronic structure calculation, while the 64-atom electronic structure calculation employed a $6 \\times 6 \\times 6$ MP $k$-point mesh.\n\n\n\\begin{figure}\n \\includegraphics{Fig1_20191005.pdf}\n \\caption{$M(H)$ curves for films with $0.38 \\leq x \\leq 0.61$ measured at $T = 2$ K with $H$ parallel to the film plane. A temperature independent diamagnetic background corresponding to the combined magnetization of each sample's substrate and capping layer as measured at $T=300$ K has been subtracted from each measurement. Inset: expanded view of the $M(H)$ curves with $x < 0.50$, each normalized to its saturation magnetization as defined in the text and overlaid with Brillouin functions corresponding to $S = 3\/2$ and $S = 1\/2$. Data points are connected as a guide to the eye.}\n \\label{f1}\n\\end{figure}\n\n\n\\section{Results}\n\\subsection{Magnetization}\n\nExperimental magnetization curves at $T = 2$ K with the applied field $H$ in the plane of the film are shown in Fig.~\\ref{f1} for \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace with $x=0.38$, 0.45, 0.48, 0.54, and 0.61. \nWhile the M(H) curves for $x > 0.50$ primarily exhibit a squareness and absence of hysteresis associated with an otherwise unremarkable soft ferromagnet, we note the curvature at $H < 2500$~Oe. For lower $x$ ($x = 0.48$ and 0.45) this curvature is dramatically exaggerated and the curve takes on an S-shape while also developing a small hysteresis at low fields. \nThe low-$H$ curvature at high $x$ and S-shaped curves at lower $x$ hint at non-collinear spin textures in \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace ($0.45 \\leq x \\leq 0.61$). Such spin textures have since been observed directly in this system via resonant X-ray scattering and Lorentz transmission electron microscopy; detailed results will be reported elsewhere.~\\cite{Chen2019,Streubel2019}\n\n\n\n\\begin{figure}\n \\includegraphics{Fig2ab_withDFT_natomic_20190429.pdf}\n \\caption{Comparison of magnetic and structural properties of \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace (blue symbols) and \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace (green symbols) indicates that both materials exhibit a Stoner model-type itinerant ferromagnetism. The purple $\\mathbf{\\times}$ marks $T = 5$ K measurements of B20 FeGe for comparison. (a) Magnetization per Fe atom (filled circles) increases roughly linearly as a function of Fe concentration $x$ for both \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace and \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace. MD-DFT calculations of \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace using a 64-atom supercell (open blue squares) yield the same values of $M_S$ as those using a 128-atom supercell (open blue diamonds); these are discussed further in the text. (b) Total atomic number density increases slightly with $x$; solid lines are linear fits to experimental data and dotted lines are extrapolations of those fits shown as guides to the eye. \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace MD-DFT calculations and $T = 2$ K experimental data are from Ref.~\\citenum{Karel2014a}, and $T = 5$ K B20 FeGe experimental data is from Ref.~\\citenum{Gallagher2016a}.}\n \\label{f2}\n\\end{figure}\n\n\nAlthough the $M(H)$ loops for \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace are qualitatively similar to \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace~\\cite{Karel2016} for the same $x$, the volume magnetization is slightly greater in \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace and the S-shape of the magnetization in the low-$x$ samples is exaggerated, indicating a more complex spin structure in \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace that persists to higher fields.\nThe measured and calculated values of the $T=2$~K saturation magnetization per Fe atom of \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace and \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace are compared quantitatively in Fig.~\\ref{f2}(a), where the data and calculations for \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace are from Ref.~\\citenum{Karel2014a}. \nThe \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace saturation magnetization was obtained for high $x$ (reasonably square loops in Fig.~\\ref{f1}) by extrapolating the $M(H)$ curve for $H \\geq 4$ T to $H = 0$; this extrapolation yields almost exactly $M_S = M(H = 5\\mathrm{\\,T})$ so the $H = 5$ T value of $M$ was chosen as $M_S$ for the low $x$ measurements (S-shaped loops in Fig.~\\ref{f1}). \nThe enhanced $M_S$ in \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace compared to \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace is supported by the presence of sharper peaks in the calculated spin-resolved density of states in \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace, which will be further discussed later in the paper.\n\n\n\\begin{figure*}\n \\includegraphics{rhoOfT_and_sigma0_20191005.pdf}\n \\caption{Longitudinal charge transport properties of \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace (blue lines and hexagons), shown with \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace data from Ref.~\\citenum{Karel2016} (green triangles) for comparison. (a) Longitudinal resistivity $\\rho_{xx}$ as a function of temperature $T$ exhibits a negative temperature coefficient of resistance for all compositions $x$, and decreases with increasing $x$ at all $T$. Individual data points are too closely spaced to be distinguishable, so a solid line is shown instead. (b) Residual longitudinal conductivity $\\sigma_{xx,0}$ measured at $T = 4 \\,\\mathrm{K}$ as a function of Fe concentration $x$ for \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace (solid blue hexagons) and \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace (solid green triangles). Spline fits to the data (dashed lines) are shown as a guide to the eye. (c) Carrier concentration $n_h$ obtained from Hall effect measurements at $T = 2$ K for \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace (open blue hexagons) and \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace (open green triangles). Spline fits to the data (dashed lines) are shown as a guide to the eye. }\n \\label{fRho}\n\\end{figure*}\n\n\\begin{figure}\n \\includegraphics{MR_allX_20191005.pdf}\n \\caption{Normalized magnetoresistance with $H$ oriented out of the film plane for \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace. Data is symmetrized according to $\\rho(H) = \\frac{1}{2}[\\rho(+H) + \\rho(-H)]$ to remove contact asymmetry effects; data points are connected as a guide to the eye. Poor signal-to-noise is a side effect of the measurement geometry, which was chosen to optimize the Hall voltage signal. (a) Composition dependence of magnetoresistance at $T = 2$ K shows stronger negative magnetoresistance for lower $x$. (b) Temperature dependence of magnetoresistance for $x = 0.48$ shows negative magnetoresistance to $T = 40$ K, disappearing by $T = 80$ K.}\n \\label{fMR}\n\\end{figure}\n\n\nFig.~\\ref{f2}(b) shows measured and calculated values of the atomic number density $n_{\\mathrm{total}}$\\xspace for \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace and \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace; $n_{\\mathrm{total}}$\\xspace for crystalline B20 FeGe is also shown for comparison. \nThe increased size of the Ge atom compared to the Si atom is responsible for the 15-20\\% reduction in $n_{\\mathrm{total}}$\\xspace of \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace compared to that of \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace.\nSince Fe structures itself more compactly than either Si or Ge, $n_{\\mathrm{total}}$\\xspace unsurprisingly increases with increasing $x$ for both systems; DFT calculations reproduce this trend in good qualitative agreement with experiment for both \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace and \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace. \nCursory extrapolations of the measured trend indicate that, for this $x$ regime, $n_{\\mathrm{total}}$\\xspace for both systems approaches the atomic number density of bulk Fe ($n_{\\mathrm{Fe}}$, orange arrow on right vertical axis) as $x$ approaches 1. \nHowever, neither extrapolation recovers its group IV element atomic number density (arrows on left vertical axis: green for $n_{\\mathrm{Si}}$ and blue for $n_{\\mathrm{Ge}}$) as $x$ approaches 0, suggesting the existence of one or more polyamorphous transitions in both systems.\n\n\n\n\n\n\n\\subsection{Magnetotransport}\nLongitudinal charge transport measurements are shown in Figs.~\\ref{fRho} and~\\ref{fMR}, while transverse measurements are shown in Fig.~\\ref{f3}; we first examine the $H = 0$ longitudinal transport properties. \nFig.~\\ref{fRho}(a) shows the temperature dependence of the longitudinal resistivity $\\rho_{xx}$, or simply $\\rho$, for \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace with $0.40 \\leq x \\leq 0.65$, with higher $x$ values in darker colors (solid lines are shown because the individual data points are too closely spaced to be distinguishable). \nThe temperature dependence of $\\rho$ for each $x$ is relatively weak compared to the composition dependence of $\\rho$ across the range of $x$ studied. \nBoth the weak temperature dependence of the resistivity and the negative sign of the temperature coefficient of resistance $\\alpha$ ($\\alpha \\equiv \\rho^{-1} \\, \\partial \\rho \/ \\partial T$) are consistent with the temperature-independent scattering length $\\ell \\sim a$ of an amorphous metal (where $a$ is the average interatomic spacing); this temperature-independent $\\ell$ leads to the condition $\\rho \\gtrsim 150 \\, \\mu\\Omega\\cdot\\mathrm{cm}$ for amorphous metals, which is apparent in our measurements. \nThe systematic increase in $\\rho$ with decreasing $x$ reflects the decrease in carrier concentration with decreasing $x$, which will be further discussed next.\n\n\\begin{figure}\n \\includegraphics{Fig3_20191005.pdf}\n \\caption{Measured Hall resistivity $\\rho_{xy}$ as a function of applied magnetic field at $T = 2 \\mathrm{K}$ for various Fe concentrations $x$ of \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace shows a dominant anomalous Hall effect with a very large magnitude for all $x$. Inset: normalized anomalous Hall resistivity $\\rho_{xy}^{\\mathrm{AH}} (H) \\equiv \\rho_{xy} (H) - R_0 H$ (green) overlaid with normalized measured magnetization (orange), showing excellent agreement and further corroborating the weak ferromagnetism in the $x=0.45$ and $0.48$ films. Data points are connected as a guide to the eye.}\n \\label{f3}\n\\end{figure}\n\n\nFig.~\\ref{fRho}(b) shows the residual conductivity $\\sigma_{xx,0}(T = 4\\,\\mathrm{K})$ while Fig.~\\ref{fRho}(c) shows the carrier concentration for \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace compared to \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace (\\textit{a}-Fe$_x$Si$_{1-x}$\\xspace data from Ref.~\\citenum{Karel2016}).\nThe carrier concentration was obtained from magnetotransport measurements carried out at $T = 2$ K (Fig.~\\ref{f3}) with the samples set up in the van der Pauw geometry. \nThe anomalous Hall effect dominates $\\rho_{xy}$ for all four samples; the additional positive slope due to the ordinary Hall effect (indicative of hole carriers) is apparent for the $x=0.45$ and $0.48$ samples, but is hardly visible at higher $x$ so the density of holes $n_h$ was extracted from $\\rho_{xy}(H)$ by iteratively fitting the parameters $R_0$ and $R_S$ to Eq.~\\ref{eqHall} in Python, using measured $M_z(H)$ data for each sample. \n$R_0$ is related to the carrier concentration by $|R_0| = (ne)^{-1}$, where $n$ is the carrier concentration and $e$ is the electronic charge; our fits yield the values of hole concentration $n_h$ shown by open blue hexagons in Fig.~\\ref{fRho}(c). \nComparing our results to the measured (for $0.43 \\leq x \\leq 0.48)$ and extrapolated (for $x > 0.48$) values of $n_h$ for \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace (open green triangles) confirms that the higher carrier concentration in \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace is responsible for its higher $\\sigma_{xx,0}$ for any $x$, represented by filled blue hexagons in Fig.~\\ref{fRho}(b), compared to \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace (filled green triangles).\n\nThe magnetoresistance (MR) ratio, defined as $\\mathrm{MR}(H) \\equiv [\\rho(H) - \\rho(0)]\/\\rho(0)$, was also measured for \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace and is shown in Fig.~\\ref{fMR}(a) at $T = 2$ K with $H$ oriented perpendicular to the film plane. \nAs expected for ferromagnets, the MR is negative,~\\cite{Spaldin2010} and the weakly ferromagnetic $x = 0.45$ and 0.48 samples show a larger negative magnetoresistance due to increased suppression of spin-disorder scattering by an applied magnetic field. \nFig.~\\ref{fMR}(b) shows that, in contrast to the positive MR of \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace for $T \\geq 16$ K,~\\cite{Karel2016} this significantly enhanced negative contribution to the MR of \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace dominates up to temperatures between 40 K and 80 K, resulting in a net negative MR for $x = 0.48$ over a wide temperature range.\nWe note that, while still small, the magnitude of the $T = 2$ K MR in \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace is more than 200 times greater than the effect measured in the same geometry (H perpendicular to the film and therefore also perpendicular to the current) in \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace for comparable Fe concentrations, despite similar $M(H)$. \nSince we have shown our samples to be structurally and chemically homogeneous (Fig.~\\ref{fStruct}), we attribute this enhanced negative MR in \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace both to a stronger coupling between carriers and local moments and to a greater reduction in the disorder seen by the carriers. \nThe latter effect reinforces our observation, based on the $M(H)$ curves, that \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace hosts a more complicated spin texture than \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace. \n\n\n\n\n\n\n \n \n \n \n \n\n\n\nWe isolate the anomalous component of the Hall resistivity by subtracting the OHE from the total $\\rho_{xy}$, and show the result for $x=0.45$ in the inset to Fig.~\\ref{f3} normalized by its $H=5$ T value and overlaid with the correspondingly normalized $M_z(H)$ to emphasize the unmistakable magnetic origin of this Hall signal, even in our most weakly ferromagnetic sample. \nThis inset also exemplifies the absence of additional measurable contributions to the Hall effect, such as a topological Hall effect that has been observed in several systems as a consequence of the adiabatic change in the carrier phase by a noncollinear spin texture. \nWhile the samples shown here likely host local noncollinear spin textures due to the Dzyaloshinskii-Moriya interaction in the Fe-Ge system, the absence of global chirality in the amorphous structure reduces any net signal from localized topological contributions to the Hall resistivity below the sensitivity of our setup. \n\n\n\\begin{figure}\n \\includegraphics{Fig4_20190614.pdf}\n \\caption{Scaling plot of the anomalous Hall conductivity $\\sigma_{xy}^{\\mathrm{AH}}$ reveals the origin of the anomalous Hall effect in \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace and \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace across different regimes of longitudinal conductivity $\\sigma_{xx}$. (a) Normalizing $\\sigma_{xy}^{\\mathrm{AH}}$ by the saturation magnetization $M_z$ yields a power law dependence that deviates from the empirical $\\sigma_{xy}^{\\mathrm{AH}} \\sim \\sigma_{xx}^{1.6-1.8}$. (b) Normalizing further by a free-electron-type dependence on the carrier concentration, $n_h^{2\/3}$, yields an essentially constant value for both \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace and \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace. Dashed lines are average values of $\\sigma_{xy}^{\\mathrm{AH}}\/(M_z n_h^{2\/3})$ for \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace (blue) and \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace (green). Amorphous and epitaxial Fe-Si data from Ref.~\\citenum{Karel2016}; B20 FeGe data from Ref.~\\citenum{Gallagher2016a}.}\n \\label{f4}\n\\end{figure}\n\n\n\n\n\n\n\\section{Discussion}\n\\subsection{Magnetization}\nThe onset of magnetic order at $T = 2$ K in \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace occurs between $x = 0.45$ and $x = 0.38$, in agreement with previous work.~\\cite{Suran1976} The inset of Fig.~\\ref{f1} confirms this by comparing the magnetization of the $x = 0.38,\\,0.45,$ and $0.48$ films to Brillouin functions of ideal paramagnets with $S = 1\/2$ and $S = 3\/2$; the paramagnetic $x=0.38$ curve falls squarely between the Brillouin functions while no single Brillouin function adequately models both the low- and high-field behavior of the $x=0.45$ and $x=0.48$ curves. The steep slope and finite hysteresis of their magnetization at low fields suggests ferromagnetism, but the magnetization continues to increase without saturating to fields above $H = 7$ T, leading to the conclusion that \\textit{a}-Fe$_{0.45}$Ge$_{0.55}$ and \\textit{a}-Fe$_{0.48}$Ge$_{0.52}$ are only weakly ferromagnetic.\nNotably, the Ising model from which the Brillouin functions arise does not capture the profusion of spin textures that form across the crystalline Fe-Ge system thanks to the competition between Heisenberg and DM interactions in different lattice configurations, and the non-square features of the hysteresis loops noted previously indicate that this competition persists in \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace.\n\nFor both \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace and \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace, the magnetization per Fe atom increases with increasing Fe concentration $x$; however, for any given $x$, \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace has a significantly higher magnetization per Fe atom than \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace, despite having only slightly higher magnetization per unit volume, due to the different atomic densities of these two alloys at all $x$ [Fig.~\\ref{f2}(b)]. \nIn contrast to the Fe-Si system, in which the magnetization of the crystalline phase is an order of magnitude (or more) less than than that of \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace,~\\cite{Karel2014a} the measured magnetization per Fe atom of B20 FeGe at $T = 5$ K from Ref.~\\citenum{Gallagher2016a} aligns very well with our experimental data for \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace; taken together with existing evidence that the local atomic environment strongly influences the magnetic state of amorphous transition metal germanides and silicides, this suggests that the local atomic environment in our amorphous films resembles that of B20 FeGe.\nThe DFT calculations of magnetization in \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace~\\cite{Karel2014a} and \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace [open diamonds and squares in Fig.~\\ref{f2}(a)] reproduce this experimental trend as well as the relative values of $M$ between both systems, but yield excellent quantitative agreement with experiment only in \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace. \nThe discrepancy between calculated and measured magnetization in \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace is likely due to a noncollinear spin texture, which suppresses the net magnetization and is not computationally taken into account because of the difficulty of calculating the spin texture of an amorphous system using DFT. \n\n\\begin{figure}\n \\includegraphics{DoScomparison_20191005.pdf}\n \\caption{Calculated density of states (DOS) near the Fermi level for the compositions $x$ of \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace studied experimentally (blue curves), and for \\textit{a}-Fe$_{0.65}$Si$_{0.35}$ (green dashed curve, from Ref.~\\citenum{Karel2014a}), all based on a 128-atom unit cell. The peaks of the majority spin in the DOS are narrowed and sharpened by substituting the larger Ge atom for the Si atom for a fixed $x$, as can be seen from comparing the DOS of \\textit{a}-Fe$_{0.65}$Si$_{0.35}$ to that of \\textit{a}-Fe$_{0.61}$Ge$_{0.39}$, explaining the enhanced magnetization in \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace.}\n \\label{fDoS}\n\\end{figure}\n\n\n\nThe increased size of the Ge atom relative to the Si atom enhances the magnetization of \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace relative to \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace [Fig.~\\ref{f2}(a)].\nA local-moment picture does not fully capture the physics in these systems, so we turn to the calculated densities of states (DOS) of \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace ($0.45 \\leq x \\leq 0.61$)and a-Fe$_{0.65}$Si$_{0.35}$~\\cite{Karel2014a} shown in Fig.~\\ref{fDoS} for a more complete explanation of the role of Ge and Si atomic size. \nIntuitively, substituting the larger, isoelectronic Ge atom for Si in a \\emph{crystalline} system will increase the lattice constant, shrink the Brillouin zone, and compress the energy bands in $\\vec{k}$-space, thereby narrowing and sharpening the features in the density of states . \nFor our \\emph{amorphous} systems, $\\vec{k}$ is no longer a good quantum number so Brillouin zones and energy bands are not meaningful; however, the average interatomic spacing and the density of states make no reference to $\\vec{k}$ and so provide a meaningful extension of our crystalline intuition into amorphous systems.\nThe reduced atomic number density corresponds to an increased average interatomic spacing in \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace compared to \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace. \nThis leads to a sharper DOS peak and a stronger spin split near the Fermi level, as shown in Fig.~\\ref{fDoS}, which explains the enhanced magnetization, as well as its pronounced $x$-dependence, in \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace when considered in the framework of a simple Stoner band model of itinerant ferromagnetism.~\\cite{Stoner1938} We therefore conclude that the scattering from the disorder associated with the amorphous structure is sufficiently weak that it does not substantially redistribute the majority and minority DOS of the Fe-$3d$ electrons, so the exchange interaction remains strong enough to spin-split the density of states and yield a net magnetization.\n\nFurthermore, the density of states in Fig.~\\ref{fDoS} allows us to approximate the spin polarization in \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace; for example, we count states at the Fermi energy $\\varepsilon_F$ for \\textit{a}-Fe$_{0.61}$Ge$_{0.39}$ and estimate a 37\\% spin polarization, nearly identical to the calculated spin polarization for \\textit{a}-Fe$_{0.65}$Si$_{0.35}$.~\\cite{Karel2014a} \nThe low-temperature spin polarization of \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace with $0.58 \\leq x \\leq 0.68$ has been measured using point-contact Andreev reflection spectroscopy and was found to peak at almost 70\\% for $x = 0.65$,~\\cite{Karel2018} roughly double the prediction from the calculated DOS; this discrepancy was there attributed to the small size of the supercell used in the calculations. The result in \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace leads us to suspect a similarly large spin polarization exists in \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace.\n\n\\subsection{Anomalous Hall Effect}\nThese films fall at the high conductivity edge of the low conductivity regime, with $10^3 < \\sigma_{xx} < 10^4 \\,(\\mathrm{\\Omega\\; cm})^{-1}$ and finite $\\rho_{xx}$ as $T \\to 0$, so hopping conduction does not apply. To apply a standard empirical scaling argument to the AHC in \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace, an appropriate normalization is essential; we consider two factors to enable comparison of our results to the scaling of the AHC in \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace.~\\cite{Karel2016}\nFirst, in changing the Fe concentration $x$, $M_z$ is also modified. \nSince $\\sigma_{xy}^{\\mathrm{AH}} \\propto \\rho_{xy}^{\\mathrm{AH}} \\propto M_z$, changing $x$ alters $\\sigma_{xy}^{\\mathrm{AH}}$ directly due to the dependence on $M_z$; we remove this dependence by dividing $\\sigma_{xy}^{\\mathrm{AH}}$ by $M_z$ and obtain the data shown in Fig.~\\ref{f4}(a).\nThese data can be fit by $\\sigma_{xy}^{\\mathrm{AH}} \\propto \\sigma_{xx}^{1.1}$, similar to what was obtained for \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace but inconsistent with the theoretical predictions of Onoda~\\cite{Onoda2006} and Liu.~\\cite{Liu2011} \nAdditionally, since the unified theory is expressed in terms of the carrier lifetime $\\tau$ and not the conductivity $\\sigma_{xx}$, we must account for the effect of changing $x$ on $\\tau$. Hence, we consider a simple free-electron-type model which gives $n_h^{2\/3}$ as our second normalization factor, using the values of $n_h$ shown in Fig.~\\ref{fRho}(b). This normalization yields the scaling plot in Fig.~\\ref{f4}(b), in which $\\sigma_{xy}^{\\mathrm{AH}}\/M_z n_h^{2\/3}$ is essentially independent of $\\sigma_{xx}$. Both scaling plots in Fig.~\\ref{f4} also show the appropriately normalized anomalous Hall conductivity in \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace from Ref.~\\citenum{Karel2016} as a point of comparison; we attribute the quantitative similarity in the normalized AHC of \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace and \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace to the spin-orbit coupling introduced near $\\varepsilon_F$ by the Fe $d$-states in both systems, since the spin-orbit coupling due to the Ge (or Si) $p$-states is diluted over a wider energy range.\n\n\\begin{figure}\n \\includegraphics{AnomalousHallConductivity_theoryVsExp_20190429.pdf}\n \\caption{Comparison of calculated \\emph{intrinsic} anomalous Hall conductivity from 128-atom MD-DFT (turquoise diamonds) to experimentally measured \\emph{total} anomalous Hall conductivity (blue dots). The main axis shows the AHC normalized by the saturation magnetization $M_z$, where experimental values have been normalized by the experimentally measured $M_z$ and theoretical values have been normalized by the theoretically calculated $M_z$ for consistency. Unnormalized values of the measured total and calculated intrinsic AHC are shown in the inset. Spline fits to data (dashed lines) are shown as a guide to the eye.}\n \\label{f:AHCtheoryexpt}\n\\end{figure}\n\nThe fact that $\\sigma_{xy}^{\\mathrm{AH}}\/M_z n_h^{2\/3}$ is independent of $\\sigma_{xx}$ implies that either the side-jump or the intrinsic mechanism, or some combination of the two, is responsible for the anomalous Hall conductivity. \nIn the case of \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace, these two contributions were qualitatively deconvolved by comparison to measurements on crystalline Fe$_x$Si$_{1-x}$, which were compared to calculations of the intrinsic and side-jump mechanisms in the AHC of bcc Fe.~\\cite{Karel2016} \nTo more rigorously separate the contributions of these two mechanisms in \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace, we compare \\textit{ab initio} values of the \\textit{intrinsic} anomalous Hall conductivity calculated from our spin-orbit-coupled 128-atom MD-DFT, which are normalized by the calculated magnetization and shown in Fig.~\\ref{f:AHCtheoryexpt}, to experimental values of the \\textit{total} anomalous Hall conductivity, normalized by the measured magnetization; this comparison shows excellent agreement in the trend of the calculated and experimental values, suggesting that the measured AHC consists of a large intrinsic component, which varies with composition and is partially offset by a composition-independent side-jump component. \nWhile the intrinsic AHC is generally expressed as the integral of the Berry curvature taken over all occupied bands, this result independently verifies the outcome of our scaling argument and unambiguously shows that the intrinsic mechanism persists in systems whose band structure is ill-defined, further validating the real-space formulation of the AHC in Ref.~\\citenum{Marrazzo2017a}. \n\n\n\\begin{figure}\n \\centering\n \\includegraphics{DensityOfCurvature_1005.pdf}\n \\caption{Density of Berry curvature as a function of chemical potential calculated from 128-atom MD-DFT for \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace with $x = 0.45$, 0.48, 0.54 and 0.61. }\n \\label{f:DOC}\n\\end{figure}\n\nOur spin-orbit coupled DFT calculations provide computational foundations and a theoretical paradigm shift for understanding the \\emph{intrinsic} anomalous Hall conductivity in an amorphous material. The intrinsic AHC is the integral over occupied states of the Berry curvature; however, as $\\vec{k}$ is not a good quantum number in an amorphous system, expressing the Berry curvature as $\\Omega(\\vec{k})$ is meaningless here.\nInstead, we construct a framework appropriate to our system based on the \\textit{density of Berry curvature}:~\\cite{Guo2008, Sahin2015}\n\\begin{equation}\n \\rho_{\\mathrm{DOC}}(\\varepsilon) = \\sum_{\\vec{k}}^{} \\Omega(\\vec{k}) \\delta(\\varepsilon_{\\vec{k}} - \\varepsilon)\n\\end{equation}\nwhich corresponds to the Berry curvature within an energy range bounded by $\\varepsilon$ and $\\varepsilon + d\\varepsilon$ integrated throughout the Brillouin zone. \nThis can, in principle, be computed in an amorphous material without reference to $\\vec{k}$-space by adding together the partial densities of states for local orbital states with spin-orbit correlation parallel and antiparallel, which are energetically offset by the self-consistently determined exchange energy.\nIf the energy scales of the disorder potentials that scatter states from momentum $\\vec{k}$ to $\\vec{k}'$ are relatively weak compared to the energy scale spanned by the features in $\\rho_{\\mathrm{DOC}}(\\varepsilon)$, then the density of Berry curvature would be approximately preserved even as momentum fails to remain a good quantum number in an amorphous system.\n\nFig.~\\ref{f:DOC} shows the density of Berry curvature as a function of chemical potential for the compositions $x$ of \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace studied in this work; integrating the density of curvature over occupied energy states yields the intrinsic AHC shown in Fig.~\\ref{f:AHCtheoryexpt}, in the same way that integrating the spin-resolved density of states over occupied energy states yields the magnetization.\nFig.~\\ref{f:DOC} further indicates that the energy scale of the density of Berry curvature is on the order of 5 eV, an energy scale set in part by the spin-orbit interaction-induced splitting of parallel and antiparallel spin-orbit correlated states and in part by the exchange energy in our system. \nAs long as the disorder potentials are typically smaller than 5 eV our conclusions about the AHC would remain similar in both the clean and disordered systems; otherwise, the spin-orbit correlations that give rise to the AHC would be lost.\nThis energy scale lends confidence that the calculated density of curvature, which imposes an artificial periodicity on the simulated 128-atom amorphous supercell, is a suitable approximation for that of the fully amorphous material: the similarity between the simulated and measured atomic number densities [Fig.~\\ref{f2}(b)] indicates that the supercell accurately reproduces the structural disorder, and hence the disorder potentials, of the actual amorphous structure.\n\n \n \n \n \n\n\n\n\n\n\n\\section{Conclusion}\nIn summary, we presented experimental and computational studies of the magnetic and transport properties of amorphous Fe$_x$Ge$_{1-x}$ ($0.45 \\leq x \\leq 0.61$) thin films, including the first measurement of the anomalous Hall effect in \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace. \nIts magnetization is well explained by a Stoner band model above the onset of magnetic order around $x=0.4$, with the larger Ge atom distorting the density of states and causing enhanced magnetization at all $x$ in \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace compared to \\textit{a}-Fe$_x$Si$_{1-x}$\\xspace.\nThe resistivity of \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace agrees with established work on amorphous metals, and indicates that a metal-insulator transition occurs at lower $x$ than the onset of ferromagnetism. \nThe anomalous Hall conductivity of \\textit{a}-Fe$_x$Ge$_{1-x}$\\xspace is independent of the longitudinal conductivity when appropriately normalized by $M_z n_h^{2\/3}$ to account for the role of changing the Fe concentration on the magnetization and carrier lifetime; our DFT calculations refine this scaling argument and indicate the AHC is comprised of a dominant intrinsic component whose magnitude is influenced by the Fe concentration, and of an opposing composition-independent side-jump component.\nThe calculated density of Berry curvature shows that the AHC in this amorphous material is indeed intrinsic; moreover, because the density of curvature can be calculated from either the spin-orbit correlations of local orbital states in a disordered material or the band structure in a crystalline one, it provides a novel and versatile Stoner-esque model for understanding the electronic origins of the intrinsic AHC in systems possessing and lacking long-range order.\nSince the spin and orbital Hall conductivities arise from mathematically analogous Berry curvature-like quantities, we anticipate that the straightforward extension of this model to those phenomena will spur experimental investigation of the spin and orbital Hall effects in amorphous materials, portending future application of such materials as spin and orbital torque generators in next-generation devices.\n\n\\begin{acknowledgements}\nThe authors thank C. \\c{S}ahin, J. Karel, S. Mack, and N. D. Reynolds for illuminating discussions.\nThis work was primarily funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Materials Sciences and Engineering Division under Contract No. DE-AC02-05-CH11231 (NEMM program MSMAG). \nWork for 128-atom DFT calculations was supported by DOE-BES (Grant No. DE-FG02-05-ER46237). Additionally, BHZ acknowledges support from the Basic Research Program of China (2015CB921400).\nSupport for the density of Berry curvature framework for the AHC was provided by the Center for Emergent Materials, an NSF MRSEC under Award No. DMR-1420451.\n\\end{acknowledgements}\n\n\n","meta":{"redpajama_set_name":"RedPajamaArXiv"}} +{"text":"\\chapter{\\LARGE #1}}\n\\newcommand{\\middle}[1]{\\raisebox{1.5ex}[0pt]{#1}}\n\\newcommand{\\eqn}[1]{equation \\ref{eqn:#1}}\n\\newcommand{\\fig}[1]{figure \\ref{fig:#1}}\n\\newcommand{\\tab}[1]{table \\ref{tab:#1}}\n\\newcommand{\\Eqn}[1]{Equation \\ref{eqn:#1}}\n\\newcommand{\\Fig}[1]{Figure \\ref{fig:#1}}\n\\newcommand{\\Tab}[1]{Table \\ref{tab:#1}}\n\\newcommand{\\begin{center}}{\\begin{center}}\n\\newcommand{\\end{center}}{\\end{center}}\n\n\\newcommand{S_g\\left[U\\right]}{S_g\\left[U\\right]}\n\\newcommand{\\bar{\\psi}}{\\bar{\\psi}}\n\\newcommand{\\bar{\\eta}}{\\bar{\\eta}}\n\\newcommand{\\mathcal{U}}{\\mathcal{U}}\n\\newcommand{D\\!\\!\\!\\!\/}{D\\!\\!\\!\\!\/}\n\\newcommand{Z_V^{\\rm eff}}{Z_V^{\\rm eff}}\n\\newcommand{Z_A^{\\rm eff}}{Z_A^{\\rm eff}}\n\\newcommand{\\mathcal{D}}{\\mathcal{D}}\n\\newcommand{\\mathcal{O}}{\\mathcal{O}}\n\\newcommand{\\mathrm{Tr}}{\\mathrm{Tr}}\n\\newcommand{\\pme}[2]{{}^{+#1}_{-#2}}\n\\newcommand{\\lambda_{\\rm min}}{\\lambda_{\\rm min}}\n\n\\font\\tenmsb=msbm10 scaled\\magstep1\n\\font\\sevenmsb=msbm7 scaled\\magstep1\n\\font\\fivemsb=msbm5 scaled\\magstep1\n\\newfam\\msbfam\n\\textfont\\msbfam=\\tenmsb\n\\scriptfont\\msbfam=\\sevenmsb\n\\scriptscriptfont\\msbfam=\\fivemsb\n\\def\\fam\\msbfam\\tenmsb{\\fam\\msbfam\\tenmsb}\n\\def\\Bbb#1{{\\fam\\msbfam\\relax#1}}\n\\newcommand{\\Bbb{R}}{\\Bbb{R}}\n\\newcommand{\\Bbb{C}}{\\Bbb{C}}\n\\newcommand{\\Bbb{Z}}{\\Bbb{Z}}\n\\newcommand{\\Bbb{I}}{\\Bbb{I}}\n\\newcommand{Bhattacharya \\emph{ et al.} }{Bhattacharya \\emph{ et al.} }\n\n\\newcommand{\\spprop}[4]{G^{#1}(#2^{#4},#3^{#4};U^{#4})}\n\\newcommand{\\fprop}[3]{\\left \\langle 0 \\left | \\psi^{#1}(#2;U) \\bar{\\psi}^{#1} (#3;U) \\right | 0 \\right \\rangle}\n\\newcommand{\\order}[1]{{\\mathcal O}(#1)}\n\\newcommand{\\cl}[1]{\\mathcal{#1}}\n\\newcommand{\\BF}[1]{\\mathbf{#1}}\n\\newcommand{\\Lslash}[1]{#1\\!\\!\\!\\!\\!\\;\\slash}\n\\newcommand{\\lslash}[1]{#1\\!\\!\\!\\!\\;\\slash}\n\\newcommand{\\fp}[1]{f^{#1}_+(q^2)}\n\\newcommand{\\fz}[1]{f^{#1}_0(q^2)}\n\\newcommand{f_1(v\\cdot k)}{f_1(v\\cdot k)}\n\\newcommand{f_2(v\\cdot k)}{f_2(v\\cdot k)}\n\\newcommand{v\\cdot k}{v\\cdot k}\n\\newcommand{v_A \\cdot p_B}{v_A \\cdot p_B}\n\\newcommand{\\Delta_{m^2}}{\\Delta_{m^2}}\n\\newcommand{\\bra}[1]{\\Big\\langle#1\\Big |}\n\\newcommand{\\ket}[1]{\\Big |#1\\Big\\rangle}\n\\newcommand{\\kappa_{\\rm crit}}{\\kappa_{\\rm crit}}\n\\newcommand{\\kappa^{\\rm sea}}{\\kappa^{\\rm sea}}\n\\newcommand{\\kappa^{\\rm val}}{\\kappa^{\\rm val}}\n\\newcommand{V_{\\rm ub}}{V_{\\rm ub}}\n\\newcommand{f_B\/f_{\\pi}}{f_B\/f_{\\pi}}\n\\newcommand{\\delt}[1]{\\Delta_t^{(#1)}}\n\\newcommand{v^\\prime}{v^\\prime}\n\\newcommand{\\bar{B}}{\\bar{B}}\n\\newcommand{\\Bmix}[1]{B_{#1}-\\bar{B}_{#1}}\n\\newcommand{\\Vab}[1]{V_{\\rm #1}}\n\\newcommand{\\overline{\\rm MS}}{\\overline{\\rm MS}}\n\\newcommand{\\err}[2]{{}^{+#1}_{-#2}}\n\\newcommand{\\rm MeV}{\\rm MeV}\n\\newcommand{\\rm nlo}{\\rm nlo}\n\\newcommand{q^2_{\\rm max}}{q^2_{\\rm max}}\n\\newcommand{m_{\\rm res}}{m_{\\rm res}}\n\\newenvironment{my_theorem}{\\begin{quote}\\itshape}{\\end{quote}}\n\n\n\n\n\n\n\n\n\n\n\n\\usepackage{epsfig}\n\n\\title{Baryons in 2+1 flavour domain wall QCD}\n\\author{\nD.J.~Antonio, K.C.~Bowler, P.A.~Boyle, M.A.~Clark, B.~Jo\\'o,\nA.D.~Kennedy, R.D.~Kenway, \\speaker{C.M.~Maynard}, R.J.~Tweedie.\n\t\\\\School of Physics, University of Edinburgh, Edinburgh, EH9 3JZ, UK.\\\\ \n\tE-mail: \\\\ \\email{$\\ \\ $s0459477@sms.ed.ac.uk}, \n\t\t\\\\ \\email{$\\ \\ $kcb@ph.ed.ac.uk}, \n\t\t\\\\ \\email{$\\ \\ $paboyle@ph.ed.ac.uk},\n\t\t\\\\ \\email{$\\ \\ $mike@ph.ed.ac.uk},\n\t\t\\\\ \\email{$\\ \\ $bj@ph.ed.ac.uk},\n\t\t\\\\ \\email{$\\ \\ $adk@ph.ed.ac.uk},\n\t\t\\\\ \\email{$\\ \\ $r.d.kenway@ed.ac.uk},\n\t\t\\\\ \\email{$\\ \\ $cmaynard@ph.ed.ac.uk},\n\t\t\\\\ \\email{$\\ \\ $rjt@ph.ed.ac.uk}}\n\\author{A.~Yamaguchi\\\\Department of Physics and Astronomy, University of Glasgow, Glasgow, G12 8QQ, UK.\\\\\n\t\tE-mail: \\\\\\email{$\\ \\ $a.yamaguchi@physics.gla.ac.uk}}\n\\author{RBC and UKQCD Collaborations}\n\\abstract{\nWe present results for some of the light baryon masses and their\nexcited states in 2+1 flavour domain wall QCD. We considered\nseveral lattice spacings, with the DBW2 and Iwasaki gauge actions and\ndifferent sea quark masses on a volume of $16^3\\times32$ and a fifth\ndimension of size 8. All data were generated on the QCDOC machines.\nDespite large residual massses and a limited number of sea quark mass\nvalues with which to perform chiral extrapolations, our results are in\nreasonable agreement with experiment and scale within errors. Finite size\neffects on most ensembles appear to be small.\n}\n\n\\PoS{PoS(LAT2005)098}\n\\ShortTitle{Baryons in 2+1 flavour domain wall QCD}\n\\FullConference{XXIIIrd International Symposium on Lattice Field Theory\n\\\\Trinity College, Dublin, Ireland\\\\25-30 July 2005}\n\\begin{document}\n\n\n\n\n\n\n\\section{Introduction}\nThe calculation of many quantities from lattice QCD with quenched, or\nheavy dynamical, quarks has produced results which, although in\nqualitative agreement with experiment, have uncontrolled sources of\nerror. To progress beyond this, calculations with light dynamical\nquarks are necessary. Using fermions which satisfy the Ginsparg-Wilson\n(GW) relation is advantageous, as the theory is well defined within\nbroad parameter ranges. It has lattice versions of the symmetries of\ncontinuum QCD, and the correct flavour content. Mixing of operators\nwith different chirality is suppressed, renormalisation is simplified,\nand a continuum-like chiral perturbation theory can be used for the\nextrapolation of quantities to the chiral limit. Domain wall fermions\n(DWF) satisfy these requirements. The QCDOC machine and the RHMC\nalgorithm have allowed for the first time calculations using DWF with\n$2+1$ flavours of dynamical quarks.\n\nBaryon physics is an area rich in\nphenomenology. Unanswered questions as to the nature of some of the\nexcited states, the decay of the proton predicted by some Grand\nUnified and super~symmetric models, and the determination of \nmatrix elements related to the structure functions and the neutron electric\ndipole moment can, in principle, be determined by lattice QCD\ncalculations. These calculations are very computationally challenging,\nas they need both light sea quarks and large volumes, as well as fermions\nwith the correct symmetry properties. In this work we report on a study\nof the lowest lying states in the baryon spectrum, $\\{N , \\Delta ,\n\\Omega , N^{\\star}\\}$, on ensembles of configurations produced by\nQCDOC. It is important for any calculation claiming to be ``full QCD''\nto be able to reproduce this spectrum. These initial ensembles were\nproduced primarily for a search of parameter space to guide larger\nproduction runs. As such, they have a small volume, too small\ncertainly for excited states such as the $N^{\\star}$, but this can be\nused, eventually in combination with the productions runs on larger\nvolumes to try and estimate the size of the finite volume effects on\nthe remaining spectrum.\n\nThe DWF action is given in~\\cite{Furman:1994ky} with\nthe Pauli-Villars field in~\\cite{Vranas:1997da} for the dynamical\nsimulation. The gauge fields were generated with renormalisation group\n(RG) improved actions, as follows:\n\\begin{equation}\n S_G=-\\frac{\\beta}{3}\\left[ (1-8) c_1 \\sum_{x,\\mu\\nu} P(x)_{\\mu\\nu} +\n c_1 \\sum_{x,\\mu\\neq\\nu} R(x)_{\\mu\\nu}\\right]\n\\end{equation}\nwith either $c_1=-1.4069$ for the DBW2 action~\\cite{deForcrand:1999bi}\nor $c_1=-0.331$ for the Iwasaki action~\\cite{Iwasaki:1984cj}. It has\nbeen noted in the quenched DWF calculations~\\cite{Blum:2000kn} that\nthese actions reduce the chiral symmetry breaking resulting from the\nfinite fifth dimension. The mechanism and size of chiral symmetry\nbreaking on these ensembles is studied in detail in~\\cite{PeterBoyle}.\n\nIn the DWF formalism, the 4D quark fields are constructed\nfrom left and right projections of the 5D fermion fields\non the boundaries. With a finite fifth dimension, there is still\nan overlap between these left- and right-handed fields, which manifests\nitself as an additive mass renormalisation, known as the residual mass.\nThis can be determined directly from the axial Ward-Takahashi identity\n\\begin{eqnarray}\n \\partial_\\mu A_\\mu(x)& = & 2am_fP(x)+ 2 J_5(x)\\\\\\nonumber\n & \\approx & 2 (am_f + am_{\\rm res})P(x)\n\\end{eqnarray}\nwhere $J_5(x)$ is the point-split current constructed from fields at the \nmid-point of the fifth dimension and $P(x)$ the pseudoscalar density.\n\n\n\\section{Details of the calculation}\nThe ensembles were all generated on QCDOC machines, using the exact\nRHMC algorithm~\\cite{Kennedy:1998cu,MikeClark}, with a volume of\n$16^3\\times32$ and a fifth dimension of size $L_S=8$ and are detailed in\nTable~\\ref{tab:Ensembles}. The integrated autocorrelation times are\nestimated to be $\\order{50}$ for mesonic correlators. To maximise\nstatistics, the correlation functions were measured every 5\ntrajectories, and then binned so that the separation between\nindependent measurements is 100 trajectories. The correlators were\ncomputed from up to four sources on different time-planes with as many as\nthree different smeared sources.\n\n\\begin{table}\n\\begin{center}\n\\begin{tabular}{cccccccc}\n$\\beta$ & $am_l\/am_s$ & $r_0\/a$ & $a^{-1}$(GeV) & $L$(fm) & $Lm_P$ & $m_P\/m_V$ & $\\#$traj \\\\\\hline\n$0.72$ & 0.04\/0.04 & & & & $7.7(1)$ & $0.692(5)$ & 3400\\\\\n$0.72$ & 0.02\/0.04 & \\raisebox{1.5ex}[0pt]{$4.3(1)$} &\\raisebox{1.5ex}[0pt]{$1.7(1)$} & \\raisebox{1.5ex}[0pt]{$1.9(1)$} & $6.0(1)$ & $0.589(3)$ & 6000 \\\\\\hline\n$0.764$ & 0.04\/0.04 & & & &$6.7(1)$ & $0.699(4)$ & 5750\\\\\n$0.764$ & 0.02\/0.04 & \\raisebox{1.5ex}[0pt]{$5.1(2)$} &\\raisebox{1.5ex}[0pt]{$2.0(1)$} & \\raisebox{1.5ex}[0pt]{$1.6(1)$} & $5.1(1)$ & $0.619(4)$ & 3000 \\\\\\hline\n$2.13$ & 0.04\/0.04 & & & & $7.5(1)$ & $0.700(8)$ & 3600\\\\\n$2.13$ & 0.02\/0.04 & \\raisebox{1.5ex}[0pt]{$4.6(2)$} &\\raisebox{1.5ex}[0pt]{$1.8(1)$} & \\raisebox{1.5ex}[0pt]{$1.8(1)$} & $5.8(1)$ & $0.615(5)$ & 3600 \\\\\\hline\n$2.2$ & 0.04\/0.04 & & & & $6.8(1)$ & $0.726(2)$ & 4500\\\\\n$2.2$ & 0.02\/0.04 & \\raisebox{1.5ex}[0pt]{$5.3(1)$} &\\raisebox{1.5ex}[0pt]{$2.1(1)$} & \\raisebox{1.5ex}[0pt]{$1.5(1)$}& $5.1(1)$ & $0.667(8)$ & 3200 \\\\\\hline\n\\end{tabular}\n\\caption{Properties of the ensembles used in this study. The value of $r_0\/a$ was determined in~\\cite{KoichiHashimoto}.