October 2020 arXiv papers — page 49

Ting Cai, Peyman Mohtat, Anna G. Stefanopoulou, Jason B. Siegel

Internal short circuits are a leading cause of battery thermal runaway, and hence a major safety issue for electric vehicles. An internal short circuit with low resistance is called a hard internal short, which causes a high internal current flow that leads to an extremely fast temperature rise, gas generation, cell swelling, and ultimately battery rupture a

Taylor Faucett, Jesse Thaler, Daniel Whiteson

We present a technique for translating a black-box machine-learned classifier operating on a high-dimensional input space into a small set of human-interpretable observables that can be combined to make the same classification decisions. We iteratively select these observables from a large space of high-level discriminants by finding those with the highest d

Kirill D. Cherednichenko, Alexander V. Kiselev, Luis O. Silva

Using a generalisation of the classical notion of Dirichlet-to-Neumann map and the related formulae for the resolvents of boundary-value problems, we analyse the asymptotic behaviour of solutions to a "transmission problem" for a high-contrast inclusion in a continuous medium, for which we prove the operator-norm resolvent convergence to a limit problem of "

Kaito Ariu, Kenshi Abe, Alexandre Proutière

In this paper, we revisit the regret minimization problem in sparse stochastic contextual linear bandits, where feature vectors may be of large dimension $d$, but where the reward function depends on a few, say $s_0\ll d$, of these features only. We present Thresholded Lasso bandit, an algorithm that (i) estimates the vector defining the reward function as w

S. W. Belling, Y. C. Li, A. H. Davoody, A. J. Gabourie

We present the numerical tool DECaNT (Diffusion of Excitons in Carbon NanoTubes) that simulates exciton transport in thin films of carbon nanotubes. Through a mesh of nanotubes generated using the Bullet Physics C++ library, excitons move according to an ensemble Monte Carlo algorithm, with the scattering rates that account for tube chirality, orientation, a

Adam Ligocki, Ales Jelinek, Ludek Zalud

In this paper, we present our software sensor fusion framework for self-driving cars and other autonomous robots. We have designed our framework as a universal and scalable platform for building up a robust 3D model of the agent's surrounding environment by fusing a wide range of various sensors into the data model that we can use as a basement for the decis

Miguel Á. Javaloyes, Enrique Pendás-Recondo, Miguel Sánchez

A general framework for the description of classic wave propagation is introduced. This relies on a cone structure $C$ determined by an intrinsic space $\Sigma$ of velocities of propagation (point, direction and time-dependent) and an observers' vector field $\partial_t$ whose integral curves provide both a Zermelo problem for the wave and an auxiliary Loren

Alexander R. Block, Jeremiah Blocki, Elena Grigorescu, Shubhang Kulkarni

Recent efforts in coding theory have focused on building codes for insertions and deletions, called insdel codes, with optimal trade-offs between their redundancy and their error-correction capabilities, as well as efficient encoding and decoding algorithms. In many applications, polynomial running time may still be prohibitively expensive, which has motivat

Bailin Wang, Mirella Lapata, Ivan Titov

The importance of building semantic parsers which can be applied to new domains and generate programs unseen at training has long been acknowledged, and datasets testing out-of-domain performance are becoming increasingly available. However, little or no attention has been devoted to learning algorithms or objectives which promote domain generalization, with

N. Bence, A. Lengyel, Z. Tarics, E. Martynov

We assume that the scattering amplitude is represented by Froissaron, Maximal Odderon as well as by standard Regge poles. From the fit to the data of $pp$ and $\bar pp$ scattering at high energy and not too large momentum transfers we found that this model taking into account the spin is available to describe not only the differential, total cross section an

LHCb collaboration, R. Aaij, C. Abellán Beteta, T. Ackernley

A branching fraction measurement of the $B^{0}\rightarrow D_{s}^{+}\pi^{-}$ decay is presented using proton-proton collision data collected with the LHCb experiment, corresponding to an integrated luminosity of $5.0\,$fb$^{-1}$. The branching fraction is found to be ${\mathcal{B}(B^{0}\rightarrow D_{s}^{+}\pi^{-}) = (19.4 \pm 1.8\pm 1.3 \pm 1.2)\times 10^{-6

