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Theoretical formalisms for the homogenization of particulate composites are identified as following either the direct scattering approach (DSA) or the indirect scattering approach (ISA). Both approaches can take inclusion size-dependence and distribution statistics into account. However, the DSA is generally limited to mediums with direction-independent constitutive properties and inclusions with simple shapes, but the ISA is not hobbled thus. | physics |
Deployment and operation of autonomous underwater vehicles is expensive and time-consuming. High-quality realistic sonar data simulation could be of benefit to multiple applications, including training of human operators for post-mission analysis, as well as tuning and validation of autonomous target recognition (ATR) systems for underwater vehicles. Producing realistic synthetic sonar imagery is a challenging problem as the model has to account for specific artefacts of real acoustic sensors, vehicle altitude, and a variety of environmental factors. We propose a novel method for generating realistic-looking sonar side-scans of full-length missions, called Markov Conditional pix2pix (MC-pix2pix). Quantitative assessment results confirm that the quality of the produced data is almost indistinguishable from real. Furthermore, we show that bootstrapping ATR systems with MC-pix2pix data can improve the performance. Synthetic data is generated 18 times faster than real acquisition speed, with full user control over the topography of the generated data. | computer science |
We follow the idea of formulating vision as inverse graphics and propose a new type of element for this task, a neural-symbolic capsule. It is capable of de-rendering a scene into semantic information feed-forward, as well as rendering it feed-backward. An initial set of capsules for graphical primitives is obtained from a generative grammar and connected into a full capsule network. Lifelong meta-learning continuously improves this network's detection capabilities by adding capsules for new and more complex objects it detects in a scene using few-shot learning. Preliminary results demonstrate the potential of our novel approach. | computer science |
We experimentally and theoretically study impacts into dense cornstarch and water suspensions. We vary impact speed as well as intruder size, shape, and mass, and we characterize the resulting dynamics using high-speed video and an onboard accelerometer. We numerically solve previously proposed models, most notably the added-mass model as well as a class of models where the viscous forces at the boundary of the jammed front are dominant. We find that our experimental data are inconsistent with the added mass model, but are consistent with the viscous model. Our results strongly suggest that the added-mass model, which is the dominant model for understanding the dynamics of impact into dense suspensions, should be updated to include these viscous-like forces. | condensed matter |
Image cropping aims to improve the composition as well as aesthetic quality of an image by removing extraneous content from it. Existing image cropping databases provide only one or several human-annotated bounding boxes as the groundtruth, which cannot reflect the non-uniqueness and flexibility of image cropping in practice. The employed evaluation metrics such as intersection-over-union cannot reliably reflect the real performance of cropping models, either. This work revisits the problem of image cropping, and presents a grid anchor based formulation by considering the special properties and requirements (e.g., local redundancy, content preservation, aspect ratio) of image cropping. Our formulation reduces the searching space of candidate crops from millions to less than one hundred. Consequently, a grid anchor based cropping benchmark is constructed, where all crops of each image are annotated and more reliable evaluation metrics are defined. We also design an effective and lightweight network module, which simultaneously considers the region of interest and region of discard for more accurate image cropping. Our model can stably output visually pleasing crops for images of different scenes and run at a speed of 125 FPS. Code and dataset are available at: https://github.com/HuiZeng/Grid-Anchor-based-Image-Cropping. | computer science |
Recently, deep neural networks (DNNs) have shown advantages in accelerating optimization algorithms. One approach is to unfold finite number of iterations of conventional optimization algorithms and to learn parameters in the algorithms. However, these are forward methods and are indeed neither iterative nor convergent. Here, we present a novel DNN-based convergent iterative algorithm that accelerates conventional optimization algorithms. We train a DNN to yield parameters in scaled gradient projection method. So far, these parameters have been chosen heuristically, but have shown to be crucial for good empirical performance. In simulation results, the proposed method significantly improves the empirical convergence rate over conventional optimization methods for various large-scale inverse problems in image processing. | computer science |
The goal of this article is to investigate nontrivial $m$-quasi-Einstein manifolds globally conformal to an $n$-dimensional Euclidean space. By considering such manifolds, whose conformal factors and potential functions are invariant under the action of an $(n-1)$-dimensional translation group, we provide a complete classification when $\lambda=0$ and $m\geq 1$ or $m=2-n.$ | mathematics |
Streaming 360{\deg} videos requires more bandwidth than non-360{\deg} videos. This is because current solutions assume that users perceive the quality of 360{\deg} videos in the same way they perceive the quality of non-360{\deg} videos. This means the bandwidth demand must be proportional to the size of the user's field of view. However, we found several qualitydetermining factors unique to 360{\deg}videos, which can help reduce the bandwidth demand. They include the moving speed of a user's viewpoint (center of the user's field of view), the recent change of video luminance, and the difference in depth-of-fields of visual objects around the viewpoint. This paper presents Pano, a 360{\deg} video streaming system that leverages the 360{\deg} video-specific factors. We make three contributions. (1) We build a new quality model for 360{\deg} videos that captures the impact of the 360{\deg} video-specific factors. (2) Pano proposes a variable-sized tiling scheme in order to strike a balance between the perceived quality and video encoding efficiency. (3) Pano proposes a new qualityadaptation logic that maximizes 360{\deg} video user-perceived quality and is readily deployable. Our evaluation (based on user study and trace analysis) shows that compared with state-of-the-art techniques, Pano can save 41-46% bandwidth without any drop in the perceived quality, or it can raise the perceived quality (user rating) by 25%-142% without using more bandwidth. | computer science |
We investigate the size scaling of the entanglement entropy (EE) in nonequilibrium steady states (NESSs) of a one-dimensional open quantum system with a random potential. It models a mesoscopic conductor, composed of a long quantum wire (QWR) with impurities and two electron reservoirs at zero temperature. The EE at equilibrium obeys the logarithmic law. However, in NESSs far from equilibrium the EE grows anomalously fast, obeying the `quasi volume law,' although the conductor is driven by the zero-temperature reservoirs. This anomalous behavior arises from both the far from equilibrium condition and multiple scatterings due to impurities. | quantum physics |
The potentially realizable beam power at the Fermilab long-baseline neutrino program has motivated a reinvigorated design and optimization effort for a rapid-cycling synchrotron (RCS) intensity upgrade of the Fermilab proton complex. We examine areas of technological development with the potential for high-impact on the Fermilab RCS design - low-loss slip-stacking, advanced neutrino-target R\&D, laser-stripping H$^{-}$ injection, fast-ramping super-ferric magnets, nonlinear integrable optics, electron lens devices, and next-generation halo monitors. A brief overview is given on the Fermilab Accelerator Science \& Technology (FAST) facility, where the latter three technologies will undergo comprehensive beam tests. | physics |
We study the relation between lack of Information Backflow and completely positive divisibility (CP divisibility) for non-invertible qubit dynamical maps. Recently, these two concepts were shown to be fully equivalent for the so called image non-increasing dynamical maps. Here we show that this equivalence is universal for any qubit dynamical map. A key ingredient in our proof is the observation that there does not exist CPTP projector onto a 3-dimensional subspace spanned by qubit density operators. Our analysis is illustrated by several examples of qubit evolution including also dynamical maps which are not image non-increasing. | quantum physics |
We posit the existence of the Marshland within string theory. This region is the boundary between the landscape of consistent low-energy limits of quantum gravity, and the swampland of theories that cannot be embedded within string theory because they violate certain trendy and obviously uncontroversial conjectures. The Marshland is probably fractal, and we show some pretty pictures of fractals that will be useful in talks. We further show that the Marshland contains theories with a large number of light axions, allowing us to cite lots of our own papers. We show that the Marshland makes up most of the volume of the landscape, and admits a novel, weakly broken $\mathbb{Z}_2$ Marshymmetry that we find strong evidence for by considering a carefully crafted example. | high energy physics theory |
We observe the actions of a $K$ sub-sample of $N$ individuals up to time $t$ for some large $K<N$. We model the relationships of individuals by i.i.d. Bernoulli($p$)-random variables, where $p\in (0,1]$ is an unknown parameter. The rate of action of each individual depends on some unknown parameter $\mu> 0$ and on the sum of some function $\phi$ of the ages of the actions of the individuals which influence him. The function $\phi$ is unknown but we assume it rapidly decays. The aim of this paper is to estimate the parameter $p$ asymptotically as $N\to \infty$, $K\to \infty$, and $t\to \infty$. Let $m_t$ be the average number of actions per individual up to time $t$. In the subcritical case, where $m_t$ increases linearly, we build an estimator of $p$ with the rate of convergence $\frac{1}{\sqrt{K}}+\frac{N}{m_t\sqrt{K}}+\frac{N}{K\sqrt{m_t}}$. In the supercritical case, where $m_{t}$ increases exponentially fast, we build an estimator of $p$ with the rate of convergence $\frac{1}{\sqrt{K}}+\frac{N}{m_{t}\sqrt{K}}$. | mathematics |
Balancing the model complexity and the representation capability towards the process to be captured remains one of the main challenges in nonlinear system identification. One possibility to reduce model complexity is to impose structure on the model representation. To this end, this work considers the linear fractional representation framework. In a linear fractional representation the linear dynamics and the system nonlinearities are modeled by two separate blocks that are interconnected with one another. This results in a structured, yet flexible model structure. Estimating such a model directly from input-output data is not a trivial task as the involved optimization is nonlinear in nature. This paper proposes an initialization scheme for the model parameters based on the best linear approximation of the system and shows that this approach results in high quality models on a set of benchmark data sets. | electrical engineering and systems science |
In the holographic model of Dirac semimetals being the Einstein-Maxwell scalar gravity with the auxiliary $U(1)$-gauge field, coupled to the ordinary Maxwell one by {\it kinetic mixing } term, the black brane response to the electric fields and temperature gradient has been elaborated. Using the foliation by hypersurfaces of constant radial coordinate we derive the exact form of the Hamiltonian and equations of motion in the considered phase space. Examination of the Hamiltonian constraints enables us, to the leading order expansion of the linearised perturbations at the black brane event horizon, to derive Stokes equations for incompressible doubly charged fluid. Solving the aforementioned equations, one arrives at the DC conductivities for the holographic Dirac semimetals. | high energy physics theory |