\nThe lattice spacing, and thus the volume are set by choosing $r_0=0.5$fm. Trajectories are of length 0.5}\n\\label{tab:Ensembles}\n\\end{center}\n\\end{table}\n\nThe masses of the pseudoscalar and vector mesons were determined by simultaneous\nfits to the local and smeared correlators with two exponentials, the ground state and the\nexcited state. Similarly $m_{\\rm res}$ was determined by a simultaneous fit of a plateau to \na ratio of correlators, with both smeared and local sources.\n\nThe standard baryon interpolating operator is given by\n\\begin{equation}\n \\Omega(x)=\\epsilon_{ijk}\\left[\\psi_i(x) C \\Gamma \\psi_j(x)\\right]\\psi_k(x)\n\\end{equation}\nFor the $I=\\{\\frac{1}{2},\\frac{3}{2}\\}$ baryons,\n$\\Gamma=\\{\\gamma_5,\\gamma_5\\gamma_k\\}$. Another operator, which\nprojects onto the negative parity $I=\\frac{1}{2}$ state, with\n$\\Gamma=1$ was also used. For baryon correlators in a finite box\nwith periodic boundary conditions, the backward propagating state is\nthe negative parity partner, that is\n\\begin{equation}\n C_B(t) = A_+e^{-m_+t} + A_-e^{-m_-(T-t)}\n \\label{eqn:baryonCorr}\n\\end{equation}\nFor the $I=\\frac{1}{2}$ baryon, the masses of the positive and negative\nparity states were determined by a simultaneous fit to equation\n(\\ref{eqn:baryonCorr}) using the standard operator, and a single\nexponential to the negative parity correlator. This is shown in\nFigure~\\ref{fig:effMass}(a). Typically this was computed for the\nsmeared correlator only, as the local correlator had a poor\nsignal. \n\nThe mass of the $I=\\frac{3}{2}$ baryon was determined from a single\nexponential fit to the smeared correlator, as the signal for the\nexcited, negative parity partner was poor, as might be expected on\nrelatively small numbers of configurations.\n\n\\begin{figure}\n\\begin{center}\n \\epsfig{file=Nstar_m0.02.eps,height=0.49\\textwidth,width=0.49\\textwidth}\n \\epsfig{file=EdinburghPlot.eps,height=0.49\\textwidth,width=0.49\\textwidth}\n \\caption{(a) The effective mass of $I=\\frac{1}{2}$ baryon correlator on the DBW2\n $\\beta=0.72$, $am_l\/am_s=0.02\/0.04$ ensemble. The red symbol shows\n the data for the positive parity state, the closed blue squares are\n the time-reversed backward propagating negative parity state data and\n the open blue squares are the negative parity data from the second correlator.\n (b) The Edinburgh plot for the different ensembles.}\n \\label{fig:effMass}\n\\end{center}\n\\end{figure}\n\n\\section{Preliminary Results}\nShown in Figure~\\ref{fig:effMass}(b) is the Edinburgh plot. It is\nreassuring that, even at relatively coarse lattice spacing, with a\nsmall fifth dimension and consequently moderate chiral\nsymmetry breaking, the data follows the phenomenological curve very well. \nThe only exception is the lightest Iwasaki $\\beta=2.2$ datum. Naively, one\nmight expect this to be a finite size effect, especially, examining \nTable~\\ref{tab:Ensembles}, given that the lattice spacing\nand thus the box size are rather small. However, the value of $Lm_P$ is not\nsignificantly smaller than the other data sets and, critically, $Lm_P>4$, suggesting\nthat the box is big enough as measured by the pseudoscalar meson. \n\nFor this particular ensemble the signal for the vector meson mass is\nnot good. In particular, the effective mass plot has a poor plateau,\nand a stable fit can only be achieved for the lowest region. The net\neffect is for a rather low vector meson mass. It is probable that this\nis due simply to low statistics. A low estimate of the vector mass\nwould cause this datum in the Edinburgh plot to be shifted up and to the\nright, which could be mistaken for a finite volume effect increasing\nthe mass of the nucleon.\n\nThe quark mass was defined as\n\\begin{equation}\n am_q=am_f + am_{\\rm res}(m_f)\n\\end{equation}\nwith the chiral limit at $am_q=0$. With two sea quark masses,\nonly a crude chiral extrapolation could be attempted, {\\em i.e.} drawing a\nstraight line through the two data points. The strange quark mass, (for the\n$\\Omega$ baryon) was set from the kaon mass.\n\n\\begin{figure}\n\\begin{center}\n \\epsfig{file=scaling.eps,height=0.49\\textwidth,width=0.49\\textwidth}\n \\caption{Scaling of the baryon spectrum with lattice spacing squared.\n\t The symbols denote the following: Closed circles $N$, open circles\n\t $N^{\\star}$, squares $\\Delta$, diamonds $\\Omega$. Black symbols denote\n experiment, red DBW2 ensembles, blue Iwasaki ensembles.\n\t The value of $r_0=0.5$fm was chosen, to give an indication of \n\t the experimental spectrum in these units. The $N^{\\star}$ measured\n\t on the $\\beta=2.13$ ensemble (the furthest right open blue circle) has\n\t been offset to the left for clarity.}\n \\label{fig:Scaling}\n\\end{center}\n\\end{figure}\n\nShown in Figure~\\ref{fig:Scaling} is the dependence of the baryon\nspectrum, in dimensionless units, on the lattice spacing. A continuum\nextrapolation cannot be attempted with these ensembles. However, the\ndata for the ground states, $\\{N,\\Delta ,\\Omega\\}$, shows reasonable\nscaling, albeit with large errors. These large uncertainties are due\nto the crude nature of the chiral extrapolation. The determination of\n$r_0$ is well defined for each ensemble, and thus it is a good\nquantity to use to examine scaling behaviour. As the value of $r_0$ in\nthe continuum is unknown, rather than setting the absolute scale with\n$r_0$, a better strategy is to predict dimensionless ratios of\nphysical quantities in the continuum, while using $r_0$ to just\nexamine the scaling behaviour.\n\nThe negative parity partner of the nucleon, the $N^\\star$ is expected\nto become degenerate with the nucleon in a small enough box. This\neffect can be clearly seen from Figure~\\ref{fig:Scaling}; the\n$N^\\star$ mass drops dramatically as the volume is reduced. This\nsuggests that finite size effects may also be beginning to affect the\nground states for the ensembles at finest lattice spacing. These\nfinite size effects would tend increase the mass of the ground\nstates. The slight upward tendancy in the scaling plot as the lattice\nspacing decreases is consistent with the finite size effects spoiling\notherwise very good scaling, or a small scaling violation for the\nnucleon mass.\n\n\\section{Conclusions}\nWe have determined the spectrum of the lowest lying baryon states for several\nensembles with two different gauge actions. The QCDOC machines and the RHMC algorithm\nhave made $2+1$ flavours of DWF ensembles possible for the first time. With limited\nstatistics, and only two different sea quark masses, we qualitatively reproduce the\nexperimental spectrum. There is limited evidence that finite size effects may be \ninfluencing the ground state baryons on the smaller volumes. Both the\nEdinburgh plot, and the scaling analysis suggest that a programme of baryon\nphysics on larger volumes and at lighter quark mass will yield very interesting\nresults.\n\n\\section{Acknowledgements}\nWe thank Saul Cohen, Sam Li and Meifeng Lin for help generating the datasets used\nin this work. We thank Dong Chen, Norman Christ, Saul Cohen, Calin\nCristian, Zhihua Dong, Alan Gara, Andrew Jackson, Chulwoo Jung,\nChanghoan Kim, Ludmila Levkova, Xiaodong Liao, Guofeng Liu, Robert\nMawhinney, Shigemi Ohta, Konstantin Petrov and Tilo Wettig for\ndeveloping with us the QCDOC machine and its software. This development\n and the resulting computer equipment used in this calculation were funded\n by the U.S. DOE grant DE-FG02-92ER40699, PPARC JIF grant PPA\/J\/S\/1998\/00756\n and by RIKEN. This work was supported by PPARC grant PPA\/G\/O\/2002\/00465.\n\n\n\\providecommand{\\href}[2]{#2}\\begingroup\\raggedright","meta":{"redpajama_set_name":"RedPajamaArXiv"}} diff --git a/data_all_eng_slimpj/shuffled/split2/finalzzabzr b/data_all_eng_slimpj/shuffled/split2/finalzzabzr new file mode 100644 index 0000000000000000000000000000000000000000..52652a42b5d80d18636f98391f4471c347789fda --- /dev/null +++ b/data_all_eng_slimpj/shuffled/split2/finalzzabzr @@ -0,0 +1,5 @@ +{"text":"\\section{Introduction} \\label{Introduction}\n\nSolar flares have been studied in detail both observationally and theoretically ever since their discovery by \\citet{Ca859}. Although increasingly more sophisticated instrumentation provides ever more detailed data, we still lack the basic understanding of many processes at work in a solar flare. \n\nThe common flare picture as deduced from hard X-ray (HXR) observations features an HXR source in the corona~\\citep[coronal or loop-top source,][]{Fr71,Hu78}, and two or more HXR sources (footpoints) in the chromosphere \\citep{Hoy81}. These sources are thought to be due to bremsstrahlung emission produced by fast electrons accelerated somewhere above the loop. If we assume that a single particle beam creates both coronal and footpoint emission, the most basic model would involve thin target emission at the top of the coronal loop and thick target emission from the footpoints, which both produce characteristic spectra. \n\\citet{Wh95} developed a more sophisticated model (intermediate thin-thick target or ITTT model) to fit observations by Yohkoh. They based their model on observations by \\citet{Fe94}, who found high column densities at the loop top, which might act as a thick target below a certain electron energy. In the ITTT model, the shape of the coronal and footpoint non-thermal spectra and the relation between them, observed by Yohkoh, can be explained. The column density in the coronal source determines a critical energy level for the electrons. Electrons that have an energy below this critical energy are stopped in the coronal region. Consequently, the distribution of electron energies measured at the footpoints is depleted in low energy electrons. If the column density is high, the coronal source may act as a thick target to electrons of energies as high as 60 keV, which would leave almost no footpoint emission. Observational evidence for such coronal thick targets were found in RHESSI observations \\citep[eg.][]{Ve04}.\n\nLess extreme cases, flares with one or more footpoints, have frequently been observed by RHESSI.\nTo study the spectral time evolution of individual sources, five well-observed events were analyzed by \\citet{Ba06} who focused on the differences between the spectral indices of coronal and footpoint spectra. They found that in two of those events, the differences at specific times as well as the time-averaged difference was significantly larger than two, ruling out a simple thin-thick target interpretation. In \\citet{Ba07}, the spectra of the five events were compared with the predictions of the ITTT model. The authors exploited the order of magnitude improvement in spectral resolution of RHESSI over the 4-point Yohkoh spectra and showed that most RHESSI observations could not be explained by the ITTT model. \n\n\\citet{Ba07} proposed that by considering non-collisional energy loss inside the loop this inconsistency could be resolved. \nA possible mechanism that causes non-collisional energy loss is an electric field. Accelerating electrons out of the coronal source region drives a return current to maintain charge neutrality in the whole loop. For finite conductivity, Ohm's law implies that an electric field must be present. The beam electrons lose energy because of work expended in moving inside the electric potential. This produces a change in the shape of the electron spectrum at the footpoints. The formation and evolution of these return currents were studied by various authors \\cite[e.g.][]{Kn77,SS84,La89,Oo90}. \\citet{Zh06} proposed that return currents could explain the high energy break observed in flare HXR spectra. \nMost studies have, however, been theoretical proposals or numerical simulations, based on standard flare values, that do not attempt to explain or reproduce true solar flare observations. \n\n\\citet{Ba07} compared RHESSI spectra to the ITTT-model of \\citet{Wh95}, demonstrating that the qualitative shape and relations between coronal and footpoint-spectrum often do not agree with the model predictions. In this study, we take an additional step by completing a quantitative analysis of the relation linking coronal and footpoint spectra in the context of the thin-thick target model; we demonstrate that, in some cases, electric fields related to return currents can indeed explain the relation between coronal and footpoint spectra.\n\nIn Sect.~\\ref{Theory} we summarize the basic physical concepts applied in the paper. Section~\\ref{evdescription} provides a brief overview of the analyzed events and a description of the spectral analysis. In Sect. \\ref{Method}, we describe our calculation of the energy loss required to reproduce the observed footpoint spectrum, constrained by the coronal emission. Our results are presented in Sect.~\\ref{results}. In Sect. \\ref{retcurrnefield}, we link those results to the concept of return currents. \n\n\\section{Thin and Thick target emission} \\label{Theory}\n\nTwo types of bremsstrahlung emission are distinguished. If the electrons pass a target without losing a significant amount of energy, the corresponding emission is referred to as thin target \\citep{Da73}. This situation is expected to occur in coronal regions when electrons pass through a target of insufficient column density to stop them. If the electrons are fully stopped inside the target, the resultant emission is called thick target emission \\citep{Br71}. This is the case for the dense chromospheric material at the footpoints. \n\nFor an input power-law electron distribution of the shape $F(E)=A_{E}E^{-\\delta}$, the non-relativistic bremsstrahlung theory predicts power-law photon spectra \n\\[I(\\epsilon)\\propto \\epsilon^{-\\gamma}\\quad\\mbox{where}\\quad\\left\\{\\begin{array}{l} \\gamma=\\delta+1\\quad\\mbox{in the thin target case} \\\\ \\gamma=\\delta-1\\quad\\mbox{in the thick target case} \\end{array} \\right. \\] \nThe observable distinction between the two emission mechanisms is a difference $\\Delta \\gamma$ of value 2 in their observed photon spectral indices. \n\nAssuming a final column density in the coronal source, the coronal source spectrum is a thick target at low energies and a thin target at high energies with a break at some critical energy. The footpoint spectrum is depleted at low energies, as low energy electrons do not reach the chromosphere. An illustration of this can be found in \\citet{Wh95} or \\citet{Ba07}.\n\nIn the events that we analyze here, a thermal component is present in all observations. Observation of the non-thermal emission is therefore only possible at photon energies higher than 15 keV. For these energies we can assume that the coronal source is a pure thin target and the footpoints are a pure thick target.\n\n\n\\section{Event description and spectral analysis} \\label{evdescription}\nThe two events that we analyze were described in detail by \\citet{Ba06, Ba07}. They were selected because of the significant differences between the footpoint and coronal non-thermal spectral index. The first event occurred on 24 October 2003 around 02:00 UT (GOES M7.7), the second on 13 July 2005 around 14:15 UT (GOES M5.1). Both events occurred close to the limb but were not occulted; two footpoints were therefore fully observed in both cases. RHESSI light curves from the time of main emission are shown in Fig.~\\ref{2flimages}. An EIT image of the 24 October 2003 event and a GOES SXI image for the event of 13 July 2005 are presented for orientation. The contours of the coronal source and the footpoints from RHESSI images are overlaid. \n\\begin{figure*} \n\\resizebox{\\hsize}{!}{\\includegraphics{9418fig1.eps}}\n\\caption {\\textit{Top}: RHESSI light curves in the 6-12 and 25-50 keV energy band. The analyzed time interval is indicated by the \\textit{vertical bar}. \\textit{Bottom}: SOHO\/EIT image at 24 October 2003 02:47:31 (\\textit{left}), GOES SXI image at 13 July 2005 14:19:04 (\\textit{right}). The 30 \\%, 50 \\% and 70 \\% contours from RHESSI Pixon images of the coronal source at 12-16 keV (\\textit{solid contours}) and 20-24 keV (\\textit{dashed contours}, mainly non-thermal emission) are overlaid along with the 50\\% contour of the footpoint sources at 25-50 keV.}\n\\label{2flimages}\n\\end{figure*}\n\n\n\\subsection{Spectral fitting and analysis} \\label{fitting}\n\nThe two events were analyzed using imaging spectroscopy with the PIXON algorithm \\citep{Me96, Hur02}. Images were made in a 30 second time interval during which the flux was sufficiently high for good images but pile-up was low. The image times are given in Table~\\ref{fitpartable} and shown in Fig.~\\ref{2flimages}. The spectra of the footpoints and the coronal source were measured and fitted. The regions of interest from which the spectra were computed were chosen to be a circle around the coronal source and a polygon around the footpoints to include all of the emission at all energies. The effects of this method of region selection are discussed in \\cite{Ba05}. As a simplification, the footpoints were treated as one region and the spectrum was fitted with a single power-law. In the presence of the footpoints, the non-thermal emission in coronal sources is difficult to observe. Therefore, two methods of fitting the coronal source were used. First, a thermal component was fitted to the spectrum at low energies and a single power-law to the energies higher than about 25 keV. As a second method, the full sun thermal spectrum was fitted. As shown in \\cite{Ba05}, the thermal emission observed in full sun spectra is mostly coronal emission. We therefore used the thermal full sun fit as an approximation to the coronal thermal component and completed a power-law fit at the higher energies, while the thermal emission was fixed. This supports the idea that non-thermal emission exists in the coronal source and provides an estimate of the accuracy of the non-thermal coronal fit. The energy ranges for the fits were 8-36 keV for the coronal source and 24-80 keV for the footpoints. All fit parameters are provided in Table~\\ref{fitpartable}.\n\nIn the thin-thick target model an electron beam is assumed to be injected into the center of the coronal source.\nThe column depth that the electrons travel through in the corona is then $\\Delta N=n_e\\cdot l$, where the path length \\textit{l} is half the coronal source length. \nFrom RHESSI images in the 10-12 keV band, the source area \\textit{A} was measured to be the 50\\% contour of the maximum emission. We approximate the source volume to be $V=A^{3\/2}$ and the path length to be $l=\\sqrt{A}\/2$. Using the observed emission measure EM, the particle density is computed to be $n_e=\\sqrt{EM\/V}$ which corresponds to a column depth of $\\Delta N=\\sqrt{EM}A^{-1\/4}\/2$ expressed in observable terms.\nA volume filling factor of 1 was assumed for the computation of the density, which will be improved in Sect.~\\ref{expfemissionloss}.\nThe emission measures were taken from the spectral fits to the coronal source and to full sun spectra. Additionally, temperatures and emission measures observed by GOES were included. This provides a range for the emission measures, temperatures, and column depths, and an estimate of their uncertainty. \\\\\n\n\n\\section{Method}\\label{Method}\n\nStarting from the assumption that the observed coronal spectrum at high photon energies is caused by thin target emission, we compute the electron distribution and therefore the expected footpoint photon spectrum. \nThis is completed via the following steps.\n\\begin{enumerate}\n\\item We assume that the observed coronal photon spectrum can be fitted by a power law:\n\\begin{equation}\n F^{cs}_{obs}(\\epsilon)=A_{\\epsilon}^{cs}\\epsilon^{-\\gamma^{cs}},\n\\end{equation} where A$_{\\epsilon}^{cs}$ is the normalization and $\\gamma^{cs}$ the photon spectral index.\n\\item Using thin target emission, the injected electron spectrum F(E) is then proportional to \\label{itemelsp}\n\\begin{equation} \\label{bla}\nF(E)=A_E E^{-\\delta}\\sim\\frac{A_{\\epsilon}^{cs}}{\\Delta N}E^{-\\gamma^{cs}+1}\n\\end{equation} where $\\Delta N$ is the column depth the electrons travel through inside the coronal target \\citep{Da73}. \n\\item The expected thick target emission $F_{exp}^{fp}(\\epsilon)$ caused by this electron distribution in the footpoints can be computed as follows \\citep{Br71}:\n\\begin{equation}\n F^{fp}_{exp}(\\epsilon)=A_{\\epsilon,exp}^{fp}\\epsilon^{-\\gamma^{fp}_{exp}}\\sim\\frac{A_{\\epsilon}^{cs}}{\\Delta N}\\epsilon^{-(\\gamma^{cs}-2)}\n\\end{equation}\nThe superscripts fp and cs denote the footpoint and coronal source values, respectively.\n\\item The normalization and spectral index of $F^{fp}_{exp}(\\epsilon)$ is compared to the observed footpoint spectrum $F^{fp}_{obs}(\\epsilon)$.\n\\end{enumerate}\nIn thin-thick target models, the difference in spectral index $\\Delta \\gamma=|\\gamma^{cs}-\\gamma^{fp}|$ is 2. As the observed difference is larger than 2 in the selected events, a mechanism has to be found that causes the electron spectrum to harden while the beam passes down the loop. We present a mechanism that assumes an electric field which causes electrons to lose the energy $\\mathcal{E}_{loss}$ independently of the initial electron energy. The resulting spectrum is flatter, although not strictly a power-law function anymore (Fig.~\\ref{elsp}a). The deviation becomes substantial below 2 $\\mathcal{E}_{loss}$.\n\n\nThe necessary energy loss is determined as follows:\n\\begin{enumerate}\n\\item We start with the coronal electron distribution as found from Point~\\ref{itemelsp} in the above list.\n\\item By assuming a thin target, the electron distribution leaves the coronal source and propagates down the loop. A constant energy loss $\\mathcal{E}_{loss}$ is subtracted from the electron energies as the energy loss is independent of the electron energy.\n\\item We compute the expected thick target photon spectrum $F^{fp}_{exp}(\\epsilon)$ from this altered electron spectrum.\n\\item A power law is fitted to $F^{fp}_{exp}(\\epsilon)$. The fitted energy range is 30-80~keV. This is the range for which footpoint emission is typically observed. \n\\end{enumerate}\nThe relation between the energy loss experienced and the corresponding photon spectral index of the best-fit power law function depends on the initial electron spectral index $\\delta$ and the energy loss $\\mathcal{E}_{loss}$. It is equivalent to the elementary charge times the electric potential between the coronal source and the footpoints. If the initial electron spectral index is 8 for instance, the thick target photon spectral index without energy loss is 7. With increasing energy loss, this value decreases rapidly. The effect is less pronounced when the initial electron spectrum is harder. This is shown in Fig.~\\ref{elsp}b for several values of $\\delta$ and $\\mathcal{E}_{loss}$. Using the curves in this figure, we can easily determine the energy loss that causes an electron spectrum of spectral index $\\delta$ to result in a fitted photon spectral index $\\gamma^{fp}$. \n\n\\begin{figure*} \n\\resizebox{\\hsize}{!}{\\includegraphics{9418fig2.eps}}\n\\caption {a) Normalized electron power-law spectrum (\\textit{solid}) and altered spectrum due to a constant energy loss of 30 keV (\\textit{dashed}). b) Relation between loss energy $\\mathcal{E}_{loss}$ and fitted thick target photon power-law spectral index $\\gamma^{fp}$ for initial electron spectral index $\\delta=3,4,5,6,7,8$ in the accelerator.}\n\\label{elsp}\n\\end{figure*}\n\n\n\n\n\n\n\\begin{table*}\n\n\\begin{minipage}[t][]{2\\columnwidth}\n\n\n\\caption{Overview of main event properties and fit parameters }\n\\renewcommand{\\footnoterule}{} \n\\begin{tabular}{l|lll|lll} \n\\hline \\hline\nTime interval &\\multicolumn{3}{c}{24 October 2003 02:48:20-02:48:50 }& \\multicolumn{3}{c}{13 July 2005 14:15:00-14:15:30 }\\\\\n\\hline\nArea [cm$^2$] \/ Volume [cm$^3$]&\\multicolumn{3}{c}{$7.9\\cdot 10^{18}$ \/ $2.2\\cdot 10^{28}$}&\\multicolumn{3}{c}{$1.7\\cdot 10^{18}$ \/ $2.2\\cdot 10^{27}$} \\\\\n\\hline\n&full sun&imspec& GOES&full sun&imspec&GOES\\\\\n\\hline\nTemperature [MK]\\footnote{ Thermal parameters for three different measuring methods (RHESSI full sun fit, RHESSI imaging spectroscopy, GOES). See also comment in Sect~\\ref{obsspectra}. }&21.6&23.2&15.4&23.8&22.3&18.1\\\\\nEmission measure [$10^{49}$cm$^{-3}$]&0.98&0.44&3.4&0.22&0.22&0.47\\\\\nElectron density [$10^{10}$cm$^{-3}$]&2.1&1.4&3.9&3.2&3.2&4.6\\\\\nColumn density [$10^{19}$cm$^{-2}$]&2.9&2.0&5.5&2.1&2.1&3.0 \\\\\n\\hline\n&footpoints&cs fit 1&cs fit2&footpoints&cs fit 1&cs fit 2\\\\\n$\\gamma$\\footnote{ Two different values (cs fit 1, cs fit 2) for the non-thermal coronal fit, distinguishing the two fitting methods used (compare Sect~\\ref{fitting}).}&2.6&6.2&6.1&2.9&5.1&5.6 \\\\\n$F_{50}[\\mathrm{photons\\, cm^{-2}s^{-1}keV^{-1}}]$&2.0&0.07&0.07&0.88&0.06&0.05 \\\\\n\n\\hline\n\\end{tabular}\n\\label{fitpartable}\n\\end{minipage}\n\n\\end{table*}\n\n\n\n\n\\section{Results}\\label{results}\n\n\\subsection{Observed spectra} \\label{obsspectra}\n\nFigure~\\ref{spectra} shows the observed spectra overlaid with the spectral fits. As indicated in Sect. \\ref{fitting}, the thermal fits differ slightly from each-other. The main reason why the fits do not agree is the wider energy binning adopted by imaging spectroscopy. With this binning, the atomic lines are not resolved, contrary to full sun spectroscopy.\n\\begin{figure*} \n\\resizebox{\\hsize}{!}{\\includegraphics{9418fig3.eps}}\n\\caption {Coronal and footpoint source spectra overlaid with the according fits. \\textit{Dots} are the measured footpoint spectrum, the \\textit{dashed-dotted} line indicates the fit to this spectrum in the range 30-80 keV. \\textit{Squares} indicate the observed coronal source spectrum. The \\textit{solid} lines provide the thermal and non-thermal fits as found from imaging spectroscopy. The \\textit{dotted} lines give the thermal fit to the full sun spectrum and the resulting non-thermal fit in imaging spectroscopy.}\n\\label{spectra}\n\\end{figure*}\n\nUsing the different fitting methods as an estimate of the uncertainty, an average difference in spectral index of $\\Delta \\gamma = 3.55 \\pm 0.07$ for the event of 24 October 2003 and $\\Delta \\gamma = 2.45 \\pm 0.35$ for the event of 13 July 2005 is found between the coronal source and footpoints. \n\\subsection{Expected footpoint emission and energy loss} \\label{expfemissionloss}\nAs described in Sect.~\\ref{Method}, we computed the electron distribution from the coronal source photon spectrum and the expected thick target emission (footpoint spectrum) caused by this electron distribution. Figure~\\ref{efieldspec} shows the measured spectra, the expected footpoint spectrum from a pure thick target, and the footpoint spectrum when introducing energy loss. \n\nTo compute the electron flux, the coronal column density is required. As given in Table~\\ref{fitpartable}, three different values of the column density were estimated. Using those, we are able to reproduce a range of possible electron spectra (Table \\ref{beamvalues}) and, therefore footpoint spectra. The confidence range of the footpoint spectra is indicated by a light gray (green) area in Fig.~\\ref{efieldspec}. \n\n\n\\begin{figure*} \n\\resizebox{\\hsize}{!}{\\includegraphics{9418fig4.eps}}\n\\caption {Observed (fitted) power-laws of the non-thermal coronal source and footpoints (\\textit{solid}). The \\textit{light-gray (green)} area indicates the range of expected footpoint spectra without energy loss. The \\textit{dark-gray (red)} area marks the range of expected footpoint spectra when energy loss is applied to the electrons to find the same spectral index as the observed footpoint spectrum. The \\textit{dash-dotted} lines give the expected spectra at the footpoints if the only transport effect was Coulomb collisions of the beam electrons (cf. Sect.~\\ref{collisions}).}\n\\label{efieldspec}\n\\end{figure*}\n\n\nThe derived energy loss depends on the fitted coronal and footpoint spectra. For the two different coronal fitting methods, a range of loss energies $\\mathcal{E}_{loss}=[58.0,59.4]$ keV is found for the event of 24 October 2003 and $\\mathcal{E}_{loss}=[8.7,26]$ keV for the event of 13 July 2005. The normalization of the new spectrum depends on the initial electron distribution. The initial electron distribution is computed according to Eq.~(\\ref{bla}). It depends on the column depth. If the column depth is lower, more electrons are needed to produce the same X-ray intensity. The resulting range of possible spectra is shaded in dark-gray in Fig.~\\ref{efieldspec}. As shown in the figure, the footpoint spectrum with energy loss reproduces well the observed footpoint spectrum for the event of 13 July 2005. \n\nDuring the event of 24 October 2003, the predicted footpoint spectrum is, however, an order of magnitude less intense than observed. In the context of the ITTT model, this implies that the electron flux density emanating from the coronal region is higher than predicted. The discrepancy may be explained by density inhomogeneities in the coronal source resulting in a smaller effective column density. The electron flux is underestimated if the non-thermal X-ray emission originates in regions that are less dense than average. In the following we therefore assume that the coronal source has an inhomogeneous density; this is represented by dense regions with filling factor smaller than 1 for thermal emission and, for the non-thermal coronal source in the 24 October 2003 event, a density that is lower by an order of magnitude. The observations do not allow to determine the filling factor.\nAs can be seen from Fig.~\\ref{2flimages}, the coronal source in the event of 13 July 2005 is very compact, while the source in the event of 24 October 2003 is more extended, showing isolated intense regions. This supports the assumption that the density is inhomogeneous in the 24 October 2003 coronal source and the true column density in the X-ray emitting plasma might be smaller than deduced from the measurements. Since $F_{exp}^{fp}(\\epsilon)$ is proportional to $1\/\\Delta N$, an effective column density of an order of magnitude less than the observed could produce the observed footpoint spectrum. \nIn the computations presented in Sect.~\\ref{retcurrnefield}, we assume an effective column density $\\Delta N_{eff} = \\Delta N\/14$ for the event of 24 October 2003.\n\n\n\\section{Return current and electric field} \\label{retcurrnefield}\nIn the above analysis, we assumed that the electrons experienced a constant energy loss while streaming down the loop. We now demonstrate that this energy loss could be caused by an electric potential in the loop that drives a return current. \nThere was much controversy surrounding the precise physical mechanism that generates the return current \\citep[eg.][]{Kn77, SS84, Oo90}. The basic scenario is the following: We assume that the electrons are accelerated in the coronal source region. When a beam of accelerated electrons, which is not balanced by an equal beam of ions, leaves this region, a return current prohibits charge build-up and the induction of a beam-associated magnetic field. In the return current, thermal electrons move towards the coronal source. Since their velocity is relatively small, they collide with background ions and cause resistivity. Ohm's law then implies the presence of an electric field in the downward direction. \nThe return current density $j_{ret}$ can be derived from the equation of motion for the background electrons \\citep{Bebook}.\n\\begin{equation}\n\\frac{\\partial \\vec{v}}{\\partial t}+(\\vec{v}\\cdot \\triangledown)\\vec{v}=-\\frac{e}{m}\\vec{E_{ind}}-\\frac{e}{mc}(\\vec{v}\\times \\vec{B})-\\nu_{e,i}\\vec{v}\n\\end{equation}\nwhere $\\vec{E_{ind}}$ is the electric field induced by the return current, $\\vec{v}$ is the mean velocity of the electrons that represent the return current, and $\\nu_{e,i}$ is the electron-ion collision frequency. Using $\\vec{j_{ret}}=-en\\vec{v}$, this expression can be written as\n\\begin{equation} \\label{fullohm}\n\\left(\\frac{\\partial}{\\partial t}+\\nu_{e,i}\\right)\\vec{j_{ret}}=\\frac{(\\omega_p^e)^2}{4\\pi}\\vec{E_{ind}}+\\frac{e}{mc}[\\vec{j_{ret}}\\times (\\vec{B_0}+\\vec{B_{ind}})],\n\\end{equation}\nwhere $B_0$ is the guiding magnetic field and $B_{ind}$ the field induced by the beam. We neglect the last term on the right side of Eq.~\\ref{fullohm} by assuming that the beam and return currents are anti-parallel, oriented along the guiding magnetic field, and that the perpendicular component of $B_{ind}$ vanishes. We then obtain\n\\begin{equation}\n\\left(\\frac{\\partial}{\\partial t}+\\nu_{e,i}\\right)\\vec{j_{ret}}=\\frac{(\\omega_p^e)^2}{4\\pi}\\vec{E_{ind}}.\n\\end{equation}\n\nSince we consider a fixed time interval that is far longer than the collision time, we assume a steady state, neglecting the time derivative of the return current. The equation then takes the form of the classical Ohm's law:\n\\begin{equation}\n\\vec{j_{ret}}=\\frac{(\\omega_p^e)^2}{4\\pi \\nu_{e,i}}\\vec{E_{ind}}=\\sigma \\vec{E_{ind}}.\n\\end{equation}\n\n\nWe estimate whether the energy loss computed in Sect.~\\ref{results} is caused by this electric field.\nFrom the observations, we estimated the electron loss energy $\\mathcal{E}_{loss}$ that the electrons experience in the loop (Sect.~\\ref{expfemissionloss}). Assuming this loss is caused by the induced electric field $E_{ind}$ and across the distance \\textit{s} from the coronal source to the footpoints (i.e. half the loop length), we compute the electric field to be\n\\begin{equation}\nE_{ind}=\\frac{\\mathcal{E}_{loss}}{e\\cdot s}.\n\\end{equation}\n\nUsing Spitzer conductivity~\\citep{Spbook}, the term for the return current is related to the observed loss energy by:\n\\begin{equation} \\label{returneq}\nj_{ret}=6.9\\cdot 10^6T_{loop}^{3\/2}\\frac{\\mathcal{E}_{loss}}{e\\cdot s}\\quad \\mathrm{[statamp\/cm^2]},\n\\end{equation}\nwhere $T_{loop}$ is the temperature in the loop.\n\nOn the other hand, the beam current density can be written as\n\\begin{equation} \\label{jbeam}\nj_{beam}=\\frac{F_{tot}(E)}{A_{fp}}\\cdot e \\quad \\mathrm{[statamp\/cm^2]},\n\\end{equation}\nwhere $A_{fp}$ is the total footpoint area. The total electron flux per second $F^{tot}(E)$ is computed from the observed electron spectrum as follows: Let the electron spectrum be $F(E)=A_eE^{-\\delta}$. The total flux of streaming electrons per second above a cutoff energy $E_{cut}$ is then:\n\\begin{equation} \nF_{tot}(E)=\\int_{E_{cut}}^{\\infty}F(E) \\mathrm{d}E=\\frac{A_e}{\\delta-1}E_{cut}^{-(\\delta-1)}.\n\\end{equation}\n\nIn a steady state, the relation \n\\begin{equation}\nj_{beam}=j_{ret}\n\\end{equation}\n is valid. \\\\\n\nComparing the beam current as described in Eq.~(\\ref{jbeam}) with the return current from the observed energy loss according to Eq.~(\\ref{returneq}), we test whether the assumption of Spitzer conductivity holds.\n\n\n\\subsection{Results} \\label{retresults}\nTable \\ref{beamvalues} presents the relevant physical parameters necessary for the derivation of the beam- and return currents.\nFor Spitzer conductivity, the loop temperature $T_{loop}$ is required. Its is expected to have a value between the coronal source temperature and the footpoint temperature (see Table~\\ref{beamvalues}). As a first assumption, a mean temperature of $T_{loop}=15$ MK is chosen. The loop length is evaluated from RHESSI images, approximating the distance between the sources from the centroid positions and assuming a symmetrical loop structure. This provides a typical half loop length of $4\\cdot 10^9$ cm. \nThe footpoint area is measured from the 50\\% contour in RHESSI images in the 25-50 keV energy range, yielding a total footpoint area of $\\approx (6-7)\\cdot 10^{17}$ cm$^2$. \nThe beam current density depends critically on the electron cut off energy $E_{cut}$. We use a value of 20 keV. This gives an approximate lower limit to the total amount of streaming electrons. \n\nUsing the presented observations, Eq.(\\ref{jbeam}) and by assuming Spitzer conductivity (Eq. \\ref{returneq}), the return current results to be of an order of magnitude higher than the beam current. This contradicts the assumptions of a steady state, and is also unphysical. \n\\begin{table*}\n\\caption{Values used for the computation of the beam and return currents and computed currents. } \n\\begin{tabular}{lrr} \n\\hline \\hline\nEvent & 24 October 2003 & 13 July 2005 \\\\\n\\hline\nAssumed loop temperature $T_{loop}$ [MK] & 15 & 15 \\\\\n1\/2 Loop length s [cm] & $3.2\\cdot 10^9$&$4.3\\cdot 10^9$ \\\\\nElectron flux $F(E)$ [s$^{-1}$ keV$^{-1}$]&6.33$\\cdot 10^{41}E^{-5.2}$-1.5$\\cdot 10d^{42}E^{-5.2}$&1.7$\\cdot10^{40}E^{-4.1}-8.4\\cdot 10^{40}E^{-4.6}$\\\\\nElectron cutoff energy [keV] & 20 & 20 \\\\\nTotal footpoint area [cm$^2$] & $7.2\\cdot10^{17}$& $6.2\\cdot10^{17}$ \\\\\n$E_{loss}$ [keV] & 58-59.4 & 8.7-26 \\\\\nElectric field strength [statvolt\/cm] &$(6-6.3) \\cdot 10^{-8}$&$(6.7-20.3)\\cdot 10^{-9}$ \\\\\n\\hline\n$j_{ret}$[$statamp\/cm^2$]&$(2.4-2.5) \\cdot 10^{10}$& $(2.7-8.1)\\cdot 10^9$\\\\\n$j_{beam}$ [$statamp\/cm^2$]&$(5.1-14.4) \\cdot 10^9$&$(1.9-3.6) \\cdot 10^8$ \\\\\n\\hline\n\\end{tabular}\n\n\\label{beamvalues}\n\\end{table*}\n\n\n\\section{Discussion} \\label{discussion}\n\n\\subsection{Instability}\nIn Sect.~\\ref{retresults}, we assumed Spitzer conductivity when computing the return current which produced the unphysical result of $j_{ret}>j_{beam}$. Using Eq.~(\\ref{returneq}), the loop temperature required to maintain equality between the return current and beam current ($j_{ret}=j_{beam}$) can be computed. In the 24 October 2003 event, the loop temperature $T_{loop}$ would need to be smaller than 10 MK; in the 13 July 2005 event, $T_{loop}$ should be less than 3.9 MK. Such low loop temperatures are highly unlikely.\nHowever, it is possible that the return current is unstable to wave growth. For an extended discussion of instabilities in parallel electric currents, see e.g. \\citet{Bebook}. Instability causes an enhanced effective collision frequency of electrons in the return current and therefore a lower effective conductivity. The ion cyclotron instability develops if the drift velocity of the beam particles $V_d$ exceeds the thermal ion velocity $v_{th}^{ion}$ as follows: \n\n\\begin{equation} \\label{instcond}\nV_d\\ge15\\frac{T_i}{T_e}v_{th}^{ion}\n\\end{equation}\nwith $v_{th}^{ion}=\\sqrt{\\frac{k_BT_i}{m_i}}$ and $T_e$ and $T_i$ being the electron and ion temperatures, respectively. \n\nWe assume a steady state for which $j_{beam}=j_{ret}=n_e eV_d$, where $V_d$ is the mean drift velocity of the electrons constituting the return current. We therefore express $V_d$ as\n\\begin{equation}\nV_d=\\frac{j_{beam}}{n_e e}\n\\end{equation}\nand substitute this expression and that for $v_{th}^{ion}$ in Eq. (\\ref{instcond}). Assuming $T_e = T_i=T_{loop}$ and solving Eq.~(\\ref{instcond}) for $T_{loop}$ the instability condition holds\n\\begin{equation} \\label{tcond}\nT_{loop}\\le 2.3\\cdot 10^8 \\left(\\frac{j_{beam}}{n_e}\\right)^2 \\quad \\mathrm{[K]}.\n\\end{equation}\n\nSince the loop temperature and density are not known exactly, \nthis relation is illustrated in Fig.~\\ref{instab} for several values of $n_e$ and $T_{loop}$ typical in flare loops. For the values of $j_{beam}$ found for the observations of the two events, we find that instability occurs in the 24 October 2003 event for all values of $n_e$ and $T_{loop}$ in Fig.~\\ref{instab}.\nFor the 13 July 2005 flare, three distinct regions in the diagram can be found. The solid line indicates the relation of Eq. (\\ref{tcond}). Below this line, the return current is unstable. At high densities and low temperatures (lower right), the return current is stable and $j_{beam}=j_{ret}$ with Spitzer conductivity. The range of beam currents $j_{beam}$ deduced from the data allows for loop temperatures $< 3.9$ MK. \nIn the upper right quadrangle, Spitzer conductivity would imply $j_{ret}>j_{beam}$, which is unphysical. If the loop was in this parameter range, the current instability would be most likely saturated and $T_e>T_i$. This would shift the instability threshold in Fig.~\\ref{instab} to the right. Further, a loop in the state presented by the uppermost part of the figure (temperature above 10 MK, high density) would be detectable by the RHESSI satellite even in the presence of the coronal source. Since no loop emission is observed, we conclude that the loop is either less dense, cooler or both. The values in the upper right quadrangle are therefore unlikely. \n\n\n\\begin{figure} \n\\resizebox{\\hsize}{!}{\\includegraphics{9418fig5.eps}}\n\\caption {Region of instability in the density\/temperature space for the event of 13 July 2005. The \\textit{grey} region indicates the densities and temperatures $T_{loop}$ for which the return current is unstable (Eq.~\\ref{instcond}). In the lower right part, the return current is stable and $j_{beam}=j_{ret}$ with Spitzer conductivity. The current in the event of 24 October 2003 is unstable for all values of density and temperature in the Figure.}\n\\label{instab}\n\\end{figure}\n\n\n\\subsection{Low energy electron cutoff}\nIn the above computations, a value of 20 keV for the electron cutoff energy $E_{cut}$ was assumed. This value is within the range for which the thermal and non-thermal components of the spectrum intersect. Values around 20 keV or higher are also supported by detailed studies of the exact determination of low-energy cutoffs \\citep[eg.][]{Sa05,Ve05,Sui07}. What if the cutoff energy were substantially lower than 20 keV? A cutoff energy as low as 10 keV would increase the total electron flux and therefore the beam current by an order of magnitude, leading to $j_{ret}\\approx j_{beam}$ for Spitzer conductivity. Conductivity could then not be reduced significantly by wave turbulence, and instability would be marginal. If the low energy cutoff were even lower than 10 keV, we would find that $j_{ret}< j_{beam}$. This could not be explained in terms of the model used here.\n\\subsection{Source inhomogeneity and filling factor} \\label{filling}\nIn the above paragraphs, it was demonstrated that the energy loss for the electrons due to an electric field could resolve the inconsistency in the difference between footpoint and coronal source spectral indices (Sect. \\ref{results}). For the event of the 24 October 2003, this produces footpoint emission that is lower than the observed emission (Fig. \\ref{efieldspec}). Images show that the coronal source in this event is not compact, but extended with brighter and darker regions. It is therefore possible that the standard density estimate, which favors high density regions, produces higher densities than average and that the effective column density of the regions, where the largest part of the non-thermal emission originates, is lower. This would provide a higher expected footpoint emission, in closer agreement with observations. \n\nAs mentioned in Sect.~\\ref{fitting}, a filling factor of 1 was used for the computation of the column density. A filling factor smaller than 1 would lead to even higher densities of the SXR emitting plasma. However, this would not affect the lower effective column density of the regions, where the HXR emission originates when assuming source inhomogeneity. \n\n\\subsection{Collisions and other possible scenarios} \\label{collisions}\nWhile return currents may not be the only means of attaining non-collisional energy loss, they are the most obvious and best studied. However, other scenarios are conceivable, which could produce a harder footpoint spectrum (or a softer coronal spectrum). \nIn the model presented here, collisional energy loss of beam electrons is neglected. This is a valid assumption for the following reasons: If collisions of the beam electrons in the loop were to play an important role, significant HXR emission should originate in the loop. Within the dynamical range limitations of RHESSI, this is not the case. However, GOES SXI and SOHO\/EIT images imply that the loop is filled with hot material. To study possible effects of collisions, we compared the change in the electron spectrum and the resulting footpoint spectrum for collisional energy loss and energy loss due to the electric field. The change in the electron spectrum due to collisions depends on the column depth through which the beam passes and was computed by \\citet{Le81} and \\citet{Br75}. We assume a column depth derived from the density in the loop times half the loop length. Assuming the same density as in the coronal source, we derive an upper limit to the collisional effects. The expected footpoint spectrum from purely collisional losses is indicated in Fig.