Jianing Yang, Yongxin Wang, Ruitao Yi, Yuying Zhu

Human communication is multimodal in nature; it is through multiple modalities such as language, voice, and facial expressions, that opinions and emotions are expressed. Data in this domain exhibits complex multi-relational and temporal interactions. Learning from this data is a fundamentally challenging research problem. In this paper, we propose Modal-Temp

Brendan D. Faeth, Shuolong Yang, Jason K. Kawasaki, Jocienne N. Nelson

In many unconventional superconductors, the presence of a pseudogap - a suppression in the electronic density of states extending above the critical temperature - has been a long-standing mystery. Here, we employ combined \textit{in situ} electrical transport and angle-resolved photoemission spectroscopy (ARPES) measurements to reveal an unprecedentedly larg

Saul A. Kripke

In his paper on the incompleteness theorems, G\"odel seemed to say that a direct way of constructing a formula that says of itself that it is unprovable might involve a faulty circularity. In this note, it is proved that 'direct' self-reference can actually be used to prove his result.

Gracjan Maciejewski

Origins of giant planets on tight orbits, so called hot Jupiters, are a long-lasting question in the planetary formation and evolution theory. The answer seems to be hidden in architectures of those systems that remain only partially understood. Using multi-sector time-series photometry from the Transiting Exoplanet Survey Satellite, we searched for addition

M. L. Pereira Júnior, C. M. Viana de Araújo, J. M. de Sousa, R. T. de Sousa Júnior

We carried out fully-atomistic reactive molecular dynamics simulations to study the elastic properties and fracture patterns of transition metal dichalcogenide (TMD) MoX2 (X=S, Se, Te) membranes, in their 2H and 1T phases, within the framework of the Stillinger-Weber potential. Results showed that the fracture mechanism of these membranes occurs through a fa

Quntao Zhuang

A phase reference has been a standard requirement in continuous-variable quantum sensing and communication protocols. However, maintaining a phase reference is challenging due to environmental fluctuations, preventing quantum phenomena such as entanglement and coherence from being utilized in many scenarios. We show that quantum communication and entanglemen

MATE Collaboration, M. Arnaud, S. Ettori, G. W. Pratt

The Cluster HEritage project with XMM-Newton - Mass Assembly and Thermodynamics at the Endpoint of structure formation (CHEX-MATE) is a three mega-second Multi-Year Heritage Programme to obtain X-ray observations of a minimally-biased, signal-to-noise limited sample of 118 galaxy clusters detected by Planck through the Sunyaev-Zeldovich effect. The programme

Jie Wang, Rui Gao, Yao Xie

We develop a projected Wasserstein distance for the two-sample test, a fundamental problem in statistics and machine learning: given two sets of samples, to determine whether they are from the same distribution. In particular, we aim to circumvent the curse of dimensionality in Wasserstein distance: when the dimension is high, it has diminishing testing powe

John Arban Lewis, Charles Lada, John Bieging, Anoush Kazarians

We study the relationship between molecular gas and dust in the California Molecular Cloud over an unprecedented dynamic range of cloud depth (Av = 3 - 60 magnitudes). We compare deep Herschel-based measurements of dust extinction with observations of the 12CO, 13CO, and C18O J=2-1 lines on sub-parsec scales across the cloud. We directly measure the ratio of

Renu Sharma, Arun Ross

In this paper, we propose the use of Optical Coherence Tomography (OCT) imaging for the problem of iris presentation attack (PA) detection. We assess its viability by comparing its performance with respect to traditional iris imaging modalities, viz., near-infrared (NIR) and visible spectrum. OCT imaging provides a cross-sectional view of an eye, whereas tra

Eric P. Andersson, Florent Renaud, Oscar Agertz

In the outskirts of nearby spiral galaxies, star formation is observed in extremely low gas surface densities. Star formation in these regions, where the interstellar medium is dominated by diffuse atomic hydrogen, is difficult to explain with classic star formation theories. In this letter, we introduce runaway stars as an explanation for this observation.