Neural prosthetics are typically situated in an aggressive, biochemical environment that requires materials with superior stability and performance. These probes have dual functionalities of recording and stimulation. The material stability is defined by the ability of these probes to withstand the operating conditions throughout billions of cycles of electrical modulations. On the other hand, performance is measured by the electrochemical response of the microelectrode materials. In this paper, microelectrodes made of two material systems; namely, platinum and glassy carbon thin-films, supported on a flexible substrate are fabricated and investigated for the correlation between process parameters and the electrochemical efficacy of the neural interfaces. The resulting neural electrodes were used to investigate the interrelation between process parameters, surface morphology and topography of platinum and glassy carbon films using scanning electron, and atomic force microscopies. The results show that changes in surface topography and the rate of corrosion are relative to variations in the process parameters. Furthermore, the results indicate a general trend between surface roughness and corrosion rate, in which the increase or decrease of the former corresponds to a similar change in the latter. | physics |
We determine the non-perturbative corrections to the gauge coupling constant and the topological charge in the Yang Mills theory. The method makes no explicit use of instanton calculations but instead relies on boundary properties of the quantum partition function. The approach may offer important clues regarding the behavior of the coupling constant and the theta angle for other gauge theories like QCD and supersymmetric QCD. | high energy physics phenomenology |
Based on ab initio relativistic ${\mathbf k}\cdot{\mathbf p}$ theory, we derive an effective two-band model for surface states of three-dimensional topological insulators up to seventh order in $\mathbf{k}$. It provides a comprehensive description of the surface spin structure characterized by a non-orthogonality between momentum and spin. We show that the oscillation of the non-orthogonality with the polar angle of $\mathbf{k}$ with a $\pi/3$ periodicity can be seen as due to effective six-fold symmetric spin-orbit magnetic fields with a quintuple and septuple winding of the field vectors per single rotation of $\mathbf{k}$. Owing to the dominant effect of the classical Rashba field, there remains a single-winding helical spin structure but with a periodic few-degree deviation from the orthogonal locking between momentum and spin. | condensed matter |
In a recent paper, Balthazar, Rodriguez and Yin found some remarkable agreement between the results of c=1 matrix model and D-instanton corrections in two dimensional string theory. Their analysis left undetermined two constants in the string theory computation which had to be fixed by comparing the results with the matrix model results. One of these constants is affected by possible renormalization of the D-instanton action that needs to be computed separately. In this paper we fix the other constant by reformulating the world-sheet analysis in the language of string field theory. | high energy physics theory |
The friction force on a test particle traveling through a plasma that is both strongly coupled and strongly magnetized is studied using molecular dynamics simulations. In addition to the usual stopping power component aligned antiparallel to the velocity, a transverse component that is perpendicular to both the velocity and Lorentz force is observed. This component, which was recently discovered in weakly coupled plasmas, is found to increase in both absolute and relative magnitude in the strongly coupled regime. Strong coupling is also observed to induce a third component of the friction force in the direction of the Lorentz force. These first-principles simulations reveal novel physics associated with collisions in strongly coupled, strongly magnetized, plasmas that are not predicted by existing kinetic theories. The effect is expected to influence macroscopic transport in a number of laboratory experiments and astrophysical plasmas. | physics |
Antenna arrays have many applications in direction-of-arrival (DOA) estimation. Sparse arrays such as nested arrays, super nested arrays, and coprime arrays have large degrees of freedom (DOFs). They can estimate large number of sources greater than the number of elements. They also have closed form expressions for antenna locations and the achievable DOFs. The multi-level prime array (MLPA) uses multiple uniform linear subarrays where the number of elements in the subarrays are pairwise coprime integers. The array achieves large DOFs and it has closed form expressions for the antenna locations and the required aperture size. For a given number of subarrays and total number of elements, there are different design alternatives. This paper finds the optimum number of elements within each subarray and the optimized ordered inter-element spacing. In almost all cases, we have found that a unique configuration jointly realizes the maximum number of unique lags and the maximum number of consecutive lags. | electrical engineering and systems science |
Line intensity maps (LIMs) are in principle sensitive to a large amount of information about faint, distant galaxies which are invisible to conventional surveys. However, actually extracting that information from a confused, foreground-contaminated map can be challenging. In this work we present the first application of convolutional neural network (CNN) to directly determine the underlying luminosity function of a LIM, including a treatment of extragalactic foregrounds and instrumental noise. We apply the CNN to simulations of mock Carbon Monoxide (CO) line intensity maps similar to those which will be produced by the currently-active COMAP experiment. We evaluate the trained CNN on a number of noise scenarios in order to determine how robust the network predictions are for application to realistic data. We find that, in the ideal case where the mock data capture all of the features of the real data, the CNN performs comparably to or better than conventional analyses. However, the network's accuracy degrades considerably when tested on signals and systematics outside of those it was trained on. For both intensity mapping and cosmology as a whole, this motivates a broad-based study of whether simulated data can ever be generated with sufficient detail to realize the enormous potential of machine learning methods. | astrophysics |
We present enhancements to SDPB, an open source, parallelized, arbitrary precision semidefinite program solver designed for the conformal bootstrap. The main enhancement is significantly improved performance and scalability using the Elemental library and MPI. The result is a new version of SDPB that runs on multiple nodes with hundreds of cores with excellent scaling, making it practical to solve larger problems. We demonstrate performance on a moderate-size problem in the 3d Ising CFT and a much larger problem in the $O(2)$ Model. | high energy physics theory |
We propose an importance sampling (IS)-based transport map Hamiltonian Monte Carlo procedure for performing full Bayesian analysis in general nonlinear high-dimensional hierarchical models. Using IS techniques to construct a transport map, the proposed method transforms the typically highly challenging target distribution of a hierarchical model into a target which is easily sampled using standard Hamiltonian Monte Carlo. Conventional applications of high-dimensional IS, where infinite variance of IS weights can be a serious problem, require computationally costly high-fidelity IS distributions. An appealing property of our method is that the IS distributions employed can be of rather low fidelity, making it computationally cheap. We illustrate our algorithm in applications to challenging dynamic state-space models, where it exhibits very high simulation efficiency compared to relevant benchmarks, even for variants of the proposed method implemented using a few dozen lines of code in the Stan statistical software. | statistics |
This survey contains statistics on elections in Russia published in different places and available online. This data is discussed from the viewpoint of statistical model selection. The current version is updated including the materials up to July, 2020 voting on constitutional changes, Belarus 2020 elections and papers that appeared in 2020; most of the data are not consistent with the assumption of fair elections. | statistics |
Solar flares emanate from solar active regions hosting complex and strong bipolar magnetic fluxes. Estimating the probability of an active region to flare and defining reliable precursors of intense flares is an extremely challenging task in the space weather field. In this work, we focus on two metrics as flare precursors, the unsigned flux R, tested on MDI/SOHO data and one of the most used parameters for flare forecasting applications, and a novel topological parameter D representing the complexity of a solar active region. More in detail, we propose an algorithm for the computation of the R value which exploits the higher spatial resolution of HMI maps. This algorithm leads to a differently computed R value, whose functionality is tested on a set of cycle 24th solar flares. Furthermore, we introduce a topological parameter based on the automatic recognition of magnetic polarity-inversion lines in identified active regions, and able to evaluate its magnetic topological complexity. We use both a heuristic approach and a supervised machine learning method to validate the effectiveness of these two descriptors to predict the occurrence of X- or M- class flares in a given solar active region during the following 24 hours period. Our feature ranking analysis shows that both parameters play a significant role in prediction performances. Moreover, the analysis demonstrates that the new topological parameter D is the only one, among 173 overall predictors, which is always present for all test subsets and is systematically ranked within the top-ten positions in all tests concerning the computation of the weighs with which each predictor impacts the flare forecasting. | astrophysics |
In this paper we establish asymptotics (as the size of the graph grows to infinity) for the expected number of cliques in the Chung--Lu inhomogeneous random graph model in which vertices are assigned independent weights which have tail probabilities $h^{1-\alpha}l(h)$, where $\alpha>2$ and $l$ is a slowly varying function. Each pair of vertices is connected by an edge with a probability proportional to the product of the weights of those vertices. We present a complete set of asymptotics for all clique sizes and for all non-integer $\alpha > 2$. We also explain why the case of an integer $\alpha$ is different, and present partial results for the asymptotics in that case. | mathematics |
Ultra-fast femtosecond (fs) lasers provide a unique technological opportunity to precisely and efficiently micromachine materials with minimal thermal damage owing to the reduced heat transfer into the bulk of the work material offered by short pulse duration, high laser intensity and focused optical energy delivered on a timescale shorter than the rate of thermal diffusion into the surrounding area of a beam foci. There is an increasing demand to further develop the fs machining technology to improve the machining quality, minimize the total machining time and increase the flexibility of machining complex patterns on diamond. This article offers an overview of recent research findings on the application of fs laser technology to micromachine diamond. The laser technology to precisely micromachine diamond is discussed and detailed, with a focus on the use of fs laser irradiation systems and their characteristics, laser interaction with various types of diamonds, processing and the subsequent post-processing of the irradiated samples and, appropriate sample characterisation methods. Finally, the current and emerging application areas are discussed, and the challenges and the future research prospects in the fs laser micromachining field are also identified. | condensed matter |
In the present work we study the implications at the future $e^+e^-$ colliders of the modified interaction vertices $WWH$, $WWHH$, $HHH$ and $HHHH$ within the context of the non-linear effective field theory given by the Electroweak Chiral Lagrangian. These vertices are given by four parameters, $a$, $b$, $\kappa_3$ and $\kappa_4$, respectively, that are independent and without any constraint from symmetry considerations in this non-linear effective Lagrangian context, given the fact the Higgs field is a singlet. This is in contrast to the Standard Model, where the vertices are related by $V_{WWH}^{\rm SM}=v V_{WWHH}^{\rm SM}$ and $V_{HHH}^{\rm SM}=v V_{HHHH}^{\rm SM}$, with $v=246$ GeV. We investigate the implications of the absence of these relations in the Electroweak Chiral Lagrangian case. We explore the sensitivity to these Higgs anomalous couplings in the two main channels at these colliders: double and triple Higgs production (plus neutrinos). Concretely, we study the access to $a$ and $b$ in $e^+e^- \to HH \nu \bar{\nu}$ and the access to $\kappa_3$ and $\kappa_4$ in $e^+e^- \to HHH \nu \bar{\nu}$. Our study of the beyond the Standard Model couplings via triple Higgs boson production at $e^+e^-$ colliders is novel and shows for the first time the possible accessibility to the quartic Higgs self-coupling. | high energy physics phenomenology |