~\\ref{efieldspec} as dash-dotted lines. Collisions affect the low energetic electrons most where a significant change in the spectrum is found. At the higher energies observed in this study, the spectrum does not change significantly. The neglect of collisional effects is therefore justified.\n\\citet{Br08} showed that in certain cases, emission from non-thermal recombination can be important, generating a coronal spectrum that is steeper than expected by the thin-target model. This could also produce a difference in the spectral index that is larger than two. Acceleration over an extended region \\citep[as proposed by][]{Xu08} could alter the electron distribution at the footpoints. If the distribution was harder at the edge of the region, a spectral index difference larger than 2 would result. A thorough comparison of such models with observations may be the scope of future work. \n\\section{Conclusions} \\label{conclusions}\nThe spectral relations between coronal and footpoint HXR-sources provide information about electron transport processes in the coronal loop between the coronal source and the footpoints. Most models neglect these processes in the prediction of the shape and quantitative differences between the source spectra. As shown by \\citet{Ba07}, the observations of some solar flares do not fit the predictions of such models, in particular the intermediate thin-thick target model by \\citet{Wh95}: there is a discrepancy concerning the difference in coronal and footpoint spectral indices, which is expected to be 2. \n\nWe have analyzed the two out of five events that display a spectral index difference larger than two in more detail. Such a behavior can be attributed to energy loss during transport that is not proportional to electron energy, but $\\mathcal{E}_{loss}\/E$ is larger at low energies. Such an energy loss causes the footpoint spectrum to flatten, which increases the difference in spectral indices. Two loss mechanisms come to mind immediately: Coulomb collisions and an electric potential. Figure 4 demonstrates that the assumption of an electric potential reproduces the observations more accurately.\n\nIn one of the two events, there remains a discrepancy between the observed and expected footpoint emission, such that the electron flux at the footpoints is larger than predicted. This flux was estimated from the observed non-thermal HXR (photon) flux and the observed thermal emission of the coronal source. We attribute the discrepancy to propagation or acceleration in low density plasma, which also heats the adjacent high-density regions. \n\nThe energy loss can therefore be explained by an electric field in the loop associated to the return current, which builds up as a reaction to the electrons streaming down the loop and the associated beam current. In a steady state ($j_{beam}=j_{ret}$), the return current is unstable to wave growth in one event for all realistic temperature and density parameters in the loop. The kinetic current instability drives a wave turbulence that enhances the electric resistivity by many orders of magnitude. This anomalous resistivity in turn significantly enhances the electric field. In the event of 13 July 2005, the return current may be stable if the loop density is high and the temperature is low, and Spitzer conductivity is applied. Both cases (out of five) present strong evidence for a return current in flares for the first time.\n\nTransport effects by return currents constitute a considerable energy input by Ohmic heating into the loop outside the acceleration region. It may be observable in EUV. Comprehensive MHD modeling including the coronal source, the footpoints, and the region in-between, may be the goal of future theoretical work.\n\n\n\n\n\n\\begin{acknowledgements}\nRHESSI data analysis at ETH Z\\\"urich is supported by ETH grant TH-1\/04-2 and the Swiss National Science Foundation (grant 20-105366). \nWe thank S\\\"am Krucker for helpful comments and discussions.\n\\end{acknowledgements}\n\n\n\\bibliographystyle{aa}\n","meta":{"redpajama_set_name":"RedPajamaArXiv"}} +{"text":"\\section{Introduction}\nThe ability to design nanostructures which accurately self-assemble from \nsimple units is central to the goal of engineering objects and machines \non the nanoscale. \nWithout self-assembly, structures must be laboriously constructed in a step \nby step fashion. Double-stranded DNA (dsDNA) has the ideal properties for \na nanoscale building block,\\cite{Seeman2003,Pitchiaya2006} \nwith structural length scales determined by the \nseparation of base pairs, the helical pitch and its persistence length \n(approximately 0.33\\,nm, 3.4\\,nm (Ref.\\ \\onlinecite{Saenger1984}) and \n50\\,nm,\\cite{Hagerman1988} respectively). \nOver these distances, dsDNA acts as an almost rigid \nrod and so it is capable of forming well-defined three dimensional structures.\n\nIt is the selectivity of base pairing between single strands, however, that makes DNA ideal for controlled self-assembly. \nBy designing sections of different strands to be complementary, a certain configuration of a system of oligonucleotides can be specified as the global minimum of the energy landscape. \nIn this way the target structure (usually consisting of branched double helices) can be `programmed' into the sequences. \nThis approach was initially demonstrated for a four-armed junction by the Seeman\ngroup in 1983.\\cite{Kallenbach83}\nSuch junctions and more rigid double crossover motifs\\cite{Fu93}\ncan then be used to create two-dimensional lattices.\\cite{Winfree98,Malo2005}\nYan \\it et al. \\rm \\cite{Yan2003} have also constructed ribbons and two dimensional lattices from larger four-armed structures, each arm consisting of a junction of four strands. \nFurthermore, using Rothemund's DNA ``origami'' approach an almost arbitrary \nvariety of two-dimensional shapes can be created.\\cite{Rothemund06}\n\nProgress in forming three-dimensional DNA nanostructures was initially much \nslower. The Seeman goup managed to synthesize a DNA cube\\cite{Chen91} and \na truncated octahedron,\\cite{Zhang94} but only after a long series of steps and \nwith a low final yield.\nMore recently, approaches have been developed that allow polyhedral cages, \nsuch as tetrahedra,\\cite{Goodman2005} trigonal bipyramids,\\cite{Erben07} \noctahedra,\\cite{Shih04,Anderson08} dodecahedra and truncated icosahedra,\n\\cite{He2008} to been obtained in high yields simply by cooling \nsolutions of appropriately designed oligonucleotides from high temperature. \nAdditional structures have also been produced using pre-assembled modular building blocks incorporating other organic molecules.\\cite{Aldaye2007,Zimmermann08} \n\nIn designing strand sequences, it is important to minimize the stability of competing structures with respect to the stability of the target configuration. \nIn addition, if systems can be designed to follow certain routes through configuration space---for example, by the hierarchical assembly of simple motifs \\cite{Pistol2006}---the target can potentially be reached more efficiently. \nA standard approach to hierarchical assembly, such as that described by \nHe {\\it et al.},\\cite{He2008}\ninvolves choosing sequences so that bonds between different pairs of oligonucleotides become stable at different temperatures. \nThis allows certain motifs to form in isolation at high temperatures before bonding to each other as the solution is cooled. \nAn alternative, elegant system for programming assembly pathways has been proposed by Yin \\it et al. \\rm \\cite{Yin2008}, which relies on the metastability of single stranded loop structures and the possibility of catalyzing their interactions using other oligonucleotides.\n\nGiven these recent experimental advances in creating DNA nanostructures, it would be useful to have\ntheoretical models that allow further insights into the self-assembly process.\nIn particular, a successful model would be able to provide information on the \nformation pathways and free energy landscape associated with the self-assembly, \nand as such would be of use to experimentalists wishing to consider increasingly more complex designs. \nAtomistic simulations of DNA would offer potentially the most spatially-detailed descriptions of the self-assembly. \nHowever, they are computationally very expensive, and are generally restricted to time scales that are \ntoo short to study self-assembly.\\cite{Cheatham2004}\n\nStatistical approaches such as that of Poland and Scheraga \\cite{Poland1970} and the nearest-neighbour model \\cite{Everaers2007} use simple expressions for the free energy of helix and random coil states to obtain equilibrium results for the bonding of two strands. \nWhilst the parameters in these models can be tuned to give very accurate correspondence with experimental data,\\cite{SantaLucia1998,SantaLucia2004} they give no information on the dynamics and formation pathways and hence are only useful for ensuring that the target structure has significantly lower free energy than competing configurations. \nFurthermore, any description purely based on secondary structure (i.e.\\ which bases are paired) is inherently incapable of accounting for topological effects such as linking of looped structures.\\cite{Bois2005} \n\nCoarse-grained or minimal models offer a compromise between detail and computational simplicity, and are well suited to the study of hybridization of oligonucleotides. The aim of these models is to be capable of describing both the thermodynamic and kinetic behaviour of systems, a vital feature if kinetic metastability is inherent in assembly pathways.\\cite{Yin2008} In developing such minimal models the approach is usually to retain just those physical features of the system that are essential to the behaviour that is of interest. \n\nDauxois, Peyrard and Bishop models,\\cite{Dauxois1993} and modified versions such as that proposed by Buyukdagli, Sanrey, and Joyeux,\\cite{Buyukdagli2005} \nconstitute the simplest class of dynamical models. \nAlthough these are dynamic models in the sense that the energy is a function of the separation between each base, the nucleotides are constrained to move in one dimension. This lack of conformational freedom means that these models are \nincapable of capturing the nuances of the self-assembly from single-stranded DNA (ssDNA).\n\nRecently, models have been proposed which capture the helicity of dsDNA using two \\cite{Drukker2001} or three \\cite{Knotts2007} interaction sites per nucleotide. \nThese models, however, are optimized for studying deviations from the ideal double-stranded state, and so have not been used to examine self-assembly.\nAlthough they have been used to study the thermal denaturation of dsDNA, \nit is essential for our purposes to be able to simulate the assembly of a \nstructure from ssDNA as it is this process that will reveal the kinetic traps \nand free energy landscape associated with the formation of a particular \nDNA nanostructure. \n\nSimpler, linear models, also with two interaction sites per nucleotide, have been used to investigate duplex hybridization,\\cite{Araque2006} hairpin formation \\cite{Sales-Pardo2005} and gelation of colloids functionalized with oligonucleotides.\\cite{Starr2006} \nThese models all use two interaction sites to represent one nucleotide, with backbone sites linked to each other to represent the sugar-phosphate chain, and interaction sites which represent the bases. This work investigates the possibility of extending the use of such coarse-grained models to study the self-assembly of nanostructures that involve multiple strands forming branched duplexes. We hypothesize that the self-assembly properties of DNA are dominated by the fact that ssDNA is a semi-flexible polymer with selective attractive interactions. \nWe introduce an extremely simple model, similar to that of Starr and Sciortino,\nto test this hypothesis. \\cite{Starr2006} \nThis simplicity enables us to explore the thermodynamics and kinetics of self-assembly in the model in great depth, and hence examine the feasibility of simulating nanostructure formation through minimal models.\n\nWe first describe the model in Section \\ref{methods}, then examine its success in reproducing the general features of hybridization in Section \\ref{Duplex Formation}. \nNext in Section \\ref{Holliday Junction}, we apply it to the formation of a Holliday junction, a simple nanostructure consisting of a four-armed cross.\\cite{Malo2005}\n\n\\begin{figure}\n\\begin{center}\n\\includegraphics[width=8.4cm]{Fig1.eps}\n\\end{center}\n\\caption{(Colour online) A schematic representation of the model. \nThe thick lines represent the rigid backbone monomer units and the large circles the repulsive Lennard-Jones interactions at their centres.\nThe smaller, darker circles represent the bases. \nThe panels illustrate the definitions of (a) the bending angle between two units ($\\theta$), and (b) the torsional angle ($\\phi$) which is found after the monomers have been rotated to lie parallel.}\n\\label{model picture}\n\\end{figure}\n\n\\section{Methods}\n\\label{methods}\n\\subsection{Model}\n\\label{model}\n\nWe introduce an off-lattice model inspired by that which Starr and Sciortino \nused to study the gelation of four-armed DNA dendrimers.\\cite{Starr2006} \nAs our aim is to reproduce the basic physics with as simple a \nmodel as possible, we neglect contributions to the interactions\ndue to base stacking, and the charge and asymmetry of the phosphate backbone. \nWe do not attempt to include the detailed geometrical structure \nof DNA, but instead\nrepresent the oligonucleotides as a chain of monomer units,\neach corresponding to one nucleotide (Fig.\\ \\ref{model picture}). \nA monomer consists of a rod (chosen to be rigid for simplicity) of length $l$ \nwith a repulsive backbone interaction site at the centre of the rod.\nIn addition, each unit has a bonding interaction site (or base) at a distance \nof $0.3\\,l$ from the backbone site \n(perpendicular to the rod). Each monomer is also assigned a base type \n(A,G,C,T) to model the selective nature of bonding. In this model we only \nconsider bonds between the complementary pairs A-T and G-C.\n\n\nWe do not explicitly include any solvent molecules in our simulations, but instead use effective potentials\nto describe the interactions between the DNA.\nSites interact through shifted-force \nLennard-Jones (LJ) potentials, where, as well as truncating and shifting the \npotential, an extra term is included to ensure the force goes smoothly to zero \nat the cutoff $r_c$. \nFor $r < r_{c}$\n \\begin{equation} \nV_{\\rm sf}(r)=V_{\\rm LJ }(r) - V_{\\rm LJ}(r_{c}) - \n (r-r_{c})\\left.\\frac{dV_{\\rm{LJ}}}{dr}\\right|_{r=r_c}\n \\label{potential} \n \\end{equation} \nwhere\n \\begin{equation} \n V_{\\rm LJ}(r) = 4\\epsilon \\left [\\left({\\sigma \\over r} \\right) ^{12} - \\left( {\\sigma \\over r} \\right) ^{6} \\right], \\label{LJ} \n\\end{equation} \nand $V_{\\rm sf}(r) = 0$ for $r\\ge r_{c}$. \nBackbone sites (except adjacent units on the same strand) interact through \nEq.\\ (\\ref{potential}) with $\\sigma = l$ and $r_{c} = 2^{1\/6}\\sigma$. \nThis purely repulsive interaction models the steric repulsion between strands. \nBonding sites (again excluding adjacent units on a strand) interact via \nEq.\\ (\\ref{potential}) with $\\sigma = 0.35\\,l$ and $r_{c} = 2.5\\,\\sigma$ for complementary bases (to allow for attraction) and $r_{\\rm c} = 2^{1\/6}\\sigma$ for all other pairings. \nThe depth of the resulting potential well between complementary bases, \n$\\epsilon^{\\rm eff}_{\\rm base}$, is $0.396\\epsilon$. In what follows we will measure\nthe temperature in terms of a reduced temperature, \n$T^*=k_B T\/\\epsilon^{\\rm eff}_{\\rm base}$. \nThe above choice of parameters ensures that the attractive interaction between complementary bases is largely shielded by backbone repulsion. Monomers therefore bond selectively and can only bond strongly to one other monomer at a given instant. \nThese are the key features of Watson-Crick base pairing that make DNA so useful for self-assembly.\n\nThe model also includes potentials between consecutive monomers associated with bending and twisting the strand: \n\\begin{equation} \nV_{\\rm bend} = \\begin{cases}\n k_1 (1-\\cos(\\theta))& \n \\text{if $\\theta < {3\\pi\\over4}$},\\\\ \n\t\t\\infty& \\text{otherwise}\n\t\t\t\\end{cases}\n\\label{bend} \n\\end{equation}\nand \n\\begin{equation}\nV_{\\rm twist} = k_2 (1-\\cos(\\phi)).\n\\label{twist}\n\\end{equation}\nWe define $\\theta$ as the angle between the vectors along adjacent monomer rods. As previously mentioned, consecutive backbone sites do not interact via LJ potentials. \nInstead, a hard cutoff is introduced in Eq.\\ (\\ref{bend}) to reflect the fact that an oligonucleotide cannot double back on itself. \n$\\phi$ is taken as the angle between adjacent backbone to bonding site vectors after the monomers have been rotated to lie parallel (Fig.\\ \\ref{model picture}). \nFor simplicity, we choose the torsional potential to have a minimum at $\\phi=0$. Thus, neither ssDNA or dsDNA\nwill be helical in our model.\n\n$k_1$ is chosen to be $0.1\\,\\epsilon$ to give a persistence length, $l_{\\rm ps}=3.149\\,l$ at a reduced temperature of $T^*=0.09677$ for ssDNA. \nWe obtain this result by simulating a single strand 70 bases in length, and using the definition:\\cite{Cifra2004}\n\\begin{equation}\nl_{\\rm{ps}} = \\frac{\\langle {\\bf{L} \\cdot \\bf{l_{\\rm 1}}}\\rangle} {\\langle l_{\\rm 1} \\rangle},\n\\end{equation} \nwhere $\\bf{L}$ is the end to end vector of the strand, $\\bf{l_{\\rm 1}}$ is the vector associated with the first monomer and $\\langle \\rangle$ indicates a thermal average. \nTaking $l$ to be 6.3{\\AA}, $T^*=0.09677$ is mapped to $24^\\circ$C and so the model is consistent with experimental data for ssDNA in 0.445M NaCl solution.\\cite{Murphy2004,lengthscale} $k_2$ is chosen to be $0.4\\,\\epsilon$.\n\nIn neglecting the geometrical structure of a double helix we do not accurately represent certain types of bonding. \n`Bulged' bonding occurs when consecutive bases in one of the strands attach to non-consecutive bases in the other strand. \n`Internal loops' consist of stretches of non-complementary bases (either symmetric or asymmetric in the number of bases involved in each strand). \n`Hairpins' result when a single strand doubles back and bonds to itself. The details of these motifs are complicated but an empirical description of their thermodynamic properties is given in Ref.\\ \\onlinecite{SantaLucia2004}. \nImportantly, they are generally penalized due to the disruption of the geometry of DNA in a way which is not well reproduced by our model. \nIn the case of the short strands we consider, these motifs will only play a small role as the strands are not specifically intended to have stable structures of these forms. \nIn fact, as the base sequences we use were designed to form the Holliday junction, the possibility of forming these motifs at relevant temperatures was deliberately avoided.\\cite{MaloThesis}\n\nFor simplicity we therefore include only two alterations to the model. Firstly, we define `kinked states' as those for which the number of unpaired bases between two bonding pairs on either side of a duplex is not equal (including asymmetric loops and bulges). We impose an infinite energy penalty on the formation of these kinked states if the total number of intermediate bases is less than six. Secondly, we treat complementary units within six bases of each other on the same strand as non-complementary, but allow all other hairpins without penalty. \n\nIt should be also noted that this model neglects the directional asymmetry of the sugar-phosphate backbone. Therefore,\nparallel as well as anti-parallel bonding is possible in our model, whereas parallel bonding does \nnot occur in experiment. \n\n\\subsection{Monte Carlo Simulation}\n\\label{Monte Carlo Simulation}\n\nIn a fully-atomistic model of DNA the natural way to simulate its dynamics would be to use molecular dynamics. However, the best way to simulate the dynamics\nin a coarse-grained model is an important, but not fully resolved, question, and\none that will depend on the nature of the model. Clearly, for the current model\nstandard molecular dynamics is inappropriate as it will lead to ballistic \nmotion of the strands between collisions because of the absence of explicit \nsolvent particles, whereas DNA in solution undergoes diffusive Brownian motion. \nAn alternative approach is to use Metropolis Monte Carlo (MC) \nalgorithm\\cite{Metropolis1953,Frenkel2001} where the moves \nare restricted to be local, as it has been argued that this can provide a \nreasonable approximation to the dynamics.\\cite{Kikuchi91,Berthier07,Tiana07} \nThis is the approach that we use here to simulate the dynamics of \nself-assembly of DNA duplexes and Holliday junctions. \nIn particular, the local MC moves that we use are translation and \nrotation of whole strands and bending of a strand about a particular monomer,\nthus ensuring that the strands undergo an approximation to diffusive Brownian \nmotion in the simulations.\nTherefore we expect the MC simulations, which are all initiated with free single strands, to mimic the real self-assembly processes in our model. It is \nimportant to note that this will include, as well as successful assembly into the target structure, kinetic trapping in non-equilibrium\nconfigurations and that when the latter occurs this reflects the inefficiency of\nthe self-assembly under those conditions.\n\n\nAlthough a true measure of time is impossible in Monte Carlo simulations, an approximate time scale for diffusion-limited processes can be found by comparing the diffusive properties of objects to experiment. \nBy measuring the diffusion of isolated strands, and assuming diffusion coefficients comparable to those of double strands and hairpin loops of similar length,\\cite{Lapham1997} we conclude that one step per strand corresponds to a time scale of approximately 2\\,ps. \nThus, our model allows our systems to be studied on millisecond time scales. \n\nAt the end of the above MC simulations, our systems will not necessarily have reached equilibrium, \nboth because the energy barriers to escape from misbonded configurations can be difficult to \novercome at low temperature and the low rate of association at higher \ntemperatures.\nTherefore, as a comparison we also compute\nthe equilibrium thermodynamic properties of our systems using umbrella \nsampling.\\cite{Torrie1977,Frenkel2001} \nFormally, we can write the thermal average of a function $B(\\bf{r}^N)$ in the canonical ensemble as:\n\\begin{equation}\n\\langle{B}\\rangle = \\frac\n {\\int{\\frac{B}{W(Q)} \\left[{W(Q) \\exp(-V\/\\rm{k_B}\\it T)}\\right]} d\\bf{r}^{N}} \n {\\int{\\frac{1}{W(Q)}\\left[{W(Q) \\exp(-V\/\\rm{k_B} \\it T)}\\right]} d\\bf{r}^{N}} \n\\label{US avg}\n\\end{equation}\nwhere $Q=Q(\\bf{r}^N)$ is an order parameter or reaction coordinate and $V=V(\\bf{r}^N)$ is the potential energy. \nWe are free to choose $W(Q)$, and by taking the term in square brackets as the weighting of states and keeping statistics for $B\/W$ and $1\/W$ at each step we can find $\\langle{B}\\rangle$. \nIn standard Metropolis MC, $W=1$, but by choosing $W(Q)$ in such a way that those states \nwith intermediate values of $Q$ are visited more frequently, the effective free energy barrier between \n(meta)stable states can be lowered allowing the system to pass easily between the free energy minima, and equilibrium to be reached.\n\nTo ensure that each value of $Q$ is equally likely to be sampled in an \numbrella sampling simulation, one would choose $W(Q)=\\exp(\\beta A(Q))$,\nwhere $A(Q)$ is the free energy as a function of the order parameter. \nTo achieve this, however, would require knowledge of $A(Q)$. \nInstead, there are standard methods to \nconstruct $W(Q)$ iteratively, but for the current examples it was possible to\nconstruct $W(Q)$ manually, because of the relative simplicity of the free\nenergy profiles.\n\nTo a first approximation the interaction between fully bonded structures is negligible. \nTherefore, in the umbrella sampling simulations we consider systems containing the minimum number of strands \nrequired to form a given object (two for a duplex and four for a Holliday junction). We then use the relative weight of bound and free states to extrapolate the expected fractional concentrations for larger systems.\\cite{Ouldridgeunpub}\nThe natural choice for the order parameter $Q$ is the number of correct bonds, where \ntwo monomers are defined to be bonded if their energy of interaction is negative.\n\n\\section{Results}\n\\subsection{Duplex Formation}\n\\label{Duplex Formation}\n\nWe test the model by analysing the duplex bonding of two different complementary strands. \nWe simulate systems of ten oligonucleotides, initially not bonded, in a periodic cell with a concentration of $5.49\\times10^{-5}$ molecules\\,$l^{-3}$\n(or $3.65\\times10^{-4}$\\,M). \nWe separately consider strands consisting of 7 and 13 monomers, which correspond to two of the arms of the Holliday junction studied experimentally by Malo {\\it et al.}\\cite{MaloThesis,Malo2005} and which we consider in Section \\ref{Holliday Junction}:\n\\begin{equation}\n\\text{7 bases} \\begin{cases}\n\t\t\t\t\t\\text{G-A-G-T-T-A-G}\\\\\n\t\t\t\t\t\\text{C-T-A-A-C-T-C}\n\t\t\t\t\t\\end{cases}\n\\label{7 bases}\t\t\t\t\t\n\\end{equation}\n\\begin{equation}\t\t\t\t\t\n\\text{13 bases} \\begin{cases}\n\t\t\t\t\t\\text{G-C-G-A-T-G-A-G-C-A-G-G-A}\\\\\n\t\t\t\t\t\\text{T-C-C-T-G-C-T-C-A-T-C-G-C}\n\t\t\t\t\t\\end{cases}\n\\label{13 bases}\n\\end{equation}\nwhere we have listed strands in the 5'--3' sense for consistency with the literature. \nThe yields of correctly-bonded and misbonded structures at the end of the simulations are depicted in Figure \n\\ref{7 & 13 mers} as a function of temperature.\nWe also display the predicted equilibrium fraction of correctly bonded strands for both systems obtained using umbrella sampling. \nFor convenience, we define a correctly bonded structure to have more than 70\\% of the bonds of the complete duplex and no bonds to other strands. Any other structure is recorded as `misbonded'.\n\n\\begin{figure}\n\\includegraphics[width=6.2cm,angle=-90]{Fig2.eps}\n\\caption{(Colour online) Yields of correctly-formed duplexes and misbonded configurations at the end \nof our MC simulations (lines with data points, as labelled) compared to the equilibrium probability of \nthe strands adopting the correct structure as obtained by umbrella sampling.\nThe solid and dashed lines represent results for strands with 7 and 13 monomers, respectively.\nThe MC results are averages over ten runs of length $3\\times10^8$ steps per strand with ten strands in \nthe simulation cell. }\n\\label{7 & 13 mers}\n \\end{figure}\n\nFigure \\ref{7 & 13 mers} shows a maximum in the yield as a function of temperature. \nSuch behaviour is typical of self-assembling systems \n\\cite{Brooks06,Hagan2006,Wilber2007,Rapaport08,Whitelam08} and reflects the \nthermodynamic and dynamic constraints on the self-assembly process. \nFirstly, the yield is zero at high temperature where only ssDNA is stable, and rises just below the expected \nequilibrium value as the temperature is decreased, \nthe deviation arising due to the large number of steps required to reach equilibrium. \nAt low temperatures, the yield falls away due to the presence of kinetic traps which are now stable with respect to isolated strands, as evidenced by the rise in `misbonded structures' in Figure \\ref{7 & 13 mers}. \nThus, there is a non-monotonic dependency of yield on temperature and an optimum region for successful assembly, which corresponds to the region where only the desired structure is stable against thermal fluctuations. \nFigure \\ref{5 13mers} is a snapshot from near the end of a simulation in this regime. \nIt should be noted that neglecting helicity has the effect of increasing the flexibility of dsDNA in the direction \nperpendicular to the plane of bonding \n(a helix cannot bend in any direction without disturbing its internal structure whereas a `ladder' can). \n\n\\begin{figure}\n\\includegraphics[width=8.4cm]{Fig3.eps}\n\\caption{(Colour online) Snapshot of a fully-assembled configuration in a MC simulation of\nten 13-base strands at $T^*=0.0971$.\nIn this image the colour of the backbone indicates the type of strand: red for G-C-G-A-T-G-A-G-C-A-G-G-A and grey for its complement.\nBackbone sites are indicated by the large spheres, and bases by the small, blue spheres.}\n\\label{5 13mers}\n\\end{figure}\n\nThe heat capacity obtained from umbrella sampling of pair formation is shown in Figure \\ref{thermo_duplex}(a). \nThe heat capacity peaks indicate a transition from single strands to a duplex. \nAs the formation of duplexes is essentially \na chemical equilibrium between monomers and clusters of a definite size \n(in this case two)\nthe width of the peaks will remain finite as the number of strands is increased. \nThe transition does, however, become increasingly narrow as the DNA strands become longer, as is evident from comparing the \nheat capacity peaks for the 7-mer and 13-mers.\n\n\\begin{figure}\n\\includegraphics[width=8.4cm]{Fig4.eps}\n\\caption{Thermodynamics for the formation of a single duplex. \n(a) Heat capacity curves for 7- and 13-base systems, as labelled.\n(b) Free energy profile associated with the formation of a 13 base pair duplex at different temperatures \n(as labelled), where $Q$ represents the number of correctly formed bonds in the duplex.}\n\\label{thermo_duplex}\n\\end{figure} \n\nFigures \\ref{thermo_duplex}(b) shows the free energy profile, $F(Q)$, for the \nformation of a duplex. \nThe initial peak at low $Q$ is accounted for by the entropic cost of bringing two strands together. \nOnce bonds are formed, however, adding extra bonds costs much less entropy whilst providing a significant decrease in energy, explaining the monotonic decrease in $F(Q)$ beyond $Q=2$. \nThe rise between $Q=1$ and $Q=2$ is partly due to the fact that in order to form two bonds between strands the relative orientation of strands must be specified whereas this is not true for $Q=1$: \nhence there is an additional entropy penalty to the formation of the second bond. \nIn addition, there exist structures with only one correct bond that are \nstabilized by additional incorrect bonds and these misbonded configurations \nalso contribute to $F(1)$. \nThe constant gradient above $Q=2$ indicates that the energetic gain and entropic cost of forming an extra bond are approximately constant at a given temperature, which is consistent with the assumptions underlying nearest-neighbour models of DNA melting.\\cite{Everaers2007}\n\n\\begin{figure}\n\\includegraphics[width=6.2cm,angle=-90]{Fig5.eps}\n\\caption{(Colour online) The bulk equilibrium probability of strands being in \na correct duplex extrapolated from our umbrella sampling simulations (solid lines) compared to the predictions of an empirical two-state model (dashed lines).\nResults are presented for strands with 7 and 13 bases, as labelled.\nFor the two-state model, as well as the results for the sequences\nin Eqs.\\ (\\ref{7 bases}) and (\\ref{13 bases}) (lines (a) and (d)),\nsequences corresponding to the other two arms of the Holliday junction\n(Figure \\ref{HJ schematic}) are considered.\nOnly one line is shown for the umbrella sampling results, because A-T and G-C\nhave the same binding energy in our model.\nTemperatures in our model are converted to ${\\rm^o}$C using the same mapping given in Section II A.}\n\\label{2 state}\n\\end{figure} \n\n In Figure \\ref{2 state}, we compare our melting curves to those predicted by a simple two-state model,\\cite{Everaers2007} using the same mapping of the reduced temperature as in Section \\ref{model}. In the two-state model the molar concentrations of product (AB) and reactants (A,B) are given by the equilibrium relation: \n\\begin{equation}\n\\frac{\\left[{\\rm AB }\\right]}{\\left[{\\rm A} \\right] \\left[{\\rm B}\\right]} = \\exp{\\left({\\frac{-\\Delta H_0 + T \\Delta S_0}{\\rm{k_B}\\it T}}\\right)},\n\\label{two state model}\n\\end{equation}\nwhere $\\Delta H_0$ and $\\Delta S_0$ are assumed to be constants which depend only on the strand sequences and the salt concentration (we take $\\rm{[Na^+}] = 0.445\\rm{M}$ as in Section \\ref{model}). \nWe use the enthalpy and entropy changes of duplex formation calculated by ``HyTher\",\\cite{Hyther} a program that estimates these values using the ``unified oligonucleotide nearest neighbour parameters\".\\cite{SantaLucia1998, Peyret1999} \nThe authors claim that the thermodynamic parameters predicted by HyTher give the melting temperature $T_{\\rm m}$ (the temperature at which the fraction of bonded strands is 1\/2)\nof a duplex to within a standard error of $\\pm2.2^{\\rm{o}}\\rm{C}$.\\cite{SantaLucia1998}\nFigure \\ref{2 state} shows that our system reflects the melting temperatures predicted by the two-state model with reasonable accuracy, excepting sequence dependent effects which are not included in our model, because the interaction energies \nbetween A-T and C-G complementary base pairs have for simplicity been taken to be the same. The widths of transitions are seen to be of the same order, but slightly larger for our model. \nThis feature, which is typical of coarse-grained models,\\cite{Knotts2007} indicates that the degree of entropy loss on hybridization is too small in our model, \nand is due to a failure to accurately incorporate all degrees of freedom which become frozen on hybridization. \nHowever, the agreement is sufficiently good that the basic features of physical DNA assembly should be reproducible.\n\n\\begin{figure*}\n\\begin{center}\n\\includegraphics[width=15cm]{Fig6.eps}\n\\end{center}\n\\caption{(Colour online) Snapshots illustrating four stages in the process of displacement. \n(a) A third strand binds to a misbonded pair. \n(b) The third strand is prevented from forming a complete duplex by the misbond. \n(c) Thermal fluctuations cause bonds in the misbonded structure to break and be replaced by the correct duplex. \n(d) The misbonded strand is displaced and the correct duplex is formed.}\n\\label{displacement}\n\\end{figure*}\n\nA further satisfying feature of the model is that `displacement' was observed on several occasions. This process, during which a misbonded pair of strands is broken up by a third strand, is illustrated in Figure \\ref{displacement}. The third strand is able to bond to the pair, as some bases are free in the misbonded structure. \nThermal fluctuations allow the new strand to bond to sites previously involved in misbonding, in a process known as `branch migration'. Eventually one of the misbonded strands is completely displaced, leaving a correct duplex and an isolated single strand. This behaviour is observed in real DNA systems, and is the driving mechanism of some nanomachines \\cite{Yurke2000} and DNA catalyzed reactions.\\cite{Yin2008, Zhang2007}\n\n\\begin{figure}\n\\begin{center}\n\\includegraphics[width=8.4cm]{Fig7.eps}\n\\end{center}\n\\caption{(Colour online) A schematic diagram showing the sequences of the strands used in our Holliday junction simulations, and the alternative bound states that are possible: (a) the square planar configuration and (b) the $\\chi$-stacked form.}\n\\label{HJ schematic}\n\\end{figure}\n\n\\subsection{Holliday Junction}\n\\label{Holliday Junction}\nEncouraged by the above results,\nwe next apply the model to the formation of a Holliday junction. \nHolliday junctions consist of four single strands which bind to form a four-armed cross. \nIn our case we consider a Holliday junction with two long arms (13 bases long) and two short arms (7 bases long). \nWe use the experimental base ordering of Malo {\\it et al.}\\cite{MaloThesis} with the `sticky ends' removed. \n(These sticky ends consist of six unpaired bases on the end of arms and their purpose is to allow the Holliday junctions to bond together to form a lattice). \nThe sequences of the four DNA strands and schematic diagrams of the \npossible junctions that they can form are shown in Figure \\ref{HJ schematic}.\n\nInitially we studied a system of 20 strands (five of each type) that has the potential to form five separate junctions. \nWe use a concentration of $1.56 \\times 10^{-5}$ molecules\\,$l^{-3}$\n(which corresponds to $1.04 \\times 10^{-4}$M). \nThe results are displayed in Figure \\ref{20mers}. \n\n\\begin{figure}\n\\includegraphics[width=6.0cm,angle=-90]{Fig8.eps}\n\\caption{(Colour online) \nA comparison of the kinetics and thermodynamics for a system of 20 strands that \ncan potentially form five Holliday junctions, where the MC simulations\nare initiated from a purely single-stranded configuration. \nThe MC results (lines with data points) are the final yield of Holliday junctions, and the fraction of strands involved in a correctly-formed long ($\\alpha$) or \nshort ($\\beta$) arm, or in misbonding, as labelled.\nThe results are averages over five runs of length $10^{9}$ steps per strand.\nFor comparison, the equilibrium probabilities of being in a $\\alpha$-bonded dimer\nand a Holliday junction are also plotted, along with the equilibrium probability of \nbeing in a $\\beta$-bonded dimer if the longer arms are not allowed to hybridize.\n}\n\\label{20mers}\n\\end{figure}\n\nThe results are as expected for the bonding of the longer arms (which we now describe as `$\\alpha$-bonding'). \nThe yield again displays the characteristic non-monotonic dependence on temperature. \nWe obtain very few complete junctions, however, which is due to two effects. \nFirstly, each simulation is performed at constant temperature, which means the hierarchical route to assembly is less favoured than when the system is cooled, as in the experiments.\\cite{MaloThesis,Malo2005}\nWhen the system is gradually cooled, Figure \\ref{20mers} suggests that at around $T_{\\rm m}(\\alpha) =0.111$ we would expect to find a region in which only $\\alpha$-bonded dimers were stable with respect to ssDNA. \nIf the cooling was sufficiently slow on the timescale of bonding, all strands would form $\\alpha$-structures at around $T_{\\rm m}(\\alpha)$. \nAt lower temperatures, when the Holliday junction becomes stable with respect to the $\\alpha$-bonded dimers, many competing minima would then be inaccessible to the system as they would require the disassociation of stable $\\alpha$-bonded pairs. \nThe free energy landscape of two $\\alpha$-structures forming a Holliday junction is consequentially much simpler than that of four single strands forming a junction at a given temperature. \nTherefore, one expects the yield for self-assembly at constant temperature to be \nlower than when the system is cooled, because there is only a relatively narrow \ntemperature window between where the Holliday junction becomes stable and misbonded\nconfigurations start to appear. Indeed, the shorter arms are only marginally more \nstable than some competing minima, as evidenced by \nthe rise in misbonded structures in Fig.\\ \\ref{20mers} at temperature just below \nwhere $\\beta$-bonded structures first appear.\n\n\\begin{figure}\n\\begin{center}\n\\includegraphics[width=8.4cm]{Fig9.eps}\n\\end{center}\n\\caption{(Colour online) Snapshot showing five Holliday junctions formed at $T=0.0842$ after \n$5.67 \\times 10^8$ MC steps per strand. Again, the backbone colour indicates strand type (1: red, 2: grey,\n 3: orange, 4: yellow) where numbers refer to Figure \\ref{HJ schematic}}\n\\label{5 HJs}\n\\end{figure}\n\nSecondly, even in the temperature range where Holliday junction formation is \nnot hindered by the formation of misbonded configurations, the yield is low\nbecause the Metropolis MC algorithm artificially reduces the diffusion of bound \npairs, and hence the likelihood that two pairs of $\\alpha$-bonded strands come together to form a junction is also reduced.\nThis is because the acceptance probability of trial moves for bonded strands is much lower than for isolated strands \\cite{Luijten2006}, due to the energy penalty associated with trying to move a bound pair apart. \n\n\\begin{figure}\n\\includegraphics[width=6.0cm,angle=-90]{Fig10.eps}\n\\caption{(Colour online) The yields of Holliday junctions (HJ) and misbonded configurations \nfor MC simulations, where the initial configuration was a pair of \n$\\alpha$-bonded dimers. For comparison, \nthe equilibrium probabilities of being in a $\\alpha$-bonded dimer \nand a Holliday junction are also plotted.\nThe results are averages over five runs of length \n$7.5 \\times 10^8$ steps per strand.\n}\n\\label{HJ thermo}\n\\end{figure}\n\nInterestingly, examination of the equilibrium lines in Figure \\ref{20mers} shows that the Holliday junctions are actually stable at a higher temperature than the individual shorter arms. \nThis is because the total loss of entropy when two $\\alpha$-bonded dimers bind together is considerably less than that for two short arms in isolation (as fewer translational degrees of freedom are lost), whereas the energy change is comparable. \nThus, there is a small temperature window at $T^*\\approx 0.1$ where hierarchical assembly can occur at constant temperature as the short arms are only stable once $\\alpha$-bonding has taken place. \nHowever, due to the deficiencies in the MC simulations mentioned above, the yield\nof Holliday junctions in this region is practically zero. Instead, the maximum\nyield of Holliday junctions occurs at lower temperatures where non-hierarchical\npathways that proceed by the addition of single strands become feasible.\n\nThe above simulations were only able to successfully model the first stage of \nthe Holliday junction assembly, namely the formation of $\\alpha$-bonded dimers. \nTo probe the second stage of assembly, we must first make two modifications to \nour simulation approach to overcome the two deficiencies mentioned above. \nFirstly, we study systems initially consisting of pairs of $\\alpha$-bonded strands, which we assume have successfully formed at some higher temperature---this is \nreasonable given the results of our earlier simulations.\nSecondly, we also include simple local cluster moves in addition to those which move only one strand, i.e.\\ translations, rotations and bending of pairs of $\\alpha$-bonded strands. \nWith these changes incorporated, we simulate the same system for $7.5 \\times 10^8$ steps per strand at a range of temperatures below $T_{\\rm m}(\\alpha)$. \nIt should be noted that due to a change in the size of typical moves, one move per strand now corresponds to approximately 10ps.\n\nWe find that Holliday junctions form over a wide range of intermediate temperatures, whilst kinetic traps at low temperature lead to incomplete bonding and consequently to the possibility of forming large clusters. A typical result from the high-yield regime is shown in Figure \\ref{5 HJs}. \nAs fully-bonded Holliday junctions are essentially inert, \nit is reasonable to analyse their assembly behaviour by considering only one \njunction. The smaller system size has the effect of increasing the assembly rate, because the strands have less distance to diffuse, but does not affect the basic assembly mechanism. \nWe therefore simulated systems consisting of two $\\alpha$-bonded pairs with the same concentration as above. \n\nWe also introduced some modifications to the the umbrella sampling scheme in order\nto more efficiently compute the thermodynamics of the second-stage of \nHolliday junction formation. \nAs well as cluster moves, we also introduced a `tethering' component in the \nweighting function $W(Q)$. \nWe introduce a length $r_{\\rm min}$ that corresponds to the shortest distance between any pair of backbone sites on different strands. \nWe then split $Q=0$ into two regions: we weight those states with $r_{\\rm min} < 3l$ with $W=1$ but for $r_{\\rm min} \\geq 3l$ we use $W=0.1$. \nThis enables us to increase the rate of transitions between $Q=0$ and 1, and reduces the time spent \nsimply simulating the diffusion of $\\alpha$-bonded dimers waiting for a collision to occur.\n\nThe MC results are plotted in Figure \\ref{HJ thermo} along with \nthe equilibrium results obtained from umbrella sampling.\nWith the cluster moves in place, we now see a high yield of Holliday junctions\nand a broad maximum in the yield as a function of temperature.\nThe hierarchical pathway has the effect suggested earlier. \nNamely, the temperature window over which correct formation can occur is \nvastly increased, as the most significant competing minima are inaccessible because their formation would require dissociation of the $\\alpha$-bonded pairs. \n\nThe model is therefore consistent with the experimentally observed hierarchical assembly of Holliday junctions as the system is cooled.