Myles A. Mitchell, Christian Arnold, Baojiu Li

We test two methods, including one that is newly proposed in this work, for correcting for the effects of chameleon $f(R)$ gravity on the scaling relations between the galaxy cluster mass and four observable proxies. Using the first suite of cosmological simulations that simultaneously incorporate both full physics of galaxy formation and Hu-Sawicki $f(R)$ g

Andrew K. Saydjari, Stephen K. N. Portillo, Zachary Slepian, Sule Kahraman

The complex interplay of magnetohydrodynamics, gravity, and supersonic turbulence in the interstellar medium (ISM) introduces non-Gaussian structure that can complicate comparison between theory and observation. We show that the Wavelet Scattering Transform (WST), in combination with linear discriminant analysis (LDA), is sensitive to non-Gaussian structure

Donaji Esparza-Arredondo, Natalia Osorio-Clavijo, Omaira González-Martín, Cesar Victoria-Ceballos

Physical processes such as re-ignition, enhancement, and fading of active galactic nuclei (AGN) are not entirely understood because the timeline of these events is expected to last many years. However, it is well known that the differences in the energy budget between AGN components, like the optical ionizing region and the mid-infrared (MIR) dust echoes, ca

Timon Thomas, Christoph Pfrommer, Rüdiger Pakmor

We present a new numerical algorithm to solve the recently derived equations of two-moment cosmic ray hydrodynamics (CRHD). The algorithm is implemented as a module in the moving mesh Arepo code. Therein, the anisotropic transport of cosmic rays (CRs) along magnetic field lines is discretised using a path-conservative finite volume method on the unstructured

Martín de los Rios, Héctor Julián Martínez, Valeria Coenda, Hernán Muriel

We present the ROGER (Reconstructing Orbits of Galaxies in Extreme Regions) code, which uses three different machine learning techniques to classify galaxies in, and around, clusters, according to their projected phase-space position. We use a sample of 34 massive, $M_{200}>10^{15} h^{-1} M_{\odot}$, galaxy clusters in the MultiDark Planck 2 (MDLP2) simulati

Erin Boettcher, Hsiao-Wen Chen, Fakhri S. Zahedy, Thomas J. Cooper

We report the serendipitous detection of an H$_{2}$-bearing damped Lyman-$\alpha$ absorber at z = 0.576 in the spectrum of the QSO J0111-0316 in the Cosmic Ultraviolet Baryon Survey. Spectroscopic observations from HST-COS in the far-ultraviolet reveal a damped absorber with log[N(HI)/cm^-2] = 20.1 +/- 0.2 and log[N(H$_{2}$)/cm^-2] = 18.97 (-0.06, +0.05). Th

Oscar Pozo, Peng Rao, Chuan Chen, Inti Sodemann

We study in detail the properties of pi-fluxes embedded in a state with a finite density of anyons that form either a Fermi liquid or a Bose-Einstein condensate. By employing a recently developed exact lattice bosonization in 2D, we demonstrate that such pi-flux remains a fully deconfined quasiparticle with a finite energy cost in a Fermi liquid of emergent

Carmelo Evoli, Elena Amato, Pasquale Blasi, Roberto Aloisio

We present a novel calculation of the spectrum of electrons and positrons from random sources, supernova remnants and pulsars, distributed within the spiral arms of the Galaxy. The pulsar emissivity in terms of electron-positron pairs is considered as time dependent, following the magnetic dipole spin-down luminosity, and the temporal evolution of the potent

Christopher T. Davies, Marius Cautun, Benjamin Giblin, Baojiu Li

Upcoming surveys such as \LSST{} and \Euclid{} will significantly improve the power of weak lensing as a cosmological probe. To maximise the information that can be extracted from these surveys, it is important to explore novel statistics that complement standard weak lensing statistics such as the shear-shear correlation function and peak counts. In this wo

Christie S. Chiu, Da-Shuai Ma, Zhi-Da Song, B. Andrei Bernevig

The geometric properties of a lattice can have profound consequences on its band spectrum. For example, symmetry constraints and geometric frustration can give rise to topologicially nontrivial and dispersionless bands, respectively. Line-graph lattices are a perfect example of both of these features: their lowest energy bands are perfectly flat, and here we

Tanay Nag, Bitan Roy

Electronic bands featuring nontrivial bulk topological invariant manifest through robust gapless modes at the boundaries, e.g., edges and surfaces. As such this bulk-boundary correspondence is also operative in driven quantum materials. For example, a suitable periodic drive can convert a trivial insulator into a Floquet topological insulator (FTI) that acco

Yubo Su, Dong Lai, Bin Liu

Black-hole (BH) binary mergers driven by gravitational perturbations of tertiary companions constitute an important class of dynamical formation channels for compact binaries detected by LIGO/VIRGO. Recent works have examined numerically the combined orbital and spin dynamics of BH binaries that undergo large Lidov-Kozai (LK) eccentricity oscillations induce