The \emph{matching book embedding} of a graph $G$ is to arrange its vertices on the spine, and draw its edges into the pages so that the edges on every page do not intersect each other and the maximum degree of vertices on every page is one. The \emph{matching book thickness} is the minimum number of pages in which the graph $G$ can be matching embedded. In this paper, the matching book thickness of Halin graphs is determined. | mathematics |
This paper investigates the transient stability of power systems co-dominated by different types of grid-forming (GFM) devices. Synchronous generators (SGs and VSGs) and droop-controlled inverters are typical GFM devices in modern power systems. SGs/VSGs are able to provide inertia while droop-controlled inverters are generally inertia-less. The transient stability of power systems dominated by homogeneous GFM devices has been extensively studied. Regarding the hybrid system jointly dominated by heterogeneous GFM devices, the transient stability is rarely reported. This paper aims to fill this gap. It is found that the synchronization behavior of the hybrid system can be described by a second-order motion equation, resembling the swing equation of SGs. More importantly, two significant differences from conventional power systems are discovered. The first is that the droop control dramatically enhances the damping effect, greatly affecting the transient stability region. The second is that the frequency state variable exhibits an abrupt change at the moment of fault disturbances, thus impacting the post-fault initial-state location and stability assessment. The underlying mechanism behind the two new characteristics is clarified and the impact on the transient stability is analyzed and verified in this paper. The findings provide new insights into the stability of power systems hosting heterogeneous devices. | electrical engineering and systems science |
Quantum state preparation is an important class of quantum algorithms that is employed as a black-box subroutine in many algorithms, or used by itself to generate arbitrary probability distributions. We present a novel state preparation method that utilizes less quantum computing resource than the existing methods. Two variants of the algorithm with different emphases are introduced. One variant uses fewer qubits and no controlled gates, while the other variant potentially requires fewer gates overall. A general analysis is given to estimate the number of qubits necessary to achieve a desired precision in the amplitudes of the computational basis states. The validity of the algorithm is demonstrated using a prototypical problem of generating Ising model spin configurations according to its Boltzmann distribution. | quantum physics |
The basic Susceptible-Infected-Recovered (SIR) model is extended to include effects of progressive social awareness, lockdowns and anthropogenic migration. It is found that social awareness can effectively contain the spread by lowering the basic reproduction rate $R_0$. Interestingly, the awareness is found to be more effective in a society which can adopt the awareness faster compared to the one having a slower response. The paper also separates the mortality fraction from the clinically recovered fraction and attempts to model the outcome of lockdowns, in absence and presence of social awareness. It is seen that staggered exits from lockdowns are not only economically beneficial but also helps to curb the infection spread. Moreover, a staggered exit strategy with progressive social awareness is found to be the most efficient intervention. The paper also explores the effects of anthropogenic migration on the dynamics of the epidemic in a two-zone scenario. The calculations yield dissimilar evolution of different fractions in different zones. Such models can be convenient to strategize the division of a large zone into smaller sub-zones for a disproportionate imposition of lockdown, or, an exit from one. Calculations are done with parameters consistent with the SARS-COV-2 pathogen in the Indian context. | physics |
We present an analysis of spectropolarimetric observations of the low-mass weak-line T Tauri stars TWA 25 and TWA 7. The large-scale surface magnetic fields have been reconstructed for both stars using the technique of Zeeman Doppler imaging. Our surface maps reveal predominantly toroidal and non-axisymmetric fields for both stars. These maps reinforce the wide range of surface magnetic fields that have been recovered, particularly in pre-main sequence stars that have stopped accreting from the (now depleted) central regions of their discs. We reconstruct the large scale surface brightness distributions for both stars, and use these reconstructions to filter out the activity-induced radial velocity jitter, reducing the RMS of the radial velocity variations from 495 m/s to 32 m/s for TWA 25, and from 127 m/s to 36 m/s for TWA 7, ruling out the presence of close-in giant planets for both stars. The TWA 7 radial velocities provide an example of a case where the activity-induced radial velocity variations mimic a Keplerian signal that is uncorrelated with the spectral activity indices. This shows the usefulness of longitudinal magnetic field measurements in identifying activity-induced radial velocity variations. | astrophysics |
Symmetry protected topological (SPT) states have boundary 't Hooft anomalies that obstruct an effective boundary theory realized in its own dimension with UV completion and an on-site $G$-symmetry. In this work, yet we show that a certain anomalous non-on-site $G$ symmetry along the boundary becomes on-site when viewed as an extended $H$ symmetry, via a suitable group extension $1\to K\to H\to G\to1$. Namely, a non-perturbative global (gauge/gravitational) anomaly in $G$ becomes anomaly-free in $H$. This guides us to construct exactly soluble lattice path integral and Hamiltonian of symmetric gapped boundaries, always existent for any SPT state in any spacetime dimension $d \geq 2$ of any finite symmetry group, including on-site unitary and anti-unitary time-reversal symmetries. The resulting symmetric gapped boundary can be described either by an $H$-symmetry extended boundary of bulk $d \geq 2$, or more naturally by a topological emergent $K$-gauge theory with a global symmetry $G$ on a 3+1D bulk or above. The excitations on such a symmetric topologically ordered boundary can carry fractional quantum numbers of the symmetry $G$, described by representations of $H$. (Apply our approach to a 1+1D boundary of 2+1D bulk, we find that a deconfined gauge boundary indeed has spontaneous symmetry breaking with long-range order. The deconfined symmetry-breaking phase crosses over smoothly to a confined phase without a phase transition.) In contrast to known gapped interfaces obtained via symmetry breaking (either global symmetry breaking or Anderson-Higgs mechanism for gauge theory), our approach is based on symmetry extension. More generally, applying our approach to SPT, topologically ordered gauge theories and symmetry enriched topologically ordered (SET) states, leads to generic boundaries/interfaces constructed with a mixture of symmetry breaking, symmetry extension, and dynamical gauging. | condensed matter |
A double-tip scanning tunneling microscope with nanometer scale tip separation has the ability to access the single electron Green's function in real and momentum space based on second order tunneling processes. Experimental realization of such measurements has been limited to quasi-one-dimensional systems due to the extremely small signal size. Here we propose an alternative approach to obtain such information by exploiting the current-current correlations from the individual tips, and present a theoretical formalism to describe it. To assess the feasibility of our approach we make a numerical estimate for a $\sim$ 25 nm Pb nanoisland and show that the wavefunction in fact extends from tip-to-tip and the signal depends less strongly on increased tip separation in the diffusive regime than the one in alternative approaches relying on tip-to-tip conductance. | condensed matter |
One of the conspicuous features of real slices of bicritical rational maps is the existence of Tricorn-type hyperbolic components. Such a hyperbolic component is called invisible if the non-bifurcating sub-arcs on its boundary do not intersect the closure of any other hyperbolic component. Numerical evidence suggests an abundance of invisible Tricorn-type components in real slices of bicritical rational maps. In this paper, we study two different families of real bicritical maps and characterize invisible Tricorn-type components in terms of suitable topological properties in the dynamical planes of the representative maps. We use this criterion to prove the existence of infinitely many invisible Tricorn-type components in the corresponding parameter spaces. Although we write the proofs for two specific families, our methods apply to generic families of real bicritical maps. | mathematics |
In the framework of the QCD shock-wave approach, we review our results on the description of diffractive production of various final states (jets, meson) at next-to-leading order. This is applied to exclusive diffractive dijet electroproduction at HERA. | high energy physics phenomenology |
The AGN bolometric correction is a key element to understand BH demographics and compute accurate BH accretion histories from AGN luminosities. However, current estimates still differ from each other by up to a factor of two to three, and rely on extrapolations at the lowest and highest luminosities. Here we revisit this fundamental issue presenting general hard X-ray ($K_{X}$) and optical ($K_{O}$) bolometric corrections, computed combining several AGN samples spanning the widest (about 7 dex) luminosity range ever used for this kind of studies. We analysed a total of $\sim 1000$ type 1 and type 2 AGN for which a dedicated SED-fitting has been carried out. We provide a bolometric correction separately for type 1 and type 2 AGN; the two bolometric corrections results to be in agreement in the overlapping luminosity range and therefore, for the first time, a universal bolometric correction for the whole AGN sample (both type 1 and type 2) has been computed. We found that $K_{X}$ is fairly constant at $log(L_{BOL}/L_{\odot}) < 11$, while it increases up to about one order of magnitude at $log(L_{BOL}/L_{\odot}) \sim 14.5$. A similar increasing trend has been observed when its dependence on either the Eddington ratio or the BH mass is considered, while no dependence on redshift up to $z\sim3.5$ has been found. On the contrary, the optical bolometric correction appears to be fairly constant (i.e. $K_{O} \sim 5$) whatever is the independent variable. We also verified that our bolometric corrections correctly predict the AGN bolometric luminosity functions. According to this analysis, our bolometric corrections can be applied to the whole AGN population in a wide range of luminosity and redshift. | astrophysics |
Voice-controlled house-hold devices, like Amazon Echo or Google Home, face the problem of performing speech recognition of device-directed speech in the presence of interfering background speech, i.e., background noise and interfering speech from another person or media device in proximity need to be ignored. We propose two end-to-end models to tackle this problem with information extracted from the "anchored segment". The anchored segment refers to the wake-up word part of an audio stream, which contains valuable speaker information that can be used to suppress interfering speech and background noise. The first method is called "Multi-source Attention" where the attention mechanism takes both the speaker information and decoder state into consideration. The second method directly learns a frame-level mask on top of the encoder output. We also explore a multi-task learning setup where we use the ground truth of the mask to guide the learner. Given that audio data with interfering speech is rare in our training data set, we also propose a way to synthesize "noisy" speech from "clean" speech to mitigate the mismatch between training and test data. Our proposed methods show up to 15% relative reduction in WER for Amazon Alexa live data with interfering background speech without significantly degrading on clean speech. | computer science |