\\cite{Malo2005, MaloThesis} \nIt should be noted, however, that the junctions in our model usually form in the `square planar' as opposed to the `$\\chi$-stacked' shape (Figure \\ref{HJ schematic}) that is observed under normal experimental conditions. \nThe preference for one structure is a subtle consequence of the concentration of cations and the precise helical geometry of DNA.\\cite{Ortiz-Lombardia1999} \nThis level of detail is not included in our coarse-grained model, so it is not surprising that it cannot reproduce the preference for $\\chi$-stacked structures.\nMoreover, it is relatively easy to see why in our model, which forms \n`ladders' rather than helices, a planar geometry is preferred for the junction.\n\n\\begin{figure}\n\\includegraphics[width=8.4cm]{Fig11.eps}\n\\caption{Thermodynamics for the formation of a single Holliday junction.\n(a) Heat capacity curves for two $\\alpha$-bonded dimers forming a Holliday junction (HJ) \nand four strands forming two $\\alpha$-bonded dimers, as labelled.\n(b) Free energy profiles for the formation of a Holliday junction from two $\\alpha$-bonded dimers \nat different temperatures, as labelled. \n$Q$ represents the total number of correct bonds in the short arms of the junction.\n}\n\\label{thermo_HJ}\n\\end{figure}\n\nSome of the equilibrium thermodynamic properties associated with the formation\nof a Holliday junction are shown in Figure \\ref{thermo_HJ}. \nIn particular, Fig.\\ \\ref{thermo_HJ}(b) shows the free energy profile for the \nformation of a Holliday junction from two $\\alpha$-bonded pairs. \nThe initial peak and subsequent drop is very similar to that for the duplexes and can be accounted for in the same way. \nHowever, the formation of the two arms is not like the zipping up of a \n14-base duplex, because there is much more relative freedom of movement for \nthe bases on either side of the $\\alpha$-bonded sections in the dimers\nthan for consecutive bases on single-stranded DNA.\nThus, there is a rise between $M=7$ and $M=8$ that is a result of the entropy \npenalty of bringing together the two ends to make the second short arm. \nWe note that the penalty is much smaller than the initial cost of bringing the two $\\alpha$-bonded pairs together, and as a result, \nthe value of $T_{\\rm{m}}$ for the junction is higher than for the short arms \nin isolation, as noted earlier.\n\nAn interesting feature of Figure \\ref{thermo_HJ}(b) is the plateau between $Q=6$ and $Q=7$. \nIn general, when two $\\alpha$-bonded pairs meet to form one short arm, there is an entropic penalty associated with the excluded volume that the remaining bases in the $\\alpha$-structures represent to each other. \nThis excluded volume is a large fraction of the total available space if one complete short arm is formed, so that there are no free monomers between the short arm and the $\\alpha$-bonded sections. As a consequence, there is not the usual free energy benefit from forming the final bond in the short arm (the one closest to the centre of the Holliday junction), as the excluded volume penalty is large and those states that are allowed involve distortion of the backbones and bonds near the centre of the Holliday junction. \nAlthough the details of this free energy penalty and the other features in \nFig.\\ \\ref{thermo_HJ}(b) will depend on the exact geometry of the system, \nwe expect the calculated free energy profile to be representative of that \nfor real DNA.\n\nIt is possible to extend the two-state model discussed in Section \\ref{Duplex Formation} to the formation of a Holliday junction by considering the concentrations of all four isolated strands, the two $\\alpha$-bonded intermediates and the junction itself. \nWe assume Eq.\\ (\\ref{two state model}) holds for every possible transition, use the same thermodynamic parameters as before and apply conservation of total strand number. To estimate $\\Delta H_0$ and $\\Delta S_0$ associated with the formation of a Holliday junction, we construct a single strand by linking the ends of the oligonucleotides together with four non-bonding bases. The thermodynamic parameters associated with the folding of this structure are predicted by ``UNAFold''.\\cite{Markham2008} \nThe correction for the fact that our strands are not connected by loops is discussed by Zuker.\\cite{Zuker2003} \nThis leaves five simultaneous equations (assuming perfect stochiometry) which can be solved numerically.\n\n\\begin{figure}\n\\includegraphics[width=6.2cm,angle=-90]{Fig12.eps}\n\\caption{(Colour online) Bulk equilibrium probability of strands being in a Holliday junction (HJ) or\nan $\\alpha$-bonded dimer computed by umbrella sampling (solid lines) and by \nthe extended two-state model (dashed lines), where lines (a) and (b) represent the two possible $\\alpha$-bonded dimers.\n}\n\\label{etsm HJ}\n\\end{figure}\n\nFigure \\ref{etsm HJ} compares this extended two-state model (ETSM) with the bulk thermodynamics predicted by umbrella sampling (using the same temperature scaling as before). \nETSM predictions for both stages of Holliday junction formation agree well with our results, which again supports our hypothesis that much of the physics of self-assembly can be reproduced by a simple coarse-grained model. The extra width of the transitions in our model occurs for the same reasons as mentioned in Section \\ref{Duplex Formation} when discussing Fig.\\ \\ref{2 state}. \n\n\\begin{figure}\n\\includegraphics[width=6.1cm,angle=-90]{Fig13.eps}\n\\caption{(Colour online) Simulation results for the badly-designed Holliday \njunction of Section \\ref{negative}, where the initial configuration was a pair \nof $\\alpha$-bonded dimers. The lines with data points give the yield of \ncorrectly-formed junctions and misbonded configurations, as labelled.\nFor comparison the solid line gives the equilibrium probability that the \nwell-designed sequences of Section \\ref{Holliday Junction} adopt a \nHolliday junction.}\n\\label{thermo neg}\n\\end{figure}\n\n\\begin{figure}\n\\begin{center}\n\\includegraphics[width=7.4cm]{Fig14.eps}\n\\end{center}\n\\caption{(Colour online) Example of a competing minimum for a badly designed Holliday junction. The snapshot is \ntaken from a simulation at $T^*=0.0936$. \n}\n\\label{misbond neg}\n\\end{figure}\n\n\\subsection{Negative Design}\n\\label{negative}\nThe hierarchical pathway for the formation of the Holliday junction is one \naspect of the sequence design that aids the formation of the correct structure.\nThe experimental base ordering of the Holliday junction, however, was also chosen to minimize the number of competing structures---a typical example of `negative design'.\\cite{Doye04b} \nWe illustrate the importance of such negative design by considering a badly-designed junction, where the complementary seven-base sections consist of just one base type each. \nWe simulate a system of two $\\alpha$-bonded pairs with the short arms so modified \nunder the same conditions as for Fig.\\ \\ref{HJ thermo} and \nthe results are shown in Figure \\ref{thermo neg}. \nAlthough there is some probability of forming the correct junction, the simulations\nare dominated by misbonded junctions, such as the one depicted in Figure \\ref{misbond neg}.\nAlthough these competing structures are energetically less stable than the target\njunction because of the presence of unpaired bases at the `dangling' ends,\nthey are readily accessible, because the likelihood that the first bonds formed\nbetween two $\\alpha$-bonded pairs are in the same registry as the target structure \nis low. The yield of the correct Holliday junctions will then depend upon how\nreadily the system is able escape from these malformed junctions. Clearly,\nthis process is slow on the time scales of the current simulations, and is \nalso likely to hinder the location of the target structure in experiment.\n\n\\section{Discussion}\nIn this paper we have introduced a simple coarse-grained model of DNA in order to test the feasibility of modeling the self-assembly of DNA nanostructure by \nMonte Carlo simulations. Any such model involves a trade-off between detail and \ncomputational simplicity, and here we deliberately chose to keep the model as simple\nas possible in order to give us the best chance of being able to probe the time\nscales relevant to self-assembly. The model involves just two interaction sites\nper nucleotide. \n\nThe results from our model are very encouraging. Firstly, we have shown that\nusing our model it is feasible to model the self-assembly of both DNA duplexes\nand a Holliday junction. The latter represents, to the best of our knowledge, the\nfirst example of the simulation of the self-assembly of a DNA structure beyond a \nduplex. Secondly, the model succeeds in reproducing many of the known thermodynamic\nand dynamic features of this self-assembly. \nFor example, the equilibrium melting curves agree well with those predicted by \nthe nearest-neighbour two-state model,\\cite{SantaLucia1998} which is known\nto predict melting temperatures very accurately. \nThe model is also able to capture important dynamical \nphenomena such as displacement.\n\nThirdly, by analysing the thermodynamic and dynamic constraints on assembly, we \nhave been able to gain some important physical insights into the nature of DNA\nself-assembly and how to control it. For example, the optimal conditions for \nself-assembly are in the temperature range just below the melting temperature of the\nthe target structure, where this structure is the only one stable with respect to \nthe precursors, be they ssDNA or some intermediate in a hierarchical assembly \npathway. At lower temperatures, misbonded configurations can be formed that act \nas kinetic traps and reduce the assembly yield.\nSimilar trade-offs between the thermodynamic driving force and \nkinetic accessibility have been previously seen in a variety of self-assembling\nsystems,\\cite{Brooks06,Hagan2006,Wilber2007,Rapaport08,Whitelam08} \nand also give rise to a maximum in the yield near to and below\nthe temperature at which the target structure becomes stable.\n\nWe have also seen how hierarchical self-assembly through cooling can be a \nparticularly useful strategy to aid self-assembly, because the formation of stable\nintermediates at higher temperatures simplifies the free energy landscape for the\nassembly of the next stage in the hierarchy by reducing the number of misbonded \nconfigurations available to the system. This simplification of the energy\nlandscape is likely to be a general feature of hierarchical self-assembly.\n\nThus, our results have confirmed the utility of using coarse-grained DNA models to study the self-assembly of DNA nanostructures, and supported our hypothesis that much of the physics can be explained by describing DNA as a semi-flexible polymer with selective attractive interactions. The model's success in forming junctions in reasonable computational time suggests that it will be possible to develop further models that have an increased level of detail, but which can still access the time scales relevant to self-assembly.\n\nThe model has also highlighted some features which it would be advantageous to include in such models. For example, greater accuracy in the details of oligonucleotide geometry, particularly the helicity of dsDNA, would allow features such as the characteristically long persistence length of hybridized strands to be reproduced and give the appropriate degree of rigidity to simulated nanostructures. Such improvement might also allow more complicated motifs to be accounted for, such as the preference for $\\chi$-stacked Holliday junctions that the current model could not reproduce. \n\nIt should be noted that if one is to introduce helicity in a physically\nreasonable way it should also allow for ssDNA to undergo a stacking transition \nto a helical form. \nThis transition may play a significant role in the thermodynamics and kinetics of self-assembly.\\cite{Holbrook1999}\nPreviously proposed coarse-grained DNA models that incorporate helicity have not been designed to accurately reproduce this feature. \nIncorporating extra degrees of freedom which are relevant to the stacking transition, such as the rotation of the base with respect to the sugar-base bond, may also help to increase the entropy change on hybridization and hence make the transition narrower as required.\n\nThe approximation to diffusive dynamics provided by the local move Metropolis Monte Carlo algorithm could also be improved. \nCurrently the `local' moves involve displacing, rotating or bending entire strands or pairs of strands---these effectively constitute cluster moves of groups of strongly bound nucleotides, and result in slow relaxation and translation times within bound structures. \nMore realistic dynamics may be achievable by considering trial moves of individual nucleotides, and incorporating cluster moves in a more systematic fashion, such as in the `virtual move' MC algorithm proposed by Whitelam and Geissler.\\cite{Whitelam2007,Whitelam08} \n\nOne potential issue with any coarse-graining is how it preserves the different\ntime scales in a system.\nIn Section \\ref{Monte Carlo Simulation} we assigned an approximate mapping \nbetween the number of Monte Carlo steps and physical time based upon comparison \nof diffusion coefficients. There are, however, other important time scales in the \nsystem, such as the time scale for the internal dynamics of an isolated strand and \nthe time scale over which the `zipping-up' of two strands occurs after a bond has been formed. \nComparisons of experimental diffusion coefficients \\cite{Lapham1997} and \nmelting and bubble formation from molecular dynamics \nsimulations \\cite{Drukker2001,Knotts2007} suggest a large separation in time scale \nbetween diffusion-limited processes and those that rely on the dynamics of \nindividual nucleotides. \nEncouragingly, we observe a similar time scale separation in our model:\nzipping-up and thermal relaxation of isolated strands occur over times scales \nshorter than $10^5$ steps per strand, whereas association typically required on the \norder of $10^7$ to $10^8$ steps per strand near the melting temperature \n(corresponding to tens or hundreds of microseconds). Furthermore, we would\nargue that it is this time scale separation, and not the precise ratios of the\nrelevant rate constants, that it is important to reproduce in self-assembly \nsimulations.\n\nWe should also note that the mapping of the diffusion constants between the model\nand experiment will not necessarily ensure that the rate of association is \naccurate in our model, because although the frequency of collisions in our model \nshould be correct, \nthere is also the contribution\nto the association rate from the probability that a collision will lead to \nsuccessful association. That we can reproduce the thermodynamics of the DNA melting transitions implies that the rates of association and disassociation have the right\nratio, but not that they necessarily have the correct absolute value. \nFor example, it is conceivable that helicity (both in dsDNA and possibly in ssDNA),\nwhich is not included in the current model, will influence the likelihood that a \ncollision is successful.\n\n\n\\begin{acknowledgments}\nThe authors are grateful for financial support from the EPSRC \nand the Royal Society. We also wish to acknowledge helpful discussions\nwith Jonathan Malo, John Santalucia Jr and Michael Zuker.\n\\end{acknowledgments}\n\n\n","meta":{"redpajama_set_name":"RedPajamaArXiv"}} +{"text":"\\section{Introduction}\n\n\n\nLet $M$ be a closed oriented smooth $d$-manifold. Let $D: H_*(M)\n\\xrightarrow{\\cong} H^{d-*}(M)$ be the Poincar\\'e duality map. Following a practice in string topology, we shift the homology grading downward by $d$ and let $\\mathbb H_{-*}(M)=H_{d-*}(M)$. The Poincar\\'e duality now takes the form $D:\\mathbb H_{-*}(M) \\xrightarrow{\\cong} H^{*}(M)$. For a homology element $a$, let $|a|$ denote its \n$\\mathbb H_*$-grading of $a$. \n\nThe intersection product $\\cdot$ in homology is defined as the Poincar\\'e dual of the cup product. Namely, for $a,b\\in \\mathbb H_*(M)$, $D(a\\cdot b)=D(a)\\cup D(b)$. If $\\alpha\\in H^*(M)$ is dual to $a$, then $\\alpha\\cap b=a\\cdot b$, and its Poincar\\'e dual is $\\alpha\\cup D(b)$. Thus, through Poincar\\'e duality, the intersection product, the cap product, and the cup product are all the same. In particular, the cap product and the intersection product commute:\n\\begin{equation}\n\\alpha\\cap (b\\cdot c)=(\\alpha\\cap b)\\cdot c\n=(-1)^{|\\alpha||b|}b\\cdot(\\alpha\\cap c). \n\\end{equation}\nIn fact, the direct sum $H^*(M)\\oplus \\mathbb H_*(M)$ can be made into a graded commutative associative algebra with unit, given by $1\\in H^0(M)$, using the cap and the cup product.\n\nFor an infinite dimensional manifold $N$, there is no longer\nPoincar\\'e duality, and geometric intersections of finite dimensional\ncycles are all trivial. However, cap products can still be nontrivial\nand the homology $H_*(N)$ is a module over the cohomology ring\n$H^*(N)$.\n\nWhen the infinite dimensional manifold $N$ is a free loop space $LM$\nof continuous maps from the circle $S^1=\\mathbb R\/\\mathbb Z$ to $M$,\nthe homology $\\mathbb H_*(LM)=H_{*+d}(LM)$ has a great deal more structure. As before, $|a|$ denotes the $\\mathbb H_*$-grading of a homology element $a$ of $LM$. Chas and\nSullivan \\cite{CS} showed that $\\mathbb H_*(LM)$ has a degree preserving associative graded\ncommutative product $\\cdot$ called the loop product, a\nLie bracket $\\{\\ ,\\ \\}$ of degree $1$ called the loop bracket\ncompatible with the loop product, and the BV operator $\\Delta$ of\ndegree $1$ coming from the homology $S^1$ action. These structures turn\n$\\mathbb H_*(LM)$ into a Batalin-Vilkovisky (BV) algebra. The purpose of this\npaper is to clarify the interplay between the cap product with cohomology elements and the BV structure in $\\mathbb H_*(LM)$.\n\n\n\nLet $p: LM \\rightarrow M$ be the base point map\n$p(\\gamma)=\\gamma(0)$ for $\\gamma\\in LM$. For a cohomology class\n$\\alpha\\in H^*(M)$ in the base manifold, its pull-back $p^*(\\alpha)\\in\nH^*(LM)$ is also denoted by $\\alpha$. Let $\\Delta: S^1\\times LM\n\\longrightarrow LM$ be the $S^1$-action map. This map induces a degree $1$ map $\\Delta$ in homology given by $\\Delta a=\\Delta_*([S^1]\\times a)$\nfor $a\\in \\mathbb H_*(LM)$. For a cohomology class $\\beta\\in H^*(LM)$, the formula \n$\\Delta^*(\\beta)=1\\times\\beta+\\{S^1\\}\\times\\Delta\\beta$ defines a degree $-1$ map $\\Delta$ in cohomology, where $\\{S^1\\}$ is the fundamental cohomology class. Although we use the same notation $\\Delta$ in three different but closely related situations, what is meant by $\\Delta$ should be clear in the context. \n\n\\begin{Theorem A} Let $b,c\\in \\mathbb H_*(LM)$. \nThe cap product with $\\alpha\\in H^*(M)$ graded commutes with the loop product. Namely \n\\begin{equation}\n\\alpha\\cap(b\\cdot c)=(\\alpha\\cap b)\\cdot\nc=(-1)^{|\\alpha||b|}b\\cdot(\\alpha\\cap c).\n\\end{equation}\n\nFor $\\alpha\\in H^*(M)$, the cap product with $\\Delta\\alpha\\in H^*(LM)$\nacts as a derivation on the loop product and the\nloop bracket\\textup{:}\n\\begin{align}\n(\\Delta\\alpha)\\cap(b\\cdot c)=(\\Delta\\alpha\\cap b)\\cdot c+\n(-1)^{(|\\alpha|-1)|b|}b\\cdot (\\Delta\\alpha\\cap c), \\\\\n(\\Delta\\alpha)\\cap\\{b,c\\}=\\{\\Delta\\alpha\\cap b,c\\}+\n(-1)^{|\\alpha|-1)(|b|+1)}\\{b,\\Delta\\alpha\\cap c\\}.\n\\end{align}\n\nThe operator $\\Delta$ acts as a derivation on the cap product. Namely, for $\\alpha\\in H^*(M)$ and $b\\in \\mathbb H_*(LM)$.\n\\begin{equation}\n\\Delta(\\alpha\\cap b)=\\Delta\\alpha\\cap b + (-1)^{|\\alpha|} \\alpha\\cap\n\\Delta b.\n\\end{equation}\n\\end{Theorem A}\n \nWe recall that in the BV algebra $\\mathbb H_*(LM)$, the following identities\nare valid for $a,b,c\\in \\mathbb H_*(LM)$ \\cite{CS}:\n\\begin{gather}\n\\Delta(a\\cdot b)=(\\Delta a)\\cdot b + (-1)^{|a|}a\\cdot \\Delta b +\n(-1)^{|a|}\\{a,b\\} \n\\tag{BV identity} \\\\ \n\\{a, b\\cdot c\\} =\\{a,b\\}\\cdot c + (-1)^{|b|(|a|+1)}b\\cdot\\{a,c\\} \n\\tag{Poisson identity} \\\\ \na\\cdot b=(-1)^{|a||b|}b\\cdot a,\\qquad\n\\{a,b\\}=-(-1)^{(|a|+1)(|b|+1)}\\{b,a\\}\n\\tag{Commutativity} \\\\\n\\{a,\\{b,c\\}\\}=\\{\\{a,b\\},c\\}+(-1)^{(|a|+1)(|b|+1)}\\{b,\\{a,c\\}\\}\n\\tag{Jacobi identity}\n\\end{gather} \nHere, $\\deg a\\cdot b=|a|+|b|, \\deg \\Delta a=|a|+1$, and $\\deg\\{a,b\\}=|a|+|b|+1$. \n\nWe can extend the loop product and the loop bracket in $\\mathbb H_*(LM)$ to\ninclude $H^*(M)$ in the following way. For $\\alpha\\in H^*(M)$ and\n$b\\in \\mathbb H_*(LM)$, we define the loop product and the loop bracket of \n$\\alpha$ and $b$ by \n\\begin{equation}\n\\alpha\\cdot b=\\alpha\\cap b, \\qquad\n\\{\\alpha,b\\}=(-1)^{|\\alpha|}(\\Delta\\alpha)\\cap b.\n\\end{equation} \n\nFurthermore, the BV structure in $\\mathbb H_*(LM)$ can be extended to the direct sum $A_*=H^*(M)\\oplus \\mathbb H_*(LM)$ by defining the BV operator $\\boldsymbol\\Delta$ on $A_*$ to be trivial on $H^*(M)$ and to be the usual homological $S^1$ action $\\Delta$ on $\\mathbb H_*(LM)$. Here in $A_*$, elements in $H^k(M)$ are regarded as having homological degree $-k$. \n\n\\begin{Theorem B} The direct sum $H^*(M)\\oplus \\mathbb H_*(LM)$ has a structure of a BV algebra. In particular, for $\\alpha\\in H^*(M)$ and $b,c\\in \\mathbb H_*(LM)$, the following form of\nPoisson identity and the Jacobi identity hold\\textup{:}\n\\begin{gather} \n\\begin{split}\n\\{\\alpha\\cdot b,c\\}&=\\alpha\\cdot\\{b,c\\}+\n(-1)^{|b|(|c|+1)}\\{\\alpha,c\\}\\cdot b \\\\ &=\\alpha\\cdot\\{b,c\\} +\n(-1)^{|\\alpha||b|} b\\cdot\\{\\alpha,c\\},\n\\end{split} \\\\\n\\{\\alpha,\\{b,c\\}\\}=\\{\\{\\alpha,b\\},c\\} +\n(-1)^{(|\\alpha|+1)(|b|+1)}\\{b,\\{\\alpha,c\\}\\}.\n\\end{gather}\n\\end{Theorem B}\n\nAll the other possible forms of Poisson and Jacobi identities are\nalso valid, and the above two identities are the most nontrivial\nones. These identities are proved by using standard properties of the\ncap product and the BV identity above in $\\mathbb H_*(LM)$ relating the BV operator $\\Delta$ and the loop bracket $\\{\\,,\\,\\}$, but without using Poisson identities nor Jacobi identities in the BV algebra $\\mathbb H_*(LM)$.\n\nThe above identities may seem rather surprising, but they become\ntransparent once we prove the following result.\n\n\\begin{Theorem C} For $\\alpha\\in H^*(M)$, \nlet $a=\\alpha\\cap [M]\\in \\mathbb H_*(M)$ be its Poincar\\'e dual. Then for $b\\in \\mathbb H_*(LM)$,\n\\begin{equation}\\label{cap}\n\\alpha\\cap b=a\\cdot b,\\qquad (-1)^{|\\alpha|}\\Delta\\alpha\\cap\nb=\\{a,b\\}.\n\\end{equation} \nMore generally, for cohomology elements $\\alpha_0,\\alpha_1,\\dotsc\n\\alpha_r\\in H^*(M)$, let $a_0, a_1,\\dotsc a_r\\in \\mathbb H_*(M)$ be their Poincar\\'e duals. Then for $b\\in \\mathbb H_*(LM)$, we have\n\\begin{equation}\\label{composition of derivations}\n(\\alpha_0\\cup \\Delta\\alpha_1\\cup\\dotsm \\cup \\Delta\\alpha_r)\\cap b\n=(-1)^{|a_1|+\\dotsb+|a_r|}a_0\\cdot\\{a_1,\\{a_2,\\dotsc \\{a_r,b\\}\\dotsb \\}\\}.\n\\end{equation}\n\\end{Theorem C}\n\nSince the cohomology $H^*(M)$ and the homology $\\mathbb H_*(M)$ are isomorphic through Poincar\\'e duality and $\\mathbb H_*(M)$ is a subring of $\\mathbb H_*(LM)$, the first formula in \\eqref{cap} is not surprising. However, the main difference between $H^*(M)$ and $\\mathbb H_*(M)$ in our context is that the homology $S^1$ action $\\Delta$ is trivial on $\\mathbb H_*(M)\\subset \\mathbb H_*(LM)$, although cohomology $S^1$ action $\\Delta$ is nontrivial on $H^*(M)$ and is related to loop bracket as in \\eqref{cap}. \n\nTheorem A and Theorem C describes the cap product action of the cohomology $H^*(LM)$ on the BV algebra $\\mathbb H_*(LM)$ for most elements in $H^*(LM)$. For example, for $\\alpha\\in H^*(M)$, the cap product with $\\Delta\\alpha$ is a derivation on the loop algebra $\\mathbb H_*(LM)$ given by a loop bracket, and consequently the cap product with a cup product $\\Delta\\alpha_1\\cup\\cdots\\cup\\Delta\\alpha_r$ acts on the loop algebra as a composition of derivations, which is equal to a composition of loop brackets, according to \\eqref{composition of derivations}. If $H^*(LM)$ is generated by elements $\\alpha$ and $\\Delta\\alpha$ for $\\alpha\\in H^*(M)$ (for example, this is the case when $H^*(M)$ is an exterior algebra, see Remark \\ref{exterior algebra}), then Theorem C gives a complete description of the cap product with arbitrary elements in $H^*(LM)$ in terms of the BV algebra structure in $\\mathbb H_*(LM)$. However, $H^*(LM)$ is general bigger than the subalgebra generated by $H^*(M)$ and $\\Delta H^*(M)$. \n\nSince $\\mathbb H_*(LM)$ is a BV algebra, in view of Theorem C, the validity of Theorem B may seem obvious. However, in the proof of Theorem B, we only used standard properties of the cap product and the BV identity. In fact, Theorem B gives an alternate elementary and purely homotopy theoretic proof of Poisson and Jacobi identities in $\\mathbb H_*(LM)$, when at least one of the elements $a,b,c$ are in $\\mathbb H_*(M)$. Similarly, Theorem C gives a purely homotopy theoretic interpretation of the loop product and the loop bracket if one of the elements are in $\\mathbb H_*(M)$.\n\nOur interest in cap products in string topology comes from an\nintuitive geometric picture that cohomology classes in $LM$ are dual\nto finite codimension submanifolds of $LM$ consisting of certain loop\nconfigurations. We can consider configurations of loops\nintersecting in particular ways (for example, two loops having their base points in common), or we can consider a family of loops\nintersecting transversally with submanifolds of $M$ at\ncertain points of loops. In a given family of loops, taking the cap product with a cohomology class selects a subfamily of a certain loop configuration, which are ready for certain loop interactions. In this context, roughly speaking, composition of two interactions of loops correspond to the cup product of corresponding cohomology classes.\n\nThe organization of this paper is as follows. In section 2, we\ndescribe a geometric problem of describing certain family of intersection configuration of loops in terms of cap products. This gives a geometric motivation for the remainder of the paper. In section 3, we review the loop product in $\\mathbb H_*(LM)$ in detail from the point of view of the intersection product in $\\mathbb H_*(M)$. Here we pay careful attention to signs. In particular, we give a homotopy theoretic proof of graded commutativity in the BV algebra $\\mathbb H_*(LM)$, which turned out to be not so trivial. In section 4, we prove compatibility\nrelations between the cap product and the BV algebra structure, and\nprove Theorems A and B. In the last section, we prove Theorem C.\n\nWe thank the referee for numerous suggestions which lead to clarification and improvement of exposition. \n\n\n\n\n\n\\section{Cap products and intersections of loops}\n\nLet $A_1,A_2,\\dotsc A_r$ and $B_1,B_2,\\dotsc B_s$ be oriented closed\nsubmanifolds of $M^d$. Let $F\\subset LM$ be a compact family of\nloops. We consider the following question. \n\n\\smallskip\n\n\\textbf{Question} : Fix $r$ points $0\\le t_1^*,t_2^*,\\dotsc,t_r^*\\le\n1$ in $S^1=\\mathbb R\/\\mathbb Z$. Describe the homology class of the subset $I$ of the compact family $F$\nconsisting of loops $\\gamma$ in $F$ such that $\\gamma$ intersects\nsubmanifolds $A_1,\\dotsc A_r$ at time $t_1^*,\\dotsc t_r^*$ and\nintersects $B_1,\\dotsc B_s$ at some unspecified time.\n\n\\smallskip\n\nThis subset $I\\subset F$ can be described as follows. We consider the following diagram of an evaluation map and a projection map: \n\\begin{equation} \\label{eval}\n\\begin{CD}\n\\overset{s}{\\overbrace{(S^1\\times\\dotsb\\times S^1)}}\\times LM @>{e}>>\n \\overset{r}{\\overbrace{M\\times \\dotsb\\times M}}\\times\n\\overset{s}{\\overbrace{M\\times\\dotsb\\times M}} \\\\\n@V{\\pi_2}VV @. \\\\\nLM @. \n\\end{CD}\n\\end{equation}\ngiven by $e\\bigl((t_1,\\dotsc t_s),\\gamma\\bigr)\n=\\bigl(\\gamma(t_1^*),\\dotsc \\gamma(t_r^*), \\gamma(t_1), \\dotsc\n\\gamma(t_s)\\bigr)$. Then the pull-back set\n$e^{-1}(\\prod_iA_i\\times\\prod_jB_j)$ is a closed \nsubset of $S^1\\times\\dotsb\\times S^1\\times LM$. Let\n\\begin{equation*}\n\\tilde{I}=e^{-1}(\\prod_iA_i\\times \\prod_jB_j)\\cap \n(S^1\\times\\dotsb\\times S^1\\times F). \n\\end{equation*} \nThe set $I$ in\nquestion is given by $I=\\pi_2(\\tilde{I})$. We want to understand this set $I$ homologically, including multiplicity. Although $e^{-1}(\\prod_iA_i\\times\\prod_jB_j)$ is infinite dimensional, it has finite codimension in $(S^1)^r\\times LM$. So we work cohomologically.\n\nLet $\\alpha_i, \\beta_j\\in H^*(M)$ be cohomology classes dual to $[A_i], [B_j]$ for $1\\le i\\le r$ and $1\\le j\\le s$. Then the subset $e^{-1}(\\prod_iA_i\\times \\prod_jB_j)$ is dual to the cohomology class $e^*(\\prod_i\\alpha_i\\times\\prod_j\\beta_j)\\in H^*((S^1)^s\\times LM)$. Suppose the family $F$ is parametrized by a closed oriented manifold $K$ by an onto map $\\lambda:K \\longrightarrow F$ and let $b=\\lambda_*([K])\\in \\mathbb H_*(LM)$ be the homology class of $F$ in $LM$. Then the homology class of $\\tilde{I}$ in $(S^1)^s\\times LM$ is given by \n\\begin{equation}\n[\\tilde{I}]=e^*(\\prod_i\\alpha_i\\times\\prod_j\\beta_j)\\cap ([S^1\\times\\dotsb\\times S^1]\\times b). \n\\end{equation} \nNote that the homology class $(\\pi_2)_*([\\tilde{I}])$ represents the homology class of $I$ with multiplicity. \n\n\\begin{proposition}\\label{loop intersection} With the above notation, $(\\pi_2)_*([\\tilde{I}])$ is given by the following formula in terms of the cap product or in terms of the BV structure\\textup{:}\n\\begin{equation}\n\\begin{aligned}\n(\\pi_2)_*([\\tilde{I}])&=(-1)^{\\sum_jj|\\beta_j|-s}\n\\bigl(\\alpha_1\\dotsm\\alpha_r(\\Delta\\beta_1)\\dotsm(\\Delta\\beta_s)\\bigr)\n\\cap b \\\\\n&=(-1)^{\\sum_jj|\\beta_j|-s}[A_1]\\cdots[A_s]\\cdot\\{[B_1],\\{\\cdots\\{[B_s],b\\}\\cdots\\}\n\\in \\mathbb H_*(LM). \n\\end{aligned}\n\\end{equation}\n\\end{proposition} \n\\begin{proof} The evaluation map $e$ in \\eqref{eval} is \ngiven by the following composition.\n\\begin{multline*} \n\\overset{s}{\\overbrace{S^1\\times\\dotsb\\times S^1}}\\times LM \n\\xrightarrow{1\\times\\phi} \n(S^1\\times\\dotsb\\times S^1) \\times\n\\overset{r+s}{\\overbrace{LM\\times\\dotsb\\times LM}} \\\\\n\\xrightarrow{T} \n\\overset{r}{\\overbrace{LM\\times\\dotsb\\times LM}}\\times\n\\overset{s}{\\overbrace{(S^1\\times LM)\\times\\dotsb\\times(S^1\\times LM)}} \\\\\n\\xrightarrow{1^r\\times\\Delta^s}\n(LM\\times\\dotsb\\times LM) \\times\n(LM\\times\\dotsb\\times LM)\n\\xrightarrow{p^r\\times p^s} \n(M\\times\\dotsb\\times M) \\times\n(M\\times\\dotsb\\times M),\n\\end{multline*} \nwhere $\\phi$ is a diagonal map, $T$ moves $S^1$ factors. Since we\napply $(\\pi_2)_*$ later, we only need terms in $e^*(\\prod A_i\\times\n\\prod B_j)$ containing the factor\n$\\{S^1\\}\\times\\dotsb\\times\\{S^1\\}$. Since\n$\\Delta^*p^*(\\beta_j)=1\\times p^*(\\beta_j)\n+\\{S^1\\}\\times\\Delta\\beta_j$ for $1\\le j\\le s$, following the above\ndecomposition of $e$, we have\n\\begin{equation*}\ne^*(\\alpha_1\\times\\dotsb\\times\\alpha_r\\times\\beta_1\\times\\dotsb\\times\\beta_s)\n=\\varepsilon\n\\{S^1\\}^s\\times \\bigl(\\alpha_1\\dotsm\\alpha_r(\\Delta\\beta_1)\\dotsm\n(\\Delta\\beta_s)\\bigr) + \\text{ other terms},\n\\end{equation*}\nwhere the sign $\\varepsilon$ is given by $\\varepsilon=\n(-1)^{\\sum_{\\ell=1}^s(s-\\ell)(|\\beta_{\\ell}|-1)\n+s\\sum_{\\ell=1}^r|\\alpha_{\\ell}|}$. Thus, taking the cap product with\n$[S^1]^s\\times b$ and applying $(\\pi_2)_*$, we get\n\\begin{multline*}\n{\\pi_2}_*\n\\bigl(e^*(\\alpha_1\\times\\dotsb\\times\\alpha_r\\times\n\\beta_1\\times\\dotsb\\times\\beta_s)\n\\cap ([S^1]\\times\\dotsb\\times[S^1]\\times b)\\bigr) \\\\\n=(-1)^{\\sum_{\\ell=1}^{s}\\ell|\\beta_{\\ell}|-s}\n\\alpha_1\\dotsm\\alpha_r(\\Delta\\beta_1)\\dotsm(\\Delta\\beta_s)\\cap b.\n\\end{multline*}\nThe second equality follows from the formula \\eqref{composition of derivations}. \n\\end{proof}\n\n\\begin{remark} In the diagram \\eqref{eval}, \nin terms of cohomology transfer ${\\pi_2}^!$ we have \n\\begin{equation}\n{\\pi_2}^!\ne^*(\\alpha_1\\times\\dotsb\\times\\alpha_r\\times\\beta_1\\times\\dotsb\\times\\beta_s)\n=\\pm\n\\alpha_1\\dotsm\\alpha_r(\\Delta\\beta_1)\\dotsm(\\Delta\\beta_s), \n\\end{equation}\nwhere ${\\pi_2}^!(\\alpha)\\cap\nb=(-1)^{s|\\alpha|}{\\pi_2}_*\\bigl(\\alpha\\cap{\\pi_2}_!(b)\\bigr)$ for any\n$\\alpha\\in H^*((S^1)^s\\times LM)$ and $b\\in \\mathbb H_*(LM)$. Here\n${\\pi_2}_!(b)=[S^1]^s\\times b$.\n\\end{remark}\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\\section{The intersection product and the loop product}\n\n\n\n\n\n\n\nLet $M$ be a closed oriented smooth $d$-manifold. The loop product in\n$\\mathbb H_*(LM)$ was discovered by Chas and Sullivan \\cite{CS}, in terms of\ntransversal chains. Later, Cohen and Jones \\cite{CJ} gave a homotopy\ntheoretic description of the loop product. The loop product is a\nhybrid of the intersection product in $\\mathbb H_*(M)$ and the Pontrjagin\nproduct in the homology of the based loop spaces $H_*(\\Omega M)$. In\nthis section, we review and prove some properties of the loop product\nin preparation for the next section. Our treatment of the loop product\nfollows \\cite{CJ}. However, we will be precise with signs and give a\nhomotopy theoretic proof of the graded commutativity of the loop\nproduct, which \\cite{CJ} did not include. For the Frobenius compatibility formula with careful discussion of signs, see \\cite{T2}. For homotopy theoretic deduction of the BV identity, see \\cite{T3}. \n\nFor our purpose, the free loop space $LM$ is the space of {\\it continuous} maps from $S^1=\\mathbb R\/\\mathbb Z$ to $M$. Our discussion is homotopy theoretic and does not require smoothness of loops, although we do need smoothness of $M$ which is enough to allows us to have tubular neighborhoods for certain submanifolds in the space of continuous loops. Recall that the space $LM$ of continuous loops can be given a structure of a smooth manifold. See the discussion before Definition \\ref{definition of loop product}. \n\nLet $p: LM \\longrightarrow M$ be the base\npoint map given by $p(\\gamma)=\\gamma(0)$. Let $s: M \\longrightarrow\nLM$ be the constant loop map given by $s(x)=c_x$, where $c_x$ is the\nconstant loop at $x\\in M$. Since $p_*\\circ s_*=1$, $\\mathbb H_*(M)$ is\ncontained in $\\mathbb H_*(LM)$ through $s_*$ and we often regard $\\mathbb H_*(M)$ as a subset of $\\mathbb H_*(LM)$.\n\nWe start with a discussion on the intersection ring $\\mathbb H_*(M)$ and later we compare it with the loop homology algebra $\\mathbb H_*(LM)$. An exposition on intersection products in homology of manifolds can be found on Dold's book \\cite{D}, Chapter VIII, \\S13. Our sign convention (which follows Milnor \\cite{M}) is slightly different from Dold's. We give a fairly detailed discussion of the intersection ring $\\mathbb H_*(M)$ because the\ndiscussion for the loop homology algebra goes almost in parallel, and\nbecause our choice of the sign for the loop product comes from and is\ncompatible with the intersection product in $\\mathbb H_*(M)$. Compare formulas \\eqref{intersection product} and \\eqref{loop product}.\n\nThose who are familiar with intersection product and loop products can skip this section after checking Definition \\ref{definition of loop product}. \n\nLet $D: \\mathbb H_*(M) \\xrightarrow{\\cong} H^{d-*}(M)$ be the Poincar\\'e duality map such that $D(a)\\cap[M]=a$ for $a\\in \\mathbb H_*(M)$. We discuss two ways to define\nintersection product in $\\mathbb H_*(M)$. The first method is the official one\nand we simply define the intersection product as the Poincar\\'e dual\nof the cohomology cup product. Thus, $D(a\\cdot b)=D(a)\\cup D(b)$ for\n$a,b\\in \\mathbb H_*(M)$. For example, we have $a\\cdot\nb=(-1)^{|a||b|}b\\cdot a$.\n\nThe second method uses the transfer map induced from the diagonal map\n$\\phi: M \\longrightarrow M\\times M$. Let $\\nu$ be the normal bundle to\n$\\phi(M)$ in $M\\times M$, and we orient $\\nu$ by $\\nu\\oplus\n\\phi_*(TM)\\cong T(M\\times M)|_{\\phi(M)}$. Let $u'\\in\nH^d(\\phi(M)^{\\nu})$ be the Thom class of $\\nu$. Let $N$ be a closed\ntubular neighborhood of $\\phi(M)$ in $M\\times M$ so that $D(\\nu)\\cong\nN$, where $D(\\nu)$ is the associated closed disc bundle of $\\nu$. Let\n$\\pi: N \\longrightarrow M$ be the projection map. Then the above Thom\nclass can be thought of as $u'\\in \\tilde{H}^d(N\/\\partial N)$, and we\nhave the following commutative diagram, where $c: M\\times M\n\\longrightarrow N\/\\partial N$ is the Thom collapse map, and $\\iota_N$\nand $j$ are obvious maps.\n\\begin{equation}\n\\begin{CD} \nH^d(N, N-\\phi(M)) @>{\\cong}>> H^d(N,\\partial N)\\ni u' \\\\\n@A{\\cong}A{\\iota_N^*}A @VV{c^*}V \\\\\nu''\\in H^d\\bigl(M\\times M, M\\times M-\\phi(M)\\bigr) @>{j^*}>> H^d(M\\times M)\\ni u\n\\end{CD}\n\\end{equation} \nLet $u''\\in H^d\\bigl(M\\times M, M\\times M-\\phi(M)\\bigr)$ and $u\\in\nH^d(M\\times M)$ be the classes corresponding to the Thom class. We\nhave $u=c^*(u')=j^*(u'')$. This class $u$ is characterized by the\nproperty $u\\cap[M\\times M]=\\phi_*([M])$, and $\\phi^*(u)=e_M\\in H^d(M)$\nis the Euler class of $M$. See for example section 11 of \\cite{M}. The\ntransfer map $\\phi_!$ is defined as the following composition:\n\\begin{equation}\n\\phi_!: H_*(M\\times M) \\xrightarrow{c_*} \\tilde{H}_*(N\/\\partial N)\n\\xrightarrow[\\cong]{u'\\cap(\\ )} H_{*-d}(N) \\xrightarrow[\\cong]{\\pi_*}\nH_{*-d}(M).\n\\end{equation} \n\nFor a homology element $a$, let $|a|'$ denote its regular homology degree of $a$, so that we have $a\\in H_{|a|}(M)$ and $|a|'=|a|+d$. \n\n\\begin{proposition}\\label{properties of phi} Suppose $M$ is a connected \noriented closed $d$-manifold with a base point $x_0$. The transfer map\n$\\phi_!: H_*(M\\times M) \\longrightarrow H_{*-d}(M)$ satisfies the\nfollowing properties. For $a,b\\in H_*(M)$,\n\\begin{align}\n\\phi_*\\phi_!(a\\times b)&=u\\cap(a\\times b) \\\\ \\phi_!\\phi_*(a\\times\nb)&=\\chi(M)[x_0]\n\\end{align}\nFor $\\alpha\\in H^*(M\\times M)$ and $b,c\\in H_*(M)$, we have \n\\begin{equation}\n\\phi_!\\bigl(\\alpha\\cap(b\\times c)\\bigr)\n=(-1)^{d|\\alpha|}\\phi^*(\\alpha)\\cap\\phi_!(b\\times c).\n\\end{equation} \nThe intersection product and the transfer map coincide up to a sign. \n\\begin{equation}\\label{intersection product}\na\\cdot b=(-1)^{d(|a|'-d)}\\phi_!(a\\times b).\n\\end{equation}\n\\end{proposition} \n\\begin{proof} For the first identity, we consider the following \ncommutative diagram, where $M^2$ denotes $M\\times M$. \n\\begin{equation*}\n\\begin{CD}\nH_*(M^2) @>{c_*}>> H_*(N,\\partial N) @>{u'\\cap (\\ )}>{\\cong}> H_{*-d}(N) \n@>{\\pi_*}>{\\cong}> H_{*-d}(M) \\\\\n@| @V{\\cong}V{{\\iota_N}_*}V @VV{{\\iota_N}_*}V @VV{\\phi_*}V \\\\\nH_*(M^2) @>{j_*}>> H_*\\bigl(M^2, M^2-\\phi(M)\\bigr) \n@>{u''\\cap(\\ )}>{\\cong}> H_{*-d}(M^2) @= H_{*-d}(M^2)\n\\end{CD}\\end{equation*}\nThe commutativity implies that for $a,b\\in H_*(M)$, we have $\\phi_*\\phi_!\n=u''\\cap j_*(a\\times b)=j^*(u'')\\cap(a\\times b)=u\\cap(a\\times b)$. \n\nTo check the second formula, we first compute\n$\\phi_*\\phi_!\\phi_*([M])$. By the first formula,\n$\\phi_*\\phi_!\\phi_*([M])=u\\cap\\phi_*([M])=\\phi_*(\\phi^*(u)\\cap[M])$. Since\n$\\phi^*(u)$ is the Euler class $e_M$, this is equal to\n$\\phi_*(e_M\\cap[M])=\\chi(M)[(x_0,x_0)]$. Since $M$ is assumed to be\nconnected, $\\phi_*$ is an isomorphism in $H_0$. Hence\n$\\phi_!\\phi_*([M])=\\chi(M)[x_0]\\in H_0(M)$.\n\nFor the next formula, we examine the following commutative diagram. \n\\begin{equation*}\n\\begin{CD} \nH_*(M^2) @>{c_*}>> H_*(N,\\partial N) @>{u'\\cap(\\ )}>{\\cong}> H_{*-d}(N)\n@<{\\iota_*'}<{\\cong}< H_{*-d}(M) \\\\ \n@V{\\alpha\\cap(\\ )}VV\n@V{\\iota_N^*(\\alpha)\\cap(\\ )}VV @V{\\iota_N^*(\\alpha)\\cap(\\ )}VV\n@V{\\iota^*(\\alpha)}VV \\\\ \nH_{*-|\\alpha|}(M^2) @>{c_*}>>\nH_{*-|\\alpha|}(N,\\partial N) @>{u'\\cap(\\ )}>{\\cong}> H_{*-d-|\\alpha|}(N)\n@<{\\iota_*'}<{\\cong}< H_{*-d-|\\alpha|}(M)\n\\end{CD}\n\\end{equation*}\nwhere $\\iota': M\\rightarrow N$ is an inclusion map and\n$\\iota_*'=(\\pi_*)^{-1}$. The middle square commutes up to\n$(-1)^{|\\alpha|d}$. The commutativity of this diagram immediately\nimplies that $\\iota^*(\\alpha)\\cap\\phi_!(a\\times b)\n=(-1)^{|\\alpha|d}\\phi_!\\bigl(\\alpha\\cap(a\\times b)\\bigr)$.\n\nFor the last identity, we apply $\\phi_*$ on both sides and\ncompare. Since $a\\cdot b=\\phi^*(D(a)\\times D(b))\\cap[M]$, we have\n\\begin{align*} \n\\phi_*(a\\cdot b)&=\\bigl(D(a)\\times D(b)\\bigr)\\cap \\phi_*([M]) \\\\\n&=\\bigl(D(a)\\times D(b)\\bigr)\\cap \\bigl(u\\cap[M]\\bigr) \\\\\n&=(-1)^{d(|a|'-d)}u\\cap(a\\times b)=(-1)^{d(|a|'-d)}\\phi_*\\phi_!(a\\times b).\n\\end{align*} \nSince $\\phi_*$ is injective, we have $a\\cdot\nb=(-1)^{d(|a|'-d)}\\phi_!(a\\times b)$.\n\\end{proof} \n\nThese two intersection products, one defined using the Poincar\\'e\nduality, and the other using Pontrjagin Thom construction, differ only\nin signs. However, the formulas for graded commutativity take\ndifferent forms.\n\\begin{align}\na\\cdot b&=(-1)^{(d-|a|')(d-|b|')}b\\cdot a \\\\\n\\phi_!(a\\times b)&=(-1)^{|a|'|b|'+d}\\phi_!(b\\times a)\n\\end{align}\nThe sign $(-1)^d$ in the second formula above comes from the fact that\nthe Thom class $u\\in H^d(M\\times M)$ satisfies $T^*(u)=(-1)^du$, where\n$T$ is the switching map of factors.\n\nNext we turn to the loop product in $H_*(LM)$. We consider the\nfollowing diagram.\n\\begin{equation}\n\\begin{CD}\nLM\\times LM @<{j}<< LM\\times_M LM @>{\\iota}>> LM \\\\\n@V{p\\times p}VV @V{q}VV @. \\\\\nM\\times M @<{\\phi}<< M @. \n\\end{CD}\n\\end{equation}\nwhere $LM\\times_M LM=(p\\times p)^{-1}(\\phi(M))$ consists of pairs of\nloops $(\\gamma,\\eta)$ with the same base point, and\n$\\iota(\\gamma,\\eta)=\\gamma\\cdot\\eta$ is the product of composable\nloops. Let $\\widetilde{N}=(p\\times p)^{-1}(N)$ and let $\\tilde{c}:\nLM\\times LM \\longrightarrow \\widetilde{N}\/\\partial\\widetilde{N}$ be the Thom collapse map. Let $\\tilde{\\pi}: \\widetilde{N} \\longrightarrow\nLM\\times_MLM$ be a projection map defined as follows. For\n$(\\gamma,\\eta)\\in\\widetilde{N}$, let their base points be $(x,y)\\in\nN$. Let $\\pi(x,y)=(z,z)\\in \\phi(M)$. Since $N\\cong D(\\nu)$ \nhas a bundle structure,\nlet $\\ell(t)=(\\ell_1(t),\\ell_2(t))$ be the straight ray in the fiber\nover $(z,z)$ from $(z,z)$ to $(x,y)$. Then let\n$\\tilde{\\pi}\\bigl((\\gamma,\\eta)\\bigr)=(\\ell_1\\cdot\\gamma\\cdot\\ell_1^{-1},\n\\ell_2\\cdot\\eta\\cdot\\ell_2^{-1})$. By considering $\\ell_{[t,1]}$, we\nsee that $\\tilde{\\pi}$ is a deformation retraction. \n\nIn fact, more is true. Stacey (\\cite{St}, Proposition 5.3) showed that when $L_{\\text{smooth}}M$ is the space of {\\it smooth} loops, $\\widetilde{N}$ has an actual structure of a tubular neighborhood of $LM\\times_MLM$ inside of $LM\\times LM$ equipped with a diffeomorphism $p^*\\bigl(D(\\nu)\\bigr)\\cong \\widetilde{N}$. His proof only uses the smoothness of $M$ and exactly the same proof applies to the space $LM$ \nof {\\it continuous} loops and $\\widetilde{N}$ still has the structure of a tubular neighborhood and we again have a diffeomorphism $p^*\\bigl(D(\\nu)\\bigr)\\cong \\widetilde{N}$ between spaces of continuous loops. But we do not need this much here. \n\nLet $\\tilde{u}'=(p\\times p)^*(u')\\in\n\\tilde{H}^d(\\widetilde{N}\/\\partial\\widetilde{N})$, and $\\tilde{u}=(p\\times p)^*(u)\\in H^d(LM\\times LM)$ be pull-backs of Thom classes. Define the\ntransfer map $j_!$ by the following composition of maps.\n\\begin{equation} \nj_!: H_*(LM\\times LM) \\xrightarrow{\\tilde{c}_*} \n\\tilde{H}_*(\\widetilde{N}\/\\partial\\widetilde{N})\n\\xrightarrow[\\cong]{\\tilde{u}'\\cap(\\ )} H_{*-d}(\\widetilde{N}) \n\\xrightarrow[\\cong]{\\tilde{\\pi}_*}\nH_{*-d}(LM\\times_MLM).\n\\end{equation}\nThe tubular neighborhood structure of $\\widetilde{N}$ implies that the middle map is a genuine Thom isomorphism. \n\n\\begin{definition}\\label{definition of loop product} \nLet $M$ be a closed oriented $d$-manifold. For $a,b\\in \\mathbb H_*(LM)$, their loop product, denoted by $a\\cdot b$, is defined by\n\\begin{equation}\\label{loop product} \na\\cdot b=(-1)^{d(|a|'-d)}\\iota_*j_!(a\\times b)\n=(-1)^{d|a|}\\iota_*j_!(a\\times b). \n\\end{equation}\n\\end{definition} \n\nThe sign $(-1)^{d(|a|'-d)}$ appears in \\cite{CJY} in the commutative\ndiagram (1-7). We include this sign explicitly in the definition of\nthe loop product for at least three reasons. The most trivial reason\nis that on the left hand side, the dot representing the loop product\nis between $a$ and $b$. On the right hand side, $j_!$ of degree $-d$\nrepresenting the loop product is in front of $a$. Switching $a$ and\n$j_!$ gives the sign $(-1)^{d|a|'}$. The other part of the sign\n$(-1)^d$ comes from our choice of orientation of $\\nu$ and ensures\nthat $s_*([M])\\in \\mathbb H_0(LM)$, with the $+$ sign, is the unit of the loop\nproduct. We quickly verify the correctness of the sign.\n\\begin{lemma} \nThe element $s_*([M])\\in\\mathbb H_0(LM)$ is the unit of the loop\nproduct. Namely for any $a\\in \\mathbb H_*(LM)$,\n\\begin{equation}\ns_*([M])\\cdot a=a\\cdot s_*([M])=a.