Nihan S. Pol, Stephen R. Taylor, Luke Zoltan Kelley, Sarah J. Vigeland

The NANOGrav Collaboration reported strong Bayesian evidence for a common-spectrum stochastic process in its 12.5-yr pulsar timing array dataset, with median characteristic strain amplitude at periods of a year of $A_{\rm yr} = 1.92^{+0.75}_{-0.55} \times 10^{-15}$. However, evidence for the quadrupolar Hellings \& Downs interpulsar correlations, which are c

Tom Marianer, Dovi Poznanski, J. Xavier Prochaska

By now, tens of gravitational-wave (GW) events have been detected by the LIGO and Virgo detectors. These GWs have all been emitted by compact binary coalescence, for which we have excellent predictive models. However, there might be other sources for which we do not have reliable models. Some are expected to exist but to be very rare (e.g., supernovae), whil

Greg Salvesen, Jonah M. Miller

The two established techniques for measuring black hole spin in X-ray binaries often yield conflicting results, which must be resolved before either method may be deemed robust. In practice, black hole spin measurements based on fitting the accretion disc continuum effectively do not marginalize over the colour correction factor $f_{\mathrm{col}}$. This fact

Bartosz Regula, Ryuji Takagi

Quantum channels underlie the dynamics of quantum systems, but in many practical settings it is the channels themselves that require processing. We establish universal limitations on the processing of both quantum states and channels, expressed in the form of no-go theorems and quantitative bounds for the manipulation of general quantum channel resources und

Chu-Cheng Lin, Aaron Jaech, Xin Li, Matthew R. Gormley

Standard autoregressive language models perform only polynomial-time computation to compute the probability of the next symbol. While this is attractive, it means they cannot model distributions whose next-symbol probability is hard to compute. Indeed, they cannot even model them well enough to solve associated easy decision problems for which an engineer mi

Reza Baghdadi, Ekkehart Schmidt, Saman Jahani, Ilya Charaev

Current crowding at bends of superconducting nanowire single-photon detectors is one of the main factors limiting the performance of meander-style detectors with large filling factors. In this paper, we propose a new concept to reduce influence of the current crowding effect, a so-called variable thickness SNSPD, which is composed of two regions with differe

Douglas Hardin, Edward B. Saff, Oleksandr Vlasiuk

We describe a framework for extending the asymptotic behavior of a short-range interaction from the unit cube to general compact subsets of $ \mathbb R^d $. This framework allows us to give a unified treatment of asymptotics of hypersingular Riesz energies and optimal quantizers. We further obtain new results about the scale-invariant nearest neighbor intera

K V Sushena Sree, Prasad Krishnan

The performance of replication-based distributed databases is affected due to non-uniform storage across storage nodes (also called \textit{data skew}) and reduction in the replication factor during operation, particularly due to node additions or removals. Data rebalancing refers to the communication involved between the nodes in correcting this data skew,

Linting Xue, Noah Constant, Adam Roberts, Mihir Kale

The recent "Text-to-Text Transfer Transformer" (T5) leveraged a unified text-to-text format and scale to attain state-of-the-art results on a wide variety of English-language NLP tasks. In this paper, we introduce mT5, a multilingual variant of T5 that was pre-trained on a new Common Crawl-based dataset covering 101 languages. We detail the design and modifi

Jianxue Wang, Shutang You, Xingzhong Bai, Mingqiao Peng

Due to a series of supporting policies in recent years, China wind power has developed rapidly through a large-scale and centralized mode. This paper analyzes the two major concerns faced by wind power development in China: wind generation reliability and wind energy balancing. More specifically, wind farm tripping-off-grid incidents and wind power curtailme

Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn

While the Transformer architecture has become the de-facto standard for natural language processing tasks, its applications to computer vision remain limited. In vision, attention is either applied in conjunction with convolutional networks, or used to replace certain components of convolutional networks while keeping their overall structure in place. We sho

Pranshu Gupta, Yannick Mogge, Simón Piga, Bjarne Schülke

Given integers $r\geq 2$ and $n,t\geq 1$ we call families $\mathcal{F}_1,\dots,\mathcal{F}_r\subseteq\mathscr{P}([n])$ $r$-cross $t$-intersecting if for all $F_i\in\mathcal{F}_i$, $i\in[r]$, we have $\vert\bigcap_{i\in[r]}F_i\vert\geq t$. We obtain a strong generalisation of the classic Hilton-Milner theorem on cross intersecting families. In particular, we