A typical problem in air pollution epidemiology is exposure assessment for individuals for which health data are available. Due to the sparsity of monitoring sites and the limited temporal frequency with which measurements of air pollutants concentrations are collected (for most pollutants, once every 3 or 6 days), epidemiologists have been moving away from characterizing ambient air pollution exposure solely using measurements. In the last few years, substantial research efforts have been placed in developing statistical methods or machine learning techniques to generate estimates of air pollution at finer spatial and temporal scales (daily, usually) with complete coverage. Some of these methods include: geostatistical techniques, such as kriging; spatial statistical models that use the information contained in air quality model outputs (statistical downscaling models); linear regression modeling approaches that leverage the information in GIS covariates (land use regression); or machine learning methods that mine the information contained in relevant variables (neural network and deep learning approaches). Although some of these exposure modeling approaches have been used in several air pollution epidemiological studies, it is not clear how much the predicted exposures generated by these methods differ, and which method generates more reliable estimates. In this paper, we aim to address this gap by evaluating a variety of exposure modeling approaches, comparing their predictive performance and computational difficulty. Using PM$_{2.5}$ in year 2011 over the continental U.S. as case study, we examine the methods' performances across seasons, rural vs urban settings, and levels of PM$_{2.5}$ concentrations (low, medium, high). | statistics |
When the base ring is not a field, power reductivity of a group scheme is a basic notion, intimately tied with finite generation of subrings of invariants. Geometric reductivity is weaker and less pertinent in this context. We give a survey of these properties and their connections. | mathematics |
SemEval-2020 Task 12 was OffenseEval: Multilingual Offensive Language Identification in Social Media (Zampieri et al., 2020). The task was subdivided into multiple languages and datasets were provided for each one. The task was further divided into three sub-tasks: offensive language identification, automatic categorization of offense types, and offense target identification. I have participated in the task-C, that is, offense target identification. For preparing the proposed system, I have made use of Deep Learning networks like LSTMs and frameworks like Keras which combine the bag of words model with automatically generated sequence based features and manually extracted features from the given dataset. My system on training on 25% of the whole dataset achieves macro averaged f1 score of 47.763%. | computer science |
Explosive growth in spatio-temporal data and its wide range of applications have attracted increasing interests of researchers in the statistical and machine learning fields. The spatio-temporal regression problem is of paramount importance from both the methodology development and real-world application perspectives. Given the observed spatially encoded time series covariates and real-valued response data samples, the goal of spatio-temporal regression is to leverage the temporal and spatial dependencies to build a mapping from covariates to response with minimized prediction error. Prior arts, including the convolutional Long Short-Term Memory (CovLSTM) and variations of the functional linear models, cannot learn the spatio-temporal information in a simple and efficient format for proper model building. In this work, we propose two novel extensions of the Functional Neural Network (FNN), a temporal regression model whose effectiveness and superior performance over alternative sequential models have been proven by many researchers. The effectiveness of the proposed spatio-temporal FNNs in handling varying spatial correlations is demonstrated in comprehensive simulation studies. The proposed models are then deployed to solve a practical and challenging precipitation prediction problem in the meteorology field. | computer science |
Sea ice, or frozen ocean water, freezes and melts every year in the Arctic. Forecasts of where sea ice will be located weeks to months in advance have become more important as the amount of sea ice declines due to climate change, for maritime planning and other uses. Typical sea ice forecasts are made with ensemble models, physics-based models of sea ice and the surrounding ocean and atmosphere. This paper introduces Mixture Contour Forecasting, a method to forecast sea ice probabilistically using a mixture of two distributions, one based on post-processed output from ensembles and the other on observed sea ice patterns in recent years. At short lead times, these forecasts are better calibrated than unadjusted dynamic ensemble forecasts and other statistical reference forecasts. To produce these forecasts, a statistical technique is introduced that directly models the sea ice edge contour, the boundary around the region that is ice-covered. Mixture Contour Forecasting and reference methods are evaluated for monthly sea ice forecasts for 2008-2016 at lead times ranging from 0.5-6.5 months using one of the European Centre for Medium-Range Weather Forecasts ensembles. | statistics |
Precision measurements of cosmic microwave background (CMB) polarization require extreme control of instrumental systematics. In a companion paper we have presented cosmological constraints from observations with the BICEP2 and Keck Array experiments up to and including the 2015 observing season (BK15), resulting in the deepest CMB polarization maps to date and a statistical sensitivity to the tensor-to-scalar ratio of $\sigma(r) = 0.020$. In this work we characterize the beams and constrain potential systematic contamination from main beam shape mismatch at the three BK15 frequencies (95, 150, and 220 GHz). Far-field maps of 7,360 distinct beam patterns taken from 2010-2015 are used to measure differential beam parameters and predict the contribution of temperature-to-polarization leakage to the BK15 B-mode maps. In the multifrequency, multicomponent likelihood analysis that uses BK15, Planck, and WMAP maps to separate sky components, we find that adding this predicted leakage to simulations induces a bias of $\Delta r = 0.0027 \pm 0.0019$. Future results using higher-quality beam maps and improved techniques to detect such leakage in CMB data will substantially reduce this uncertainty, enabling the levels of systematics control needed for BICEP Array and other experiments that plan to definitively probe large-field inflation. | astrophysics |
We report here the discovery of NGC 7793 ULX-4, a new transient ultraluminous X-ray source (ULX) in NGC 7793, a spiral galaxy already well known for harbouring several ULXs. This new source underwent an outburst in 2012, when it was detected by \textit{XMM-Newton} and the \textit{Swift} X-ray telescope. The outburst reached a peak luminosity of 3.4$\times 10^{39}$ erg\ s$^{-1}$ and lasted for about 8 months, after which the source went below a luminosity of $10^{37}$ erg\ s$^{-1}$; previous \textit{Chandra} observations constrain the low-state luminosity below $\sim$ 2$\times 10^{36}$ erg\ s$^{-1}$, implying a variability of at least a factor 1000. We propose four possible optical counterparts, found in archival HST observations of the galaxy. A pulsation in the \textit{XMM-Newton} signal was found at 2.52 Hz, with a significance of $\sim3.4\,\sigma$, and an associated spin-up of $\dot{f} = 3.5\times10^{-8}$ Hz.s$^{-1}$. NGC 7793 is therefore the first galaxy to host more than one pulsating ULX. | astrophysics |
A star coming too close to a supermassive black hole gets disrupted by the tidal force of the compact object in a tidal disruption event, or TDE. Following this encounter, the debris evolves into an elongated stream, half of which coming back to pericenter. Relativistic apsidal precession then leads to a self-crossing shock that initiates the formation of an accretion disc. We perform the first simulation of this process considering a realistic stellar trajectory and black hole mass, which has so far eluded investigations for computational reasons. This numerical issue is alleviated by using as initial conditions the outflow launched by the self-crossing shock according the local simulation of Lu & Bonnerot (2019). We find that the gas leaving the intersection point experiences numerous secondary shocks that result in the rapid formation of a thick and marginally-bound disc. The mass distribution features two overdensities identified as spiral shocks that drive slow gas inflow along the mid-plane. Inward motion primarily takes place along the funnels of the newly-formed torus, from which a fraction of the matter can get accreted. Further out, the gas moves outward forming an extended envelope completely surrounding the accretion flow. Secondary shocks heat the debris at a rate of a few times $10^{44} \, \rm erg \, s^{-1}$ with a large fraction likely participating to the bolometric luminosity. These results pave the way towards a complete understanding of the early radiation from TDEs that progressively becomes accessible from observations. | astrophysics |
X-ray observations provide a potentially powerful tool to study starburst feedback. The analysis and interpretation of such observations remain challenging, however, due to various complications, including the non-isothermality of the diffuse hot plasma and the inhomogeneity of the foreground absorption. We here illustrate such complications and a way to mitigate their effects by presenting an X-ray spectroscopy of the 30 Doradus nebula in the Large Magellanic Clouds, based on a 100 ks Suzaku observation. We measure the thermal and chemical properties of the hot plasma and quantitatively confront them with the feedback expected from embedded massive stars. We find that our spatially resolved measurements can be well reproduced by a global modeling of the nebula with a log-normal temperature distribution of the plasma emission measure and a log-normal foreground absorption distribution. The metal abundances and total mass of the plasma are consistent with the chemically enriched mass ejection expected from the central OB association and a ~55% mass-loading from the ambient medium. The total thermal energy of the plasma is smaller than what is expected from a simple superbubble model, demonstrating that important channels of energy loss are not accounted for. Our analysis indeed shows tentative evidence for a diffuse non-thermal X-ray component, indicating that cosmic-ray acceleration needs to be considered in such a young starburst region. Finally, we suggest that the log-normal modeling may be suitable for the X-ray spectral analysis of other giant HII regions, especially when spatially resolved spectroscopy is not practical. | astrophysics |
We propose a neurobiologically inspired visual simultaneous localization and mapping (SLAM) system based on direction sparse method to real-time build cognitive maps of large-scale environments from a moving stereo camera. The core SLAM system mainly comprises a Bayesian attractor network, which utilizes neural responses of head direction (HD) cells in the hippocampus and grid cells in the medial entorhinal cortex (MEC) to represent the head direction and the position of the robot in the environment, respectively. Direct sparse method is employed to accurately and robustly estimate velocity information from a stereo camera. Input rotational and translational velocities are integrated by the HD cell and grid cell networks, respectively. We demonstrated our neurobiologically inspired stereo visual SLAM system on the KITTI odometry benchmark datasets. Our proposed SLAM system is robust to real-time build a coherent semi-metric topological map from a stereo camera. Qualitative evaluation on cognitive maps shows that our proposed neurobiologically inspired stereo visual SLAM system outperforms our previous brain-inspired algorithms and the neurobiologically inspired monocular visual SLAM system both in terms of tracking accuracy and robustness, which is closer to the traditional state-of-the-art one. | computer science |
Kinematic dynamo in incompressible isotropic turbulent flows with high magnetic Prandtl number is considered. The approach interpreting an arbitrary magnetic field distribution as a superposition of localized perturbations (blobs) is proposed. We derive a relation between stochastic properties of a blob and a stochastically homogenous distribution of magnetic field advected by the same stochastic flow. This relation allows to investigate the evolution of a localized blob at late stage when its size exceeds the viscous scale. It is shown that in 3-dimansional flows, the average magnetic field of the blob increases exponentially in the inertial range of turbulence, as opposed to the late-Batchelor stage when it decreases. Our approach reveals the mechanism of dynamo generation in the inertial range both for blobs and homogenous contributions. It explains the absence of dynamo in the two-dimensional case and its efficiency in three dimensions. We propose the way to observe the mechanism in numerical simulations. | physics |