\n\\end{equation}\n\\end{lemma}\n\\begin{proof} We consider the following diagram. \n\\begin{equation*}\n\\begin{CD}\n@. LM @= LM \\\\\n@. @A{\\pi_2}AA @| @. \\\\\nM\\times M @<{1\\times p}<< M\\times LM @<{j'}<< M\\times_M LM @= LM \\\\\n@| @V{s\\times 1}VV @V{s\\times_M1}VV @| \\\\\nM\\times M @<{p\\times p}<< LM\\times LM @<{j}<< LM\\times_M LM @>{\\iota}>> LM \n\\end{CD}\n\\end{equation*} \nIn the induced homology diagram with transfers $j_!$ and $j'_!$, the\nbottom middle square commutes because transfers are defined using Thom\nclasses pulled back from the same Thom class $u$ of the base\nmanifold. Thus,\n\\begin{equation*}\ns_*([M])\\cdot a=\\iota_*j_!(s\\times 1)_*([M]\\times a)=j'_!([M]\\times a). \n\\end{equation*}\nHere, since $[M]$ has degree $d$, the sign in \\eqref{loop product} is $+1$. Since $\\pi_2\\circ j'=1$, the identity on $LM$,\n\\begin{equation*}\nj'_!([M]\\times a)={\\pi_2}_*j'_*j'_!([M]\\times a)\n={\\pi_2}_*\\bigl((1\\times p)^*(u)\\cap([M]\\times a)\\bigr).\n\\end{equation*}\nDue to the way $\\nu$ is oriented, the Thom class $u$ is of the form\n$u=\\{M\\}\\times 1+\\dotsb+(-1)^d1\\times\\{M\\}$. Hence\n${\\pi_2}_*\\bigl((1\\times p)^*(u)\\cap([M]\\times\na)\\bigr)={\\pi_2}_*([x_0]\\times a+\\dotsm)=a$.\n\nThe other identity $a\\cdot s_*([M])=a$ can be proved similarly. This\ncompletes the proof.\n\\end{proof} \n\n\nThe second reason is that this choice of sign for the loop product is\nthe same sign appearing in the formula for the intersection product\ndefined in terms of the transfer map \\eqref{intersection\nproduct}. This makes the loop product compatible with the intersection\nproduct in the following sense.\n\n\\begin{proposition}\nBoth of the following maps are algebra maps preserving units between\nthe loop algebra $\\mathbb H_*(LM)$ and the intersection ring $\\mathbb H_*(M)$.\n\\begin{equation}\np_*: \\mathbb H_*(LM) \\longrightarrow \\mathbb H_*(M),\\qquad \ns_*: \\mathbb H_*(M) \\longrightarrow\n\\mathbb H_*(LM).\n\\end{equation}\n\\end{proposition} \n\\begin{proof} The proof is more or less straightforward, \nbut we discuss it briefly. We consider the following diagram.\n\\begin{equation*}\n\\begin{CD}\nLM\\times LM @<{j}<< LM\\times_M LM @>{\\iota}>> LM \\\\ @V{p\\times p}VV\n@V{p}VV @V{p}VV \\\\ M\\times M @<{\\phi}<< M @= M \\\\ @V{s\\times s}VV\n@V{s}VV @V{s}VV \\\\ LM\\times LM @<{j}<< LM\\times_M LM @>{\\iota}>> LM\n\\end{CD}\\end{equation*}\nSince the Thom classes for embeddings $j$ and $\\phi$ are compatible\nvia $(p\\times p)^*$, the induced homology diagram with transfers\n$j_!$ and $\\phi_!$ is commutative. Then by diagram chasing, we can\neasily check that $p_*$ and $s_*$ preserve products because of the\nsame signs appearing in \\eqref{intersection product} and \n\\eqref{loop product}. \n\\end{proof} \n\nThe third reason of the sign for the loop product is that it gives the\ncorrect graded commutativity, as given in \\cite{CS} proved in terms of chains. We discuss a homotopy theoretic proof of graded commutativity because \\cite{CJ} did not include it, and because the homotopy theoretic proof itself is not so trivial with careful treatment of transfers and signs. Contrast the present homotopy theoretic proof with the simple geometric proof given in \\cite{CS}. \n\n\\begin{proposition} \nFor $a,b\\in \\mathbb H_*(LM)$, the following graded commutativity relation holds\\textup{:}\n\\begin{equation} \na\\cdot b=(-1)^{(|a|'-d)(|b|'-d)}b\\cdot a=(-1)^{|a||b|}b\\cdot a. \n\\end{equation}\n\\end{proposition} \n\\begin{proof}\nWe consider the following commutative diagram, where $R_{\\frac12}$ is\nthe rotation of loops by $\\frac12$, that is,\n$R_{\\frac12}(\\gamma)(t)=\\gamma(t+\\frac12)$.\n\\begin{equation*}\n\\begin{CD}\nLM\\times LM @<{j}<< LM\\times_M LM @>{\\iota}>> LM \\\\\n@V{T}VV @V{T}VV @V{R_{\\frac12}}VV \\\\\nLM\\times LM @<{j}<< LM\\times_M LM @>{\\iota}>> LM\n\\end{CD}\n\\end{equation*}\nSince $R_{\\frac12}$ is homotopic to the identity map, we have\n${R_{\\frac12}}_*=1$. Hence\n\\begin{equation*}\na\\cdot b=(-1)^{d(|a|'-d)}\\iota_*j_!(a\\times b)\n=(-1)^{d(|a|'-d)}\\iota_*T_*j_!(a\\times b).\n\\end{equation*} \nNext we show that the induced homology square with transfer $j_!$, we\nhave $T_*j_!=(-1)^dj_!T_*$. Since the left square in the above diagram\ncommutes on space level, we have that $T_*j_!$ and $j_!T_*$ coincides\nup to a sign. To determine this sign, we compose $j_*$ on the left of\nthese maps and compare. Since the homology square with induced\nhomology maps commute,\n\\begin{equation*}\nj_*T_*j_!(a\\times b)=T_*j_*j_!(a\\times\nb)=T_*\\bigl(\\tilde{u}\\cap(a\\times b)\\bigr).\n\\end{equation*}\nOn the other hand, \n\\begin{equation*}\nj_*j_!T_*(a\\times b)=\\tilde{u}\\cap T_*(a\\times b)\n=T_*\\bigl(T^*(\\tilde{u})\\cap(a\\times b)\\bigr). \n\\end{equation*}\nWe compare $T^*(\\tilde{u})$ and $\\tilde{u}$. Since $\\tilde{u}=(p\\times\np)^*(u)$, we have $T^*(\\tilde{u})=(p\\times p)^*T^*(u)$. Since $u$ is\ncharacterized by the property $u\\cap[M\\times M]=\\phi_*([M])$ and\n$T\\circ \\phi=\\phi$, we have\n\\begin{equation*}\n\\phi_*([M])=T_*\\phi_*([M])=T^*(u)\\cap T_*([M\\times\nM])=T^*(u)\\cap(-1)^d[M\\times M].\n\\end{equation*}\nThus $T^*(u)=(-1)^du$. Hence $T^*(\\tilde{u})=(-1)^d\\tilde{u}$. In view\nof the above two identities, this implies that\n$j_*T_*j_!=(-1)^dj_*j_!T_*$, or $T_*j_!=(-1)^dj_!T_*$. \n\nContinuing our computation,\n\\begin{equation*} \na\\cdot b=(-1)^{d|a|'}\\iota_*j_!T_*(a\\times b)\n=(-1)^{|a|'|b|'+d|\\alpha|}\\iota_*j_!(b\\times a)=(-1)^{(|a|'-d)(|b|'-d)}b\\cdot a.\n\\end{equation*}\nThis completes the homotopy theoretic proof of commutativity formula. \n\\end{proof}\n\n\\begin{remark}\nIf we let $\\mu=\\iota_*j_!:\\mathbb H_*(LM)\\otimes \\mathbb H_*(LM) \\longrightarrow \\mathbb H_*(LM)$, then using the method in \\cite{T2}, we can show that the associativity of $\\mu$ takes the form $\\mu\\circ(1\\otimes \\mu)=(-1)^d\\mu\\circ(\\mu\\otimes 1)$. With our choice of the sign for the loop product in Definition \\ref{definition of loop product}, we can get rid of the above sign and we have a usual associativity relation $(a\\cdot b)\\cdot c=a\\cdot(b\\cdot c)$ for the loop product without any signs for $a,b,c\\in\\mathbb H_*(LM)$. This is yet another reason of our choice of the sign in the definition of the loop product. \n\\end{remark}\n\n\nThe transfer map $j_!$ enjoys the following properties similar to\nthose satisfies by $\\phi_!$ as given in Proposition~\\ref{properties of\nphi}. The proof is similar, and we omit it.\n\n\\begin{proposition}\nFor $a,b\\in \\mathbb H_*(LM)$ and $\\alpha\\in H^*(LM\\times LM)$, the following\nformulas are valid.\n\\begin{align}\nj_*j_!(a\\times b)&=\\tilde{u}\\cap(a\\times b) \\label{j_!1}\\\\\nj_!\\bigl(\\alpha\\cap(a\\times b)\\bigr)&=\n(-1)^{d|\\alpha|}j^*(\\alpha)\\cap j_!(b\\times c) \\label{j_!2}\n\\end{align}\n\\end{proposition}\n\nThe second formula says that $j_!$ is a $H^*(LM\\times LM)$-module map. \n\n\n\n\n\n\n\n\n\n\n\\section{Cap products and extended BV algebra structure}\n\n\n\n\n\n\nWe examine compatibility of the cap product with the various\nstructures in the BV-algebra $\\mathbb{H}_*(LM)=H_{*+d}(LM)$.\n\nWe recall that a BV-algebra $A_*$ is an associative graded commutative\nalgebra equipped with a degree $1$ Lie bracket $\\{\\ ,\\ \\}$ and a\ndegree $1$ operator $\\Delta$ satisfying the following relations for\n$a,b,c\\in A_*$:\n\\begin{gather}\n\\Delta(a\\cdot b)=(\\Delta a)\\cdot b + (-1)^{|a|}a\\cdot \\Delta b +\n(-1)^{|a|}\\{a,b\\} \n\\tag{BV identity} \\\\ \n\\{a, b\\cdot c\\} =\\{a,b\\}\\cdot c + (-1)^{|b|(|a|+1)}b\\cdot\\{a,c\\} \n\\tag{Poisson identity} \\\\ \na\\cdot b=(-1)^{|a||b|}b\\cdot a,\\qquad \n\\{a,b\\}=-(-1)^{(|a|+1)(|b|+1)}\\{b,a\\}\n\\tag{Commutativity} \\\\\n\\{a,\\{b,c\\}\\}=\\{\\{a,b\\},c\\}+(-1)^{(|a|+1)(|b|+1)}\\{b,\\{a,c\\}\\}\n\\tag{Jacobi identity}\n\\end{gather} \nHere, degrees of elements are given by $\\Delta a\\in A_{|a|+1}, a\\cdot b\\in A_{|a|+|b|}$, and $\\{a,b\\}\\in A_{|a|+|b|+1}$. \nOne way to view these relations is to consider operators $D_a$ and\n$M_a$ acting on $A_*$ for each $a\\in A_*$ given by $D_a(b)=\\{a,b\\}$ and\n$M_a(b)=a\\cdot b$. Let $[x,y]=xy-(-1)^{|x||y|}yx$ be the graded\ncommutator of operators. Then the Poisson identity and the Jacobi\nidentity take the following forms:\n\\begin{equation}\n[D_a,M_b]=M_{\\{a,b\\}},\\qquad [D_a,D_b]=D_{\\{a,b\\}},\n\\end{equation}\nwhere degrees of operators are $|D_a|=|a|+1$ and $|M_b|=|b|$. \n\nOne nice context to understand BV identity is in the context of odd symplectic geometry (\\cite{G}, \\S2), where BV operator $\\Delta$ appears as a mixed second order odd differential operator, and BV identity can be simply understood as Leipnitz rule in differential calculus. This context actually arises in loop homology. In \\cite{T1}, we explicitly computed the BV structure of $\\mathbb H_*(LM)$ for the Lie group $\\text{SU}(n+1)$ and complex Stiefel manifolds. There, the BV operator $\\Delta$ is given by second order mixed odd differential operator as above, and $\\mathbb H_*(LM)$ is interpreted as the space of polynomial functions on the odd symplectic vector space. \n\nThe fact that the loop algebra $\\mathbb{H}_*(LM)$ is a\nBV-algebra was proved in \\cite{CS}. Note that the above BV relations\nare satisfied with respect to $\\mathbb{H}_*$-grading, rather than the\nusual homology grading. \nThe same is true for compatibility relations\nwith cap products. \n\nFirst we discuss cohomological $S^1$ action operator $\\Delta$ on $H^*(LM)$. Let $\\Delta:\nS^1\\times LM \\longrightarrow LM$ be the $S^1$ action map given by\n$\\Delta(t,\\gamma)=\\gamma_t$, where $\\gamma_t(s)=\\gamma(s+t)$ for\n$s,t\\in S^1=\\mathbb{R}\/\\mathbb{Z}$. The degree $-1$ operator\n$\\Delta: H^*(LM) \\longrightarrow H^{*-1}(LM)$ is defined by the\nfollowing formula for $\\alpha\\in H^*(LM)$:\n\\begin{equation}\n\\Delta^*(\\alpha)=1\\times\\alpha + \\{S^1\\}\\times \\Delta\\alpha\n\\end{equation}\nwhere $\\{S^1\\}$ is the fundamental cohomology class of $S^1$. The\nhomological $S^1$ action $\\Delta$ is not a derivation with respect to the loop product and the deviation from being a derivation is given \nby the loop bracket. However, the\ncohomology $S^1$-operator $\\Delta$ is a derivation with respect to the cup product.\n\n\\begin{proposition}\nThe cohomology $S^1$-operator $\\Delta$ satisfies $\\Delta^2=0$, and it acts as a derivation on the cohomology ring $H^*(LM)$. That is, for\n$\\alpha,\\beta\\in H^*(LM)$,\n\\begin{equation}\\label{delta and cup}\n\\Delta(\\alpha\\cup\\beta)=(\\Delta\\alpha)\\cup\\beta +\n(-1)^{|\\alpha|}\\alpha\\cup\\Delta\\beta.\n\\end{equation}\n\\end{proposition}\n\\begin{proof} The property $\\Delta^2=0$ is straightforward \nusing the following diagram\n\\begin{equation*}\n\\begin{CD}\nS^1\\times S^1 \\times LM @>{1\\times\\Delta}>> S^1\\times LM \\\\ @V{\\mu\\times 1}VV\n@V{\\Delta}VV \\\\ S^1\\times LM @>{\\Delta}>> LM\n\\end{CD}\n\\end{equation*}\nComparing both sides of $(1\\times\\Delta)^*\\Delta^*(\\alpha)=(\\mu\\times\n1)^*\\Delta^*(\\alpha)$, we obtain $\\Delta^2(\\alpha)=0$.\n\nFor the derivation property, we consider the following diagram. \n\\begin{equation*}\n\\begin{CD}\nS^1\\times LM @>{\\phi\\times\\phi}>> (S^1\\times S^1)\\times (LM\\times LM) \n@>{1\\times T\\times 1}>> (S^1\\times LM)\\times (S^1\\times LM) \\\\\n@V{\\Delta}VV @. @V{\\Delta\\times\\Delta}VV \\\\\nLM @>{\\phi}>> LM\\times LM @= LM\\times LM \n\\end{CD}\n\\end{equation*} \nOn the one hand, $\\Delta^*\\phi^*(\\alpha\\times\n\\beta)=\\Delta^*(\\alpha\\cup\\beta) =1\\times(\\alpha\\cup\\beta) +\n\\{S^1\\}\\times \\Delta(\\alpha\\cup\\beta)$. On the other hand,\n\\begin{equation*}\n(\\phi\\times\\phi)^*(1\\times T\\times 1)^*(\\Delta\\times\n\\Delta)^*(\\alpha\\times \\beta) =1\\times(\\alpha\\cup\\beta) +\n(-1)^{|\\alpha|}\\{S^1\\}\\times \\bigl(\\alpha\\cup\\Delta\\beta \n+ \\Delta\\alpha\\cup\\beta\\bigr).\n\\end{equation*}\nComparing the above two identities, we obtain the derivation formula.\n\\end{proof} \n\nWe can regard the cohomology ring $H^*(LM)$ together with cohomological $S^1$ action $\\Delta$ as a BV algebra with trivial bracket product. \n\nNow we show that the cap product is compatible with the loop product\nin the BV-algebra $\\mathbb H_*(LM)$. The following theorem describes the behavior of the cap product with those elements in the subalgebra of $H^*(LM)$ generated by $H^*(M)$ and $\\Delta\\bigl(H^*(M)\\bigr)$.\n\n\\begin{theorem} Let $\\alpha\\in H^*(M)$ and $b,c\\in \\mathbb H_*(LM)$. \nThe cap product with $p^*(\\alpha)$ behaves\nassociatively and graded commutatively with respect to the loop\nproduct. Namely\n\\begin{equation}\\label{cap and loop product} \np^*(\\alpha)\\cap(b\\cdot c)=(p^*(\\alpha)\\cap b)\\cdot c\n=(-1)^{|\\alpha||b|}b\\cdot(p^*(\\alpha)\\cap c).\n\\end{equation}\n\nThe cap product with \n$\\Delta\\bigl(p^*(\\alpha)\\bigr)$ is a derivation on the loop product. Namely, \n\\begin{equation}\\label{cap derivation} \n\\Delta\\bigl(p^*(\\alpha)\\bigr)\\cap(b\\cdot c)\n=\\bigl(\\Delta\\bigl(p^*(\\alpha)\\bigr)\\cap b\\bigr)\\cdot c +\n(-1)^{(|\\alpha|-1)|b|}b\\cdot\\bigl(\\Delta\\bigl(p^*(\\alpha)\\bigr)\\cap\nc\\bigr).\n\\end{equation}\n\\end{theorem} \n\\begin{proof}\nFor the first formula, we consider the following diagram, \nwhere $\\pi_i$ is the projection onto the $i$th factor for $i=1,2$. \n\\begin{equation*}\n\\begin{CD} \nLM @<{\\pi_i}<< LM\\times LM @<{j}<< LM\\times_M LM @>{\\iota}>> LM \\\\\n@V{p}VV @V{p\\times p}VV @V{q}VV @V{p}VV \\\\\nM @<{\\pi_i}<< M\\times M @<{\\phi}<< M @= M \n\\end{CD}\n\\end{equation*} \nSince $p^*(\\alpha)\\cap(b\\cdot c)\n=(-1)^{d|b|}\\iota_*\\bigl(\\iota^*p^*(\\alpha)\\cap j_!(b\\times c)\\bigr)$, \nwe need to understand $\\iota^*p^*(\\alpha)$. From the above commutative \ndiagram, we have $\\iota^*p^*(\\alpha)=j^*\\pi_i^*p^*(\\alpha)$, which is\nequal to either $j^*(p^*(\\alpha)\\times 1)$ or $j^*(1\\times\np^*(\\alpha))$. In the first case, continuting our computation using \n\\eqref{j_!2}, we have \n\\begin{align*}\np^*(\\alpha)\\cap(b\\cdot c)&=\n(-1)^{d|b|}\\iota_*\\bigl(j^*(p^*(\\alpha)\\times 1)\n\\cap j_!(b\\times c)\\bigr) \\\\\n&=(-1)^{d|b|+d|\\alpha|}\\iota_*j_!\n\\bigl((p^*(\\alpha)\\times 1)\\cap(b\\times c)\\bigr) \\\\\n&=(-1)^{d|b|+d|\\alpha|}\\iota_*j_!\n\\bigl((p^*(\\alpha)\\cap b)\\times c\\bigr) \\\\\n&=(p^*(\\alpha)\\cap b)\\cdot c.\n\\end{align*}\nSimilarly, using $\\iota^*p^*(\\alpha)\n=j^*\\bigl(1\\times p^*(\\alpha)\\bigr)$, we get the other identity. This\nproves (1). \n\nFor (2), we first note that the element\n$\\Delta\\bigl(p^*(\\alpha)\\bigr)\\cap(b\\cdot c)$ is equal to \n\\begin{equation*}\n\\Delta\\bigl(p^*(\\alpha)\\bigr)\\cap (-1)^{d|b|}\\iota_*j_!(b\\times c)\n=(-1)^{d|b|}\\iota_*\\bigl(\\iota^*\\bigl(\\Delta(p^*(\\alpha))\\bigr)\n\\cap j_!(b\\times c)\\bigr).\n\\end{equation*}\nThus, we need to understand the element\n$\\iota^*\\bigl(\\Delta(p^*(\\alpha))\\bigr)$. We need some notations. Let\n$I=I_1\\cup I_2$, where $I_1=[0,\\frac12]$ and $I_2=[\\frac12,1]$, and\nset $S_i^1=I_i\/\\partial I_i$ for $i=1,2$. Let $r: S^1=I\/\\partial I \n\\longrightarrow I\/\\{0,\\frac12,1\\}=S^1_1\\vee S^1_2$ be an\nidentification map, and let $\\iota_i: S^1_i \\longrightarrow S^1_1\\vee\nS^1_2$ be the inclusion map into the $i$th wedge summand. We examine\nthe following diagram \n\\begin{equation*}\n\\begin{CD}\nS^1\\times(LM\\underset{M}{\\times}LM) @>{r\\times 1}>> \n(S^1_1\\vee S^1_2)\\times\n(LM\\underset{M}{\\times}LM) @<<< \\{0\\}\\times (LM\\underset{M}{\\times}LM) \\\\\n@V{1\\times\\iota}VV @V{e'}VV @V{\\iota}VV \\\\\nS^1\\times LM @>{e}>> M @<{p}<< LM \n\\end{CD}\n\\end{equation*} \nwhere $e=p\\circ\\Delta$ is the evaluation map for $S^1\\times LM$, and\nthe other evaluation map $e'$ is given by \n\\begin{equation*}\ne'(t,\\gamma,\\eta)=\n\\begin{cases}\n\\gamma(2t)& 0\\le t\\le\\frac12,\\\\\n\\eta(2t-1)& \\frac12\\le t\\le 1.\n\\end{cases}\n\\end{equation*}\nFor $\\alpha\\in H^*(M)$, we let \n\\begin{equation*}\n{e'}^*(\\alpha)=1\\times \\iota^*p^*(\\alpha) \n+\\{s^1_1\\}\\times \\Delta_1(\\alpha) \n+\\{S^1_2\\}\\times \\Delta_2(\\alpha)\n\\end{equation*}\nfor some $\\Delta_i(\\alpha)\\in H^*(LM\\times_M LM)$ for $i=1,2$. The\nfirst term in the right hand side is identified using the right square\nof the above commutative diagram. Since $r^*(\\{S^1_i\\})=\\{S^1\\}$ for\n$i=1,2$, \n\\begin{equation*}\n(r\\times 1)^*{e'}^*(\\alpha)=1\\times \\iota^*p^*(\\alpha) + \n\\{S^1\\}\\times \\bigl(\\Delta_1(\\alpha)+\\Delta_2(\\alpha)\\bigr). \n\\end{equation*}\nThe commutativity of the left square implies that this must be equal to \n\\begin{equation*}\n(1\\times\\iota)^*\\Delta^*p^*(\\alpha)\n=1\\times \\iota^*p^*(\\alpha)+\\{S^1\\}\\times \n\\iota^*\\Delta\\bigl(p^*(\\alpha)\\bigr). \n\\end{equation*}\nHence we have \n\\begin{equation*}\n\\iota^*\\bigl(\\Delta(p^*(\\alpha))\\bigr)\n=\\Delta_1(\\alpha)+\\Delta_2(\\alpha)\\in H_*(LM\\times_M LM). \n\\end{equation*}\nTo understand elements $\\Delta_i(\\alpha)$, we consider the following\ncommutative diagram, where $\\ell_1(t)=2t$ for $0\\le t\\le\\frac12$ and \n$\\ell_2(t)=2t-1$ for $\\frac12\\le t\\le 1$. \n\\begin{equation*}\n\\begin{CD}\nS^1_i\\times(LM\\times_M LM) @>{\\ell_i\\times j}>> S^1\\times(LM\\times LM)\n@>{1\\times\\pi_i}>> S^1\\times LM \\\\\n@V{\\iota_i\\times 1}VV @. @V{\\Delta}VV \\\\\n(S^1_1\\vee S^1_2)\\times(LM\\times_M LM) @>{e'}>> M @<{p}<< LM \n\\end{CD} \n\\end{equation*} \nOn the one hand, $(\\iota_1\\times 1)^*{e'}^*(\\alpha)\n=1\\times\\iota^*p^*(\\alpha)+ \\{S^1_1\\}\\times\\Delta_1(\\alpha)$. On the\nother hand, \n\\begin{equation*}\n(\\ell_1\\times j)^*(1\\times \\pi_1)^*\\Delta^*p^*(\\alpha)=\n1\\times j^*\\bigl(p^*(\\alpha)\\times 1\\bigr)\n+\\{S^1_1\\}\\times j^*\\bigl(\\Delta(p^*(\\alpha))\\times 1\\bigr).\n\\end{equation*}\nBy the commutativity of the diagram, we\nget $\\Delta_1(\\alpha)=j^*\\bigl(\\Delta(p^*(\\alpha))\\times\n1\\bigr)$. Similarly, $i=2$ case implies $\\Delta_2(\\alpha)\n=j^*\\bigl(1\\times\\Delta(p^*(\\alpha))\\bigr)$. Hence we finally obtain \n\\begin{equation*}\n\\iota^*\\bigl(\\Delta(p^*(\\alpha))\\bigr)\n=j^*\\bigl(\\Delta(p^*(\\alpha))\\times 1 + 1\\times\n\\Delta(p^*(\\alpha))\\bigr).\n\\end{equation*}\nWith this identification of $\\iota^*\\bigl(\\Delta(p^*(\\alpha))\\bigr)$\nas $j^*$ of some other element, we can continue our initial\ncomputation. \n\\begin{equation*}\n\\begin{split}\n\\Delta\\bigl(&p^*(\\alpha)\\bigr)\\cap(b\\cdot c)\n=(-1)^{d|b|}\\iota_*\\bigl(j^*\\bigl(\\Delta(p^*(\\alpha))\\times 1 + \n1\\times \\Delta\\bigl(p^*(\\alpha)\\bigr)\\bigr)\\cap j_!(b\\times c)\\bigr)\n\\\\\n&=(-1)^{d|b|+(|\\alpha|-1)d} \n\\iota_*j_!\\Bigl(\\bigl(\\Delta(p^*(\\alpha))\\times 1 \n+1\\times \\Delta\\bigl(p^*(\\alpha)\\bigr)\\bigr)\\cap(b\\times c)\\Bigr) \\\\\n&=(-1)^{d(|\\alpha|+|b|-1)}\\iota_*j_!\\Bigl(\n\\bigl(\\Delta(p^*(\\alpha))\\cap b\\bigr)\\times c +\n(-1)^{(|b|+d)(|\\alpha|-1)}b\\times \n\\bigl(\\Delta(p^*(\\alpha))\\cap c\\bigr)\\Bigr) \\\\\n&=\\bigl(\\Delta(p^*(\\alpha))\\cap b\\bigr)\\cdot c +\n(-1)^{(|\\alpha|-1)|b|}b\\cdot\\bigl(\\Delta(p^*(\\alpha))\\cap c\\bigr).\n\\end{split}\n\\end{equation*}\nThis completes the proof of the derivation property of the cap product\nwith respect to the loop product. \n\\end{proof} \n\nNext we describe the relation between the cap product and the BV\noperator in homology and cohomology. \n\n\\begin{proposition} For $\\alpha\\in H^*(LM)$ and $b\\in \\mathbb H_*(LM)$, the BV-operator $\\Delta$ satisfies \n\\begin{equation}\\label{delta and cap}\n\\Delta(\\alpha\\cap b)=(\\Delta\\alpha)\\cap b+(-1)^{|\\alpha|}\\alpha\\cap\n\\Delta b.\n\\end{equation}\n\\end{proposition}\n\\begin{proof}\nOn the one hand, the $S^1$-action map $\\Delta: S^1\\times LM\n\\longrightarrow LM$ satisfies \n\\begin{equation*}\n\\Delta_*\\bigl(\\Delta^*(\\alpha)\\cap([S^1]\\times b)\\bigr)\n=\\alpha\\cap\\Delta_*([S^1]\\times b)\n=\\alpha\\cap\\Delta b.\n\\end{equation*}\nOn the other hand, since $\\Delta^*(\\alpha)=1\\times\\alpha +\n\\{S^1\\}\\times \\Delta\\alpha$, we have \n\\begin{equation*}\n\\begin{split}\n\\Delta_*\\bigl(\\Delta^*(\\alpha)\\cap([S^1]\\times b)\\bigr)\n&=\\Delta_*\\bigl(\n(-1)^{|\\alpha|}[S^1]\\times(\\alpha\\cap b) +\n(-1)^{|\\alpha|-1}[pt]\\times(\\Delta\\alpha\\cap b)\\bigr) \\\\\n&=(-1)^{|\\alpha|}\\Delta(\\alpha\\cap b) + \n(-1)^{|\\alpha|-1}\\Delta\\alpha\\cap b. \n\\end{split}\n\\end{equation*}\nComparing the above two formulas, we obtain \n$\\Delta(\\alpha\\cap b)=\\Delta\\alpha\\cap b + \n(-1)^{|\\alpha|}\\alpha\\cap\\Delta b$. \n\\end{proof} \nSince homology BV operator $\\Delta$ on $\\mathbb H_*(LM)$ acts trivially on $\\mathbb H_*(M)$, the\nfollowing corollary is immediate. \n\\begin{corollary}\nFor $\\alpha\\in H^*(M)$, the cap product of $\\Delta\\alpha$ with\n$\\mathbb H_*(M)\\subset \\mathbb H_*(LM)$ is trivial.\n\\end{corollary} \n\\begin{proof} For $b\\in\\mathbb H_*(M)$, the operator $\\Delta$ acts trivially on both $\\alpha\\cap b$ and $b$. Hence formula \\eqref{delta and cap} implies $(\\Delta\\alpha)\\cap b=0$. \n\\end{proof} \n\nNext, we discuss a behavior of the cap product with respect to the\nloop bracket.\n\n\\begin{theorem} The cap product with $\\Delta\\bigl(p^*(\\alpha)\\bigr)$ \nis a derivation on the loop bracket. Namely, for $\\alpha\\in H^*(M)$\nand $b,c\\in \\mathbb H_*(LM)$,\n\\begin{equation}\\label{cap-loop bracket}\n\\Delta\\bigl(p^*(\\alpha)\\bigr)\\cap\\{b,c\\}\n=\\{\\Delta\\bigl(p^*(\\alpha)\\bigr)\\cap b, c\\} +\n(-1)^{(|\\alpha|-1)(|b|-1)}\\{b, \\Delta\\bigl(p^*(\\alpha)\\bigr)\\cap\nc\\}.\n\\end{equation}\n\\end{theorem} \n\\begin{proof} Our proof is computational using previous results. \nWe use the BV identity as the definition of the loop bracket. Thus,\n\\begin{equation*}\n\\{b,c\\}=(-1)^{|b|}\\Delta(b\\cdot c)-(-1)^{|b|}(\\Delta b)\\cdot c \n-b\\cdot \\Delta c.\n\\end{equation*} \nWe compute the right hand side of \\eqref{cap-loop bracket}. \nFor simplicity, we write $\\Delta\\alpha$\nfor $\\Delta\\bigl(p^*(\\alpha)\\bigr)$. Each term in the right hand side\nof \\eqref{cap-loop bracket} gives\n\\begin{gather*}\n\\!\\!\\!\\!\\!\\!\\!\\{\\Delta\\alpha\\cap b, c\\}\n=(-1)^{|b|-|\\alpha|+1}\\Delta\\bigl((\\Delta\\alpha\\cap b)\\cdot c\\bigr)\n-(-1)^{|b|}(\\Delta\\alpha\\cap \\Delta b)\\cdot c \n-(\\Delta\\alpha\\cap b)\\cdot\\Delta c, \\\\\n\\!\\!\\!\\!\\!\\!\\!\\!\\!\\!\\!\\!\\{b,\\Delta\\alpha\\cap c\\}\n=(-1)^{|b|}\\Delta\\bigl(b\\cdot(\\Delta\\alpha\\cap c)\\bigr)\n-(-1)^{|b|}\\Delta b\\cdot(\\Delta\\alpha\\cap c) \n-(-1)^{|\\alpha|-1}b\\cdot(\\Delta\\alpha\\cap\\Delta c),\n\\end{gather*}\nHere we used \\eqref{delta and cap} for the second term in the first\nidentity and in the third term in the second identity. Combining these\nformulas, we get\n\\begin{multline*} \n\\{\\Delta\\alpha\\cap b, c\\}+ (-1)^{(|\\alpha|-1)(|b|+1)}\n\\{b,\\Delta\\alpha\\cap c\\} \\\\\n=\\bigl[ \n(-1)^{|b|-|\\alpha|+1}\\Delta\\bigl((\\Delta\\alpha\\cap b)\\cdot c\\bigr)\n+(-1)^{|b|+(|\\alpha|-1)(|b|+1)}\n\\Delta\\bigl(b\\cdot(\\Delta\\alpha\\cap c)\\bigr)\\bigr] \\\\\n-\\bigl[(-1)^{|b|}(\\Delta\\alpha\\cap\\Delta b)\\cdot c + \n(-1)^{(|\\alpha|-1)(|b|+1)+|b|}\\Delta b\\cdot(\\Delta\\alpha\\cap c)\\bigr] \\\\\n-\\bigl[(\\Delta\\alpha\\cap b)\\cdot \\Delta c +\n(-1)^{(|\\alpha|-1)(|b|+1)+|\\alpha|-1}b\\cdot(\\Delta\\alpha\\cap \\Delta c)\\bigr].\n\\end{multline*}\nUsing the derivation formula for $\\Delta\\alpha\\cap(\\ )$ with respect\nto the loop product \\eqref{cap derivation}, three pairs of terms above\nbecome\n\\begin{multline*}\n(-1)^{|b|-|\\alpha|+1}\\Delta\\bigl(\\Delta\\alpha\\cap(b\\cdot c)\\bigr)\n-(-1)^{|b|}\\Delta\\alpha\\cap(\\Delta b\\cdot c)\n-\\Delta\\alpha\\cap(b\\cdot\\Delta c) \\\\\n=\\Delta\\alpha\\cap\\bigl[(-1)^{|b|}\\Delta(b\\cdot c)\n-(-1)^{|b|}\\Delta b\\cdot c -b\\cdot\\Delta c\\bigr] = \\Delta\\alpha\\cap\\{b,c\\}.\n\\end{multline*}\nThis completes the proof of the derivation formula for the loop bracket. \n\\end{proof} \n\nRecall that in the BV algebra $\\mathbb H_*(LM)$, for every $a\\in \\mathbb H_*(LM)$ the\noperation $\\{a,\\ \\cdot \\ \\}$ of taking the loop bracket with $a$ is a\nderivation with respect to both the loop product and the loop bracket,\nin view of the Poisson identity and the Jacobi identity. Since we have\nproved that the cap product with $\\Delta p^*(\\alpha)$ for $\\alpha\\in\nH^*(M)$ is a derivation with respect to both the loop product and the\nloop bracket, we wonder if we can extend the BV structure in $\\mathbb H_*(LM)$ to a BV structure in $H^*(M)\\oplus \\mathbb H_*(LM)$. Indeed this is possible by extending the loop product and the loop bracket to elements in $H^*(M)$ as follows.\n\\begin{definition}\nFor $\\alpha,\\beta\\in H^*(M)$ and $b\\in \\mathbb H_*(LM)$, we define their loop product and loop bracket by\n\\begin{equation}\n\\begin{gathered}\n\\alpha\\cdot b=\\alpha\\cap b,\\qquad \n\\{\\alpha,b\\}=(-1)^{|\\alpha|}(\\Delta\\alpha)\\cap b,\\\\\n\\alpha\\cdot\\beta=\\alpha\\cup\\beta, \\qquad \\{\\alpha,\\beta\\}=0.\n\\end{gathered}\n\\end{equation}\nThis defines an associative graded commutative loop product by \\eqref{cap and loop product}, and a bracket product on $H^*(M)\\oplus\\mathbb H_*(LM)$. \n\\end{definition}\nNote that this loop product on $H^*(M)\\oplus\\mathbb H_*(LM)$ reduces to the ring structure on $H^*(M)\\oplus \\mathbb H_*(M)$ mentioned in the introduction. \n\nWith this definition, Poisson identities and Jacobi identities are\nstill valid in $H^*(M)\\oplus \\mathbb H_*(LM)$.\n\n\\begin{theorem} Let $\\alpha,\\beta\\in H^*(M)$, and let $b,c\\in \\mathbb H_*(LM)$. \n\n\\noindent\\textup{(I)} The following Poisson identities are valid in $H^*(M)\\oplus\\mathbb H_*(LM)$\\textup{:} \n\\begin{align}\n\\{\\alpha,\\beta\\cdot c\\}\n&=\\{\\alpha,\\beta\\}\\cdot c+ \n(-1)^{|\\beta|(|\\alpha|-1)}\\beta\\cdot\\{\\alpha,c\\} \\label{eq1}\\\\\n\\{\\alpha\\beta,c\\}&=\\alpha\\cdot\\{\\beta,c\\}\n+(-1)^{|\\alpha||\\beta|}\\beta\\cdot\\{\\alpha,c\\} \\label{eq2}\\\\\n\\{\\alpha,b\\cdot c\\}&=\\{\\alpha,b\\}\\cdot c\n+(-1)^{(|b|-d)(|\\alpha|-1)}b\\cdot\\{\\alpha,c\\} \\label{eq3}\\\\\n\\{\\alpha\\cdot b,c\\}&=\\alpha\\cdot\\{b,c\\}+\n(-1)^{|\\alpha|(|b|-d)}b\\cdot\\{\\alpha,c\\}. \\label{eq4} \n\\end{align}\n\n\\noindent\\textup{(II)} The following Jacobi identities are valid in $H^*(M)\\oplus\\mathbb H_*(LM)$\\textup{:}\n\\begin{align}\n\\{\\alpha,\\{\\beta,c\\}\\}&=\\{\\{\\alpha,\\beta\\},c\\}+\n(-1)^{(|\\alpha|-1)(|\\beta|-1)}\\{\\beta,\\{\\alpha,c\\}\\} \\label{eq5} \\\\\n\\{\\alpha,\\{b,c\\}\\}&=\\{\\{\\alpha,b\\},c\\}+\n(-1)^{(|\\alpha|-1)(|b|-d+1)} \\{b,\\{\\alpha,c\\}\\}. \\label{eq6}\n\\end{align}\n\\end{theorem}\n\\begin{proof} If we unravel definitions, we see that \\eqref{eq1} \nand \\eqref{eq5} are really the same as the graded commutativity of the\ncup product of the following form\n\\begin{align*}\n(\\Delta\\alpha)\\cap(b\\cap c)&=\n(-1)^{|\\beta|(|\\alpha|-1)}\\beta\\cap(\\Delta\\alpha\\cap c), \\\\\n(\\Delta\\alpha)\\cap(\\Delta\\beta\\cap c)&=(-1)^{(|\\alpha|-1)(|\\beta|-1)}\n(\\Delta\\beta)\\cap\\bigl((\\Delta\\alpha)\\cap c\\bigr).\n\\end{align*}\nthe identity \\eqref{eq2} is equivalent to the derivation formula \\eqref{delta and cup} of\nthe cohomology $S^1$ action operator with respect to the cup product.\n\\begin{equation*}\n\\Delta(\\alpha\\cup \\beta)=(\\Delta\\alpha)\\cup \\beta + (-1)^{|\\alpha|}\n\\alpha\\cup (\\Delta \\beta).\n\\end{equation*}\nThe identity \\eqref{eq3} says that $\\Delta\\alpha\\cap (\\ )$ is a\nderivation with respect to the loop product, and the identity\n\\eqref{eq6} says that $\\Delta\\alpha\\cap(\\ )$ is a derivation with\nrespect to the loop bracket. We have already verified both of these\ncases. Thus, what remains to be checked is formula \\eqref{eq4}, which\nsays\n\\begin{equation*}\n\\{\\alpha\\cap b,c\\}=\\alpha\\cap\\{b,c\\}+\n(-1)^{|\\alpha||b|+|\\alpha|}b\\cdot(\\Delta\\alpha\\cap c).\n\\end{equation*}\nUsing the BV identity, the derivation formula \\eqref{delta and cap} \nof the BV operator with\nrespect to the cap product, and properties of $\\alpha\\cap(\\ )$ and\n$\\Delta\\alpha\\cap(\\ )$, we can prove this identity as follows.\n\\begin{multline*}\n(-1)^{|b|-|\\alpha|}\\{\\alpha\\cap b,c\\}\n=\\Delta\\bigl((\\alpha\\cap b)\\cdot c\\bigr)-\\Delta(\\alpha\\cap b)\\cdot c\n-(-1)^{|b|-|\\alpha|}(\\alpha\\cap b)\\cdot\\Delta c \\\\\n=\\Delta\\bigl(\\alpha\\cap(b\\cdot c)\\bigr)\n-(\\Delta\\alpha\\cap b+(-1)^{|\\alpha|}\\alpha\\cap\\Delta b)\\cdot c\n-(-1)^{|b|-|\\alpha|}\\alpha\\cap(b\\cdot\\Delta c) \\\\\n=(\\Delta\\alpha)\\cap(b\\cdot c)\n-(\\Delta\\alpha\\cap b)\\cdot c\n+(-1)^{|\\alpha|}\\alpha\\cap\\Delta(b\\cdot c) \\\\\n-(-1)^{|\\alpha|}\\alpha\\cap(\\Delta b\\cdot c)\n-(-1)^{|b|-|\\alpha|}\\alpha\\cap(b\\cdot\\Delta c) \\\\\n=(-1)^{(|\\alpha|-1)|b|}b\\cdot(\\Delta\\alpha\\cap c)\n+(-1)^{|\\alpha|+|b|}\\alpha\\cap\\{b,c\\}.\n\\end{multline*}\nCanceling some signs, we get the desired formula. This completes the proof. \n\\end{proof}\n\nOther Poisson and Jacobi identities with cohomology elements in the second argument formally follow from above identities by making following definitions for $\\alpha\\in H^*(M)$ and $b\\in\\mathbb H_*(LM)$: \n\\begin{equation*}\nb\\cdot\\alpha=(-1)^{|\\alpha||b|}\\alpha\\cdot b,\\qquad \n\\{b,\\alpha\\}=-(-1)^{(|\\alpha|+1)(|b|+1)}\\{\\alpha,b\\}.\n\\end{equation*}\n\nFor $\\alpha\\in H^*(M)$ we showed that $\\Delta\\alpha\\cap(\\ )$ is a\nderivation for both the loop product and the loop bracket, and\n$\\alpha\\cap(\\ )$ is graded commutative and associative with respect to\nthe loop product. What is the behavior\nof $\\alpha\\cap(\\ )$ is with respect to the loop bracket? \nFormula \\eqref{eq4} says that $\\alpha\\cap(\\ \\cdot\\ )$ on loop bracket is not a derivation or graded commutativity: it is a Poisson identity!\n\nPoisson identities and Jacobi identities we have just proved in $A_*=H^*(M)\\oplus\\mathbb H_*(LM)$ show that $A_*$ is a Gerstenhaber algebra. In fact, $A_*$ can be formally turned into a BV algebra by defining a BV operator $\\boldsymbol\\Delta$ on $A_*$ to be trivial on $H^*(M)$ and to be the usual one on $\\mathbb H_*(LM)$ coming from the homological $S^1$ action. \n\n\\begin{corollary}\\label{BV structure on direct sum} \nThe direct sum $A_*=H^*(M)\\oplus\\mathbb H_*(LM)$ has the structure of a BV algebra. \n\\end{corollary}\n\\begin{proof} Since $\\mathbb H_*(LM)$ is a BV algebra and since we have already verified Poisson identities and Jacobi identities in $A_*$, we only have to verify BV identities in $A_*$. For $\\alpha,\\beta\\in H^*(M)$, an identity \n\\begin{equation*}\n\\boldsymbol\\Delta(\\alpha\\cup\\beta)=(\\boldsymbol\\Delta\\alpha)\\cup\\beta\n+(-1)^{|\\alpha|}\\alpha\\cup(\\boldsymbol\\Delta\\beta)\n+(-1)^{|\\alpha|}\\{\\alpha,\\beta\\}\n\\end{equation*}\nis trivially satisfied since all terms are zero by definition of BV operator $\\boldsymbol\\Delta$ and the loop bracket on $H^*(M)\\subset A_*$. \n\nNext, let $\\alpha\\in H^*(M)$ and $b\\in\\mathbb H_*(LM)$. Since the BV operator $\\boldsymbol\\Delta$ on $A_*$ acts trivially on $H^*(M)$, an identity \n\\begin{equation*}\n\\boldsymbol\\Delta(\\alpha\\cap b)=(\\boldsymbol\\Delta\\alpha)\\cap b\n+(-1)^{|\\alpha|}\\alpha\\cap(\\boldsymbol\\Delta b)\n+(-1)^{|\\alpha|}\\{\\alpha,b\\}\n\\end{equation*}\nis really a restatement of the derivative formula of the homology $S^1$ action operator $\\Delta$ on cap product: $\\Delta(\\alpha\\cap b)=(-1)^{|\\alpha|}\\alpha\\cap(\\Delta b)+(\\Delta\\alpha)\\cap b$ in formula \\eqref{delta and cap}. \n\\end{proof}\n\nIn connection with the above Corollary, we can ask whether $H^*(LM)\\oplus \\mathbb H_*(LM)$ has a structure of a BV algebra. Of course, $H^*(LM)$ together with the cohomological $S^1$ action operator $\\Delta$, which is a derivation, is a BV algebra with trivial bracket product. Thus, as a direct sum of BV algebras, $H^*(LM)\\oplus\\mathbb H_*(LM)$ is a BV algebra, although products between $H^*(LM)$ and $\\mathbb H_*(LM)$ are trivial. More meaningful question would be to ask whether the direct sum $H^*(LM)\\oplus\\mathbb H_*(LM)$ has a BV algebra structure extending the one on $A_*$ described in Corollary \\ref{BV structure on direct sum}. If we want to use the cap product as an extension of the loop product, the answer is no. This is because the cap product with an arbitrary element $\\alpha\\in H^*(LM)$ does not behave associatively with respect to the loop product in $\\mathbb H_*(LM)$: if $\\alpha$ is of the form $\\alpha=\\Delta\\beta$ for some $\\beta\\in H^*(M)$, then $\\alpha\\cap(\\ \\cdot\\ )$ acts as a derivation on loop product in $\\mathbb H_*(LM)$ due to \\eqref{cap derivation} and does not satisfy associativity. \n\n\\begin{remark} In the course of our investigation, we noticed the \nfollowing curious identity, which is in some sense symmetric in three\nvariables, for $\\alpha\\in H^*(M)$ and $b,c\\in\\mathbb H_*(LM)$. \n\\begin{equation}\n\\begin{split}\n\\{\\alpha,b\\cdot c\\}+(-1)^{|b|}\\alpha\\cdot\\{b,c\\}\n&=\\{\\alpha,b\\}\\cdot c+(-1)^{|b|}\\{\\alpha\\cdot b,c\\} \\\\\n&=(-1)^{(|\\alpha|+1)|b|}\\bigl(b\\cdot\\{\\alpha,c\\}\n+(-1)^{|\\alpha|}\\{b,\\alpha\\cdot c\\}\\bigr).\n\\end{split}\n\\end{equation}\nThis identity is easily proved using Poisson identities. But we wonder\nthe meaning of this symmetry.\n\\end{remark} \n\n\n\n\n\n\n\n\n\n\\section{Cap products in terms of BV algebra structure} \n\n\n\n\n\n\nIn the previous section, we showed that the BV algebra structure in $\\mathbb H_*(LM)$ can be extended to the BV algebra structure in $H^*(M)\\oplus \\mathbb H_*(LM)$ by proving Poisson identities and Jacobi identities. This may be a bit surprising. But this turns out to be very natural through Poincar\\'e duality in the following way. For $a\\in \\mathbb H_*(M)$, we denote the element $s_*(a)\\in \\mathbb H_*(LM)$ by $a$, where $s:M\\to LM$ is the inclusion map. \n\n\\begin{theorem} For $a\\in \\mathbb H_*(M)$, let $\\alpha=D(a)\\in H^*(M)$ be its Poincar\\'e dual. Then for any $b\\in \\mathbb H_*(LM)$, the following identities hold. \n\\begin{equation}\np^*(\\alpha)\\cap b=a\\cdot b,\\qquad \n(-1)^{|\\alpha|}\\Delta \\bigl(p^*(\\alpha)\\bigr)\\cap b=\\{a,b\\}.\n\\end{equation}\n\\end{theorem}\n\\begin{proof} Let $1=s_*([M])\\in \\mathbb H_0(LM)$ be the unit of the loop product. Since $p^*(\\alpha)\\cap b=p^*(\\alpha)\\cap(1\\cdot b)=\n\\bigl(p^*(\\alpha)\\cap1\\bigr)\\cdot b$ by \\eqref{cap and loop product}, and since \n\\begin{equation*}\np^*(\\alpha)\\cap1=p^*(\\alpha)\\cap s_*([M])=s_*\\bigl(s^*p^*(\\alpha)\\cap[M]\\bigr)\n=s_*(\\alpha\\cap[M])=a,\n\\end{equation*}\nwe have $p^*(\\alpha)\\cap b=a\\cdot b$. This proves the first identity. \n\nFor the second identity, in the BV identity\n\\begin{equation*}\n(-1)^{|a|}\\{a,b\\}=\\Delta(a\\cdot b)-(\\Delta a)\\cdot b\n-(-1)^{|a|}a\\cdot\\Delta b,\n\\end{equation*}\nthe first term in the right hand side gives \n\\begin{equation*}\n\\Delta(a\\cdot b)=\\Delta(p^*(\\alpha)\\cap\nb)=\\Delta\\bigl(p^*(\\alpha)\\bigr)\\cap b\n+(-1)^{|\\alpha|}p^*(\\alpha)\\cap\\Delta b\n\\end{equation*}\nin view of the first identity we just proved and the derivation\nproperty of the homological $A^1$ action operator on cap products. Here\n$p^*(\\alpha)\\cap\\Delta b=a\\cdot\\Delta b$. Since $a\\in \\mathbb H_*(M)$ is a\nhomology class of constant loops, we have $\\Delta a=0$. Thus,\n\\begin{equation*}\n(-1)^{|a|}\\{a,b\\}=\\Delta\\bigl(p^*(\\alpha)\\bigr)\\cap b\n+(-1)^{|\\alpha|}a\\cdot\\Delta b-(-1)^{|a|}a\\cdot\\Delta b\n=\\Delta\\bigl(p^*(\\alpha)\\bigr)\\cap b,\n\\end{equation*}\nsince $|\\alpha|=-|a|$. Thus, $\\{a,b\\}=(-1)^{|\\alpha|}\n\\Delta\\bigl(p^*(\\alpha)\\bigr)\\cap b$. This completes the proof. \n\\end{proof}\n\nIn view of this theorem, since $\\mathbb H_*(LM)$ is already a BV algebra, the\nPoisson identities and Jacobi identities we proved in section 4 may\nseem obvious. However, what we did in section 4 is that we gave a\n\\emph{new and elementary homotopy theoretic proof} of Poisson\nidentities and Jacobi identities using only basic properties of the\ncap product and the BV identity, when at least one of the elements is\nfrom $\\mathbb H_*(M)$.\n\nThe above theorem shows that loop products and loop brackets with elements in $\\mathbb H_*(M)$ can be written as cap products with cohomology elements in $LM$. Thus, compositions of loop products and loop brackets with elements in $\\mathbb H_*(M)$ corresponds to a cap product with the product of corresponding cohomology classes in $H^*(LM)$. Namely,\n\\begin{corollary}\nLet $a_0, a_1, \\dotsc, a_r\\in \\mathbb H_*(M)$, and let\n$\\alpha_0,\\alpha_1,\\dotsc\\alpha_r\\in H^*(M)$ be their Poincar\\'e\nduals. Then for $b\\in \\mathbb H_*(LM)$,\n\\begin{equation}\na_0\\cdot\\{a_1,\\{a_2,\\dotsc\\{a_r,b\\}\\dotsb\\}\\}\n=(-1)^{|a_1|+\\dotsb+|a_r|}\n\\bigl[\\alpha_0(\\Delta\\alpha_1)(\\Delta\\alpha_2)\n\\dotsm(\\Delta\\alpha_r)\\bigr]\\cap b.\n\\end{equation}\n\\end{corollary}\n\nIn section 2, we considered a problem of intersections of loops with\nsubmanifolds in certain configurations, and we saw that the homology\nclass of the intersections of interest can be given by a cap product\nwith cohomology cup products of the above form (Proposition \\ref{loop\nintersection}). The above corollary computes this homology class in\nterms of BV structure in $\\mathbb H_*(LM)$ using the homology classes of these\nsubmanifolds.\n\n\\begin{remark} \\label{exterior algebra}\nIn general, elements $\\alpha,\\Delta\\alpha$ for $\\alpha\\in H^*(M)$ do not generate the entire cohomology ring $H^*(LM)$. However, if $H^*(M;\\mathbb{Q})=\\Lambda_{\\mathbb{Q}}(\\alpha_1,\\alpha_2,\\dotsc\\alpha_r)$ is an exterior algebra, over $\\mathbb{Q}$, then using minimal models or spectral sequences, we have\n\\begin{equation}\nH^*(LM;\\mathbb{Q})=\\Lambda_{\\mathbb{Q}}(\\alpha_1,\\alpha_2,\\dotsc\\alpha_r)\\otimes\n\\mathbb{Q}[\\Delta\\alpha_1,\\Delta\\alpha_2,\\dotsc\\Delta\\alpha_r],\n\\end{equation}\nand thus we have the complete description of the cap products with any elements in $H^*(LM;\\mathbb{Q})$ in terms of the BV structure in $\\mathbb H_*(LM;\\mathbb{Q})$. \n\\end{remark}\n\n\n\n\n\n\n\n\n\n","meta":{"redpajama_set_name":"RedPajamaArXiv"}} +{"text":"\\section{Introduction}\nNASA's \\textit{Kepler} mission has been continuously monitoring more than\n150\\,000 stars for the past 4 years, searching for transiting exoplanets\n\\citep{Borucki-Kepler}.\nThe unprecedented quality of the photometric light curves delivered by\n\\textit{Kepler} makes them also very well suited to study stellar variability in\ngeneral. Automated light curve classification techniques with the goal to\nrecognize \nand identify the many variable stars hidden in the \\textit{Kepler} database have\nbeen developed. The application of these methods to the\npublic \\textit{Kepler} Q1 data is described in \\cite{Debosscher:2011}. There,\nthe authors paid special attention to the detection of pulsating stars \nin eclipsing binary systems. These systems are relatively rare, and especially\ninteresting for asteroseismic studies \\citep[see\ne.g.][]{Maceroni:2009,Welsh:2011}. By modelling the orbital dynamics of the\nbinary, using photometric time series complemented with spectroscopic follow-up\nobservations, we can\nobtain accurate constraints on the masses and radii of the pulsating stars.\nThese\nconstraints are needed for asteroseismic modelling, and are difficult to obtain\notherwise. \n\nNumerous candidate pulsating binaries were identified in the\n\\textit{Kepler} data, and spectroscopic follow-up is ongoing. In this work, we\npresent the results obtained for KIC 11285625 (BD+48 2812), which turns out to be an\neclipsing binary system containing a $\\gamma$ Dor pulsator. The KIC (\\textit{Kepler} Input Catalog) lists the following properties for this target: $V = 10.143$ \\,mag, $T_{\\rm eff}$ = 6882 K, $\\log g$ = 3.753,\n$R$ = 2.61 $\\unit{R_{\\sun}}$ and $[Fe\/H]$ = -0.127.\nSpectroscopic follow-up revealed it to be a double-lined binary (Section \\ref{rv}). Currently, only a few $\\gamma$ Dor pulsators in double-lined spectroscopic binaries are known, making their analysis very relevant for asteroseismology. \\cite{Maceroni:2013} studied a $\\gamma$ Dor pulsators in an eccentric binary system, observed by CoRoT. Here, we are dealing with a non-eccentric system with a longer orbital period. The longer time span and the higher photometric precision of the \\textit{Kepler} observations (almost a factor 6) allowed us to study the pulsation spectrum with significantly increased frequency resolution and down to lower amplitudes.\n\nA combined\nanalysis of the \\textit{Kepler} light curve and spectroscopic radial velocities\nallowed us to obtain a good binary model for KIC 11285625, resulting in accurate\nestimates of the masses and radii of both components (Section \\ref{binmod}). \nThis binary model was also\nused to disentangle the pulsations from the orbital variability in the\n\\textit{Kepler} light curve in an iterative way. In this paper, we describe\nprocedures to\nperform this task in an automated way. The low signal-to-noise composite\nspectra used for the determination of the radial velocities were used to obtain\nhigher signal-to-noise mean spectra of the components, by means of\nspectral disentangling. These spectra were then used to obtain fundamental\nparameters of the stars (Section \\ref{disentangling}). \nThe resulting pulsation signal of the primary is analysed in detail in Section \\ref{puls-spec}.\nThere we discuss the global characteristics of the frequency spectrum, we list\nthe dominant frequencies and their amplitudes detected by means of prewhitening,\nand search for signs of rotational splitting. \n \n\n\\section{\\textit{Kepler} data}\n\nKIC 11285625 has been almost continuously observed by \\textit{Kepler}; data are\navailable for observing quarters Q0-Q10. We only used long cadence data in this work (with a time resolution of 29.4 minutes), since short cadence data is only available for three quarters and is not needed for our purposes. During quarter Q4, one of the CCD modules failed, the reason why part of the Q4 data are missing. No Q8 data could be observed either, since\nthe target was positioned on the same broken CCD module during that quarter.\nThe \\textit{Kepler} spacecraft needs to make rolls every 3 months (for\ncontinuous illumination of its solar arrays), causing targets to fall on\ndifferent CCD modules depending on the observing quarter. \nGiven the different nature of the CCDs, and the different aperture masks used,\nthis caused some issues with the data reduction. The average flux level of the\nlight curve for KIC 11285625 varies significantly \nbetween quarters, and for some, instrumental trends are visible. The top\npanel of Fig. \\ref{LC-all-quarters} plots all the observed\ndatasets, showing the quarter-to-quarter\nvariations. Merging the quarters correctly is not\ntrivial, since the trends have to be removed for each quarter separately, and \nthe data have to be shifted so that all quarters are at the same average level\n(see below).\nOften, polynomials are used to remove the trends, but it is difficult to\ndetermine a reasonable order for the polynomial. This is especially the case\nwhen large amplitude variability, at time scales comparable to the total time\nspan of the data, is present in the light curve.\n\nFortunately, pixel target files are available for all observed quarters for\nKIC 11285625, allowing us to do the light curve extraction based on custom aperture masks. We can define a custom aperture mask, determining\nwhich pixels to include or not. It turned out that the standard aperture mask, used by\nthe data reduction pipeline, was not optimal for all quarters. \nThis is clearly visible in the top panel of Fig. \\ref{LC-all-quarters} for\nquarters Q3 and Q7. The clear upward trends and smaller variability amplitudes\ncompared to the other quarters are caused by a suboptimal aperture mask. The\ntrends can be explained by a small drift of the star on the CCD, changing the\namount of stellar flux included in the aperture during the quarter.\nChecking the target pixel files for those quarters revealed that pixels with\nsignificant flux contribution were not included in the mask. Fig. \\ref{mask}\nshows the \\textit{Kepler} aperture from the automated pipeline, and a single\ntarget pixel image obtained during quarter Q3. As can be seen, the\n\\textit{Kepler} aperture misses a pixel\nwith significant flux contribution (the lowest blue coloured pixel). \nAdding this pixel to the aperture mask effectively removed the trend in the\nlight curve and increased the variability amplitude to the level of the other\nquarters.\n\nAn automated method was developed to optimize the aperture mask for each\nquarter, with the goal to maximize the signal-to-noise ratio (S\/N) in the\nFourier amplitude spectrum. \nThe standard mask provided with the target pixel files is used as a starting\npoint. The\nmethod then loops over each pixel in the images outside of the original mask\ndelivered by the \\textit{Kepler} pipeline. For each of those pixels, a new light\ncurve is constructed by adding the flux values of the pixel\nto the summed flux of the pixels within the original \\textit{Kepler} mask. The\namplitude spectrum of the resulting light curve is then computed and the S\/N of\nthe highest peak (in this case, the main pulsation frequency of the star) is\ndetermined.