We study the position-dependent power spectrum and the integrated bispectrum statistic for 2D cosmological fields on the sphere (integrated angular bispectrum). First, we derive a useful, $m$-independent, formula for the full-sky integrated angular bispectrum, based on the construction of azimuthally symmetric patches. We then implement a pipeline for integrated angular bispectrum estimation, including a mean-field correction to account for spurious isotropy-breaking effects in realistic conditions (e.g., inhomogenous noise, sky masking). Finally, we show examples of applications of this estimator to CMB analysis, both using simulations and actual Planck data. Such examples include $f_\mathrm{NL}$ estimation, analyses of non-Gaussianity from secondary anisotropies (ISW-lensing and ISW-tSZ-tSZ bispectra) and studies of non-Gaussian signatures from foreground contamination. | astrophysics |
Observations of extrasolar planets were not projected to be a significant part of the Spitzer Space Telescope's mission when it was conceived and designed. Nevertheless, Spitzer was the first facility to detect thermal emission from a hot Jupiter, and the range of Spitzer's exoplanetary investigations grew to encompass transiting planets, microlensing, brown dwarfs, and direct imaging searches and astrometry. Spitzer used phase curves to measure the longitudinal distribution of heat as well as time-dependent heating on hot Jupiters. Spitzer's secondary eclipse observations strongly constrained the dayside thermal emission spectra and corresponding atmospheric compositions of hot Jupiters, and the timings of eclipses were used for studies of orbital dynamics. Spitzer's sensitivity to carbon-based molecules such as methane and carbon monoxide was key to atmospheric composition studies of transiting exoplanets as well as imaging spectroscopy of brown dwarfs, and complemented Hubble spectroscopy at shorter wavelengths. Spitzer's capability for long continuous observing sequences enabled searches for new transiting planets around cool stars, and helped to define the architectures of planetary systems like TRAPPIST-1. Spitzer measured masses for small planets at large orbital distances using microlensing parallax. Spitzer observations of brown dwarfs probed their temperatures, masses, and weather patterns. Imaging and astrometry from Spitzer was used to discover new planetary mass brown dwarfs and to measure distances and space densities of many others. | astrophysics |
The Van der Pol equation is a paradigmatic model of relaxation oscillations. This remarkable nonlinear phenomenon of self-sustained oscillatory motion underlies important rhythmic processes in nature and electrical engineering. Relaxation oscillations in a real system are usually coupled to environmental noise, which further enriches their dynamics, but makes theoretical analysis of such systems and determination of the equation's parameter values a difficult task. In a companion paper we have proposed an analytic approach to a similar problem for another classical nonlinear model, the bistable Duffing oscillator. Here we extend our techniques to the case of the Van der Pol equation driven by white noise. We analyze the statistics of solutions and propose a method to estimate parameter values from the oscillator's time series. We use experimental data of active oscillations in a biological system to demonstrate how our method applies to real observations and how it can be generalized for more complex models. | condensed matter |
We discuss the low-energy dynamics of superfluidity with topological order in $(3+1)$ spacetime dimensions. We generalize a topological $BF$ theory by introducing a non-square $K$ matrix, and this generalized $BF$ theory can describe massless Nambu-Goldstone bosons and anyonic statistics between vortices and quasiparticles. We discuss the general structure of discrete and continuous higher-form symmetries in this theory, which can be used to classify quantum phases. We describe how to identify the appearance of topological order in such systems and discuss its relation to a mixed 't Hooft anomaly between discrete higher-form symmetries. We apply this framework to the color-flavor locked phase of dense QCD, which shows anyonic particle-vortex statistics while no topological order appears. An explicit example of superfluidity with topological order is discussed. | high energy physics theory |
In this paper, we investigate a class of nonzero-sum dynamic stochastic games, where players have linear dynamics and quadratic cost functions. The players are coupled in both dynamics and cost through a linear regression (weighted average) as well as a quadratic regression (weighted covariance matrix) of the states and actions, where the linear regression of states is called deep state. We study collaborative and non-collaborative games under three information structures: perfect sharing, deep state sharing, and no sharing for three different types of weights: positive, homogeneous and asymptotically vanishing weights. For perfect and deep state sharing information structures, we propose a transformation-based technique to solve for the best-response equations of players and identify a few sufficient conditions under which a unique subgame perfect Nash equilibrium exists. The equilibrium is linear in the local state and deep state, and the corresponding gains are obtained by solving a novel non-standard Riccati equation (whose dimension is independent of the number of players, thus making the solution scalable). When the information structure is no-sharing and the number of players is asymptotically large, one approximate population-size-dependent equilibrium and one approximate population-size-independent equilibrium (also called sequential weighted mean-field equilibrium) are proposed, and their convergence to the infinite-population limits are established. In addition, the main results are extended to infinite-horizon cost function, and generalized to multiple orthogonal linear regressions and heterogeneous sub-populations. A numerical example is provided to demonstrate the difference between the two proposed approximate equilibria. | mathematics |
In a recent paper~[Nature Catalysis 3, 573 (2020)], Robatjazi {\em et al.} demonstrate hydrodefluorination on Al nanocrystals decorated by Pd islands under illumination and under external heating. They conclude that photocatalysis accomplishes the desired transformation \ce{CH3F + D2 -> CH3D + DF} efficiently and selectively due to "hot" electrons, as evidenced by an illumination-induced reduction of the activation energy. Although some of the problems identified in prior work by the same group have been addressed, scrutiny of the data in~[Nature Catalysis 3, 573 (2020)] raises doubts about both the methodology and the central conclusions. First, we show that the thermal control experiments in~[Nature Catalysis 3, 573 (2020)] do not separate thermal from "hot electron" contributions, and therefore any conclusions drawn from these experiments are invalid. We then show that an improved thermal control implies that the activation energy of the reaction does not change, and that an independent purely thermal calculation (based solely on the sample parameters provided in the original manuscript) explains the measured data perfectly. For the sake of completeness, we also address technical problems in the calibration of the thermal camera, an unjustifiable disqualification of some of the measured data, as well as concerning aspects of the rest of the main results, including the mass spectrometry approach used to investigate the selectivity of the reaction, and claims about the stoichiometry and reaction order. All this shows that the burden of proof for involvement of hot electrons has not been met. | physics |
The recent discovery of borophene, a two-dimensional allotrope of boron, raises many questions about its structure and its chemical and physical properties. Boron has a high chemical affinity to oxygen but little is known about the oxidation behavior of borophene. Here we use first principles calculations to study the phase diagram of free-standing, two-dimensional $\mathrm{B_{1-x}O_x}$ for compositions ranging from $x=0$ to $x=0.6$, which correspond to borophene and $\mathrm{B_2O_3}$ sheets, respectively. Our results indicate that no stable compounds except borophene and $\mathrm{B_2O_3}$ sheets exist. Intermediate compositions are heterogeneous mixtures of borophene and $\mathrm{B_2O_3}$. Other hypothetical crystals such as $\mathrm{B_2O}$ are unstable and some of them were found to undergo spontaneous disproportionation into borophene and $\mathrm{B_2O_3}$. It is also shown that oxidizing borophene inside the flakes is thermodynamically unfavorable over forming $\mathrm{B_2O_3}$ at the edges. All findings can be rationalized by oxygen's preference of two-fold coordination which is incompatible with higher in-plane coordination numbers preferred by boron. These results agree well with recent experiments and pave the way to understand the process of oxidation of borophene and other two-dimensional materials. | condensed matter |
We present a new framework in which the interactions among quantum fields are constrained by Lorentz-invariant thermalization. Thermalization, which occurs as a natural and inevitable consequence of the interactions among the modes of quantum fields, renders the scattering amplitudes naturally divergence-free at all orders. We present the following calculations as a preliminary test of the new framework. The 1-loop correction to electron's anomalous magnetic moment, calculated using the new framework, is shown to differ from the experimentally measured value by less than 0.06%. The calculation of the Lamb shift yields a result that differs from the experimentally measured value by less than 0.33%. At momentum transfer scales that are one to four orders of magnitude above the electron mass scale, the running of the fine structure constant, calculated in the new framework, is shown to deviate from the previously known results by less than 0.8% (deviating by less than 0.5% at the upper end of the range). At the tree level, the angular distribution of the differential cross-section for Compton scattering predicted by the new framework is shown to be in good agreement with the experimental results of Friedrich and Goldhaber and the well-known Klein-Nishina formula. Finally, the free Maxwell field's contribution to vacuum energy density predicted by the new framework is shown to be approximately three orders of magnitude smaller than the WMAP's latest upper bound for dark energy density in contrast to the divergent contribution predicted by previous results. | physics |
We propose a novel sparse dictionary learning method for planar shapes in the sense of Kendall, namely configurations of landmarks in the plane considered up to similitudes. Our shape dictionary method provides a good trade-off between algorithmic simplicity and faithfulness with respect to the nonlinear geometric structure of Kendall's shape space. Remarkably, it boils down to a classical dictionary learning formulation modified using complex weights. Existing dictionary learning methods extended to nonlinear spaces either map the manifold to a reproducing kernel Hilbert space or to a tangent space. The first approach is unnecessarily heavy in the case of Kendall's shape space and causes the geometrical understanding of shapes to be lost, while the second one induces distortions and theoretical complexity. Our approach does not suffer from these drawbacks. Instead of embedding the shape space into a linear space, we rely on the hyperplane of centered configurations, including pre-shapes from which shapes are defined as rotation orbits. In this linear space, the dictionary atoms are scaled and rotated using complex weights before summation. Furthermore, our formulation is more general than Kendall's original one: it applies to discretely-defined configurations of landmarks as well as continuously-defined interpolating curves. We implemented our algorithm by adapting the method of optimal directions combined to a Cholesky-optimized order recursive matching pursuit. An interesting feature of our shape dictionary is that it produces visually realistic atoms, while guaranteeing reconstruction accuracy. Its efficiency can mostly be attributed to a clear formulation of the framework with complex numbers. We illustrate the strong potential of our approach for the characterization of datasets of shapes up to similitudes and the analysis of patterns in deforming 2D shapes. | electrical engineering and systems science |
We present a general method to derive the appropriate Darmois-Israel junction conditions for gravitational theories with higher-order derivative terms by integrating the bulk equations of motion across the singular hypersurface. In higher derivative theories, the field equations can contain terms which are more singular than the Dirac delta distribution. To handle them appropriately, we formulate a regularization procedure based on representing the delta function as the limit of a sequence of classical functions. This procedure involves imposing suitable constraints on the extrinsic curvature such that the field equations are compatible with the singular source being a delta distribution. As explicit examples of our approach, we demonstrate in detail how to obtain the generalized junction conditions for quadratic gravity, $\mathcal{F}(R)$ theories, a 4D low-energy effective action in string theory and action terms that are Euler densities. Our results are novel, and refine the accuracy of previously claimed results in $\mathcal{F} (R)$ theories and quadratic gravity. In particular, when the coupling constants of quadratic gravity are those for the Gauss-Bonnet case, our junction conditions reduce to the known ones for the latter obtained independently by boundary variation of a surface term in the action. Finally, we briefly discuss a couple of applications to thin-shell wormholes and stellar models. | high energy physics theory |
Traffic Collision Avoidance Systems (TCAS) are safety-critical systems required on most commercial aircrafts in service today. However, TCAS was not designed to account for malicious actors. While in the past it may have been infeasible for an attacker to craft radio signals to mimic TCAS signals, attackers today have access to open-source digital signal processing software, like GNU Radio, and inexpensive software defined radios (SDR) that enable the transmission of spurious TCAS messages. In this paper, methods, both qualitative and quantitative, for analyzing TCAS from an adversarial perspective are presented. To demonstrate the feasibility of inducing near mid-air collisions between current day TCAS-equipped aircraft, an experimental Phantom Aircraft generator is developed using GNU Radio and an SDR against a realistic threat model. | electrical engineering and systems science |
Over the ages, efforts have been made to use composite design to reinforce metals and alloys in order to increase their strength and modulus. On the other hand, nature herself improves the strength, ductility, stiffness and toughness of materials by strengthening them with liquids having zero strength/modulus. Here, emulating nature, efforts have been made to develop a new class of tin based alloy/composite with liquid metal reinforcement (LMM). Based on thermodynamic calculations, a composition has been designed such that on melting and casting it forms a solid metal (tin solid solution) and the eutectic mixture remains in liquid form at room temperature. The composite structure named as LMM shows multifold improvement in hardness, strength, ductility, toughness and wear resistance as compared to conventional solder alloys. A Finite Element Method (FEM) based simulation shows strain distribution in the composite which results in the unique behavior. The LMM also shows a negative coefficient of thermal expansion which is further verified using in-situ microscopy and thermodynamic calculations. | physics |
The conditions of field and voltage for inducing steady state excitations in fully perpendicular magnetic tunnel junctions (pMTJs), adapted for memory applications, were numerically investigated by the resolution of the Landau-Lifshitz-Gilbert equation in the macrospin approach. Both damping-like and the field-like spin transfer torque terms were taken into account in the simulations, as well as the contribution of the second order uniaxial anisotropy term (K2), which has been recently revealed in MgO-based pMTJs. An in-plane applied magnetic field balances the out of plane symmetry of the pMTJ and allows the signal detection. Using this model, we assessed the states of the free layer magnetization as a function of strength of K2 and polar theta_H angle of the applied field (varied from 90 to 60 deg.). There are two stable states, with the magnetization in-plane or out of plane of the layer, and two dynamic states with self-sustained oscillations, called in-plane precession state (IPP) or out of plane precession state (OPP). The IPP mode, with oscillation frequencies up to 7 GHz, appears only for positive voltages if theta_H = 90 deg. However, it shows a more complex distribution when the field is slightly tilted out of plane. The OPP mode is excited only if K2 is considered and reaches a maximum oscillation frequency of 15 GHz. Large areas of dynamic states with high frequencies are obtained for strong values of the field-like torque and K2, when applying a slightly tilted external field toward the out of plane direction. The non-zero temperature does not modify the phase diagrams, but reduces drastically the power spectral density peak amplitudes. | physics |
We prove a Lieb--Thirring inequality for Schr\"odinger operators on the semi-axis with Robin boundary condition at the origin. The result improves on a bound obtained by P. Exner, A. Laptev and M. Usman [Commun. Math. Phys. 362(2), 531--541 (2014)]. The main difference in our proof is that we use the double commutation method in place of the single commutation method. We also establish an improved inequality in the case of a Dirichlet boundary condition. | mathematics |
Preliminary evidence for the occurrence of high-Tc superconductivity in alkali-doped organic materials, such as potassium-doped p-terphenyl (KPT), were recently obtained by magnetic susceptibility measurements and by the opening of a large superconducting gap as measured by ARPES and STM techniques. In this work, KPT samples have been synthesized by a chemical method and characterized by low-temperature Raman scattering and resistivity measurements. Here, we report the occurrence of a resistivity drop of more than 4 orders of magnitude at low temperatures in KPT samples in the form of compressed powder. This fact was interpreted as a possible sign of a broad superconducting transition taking place below 90 K in granular KPT. The granular nature of the KPT system appears to be also related to the 20 K broadening of the resistivity drop around the critical temperature. | condensed matter |
The kinetic processes in nanoparticle-based catalysis are dominated by large fluctuations and spatiotemporal heterogeneities, in particular for diffusion-influenced reactions which are far from equilibrium. Here, we report results from particle-resolved reaction-diffusion simulations of steady-state bimolecular reactions catalyzed on the surface of a single, perfectly spherical nanoparticle. We study various reactant adsorption and diffusion regimes, in particular considering the crowding effects of the reaction products. Our simulations reveal that fluctuations, significant coverage cross-correlations, transient self-poisoning, related domain formation, and excluded-volume effects on the nanoparticle surface lead to a complex kinetic behavior, sensitively tuned by the balance between adsorption affinity, mixed 2D and 3D diffusion, and chemical reaction propensity. The adsorbed products are found to influence the correlations and fluctuations, depending on overall reaction speed, thereby going beyond conventional steric (e.g., Langmuir-like) product inhibition mechanisms. We summarize our findings in a state diagram depicting the nonlinear kinetic regimes by an apparent surface reaction order in dependence of the intrinsic reaction propensity and adsorption strength. Our study using a simple, perfectly spherical, and inert nanocatalyst demonstrates that spatiotemporal heterogeneities are intrinsic to the reaction-diffusion problem and not necessarily caused by any dynamical surface effects from the catalyst (e.g., dynamical surface reconstruction), as often argued. | physics |
The partition function $ p_{[1^c11^d]}(n)$ can be defined using the generating function, \[\sum_{n=0}^{\infty}p_{[1^c{11}^d]}(n)q^n=\prod_{n=1}^{\infty}\dfrac{1}{(1-q^n)^c(1-q^{11 n})^d}.\] In this paper, we prove infinite families of congruences for the partition function $ p_{[1^c11^d]}(n)$ modulo powers of $11$ for any integers $c$ and $d$, which generalizes Atkin and Gordon's congruences for powers of the partition function. The proofs use an explicit basis for the vector space of modular functions of the congruence subgroup $\Gamma_0(11)$. | mathematics |
The use of linguistic typological resources in natural language processing has been steadily gaining more popularity. It has been observed that the use of typological information, often combined with distributed language representations, leads to significantly more powerful models. While linguistic typology representations from various resources have mostly been used for conditioning the models, there has been relatively little attention on predicting features from these resources from the input data. In this paper we investigate whether the various linguistic features from World Atlas of Language Structures (WALS) can be reliably inferred from multi-lingual text. Such a predictor can be used to infer structural features for a language never observed in training data. We frame this task as a multi-label classification involving predicting the set of non-mutually exclusive and extremely sparse multi-valued labels (WALS features). We construct a recurrent neural network predictor based on byte embeddings and convolutional layers and test its performance on 556 languages, providing analysis for various linguistic types, macro-areas, language families and individual features. We show that some features from various linguistic types can be predicted reliably. | computer science |
Employing a combination of symmetry analysis, low-energy modeling, and ab initio simulations, we predict the presence of magnetic-field-induced Weyl points close to the Fermi level in CaKFe$_4$As$_4$. Depending on the relative strengths of the magnetic field and of the spin-orbit coupling, the Weyl fermions can carry a topological charge of $\pm1$ or $\pm2$, making CaKFe$_4$As$_4$ a rare realization of a double-Weyl semimetal. We further predict experimental manifestations of these Weyl points, both in bulk properties, such as the anomalous Hall effect, and in surface properties, such as the emergence of prominent Fermi arcs. Because CaKFe$_4$As$_4$ displays unconventional fully-gapped superconductivity below 30 K, our findings open a novel route to investigate the interplay between superconductivity and Weyl fermions. | condensed matter |
We present a new family of topological charged hairy black hole solutions in asymptotically AdS space in $D$-dimensions. We solve the coupled Einstein-Maxwell-Scalar gravity system and obtain exact charged hairy black hole solutions with planar, spherical and hyperbolic horizon topologies. The scalar field is regular everywhere. We discuss the thermodynamics of the hairy black hole and find drastic changes in its thermodynamic structure due to the scalar field. For the case of planar and spherical horizons, we find charged hairy/RN-AdS black hole phase transition, with thermodynamically preferred and stable charged hairy phases at low temperature. For the case of hyperbolic horizon, no such transition occurs and RN-AdS black holes are always thermodynamically favoured. | high energy physics theory |
We obtain a Halmos-Richter-type wandering subspace theorem for covariant representations of C*-correspondences. Further the notion of Cauchy dual and a version of Shimorin's Wold-type decomposition for covariant representations of C*-correspondences is explored and as an application a wandering subspace theorem for doubly commuting covariant representations is derived. Using this wandering subspace theorem generating wandering subspaces are characterized for covariant representations of product systems in terms of the doubly commutativity condition. | mathematics |
We applied the Thermofield Dynamics formalism to analyze how the non-classical properties of the Bell-Cat states are influenced by a gradual change of temperature values, in a thermal equilibrium system. To this purpose we calculate the thermal Wigner functions for these states, whose negative volume is associated with non-classical properties, and we evaluate how these non-classical features vary with temperature. Our results indicate that these properties are almost absent for temperatures of around $2\mathrm{K}$. | quantum physics |
A full interpolation theory for Sobolev functions with smoothness between 0 and 1 and vanishing trace on a part of the boundary of an open set is established. Geometric assumptions are of mostly measure theoretic nature and reach beyond Lipschitz regular domains. Previous results were limited to regular geometric configurations or Hilbertian Sobolev spaces. Sets with porous boundary and their characteristic multipliers on smoothness spaces play a major role in the arguments. | mathematics |