\nIf the addition of the pixel increases the S\/N (by a user specified amount), it\nwill be added to the final new light curve once each pixel has been analysed\nthis way. The method also avoids adding pixels containing significant flux of\nneighbouring contaminating targets, since these will normally decrease\nthe S\/N of the signal coming from the main target. It is also possible to detect\ncontaminating pixels within the original \\textit{Kepler} mask, using exactly the\nsame method, but now by excluding one pixel at a time from the original mask \nand checking the resulting S\/N of the new light curves.\n\nAfter determining a new optimal aperture mask for each quarter, the resulting\nlight curves still showed some small trends and offsets, but they were easily\ncorrected using second order polynomials. \nSpecial care is needed however when shifting quarters to the same level, since\nthe average value of the light curve might be ill determined, especially\nwhen large amplitude non-sinusoidal variability is present at time scales\nsimilar\nto the duration of an observing quarter.\nIn our case, we want to make the average out-of-eclipse brightness match\nbetween different quarters, and not the global average of the quarters, since\nthe latter is shifted due to the presence of the eclipses. \nTherefore, we cut out the eclipses first and interpolated the data points in the\nresulting gaps using cubic splines. This was done only to determine the\npolynomial coefficients, which were then used to subtract \nthe trends from the original light curves (including the eclipses). We first\ntransformed the fluxes into magnitudes for each quarter separately, prior to\ntrend removal. The binary modelling code we describe further needs magnitudes\nas input, but the conversion to magnitude also\nresolves any potential quarter-to-quarter variability amplitude changes caused, e.g., by a difference in CCD gains (or any other instrumental effect changing the\nflux values in a linear way). \n\nThe lower panel of Fig. \\ref{LC-all-quarters} shows the resulting light curve\nafter application of our detrending procedure using pixel target files.\n\n\n\n\\begin{figure*}\n \\centering\n \n\\includegraphics[width=14cm,angle=270,scale=0.7]{kplr11285625-all-quarters.ps}\n\\caption{Combination of observing quarters Q1-Q10 for KIC 11285625. The top\npanel shows the `raw'\nSAP (simple aperture photometry) fluxes, as they were delivered, while the lower\npanel shows the resulting combined dataset after optimal mask selection and detrending.}\n\\label{LC-all-quarters}\n\\end{figure*}\n\n\n\n\\begin{figure*}\n \\centering\n \\includegraphics[width=14cm,angle=0,scale=1.0]{aperture.ps}\n\\caption{\\textit{Kepler} aperture (left) and a single target pixel image (right)\nfor KIC 11285625, quarter Q3. Red colours in the pixel image indicate the lowest flux levels, white colours indicate the highest flux levels.}\n\\label{mask}\n\\end{figure*}\n\n\n\n\n\\section{Spectroscopic follow-up and RV determination}\n\\label{rv}\nSpectroscopic follow-up observations were obtained with the HERMES Echelle\nspectrograph at the Mercator telescope on La Palma (see \\cite{HERMES} for a detailed\ndescription of the instrument). \nIn total, 63 spectra with good orbital phase coverage were observed, with\nS\/N in \\textit{V} in the range 40-70. These spectra revealed the\ndouble-lined nature of the spectroscopic binary. \n\nRadial velocities were derived with the HERMES reduction pipeline, using the\ncross-correlation technique \nwith an F0 spectral mask. The choice for this mask was based on the F0 spectral\ntype given by SIMBAD and the effective temperature listed in the KIC (Kepler\nInput Catalogue). We also tried additional spectral masks, given the\ndouble-lined\nnature of the binary, but we did not obtain better results in terms of scatter\non the radial velocity points. Due to the numerous metal lines in the spectrum,\nthe cross-correlation technique worked very well, despite the relatively low S\/N\nspectra. The upper panel of Fig. \\ref{rv-lc} shows the radial velocity measurements obtained for\nboth components of KIC 11285625.\nThe black circles correspond to the primary and the red circles to the\nsecondary. From the scatter on the radial velocity measurements, we conclude\nthat the primary component is pulsating. A Keplerian model was fitted for both\ncomponents (shown also in the upper panel of Fig. \\ref{rv-lc} ), resulting in the orbital parameters listed in Table \\ref{final-par}.\n\nUncertainties were estimated using a Monte-Carlo perturbation approach. \nAlthough the orbital period of the system can be a free parameter in the fitting\nprocedure for the Keplerian model, we fixed it to the much more accurate value obtained from the\n\\textit{Kepler} light curve, given its longer time span (see Section \\ref{binmod}). The quality\nof the fit obtained this way (as judged from the $\\chi^2$ values) is significantly better compared to the case where\nthe orbital period is left as a free parameter.\n\n\n\n\n\\section{Binary model}\n \n\\label{binmod}\nWe used the combined \\textit{Kepler} Q1-Q10 data to obtain a binary model,\nwhich, combined with the results from the spectroscopic analysis, provided us\nwith accurate estimates of the main astrophysical properties\nof both components. Given that we are dealing with a detached binary with no or only\nlimited distortion of both components, we used JKTEBOP, written by\nJ. Southworth \\citep[see][]{Southworth:JKTEBOP1,Southworth:JKTEBOP2}.\nThis code is based on the EBOP code, originally developed by Paul B. Etzel\n\\citep[see][]{Etzel:EBOP,Popper:EBOP}. JKTEBOP has the advantage of being very\nstable, fast, and it is applicable to large datasets with thousands of\nmeasurements, such as the \\textit{Kepler} light curves. \nMoreover, it can easily be scripted (essential in our approach) and includes\nuseful error analysis options such as Monte Carlo and bootstrapping methods.\\\\\n\nSince we are dealing with a light curve containing both orbital variability\n(eclipses) and pulsations, we had to disentangle both phenomena in order to\nobtain a reliable binary model. \nIn the amplitude spectrum of the \\textit{Kepler} light curve (see Fig.\n\\ref{puls-residuals}), the $\\gamma$ Dor type pulsations have numerous significant peaks in\nthe range 0-0.7 $\\unit{d^{-1}}$, with clear repeating patterns up to around 4 $\\unit{d^{-1}}$. In the same region of the amplitude spectrum, we\nalso find peaks \ncorresponding to the orbital variability: a comb-like pattern of harmonics of\nthe orbital frequency ($f_\\mathrm{orb}$, $2f_\\mathrm{orb}$, $3f_\\mathrm{orb}$,...). Moreover, the\nmain pulsation frequency of 0.567 $\\unit{d^{-1}}$ is close to $6f_\\mathrm{orb}$ (0.556\n$\\unit{d^{-1}}$ ), though the peaks are clearly separated, given an estimated\nfrequency resolution\nof $ 1\/T \\approx0.0012\\, d^{-1}$, with T the total time span \nof the combined \\textit{Kepler} Q1-Q10 data. This near coincidence complicated the disentangling\nof both types of variability in the light curve, unlike the case where the\norbital variability is well separated from the \npulsations in frequency domain (e.g. typical for a $\\delta$ Sct pulsator in a\nlong-period binary). We used an iterative procedure, consisting of an\nalternation\nof binary modelling with JKTEBOP, and prewhitening of \nthe remaining variability (pulsations) after removal of the binary model. This\nprocedure can be done in an automated way, and the number of iterations can be\nchosen. The idea is that we gradually improve both the binary model and the\nresidual pulsation spectrum at the same time. In each step of the procedure, we\nused the entire Q1-Q10 dataset without any rebinning. \nOur iterative method is similar to the one described in \\cite{Maceroni:2013} and\nconsists of the following steps: \n\\begin{enumerate}\n \\item Remove the eclipses from the original \\textit{Kepler} light curve and\ninterpolate the resulting gaps using cubic splines.\n \\item Derive a first estimate of the pulsation spectrum by means of iterative\nprewhitening of the light curve without eclipses.\n \\item Remove the pulsation model derived in the previous step from the original\n\\textit{Kepler} light curve.\n \\item Find the best fitting binary model to the residuals using JKTEBOP.\n \\item Remove this binary model from the original \\textit{Kepler} light curve\n(dividing by the model when working in flux, or subtracting the model when\nworking in magnitudes).\n \\item Perform frequency analysis on the residuals, which delivers a new\nestimate of the pulsation spectrum. \n \\item Subtract the pulsation model obtained in the previous step from the\noriginal \\textit{Kepler} light curve. \n \\item Model the residuals (an improved estimate of the orbital variability)\nwith JKTEBOP and repeat the procedure starting from step five. \n\\end{enumerate}\n\nThe procedure is then stopped when convergence is obtained: the $\\chi^{2}$\nvalue of the binary model no longer decreases significantly.\nIn practice, convergence is obtained after just a few iterations, at least for\nKIC 11285625. The procedure can be run automatically,\nprovided that the user has a good initial guess for the orbital parameters.\nThe computation time is dominated by the prewhitening\nstep, which requires the repeated calculation of amplitude spectra. In our case,\nthe complete procedure required a few hours on a single desktop CPU. The top panel of Fig. \\ref{puls-residuals} shows part of the original \\textit{Kepler} data,\nwith the disentangled pulsation contribution overplotted in red, the lower\npanel shows the corresponding amplitude spectrum. In Fig.\n\\ref{rv-lc}, the Keplerian model fit to the HERMES RV data, the binary model\nfit to the \\textit{Kepler} data (pulsation part removed) and the residual light\ncurve are shown together, phased with the orbital period (using the\nzero-point $T_\\mathrm{0}$ = 2454953.751335 d, corresponding to a time of minimum\nof the primary eclipse). The slightly larger scatter in the residuals at the\ningress\nand egress of the primary eclipse is caused by the fact that the\nocculted surface of the pulsating primary is non-uniform and changing over\ntime, due to the non-radial pulsations.\n\nWe also investigated a different iterative approach, where we started by fitting\na binary model directly to the original \\textit{Kepler} light curve, instead of\nfirst removing the pulsations. This way, we do not remove information from the\nlight curve by cutting the eclipses, and we do not need to interpolate the data.\nAlthough the iterative procedure also converged quickly using this approach, the\nfinal binary model was not accurate. Removing the model from the original\n\\textit{Kepler} light curve introduced systematic offsets during the eclipses.\nThe reason is that the initial binary model obtained from the original light\ncurve is inaccurate due to the large amplitude and non-sinusoidal nature of the\npulsations, causing the mean light level between eclipses to be badly defined. \nThe approach starting from the light curve with the pulsations removed prior to\nbinary modelling provided much better results, as judged from the\n$\\chi^{2}$ values and visual inspection of the \nresiduals during the eclipses.\\\\\n\nA linear limb-darkening law was used for both stars, with coefficients\nobtained from \\cite{Prsa:2011}\\footnote{\\url{http:\/\/astro4.ast.villanova.edu\/aprsa\/?q=node\/8}}. \nThese coefficients have been computed for a grid of {$T_{\\rm eff}$},\n{$\\log g$} and [M\/H] values, taking into account \\textit{Kepler's} transmission,\nCCD quantum efficiency and optics. We estimated them using the KIC\n(Kepler Input Catalogue) parameters for a first\niteration, but later adjusted them using our obtained values for {$T_{\\rm eff}$},\n{$\\log g$} and [M\/H] from the combination of binary modelling and spectroscopic\nanalysis (see Section \\ref{disentangling}). We did not take gravity darkening and refection effects into account, given that both components are well separated, and are not significantly deformed by rapid rotation or binarity (the oblateness values returned by JKTEBOP are very small).\n\n\nDuring the iterative procedure, special care was paid to the following\nissues, since they all influence the quality of the final binary and\npulsation models:\n\n\n\\begin{itemize}\n \\item Removal of the pulsations from the original light curve: here, we first\ndetermined all the significant pulsation frequencies (or, more general:\nfrequencies most likely not caused by the orbital motion) from the light curve\nwith the\neclipses removed. Only frequencies with an amplitude signal-to-noise ratio (S\/N)\nabove four are considered. The noise level in the amplitude spectrum is\ndetermined from the region 20- 24 d$^{-1}$, where no significant peaks are\npresent. The often used procedure of computing the noise level in a region\naround the peak of interest would not provide reliable S\/N estimates in our\ncase, given the high density of significant peaks at low frequencies. \nWe also used false-alarm probabilities as an additional significance test,\nwith very similar results regarding the number of significant frequencies. \n\n\\item Initial parameters of the binary model: when running JKTEBOP, initial\nparameters have to be provided for the binary model. These are then refined\nusing non-linear optimization techniques (e.g. Levenberg-Marquardt). \nAlthough the optimization procedure is stable and converges fast, we have no\nguarantee that the global best solution is obtained. If the initial parameters\nare too far off from their true values, the procedure can end up in a local\nminimum. Therefore, we did some exploratory analysis first, to find a good set\nof initial \nparameters, aided by the constraints obtained from the radial velocity data. The\ninitial parameters were also refined: after completion of the first\niterative procedure, the final parameters were used as initial values for a new\nrun, etc. This also confirmed the stability of the solution, although it does\nnot guarantee that the overall best solution has been found. \n\\end{itemize}\n\nError analysis of the final binary model was done using the Monte-Carlo method\nimplemented in JKTEBOP. Here, the input light curve (with the pulsations\nremoved) is perturbed by adding Gaussian noise with standard deviation estimated\nfrom the residuals, and the binary model is recomputed. This procedure is\nrepeated typically 10000 times, to obtain confidence intervals for the obtained\nparameter values.\nThe final parameters from the combined spectroscopic and photometric analysis,\nand their estimated uncertainties (1$\\sigma$), are listed in Table \\ref{final-par}.\n\nGiven the long time span and excellent time sampling of the light curve, we also checked for the presence of eclipse time variations (e.g. due to the presence of a third body).\nWe used two different methods to check for deviations of pure periodicity of the eclipse times. The first method consists of computing the amplitude spectrum of each observing quarter \nof the light curve separately, and comparing the peaks caused by the binary signal (the comb of harmonics of the orbital frequency). We could not detect any change in orbital frequency this way.\nMoreover, the orbital peaks in the amplitude spectrum of the entire light curve also do not show any broadening or significant sidelobes (indicative of frequency changes), compared to the amplitude spectrum of the purely periodic light curve of our best binary model computed with JKTEBOP. The second method consists of determining the times of minima for each eclipse individually by fitting a parabola to the bottom of each eclipse and determining the minimum. We then compared those times with the predicted values using our best value of the orbital period (O-C diagram). This was done both for the original light curve and the light curve with pulsations removed. In the first case, we found indications of periodic shifts of the eclipse times, but these are clearly linked to the pulsation signal in the light curve, which also affects the eclipses. No periodic shifts or trends could be found when analysing the light curve with pulsations removed, and we conclude that we do not detect eclipse time variations.\n\n\\begin{table}\n\\tiny\n\\renewcommand{\\tabcolsep}{0.4mm}\n\\center\n\\caption{Orbital and physical parameters for both components of KIC 11285625,\nobtained from the combined spectroscopic and photometric analysis.}\n \\begin{tabular}{lcc}\n \\hline\n &System&\\\\\n \\hline\n Orbital period $P$ (days)& 10.790492 $\\pm$ 0.000003 &\\\\\n Eccentricity $e$ &$0.005\\pm0.003$ &\\\\\n Longitude of periastron $\\omega$ (\\degr)&90.103 $\\pm$ 0.006&\\\\\n Inclination $i$ (\\degr) & 85.32 $\\pm$ 0.02 &\\\\\n Semi-major axis $a$ ($\\unit{R_{\\sun}}$) &28.8 $\\pm$ 0.1&\\\\\n Light ratio $L_1\/L_2$ &0.38 $\\pm$ 0.01&\\\\\n System RV $\\gamma$ (km $\\unit{s^{-1}}$)&-11.7 $\\pm$ 0.2&\\\\\n $T_\\mathrm{0}$ (days)\\tablefootmark{a}&2454953.751335 $\\pm$ 0.000014 \\\\\n \\hline \n &Primary&Secondary\\\\\n \\hline\n Mass $M$ ($\\unit{M_{\\sun}}$)&$1.543\\pm0.013$ &$1.200\\pm0.016$\\\\\n Radius $R$ ($\\unit{R_{\\sun}}$) & 2.123 $\\pm$ 0.010& 1.472 $\\pm$ 0.014\\\\\n log $g$ &3.973 $\\pm$ 0.006 & 4.18 $\\pm$ 0.01 \\\\\n\\hline\n\\end{tabular}\n\\tablefoottext{a}{Reference time of minimum of a primary eclipse.}\n\\label{final-par}\n\\end{table}\n\n\n\n\\begin{figure}\n \\centering\n \\includegraphics[width=14cm,angle=0,scale=0.66]{rv-lc-model-plots-new.ps}\n\\caption{Upper panel: phased HERMES radial velocity data (open circles) and Keplerian model fits (lines) for both components (black: primary, red: secondary). Middle panel: phased \\textit{Kepler} data (pulsations removed) with the binary model overplotted in red.\nLower panel: phased residuals of the \\textit{Kepler} data, after removal of both the pulsations and the binary model. }\n\\label{rv-lc}\n\\end{figure}\n\n\n\\begin{figure*}\n \\centering\n \n\\includegraphics[width=14cm,angle=270,scale=0.7]{kplr11285625-puls-ampspec-comparison.ps} \n\\caption{Upper panel: resulting light curve after iterative removal of the\norbital variability (in red), with the original light curve shown for comparison\n(in black). Lower panel: Amplitude spectrum of the original\n\\textit{Kepler} light curve (in black), and the \namplitude spectrum of the pulsation `residuals' (in red) after iterative\nremoval of the orbital variability.}\n\\label{puls-residuals}\n\\end{figure*}\n\n\n\\section{Spectral disentangling}\n\\label{disentangling}\n\nTo derive the fundamental parameters $T_{\\rm eff}$, $\\log g$, $[M\/H]$, etc. of the $\\gamma$ Dor pulsator from\nthe high\nresolution HERMES spectra, we first needed to separate the contributions\n of both stars in the measured composite spectra. Given the similar spectral types of the components, and the large number of metal lines in the spectra, \nwe could apply the technique of spectral disentangling to accomplish this\n\\citep{Simon:1994,Hadrava:1995}. Here,\nwe used the FDBinary code \\footnote{http:\/\/sail.zpf.fer.hr\/fdbinary\/}\n\\citep{Ilijic:2004} which is based on Hadrava's Fourier approach\n\\citep{Hadrava:1995}. The overall procedures used to determine the orbital\nparameters and reconstruct the spectra of the component stars from time series\nof observed composite spectra of a spectroscopic double-lined eclipsing binary\nhave been described extensively in \\cite{Hensberge:2000} and\n\\cite{Pavlovski:2005}. \n\nThe user has to provide good initial guesses and confidence intervals for the\norbital parameters, otherwise the method might not converge towards the correct\nsolution. Luckily, we had very good\ninitial parameter values available from the Keplerian orbital fit to the radial\nvelocity data, as was described in Section \\ref{rv}. The final orbital\nparameters\nturned out to be in excellent agreement with the initial values derived from\nspectroscopy. \n\nSpectral disentangling methods have the advantage that they enable us to\ndetermine\nthe orbital parameters of the system in an independent way (although good\ninitial estimates are necessary), and that the resulting component spectra have\na higher signal-to-noise ratio than the individual original composite spectra:\nS\/N $\\sim$ $\\sqrt{N}$, with N the number of composite spectra used for\ndisentangling. The increase in S\/N is illustrated in\nFig. \\ref{disentangled-primary}, where a single observed spectrum (corrected for\nDoppler shift) is compared to the disentangled spectrum for the primary\ncomponent. Renormalization of the disentangled spectra was done using\nthe light factors obtained from the binary modelling of the \\textit{Kepler}\nlight\ncurve. \n\n\\begin{figure}\n\n \\centering\n\n\\includegraphics[width=14cm,angle=270,scale=0.5]{disentangled-spectrum.ps}\n\\caption{Comparison of a single observed composite spectrum (black circles) with\nthe disentangled spectrum of the primary component (red lines), illustrating\nthe significant increase in S\/N that is obtained.}\n\\label{disentangled-primary}\n\\end{figure}\n\nFor the spectrum analysis of both components of KIC\\,11285625, we\nuse the GSSP code \\citep[Grid Search in Stellar Parameters,][]{Tkachenko2012} that finds the optimum\nvalues of $T_{\\rm eff}$, $\\log g$, $\\xi$, $[M\/H]$, and $v\\sin{i}$\\ from the minimum\nin $\\chi^2$ obtained from a comparison of the observed spectrum with\nthe synthetic ones computed from all possible combinations of the\nabove mentioned parameters. The errors of measurement (1$\\sigma$\nconfidence level) are calculated from the $\\chi^2$ statistics, using the\nprojections of the hypersurface of the $\\chi^2$ from all grid points\nof all parameters in question. In this way, the estimated error bars include\nany possible model-inherent correlations between the parameters but do not take\ninto account imperfections of the model (such as incorrect atomic data, non-LTE\neffects, etc.) and\/or continuum normalization. A\ndetailed description of the method and its application to the\nspectra of \\textit{Kepler} $\\beta$\\,Cep and SPB candidate stars as well as\n$\\delta$\\,Sct and $\\gamma$\\,Dor candidate stars are given in\n\\citet{Lehmann2011} and \\citet{Tkachenko2012}, respectively.\n\nFor the calculation of synthetic spectra, we used the LTE-based\ncode SynthV \\citep{Tsymbal1996} which allows the computation of the\nspectra based on individual elemental abundances. The code uses\ncalculated atmosphere models which have been computed with the\nmost recent, parallelised version of the LLmodels program\n\\citep{Shulyak2004}. Both programs make use of the VALD database\n\\citep{Kupka2000} for a selection of atomic spectral lines.\nThe main limitation of the LLmodels code is that the models are\nwell suited for early and intermediate spectral type stars, but\nnot for very hot and cool stars where non-LTE effects or\nabsorption in molecular bands may become relevant, respectively.\n\n\n\\begin{table}\n\\caption{Fundamental parameters of both components of KIC\\,11285625.}\\label{Table: Fundamental parameters}\n\\begin{tabular}{lll}\n\\hline\\hline\n\\multicolumn{1}{c}{Parameter\\rule{0pt}{9pt}} & Primary & \\multicolumn{1}{c}{Secondary}\\\\\n\\hline\n$T_{\\rm eff}$\\,(K)\\rule{0pt}{11pt} &$6960\\pm 100$ & $7195\\pm200$\\\\\n$\\log g$\\,(fixed)\\rule{0pt}{11pt} & 3.97 & 4.18\\\\\n$\\xi$\\,(km\\,s$^{-1}$)\\rule{0pt}{11pt} & $0.95\\pm0.30$ & $0.09\\pm0.25$\\\\\n$v\\sin{i}$\\,(km\\,s$^{-1}$)\\rule{0pt}{11pt} & $14.2\\pm1.5$ & $8.4\\pm1.5$\\\\\n$[M\/H]$\\,(dex)\\rule{0pt}{11pt} & $-0.49\\pm0.15$ & $-0.37\\pm0.3$\\\\\n\\hline\n\\end{tabular}\n\\tablefoot{The temperature of the secondary is not reliable, as discussed in the text.}\n\\end{table}\n\nGiven that KIC\\,11285625 is an eclipsing, double-lined (SB2)\nspectroscopic binary for which unprecedented quality (\\textit{Kepler})\nphotometry is available, the masses and the radii of both components\nwere determined with very high precision. Having those two\nparameters, we evaluated surface gravities of the two stars with\nfar better precision than one would expect from the spectroscopic\nanalysis given that the S\/N of our spectra varies between 40 and 70,\ndepending on the weather conditions on the night when the\nobservations were taken. Thus, we fixed $\\log g$\\ for both\ncomponents to their photometric values (3.97 and 4.18 for the\nprimary and secondary, respectively) and adjusted the effective\ntemperature $T_{\\rm eff}$, micro-turbulent velocity $\\xi$, projected\nrotational velocity $v\\sin{i}$, and overall metallicity [M\/H] for both\nstars based on their disentangled spectra.\nGiven that the contribution of the primary component to the total\nlight of the system is significantly larger than that of the\nsecondary (72\\% compared to 28\\%) and that its decomposed spectrum\nis consequently better defined and is of higher quality than that of\nthe secondary, we were also able to evaluate individual abundances\nfor this star besides the fundamental atmospheric parameters.\nTable~\\ref{Table: Fundamental parameters} lists the fundamental\nparameters of the two stars whereas Table~\\ref {Table: Individual abundances} summarizes the results\nof chemical composition analysis for the primary component. The overall metallicities of the two\nstars agree within the quoted errors, but the derived temperature for the\nsecondary is not reliable, since we find \nit to be about 200~K hotter than the primary. From the relative eclipse depths,\nwe estimate the temperature of the secondary to be about 6400~K. The cause of\nthis temperature discrepancy is the poor quality of the disentangled spectrum of\nthe secondary, given its smaller light contribution. Normalization errors in\nthe spectra can easily translate into temperature errors of several hundred\nKelvin. Note that the listed uncertainties for the spectroscopic temperatures do not take normalization errors into account.\n\n\nFigure~\\ref{Figure: HR diagram} shows the position of the primary component in\nthe $\\log(T_{\\rm eff})$-$\\log g$\\ diagram, with respect to the observational $\\delta$~Sct\\ (solid\nlines) and $\\gamma$~Dor\\ (dashed lines) instability strips as given by\n\\cite{Rodriguez:2001} and \\cite{Handler:DSCUT}, respectively. The primary falls\ninto the $\\gamma$~Dor\\ instability strip, meaning that pure g-modes are expected to be\nexcited in its interior.\n\n\\begin{table}\n\\tabcolsep 2.2mm\\caption{Atmospheric chemical composition of the\nprimary component of KIC\\,11285625.}\n\\label{Table: Individual abundances}\n\\begin{tabular}{llllll}\n\\hline\\hline\n\\multicolumn{1}{c}{Element\\rule{0pt}{9pt}} & Value & \\multicolumn{1}{c}{Sun} & \\multicolumn{1}{c}{Element\\rule{0pt}{9pt}} & Value & \\multicolumn{1}{c}{Sun}\\\\\n\\hline\nFe\\rule{0pt}{11pt} & --0.58\\,(15) & --4.59 & Mg & --0.65\\,(23) & --4.51\\\\\nTi\\rule{0pt}{11pt} & --0.40\\,(20) & --7.14 & Ni & --0.53\\,(20) & --5.81\\\\\nCa\\rule{0pt}{11pt} & --0.41\\,(27) & --5.73 & Cr & --0.35\\,(27) & --6.40\\\\\nMn\\rule{0pt}{11pt} & --0.50\\,(35) & --6.65 & C & --0.28\\,(40) & --3.65\\\\\nSc\\rule{0pt}{11pt} & --0.31\\,(40) & --8.99 & Si & --0.68\\,(40) & --4.53\\\\\nY\\rule{0pt}{11pt} & --0.22\\,(45) & --9.83 & & & \\\\\n\\hline\n\\end{tabular}\n\\tablefoot{All values are in dex and on a\nrelative scale (compared to the Sun). Label ``Sun'' refers to the\nsolar composition given by \\citet{Grevesse2007}. Error bars\n(1-$\\sigma$ level) are given in parentheses in terms of last digits.}\n\\end{table}\n\n\\begin{figure}\n\\includegraphics[scale=0.9,clip=]{K11285625_Teff_logg.eps}\n\\caption{{\\small Location of the primary of KIC\\,11285625 in the\n$\\log(T_{\\rm eff})$-$\\log g$\\ diagram. The $\\gamma$~Dor\\ and the red edge of the $\\delta$~Sct\\\nobservational instability strips\nare represented by the dashed and solid lines, correspondingly. According to\nthe photometric $T_{\\rm eff}$\\ and $\\log g$, the secondary would be located in the lower\nright corner of the diagram, outside both instability strips. }} \\label{Figure:\nHR diagram}\n\\end{figure}\n\n\n\\section{Pulsation spectrum}\n\\label{puls-spec}\n\nFig. \\ref{as-puls-global} shows the amplitude spectrum of the \\textit{Kepler}\nlight curve with the binary model removed, in the region 0-2 d$^{-1}$, where\nmost of the dominant pulsation frequencies are found. Clearly visible\nare the three groups of peaks around 0.557, 1.124 and 1.684 {d$^{-1}$}. Some of the\nfrequencies found in the groups around 1.124 and\n1.684 {d$^{-1}$} are harmonics of frequencies present in the group around\n0.557 {d$^{-1}$}. These harmonics are caused by the\nnon-linear nature of the pulsations, and have been observed for many pulsators\nobserved by CoRoT and \\textit{Kepler}, along almost the entire main-sequence\n\\citep{Degroote:2009,Poretti:2011,Breger:2011,Balona:2012}, and in $\\gamma$~Dor\\ stars in\nparticular \\citep{Tkachenko:2013}. Closer\ninspection of the\nmain frequency groups revealed that they consist of several closely spaced\npeaks,\nalmost\nequally spaced with a frequency of $\\sim$ 0.010 {d$^{-1}$}. A likely explanation is\namplitude modulation of the pulsation signal on a timescale of $\\sim$ 100\ndays. Mathematically, the effect of amplitude modulation can be\ndescribed as follows: imagine a simplified case where a single periodic\nnon-linear\npulsation signal is being modulated with a general periodic function. We can\nwrite this signal as a product of two sums of sines, where the number of terms\n(harmonics) in each sum depends on how non-linear (non-sinusoidal) the signals\nare: \n\\begin{equation}\n\\sum_{i=1}^{N_\\mathrm{mod}} a_\\mathrm{i} \\sin{[2\\pi f_\\mathrm{mod}\ni t + \\phi^\\mathrm{mod}_\\mathrm{i}]} \\sum_{j=1}^{N_\\mathrm{puls}} b_\\mathrm{j} \\sin{[2\\pi f_\\mathrm{puls}\nj t + \\phi^\\mathrm{puls}_\\mathrm{j}]} ,\n\\end{equation}\nwith $f_\\mathrm{mod}$ the modulation frequency and $f_\\mathrm{puls}$ the pulsation frequency.\nThis product can be rewritten as a sum, using Simpson's rule:\n\\begin{eqnarray}\n\\sum_{i=1}^{N_\\mathrm{mod}} \\sum_{j=1}^{N_\\mathrm{puls}} \\frac{a_\\mathrm{i} b_\\mathrm{j}}{2}(\\cos{[2\\pi\n(f_\\mathrm{puls} j-f_\\mathrm{mod} i)t+\\phi^\\mathrm{puls}_\\mathrm{j}-\\phi^\\mathrm{mod}_\\mathrm{i}]}-\\\\\n\\cos{[2\\pi (f_\\mathrm{puls} j+f_\\mathrm{mod} i)t+\\phi^\\mathrm{puls}_\\mathrm{j}+\\phi^\\mathrm{mod}_\\mathrm{i}]}). \\nonumber\n\\end{eqnarray}\nIn the Fourier transform of this signal, we will thus see peaks at\nfrequencies which are linear combinations of the pulsation frequency and the\nmodulation frequency, where the number of combinations depends on how\nnon-linear\nboth signals are. Most of the observed substructure in the amplitude spectrum\ncan be explained by amplitude modulation of a pulsation signal with\n$f_\\mathrm{mod}\\sim$ 0.010 {d$^{-1}$}. A more detailed description of amplitude\nand frequency modulation in light curves can be found in \\cite{Benko:2011}.\nSince the period of the amplitude modulation is close to the length of a\n\\textit{Kepler} observing quarter, we checked for a possible instrumental\norigin. A very strong argument against this, is the fact that the modulation is\nnot present in the eclipse signal of the light curve, but is only affecting the\npulsation peaks. \n\nTo study the pulsation signal in detail, we performed a complete frequency\nanalysis using an iterative prewhitening procedure. The Lomb-Scargle\nperiodogram was used in combination with false-alarm probabilities to detect the\nsignificant frequencies present in the light curve. Prewhitening of the\nfrequencies was performed using linear least-squares fitting with non-linear\nrefinement. In total, hundreds of formally significant frequencies were\ndetected. We stress here that formal significance does not imply that a\nfrequency has a physical interpretation, e.g. in the sense of all being\nindependent pulsation modes. In fact, most of them are not independent at all;\nmany combination\nfrequencies and harmonics are present and many peaks arise from the fact that\nwe are performing Fourier analysis on a signal that is not strictly periodic.\nTable \\ref{freqs} lists the 50\nmost significant frequencies, together with their amplitude, and estimated S\/N.\nThe noise level used to calculate the S\/N was estimated from the average\namplitude in the frequency range between 20 and 24 {d$^{-1}$}. The last column\nindicates possible combination frequencies and harmonics. The lowest order\ncombination is always listed, but for some frequencies, these can be\nwritten equivalently as a different higher order combination of more dominant\nfrequencies (they are listed in brackets). A complete list of frequencies\nis available online in electronic format at the CDS \\footnote{Centre de\nDonn\\'{e}es astronomiques de Strasbourg,\n http:\/\/cdsweb.u-strasbg.fr\/}.\nClearly, many frequencies can\nbe explained by low-order linear combinations of the three most dominant\nfrequencies. However, given the amplitude modulation,\nthese dominant frequencies are likely not independent (corresponding to\ndifferent\npulsation modes). Instead, they are probably combination frequencies of the\nreal\npulsation frequency and (harmonics of) the modulation frequency $f_\\mathrm{mod}$\n$\\sim$ 0.010 {d$^{-1}$}. \nLooking back at the RV data for the pulsating component,\nwe expect the larger scatter in comparison to the secondary to be caused by the\npulsations. After subtraction of the Keplerian orbit fit, we performed\nfrequency analysis on the residuals, and found 2 significant\npeaks corresponding to frequencies detected in the \\textit{Kepler} data\n(f1 and f7 in Table \\ref{freqs}). The amplitude spectra of the RV residuals for\nboth components are shown in Fig. \\ref{ampspec-rv-res}. \n\nFrom spectroscopy, we found v sin i = 14.2 $\\pm$ 1.5 km\/s for the pulsating\nprimary component and v sin i = 8.4 $\\pm$ 1.5 km\/s for the secondary. Assuming that the rotation axes are perpendicular to the orbital plane, and using the orbital and stellar\nparameters listed in Table \\ref{final-par}, this corresponds to a rotation\nperiod of about 7.5 $\\pm$ 1.3 d for the primary and 8.8 $\\pm$ 1.9 d for the\nsecondary. These values suggest super-synchronous rotation, but on their own do\nnot provide sufficient evidence, given the uncertainties (1$\\sigma$), especially\nnot for the secondary.\n\nWe analysed the pulsation signal to\ndetect signs of rotational splitting of the pulsation frequencies in two\ndifferent ways: by computing the autocorrelation function of the\namplitude spectrum and by using the list of detected significant frequencies.\nThe autocorrelation function between 0 and 0.7 {d$^{-1}$} is\nshown in Fig. \\ref{autocorrelation}. Clearly, the amplitude spectrum is\nself-similar for many different frequency shifts, as is evidenced by the\ncomplex structure of the autocorrelation function. Although the\nautocorrelation function is dominated by the highest peaks in the\namplitude spectrum and their higher harmonics, we can relate some smaller peaks\nto the properties of the system. For example, the peaks indicated with\nthe red arrows correspond to the orbital frequency and the rotational frequency of the primary as derived from spectroscopy (at 0.0926 and 0.1333 {d$^{-1}$} respectively). \n\nNext, we searched the list of significant frequencies for any possible frequency\ndifferences occurring several times (given the frequency resolution). This way,\nsplittings of lower amplitude peaks can be detected more easily, which is not the\ncase when using the autocorrelation function. Since the number of significant\nfrequencies is so large, several frequency differences occur multiple times\npurely by chance (this was checked by using a list of randomly generated\nfrequencies), so one must be careful when interpreting the results\n\\citep[see e.g.][]{Papics:2012}.\nIn our search for splittings, we used frequency lists of different lengths,\nranging from the first 50 to a maximum of several hundred significant\nfrequencies (down to a S\/N of 10). We used a rather strict cutoff value of\n0.0001 {d$^{-1}$} to accept frequency differences\nas being equal ( 0.1\/T, with T the total time span of the light curve). Next, we ordered all possible frequency differences in increasing\norder of occurrence. This always resulted in the same differences showing up in\nthe top of the lists. Table \\ref{freqdiffs} shows the most abundant differences detected in a conservative list of `only' 400 frequencies (down to a S\/N of about 50). \nClearly, many of these differences are related to the\namplitude modulation in the light curve (as discussed above), with values around\n0.010 {d$^{-1}$} (suspected modulation frequency) and 0.020 {d$^{-1}$} (twice the\nmodulation frequency) occurring often. Values around 0.567 {d$^{-1}$} are related to\nthe presence of higher harmonics of the pulsation frequencies. \nIn the autocorrelation function, clear peaks are present around the orbital\nfrequency, while the orbital frequency itself only\nshows up in the list of frequency differences when going down to S\/N values\naround 10. Most likely, this is caused by small residuals of the binary signal\n(eclipses) in the light curve. \nWe also find values very close to the rotation\nfrequency from spectroscopy and values in between the rotation frequency and the orbital frequency. They are also visible as the group of peaks in the\nautocorrelation function around 0.1 {d$^{-1}$}. We interpret these as the result of\nrotational splitting. The values are compatible with the spectroscopic results\nobtained for the primary, and hence provide stronger evidence for\nsuper-synchronous rotation. We cannot unambiguously identify one unique\nrotational splitting, but rather a range of possible values. The difference in\nmeasured splitting values across the spectrum suggests non-rigid rotation in\nthe interior of the primary \\citep[see e. g.][]{Aerts:2003, Aerts:book,Dziembowski:2008}. \n \n \nIn Fig. \\ref{as-puls-global}, the structures in the amplitude spectrum caused by\nrotational splitting are indicated by means of red arrows. Clearly, the pattern\nis repeated for the higher harmonics of the pulsation frequencies. \n\nFinally, the second-most dominant peak in\nthe amplitude spectrum almost coincides with the sixth harmonic of the orbital\nfrequency. This suggests tidally affected\npulsation, although this is not expected for non-eccentric systems.\nMoreover, the frequencies do not match perfectly, and the second-most dominant\npeak is likely not an independent pulsation mode, but caused by the amplitude\nmodulation of the main oscillation frequency.\n\n\\begin{figure*}\n \\centering\n \\includegraphics[width=14cm,angle=270,scale=0.7]{as-puls-global.ps}\n\\caption{Part of the amplitude spectrum (below 2 {d$^{-1}$}) of the \\textit{Kepler}\nlight curve with the binary\nmodel removed. The red arrows indicate the splitting of groups of peaks caused\nby rotation with a splitting value around 0.1 {d$^{-1}$}.}\n\\label{as-puls-global}\n\\end{figure*}\n\n\n\\begin{figure}\n \\centering\n \\includegraphics[width=14cm,angle=270,scale=0.5]{autocorrelation.ps}\n\\caption{Autocorrelation of the amplitude spectrum, after removal of the binary\nmodel.}\n\\label{autocorrelation}\n\\end{figure}\n\n\n\n\n\\begin{table*}\n\\center\n\\caption{Dominant fifty frequencies with their amplitude and S\/N, detected in the\n\\textit{Kepler} light curve with the binary model removed, using the\nprewhitening technique as explained in the text.}\n \\begin{tabular}{c|c|c|c|c}\nNumber&Frequency (d$^{-1}$) & Amplitude (mmag)& S\/N&Combination\\\\\n\\hline\n 1 &0.5673 &17.487&720.1&-\\\\\n 2 &0.5575 &13.482&656.0&-\\\\\n 3 &0.5685 &8.378 &460.2&-\\\\\n 4 &1.1250 &7.468 &450.2&f1+f2\\\\\n 5 &0.5467 &6.559 &400.4&2f2-f3\\\\\n 6 &1.1359 &5.462 &355.8&f1+f3\\\\\n 7 &0.6594 &4.704 &323.4&-\\\\\n 8 &1.1141 &4.466 &311.7&f1+f5 (f1+2f2-f3)\\\\\n 9 &0.5563 &4.124 &296.7&f4-f3 (f1+f2-f3)\\\\\n 10 &0.4348 &3.192 &237.7&-\\\\\n 11 &0.4403 &3.288 &246.5&-\\\\\n 12 &1.6936 &2.842 &215.5&f3+f4 (f1+f2+f3)\\\\\n 13 &0.5666 &2.547 &195.9&-\\\\\n 14 &0.8985 &2.286 &178.8&-\\\\\n 15 &1.1041 &2.123 &168.1&f2+f5 (3f2-f3)\\\\\n 16 &0.3029 &2.080 &164.6&2f10-f13\\\\\n 17 &0.4483 &2.014 &161.4&-\\\\\n 18 &1.6925 &2.009 &163.2&f1+f4 (2f1+f2)\\\\\n 19 &1.6716 &1.969 &159.8&f4+f5 (f1+3f2-f3)\\\\\n 20 &0.5357 &1.963 &156.4&2f5-f2 (3f2-2f3)\\\\\n 21 &0.2365 &1.864 &150.7&2f1-f14\\\\\n 22 &1.1258 &1.847 &150.2&f2+f3\\\\\n 23 &0.4777 &1.831 &150.8&2f3-f7\\\\\n 24 &0.4337 &1.780 &148.4&2f5-f7 \\\\\n 25 &0.5784 &1.770 &147.7&f4-f5 (f1-f2+f3)\\\\\n 26 &1.2268 &1.766 &149.6&f1+f7\\\\\n 27 &1.6816 &1.738 &146.2&2f1+f5 (2f1+2f2-f3)\\\\\n 28 &0.4656 &1.712 &145.9&f4-f7 (f1+f2-f7)\\\\\n 29 &0.1272 &1.729 &149.5&f1-f11\\\\\n 30 &1.0023 &1.643 &142.2&f1+f10\\\\\n 31 &0.9979 &1.667 &146.7&f2+f11\\\\\n 32 &0.5582 &1.612 &143.8&f22-f1 (f2+f3-f1)\\\\\n 33 &0.6583 &1.539 &138.1&2f5-f10\\\\\n 34 &1.1346 &1.514 &135.7&2f1\\\\\n 35 &0.2477 &1.456 &131.7&2f7-2f20\\\\\n 36 &0.9804 &1.398 &127.6&f5+f24 (3f5-f7)\\\\\n 37 &1.2167 &1.399 &127.5&f2+f7\\\\\n 38 &1.7031 &1.388 &126.5&f1+f3\\\\\n 39 &0.4115 &1.363 &124.1&f7-f35 (2f20-f7)\\\\\n 40 &2.2609 &1.326 &122.2&f4+f6 (2f1+f2+f3)\\\\\n 41 &0.5257 &1.308 &120.3&2f5-f1\\\\\n 42 &0.5458 &1.267 &116.8&f8-f3 (f1+2f2-2f3)\\\\\n 43 &0.4200 &1.272 &117.2&2f7-f14\\\\\n 44 &0.0909 &1.240 &113.9&f7-f3\\\\\n 45 &0.5677 &1.220 &112.9&f1\\\\\n 46 &1.7043 &1.209 &113.8&f3+f6 (f1+2f3)\\\\\n 47 &0.6720 &1.201 &114.5&2f9-f11\\\\\n 48 &1.1368 &1.194 &114.4&2f3\\\\\n 49 &1.1470 &1.160 &113.0&2f6-f4 (f1-f2+2f3)\\\\\n 50 &0.2579 &1.159 &113.3&f4-2f24\\\\\n\\hline\n\n\n\\end{tabular}\n\\tablefoot{Typical uncertainties on the frequency values are\n$\\sim$ $10^{-3}$ d$^{-1}$ (using the Rayleigh criterion), and $\\sim 5 \\times\n10^{-3}$ mmag for the amplitudes. The last column indicates possible\ncombination frequencies and harmonics.}\n\\label{freqs}\n\\end{table*}\n\n\n\\begin{table*}\n\\center\n\\caption{Frequency differences and corresponding periods (in order of decreasing occurrence), detected in the list of the first 400 frequencies obtained using iterative prewhitening.}\n \\begin{tabular}{c|c|c}\nFrequency difference (d$^{-1}$)& Period (d)&Remarks\\\\\n\\hline\n 0.5674 & 1.7624 & harmonics of pulsation frequencies\\\\ \n 0.0108 & 92.5926 & amplitude modulation\\\\\n 0.5675 & 1.7621 & harmonics of pulsation frequencies\\\\\n 0.1244 & 8.0386 & rotational splitting? \\\\ \n 0.5575 & 1.7937 & harmonics of pulsation frequencies \\\\\n 0.1133 & 8.8261 & rotational splitting? \\\\\n 0.5685 & 1.7590 & harmonics of pulsation frequencies \\\\ \n 0.5672 & 1.7630 & harmonics of pulsation frequencies \\\\\n 0.1010 & 9.9010 & rotational splitting? \\\\\n 0.0210 & 47.6190 & amplitude modulation\\\\ \n 0.5577 & 1.7931 & harmonics of pulsation frequencies \\\\\n 0.3132 & 3.1928 & \\\\\n 0.2492 & 4.0128 & \\\\ \n 0.0110 & 90.9091 & amplitude modulation \\\\\n 0.0284 & 35.2113 & \\\\\n 0.2267 & 4.4111 & \\\\ \n 0.3318 & 3.0139 & \\\\\n 0.0109 & 91.7431 & amplitude modulation \\\\\n 0.0070 & 142.8571 & \\\\ \n 0.3353 & 2.9824 & \\\\\n ... & ... &\\\\\n\\hline \n\\end{tabular}\n\\label{freqdiffs}\n\\end{table*}\n\n\n\n\\begin{figure}\n \\centering\n \\includegraphics[width=14cm,angle=270,scale=0.5]{ampspec-rv-res.ps}\n\\caption{Amplitude spectrum of the radial velocity residuals for both\ncomponents, after subtraction of the best Keplerian orbit fit. The two highest\npeaks for the primary (indicated) correspond to frequencies detected in the\n\\textit{Kepler} light curve.}\n\\label{ampspec-rv-res}\n\\end{figure}\n\n\n\n\n\n\\section{Conclusions}\n\nWe have obtained accurate system parameters and astrophysical\nproperties for KIC 11285625, a double-lined eclipsing binary\nsystem with a $\\gamma$ Dor pulsator discovered by the \\textit{Kepler} space\nmission. The excellent \\textit{Kepler} data with a total time span of almost\n1000 days have been analysed together with high resolution HERMES spectra.\nThe individual composite spectra could not be used to derive fundamental\nparameters such as\n{$T_{\\rm eff}$} and {$\\log g$}, given their insufficient S\/N. This was achieved after using\nthe spectral disentangling technique for both components. \n\nAn iterative automated method was developed to separate the orbital variability\nin the \\textit{Kepler} light curve from the variability due to the pulsations of\nthe primary. The fact that the orbital frequency and its overtones are located \nin the same frequency range as the pulsation frequencies, made a simple\nseparation technique (such as a filter in the frequency domain) insufficient.\nWe plan to develop this technique further and apply it to other binary systems\nin the \\textit{Kepler} database.\n\nAfter removal of the best binary model, we studied the residual pulsation\nsignal in detail, and found indications for rotational splitting of the pulsation\nfrequencies, compatible with super-synchronous and non-rigid internal rotation.\nA detailed asteroseismic analysis of the $\\gamma$ Dor pulsator and comparison\nwith theoretical models can now be attempted on the basis of this observational work, which\nconstitutes an excellent starting point for stellar modelling of a $\\gamma$~Dor\\\nstar. A concrete interpretation of the detected amplitude modulation must await a much longer \\textit{ Kepler} light curve, given the relatively long modulation period.\n\n\\begin{acknowledgements}\nThe research leading to these results has received funding from the European\nResearch Council under the European Community's Seventh Framework Programme\n(FP7\/2007--2013)\/ERC grant agreement n$^\\circ$227224 (PROSPERITY), from the\nResearch Council of K.U.Leuven (GOA\/2008\/04), and from the Belgian federal\nscience\npolicy office (C90309: CoRoT Data Exploitation); A. Tkachenko and P. Degroote\nare postdoctoral fellows of the Fund for Scientific Research (FWO), Flanders,\nBelgium. \nFunding for the \\textit{Kepler} Discovery mission is provided by NASA's Science\nMission Directorate.\nSome of the data presented in this paper were obtained from the\nMultimission Archive at the Space Telescope Science Institute (MAST). STScI is\noperated by the Association of Universities for Research in Astronomy, Inc.,\nunder NASA contract NAS5-26555. Support for MAST for non-HST data is provided by\nthe NASA Office of Space Science via grant NNX09AF08G and by other grants and\ncontracts.\nThis research has made use of the SIMBAD database,\noperated at CDS, Strasbourg, France.\nWe would like to express our special thanks to the numerous people who helped\nmake the \\textit{Kepler} mission possible.\n\\end{acknowledgements}\n\n\\bibliographystyle{aa}\n","meta":{"redpajama_set_name":"RedPajamaArXiv"}} +{"text":"\\section{Introduction and preliminary results}\n\nIt is well known from elementary calculus that an arbitrary\npolynomial $f$ with complex coefficients (complex polynomial) of\ndegree $n \\in \\mathbb{N}$\n$$f(z)= a_0 z^{n}+ a_1 z^{n-1}+ \\dots + a_{n-1} z + a_n, \\ a_0\\neq\n0,\\eqno(1)$$\nhaving a root $\\lambda \\in \\mathbb{C}$ of multiplicity $\\mu, \\ 1\\le\n\\mu\\le n$, shares it with each of its derivatives up to order $\\mu-1$,\nbut $f^{(\\mu)}(\\lambda)\\neq 0$. When $\\lambda$ is a unique root of\n$f$, it has the form $f(z)=a(z-\\lambda)^n$, $\\mu=n$ and $\\lambda$ is\nthe same root of each derivative of $f$ up to order $n-1$. We will\ncall such a polynomial as a trivial polynomial. Obviously, as it\nfollows from fundamental theorem of algebra, $f$ has at least two\ndistinct roots, i.e. a polynomial of degree $n$ is non-trivial, if\nand only if its maximum multiplicity of roots $r$ does not exceed\n$n-1$.\n\n\nIn 2001 Casas- Alvero \\cite{CA} conjectured that an arbitrary polynomial $f$ degree $n\n\\ge 1$ with complex coefficients is of the form $f(z)=\na(z-b)^n, a, b \\in \\mathbb{C}$, if and \\ only if $f$ shares a root with each of its derivatives $f^{(1)}, f^{(2)},\n\\dots, f^{(n-1)}.$\n\nWe will call a possible non-trivial polynomial, which has a common root with each of its non-constant derivatives as the CA-polynomial. The conjecture says that there exist no CA-polynomials. The problem is still open. However, it is proved for small degrees, for infinitely many degrees, for instance, for all powers $n$, when $n$ is a prime (see in \\cite{Drai}, \\cite{Graf}, \\cite{Pols} ). We observe that such a kind of CA-polynomial of degree $n \\ge 2$ cannot have all distinct roots since at least one root is common with its first derivative. Therefore it has a multiplicity at least 2 and a maximum of possible distinct roots is $n-1$.\n\n\n\n Our main goal here is to derive necessary and sufficient conditions for an arbitrary polynomial (1) to be trivial. For example, solving a simple differential equation of the first order, we easily prove that a polynomial is trivial, if and only if it is divisible by its first derivative. In the sequel we establish other criteria, which will guarantee that an arbitrary polynomial has a unique joint root.\n\n Without loss of generality one can assume in the sequel that $f$ is a monic polynomial of degree $n$, i.e. $a_0=1$ in (1). Generally, it has $k$ distinct roots $\\lambda_j$ of multiplicities $r_j, \\ j= 1, \\dots, k, 1\\le k\\le n$ such that\n %\n$$ r_1+ r_2+ \\dots r_{k} = n\\eqno(2).$$\n %\n By $r$ we will denote the maximum of multiplicities (2), $r= \\hbox{max}_{1\\le j\\le k} (r_j)$, $r_0= \\hbox{min}_{1\\le j\\le k} (r_j)$ and by $ \\xi^{(m)}_\\nu, \\ \\nu = 1,\\dots, n-m$ zeros of $m$-th derivative $f^{(m)}, \\ m=1,\\dots, n-1.$\n For further needs we specify zeros of the $n-1$-th and $n-2$-th derivatives, denoting them by $\\xi^{(n-1)}_1=z_{n-1}$ and $\\xi^{(n-2)}_2=z_{n-2}$, respectively. It is easy to find another zero of the $n-2$-th derivative, which is equal to $\\xi^{(n-2)}_1= 2z_{n-1} -z_{n-2} $. When zeros $ z_{n-1},\\ z_{n-2}$ are real we write, correspondingly, $ x_{n-1},\\ x_{n-2}$. The value $z_{n-1}$ is called the centroid. It is a center of gravity of roots and by Gauss-Lucas theorem it is contained in the convex hull of all non-constant polynomial derivatives (see details in \\cite{Rah}).\n\n The paper is structured as follows: In Section 2 we study properties of the Abel-Goncharov interpolation polynomials, including integral and series representations and upper bounds. Section 3 deals with the Sz.-Nagy type identities and Obreshkov-Chebotarev type inequalities for roots of polynomials and their derivatives. As applications new criteria are found for an arbitrary polynomial with only real roots to be trivial. Section 4 is devoted to the Laguerre type inequalities for polynomials with only real roots to localize their zeros. The final Section 5 contains applications of these results towards solution of the Casas-Alvero conjecture and its particular cases.\n\n\n \\section{Abel-Goncharov polynomials, their upper bounds and integral and genetic sum's representations}\n\nWe begin, choosing a sequence of complex numbers (repeated terms are permitted)\n$z_0, z_1, z_2, \\dots, z_{n-1}, n \\in \\mathbb{N}$, where $z_0 \\in \\{\\lambda_1, \\lambda_2, \\dots, \\lambda_k\\},\\\nz_m \\in \\{\\xi^{(m)}_1,\\ \\xi^{(m)}_2, \\dots, \\xi^{(m)}_{n-m}\\}, \\ m=1,2,\\dots, n-1$, satisfying conditions $f^{(m)}(z_m) =0, \\\nm =0, 1,\\dots, \\ n-1$ and, clearly $f^{(n)} (z)= n!$. Then we represent $f(z)$ in the form\n\n$$\n f(z)= z^n + P_{n-1} (z),\\eqno(3)\n$$\nwhere $P_{n-1} (z)$ is a polynomial of degree at most $n-1$. To determine $P_{n-1} (z)$ we differentiate the latter equality $m$ times, and we calculate the corresponding derivatives in $z_m$ to obtain\n$$\n P_{n-1}^{(m)} (z_m) = - \\frac{n!}{ (n-m)!} z_m ^{n- m} , \\quad m= 0,1, \\dots, n-1.\\eqno(4)\n$$\nBut this is the known Abel-Goncharov interpolation problem (see \\cite{Evgrafov}) and the polynomial $P_{n-1}(z)$ can be uniquely determined via the linear system (4) of $n$ equations with $n$ unknowns and triangular\nmatrix with non-zero determinant. So, following \\cite{Evgrafov}, we derive\n\n$$\n P_{n-1} (z) = - \\sum_{k=0}^{n-1} \\frac{n!}{ (n- k)!} z_k ^{n- k} G_k(z) , \\eqno(5)\n$$\nwhere $G_k(z), k=0, 1,\\dots, n-1$ is the system of the Abel-Goncharov polynomials\n \\cite{Evgrafov}, \\cite{Levinson1}, \\cite{Levinson2}. On the other hand it is known that\n\n$$\n G_n(z)= z^n - \\sum_{k=0}^{n-1} \\frac{n!}{ (n- k)!} z_k ^{n- k} G_k(z).\\eqno(6)\n$$\nThus comparing with (3), we find that\n$$\nG_n(z)\\equiv G_n\\left(z, z_0, z_1, z_2,\\dots, z_{n-1}\\right)=f(z),\n$$\nand\n$$\n G_n\\left(\\lambda_j, z_0, z_1, z_2,\\dots, z_{n-1}\\right) = f(\\lambda_j)= 0, \\quad\nj= 1,2, \\dots, k.\n$$\nPlainly, one can make a relationship of possible CA-polynomials with the corresponding Abel-Goncharov polynomials, fixing a sequence $\\{z_m\\}_0^{n-1}$ such that\n$$z_m \\in \\{\\lambda_1, \\lambda_2, \\dots, \\lambda_k\\}, \\ m=0,1,\\dots,\\ n-1.$$\n\nFurther, It is known \\cite{Evgrafov} that the Abel-Goncharov polynomial can\nbe represented as a multiple integral in the complex plane\n$$\nG_n(z)= n! \\int_{z_0}^z \\int_{z_1}^{s_{1}} \\dots\n\\int_{z_{n-1}}^{s_{n-1}} d s_{n} \\dots d s_{1}.\\eqno (6)\n$$\nMoreover, making simple changes of variables in (6), it can be verified that $G_n(z)$ is\n a homogeneous function of degree $n$ (cf. \\cite{Levinson1}). Therefore\n$$G_n(\\alpha z)= G_n\\left(\\alpha z, \\alpha z_0, \\alpha z_1,\\dots, \\alpha z_{n-1}\\right)\n = \\alpha^n G_n(z), \\ \\alpha \\neq 0.\\eqno(7)$$\nThe following Goncharov upper bound holds for $G_n$ (see \\cite{Gon}, \\cite{Evgrafov}, \\cite{Levinson1}, \\cite{Ibra})\n$$\n\\left| G_n(z) \\right| \\le \\left( |z-z_0| + \\sum_{s=0}^{n-2} \\left\n|z_{s+1}- z_s\\right| \\right)^n.\\eqno(8)\n$$\n Let us represent the Abel-Goncharov polynomials $G_n(z)$ in a different way. To do this, we will use the following representation of the Gauss hypergeometric function given by relation (2.2.6.1) in \\cite{Prud}, namely\n$$\\int_a^b (z-a)^{\\alpha-1} (b-z)^{\\beta-1}(z + c)^\\gamma dz = (b-a)^{\\alpha+\\beta-1} (a+c)^\\gamma\nB(\\alpha,\\beta) {}_2F_1 \\left(\\alpha, -\\gamma; \\alpha +\\beta;\n\\frac{a-b}{ a+c} \\right),\\eqno(9)$$ where $\\alpha, \\beta, \\gamma $\nare positive integers, $a, b, c \\in \\mathbb{C}$ and\n$B(\\alpha,\\beta)$ is the Euler beta-function. So, our goal will be a\nrepresentation of the Abel-Goncharov polynomials in terms of the\nso-called genetic sums considered, for instance, in \\cite{Apteka}.\nMoreover, this will drive us to a sharper upper bound for these polynomials, improving the Goncharov bound (8).\n Indeed, $G_1(z)= z-z_0$. When $n \\ge 2$, we employ multiple integral (6), and appealing to\n representation (9), we obtain recursively\n$$\nG_n(z)= n! \\int_{z_0}^z \\int_{z_1}^{s_{1}} \\dots \\int_{z_{n-2}}^{s_{n-2}} \\ (s_{n-1} - z_{n-1})\n d s_{n-1} \\dots d s_{1}\n$$\n$$= n! (z_{n-2} - z_{n-1}) \\int_{z_0}^z \\int_{z_1}^{s_{1}} \\dots \\int_{z_{n-3}}^{s_{n-3}} \\ (s_{n-2} - z_{n-2})\n {}_2F_1 \\left(1, -1 ; \\ 2; \\ \\frac{ z_{n-2} - s_{n-2}}{ z_{n-2} - z_{n-1} } \\right) d s_{n-2} \\dots d s_{1} $$\n$$= n! \\sum_{j_1=0} ^ 1\\frac{(-1)_{j_1}(-1)^{j_1} }{(2)_{j_1}} (z_{n-2} - z_{n-1})^{1-j_1} \\int_{z_0}^z\n\\int_{z_1}^{s_{1}} \\dots \\int_{z_{n-3}}^{s_{n-3}} \\ (s_{n-2} - z_{n-2})^{1+j_1} d s_{n-2} \\dots d s_{1} .$$\nHence, employing properties of the Pochhammer symbol and repeating this process, we find\n$$\nG_n(z)= n! \\sum_{j_1=0} ^ 1\\frac{(z_{n-2} - z_{n-1})^{1-j_1} }{(2)_{j_1} (1-j_1)!} \\int_{z_0}^z \\int_{z_1}^{s_{1}}\n\\dots \\int_{z_{n-3}}^{s_{n-3}} \\ (s_{n-2} - z_{n-2})^{1+j_1} d s_{n-2} \\dots d s_{1} $$\n$$= n! \\sum_{j_1=0} ^ 1 \\sum_{j_2=0} ^{1+j_1} \\frac{(z_{n-2} - z_{n-1})^{1-j_1} (z_{n-3} - z_{n-2})^{1+j_1-j_2} }\n{(2)_{j_2} (1-j_1)!(1+j_1 -j_2)!} \\int_{z_0}^z \\int_{z_1}^{s_{1}} \\dots \\int_{z_{n-4}}^{s_{n-4}} \\\n(s_{n-3} - z_{n-3})^{1+j_2} d s_{n-3} \\dots d s_{1} .$$\nContinuing to calculate iterated integrals with the use of (9), we\narrive finally at the following genetic sum's representation of\nthe Abel-Goncharov polynomials ($j_0 = j_n=0,\\ z_{-1}\\equiv z $)\n$$\nG_n(z)= n! \\sum_{j_1=0} ^ 1 \\sum_{j_2=0} ^{1+j_1} \\dots \\sum_{j_{n-1}=0} ^{1+j_{n-2}} \\\n \\prod_{s=0}^{n-1} \\frac{ (z_{n-2-s}- z_{n-1-s} )^ {1+ j_s- j_{s+1}} }{ (1+ j_s- j_{s+1})!}.\\eqno(10) $$\nAnalogously, we derive the genetic sum's representation for the $m$-th derivative\n$G_{n}^{(m)}(z)$, namely ($j_0 =0 $)\n $$\nG_n^{(m)} (z)= n! \\sum_{j_1=0} ^ 1 \\sum_{j_2=0} ^{1+j_1} \\dots \\sum_{j_{n-1-m }=0} ^{1 +j_{n-2-m}}\n \\frac{ (z - z_{m} )^ {1 + j_{n-1-m}} }{ (1 + j_{n-1-m})!} \\\n \\prod_{s=0}^{n-2-m} \\frac{ (z_{n-2-s}- z_{n-1-s} )^ {1 + j_s- j_{s+1}} }{ (1+ j_s- j_{s+1} )!},\\eqno(11) $$\nwhere $m= 0,1,\\dots, n-1$.\n\nMeanwhile, the Taylor expansions of $ G_n^{(m)} (z)$ in the neighborhood of points $z_m$ give the formulas\n$$G_n^{(m)} (z) = \\frac{n!}{(n- m)!} (z-z_m)^{n-m} + \\frac {G_n^{(n-1)} (z_m)}{(n-m-1)!} (z-z_m)^{n-m- 1} + \\dots\n+ G_n^{(1+m)} (z_m) (z-z_m),\\eqno(12)$$\nwhere $m= 0,1,\\dots, n-1$. Thus comparing coefficients in front of $(z-z_m)^s, \\ s= 1, \\dots , n- m-1$ in (11) and (12), we find the values of derivatives $G_n^{(s+ m)} (z_m)$ in terms $z_m, z_{m+1}, \\dots, z_{n-1}$. Precisely, we obtain ($j_0 =0 $)\n$$G_n^{(s+m)} (z_m) = n! \\sum_{j_1=0} ^ 1 \\sum_{j_2=0} ^{1+j_1} \\dots\n\\sum_{j_{n-2-m }=0} ^{1 +j_{n-3-m}} \\frac{ (z_m - z_{m+1} )^ {2 + j_{n-2-m}-s} }{ (2 + j_{n- 2-m}-s)!} \\\n \\prod_{l=0}^{n-3-m} \\frac{ (z_{n-2-l}- z_{n-1-l} )^ {1 + j_l- j_{l+1}} }{ (1+ j_l- j_{l+1} )!},\\eqno(13)$$\nwhere $s=1,2,\\dots, n-m, \\ m=0,1,\\dots, n-1$.\n\nFinally, in this section, we will establish a sharper upper bound for the\nAbel-Goncharov polynomials. We have\n\n{\\bf Theorem 1}. {\\it Let $z, z_0, z_1, z_2,\\dots, z_{n-1} \\in\n\\mathbb{C},\\ n \\ge 1$. The following upper bound holds for the\nAbel-Goncharov polynomials\n$$| G_n\\left(z, z_0, z_1, z_2,\\dots, z_{n-1}\\right)| \\le\n\\sum_{k_0=0}^1 \\sum_{k_1=0} ^{2-k_0} \\dots \\sum_{k_{n-2}=0} ^{n-1\n- k_0-k_1-\\dots- k_{n-3}} \\ {n! \\choose k_0! k_1! \\dots k_{n-2}! \\\n(n - k_0-k_1-\\dots- k_{n-2})! }$$\n$$\\times \\prod_{s=0}^{n-1} |z_{n-2-s}- z_{n-1-s}|^ {k_s},\\eqno(14) $$\nwhere $ z_{-1}\\equiv z$ and\n$${n! \\choose l_0! l_1! \\dots l_m!} = \\frac{n!}{l_0! l_1! \\dots\nl_m!}, \\ l_0+l_1+\\dots +l_m= n$$ are multinomial coefficients. This\nbound is sharper than the Goncharov upper bound $(8)$.}\n\n\\begin{proof} In fact, making simple substitutions $k_s= 1+j_s- j_{s+1}, \\ s=0,1,\\dots, n-1, j_0=j_n=0$\nand writing identity (10) for the Abel-Goncharov polynomials (6), we\nestimate their absolute value, coming out immediately with inequality\n(14). Furthermore, appealing to the multinomial theorem, we estimate\nthe right-hand side of (14) in the following way\n$$\\sum_{k_0=0}^1 \\sum_{k_1=0} ^{2-k_0} \\dots \\sum_{k_{n-2}=0} ^{n-\n1- k_0-k_1-\\dots- k_{n-3}} \\ {n! \\choose k_0! k_1! \\dots k_{n-2}\\\n(n - k_0-k_1-\\dots- k_{n-2})! } \\prod_{s=0}^{n-1} |z_{n-2-s}-\nz_{n-1-s}|^ {k_s}$$$$\\le \\sum_{l_0+l_1+\\dots+ l_{n-1} = n} \\ {n!\n\\choose l_0! l_1!\\dots l_{n-1}!} \\prod_{s=0}^{n-1} |z_{n-2-s}-\nz_{n-1-s}|^{l_s}$$\n$$= \\left(\\sum_{m=0}^{n-1} \\left |z_{m-1}- z_{m}\\right|\\right)^n,$$\nwhere the summation now is taken over all combinations of\nnonnegative integer indices $l_0$ through $l_{n-1}$ such that the\nsum of all $l_j$ is $n$. Thus it yields (8) and completes the\nproof.\n\n\\end{proof}\n\n\n\n\\section{Sz.-Nagy type identities for roots of polynomials and their derivatives}\n\nIn this section we prove Sz.-Nagy type identities \\cite{Rah} for zeros of monic polynomials with complex coefficients and their derivatives. All notations of roots and their multiplicities given in Section 1 are involved.\n\n We begin with\n\n{\\bf Lemma 1.} {\\it Let $f$ be a monic polynomial of degree $n \\ge 2$ with complex coefficients, $m= 0,1,\\dots, n-2$ and $z \\in \\mathbb{C}$. Then the following Sz.-Nagy type identities, which are related to the roots of $f$ and its $m$-th derivative, hold }\n\n$$z_{n-1} - z = {1\\over n} \\sum_{j=1}^k r_{j}(\\lambda_j- z) = {1\\over n-m} \\sum_{j=1}^{n-m} (\\xi^{(m)}_j - z),\\eqno(15)$$\n\n$$ (z_{n-1} - z_{n-2})^2={1\\over n(n-1)} \\left[ \\sum_{j=1}^k r_{j}(\\lambda_j- z)^2- n (z_{n-1} - z)^2\\right]\n= {1\\over (n-m)(n-m -1)}$$$$\\times \\left[ \\sum_{j=1}^{n-m}\n(\\xi^{(m)}_j - z)^2 - (n-m) (z_{n-1} - z)^2\\right],\\eqno(16)$$\n\n$$ (z_{n-1} - z_{n-2})^2={1\\over n^2(n-1)} \\sum_{1\\le j < s\\le k} r_{j}r_{s}(\\lambda_j- \\lambda_s)^2\n= {1\\over (n-m)^2(n-m -1)} \\sum_{1\\le j < s \\le n-m} (\\xi^{(m)}_j -\n\\xi^{(m)}_s)^2.\\eqno(17)$$\n\n\n\n\\begin{proof} In fact, the first Vi\\'{e}te formula (see \\cite{Rah}) says that the coefficient $a_1$ ($a_0=1$) in (1) is equal to\n$$- a_1= r_{1}\\lambda_1 + r_{2} \\lambda_{2} + \\dots + r_{k}\\lambda_{k}.$$\nOn the other hand, differentiating (1) $n-1$ times, we find $z_{n-1}\n= - a_1\/ n$. Thus minding (2) we prove the first equality in (15). The second\nequality can be done similarly, using the properties of centroid,\nwhich is differentiation invariant, see, for instance, in\n\\cite{Rah}. In order to establish the first equality in (16), we\ncall formula (11) to find\n$$\\frac{f^{(n-2)} (z)}{(n-2)!} = \\frac{n(n-1)}{2} (z - z_{n-2}) (z + z_{n-2}- 2 z_{n-1}).\\eqno(18)$$\nMoreover, as a consequence of the second Vi\\'{e}te formula, the\ncoefficient $a_2$ in (1), which equals\n$$a_2= \\frac{f^{(n-2)} ( z)}{(n-2)!} - \\frac{n(n-1)}{2} z^2 + n(n-1) z_{n-1}z\\eqno(19)$$\ncan be expressed as follows\n$$a_2= {1\\over 2} \\left(\\sum_{j=1}^k r_{j} \\lambda_j\\right)^2 - {1\\over 2} \\sum_{j=1} ^k r_j\\lambda_j^2.\\eqno(20) $$\nHence letting $z=z_{n-2}$ in (18), and taking into account (15) with $z=0$,\nwe deduce\n\n$$2a_2= n^2z^2_{n-1} - \\sum_{j=1} ^k r_{j} \\lambda_j^2 = 2 n(n-1) z_{n-1}z_{n-2} - n(n-1) z_{n-2}^2 . $$\nTherefore, using again (15) and (2), we easily come out with the\nfirst equality in (16). The second one can be prove in the same\nmanner, involving roots of derivatives. Finally, we prove the first\nequality in (17). Concerning the second equality, see Lemma 6.1.5\nin \\cite{Rah}. Indeed, calling the first equality in (16), letting\n$z= z_{n-1}$ and employing (15), we derive\n\n$$ n^2(n-1)(z_{n-1} - z_{n-2})^2= n \\sum_{j=1}^k r_{j}\\lambda^2_j +\n\\left(\\sum_{s=1}^k r_{s}\\lambda_s\\right)^2 - 2\\left(\\sum_{s=1}^k\nr_{s}\\lambda_s\\right)\\left(\\sum_{j=1}^k r_{j}\\lambda_j\\right)$$\n$$= n \\sum_{j=1}^k r_{j}\\lambda^2_j - \\sum_{s=1}^k r^2_{j}\\lambda^2_j -\n2\\sum_{1\\le j < s\\le k} r_{j}r_{s}\\lambda_j\\lambda_s= \\sum_{1\\le j\n< s\\le k} r_{j}r_{s}(\\lambda_j- \\lambda_s)^2.$$\n\n\\end{proof}\n\nThe following result gives an identity, which is associated with zeros of a monic\npolynomial and common zeros of its derivatives. Precisely, we have\n\n\n{\\bf Lemma 2.} {\\it Let $f$ be a monic polynomial of exact degree $n\\ge 2$, having $k$ distinct roots of multiplicities $(2)$. Let $z_{n-1}=\\lambda_1$ be a common root of $f$ of multiplicity $r_1$ with the unique root of its $n-1$-th\nderivative. Let also $z_m= \\xi_{n-m}^{(m)}= \\lambda_{k_m}$ be a common root of $f$ of multiplicity $r_{k_m}$ and\nits $m$-th derivative, $m \\in \\{1,2,\\dots, n-2\\}$. Then, involving other roots of $f^{(m)}$,\nthe following identity holds}\n\n$$\\left[\\frac{n-m-2}{(n-m)^2} + \\frac{r_{k_m}+r_1-n}{n (n-1)}\\right]\\sum_{s=1}^{n-m-1} (z_m- \\xi^{(m)}_s)^2\n+ \\frac{n-m-2}{(n-m)^2}\\sum_{1\\le s < t \\le n-m-1} (\\xi^{(m)}_s- \\xi^{(m)}_t)^2\n$$$$= \\frac{(n-m)^2 r_{k_m}- (n-r_1)(n-m+2)}{n (n-1)} (z_m- z_{n-1})^2$$$$+ \\\n\\frac{2}{n (n-1)}\\sum_{j\\neq 1, k_m} r_j \\sum_{1 \\le s < t \\le\nn-m-1} (\\lambda_j- \\xi^{(m)}_s)(\\lambda_j- \\xi^{(m)}_t).\\eqno(21)$$\n\n\\begin{proof} We begin, appealing to (15) and letting $z=0$. We get\n$$\\sum_{s=1}^{n-m} \\xi^{(m)}_s= (n-m) z_{n-1}, \\quad \\xi_{n-m}^{(m)}=z_m.\\eqno(22) $$\nHence via identities (17) with $z=z_m$ we write the chain of equalities\n$$\\sum_{1\\le s < t \\le n-m} (\\xi^{(m)}_s- \\xi^{(m)}_t)^2=\n\\frac{(n-m-1)(n-m)^2}{n (n-1)} r_{k_m}(z_m- z_{n-1})^2 +\n\\frac{(n-m-1)(n-m)^2}{n (n-1)}\\sum_{j\\neq 1, k_m} r_j (\\lambda_j -\nz_{n-1})^2$$\n$$=\\frac{(n-m-1)(n-m)^2}{n (n-1)} r_{k_m}(z_m- z_{n-1})^2 +\n\\frac{n-m-1}{n (n-1)}\\sum_{j\\neq 1, k_m} r_j \\left(\\lambda_j - z_m+\n\\sum_{s=1}^{n-m-1} (\\lambda_j- \\xi^{(m)}_s) \\right)^2$$\n$$=\\frac{(n-m-1)(n-m)^2}{n (n-1)} r_{k_m}(z_m- z_{n-1})^2 +\n\\frac{n-m-1}{n (n-1)}\\left[\\sum_{j\\neq 1, k_m} r_j (\\lambda_j -\nz_m)^2 + \\sum_{j\\neq 1, k_m} r_j \\left(\\sum_{s=1}^{n-m-1}\n(\\lambda_j- \\xi^{(m)}_s) \\right)^2\\right.$$\n$$\\left.+ 2 \\sum_{j\\neq 1, k_m} r_j \\sum_{s=1}^{n-m-1} (\\lambda_j -\nz_m)(\\lambda_j- \\xi^{(m)}_s)\\right]= \\frac{(n-m-1)(n-m)^2}{n (n-1)}\nr_{k_m}(z_m- z_{n-1})^2$$\n$$+ \\frac{n-m-1}{n (n-1)}\\left[(2(n-m)-1) \\sum_{j\\neq 1, k_m} r_j (\\lambda_j -\nz_m)^2 + \\sum_{j\\neq 1, k_m} r_j \\left(\\sum_{s=1}^{n-m-1}\n(\\lambda_j- \\xi^{(m)}_s) \\right)^2\\right.$$\n$$\\left.+ 2 \\sum_{j\\neq 1, k_m} r_j \\sum_{s=1}^{n-m-1} (\\lambda_j -\nz_m)(z_m - \\xi^{(m)}_s)\\right]= \\frac{(n-m-1)(n-m)^2}{n (n-1)}\nr_{k_m}(z_m- z_{n-1})^2$$\n$$+ \\frac{n-m-1}{n (n-1)}\\left[(2(n-m)-1) \\sum_{j\\neq 1, k_m} r_j (\\lambda_j -\nz_m)^2 + \\sum_{j\\neq 1, k_m} r_j \\left(\\sum_{s=1}^{n-m-1}\n(\\lambda_j- \\xi^{(m)}_s) \\right)^2\\right.$$\n$$\\left. - 2 (n-m)(n-r_1)(z_m-z_{n-1})^2 \\right]= \\frac{(n-m-1)}{n (n-1)}\n\\left((n-m)^2 r_{k_m}- n+r_1\\right) (z_m- z_{n-1})^2$$\n$$+ (n-m-1)(3(n-m)-2)(z_{n-1}- z_{n-2})^2 + \\frac{(n-m-1)(n-r_1)}{n (n-1)}\\sum_{s=1}^{n-m-1}\n(z_{n-1}- \\xi^{(m)}_s)^2$$$$- \\frac{r_{k_m}(n-m-1)}{n\n(n-1)}\\sum_{s=1}^{n-m-1} (z_{m}- \\xi^{(m)}_s)^2+ 2 \\ \\frac{n-m-1}{n\n(n-1)}\\sum_{j\\neq 1, k_m} r_j \\sum_{1 \\le s < t \\le n-m-1}\n(\\lambda_j- \\xi^{(m)}_s)(\\lambda_j- \\xi^{(m)}_t).$$ Applying again\n (17), (22), we split the right-hand side of the latter\nequality in (17) in two parts, selecting the root $z_m$. Thus in the\nsame manner after straightforward calculations it becomes\n$$\\left[\\frac{n-m-2}{(n-m)^2} + \\frac{r_{k_m}+r_1-n}{n (n-1)}\\right]\\sum_{s=1}^{n-m-1} (z_m- \\xi^{(m)}_s)^2\n+ \\frac{n-m-2}{(n-m)^2}\\sum_{1\\le s < t \\le n-m-1} (\\xi^{(m)}_s-\n\\xi^{(m)}_t)^2\n$$$$= \\frac{(n-m)^2 r_{k_m}- (n-r_1)(n-m+2)}{n (n-1)} (z_m- z_{n-1})^2+ \\\n\\frac{2}{n (n-1)}\\sum_{j\\neq 1, k_m} r_j \\sum_{1 \\le s < t \\le\nn-m-1} (\\lambda_j- \\xi^{(m)}_s)(\\lambda_j- \\xi^{(m)}_t),$$\ncompleting the proof of Lemma 2.\n\n\\end{proof}\n\n{\\bf Remark 1}. It is easy to verify identity (21) for the least case $m=n-2$, when double sums are\nempty and $\\xi^{(n-2)}_1= 2z_{n-1} -z_{n-2} $ (see above).\n\n{\\bf Corollary 1.} {\\it A polynomial with only real roots of degree $n\\ge 2$ is trivial, if and only if its $n-2$-th derivative has a double root}.\n\n\\begin{proof} Indeed, necessity is obvious. To prove sufficiency we see that since the $n-2$-th derivative has a double real root $x_{n-2}$, it is equal to the root $x_{n-1}$ of the $n-1$-th derivative. Therefore letting in (16)\n$z= x_{n-1}$, we find that its left-hand side becomes zero and,\ncorrespondingly, all squares in the right-hand side are zeros. This\ngives a conclusion that all roots are equal to $x_{n-1}$.\n\n\\end{proof}\n\n{\\bf Corollary 2.} {\\it Let $f$ be an arbitrary polynomial of\ndegree $n \\ge 3$ with at least two distinct roots, whose $n-2$-th\nderivative has a double root. Then it contains at least one complex\nroot}.\n\n\\begin{proof} In fact, if all roots are real it is trivial via Corollary 1.\n\n\\end{proof}\n\n Evidently, each derivative up to $f^{(r-1)}$ of a polynomial $f$ with only real roots, where $r$ is the maximum of multiplicities of roots shares a root with $f$. Moreover, since via the Rolle theorem all roots of $f^{(m)}, \\ m=r,r+1,\\dots, n-1$ are simple, we have that a possible common root with $f$ is simple too (we note, that a number of common roots does not exceed $k-2$, because minimal and maximal roots cannot be zeros of $f^{(m)},\\ m\\ge r$). This circumstance gives an immediate\n\n {\\bf Corollary 3.} {\\it There exists no non-trivial polynomial with only real roots, having two distinct zeros and sharing a root with at least one of its derivatives, whose order exceeds $r-1,\\ r= \\hbox{max}_{1\\le j\\le k} (r_j)$. }\n\n\\begin{proof} Indeed, in the case of existence of such a polynomial, these two distinct roots cannot be within zeros of any derivative $f^{(m)},\\ m > r$ owing to the Rolle theorem. Moreover, if any of two roots is in common with roots of $f^{(r)}$, its multiplicity is greater than $r$, which is impossible.\n\n\\end{proof}\n\nWe extend Corollary 3 on three distinct real roots. Precisely, it drives to\n\n {\\bf Corollary 4.} {\\it There exists no non-trivial polynomial $f$ of degree $n \\ge 3$ with only real roots, having three distinct zeros and sharing a root with its $n-2$-th and $n-1$-th derivatives. }\n\n\\begin{proof} Let such a polynomial exist. Calling its roots $\\lambda_1= x_{n-1}, \\ \\lambda_2= x_{n-2}$ and $\\lambda_3$ of multiplicities $r_1, \\ r_2, \\ r_3$, respectively. Hence employing identities (16), we write for this case\n$$ (n^2- n- r_2) (x_{n-1} - x_{n-2})^2= r_{3}(\\lambda_3 - x_{n-1}) ^2.$$\nIn the meantime, making square of both sides of the first equality in (15) for this case after simple modifications , we obtain\n$$ r_2^2(x_{n-1} - x_{n-2})^2= r_{3}^2 (\\lambda_3 - x_{n-1}) ^2.$$\nHence, comparing with the previous equality, we come out with the relation\n$$ (n^2- n- r_2) r_3= r_2^2.$$\nBut $n=r_1+r_2+r_3,\\ r_j \\ge 1, j=1,2,3.$ Consequently,\n$$r_2^2 \\ge n(n-1)- r_2 > (n-1)^2- r_2 \\ge (r_1+r_2)^2-r_2 \\ge r_2^2+ r_2+ r_1^2 > r_2^2,$$\nwhich is impossible.\n\\end{proof}\n\n{\\bf Remark 2.} If we omit the condition for $f$ to have a common root with the $n-2$-th derivative in Corollary 4, it becomes false. In fact, this circumstance can be shown by the counterexample $f(x)= x^3-x.$\n\nThe following result deals with the case of 4 distinct roots. We have,\n\n{\\bf Corollary 5.} {\\it There exists no non-trivial polynomial $f$ of degree $n \\ge 4$ with only real roots, having four distinct zeros and sharing a root with its $n-2$-th and $n-1$-th derivatives. }\n\n\\begin{proof} Similarly to the previous corollary, we assume the existence of such a polynomial and call its roots\n$\\lambda_1= x_{n-1}, \\ \\lambda_2= x_{n-2}$ and $\\lambda_3, \\lambda_4$ of multiplicities $r_j, \\ j=1,2,3,4$, respectively.\nHence the first identity in (16) yields\n$$ (n^2- n- r_2) (x_{n-1} - x_{n-2})^2= r_{3}(\\lambda_3 - x_{n-1}) ^2+ r_{4}(\\lambda_4 - x_{n-1}) ^2 .\\eqno(23)$$\nMeanwhile, using the first equality in (15) for this case, we derive in a similar manner\n$$ r_2^2(x_{n-1} - x_{n-2})^2= r_{3}^2 (\\lambda_3 - x_{n-1}) ^2+ r_{4}^2 (\\lambda_4 - x_{n-1}) ^2+\n2 r_{3}r_4 (\\lambda_3 - x_{n-1}) (\\lambda_4 - x_{n-1}).$$\nThus, after straightforward calculations, we come out with the quadratic equation\n$$Ay^2+ By+ C=0$$\nin variable $y= (\\lambda_3 - x_{n-1}) \/ (\\lambda_4 - x_{n-1})$ with coefficients $A= r_3r_2^2- r_3^2(n^2-n-r_2),\\\nB= - 2 r_3r_4 (n^2-n-r_2),\\ C= r_4r_2^2- r_4^2(n^2-n-r_2).$ But, it is easy to verify that $B^2-4AC >0.$ Therefore the quadratic\nequation has two distinct real roots. Writing $\\lambda_3 - x_{n-1}= y (\\lambda_4 - x_{n-1})$ and substituting into (23), we obtain\n$$ (n^2- n- r_2) (x_{n-1} - x_{n-2})^2= ( r_{3}y^2+ r_4) (\\lambda_4 - x_{n-1})^2.$$\nAt the same time, since $y\\neq 0$, we have $ \\lambda_4 - x_{n-1}=\ny^{-1} (\\lambda_3 - x_{n-1})$ and\n$$y^2 (n^2- n- r_2) (x_{n-1} - x_{n-2})^2= ( r_{3}y^2+ r_4) (\\lambda_3 - x_{n-1})^2.$$\nHence,\n$$\\lambda_4= x_{n-1} \\pm \\sqrt{\\frac{n^2- n- r_2}{ r_{3}y^2+ r_4}} \\ |x_{n-1} - x_{n-2}|,$$\n$$\\lambda_3= x_{n-1} \\pm |y| \\sqrt{\\frac{n^2- n- r_2}{ r_{3}y^2+ r_4}}\\ |x_{n-1} - x_{n-2}|.$$\nConsequently,\n$$\\lambda_4- \\lambda_3 = \\sqrt{\\frac{n^2- n- r_2}{ r_{3}y^2+ r_4}} \\ |x_{n-1} - x_{n-2}| ( 1-|y|)=\n - \\sqrt{\\frac{n^2- n- r_2}{ r_{3}y^2+ r_4}} \\ |x_{n-1} - x_{n-2}| ( 1+|y|)$$\n $$= \\sqrt{\\frac{n^2- n- r_2}{ r_{3}y^2+ r_4}} \\ |x_{n-1} - x_{n-2}| ( 1+|y|)=\n \\sqrt{\\frac{n^2- n- r_2}{ r_{3}y^2+ r_4}} \\ |x_{n-1} - x_{n-2}| (|y|-1),$$\nwhich are possible only in the case $x_{n-1}=x_{n-2},$\\ $\\lambda_3=\\lambda_4$. Thus we get a contradiction with Corollary 1 and complete the proof.\n\\end{proof}\n\nIn the same manner we prove\n\n{\\bf Corollary 6.} {\\it There exists no non-trivial polynomial $f$ of degree $n \\ge 5$ with only real roots, having five distinct zeros and sharing roots with its $n-2$-th and $n-1$-th derivatives. }\n\n\\begin{proof} Assuming its existence, it has the roots $\\lambda_1= x_{n-1}, \\ \\lambda_2= x_{n-2}$, $\\lambda_3= 2x_{n-1}- x_{n-2}, \\ \\lambda_4$ and $\\lambda_5$ of multiplicities $r_j, \\ j=1,2,3,4, 5$, respectively. Hence\n$$ (n^2- n- r_2-r_3) (x_{n-1} - x_{n-2})^2= r_{4}(\\lambda_4 - x_{n-1}) ^2+ r_{5}(\\lambda_5 - x_{n-1}) ^2 .$$\nTherefore using similar ideas as in the proof of Corollary 5, we come out again to the contradiction.\n\n\\end{proof}\n\nFor general number of distinct zeros we establish the following\n\n{\\bf Corollary 7.} {\\it There exists no non-trivial polynomial $f$ of degree $n$ with only real roots, having $k \\ge 2$ distinct zeros of multiplicities $(2)$ $r_j,\\ j=1,\\dots, k$ and among them all roots of $f^{(m)}$ for some $m$, satisfying the relations\n$$ r \\le m < {1\\over 2}\\left(1-{1\\over r_0}\\right)(n-1),\\eqno(24)$$\nwhere $r,\\ r_0$ are maximum and minimum multiplicities of roots of $f$.}\n\n\\begin{proof} In fact, as a consequence of (16) we have the identity \n$${(n-m)(n-m -1)\\over n(n-1)} \\sum_{j=1}^k r_{j}(\\lambda_j- x_{n-1})^2 = \n \\sum_{j=1}^{n-m} (\\xi^{(m)}_j - x_{n-1})^2\\eqno(25)$$\nfor some $m$, satisfying condition (24). Hence, since $m\\ge r$, it has $n-m \\le k-2$ and $\\xi^{(m)}_j= \\lambda_{m_j}, \\ m_j \\in \\{1,\\dots, k\\}, \\ j= 1,\\dots, n-m$ are simple roots of $f^{(m)}$. Thus we find \n$$ \\sum_{j=1}^{n-m} \\left[ r_{m_j} {(n-m)(n-m -1)\\over n(n-1)} -1\\right] (\\lambda_{m_j}- x_{n-1})^2 + \n{(n-m)(n-m -1)\\over n(n-1)} \\sum_{j=n-m+1}^k r_{m_j}(\\lambda_{m_j} - x_{n-1})^2 = 0.$$\nBut, owing to condition (24) \n$$r_{m_j} {(n-m)(n-m -1)\\over n(n-1)} -1 \\ge r_{0} {(n-m)(n-m -1)\\over n(n-1)} -1 \\ge 0, \\ j= 1,\\dots, n-m.$$\nIndeed, we have from the latter inequality \n$$m \\le n- {1\\over 2} - \\sqrt{\\frac{n^2-n}{r_0} + {1\\over 4}}$$\nand, in turn,\n$$ n- {1\\over 2} - \\sqrt{\\frac{n^2-n}{r_0} + {1\\over 4}}= \\frac{2 (1-r_0^{-1}) (n^2-n)}\n{ 2n- 1 + \\sqrt{4(n^2-n)r^{-1}_0 + 1}}\\ge \\frac{ (1-r_0^{-1}) (n^2-n)}\n{ 2n- 1} > {1\\over 2}\\left(1-{1\\over r_0}\\right)(n-1).$$\nTherefore $\\lambda_j= x_{n-1}, \\ j=1,\\dots, k$ and this contradicts to the fact that all roots are distinct. \n\\end{proof}\n\n\n\nFinally, in this section, we will employ identities (17) to prove an analog of the Obreshkov- Chebotarev theorem for multiple roots (see \\cite{Rah}, Theorem 6.4.3), involving estimates for smallest and largest of distances between consecutive zeros of polynomials and their derivatives. Namely, it has\n\n{\\bf Theorem 2.} {\\it Let $f$ be a polynomial of degree $n > 2$ with only real zeros. Denote the largest and the smallest of the distances between consecutive zeros of $f$ by $\\Delta$ and $\\delta$, respectively. Denoting the corresponding quantities associated with $f^{(m)}, \\ m=1,2,\\dots,\\ n-2$ by $\\Delta^{(m)}$ and $\\delta^{(m)}$, the following inequalities take place\n\n$$\\delta^{(m)} \\le \\Delta \\ {rk \\over n} \\ \\sqrt{ \\frac{k^2-1}{ (n-m+1)(n-1)}},\\eqno(26)$$\n$$\\delta \\ {r_0 k \\over n} \\ \\sqrt{ \\frac{k^2-1}{ (n-m+1)(n-1)}}\\le \\Delta^{(m)} ,\\eqno(27)$$\n$$\\delta \\ {r_0 k \\over 2 n} \\ \\sqrt{ \\frac{k^2-1}{ 3 (n-1)}}\\le |x_{n-1} - x_{n-2}| \\le\n \\Delta \\ {rk \\over 2 n} \\ \\sqrt{ \\frac{k^2-1}{ 3(n-1)}},\\eqno(28)$$\nwhere $r_0,\\ r$ are minimum and maximum multiplicities of roots of $f$, respectively, and $k \\ge 2$ is a number of distinct roots.}\n\n\\begin{proof} Following similar ideas as in the proof of Theorem 6.4.3 in \\cite{Rah}, we assume distinct roots of $f$ in the increasing order and roots of its $m$-th derivative in the non-decreasing order, and taking the second identity in (17), we deduce\n$$ {[\\delta^{(m)}]^2 \\over (n-m)^2(n-m -1)} \\sum_{1\\le j < s \\le n-m} (s-j)^2 \\le {[\\Delta r]^2 \\over n^2(n-1)} \\sum_{1\\le j < s \\le k} (s-j)^2.$$\nHence, minding the value of the sum\n$$ \\sum_{1\\le j < s \\le q} (s-t)^2 = {1\\over 12} q^2(q^2-1),$$\nafter simple manipulations we arrive at the inequality (26). In the same manner (cf. \\cite{Rah}) we establish inequalities (27), (28), basing Sz.-Nagy type identities (17). \n\\end{proof}\n\n\n\n\\section{Laguerre's type inequalities }\n\nIn 1880 Laguerre proved his famous theorem for polynomials with only\nreal roots, which provides their localization with upper and lower\nbounds (see details in \\cite{Rah}). Precisely, we have the following\nLaguerre inequalities\n$$x_{n-1}- (n-1)\\left|x_{n-1}- x_{n-2}\\right| \\le w_j \\le x_{n-1} + (n-1)\\left|x_{n-1}- x_{n-2}\\right|, \\\n j=1,\\dots, n,$$\nwhere $w_j$ are roots of the polynomial $f$ of degree $n$ and $x_{n-1}, \\ x_{n-2}$ are roots of $f^{(n-1)},\\ f^{(n-2)}$, respectively. First we prove an analog of the Laguerre inequalities for multiple roots.\n\n{\\bf Lemma 3.} {\\it Let $f$ be a polynomial with only real roots of degree $n \\in \\mathbb{N}$, having $k$ distinct roots\n $\\lambda_j, \\ j=1,\\ \\dots, k$ of multiplicities $(2)$ and $x_{n-1}, \\ x_{n-2}$ be roots of $f^{(n-1)},\\ f^{(n-2)}$, respectively.\n Then the following Laguerre type inequalities hold}\n$$x_{n-1}- \\sqrt{\\frac{(n-r_j)(n-m-1)}{r_j-m} }\\left|x_{n-1}- x_{n-2}\\right| \\le \\lambda_j \\le x_{n-1} +\n\\sqrt{\\frac{(n-r_j)(n-m-1)}{r_j-m} }\\left|x_{n-1}- x_{n-2}\\right|,\\eqno(29)$$\nwhere $ j=1,\\dots, k, \\ m= 0,1,\\dots, r_j-1.$\n\n\\begin{proof} In fact, appealing to the Sz.-Nagy type identities (15), (16) and the Cauchy -Schwarz inequality, we find\n$$ (x_{n-1} - x_{n-2})^2={1\\over (n-m)(n-m-1)} \\left[ \\sum_{s=1}^{n-m} (\\xi^{(m)}_s- \\lambda_j)^2- (n-m) (x_{n-1} -\n\\lambda_j)^2\\right]$$$$ \\ge {1\\over (n-m)(n-m-1)} \\left[\n\\frac{1}{n-r_j} \\left( \\sum_{s=1}^{n-m} (\\xi^{(m)}_s-\n\\lambda_j)\\right)^2- (n-m) (x_{n-1} - \\lambda_j)^2\\right]$$$$=\n\\frac{r_j-m} {(n-r_j)(n-m-1)} \\left(x_{n-1}- \\lambda_j\\right)^2, \\\nm= 0,1,\\dots, r_j-1,$$ which yields (29).\n\n\\end{proof}\n\nAs a corollary we improve the Laguerre inequality (28) for multiple roots.\n\n\n{\\bf Corollary 8.} {\\it Let $f$ be a polynomial with only real roots of degree $n \\in \\mathbb{N}$.\nThen the multiple zero $\\lambda_j$ of multiplicity $r_j\\ge 1, \\ j=1,\\dots, k$ lies in the interval}\n$$\\left[ x_{n-1}- \\sqrt{\\left(\\frac{n}{r_j}-1\\right)(n-1) }\\left|x_{n-1}- x_{n-2}\\right|, \\quad x_{n-1} +\n\\sqrt{\\left(\\frac{n}{r_j}-1\\right)(n-1) }\\left|x_{n-1}- x_{n-2}\\right| \\right].\\eqno(30)$$\n\n\n\\begin{proof} Indeed, the fraction $\\frac{(n-r_j)(n-m-1)}{r_j-m}$ attains its minimum value, letting $m=0$ in (29).\n\\end{proof}\n\n{\\bf Remark 3.} When all roots are simple, the latter interval\ncoincides with the one generated by (28).\n\nA localization of roots of the $m$-th derivative $f^{(m)}, \\ m=0,1,\\dots, n-2$ is given by\n\n{\\bf Lemma 4.} {\\it Roots of the $m$-th derivative $f^{(m)}, \\ m=0,1,\\dots, n-2$ satisfy the following Laguerre type inequalities}\n$$x_{n-1}- (n-m-1)\\left| x_{n-1}- x_{n-2}\\right| \\le \\xi^{(m)}_\\nu \\le\n x_{n-1} + (n-m-1)\\left| x_{n-1}- x_{n-2}\\right|,\\eqno(31)$$\nwhere $\\nu=1,\\dots, n-m.$\n\n\\begin{proof} Similarly to the proof of Lemma 3, we employ the Sz.-Nagy type identities (15), (16) and the Cauchy -Schwarz inequality to deduce\n$$ (x_{n-1} - x_{n-2})^2={1\\over (n-m)(n-m-1)} \\left[ \\sum_{s=1}^{n-m} (\\xi^{(m)}_s- \\xi^{(m)}_\\nu)^2- (n-m) (x_{n-1} -\n\\xi^{(m)}_\\nu)^2\\right]$$$$ \\ge {1\\over (n-m)(n-m-1)} \\left[\n\\frac{1}{n-m-1} \\left( \\sum_{s=1}^{n-m} (\\xi^{(m)}_s-\n\\xi^{(m)}_\\nu)\\right)^2- (n-m) (x_{n-1} -\n\\xi^{(m)}_\\nu)^2\\right]$$$$= \\frac{1}{(n-m-1)^2} \\left(x_{n-1}-\n\\xi^{(m)}_\\nu\\right)^2, \\ m= 0,1,\\dots, n-2.$$ Thus we come out\nwith (31) and complete the proof.\n\n\\end{proof}\n\nWhen $x_{n-1}=\\lambda_1$ be in common with $f$ of multiplicity $r_1$, we have\n\n{\\bf Lemma 5.} {\\it Let $f$ be a polynomial with only real roots\nof degree $n \\ge 2$ and $x_{n-1}=\\lambda_1$ be a common zero with\n$f$ of multiplicity $r_1$, having $k \\ge 2$ distinct roots $\\lambda_j$ of multiplicities\n$r_j, j=1,\\dots, k$. Then the following Laguerre type inequalities\nhold}\n$$x_{n-1}- \\sqrt{\\left({1\\over r_s}- {1\\over n-r_1}\\right) (n^2-n)}\\left| x_{n-1}- x_{n-2}\\right| \\le \\lambda_s \\le x_{n-1}\n $$$$+ \\sqrt{\\left({1\\over r_s}- {1\\over n-r_1}\\right) (n^2-n)}\\left| x_{n-1}- x_{n-2}\\right|,\\eqno(32)$$\nwhere $s=2,\\dots, k.$\n\n\\begin{proof} In the same manner we involve the first Sz.-Nagy type identity in (15) with $z= \\lambda_s$, which can be written in the form\n$$(n-r_1) (x_{n-1} - \\lambda_s) = \\sum_{j=2}^k r_{j}(\\lambda_j- \\lambda_s).$$\nHence squaring both sides of the latter equality and appealing to the Cauchy -Schwarz inequality, we derive by virtue of (16)\n$$(n-r_1)^2 (x_{n-1} - \\lambda_s)^2 = \\left( \\sum_{j=2}^k r_{j}(\\lambda_j- \\lambda_s)\\right)^2$$\n$$\\le (n-r_1-r_s)\\sum_{j=2}^k r_{j}(\\lambda_j- \\lambda_s)^2= (n-r_1-r_s)\\left[ (n^2-n) ( x_{n-1}- x_{n-2})^2 +\n(n-r_1)(x_{n-1}- \\lambda_s)^2\\right].$$\nThus after simple calculations we easily arrive at (32).\n\n\\end{proof}\n\n\n{\\bf Remark 4}. Inequalities (27) are sharper than the corresponding relations, generated by interval (30).\n\n\nThe following result gives a Laguerre type localization for common roots of a possible CA-polynomial with only real roots and its $m$-th derivative.\n\n\n{\\bf Lemma 6.} {\\it Let $f$ be a CA-polynomial of degree $n \\ge\n2$ with only real distinct zeros of multiplicities $(2)$, including common\nroots $x_{n-1}=\\lambda_1$ of its $n-1$-th derivative and $x_m$ of\nits $m$-th derivative, $m= r, r+1, \\dots, n-2$, where $r=\n\\hbox{max}_{1\\le j\\le k} (r_j)$. Then the following Laguerre type\ninequality holds\n$$ \\frac{n-r_1- r_{k_m}}{(n-r_1)^2}\n\\left(n^2-r_1+ (n-r_1)(n-m) (n-m-2)\\right) (x_{n-1}- x_{n-2})^2 \\ge (x_{n-1}- x_{m})^2,\\eqno(33)$$\nwhere $x_{n-2}$ is a root of $f^{(n-2)}$ and $r_{k_m}$ is the multiplicity of $x_m$ as a root of $f$}.\n\n\\begin{proof} Appealing again to Sz.-Nagy's type identities (15), (16) with $z=x_m$, inequality (31) and the Cauchy-Schwarz inequality, we find\n$$ (x_{n-1} - x_{n-2})^2={1\\over n(n-1)} \\left[ \\sum_{j=2}^k r_{j}(\\lambda_j- x_m)^2- (n-r_1) (x_{n-1} -\nx_m)^2\\right]$$$$ \\ge {1\\over n(n-1)} \\left[ \\sum_{j=2}^k\nr_{j}(\\lambda_j- x_m)^2- (n-r_1)(n-m-1)^2(x_{n-1}- x_{n-2})^2\\right]$$\n$$ \\ge {1\\over n(n-1)} \\left[ {1\\over n-r_1- r_{j_m}} \\left(\\sum_{j=2}^k\nr_{j}(\\lambda_j- x_m)\\right)^2 - (n-r_1)(n-m-1)^2(x_{n-1}- x_{n-2})^2\\right]$$\n$$= {n-r_1\\over n(n-1)} \\left[ {n-r_1\\over n-r_1- r_{j_m}} (x_{n-1}- x_m)^2 - (n-m-1)^2(x_{n-1}- x_{n-2})^2\\right].$$\nHence, making straightforward calculations, we derive (33), completing the proof of Lemma 6.\n\n\\end{proof}\n\n\nLet us denote by $d,\\ d^{(m)},\\ D, D^{(m)}$ the following values\n$$ d= \\hbox{min}_{2\\le j\\le k} |\\lambda_j- x_{n-1}|, \\quad\n d^{(m)}= \\hbox{min}_{1\\le j\\le n-m} |\\xi^{(m)}_j - x_{n-1}|,\\eqno(34)$$\n$$ D= \\hbox{max}_{2\\le j\\le k} |\\lambda_j- x_{n-1}|, \\quad\n D^{(m)}= \\hbox{max}_{1\\le j\\le n-m} |\\xi^{(m)}_j - x_{n-1}|,\\eqno(35)$$\nand by\n$$\\hbox{span} (f) = \\lambda^*- \\lambda_*,$$\nwhere\n$$ \\lambda^*= \\hbox{max}_{1\\le j\\le k} (\\lambda_j), \\quad \\lambda_*= \\hbox{min}_{1\\le j\\le k} (\\lambda_j)$$\nare roots of $f$ of multiplicities $r^*, \\ r_*$, respectively. It has the properties $ D^{(m+1)} \\le D^{(m)}\\le D$ and\n (cf. \\cite{Rah}) $\\hbox{span}(f^{(m+1)}) \\le \\hbox{span}(f^{(m)}) \\le \\hbox{span}(f)$, where $\\hbox{span}(f^{(m)})$\n is the span of the $m$-th derivative. Moreover, the strict inequalities $ D^{(m)} < D$,\\ $\\hbox{span}(f^{(m)}) < \\hbox{span}(f)$ hold when $m$ is sufficiently large.\n\n {\\bf Lemma 7}. {\\it Let $x_{n-1}=\\lambda_1, \\ x_{n-2}=\\lambda_2$ be common roots of $f$ with its $n-1$-th, $n-2$-th derivatives, respectively, of multiplicities $r_1, r_2$ as roots of $f$, and the maximum distance $D$ (see $(35)$) be attained at the root $\\lambda_{s_0}, \\ s_0 \\in \\{ 3,\\dots, k\\},\\ k \\ge 3$ of $f$ of multiplicity $r_{s_0}$. Then the following inequalities hold }\n %\n $$\\sqrt{\\frac{n^2-n- r_2}{n-r_1-r_2}}\\ \\left|x_{n-1} - x_{n-2}\\right| \\le D \\le \\sqrt{\\frac{n^2-n-r_2}{r_{s_0}}}\n \\left|x_{n-1} - x_{n-2}\\right|,\\eqno(36)$$\n %\n $${1\\over 2} \\sqrt{ {r_{s_0} \\over 3(n-r_1) }\\left(5 + \\frac{ r_2} {n^2-n-r_2}\\right)}\\hbox{span}(f) \\le D \\le \\sqrt{{1\\over n-r_1} \\left[ n-r_1- {r_{s_0} \\over 4}\\left(5 + \\frac{ r_2} {n^2-n-r_2}\\right)\\right] } \\hbox{span}(f).\\eqno(37)$$\n \n\\begin{proof} In order to establish (36), we employ identities (16) and under condition of the lemma we write \n$$ (n^2-n- r_2)(x_{n-1} - x_{n-2})^2 = \\sum_{j=3}^k r_{j}(\\lambda_j- x_{n-1})^2 \\le (n-r_1-r_2) D^2.$$\nSince $n > r_1+r_2$ and $x_{n-2}\\neq \\lambda_{s_0}$ (otherwise $f$ is trivial, because equalities $x_{n-2}= \\lambda_{s_0}= \\lambda^*$ or $x_{n-2}= \\lambda_{s_0}= \\lambda_*$ mean that the maximum multiplicity $r > n-2$, and we appeal to Corollary 3), we come up with the lower bound (36) for $D$. The lower bound comes immediately from the estimate \n$$(n^2-n- r_2)(x_{n-1} - x_{n-2})^2 = \\sum_{j=3}^k r_{j}(\\lambda_j- x_{n-1})^2 \\ge r_{s_0} D^2.$$\nNow, since $2D \\ge \\hbox{span}(f)$, we find from (36)\n$$\\hbox{span}(f) \\le 2 \\sqrt{\\frac{n^2-n-r_2}{r_{s_0}}} \\ \\left|x_{n-1} - x_{n-2}\\right|.$$\nHence, since $D = \\hbox{max} \\left(|\\lambda^*- x_{n-1}|, \\ |\\lambda_*- x_{n-1}|\\right)$, the\n$n-2$-th derivative has roots $x_{n-2}$ and $2x_{n-1}- x_{n-2}$ and\n$\\hbox{span}(f)= D + \\Lambda$, where $\\Lambda = \\hbox{min}\n\\left(|\\lambda^*- x_{n-1}|, \\ |\\lambda_*- x_{n-1}|\\right)$, we\nappeal to the first equality in (16), letting $z= \\lambda_{s_0}$ and writing it in the form\n$$ (n-r_1)(x_{n-1} - \\lambda_{s_0})^2 = \\sum_{j=2}^k r_{j}(\\lambda_j- \\lambda_{s_0})^2 - n(n-1)(x_{n-1} -\nx_{n-2})^2.$$\nTherefore,\n$$(n-r_1)D^2 \\le \\left[ n-r_1- {5\\over 4} r_{s_0} - \\frac{r_{s_0} r_2} {4(n^2-n-r_2)}\\right] [\\hbox{span}(f)]^2$$ \nand we establish the upper bound (37) for $D$. On the other hand $\\hbox{span}(f)= D+ \\Lambda$. So,\n$$D^2 \\le \\left(1 - {r_{s_0} \\over 4(n-r_1) }\\left(5 + \\frac{ r_2} {n^2-n-r_2}\\right)\\ \\right) \\left(D^2 + \\Lambda^2 +\n2D\\Lambda\\right)$$ and we easily come out with the lower bound (37)\nfor $D$, completing the proof of Lemma 7.\n\n\\end{proof}\n\n{\\bf Lemma 8}. {\\it Let $x_{n-1}=\\lambda_1, x_{n-2}=\\lambda_2$ be\ncommon roots of $f$ with its $n-1$-th, $n-2$-th derivatives of\nmultiplicities $r_1, r_2,\\ r_1+r_2 < n$, respectively. Then we\n have the following lower bound for $\\hbox{span}(f)$}\n %\n $$\\hbox{span}(f)\\ge \\sqrt{\\frac{n^2-r_1}{n-r_1-r_2}}\\ |x_{n-1}-x_{n-2}|.\\eqno(38)$$\n\n\\begin{proof} Indeed, identities (16) with $z=x_{n-2}$ yield\n$$(n^2-r_1)(x_{n-1}-x_{n-2})^2=\\sum_{j=3}^k r_{j}(\\lambda_j- x_{n-2})^2$$\nand we derive\n$$(n^2-r_1)(x_{n-1}-x_{n-2})^2\\le (n-r_1-r_2)[\\hbox{span}(f)]^2,$$\nwhich implies (38).\n\\end{proof}\n\nNext, we establish an analog of Lemma 5 for roots of derivatives. Precisely, it has\n\n {\\bf Lemma 9}. {\\it Let $x_{n-1}, \\ x_{n-2}$ be roots of the $n-1$-, $n-2$-th derivatives of $f$, respectively. Then\n %\n $$D^{(m)} \\ge \\sqrt{n-m-1}\\ |x_{n-1}-x_{n-2}|,\\eqno(39)$$\n where $m \\in \\{r, r+1,\\dots, n-2 \\}, \\ r= \\hbox{max}_{1\\le j\\le k} (r_j).$ Besides, if $x_{n-1}$ is a root of $f^{(m)}$, then\n we have a stronger inequality $$D^{(m)} \\ge \\sqrt{n-m}\\ |x_{n-1}-x_{n-2}|.\\eqno(40)$$\nMoreover,\n %\n $$2\\ D^{(m)} \\ge \\hbox{span}(f^{(m)}) \\ge \\frac{n-m}{n-m-1}\\ D^{(m)}.\\eqno(41)$$\n and if $x_{n-1}$ is a root of $f^{(m)}$, it becomes\n $$2\\ D^{(m)} \\ge \\hbox{span}(f^{(m)}) \\ge \\sqrt{ \\frac{(n-m)(n-m-1)+1}{(n-m-1)(n-m-2)}}\\ D^{(m)},\\eqno(42)$$\nwhere $m \\in \\{r, r+1,\\dots, n-3 \\}.$}\n\\begin{proof} In fact, since (see (16))\n$$(n-m)(n-m-1)(x_{n-1} - x_{n-2})^2= \\sum_{j=1}^{n-m} (\\xi^{(m)}_{j} - x_{n-1})^2 \\le (n-m) \\left[ D^{(m)}\\right]^2,$$\nwe get (39). Analogously, we immediately come out with (40), when $x_{n-1}$ is a root of $f^{(m)}$, because one element of the sum of squares is zero. In order to prove (41), we appeal again to (16), letting $z= \\xi^{(m)}_{s_0}, \\ s_0 \\in \\{1,2, \\dots, n-m\\}$, $m \\in \\{r, r+1,\\dots, n-2 \\}, \\ r= \\hbox{max}_{1\\le j\\le k} (r_j)$, which is a root of $f^{(m)}$, where the maximum $D^{(m)}$ is attained. Hence owing to Laguerre type inequality (31)\n$$(n-m)\\left[D^{(m)}\\right]^2\\le (n- m-1) [\\hbox{span}(f^{(m)})]^2 - \\frac{n-m}{n-m-1} \\left[D^{(m)}\\right]^2,$$\nwhich drives to the lower bound for $ \\hbox{span}(f^{(m)})$ in (41). The upper bound is straightforward\nsince $x_{n-1}$ belongs to the smallest interval containing roots of $f^{(m)}$. In the same manner we establish (42), since in this case\n$$(n-m-1)\\left[D^{(m)}\\right]^2\\le (n- m-2) [\\hbox{span}(f^{(m)})]^2 - \\frac{n-m}{n-m-1} \\left[D^{(m)}\\right]^2.$$\n\n\\end{proof}\n\n{\\bf Remark 5}. The case $m=n-2$ gives equalities in (39), (41). Letting the same value of $m$ in (40), we easily get\na contradiction, which means that the only trivial polynomial is within polynomials with only real roots,\nwhose derivatives $f^{(n-2)}, \\ f^{(n-1)}$ have a common root (see Corollary 1).\n\n\n\n\\section{Applications to the Casas- Alvero conjecture}\n\nIn this final section we will discuss properties of possible CA-polynomials, which share roots with each of their non-constant derivatives. We will investigate particular cases of the Casas-Alvero conjecture, especially for polynomials with only real roots, showing when it holds true or, possibly, is false. \n\nWe begin with \n\n\n{\\bf Proposition 1}. {\\it The Casas-Alvero conjecture holds true, if and only if it is true for common roots $\\{z_\\nu \\}_0^{n-1}$ lying in the unit circle.