A subset $S$ of a cardinal $\kappa$ is Ramsey if for every function $f:[S]^{<\omega}\to \kappa$ with $f(a)<\min a$ for all $a\in[S]^{<\omega}$, there is a set $H\subseteq S$ of cardinality $\kappa$ which is \emph{homogeneous} for $f$, meaning that $f\upharpoonright[H]^n$ is constant for each $n<\omega$. Baumgartner proved \cite{MR0384553} that if $\kappa$ is a Ramsey cardinal, then the collection of non-Ramsey subsets of $\kappa$ is a normal ideal on $\kappa$. Sharpe and Welch \cite{MR2817562}, and independently Bagaria \cite{MR3894041}, extended the notion of $\Pi^1_n$-indescribability where $n<\omega$ to that of $\Pi^1_\xi$-indescribability where $\xi\geq\omega$. We study large cardinal properties and ideals which result from Ramseyness properties in which homogeneous sets are demanded to be $\Pi^1_\xi$-indescribable. By iterating Feng's Ramsey operator \cite{MR1077260} on the various $\Pi^1_\xi$-indescribability ideals, we obtain new large cardinal hierarchies and corresponding nonlinear increasing hierarchies of normal ideals. We provide a complete account of the containment relationships between the resulting ideals and show that the corresponding large cardinal properties yield a strict linear refinement of Feng's original Ramsey hierarchy. We also show that, given any ordinals $\beta_0,\beta_1<\kappa$ the increasing chains of ideals obtained by iterating the Ramsey operator on the $\Pi^1_{\beta_0}$-indescribability ideal and the $\Pi^1_{\beta_1}$-indescribability ideal respectively, are eventually equal; moreover, we identify the least degree of Ramseyness at which this equality occurs. As an application of our results we show that one can characterize our new large cardinal notions and the corresponding ideals in terms of generic elementary embeddings; as a special case this yields generic embedding characterizations of $\Pi^1_\xi$-indescribability and Ramseyness. | mathematics |
We propose reducible algebraic curves as a mechanism to construct Partial MDS (PMDS) codes geometrically. We obtain new general existence results, new explicit constructions and improved estimates on the smallest field sizes over which such codes can exist. Our results are obtained by combining ideas from projective algebraic geometry, combinatorics and probability theory. | computer science |
Metasurfaces are optically thin metamaterials that promise complete control of the wavefront of light but are primarily used to control only the phase of light. Here, we present an approach, simple in concept and in practice, that uses meta-atoms with a varying degree of form birefringence and rotation angles to create high-efficiency dielectric metasurfaces that control both the optical amplitude and phase at one or two frequencies. This opens up applications in computer-generated holography, allowing faithful reproduction of both the phase and amplitude of a target holographic scene without the iterative algorithms required in phase-only holography. We demonstrate all-dielectric metasurface holograms with independent and complete control of the amplitude and phase at up to two optical frequencies simultaneously to generate two- and three-dimensional holographic objects. We show that phase-amplitude metasurfaces enable a few features not attainable in phase-only holography; these include creating artifact-free two-dimensional holographic images, encoding phase and amplitude profiles separately at the object plane, encoding intensity profiles at the metasurface and object planes separately, and controlling the surface textures of three-dimensional holographic objects. | physics |
Decision trees are simple, yet powerful, classification models used to classify categorical and numerical data, and, despite their simplicity, they are commonly used in operations research and management, as well as in knowledge mining. From a logical point of view, a decision tree can be seen as a structured set of logical rules written in propositional logic. Since knowledge mining is rapidly evolving towards temporal knowledge mining, and since in many cases temporal information is best described by interval temporal logics, propositional logic decision trees may evolve towards interval temporal logic decision trees. In this paper, we define the problem of interval temporal logic decision tree learning, and propose a solution that generalizes classical decision tree learning. | computer science |
Let $1\leq p<\infty$ and let $T\colon L^p({\mathcal M})\to L^p({\mathcal N})$ be a bounded map between noncommutative $L^p$-spaces. If $T$ is bijective and separating (i.e., for any $x,y\in L^p({\mathcal M})$ such that $x^*y=xy^*=0$, we have $T(x)^*T(y)=T(x)T(y)^*=0$), we prove the existence of decompositions ${\mathcal M}={\mathcal M}_1\mathop{\oplus}\limits^\infty{\mathcal M}_2$, ${\mathcal N}={\mathcal N}_1 \mathop{\oplus}\limits^\infty{\mathcal N}_2$ and maps $T_1\colon L^p({\mathcal M}_1)\to L^p({\mathcal N}_1)$, $T_2\colon L^p({\mathcal M}_2)\to L^p({\mathcal N}_2)$, such that $T=T_1+T_2$, $T_1$ has a direct Yeadon type factorisation and $T_2$ has an anti-direct Yeadon type factorisation. We further show that $T^{-1}$ is separating in this case. Next we prove that for any $1\leq p<\infty$ (resp. any $1\leq p\not=2<\infty$), a surjective separating map $T\colon L^p({\mathcal M})\to L^p({\mathcal N})$ is $S^1$-bounded (resp. completely bounded) if and only if there exists a decomposition ${\mathcal M}={\mathcal M}_1 \mathop{\oplus}\limits^\infty{\mathcal M}_2$ such that $T|_{L^p({\tiny {\mathcal M}_1})}$ has a direct Yeadon type factorisation and ${\mathcal M}_2$ is subhomogeneous. | mathematics |
We consider 2D Yukawa theory in the strong scalar wave background. We use operator and functional formalisms. In the latter the Schwinger--Keldysh diagrammatic technique is used to calculate retarded, advanced and Keldysh propagators. We use simplest states in the two formalisms in question, which appear to be different from each other. As the result two Keldysh propagators found in different formalisms do not coincide, while the retarded and advanced ones do coincide. We use these propagators to calculate physical quantities. Such as the fermion stress energy flux and the scalar current. The latter one is necessary to know to address the backreaction problem. It happens that while in the functional formalism (for the corresponding simplest state) we find zero fermion flux, in the operator formalism (for the corresponding simplest state) the flux is not zero and is proportional to a Schwarzian derivative. Meanwhile the scalar current is the same in both formalisms, if the background field is large and slowly changing. | high energy physics theory |
We describe a new data product from the CGEM (Coronal Global Evolutionary Model) collaboration that estimates the Lorentz force in active regions (ARs) based on HMI vector magnetogram patches. Following Fisher et al. (2012), we compute three components of the integrated Lorentz force over the outer solar atmosphere every 12 minutes throughout an AR's disk passage. These estimates, differenced during solar eruptive events, can provide valuable diagnostics on dynamic processes. We describe the pipeline modules, provide data retrieval examples, and document some systematic uncertainties that users should be aware of. Finally we document the formal uncertainty propagation procedures. | astrophysics |
We revisit curious objects in string and M-theory called exotic brane---objects that are highly non-perturbative, possessing a tension that scales less than $g_s^{-2}$ and are generically of low-codimension. They are non-geometric in the sense that they are only well-defined locally as supergravity solutions and require duality transformations to patch correctly, in addition to the usual diffeomorphisms and gauge transformations. We argue that Double Field Theory (DFT) and Exceptional Field Theory (EFT) are the prime setting in which to examine such objects. To emphasise this, we construct an explicit solution in $E_{7(7)} \times \mathbb{R}^+$ EFT that unifies many of the codimension-2 exotic branes into a single well-behaved solution on an extended spacetime. We further argue that there are in fact an infinite number of exotic branes in string- and M-theory, many of which fall into a more general class of exotic branes that do not afford even a local description in terms of conventional supergravity. | high energy physics theory |
A prioritized inverse kinematics (PIK) solution can be considered as a (regulation or output tracking) control law of a dynamical system with prioritized multiple outputs. We propose a method that guarantees that a joint trajectory generated from a class of PIK solutions exists uniquely in a nonsingular configuration space. We start by assuming that desired task trajectories stay in nonsingular task spaces and find conditions for task trajectories to stay in a neighborhood of desired task trajectories in which we can guarantee existence and uniqueness of a joint trajectory in a nonsingular configuration space. Based on this result, we find a sufficient condition for task convergence and analyze various stability notions such as stability, uniform stability, uniform asymptotic stability, and exponential stability in both continuous and discrete times. We discuss why the number of tasks is limited in discrete time and show how preconditioning can be used in order to overcome this limitation. | electrical engineering and systems science |
This paper describes a large set of related theorem proving problems obtained by translating theorems from the HOL4 standard library into multiple logical formalisms. The formalisms are in higher-order logic (with and without type variables) and first-order logic (possibly with multiple types, and possibly with type variables). The resultant problem sets allow us to run automated theorem provers that support different logical formats on corresponding problems, and compare their performances. This also results in a new "grand unified" large theory benchmark that emulates the ITP/ATP hammer setting, where systems and metasystems can use multiple ATP formalisms in complementary ways, and jointly learn from the accumulated knowledge. | computer science |
We propose two novel samplers to generate high-quality samples from a given (un-normalized) probability density. Motivated by the success of generative adversarial networks, we construct our samplers using deep neural networks that transform a reference distribution to the target distribution. Training schemes are developed to minimize two variations of the Stein discrepancy, which is designed to work with un-normalized densities. Once trained, our samplers are able to generate samples instantaneously. We show that the proposed methods are theoretically sound and experience fewer convergence issues compared with traditional sampling approaches according to our empirical studies. | statistics |
We study the problem of an online advertising system that wants to optimally spend an advertiser's given budget for a campaign across multiple platforms, without knowing the value for showing an ad to the users on those platforms. We model this challenging practical application as a Stochastic Bandits with Knapsacks problem over $T$ rounds of bidding with the set of arms given by the set of distinct bidding $m$-tuples, where $m$ is the number of platforms. We modify the algorithm proposed in Badanidiyuru \emph{et al.,} to extend it to the case of multiple platforms to obtain an algorithm for both the discrete and continuous bid-spaces. Namely, for discrete bid spaces we give an algorithm with regret $O\left(OPT \sqrt {\frac{mn}{B} }+ \sqrt{mn OPT}\right)$, where $OPT$ is the performance of the optimal algorithm that knows the distributions. For continuous bid spaces the regret of our algorithm is $\tilde{O}\left(m^{1/3} \cdot \min\left\{ B^{2/3}, (m T)^{2/3} \right\} \right)$. When restricted to this special-case, this bound improves over Sankararaman and Slivkins in the regime $OPT \ll T$, as is the case in the particular application at hand. Second, we show an $ \Omega\left (\sqrt {m OPT} \right)$ lower bound for the discrete case and an $\Omega\left( m^{1/3} B^{2/3}\right)$ lower bound for the continuous setting, almost matching the upper bounds. Finally, we use a real-world data set from a large internet online advertising company with multiple ad platforms and show that our algorithms outperform common benchmarks and satisfy the required properties warranted in the real-world application. | computer science |
We consider the change in the asymptotic behavior of solutions of the type of flat domain walls (i.e., kink solutions) in field-theoretic models with a real scalar field. We show that when the model is deformed by a bounded deforming function, the exponential asymptotics of the corresponding kink solutions remain exponential, while the power-law ones remain power-law. However, the parameters of these asymptotics, which are related to the wall thickness, can change. | high energy physics theory |
This article proposes a methodology for the development of adaptive traffic signal controllers using reinforcement learning. Our methodology addresses the lack of standardization in the literature that renders the comparison of approaches in different works meaningless, due to differences in metrics, environments, and even experimental design and methodology. The proposed methodology thus comprises all the steps necessary to develop, deploy and evaluate an adaptive traffic signal controller -- from simulation setup to problem formulation and experimental design. We illustrate the proposed methodology in two simple scenarios, highlighting how its different steps address limitations found in the current literature. | electrical engineering and systems science |