}\n\n\\begin{proof} The necessity is trivial. Let's l prove the sufficiency. Let the conjecture be true for common roots $\\{z_\\nu \\}_0^{n-1}$ of a complex polynomial $f$ and its non-constant derivatives, which lie in the unit circle. Associating with $f$ an Abel-Goncharov polynomial $G_n$ (6), one can choose an arbitrary $\\alpha >0$ such that $\\ |z_\\nu| < \\alpha^{-1}, \\ \\nu=0, 1, \\dots , n-1. $ Hence owing to (7)\n$$ f (\\alpha z_\\nu) = G_n\\left(\\alpha z_0, \\alpha z_\\nu, \\alpha z_1,\\dots, \\alpha z_{n-1}\\right)\n= \\alpha^n G_n( z_\\nu) = \\alpha^n f ( z_\\nu)= 0,\\ \\nu=0, 1,\\dots , n-1,$$\nand\n$$f^{(\\nu)} _n(\\alpha z ) = n! {d^{\\nu}\\over d z^{\\nu}}\n\\int_{\\alpha z_0}^{\\alpha z} \\int_{\\alpha z_1}^{s_{1}} \\dots \\int_{\\alpha z_{n-1}}^{s_{n-1}} d s_{n} \\dots d s_{1}\n=n! \\alpha ^\\nu \\int_{\\alpha z_\\nu}^{\\alpha z} \\int_{\\alpha z_{\\nu+1}}^{s_{\\nu+ 1}} \\dots \\int_{\\alpha z_{n-1}}^{s_{n-1}} d s_{n} \\dots d s_{\\nu+1},$$\nwe find $f^{(\\nu)} _n(\\alpha z_\\nu ) =0$. Hence $\\alpha z_\\nu, \\ \\nu=0, 1,\\dots , n-1$ are common\nroots of $\\nu$-th derivatives $f^{(\\nu)}$ and $f$, lying in the unit circle. Consequently, since via assumption the\nCasas-Alvero conjecture is true when common roots are inside the unit circle, we have that $f$ is trivial and $z_0=z_1=\\dots = z_{n-1} = a$ is a unique joint root of $f$ of the multiplicity $n$. Proposition 1 is proved.\n\\end{proof}\n\n\n\nThe following lemma will be useful in the sequel.\n\n{\\bf Lemma 10}. {\\it Let $f$ be a CA-polynomial with only real roots of degree $n \\ge 2$ and $\\{x_\\nu\n\\}_{0}^{n-1}$ be a sequence of common roots of $f$ and the corresponding derivatives $f^{(\\nu)}$. \nLet $f^{(s+\\nu)} (x_\\nu) \\ge 0, \\ s =1,2,\\dots, n-\\nu-1$ and $\\nu=0,1,\\dots, n-1$. Then $x_\\nu$ is a\nmaximal root of the derivative $f^{(\\nu)}$.}\n\n\\begin{proof} In fact, the proof is an immediate consequence of expansion (12), where we let $G_n(x)=f(x)$. Indeed, $f^{(\\nu)} (x_\\nu) =0, \\nu=0,1,\\dots, n-1$ and when $ x > x_\\nu$ we have from (12) $f^{(\\nu)} (x) > 0, \\nu=0,1,\\dots, n-1$. So, this means that there is no roots, which are bigger than $x_\\nu$. This completes the proof of Lemma 10.\n\\end{proof}\n\n\n{\\bf Proposition 2}. {\\it Under conditions of Lemma 10 the Casas-Alvero conjecture holds true for polynomials with only real roots.}\n\n\\begin{proof} We will show that under conditions of Lemma 10 there exists no CA-polynomial $f$ with only real roots. Indeed, assuming its existence, we find via conditions of the lemma that the root $x_0$ is a maximal zero of $f(x)$. This means that $x_0 \\ge x_1$. On the other hand, classical Rolle's theorem states that between zeros $x_0, \\ x_1$\nin the case $x_0 > x_1$ there exists at least one zero of the derivative $f^{(1)} (x)$, say $\\xi_1^{(1)}$,\n which is bigger than $x_1$. But this is impossible because $x_1$ is a maximal zero of the first derivative.\n Thus $x_0=x_1\\ge x_2$. Then between $x_1$ and $x_2$ in the case $x_1 > x_2$ there exists a zero $\\xi_2^{(1)}$\n of the first derivative such that $x_1> \\xi_2^{(1)} > x_2$. Hence between $x_1$ and $\\xi_2^{(1)}$ there exists at least one zero of the second derivative, which is bigger than $x_2$. But this is impossible, since $x_2$ is a maximal zero of $f^{(2)} (x)$. Therefore $x_0=x_1=x_2$. Continuing this process we observe that the sequence $\\{x_\\nu \\}_0^{n-1}$ is stationary and $f$ has a unique joint root, which contradicts the definition of the CA-polynomial. \n\\end{proof}\n\n{\\bf Corollary 9}. {\\it There exists no CA-polynomial $f$ with only real roots, having non-increasing sequence $\\{x_\\nu \\}_0^{n-1}$ of roots in common with $f$ and its non-constant derivatives.}\n\n\\begin{proof} Obviously, via (13) $f^{(s+\\nu)} (x_\\nu) \\ge 0, \\ s=1,2,\\dots, n-\\nu-1$ and conditions of Lemma 10 are satisfied.\n\\end{proof}\n\n\n{\\bf Corollary 10}. {\\it There exists no CA-polynomial $f$ with only real roots, such that each $x_\\nu$ in the sequence $\\{x_\\nu \\}_0^{n-1}$ is a maximal root of the derivative $f^{(\\nu)} (x), \\ \\nu=0,1,\\dots, n-1$.}\n\n\\begin{proof} The proof is similar to the proof of Proposition 2.\n\\end{proof}\n\nAn immediate consequence of Corollaries 3,4,5 is \n\n{\\bf Corollary 11}. {\\it The CA-polynomial, if any, with only real roots has at least 5 distinct zeros. }\n\n\n\n Let us denote by $l(m)$ the number of distinct roots of the $m$-th derivative $f^{(m)},\\ m=0, 1,\\dots, n-2$, which are in common with $f$ and different from $\\lambda_1=x_{n-1}$, which is a common root with $f^{(n-1)}$, i.e. the $m$-th derivative $f^{(m)}$ has $l(m)$ common roots with $f$\n\n$$\\lambda_{j_1}, \\dots, \\lambda_{j_{l(m)}} \\subseteq \\{ \\lambda_2, \\lambda_3, \\dots, \\ \\lambda_k\\} $$\nof multiplicities\n$$r_{j_1}, \\dots, r_{j_{l(m)}} \\subseteq \\{ r_2, r_3, \\dots, \\ r_k\\} .$$\nFor instance, $l(0)= k-1, \\ l(1)= k-1-s$, where $s$ is a number\nof simple roots of $f$. So, we see that $n-m \\ge l(m) \\ge 0$ and\nsince $f$ is a CA-polynomial, $l(m)=0$ if and only if\n$x_{n-1}=\\lambda_1$ is the only common root of $f$ with $f^{(m)}$.\n\n\n\n{\\bf Lemma 11}. {\\it There exists no CA-polynomial with only real roots, having the property\n$l(m)= l(m+1)=0$ for some $m \\in \\{r, r+1, \\dots,n-2\\},$ where $r= \\hbox{max}_{1\\le j\\le k} (r_j)$.}\n\n\\begin{proof} In fact, as we saw above, since all roots are real, it follows that all roots of $f^{(m)}, \\ m \\ge r$ are simple, which contradicts equalities $l(m)= l(m+1)=0$. Indeed, the latter equalities yield that $x_{n-1}$ is a multiple root of $f^{(m)}$. Therefore $r\\ge r_1 > m+1\\ge r+1$, which is impossible.\n\\end{proof}\n\nFurther, as in Lemma 7 we involve the root $\\lambda_{s_0}$ of multiplicity $r_{s_0}$, and $D= |\\lambda_{s_0}- x_{n-1}|$ (see (35)). Thus $\\lambda_{s_0}= \\lambda_*$ or $\\lambda_{s_0}= \\lambda^*$ and, correspondingly, $r_{s_0}=r_*$ or $r_{s_0}=r^*$. Hence, calling Sz.-Nagy identities (15), we let $z= x_{n-1}$ and assume without loss of generality that $\\lambda_{s_0}= \\lambda^*$. Then we obtain for $m \\ge r$\n$$r_*(x_{n-1}- \\lambda_*) = r^*D + \\sum_{j=2, \\ r_j\\neq r_*,\\ r^*}^{k} r_j(\\lambda_j - x_{n-1}) \\ge r^*D - D^{(m)}\n \\sum_{s=1}^{l(m)} r_{j_s} - D^{(m+1)} \\sum_{s=1}^{l(m+1)} r_{l_s} $$\n$$- \\left(n-r_1- r^*- r_*- \\sum_{s=1}^{l(m)} r_{j_s}- \\sum_{s=1}^{l(m+1)} r_{l_s}\\right)D.$$\nBut $x_{n-1}- \\lambda_*= \\hbox{span}(f)- D$. Therefore,\n$$r_* \\hbox{span}(f) + \\left(n-r_1- 2( r^*+ r_*)\\right) D \\ge (D- D^{(m)}) \\sum_{s=1}^{l(m)} r_{j_s} +\n(D- D^{(m+1)}) \\sum_{s=1}^{l(m+1)} r_{l_s}.$$\nThe right-hand side of the latter inequality is, obviously, greater or equal to $r_0 \\left(l(m)+ l(m+1)\\right) (D- D^{(m)}) $, where $1 \\le r_0= \\hbox{min}_{1\\le j\\le k} (r_j)$. Moreover, since $ \\hbox{span}(f) \\le 2D$, the left-hand side does not exceed $\\left(n-r_1\\right) D- r^* \\hbox{span}(f)$. Thus we come out with the inequality\n$$r_0 \\left(l(m)+ l(m+1)\\right) (D- D^{(m)}) \\le \\left(n-r_1\\right) D- r^* \\hbox{span}(f)$$\nor since $D- D^{(m)} > 0$ \\ ($m \\ge r$), it becomes\n$$l(m)+ l(m+1)\\le \\frac{\\left(n-r_1\\right) D- r^* \\hbox{span}(f)}{r_0(D- D^{(m)}) }.\\eqno(43)$$\nMeanwhile, appealing to (16), we get similarly \n$$n(n-1) ( x_{n-1}- x_{n-2})^2 = r^*D^2 + r_* (\\lambda_*- x_{n-1})^2 + \\sum_{j=2, \\ r_j\\neq r_*,\\ r^*}^{k}\n r_{j}(\\lambda_j- x_{n-1})^2 $$$$\n\\le r^*D^2 + r_*\\left(\\hbox{span}(f)- D\\right)^2+ \\left[D^{(m)}\\right]^2 \\sum_{s=1}^{l(m)} r_{j_s} + \\left[D^{(m+1)}\\right]^2 \\sum_{s=1}^{l(m+1)} r_{l_s}$$$$+ \\left(n-r_1- r^*- r_*- \\sum_{s=1}^{l(m)} r_{j_s}-\n \\sum_{s=1}^{l(m+1)} r_{l_s}\\right)D^2.$$\n %\n Therefore, analogously to (43), we arrive at the inequality\n %\n $$l(m)+ l(m+1)\\le \\frac{(n-r_1)D^2 + r_* \\left[\\hbox{span}(f)\\right]^2 - n(n-1) ( x_{n-1}- x_{n-2})^2 -2D r_*\\ \\hbox{span}(f)}{r_0(D^2- \\left[D^{(m)}\\right]^2) }.$$\n{\\bf Proposition 3}. {\\it There exists no CA- polynomial with only real roots of degree $n$ such that }\n$$ \\hbox{span}(f) > \\left(r^*\\right)^{-1} \\left[ (n-r_1-r_0)D + r_0 D^{(m)}\\right],\\ m\\ge r.\\eqno(44)$$\n\\begin{proof} Under condition (44), the right-hand side of (43) is less than one. Thus $l(m)= l(m+1)=0$ and Lemma 11 completes the proof.\n\\end{proof}\nLet $m=n-2$. Then since $l(n-1)=0$, inequality (43) becomes\n$$l(n-2) \\le \\frac{ (n-r_1)D - r^* \\hbox{span}(f)}{r_0(D- \\left|x_{n-1}- x_{n-2}\\right|)}.\\eqno(45)$$\n{\\bf Proposition 4}. {\\it There exists no CA- polynomial with only real roots of degree $n$ such that }\n$$D < \\left[r^* \\ \\sqrt{ \\frac{n^2-r_1}{n-r_1-r_2}} -r_0\\right] \\frac{ \\left|x_{n-1}- x_{n-2}\\right|}{n-r_1-r_0}.\\eqno(46)$$\n\n\\begin{proof} Indeed, employing the lower bound (38) for $ \\hbox{span}(f)$, we find that under condition (46) the right-hand side of (45) is strictly less than one. Consequently, $l(n-2)=0$ and owing to Corollary 1 $f$ is trivial. If the maximum of multiplicities $r > n-2$, $f$ has at most 2 distinct zeros and it is trivial via Corollary 3.\n\\end{proof}\n\nFinally, we prove \n\n{\\bf Proposition 5}. {\\it Let CA- polynomial with only real roots exist. Then it has the property\n$$ \\frac{d}{D} \\le \\sqrt{\\frac{2(n-m-1)}{2(k-1)-1}},\\eqno(47)$$\nwhere $d, D$ are defined by $(34), (35)$, respectively, and $m,\\ m+1$ belong to the interval $\\left[r, \\ {1\\over 2}\\left(1-{1\\over r_0}\\right)(n-1) \\right)$.}\n\\begin{proof} Since $m,\\ m+1$ are chosen from the interval $\\left[r, \\ {1\\over 2}\\left(1-{1\\over r_0}\\right)(n-1) \\right)$, condition (24) holds for these values. Hence assuming the existence of the CA-polynomial, we return to the Sz.-Nagy type identity (25) to have the estimate \n$$0 \\ge l(m) \\left( r_{0} {(n-m)(n-m -1)\\over n(n-1)} -1\\right) d^2 + \\left(k-1-l(m)\\right) d^2- (n-m-l(m)) D^2$$\n$$\\ge (k-1) d^2- (n-m) D^2 + l(m) (D^2-d^2).$$ \nWriting the same inequality for $m+1$\n$$0 \\ge (k-1) d^2- (n-m-1) D^2 + l(m+1) (D^2-d^2)$$ \nand adding two inequalities, we find\n$$0 \\ge 2 (k-1) d^2- (2(n-m) -1) D^2 +(l(m)+ l(m+1)) (D^2-d^2),$$\nwhich means\n$$l(m)+ l(m+1) \\le \\frac{(2(n-m) -1) D^2 - 2 (k-1) d^2}{D^2-d^2}.$$\nSo, for the existence of the CA-polynomial it is necessary that the right-hand side of the latter inequality is more or equal to 1. Thus we come out with condition (47) and complete the proof. \n\\end{proof}\n\n\n\n\n{\\bf Acknowledgment}. The present investigation was supported, in\npart, by the \"Centro de Matem{\\'a}tica\" of the University of Porto.\n\n\n\n\n\\bibliographystyle{amsplain}\n","meta":{"redpajama_set_name":"RedPajamaArXiv"}} diff --git a/data_all_eng_slimpj/shuffled/split2/finalzzbgwq b/data_all_eng_slimpj/shuffled/split2/finalzzbgwq new file mode 100644 index 0000000000000000000000000000000000000000..e3d23c54bb3d77aca39faeadbdaad83477dd1ccb --- /dev/null +++ b/data_all_eng_slimpj/shuffled/split2/finalzzbgwq @@ -0,0 +1,5 @@ +{"text":"\\section{Introduction}\n\nA standard model (SM) like Higgs boson \\cite{higgs} (denoted as H(125) in this paper) was discovered at the Large Hadron Collider (LHC) in 2012.\nIn order to test the SM and discover possible physics beyond the SM (BSM),\nit is crucial to measure the Higgs Yukawa couplings and Higgs self couplings at the LHC and future high energy colliders.\nIn the first run of the LHC, the CMS and ATLAS has constrained $h\\bar t t$ Yukawa coupling indirectly through the global fit,\nwith a precision of 20$\\%$ and 30$\\%$ respectively \\cite{Khachatryan:2014jba,a}.\nWith 300\/fb, Yukawa couplings will be measured up to 23$\\%$, 13$\\%$ and 14$\\%$ for $h\\bar b b$, $h\\tau^+ \\tau^-$ and $h\\bar t t$\nrespectively \\cite{Peskin:2012we}.\nIt was also proposed to measure the top Yukawa coupling via the associated Higgs boson production with a single top quark\n\\cite{Barger:2009ky,Ellis:2013yxa,Biswas:2012bd,Biswas:2013xva,Farina:2012xp,Englert:2014pja,Chang:2014rfa}.\n The Higgs self coupling can be measured up to $50\\%$ at the LHC with 300\/fb \\cite{Peskin:2012we}.\nThere are extensive studies on measuring anomalous triple Higgs coupling directly at the LHC \\cite{Baur:2002rb,Baur:2002qd,Baur:2003gp,Dolan:2012rv,Baglio:2012np} and\nfuture electron-positron colliders \\cite{Baer:2013cma,Asner:2013psa}.\n\n\n\nFor the future high-luminosity electron-positron colliders, it is proposed to measure\nthe Higgs self coupling up to $28\\%$ for $\\sqrt{s_{e^+e^-}}=$ 240 GeV under the model-dependent assumption that only the Higgs self coupling is modified \\cite{McCullough:2013rea} .\nThe precision of Higgs self coupling can only be reached based on the precisely measured cross section of ZH associated production up to $0.4\\%$ \\cite{Gomez-Ceballos:2013zzn}.\n Entering $e^+e^- \\rightarrow ZH$ via loops, the triple Higgs coupling will be possibly polluted heavily by other anomalous couplings,\n and among them the dominant one is the $h-Z-Z$ coupling which appears even at tree-level.\n The first run results of LHC shows that the HVV couplings including $h-Z-Z$ coupling are consistent with those in the SM \\cite{Khachatryan:2014jba,a}.\n The Higgs-top coupling contributes to the process\n$e^+e^- \\rightarrow ZH$ via loops and is potentially important for triple Higgs coupling extraction.\nActually the full one-loop correction to $e^+e^- \\rightarrow ZH$ in the SM was calculated about two decades ago \\cite{Kniehl:1991hk,Denner:1992bc,Fleischer:1982af,Denner:1991ue}.\nIn this paper we will focus on the anomalous Higgs-top coupling, especially its effects on the extraction of triple Higgs coupling.\n\nThis paper is arranged as following. In section II, we estimate the deviation of the cross section for the process $e^+e^- \\rightarrow ZH$ arising from anomalous Higgs-top coupling,\n and compare to that from triple Higgs coupling. In section III, we explore how to measure CP-violated Higgs-top coupling via the forward-backward asymmetry $A_{FB}$ for\nthe process $e^+e^- \\rightarrow ZH$. The last section contains our conclusion and discussion.\n\n\n\n\\section{ Pollution from Higgs-Top anomalous Coupling}\n\nIn the SM, the process $e^+e^- \\rightarrow ZH$ occurs at tree level and the Feynman diagram is shown in Fig. \\ref{fig1}.\n\\begin{figure}[!htbp]\n\\centering\n\\includegraphics[width=2.3in,totalheight=1.2in]{eehz.pdf}\n\\caption{Feyman diagram at tree-level for the process $e^+ e^- \\rightarrow Zh$}\n\\label{fig1}\n\\end{figure}\n\n\\begin{figure}[!htbp]\n\\includegraphics[width=2.3in,totalheight=1.2in]{eehz3h2.pdf}\n\\includegraphics[width=2.3in,totalheight=1.2in]{eehz3h.pdf}\n\\caption{Feynman diagram containing the anomalous $3h$ coupling, depicted as the black dot, at one-loop level for the process $e^+ e^- \\rightarrow Zh$. }\n\\label{fig2}\n\\end{figure}\nIn order to measure the triple Higgs coupling, one way is to produce the Higgs pair, provided that the center of mass energy of $e^+e^-$ is high enough via $ e^+e^- \\rightarrow HHZ$ or\n$ e^+e^- \\rightarrow HH \\nu \\bar \\nu$ \\cite{Levy:2015fva}. For such processes, the cross sections are notorious small.\nHigh energy and high luminosity are both required. Another way to measure the\ntriple Higgs coupling is via the virtual effects which are shown in Fig. \\ref{fig2}.\nThe capacity of measuring triple Higgs has been estimated by ref \\cite{McCullough:2013rea}. For completeness we recalculate the analytical result for\n$$\\delta_{\\sigma}\\equiv \\frac{\\Delta \\sigma}{\\sigma}=\\frac{\\sigma_{\\delta_h \\ne 0}-\\sigma_{\\delta_h = 0}}{\\sigma_{\\delta_h = 0}}$$ from the triple Higgs coupling\n$C_{SM}(1+ \\delta_h) H H H=-3i \\frac{m^2_h}{v}(1+ \\delta_h) H H H $ as\n\\begin{equation}\n\\begin{split}\n \\delta_{\\sigma}(3h) =\\frac{3 \\alpha m_h^2 \\delta_h} {16 \\pi \\beta c_w^2 s_w^2 m_z^2}\n Re\\Big[&2\\rho \\Big (C_1(m_h^2)+C_{11}(m_h^2)+C_{12}(m_h^2) \\Big)\\\\\n & -\\beta \\Big (B_0-4 C_{00}(m_h^2)+4 m_z^2C_0(m_h^2)+3m_h^2 B'_0 \\Big ) \\Big],\n\\end{split}\n\\end{equation}\nwhere $\\delta_h=0$ corresponds to the case in the SM.\nHere $$ \\beta=m_h^4-2 m_h^2 (m_z^2+s)+m_z^4+10 m_z^2 s+s^2,$$\n$$ \\rho=(m_h^2-m_z^2-s)\\left((m_h-m_z)^2-s\\right)\\left((m_h+m_z)^2-s\\right)$$\nThe definition of the one loop scalar functions B, C etc. can be found in Ref. \\cite{Ellis:2007qk} and\n$ C_0(m_h^2)=C_0(m_h^2,m_z^2,s,m_h^2,m_h^2,m_z^2)$,\n$ C(m_h^2)=C(m_h^2,s,m_z^2,m_h^2,m_h^2,m_z^2)$,\n$ B_0=B_0(m_h^2,m_h^2,m_h^2)$,\n$ B'_0=\\frac{\\partial B_0}{\\partial p^2}\\bigg|_{p^2=m_h^2}$.\n\n\\begin{figure}[!htbp]\n\\includegraphics[width=2.3in,totalheight=1.2in]{eehzhtt1.pdf}\n\\includegraphics[width=2.3in,totalheight=1.2in]{eehzhtt2.pdf}\n\\caption{Feynman diagram containing the anomalous $h\\bar t t$ coupling, depicted as the black dot, at one-loop level for the process $e^+ e^- \\rightarrow Zh$.}\n\\label{fig3}\n\\end{figure}\nIn this paper we will calculate the contributions from Higgs-top coupling which are shown in Fig. \\ref{fig3}\n\\footnote{In fact,the contributions from $Z\/\\gamma-H$ bubble transition diagrams are zero.}. The Higgs-top coupling can be parameterized as\n$$\nC_{SM}(1+ \\delta_t) H \\bar t t=-i \\frac{m_t}{v}(1+ \\delta_t) H \\bar t t,\n$$\nwhere $\\delta_t=0$ corresponds to the case in the SM.\n\nThe analytical results can be written as\n\\begin{equation}\n \\begin{split}\n &\\delta_{\\sigma}(htt)\\\\\n =&-\\frac{4 N_c\\alpha m_t^2 (s-m_z^2) v_1 v_2 \\delta_t}{3 \\pi s \\beta m_z^2 (v_1^2+a_1^2)}Re\\Big[\\beta \\Big (B_0(m_h^2)-4 C_{00}(m_t^2) \\Big)\\\\\n &-2 \\rho \\Big(C_1(m_t^2)+C_{11}(m_t^2)+C_{12}(m_t^2) \\Big)-6 m_z^2 s \\big(s+m_z^2-m_h^2 \\big ) C_0(m_t^2)\\Big] \\\\\n &+\\frac{N_c \\alpha m_t^2 \\delta_t}{\\pi c_w^2 s_w^2 m_z^2 \\beta} Re\\Big[ \\beta \\Big( 2 \\big (v_2^2+a_2^2 \\big )\\big(B_0(m_h^2)- 4 C_{00}(m_t^2)\\big) +2 a_2^2 \\big (B_0(s)+B_0(m_z^2) \\big) \\Big) \\\\\n &-\\rho\\Big( 4 \\big (v_2^2+a_2^2\\big )\\big (C_1(m_t^2)+C_{11}(m_t^2)+C_{12}(m_t^2)\\big)+2a_2^2 C_2(m_t^2) \\Big)\\\\\n &+\\Big(\\big (v_2^2+a_2^2 \\big) \\big((4 m_t^2- m_z^2-s) \\beta - \\rho \\big) +\\big (v_2^2-a_2^2 \\big) \\big (m_h^2-4 m_t^2 \\big ) \\beta \\Big) C_0(m_t^2) \\Big]\\\\\n &+\\frac{N_c\\alpha m_t^2 \\delta_t}{4 \\pi c_w^2 s_w^2 m_z^2}Re\\Big[-B_0(m_h^2)+\\big(4 m_t^2- m_h^2 \\big) B'_0(m_h^2)\\Big]\n \\end{split}\n \\label{eq2}\n\\end{equation}\nIn Eq. (\\ref{eq2}), the first\/second\/third terms are from the contributions of the diagram with photon propagator\/Z boson propagator\/the counter term of ZZH vertex, respectively.\nHere\n$ \\alpha = \\frac{e^2}{4\\pi}$,\n$N_c=3$,\n$ v_1=-\\frac{1}{4}+s_w^2$,\n$ a_1=\\frac{1}{4}$,\n$ v_2=\\frac{1}{4}-\\frac{2}{3}s_w^2$,\n$ a_2=-\\frac{1}{4}$,\n$ C_0(m_t^2)=C_0(m_h^2,m_z^2,s,m_t^2,m_t^2,m_t^2)$,\n$ C(m_t^2)=C(m_h^2,s,m_z^2,m_t^2,m_t^2,m_t^2)$,\n$ B_0(m_h^2)=B_0(m_h^2,m_t^2,m_t^2)$,\n$ B_0(m_z^2)=B_0(m_z^2,m_t^2,m_t^2)$,\n$ B_0(s)=B_0(s,m_t^2,m_t^2)$.\n\n\n\nWe use LoopTools \\cite{Hahn:1998yk} to do the scalar integral for different c.m. energies.\nIn Fig. \\ref{fig4}, we show the deviation of cross section arising from $\\delta_t$ and $\\delta_h$ as a function of $\\sqrt{s}_{e^+ e^-}$.\nSeveral numerical results for the typical c.m. energy are\n\\begin{equation}\n \\delta_\\sigma^{240,350,400,500}=1.45,0.27,0.05,-0.19\\times \\delta_h \\%\n\\end{equation}\n \\begin{equation}\n \\delta_\\sigma^{240,350,400,500}=-0.49,1.38,2.14,2.12\\times \\delta_{t} \\%\n\\end{equation}\n\\begin{figure}[!htbp]\n\n\\includegraphics[width=0.3\\textwidth]{htthhh.pdf}\n\\caption{ Relative correction $\\delta_\\sigma$ due to anomalous $h\\bar{t}t$-coupling $\\delta_t$ (red)\n and anomalous triple Higgs coupling $\\delta_h$ (blue), as a function of the $e^+ e^-$ center-of-mass (c.m.) energy from 220 GeV to 500 GeV. Note that the precision of\n relative correction can reach $0.4\\%$ for high luminosity $e^+ e^-$ colliders. }\n\\label{fig4}\n\\end{figure}\n\nThe figures show that the behavior for $\\delta_t$ and $\\delta_h$ is opposite. At low energy end, the relative correction $\\delta_\\sigma$ happen to be dominant by $\\delta_h$, on\nthe contrary for the high energy end, the $\\delta_\\sigma$ arising from anomalous Higgs-top coupling can't be neglected.\nFor the proposed collider of Circular Electron-Positron Collider with $\\sqrt{s}_{e^+e^-} \\simeq 240$ GeV, the extraction\nof triple Higgs coupling is polluted by Higgs-top coupling. For the International Linear Collider with option of high energy,\nthe pollution from Higgs-top coupling must be taken into account.\n\n\\section{ Measuring CP-violated Higgs-Top Coupling}\n\nThough the newly discovered Higgs boson H(125) is SM-like, it does not exclude the possibility that H(125) is CP mixing state. As emphasized by \\cite{zhu,Mao:2014oya} that\nCP spontaneously broken \\cite{Lee} may be closely related to the lightness of the H(125). In fact, current measurements are insensitive to the mixing, especially for\nH decaying into gauge bosons since the CP violation usually entering the couplings via loops.\n\nIn this paper we parameterize the CP violation through\n$$\nC_{SM} H\\left(1+\\delta_t +i \\delta_a \\gamma_5\\right)=-i \\frac{m_t}{v} H\\left(1+\\delta_t +i \\delta_a \\gamma_5\\right).\n$$\nIndirect constraints on $\\delta_t$ and $\\delta_a$ at the LHC have been studied in \\cite{Ellis:2013yxa}.\nAt the 68\\% CL the allowed region for ($1+\\delta_t$ , $\\delta_a$) is a crescent with apex close to the SM point(1,0) \\cite{Ellis:2013yxa}.\nThe parameter space close to the SM point, namely $\\delta_t \\rightarrow 0$ and $\\delta_a \\rightarrow 0$ is allowed. At the same time, the parameter space with\nboth non-zero $\\delta_t, \\delta_a$ is also allowed. In fact, it is quite challenging for LHC to completely exclude the latter case via the indirect method.\nOn the contrary, based on the last section analysis, the cross section deviation depends only on $\\delta_t$ but not $\\delta_a$. This point will be made clear below. Therefore\nit is important to explore the method to measure the $\\delta_a$ at electron-positron collider.\n\nThe analytical results for the differential cross section arising from $\\delta_a$ can be written as\n\\begin{equation}\n \\begin{split}\n &\\frac{1}{\\delta_a} \\frac{d\\sigma}{d cos\\alpha}\\\\\n =&\\frac{32 N_c a_1 m_t^2 \\pi \\alpha^3 cos\\alpha \\sqrt{\\left((m_h-m_z)^2-s\\right) \\left((m_h+m_z)^2-s\\right)}}{c^4_w s^4_w \\left(m_z^2-s\\right)}\\\\\n &Im\\Big[\\frac{1}{3} v_2 C_0(m_t^2)\n +\\frac{ s}{c_w^2 s_w^2 \\left(m_z^2-s\\right)} v_1\n\\big((v_2^2+a_2^2) C_0(m_t^2)+2 a_2^2 C_2(m_t^2)\\big)\\Big]\n \\end{split}\n\\end{equation}\nHere $cos\\alpha$ is the angle between the momentum of the electron and the Z boson. The differential cross section is proportional to $cos\\alpha$, which is\ndue to the term $\\varepsilon_{\\mu \\nu \\rho \\lambda} \\varepsilon^{\\mu \\nu \\alpha \\beta} p_2^{\\rho} p_1^{\\lambda} k_{1\\alpha} k_{2\\beta}$\nwhere $p_1$ $p_2$ are the momentum of electron and positron and $k_1$ $k_2$ are the momentum of Higgs and Z. Another critical requirement for non-vanishing contribution\nto the differential cross section\nis that there should be imaginary part from top loops. This requires that the $\\sqrt{s}_{e^+e^-}$ must be great than $2 m_t$.\n\n\nIt is obvious that the CP-odd contributions to the total cross section is zero.\nIn order to show the different contributions from $\\delta_t$ and $\\delta_a$ respectively, we plot the normalized differential cross sections for several $\\sqrt{s}_{e^+e^-}$\nand set the corresponding parameter $\\delta_t$ or $\\delta_a$ equal to 1.\n\\begin{figure}[!htbp]\n\\includegraphics[width=0.5\\textwidth]{total4.pdf}\n\\caption{Differential scattering cross section as a function of the scattering angle with $\\sqrt{s}=240GeV$(orange),$350GeV$(red),$400GeV$(green),$500GeV$(blue).\nAnd solid\/dashed lines stand for the contributions\n from $\\delta_t$\/$\\delta_a$ respectively. }\n\\label{6}\n\\end{figure}\nFrom the figure, it is quite clear that the differential cross sections arising from $\\delta_t$ are symmetric and anti-symmetric from $\\delta_a$.\nFor $\\sqrt{s}=240GeV$, the contribution from $\\delta_a$ is zero because there is no imaginary part of $ C_0(m_t^2)$.\nWhen $\\sqrt{s}_{e^+e^-} > 2 m_t$ there are nonzero contributions from $\\delta_a$ as expected.\n\nIn order to gauge the forward-backward asymmetry, we introduce\n$$\nA_{FB} \\equiv \\frac{\\int_{0}^1 d\\cos \\alpha \\frac{d\\sigma}{d\\cos\\alpha} - \\int_{-1}^0 d\\cos \\alpha \\frac{d\\sigma}{d\\cos\\alpha} }{\\sigma_{tot} }\n$$\n\nIn Fig. \\ref{fig9}, we plot $A_{FB}$ as a function of $\\sqrt{s}_{e^+e^-}$ with $\\delta_a=1$ for polarized and unpolarized electron\/positron beam.\n\n\\begin{figure}[!htbp]\n\\includegraphics[width=0.4\\textwidth]{afbsum.pdf}\n\\caption{ $A_{FB}$ as a function of $\\sqrt{s}_{e^+e^-}$ from $220GeV$ to $500GeV$ for polarized or unpolarized electron\/positron beams.\nThe black line, blue dashed and red dashed seperately\ncorrespond to unpolarized electron\/positron beams,$e_R^+ e_L^-$ and $e_L^+ e_R^-$ polarizations.}\n\\label{fig9}\n\\end{figure}\n\n\nFrom the figure we can see that the asymmetry can reach $0.7 \\%$ for $\\sqrt{s}_{e^+e^-}$. Such precision is comparable to that of cross section measurement.\nIt seems that the high luminosity collider is necessary.\n\n\n\n\\section{Conclusion and discussion}\n\nIn this paper, we explore the Higgs-top anomalous coupling pollution to the extraction of Higgs self coupling via precisely measuring cross section of $e^+e^- \\rightarrow ZH$.\nThe important conclusion is that the pollution is small for the $\\sqrt{s}_{e^+e^-} =240$ GeV, but can be sizable for higher energy collider.\nThe contributions to total cross section from Higgs-top CP-odd coupling is vanishing, while such interaction can\n be scrutinized via forward-backward asymmetry for $\\sqrt{s}_{e^+e^-}$ greater than $2 m_t$.\n\n\n\\section*{Acknowledgement}\n\n We would like to thank Shao Long Chen , Gang Li and Pengfei Yin for the useful discussions. This work was supported in part by the Natural Science Foundation\n of China (Nos. 11135003 and 11375014).\n\n","meta":{"redpajama_set_name":"RedPajamaArXiv"}} +{"text":"\\section{Introduction}\\label{E:introduction}\n\nWormholes are handles or tunnels in spacetime\nconnecting widely separated regions of our\nUniverse or different universes altogether.\nWhile there had been some forerunners,\nmacroscopic traversable wormholes were first\ndiscussed in detail by Morris and Thorne\n\\cite{MT88} in 1988. A few years later,\nSung-Won Kim \\cite{Kim} proposed the\npossible existence of an evolving wormhole\nin the context of the\nFriedmann-Lemaitre-Robertson-Walker (FLRW)\ncosmological model by assuming that the\nmatter content can be divided into two\nparts, the cosmological part that depends on\ntime only and the wormhole part that depends\non space only. The discussion was later\nexpanded by Cataldo et al. \\cite{mC13}.\n\nThe purpose of this paper is to study the\nrelationship between wormholes inspired by\nnoncommutative geometry and the Kim model.\nThe noncommutative-geometry background\nsimultaneously affects both the wormhole\nconstruction and the cosmological part of\nthe solution. This result differs\nsignificantly from the outcomes in Refs.\n\\cite{Kim} and \\cite{mC13}.\n\nRegarding the strategy, Ref. \\cite{MT88}\nconcentrates mainly on the wormhole\ngeometry by specifying the metric\ncoefficients. This strategy requires a\nsearch for matter or fields that can produce\nthe energy-momentum tensor needed to sustain\nthe wormhole. Here it needs to be emphasized\nthat we are able to satisfy the geometric\nrequirements from the physical properties.\nThe result is an evolving zero-tidal force\nwormhole solution; it is restricted to the\ncurvature parameters $k=0$ and $k=-1$,\ncorresponding to an open Universe.\n\nViewed from a broader perspective, it has\nalready been shown that noncommutative\ngeometry, which is an offshoot of string\ntheory, can account for the flat galactic\nrotation curves \\cite{pK17, fR12}, but\nunder certain conditions, noncommutative\ngeometry can also support traversable\nwormholes \\cite{KG14, pK18, pK16, pK15,\n Jamil14, FKRI12}.\n\nThis paper is organized as follows: Sec.\n\\ref{S:structure} briefly recalls the\nstructure of wormholes and the basic\nfeatures of noncommutative geometry.\nSec. \\ref{S:Kim} continues with the\nSung-Won Kim model. Here the discussion\nis necessarily more detailed, partly\nin the interest of completeness, but mainly\nto allow the inclusion of a more general\nform of the Einstein field equations.\nThese are subsequently used in Sec. \\ref\n{S:special} to obtain a wormhole solution\nthat does not depend on the separation\nof the matter content. In Sec. \\ref{S:nc}\nwe derive a wormhole solution from the\nnoncommutative-geometry background,\nfollowed by a discussion of the null\nenergy condition in Sec. \\ref {S:violation}.\nSec. \\ref{S:comparison} features a\n comparison to an earlier solution.\n In Sec. \\ref{S:conclusion}, we conclude.\n\n\n\\section{Wormhole structure and\n noncommutative geometry}\\label{S:structure}\n\nMorris and Thorne \\cite{MT88} proposed the\nfollowing static and spherically symmetric\nline element for a wormhole spacetime:\n\\begin{equation}\\label{E:line1}\nds^{2}=-e^{2\\Phi(r)}dt^{2}+\\frac{dr^2}{1-b(r)\/r}\n+r^{2}(d\\theta^{2}+\\text{sin}^{2}\\theta\\,\nd\\phi^{2}),\n\\end{equation}\nusing units in which $c=G=1$. Here $b=b(r)$\nis called the \\emph{shape function} and\n$\\Phi=\\Phi(r)$ is called the \\emph{redshift\nfunction}, which must be everywhere finite\nto avoid an event horizon. For the shape\nfunction we must have $b(r_0)=r_0$, where\n$r=r_0$ is the radius of the \\emph{throat}\nof the wormhole. The wormhole spacetime\nshould be asymptotically flat, i.e.,\n$\\text{lim}_{r\\rightarrow \\infty}\\Phi(r)\n=0$ and $\\text{lim}_{r\\rightarrow \\infty}\nb(r)\/r=0$. An important requirement is the\n\\emph{flare-out condition} at the throat:\n$b'(r_0)<1$, while $b(r)0.\n\\end{equation}\nAt $r=r_0$, we therefore get\n\\begin{equation}\n r_0-r_0\\frac{8\\pi\\mu\\sqrt{\\beta}r_0^2}\n {\\pi^2(r_0^2+\\beta)^2}+3mr_0^3\n -2kr_0^3>0.\n\\end{equation}\nSince $\\sqrt{\\beta}$ is extremely small, we\nactually have\n\\begin{equation}\\label{E:NEC}\n r_0+(3m-2k)r_0^3\\gtrsim 0.\n\\end{equation}\nTo check this condition, we need to return\nto Ref. \\cite{NSS06} for some additional\nobservations. The relationship between\nthe radial pressure and energy density\nis given by\n\\begin{equation}\\label{E:EoS}\n P^r=-\\rho.\n\\end{equation}\nThe reason is that the source is a\nself-gravitating droplet of anisotropic\nfluid of density $\\rho$ and the radial\npressure is needed to prevent the\ncollapse back to the matter point. In\naddition, the lateral pressure is\ngiven by\n\\begin{equation}\\label{E:tr1}\n P^t=-\\rho-\\frac{r}{2}\n \\frac{\\partial\\rho}{\\partial r}.\n\\end{equation}\nSince the length scales can be\nmacroscopic, we can retain Eq.\n(\\ref{E:EoS}) and then use Eq.\n(\\ref{E:tr1}) to write\n\\begin{equation}\\label{E:tr2}\n P^t=-\\rho-\\frac{r}{2}\n \\frac{\\partial\\rho}{\\partial r}\n =P^r+\\frac{2\\mu r^2\\sqrt{\\beta}}\n {\\pi^2(r^2+\\beta)^3}\n\\end{equation}\nby Eq. (\\ref{E:rho}). So on larger\nscales, we have $P^r=P^t$. Since the\npressure becomes isotropic, we can\nassume the equation of state to be\n$P_c=-\\rho_c$. Substituting in Eqs.\n(\\ref{E:R1}) and (\\ref{E:R2}), we get\n\\begin{equation*}\n -2\\frac{\\ddot{R}}{R}\n +2\\left(\\frac{\\dot{R}}{R}\\right)^2\n +\\frac{2k}{R^2}-\\frac{2m}{R^2}=0.\n\\end{equation*}\nThis equation can be rewritten as\n\\begin{equation}\n 3\\frac{\\ddot{R}}{R}\n -3\\left(\\frac{\\dot{R}}{R}\\right)^2=\n \\frac{3k}{R^2}-\\frac{3m}{R^2}.\n\\end{equation}\nSubtracting the Friedmann equations\n\\[\n 3\\frac{\\ddot{R}}{R}=-4\\pi(\\rho_c\n +3P_c)\n\\]\nand\n\\[\n 3\\left(\\frac{\\dot{R}}{R}\\right)^2\n =8\\pi\\rho_c-\\frac{3k}{R^2}\n\\]\nnow yields\n\\begin{equation}\n \\frac{3k}{R^2}-\\frac{3m}{R^2}=\n -4\\pi(\\rho_c+3P_c)-8\\pi\\rho_c\n +\\frac{3k}{R^2}.\n\\end{equation}\nSo if $P_c=-\\rho_c$, we obtain\n\\begin{equation}\n m=0, \\text{independently of}\\quad k.\n\\end{equation}\nApplied to Eq. (\\ref{E:NEC}), the NEC\nis violated if\n\\begin{equation}\n k=0\\quad \\text{or}\\quad k=-1.\n\\end{equation}\nThese conditions correspond to an open\nUniverse.\n\nTo summarize, we employed basic physical\nprinciples to derive the following\nzero-tidal force solution:\n\\begin{equation}\n \\Phi(r)\\equiv 0\n\\end{equation}\nand (since $m=0$)\n\\begin{multline}\\label{E:shape1}\n b(r)=\\frac{4M\\sqrt{\\beta}}{\\pi}\n \\left(\\frac{1}{\\sqrt{\\beta}}\\text{tan}^{-1}\n \\frac{r}{\\sqrt{\\beta}}-\\frac{r}{r^2+\\beta}\n \\right)\\\\\n -\\frac{4M\\sqrt{\\beta}}{\\pi}\n \\left(\\frac{1}{\\sqrt{\\beta}}\\text{tan}^{-1}\n \\frac{r_0}{\\sqrt{\\beta}}-\\frac{r_0}{r_0^2\n +\\beta}\\right)+r_0.\n\\end{multline}\nThe slowly evolving wormhole solution is\nrestricted to the values $k=0$ and $k=-1$\nto ensure that the NEC is violated. The\nwormhole spacetime is asymptotically flat.\n\n\\section{The special case $k=0$}\n \\label{S:special}\nFor completeness let us briefly consider\na wormhole solution that does not depend\non the separation of the Einstein field\nequations. We can combine Eqs.\n(\\ref{E:E1}) and (\\ref{E:E2})\nto obtain\n\\begin{equation}\n 8\\pi r^3R^2\\left[\\rho(r,t)+P^r(r,t)\n \\right]=2r^3(\\dot{R}^2-R\\ddot{R})\n +2r^3k+rb'(r)-b(r).\n\\end{equation}\nIf we now let $k=0$, then Eq.\n(\\ref{E:line2}) represents an evolving\nMorris-Thorne wormhole with the usual\nshape function $b=b(r)$. The NEC is\nviolated at the throat $r=r_0$ for all\n$t$ whenever\n\\begin{equation}\\label{E:NEC1}\n 8\\pi r_0^3R^2\\left[\\rho(r_0,t)-\n P^r(r_0,t)\\right]=2r_0^3(\\dot{R^2}\n -R\\ddot{R})+r_0b'(r_0)-b(r_0)<0.\n\\end{equation}\nIf the Universe is indeed accelerating,\nthen the term $-R\\ddot{R}$ eventually\nbecomes dominant due to the\never-increasing $R$. So for\nsufficiently large $R$, the NEC is\nviolated, thereby fulfilling a key\nrequirement for the existence of\nwormholes. (Inflating Lorentzian\nwormholes are discussed in Ref.\n\\cite{tR93}.)\n\nRecalling that the radial tension $\\tau$\nis the negative of $P^r$, Inequality\n(\\ref{E:NEC1}) can be written (since\n$b(r_0)=r_0$)\n\\begin{equation}\\label{E:NEC2}\n 8\\pi r_0^2R^2\\left[\\tau(r_0)-\\rho(r_0)\n \\right]=2r_0^2(-\\dot{R^2}+R\\ddot{R})\n -b'(r_0)+1>0.\n\\end{equation}\nIf $R(t)\\equiv 1$, this reduces to the\nstatic Morris-Thorne wormhole; so if\n$b'(r_0)<1$, then $\\tau(r_0)>\\rho(r_0)$,\nrequiring exotic matter. In Inequality\n(\\ref{E:NEC2}), however, $\\tau(r_0)>\n\\rho(r_0)$ could result from the\ndominant term $R\\ddot{R}$. In that\ncase, the NEC is violated without\nrequiring exotic matter for the\nconstruction of the wormhole itself.\n\n\\section{Comparison to an earlier solution}\n \\label{S:comparison}\nA wormhole solution inspired by\nnoncommutative geometry had already been\nconsidered in Ref. \\cite{pK15}. The\nEinstein field equation $\\rho(r)=\nb'(r)\/(8\\pi r^2)$, together with Eq.\n(\\ref{E:rho}), leads directly to the\nstatic solution, Eq. (\\ref{E:shape1}).\n(Here it is understood that $k=0$,\nbut $R(t)$ could be retained.)\nUnfortunately, this simple approach\nleaves the redshift function\nundetermined. The desirability of\nzero tidal forces then suggested the\nassumption $\\Phi(r)\\equiv 0$ in Ref.\n\\cite{pK15}. It is shown in Ref.\n\\cite{pK09}, however, that this\nassumption causes a Morris-Thorne\nwormhole to be incompatible with the\nFord-Roman constraints from quantum\nfield theory. Given the\nnoncommutative-geometry background,\nrather than the purely classical setting\nin Ref. \\cite{MT88}, this objection\ndoes not apply directly.\n\nIt is interesting to note that in the\npresent paper, the zero-tidal force\nsolution is built into the Sung-Won\nKim model and does not require any\nadditional considerations.\n\n\\section{Conclusion}\\label{S:conclusion}\nMorris-Thorne wormholes typically require\na reverse strategy for their theoretical\nconstruction: specify the geometric\nrequirements and then manufacture or search\nthe Universe for matter or fields to obtain\nthe required energy-momentum tensor. One\nof the goals in this paper is to obtain a\ncomplete wormhole solution from certain\nphysical principles. To this end, we assume\na noncommutative-geometry background, as in\nprevious studies, but we also depend on a\ncosmological model due to Sung-Won Kim that\nis based on the FLRW model with a\ntraversable wormhole. The basic assumption\nis that the matter content can be divided\ninto two parts, a cosmological part that\ndepends only on $t$ and a wormhole part\nthat depends only on the radial coordinate\n$r$. The result is a complete zero-tidal\nforce solution; it is restricted, however,\nto the values $k=0$ and $k=-1$, corresponding\nto an open Universe. This conclusion is\nconsistent with the special case $k=0$\ndiscussed in Sections \\ref{S:special}\nand \\ref{S:comparison}.\n\n\nThe wormhole is slowly evolving due to the\nscale factor $R(t)$ and, critically, the\nnoncommutative-geometry background not\nonly produces the wormhole solution, it\nalso affects in a direct manner the\ncosmological part of the solution. This\nconclusion differs significantly from\nthose in Refs. \\cite {Kim} and \\cite{mC13}.\n\n\n","meta":{"redpajama_set_name":"RedPajamaArXiv"}} +{"text":"\\section{Introduction}\n\nThe inequalit\n\\begin{equation}\nf\\left( \\frac{a+b}{2}\\right) \\leq \\frac{1}{b-a}\\int_{a}^{b}f\\left( x\\right)\ndx\\leq \\frac{f\\left( a\\right) +f\\left( b\\right) }{2} \\label{h}\n\\end{equation\nwhich holds for all convex functions $f:[a,b]\\rightarrow \n\\mathbb{R}\n$, is known in the literature as Hermite-Hadamard's inequality.\n\nIn \\cite{G}, Toader defined $m-$convexity as the following:\n\n\\begin{definition}\nThe function $f:[0,b]\\rightarrow \n\\mathbb{R}\n,$ $b>0$, is said to be $m-$convex where $m\\in \\lbrack 0,1],$ if we hav\n\\begin{equation*}\nf(tx+m(1-t)y)\\leq tf(x)+m(1-t)f(y)\n\\end{equation*\nfor all $x,y\\in \\lbrack 0,b]$ and $t\\in \\lbrack 0,1].$ We say that $f$ is \nm- $concave if $\\left( -f\\right) $ is $m-$convex.\n\\end{definition}\n\nIn \\cite{D}, Dragomir proved the following theorem.\n\nLet $f:\\left[ 0,\\infty \\right) \\rightarrow \n\\mathbb{R}\n$ be an $m-$convex function with $m\\in \\left( 0,1\\right] $ and $0\\leq a0$, is said to be $\\left( \\alpha ,m\\right) -$convex, where $\\left(\n\\alpha ,m\\right) \\in \\lbrack 0,1]^{2},$ if we hav\n\\begin{equation*}\nf(tx+m(1-t)y)\\leq t^{\\alpha }f(x)+m(1-t^{\\alpha })f(y)\n\\end{equation*\nfor all $x,y\\in \\lbrack 0,b]$ and $t\\in \\lbrack 0,1].$\n\\end{definition}\n\nDenote by $K_{m}^{\\alpha }\\left( b\\right) $ the class of all $\\left( \\alpha\n,m\\right) -$convex functions on $\\left[ 0,b\\right] $ for which $f\\left(\n0\\right) \\leq 0.$ If we take $\\left( \\alpha ,m\\right) =\\left\\{ \\left(\n0,0\\right) ,\\left( \\alpha ,0\\right) ,\\left( 1,0\\right) ,\\left( 1,m\\right)\n,\\left( 1,1\\right) ,\\left( \\alpha ,1\\right) \\right\\} ,$ it can be easily\nseen that $\\left( \\alpha ,m\\right) -$convexity reduces to increasing: \n\\alpha -$starshaped, starshaped, $m-$convex, convex and $\\alpha -$convex,\nrespectively.\n\nIn \\cite{SSOR}, Set et al. proved the following Hadamard type inequalities\nfor $\\left( \\alpha ,m\\right) -$convex functions.\n\n\\begin{theorem}\nLet $f:\\left[ 0,\\infty \\right) \\rightarrow \n\\mathbb{R}\n$ be an $\\left( \\alpha ,m\\right) -$convex function with $\\left( \\alpha\n,m\\right) \\in \\left( 0,1\\right] ^{2}.$ If \\ $0\\leq a0$ be a given $\\left( \\alpha ,m\\right) $-convex function on the\ninterval $\\left[ 0,b\\right] $. The real function $f:\\left[ 0,b\\right]\n\\rightarrow \n\\mathbb{R}\n$ is called $\\left( g-\\left( \\alpha ,m\\right) \\right) $-convex dominated on \n\\left[ 0,b\\right] $ if the following condition is satisfie\n\\begin{eqnarray}\n&&\\left\\vert \\lambda ^{\\alpha }f(x)+m(1-\\lambda ^{\\alpha })f(y)-f\\left(\n\\lambda x+m\\left( 1-\\lambda \\right) y\\right) \\right\\vert \\label{h6} \\\\\n&\\leq &\\lambda ^{\\alpha }g(x)+m(1-\\lambda ^{\\alpha })g(y)-g\\left( \\lambda\nx+m\\left( 1-\\lambda \\right) y\\right) \\notag\n\\end{eqnarray\nfor all $x,y\\in \\left[ 0,b\\right] $, $\\lambda \\in \\left[ 0,1\\right] $ and \n\\left( \\alpha ,m\\right) \\in \\left[ 0,1\\right] ^{2}.$\n\\end{definition}\n\nThe next simple characterisation of $\\left( \\alpha ,m\\right) $-convex\ndominated functions holds.\n\n\\begin{lemma}\n\\label{l1} Let $g:\\left[ 0,b\\right] \\rightarrow \n\\mathbb{R}\n$ be an $\\left( \\alpha ,m\\right) $-convex function on the interval $\\left[\n0,b\\right] $ and the function $f:\\left[ 0,b\\right] \\rightarrow \n\\mathbb{R}\n.$ The following statements are equivalent:\n\\end{lemma}\n\n\\begin{enumerate}\n\\item $f$ is $\\left( g-\\left( \\alpha ,m\\right) \\right) $-convex dominated on \n$\\left[ 0,b\\right] .$\n\n\\item The mappings $g-f$ and $g+f$ are $\\left( \\alpha ,m\\right) $-convex\nfunctions on $\\left[ 0,b\\right] .$\n\n\\item There exist two $\\left( \\alpha ,m\\right) $-convex mappings $h,k$\ndefined on $\\left[ 0,b\\right] $ such tha\n\\begin{equation*}\n\\begin{array}{ccc}\nf=\\frac{1}{2}\\left( h-k\\right) & \\text{and} & g=\\frac{1}{2}\\left( h+k\\right\n\\end{array\n.\n\\end{equation*}\n\\end{enumerate}\n\n\\begin{proof}\n1$\\Longleftrightarrow $2 The condition (\\ref{h6}) is equivalent t\n\\begin{eqnarray*}\n&&g\\left( \\lambda x+m\\left( 1-\\lambda \\right) y\\right) -\\lambda ^{\\alpha\n}g(x)-m(1-\\lambda ^{\\alpha })g(y) \\\\\n&\\leq &\\lambda ^{\\alpha }f(x)+m(1-\\lambda ^{\\alpha })f(y)-f\\left( \\lambda\nx+m\\left( 1-\\lambda \\right) y\\right) \\\\\n&\\leq &\\lambda ^{\\alpha }g(x)+m(1-\\lambda ^{\\alpha })g(y)-g\\left( \\lambda\nx+m\\left( 1-\\lambda \\right) y\\right) \n\\end{eqnarray*\nfor all $x,y\\in I$, $\\lambda \\in \\left[ 0,1\\right] $ and $\\left( \\alpha\n,m\\right) \\in \\left[ 0,1\\right] ^{2}.$ The two inequalities may be\nrearranged a\n\\begin{equation*}\n\\left( g+f\\right) \\left( \\lambda x+m\\left( 1-\\lambda \\right) y\\right) \\leq\n\\lambda ^{\\alpha }\\left( g+f\\right) (x)+m(1-\\lambda ^{\\alpha })\\left(\ng+f\\right) (y)\n\\end{equation*\nan\n\\begin{equation*}\n\\left( g-f\\right) \\left( \\lambda x+m\\left( 1-\\lambda \\right) y\\right) \\leq\n\\lambda ^{\\alpha }\\left( g-f\\right) (x)+m(1-\\lambda ^{\\alpha })\\left(\ng-f\\right) (y)\n\\end{equation*\nwhich are equivalent to the $\\left( \\alpha ,m\\right) $-convexity of $g+f$\nand $g-f,$ respectively.\n\n2$\\Longleftrightarrow $3 We define the mappings $f,g$ as $f=\\frac{1}{2\n\\left( h-k\\right) $ and $g=\\frac{1}{2}\\left( h+k\\right) $. Then, if we sum\nand subtract $f,g,$ respectively, we have $g+f=h$ and $g-f=k.$ By the\ncondition 2 of Lemma 1, the mappings $g-f$ and $g+f$ are $\\left( \\alpha\n,m\\right) $-convex on $\\left[ 0,b\\right] ,$ so $h,k$ are $\\left( \\alpha\n,m\\right) $-convex mappings too.\n\\end{proof}\n\n\\begin{theorem}\n\\label{t1} Let $g:\\left[ 0,\\infty \\right) \\rightarrow \n\\mathbb{R}\n$ be an $\\left( \\alpha ,m\\right) -$convex function with $\\left( \\alpha\n,m\\right) \\in \\left( 0,1\\right] ^{2}$. $f:\\left[ 0,\\infty \\right)\n\\rightarrow \n\\mathbb{R}\n$ is $\\left( g-\\left( \\alpha ,m\\right) \\right) -$convex dominated mapping\nand $0\\leq a0\n\\end{eqnarray*\nwhich gives for $x=a$ and $y=\\frac{b}{m}\n\\begin{eqnarray}\n&&\\left\\vert t^{\\alpha }f\\left( a\\right) +m(1-t^{\\alpha })f\\left( \\frac{b}{m\n\\right) -f\\left( ta+m(1-t)\\frac{b}{m}\\right) \\right\\vert \\label{h7} \\\\\n&& \\notag \\\\\n&\\leq &t^{\\alpha }g\\left( a\\right) +m(1-t^{\\alpha })g\\left( \\frac{b}{m\n\\right) -g\\left( ta+m(1-t)\\frac{b}{m}\\right) \\notag\n\\end{eqnarray\nand for $x=\\frac{a}{m}$, $y=\\frac{b}{m^{2}}$ and then multiply with $m$ \n\\begin{eqnarray}\n&&\\left\\vert mtf\\left( \\frac{a}{m}\\right) +m^{2}(1-t)f\\left( \\frac{b}{m^{2}\n\\right) -mf\\left( t\\frac{a}{m}+(1-t)\\frac{b}{m}\\right) \\right\\vert\n\\label{h8} \\\\\n&& \\notag \\\\\n&\\leq &mtg\\left( \\frac{a}{m}\\right) +m^{2}(1-t)g\\left( \\frac{b}{m^{2}\n\\right) -mg\\left( t\\frac{a}{m}+(1-t)\\frac{b}{m}\\right) \\notag\n\\end{eqnarray\nfor all $t\\in \\left[ 0,1\\right] .$ By properties of modulus, if we add the\ninequalities in $\\left( \\text{\\ref{h7}}\\right) $ and $\\left( \\text{\\ref{h8}\n\\right) $, we get \n\\begin{eqnarray*}\n&&\\left\\vert t^{\\alpha }\\left[ f\\left( a\\right) +mf\\left( \\frac{a}{m}\\right)\n\\right] +m(1-t^{\\alpha })\\left[ f\\left( \\frac{b}{m}\\right) +mf\\left( \\frac{\n}{m^{2}}\\right) \\right] \\right. \\\\\n&& \\\\\n&&-\\left. \\left[ f\\left( ta+m(1-t)\\frac{b}{m}\\right) +mf\\left( t\\frac{a}{m\n+(1-t)\\frac{b}{m}\\right) \\right] \\right\\vert \\\\\n&& \\\\\n&\\leq &t^{\\alpha }\\left[ g\\left( a\\right) +mg\\left( \\frac{a}{m}\\right)\n\\right] +m(1-t^{\\alpha })\\left[ g\\left( \\frac{b}{m}\\right) +mg\\left( \\frac{\n}{m^{2}}\\right) \\right] \\\\\n&& \\\\\n&&-\\left[ g\\left( ta+m(1-t)\\frac{b}{m}\\right) +mg\\left( t\\frac{a}{m}+(1-t\n\\frac{b}{m}\\right) \\right] .\n\\end{eqnarray*\nThus, integrating over $t$ on $\\left[ 0,1\\right] $ we obtain the second\ninequality. The proof is completed.\n\\end{proof}\n\n\\begin{remark}\nIf we choose $\\alpha =1$ in Theorem \\ref{t1}, we get two inequalities of\nHermite-Hadamard type for functions that are $\\left( g,m\\right) -$convex\ndominated in Theorem \\ref{a}.\n\\end{remark}\n\n\\begin{theorem}\n\\label{t2} Let $g:\\left[ 0,\\infty \\right) \\rightarrow \n\\mathbb{R}\n$ be an $\\left( \\alpha ,m\\right) -$convex function with $\\left( \\alpha\n,m\\right) \\in \\left( 0,1\\right] ^{2}$. $f:\\left[ 0,\\infty \\right)\n\\rightarrow \n\\mathbb{R}\n$ is $\\left( g-\\left( \\alpha ,m\\right) \\right) -$convex dominated \\ mapping\nand $0\\leq a