This paper presents an immersed boundary (IB) method for fluid--structure--acoustics interactions involving large deformations and complex geometries. In this method, the fluid dynamics is solved by a finite difference method where the temporal, viscous and convective terms are respectively discretized by the third-order Runge-Kutta scheme, the fourth-order central difference scheme and a fifth-order W/TENO (Weighted/Targeted Essentially Non-oscillation) scheme. Without loss of generality, a nonlinear flexible plate is considered here, and is solved by a finite element method based on the absolute nodal coordinate formulation. The no-slip boundary condition at the fluid--structure interface is achieved by using a diffusion-interface penalty IB method. With the above proposed method, the aeroacoustics field generated by the moving boundaries and the associated flows are inherently solved. In order to validate and verify the current method, several benchmark cases are conducted: acoustic waves scattered from a stationary cylinder in a quiescent flow, sound generation by a stationary and a rotating cylinder in a uniform flow, sound generation by an insect in hovering flight, deformation of a red blood cell induced by acoustic waves and acoustic waves scattered by a stationary sphere. The comparison of the sound scattered by a cylinder shows that the present IB--WENO scheme, a simple approach, has an excellent performance which is even better than the implicit IB--lattice Boltzmann method. For the sound scattered by a sphere, the IB--TENO scheme has a lower dissipation compared with the IB--WENO scheme. Applications of this technique to model fluid-structure-acoustics interactions of flapping foils mimicking an insect wing section during forward flight and flapping foil energy harvester are also presented, considering the effects of foil shape and flexibility. | physics |
Describing long-ranged electrostatics using short-ranged pair potentials is appealing since the computational complexity scales linearly with the number of particles. The foundation of this approach is to mimic the long-ranged medium response by cancelling electric multipoles within a small cutoff sphere. We propose a rigorous and formally exact new method that cancels up to infinitely many multipole moments and is free of operational damping parameters often required in existing theories. Using molecular dynamics simulations of water with and without added salt, we discuss radial distribution functions, Kirkwood-Buff integrals, dielectrics, diffusion coefficients, and angular correlations in relation to existing electrostatic models. We find that the proposed method is an efficient and accurate alternative for handling long-ranged electrostatics as compared to Ewald summation schemes. The methodology and proposed parameterization is applicable also for dipole-dipole interactions. | condensed matter |
We present a novel framework for simulating matrix models on a quantum computer. Supersymmetric matrix models have natural applications to superstring/M-theory and gravitational physics, in an appropriate limit of parameters. Furthermore, for certain states in the Berenstein-Maldacena-Nastase (BMN) matrix model, several supersymmetric quantum field theories dual to superstring/M-theory can be realized on a quantum device. Our prescription consists of four steps: regularization of the Hilbert space, adiabatic state preparation, simulation of real-time dynamics, and measurements. Regularization is performed for the BMN matrix model with the introduction of energy cut-off via the truncation in the Fock space. We use the Wan-Kim algorithm for fast digital adiabatic state preparation to prepare the low-energy eigenstates of this model as well as thermofield double state. Then, we provide an explicit construction for simulating real-time dynamics utilizing techniques of block-encoding, qubitization, and quantum signal processing. Lastly, we present a set of measurements and experiments that can be carried out on a quantum computer to further our understanding of superstring/M-theory beyond analytic results. | high energy physics theory |
By applying the Bogoliubov transformations and through the introduction of the Bargmann-Hilbert spaces, we obtain analytic representations of solutions to the driven Rabi model without ${\cal Z}_2$ symmetry, and the 2-photon and two-mode quantum Rabi models. In each case, transcendental function is analytically derived whose zeros give the energy spectrum of the model. The zeros can be numerically found by standard root-search techniques. | quantum physics |
Some theoretic results related to the cosmological constant, obtained in the 80's and 90's of last century, are reviewed. These results exhibit some interesting underlying pattern when viewed from a category-theoretic perspective. In doing this, we illustrate how Baez and Dolan's Periodic Table of $k$-tuply monoidal $n$-categories can serve as a basic framework of a quantum spacetime structure. Explicitly, we show how Einstein gravity (with the cosmological constant turned on) emerges when we de-categorify certain $2$-tuply monoidal $2$-categories properly, as Crane proposed a long time ago. In particular, we find that some recent work on Vertex Operator Algebras and 4-manifolds fits nicely into this framework. | high energy physics theory |
The health and demographic surveillance system (HDSS) is an old method for intensively monitoring a population to assess the effects of healthcare or other population-level interventions - often clinical trials. The strengths of HDSS include very detailed descriptions of whole populations with frequent updates. This often provides long time series of accurate population and health indicators for the HDSS study population. The primary weakness of HDSS is that the data describe only the HDSS study population and cannot be generalized beyond that. The 2030 agenda is the ecosystem of activities - many including population-level monitoring - that relate to the United Nations (UN) Sustainable Development Goals (SDG). With respect to the 2030 agenda, HDSS can contribute by: continuing to conduct cause-and-effect studies; contributing to data triangulation or amalgamation initiatives; characterizing the bias in and calibrating 'big data'; and contributing more to the rapid training of data-oriented professionals, especially in the population and health fields. | statistics |
We discuss new ideas for consideration of loop diagrams and angular integrals in $D$-dimensions in QCD. In case of loop diagrams, we propose the covariant formalism of expansion of tensorial loop integrals into the orthogonal basis of linear combinations of external momenta. It gives a very simple presentation for the final results and is more convenient for calculations on computer algebra systems. In case of angular integrals we demonstrate how to simplify the integration of differential cross sections over polar angles. Also we derive the recursion relations, which allow to reduce all occurring angular integrals to a short set of basic scalar integrals. All order $\epsilon$-expansion is given for all angular integrals with up to two denominators based on the expansion of the basic integrals and using recursion relations. A geometric picture for partial fractioning is developed which provides a new rotational invariant algorithm to reduce the number of denominators. | high energy physics phenomenology |
The Seidel maps are two maps associated to a Hamiltonian circle action on a convex symplectic manifold, one on Floer cohomology and one on quantum cohomology. We extend their definitions to $S^1$-equivariant Floer cohomology and $S^1$-equivariant quantum cohomology based on a construction of Maulik and Okounkov. The $S^1$-action used to construct $S^1$-equivariant Floer cohomology changes after applying the equivariant Seidel map (a similar phenomenon occurs for $S^1$-equivariant quantum cohomology). We show the equivariant Seidel map on $S^1$-equivariant quantum cohomology does not commute with the $S^1$-equivariant quantum product, unlike the standard Seidel map. We prove an intertwining relation which completely describes the failure of this commutativity as a weighted version of the equivariant Seidel map. We will explore how this intertwining relationship may be interpreted using connections in an upcoming paper. We compute the equivariant Seidel map for rotation actions on the complex plane and on complex projective space, and for the action which rotates the fibres of the tautological line bundle over projective space. Through these examples, we demonstrate how equivariant Seidel maps may be used to compute the $S^1$-equivariant quantum product and $S^1$-equivariant symplectic cohomology. | mathematics |
We study the possibility of low scale leptogenesis along with dark matter (DM) in the presence of primordial black holes (PBH). For a common setup to study both leptogenesis and DM we consider the minimal scotogenic model which also explains light neutrino mass at radiative level. While PBH in the mass range of $0.1-10^5$ g can, in principle, affect leptogenesis, the required initial PBH fraction usually leads to overproduction of DM whose thermal freeze-out occurs before PBH evaporation. PBH can lead to non-thermal source of leptogenesis as well as dilution of thermally generated lepton asymmetry via entropy injection, with the latter being dominant. The parameter space of scotogenic model which leads to overproduction of baryon or lepton asymmetry in standard cosmology can be made consistent in the presence of PBH with appropriate initial mass and energy fraction. On the other hand, for such PBH parameters, the DM is constrained to be in light mass regime where its freeze-out occurs after PBH evaporation. | high energy physics phenomenology |
Probabilistic machine learning models are often insufficient to help with decisions on interventions because those models find correlations - not causal relationships. If observational data is only available and experimentation are infeasible, the correct approach to study the impact of an intervention is to invoke Pearl's causality framework. Even that framework assumes that the underlying causal graph is known, which is seldom the case in practice. When the causal structure is not known, one may use out-of-the-box algorithms to find causal dependencies from observational data. However, there exists no method that also accounts for the decision-maker's prior knowledge when developing the causal structure either. The objective of this paper is to develop rational approaches for making decisions from observational data in the presence of causal graph uncertainty and prior knowledge from the decision-maker. We use ensemble methods like Bayesian Model Averaging (BMA) to infer set of causal graphs that can represent the data generation process. We provide decisions by computing the expected value and risk of potential interventions explicitly. We demonstrate our approach by applying them in different example contexts. | computer science |
The clustering properties of the Universe at large-scales are currently being probed at various redshifts through several cosmological tracers and with diverse statistical estimators. Here we use the three-point angular correlation function (3PACF) to probe the baryon acoustic oscillation (BAO) features in the quasars catalogue from the twelfth data release of the Sloan Digital Sky Survey, with mean redshift z = 2.225, detecting the BAO imprint with a statistical significance of 2.9{\sigma}, obtained using lognormal mocks. Following a quasi model-independent approach for the 3PACF, we find the BAO transversal signature for triangles with sides $\theta_1 = 1.0^\circ$ and $\theta_2 = 1.5^\circ$ and the angle between them of $\alpha = 1.59 \pm 0.17$ rad, a value that corresponds to the angular BAO scale ${\theta}_{BAO} = 1.82^\circ \pm 0.21^\circ$ , in excellent agreement with the value found in a recent work (${\theta}_{BAO} = 1.77^\circ \pm 0.31^\circ$ ) applying the 2PACF to similar data. Moreover, we performed two type of tests: one to confirm the robustness of the BAO signal in the 3PACF through random displacements in the dataset, and the other to verify the suitability of our random samples, a null test that in fact does not show any signature that could bias our results. | astrophysics |
A method is proposed to compute robust inner-approximations to the backward reachable set for uncertain nonlinear systems. It also produces a robust control law that drives trajectories starting in these sets to the target set. The method merges dissipation inequalities and integral quadratic constraints (IQCs) with both hard and soft IQC factorizations. Computational algorithms are presented using the generalized S-procedure and sum-of-squares techniques. The use of IQCs in backward reachability analysis allows for a variety of perturbations including parametric uncertainty, unmodeled dynamics, nonlinearities, and uncertain time delays. The method is demonstrated on two examples, including a 6-state quadrotor with actuator uncertainties. | electrical engineering and systems science |
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