Mikhail Alfimov, Boris Feigin, Ben Hoare, Alexey Litvinov

We study the dual description of the $\eta$-deformed $OSP(N|2m)$ sigma model in the asymptotically free regime ($N>2m+2$). Compared to the case of classical Lie groups, for supergroups there are inequivalent $\eta$-deformations corresponding to different choices of simple roots. For a class of such deformations we propose the system of screening charges depe

Aravind Gollakota, Sushrut Karmalkar, Adam Klivans

We consider the problem of distribution-free learning for Boolean function classes in the PAC and agnostic models. Generalizing a beautiful work of Malach and Shalev-Shwartz (2022) that gave tight correlational SQ (CSQ) lower bounds for learning DNF formulas, we give new proofs that lower bounds on the threshold or approximate degree of any function class di

Gintare Karolina Dziugaite, Alexandre Drouin, Brady Neal, Nitarshan Rajkumar

One of the principal scientific challenges in deep learning is explaining generalization, i.e., why the particular way the community now trains networks to achieve small training error also leads to small error on held-out data from the same population. It is widely appreciated that some worst-case theories -- such as those based on the VC dimension of the c

Jordan Cotler, Nicholas Hunter-Jones, Daniel Ranard

We study the fluctuations of subsystem entropies in closed quantum many-body systems after thermalization. Using a combination of analytics and numerics for both random quantum circuits and Hamiltonian dynamics, we find that the statistics of such entropy fluctuations is drastically different than in the classical setting. For instance, shortly after a syste

Paul C Bressloff

Numerical simulations of classical pattern forming reaction-diffusion systems indicate that they often operate in the strongly nonlinear regime, with the final steady-state consisting of a spatially repeating pattern of localized spikes. In activator-inhibitor systems such as the two-component Gierer-Meinhardt (GM) model, one can consider the singular limit

Fernando G. Gardim, Jean-Yves Ollitrault

We evaluate the viscous damping of anisotropic flow in heavy-ion collisions for arbitrary temperature-dependent shear and bulk viscosities. We show that the damping is solely determined by effective shear and bulk viscosities, which are weighted averages over the temperature. We determine the relevant weights for nucleus-nucleus collisions at $\sqrt{s_{\rm N

Andreas Rücklé, Gregor Geigle, Max Glockner, Tilman Beck

Massively pre-trained transformer models are computationally expensive to fine-tune, slow for inference, and have large storage requirements. Recent approaches tackle these shortcomings by training smaller models, dynamically reducing the model size, and by training light-weight adapters. In this paper, we propose AdapterDrop, removing adapters from lower tr

Annie S. Chen, HyunJi Nam, Suraj Nair, Chelsea Finn

Learning from diverse offline datasets is a promising path towards learning general purpose robotic agents. However, a core challenge in this paradigm lies in collecting large amounts of meaningful data, while not depending on a human in the loop for data collection. One way to address this challenge is through task-agnostic exploration, where an agent attem

Akari Asai, Eunsol Choi

Recent pretrained language models "solved" many reading comprehension benchmarks, where questions are written with access to the evidence document. However, datasets containing information-seeking queries where evidence documents are provided after the queries are written independently remain challenging. We analyze why answering information-seeking queries

Tobias Boege

The gaussoid axioms are conditional independence inference rules which characterize regular Gaussian CI structures over a three-element ground set. It is known that no finite set of inference rules completely describes regular Gaussian CI as the ground set grows. In this article we show that the gaussoid axioms logically imply every inference rule of at most

Sana Keita, Abdelaziz Beljadid, Yves Bourgault

We consider a class of finite element approximations for fourth-order parabolic equations that can be written as a system of second-order equations by introducing an auxiliary variable. In our approach, we first solve a variational problem and then an optimization problem to satisfy the desired physical properties of the solution such as conservation of mass

Fernando Núñez, David Canca, Ángel Arcos-Vargas

This study analyses the current viability of this business based on a sample of European countries in the year 2019; countries where electricity prices (day-ahead market) and financial conditions show a certain degree of heterogeneity. We basically follow a sequence of three analyses in our study. Firstly, a Linear Mixed-Integrated Programming model has been

Sungkyun Chang, Donmoon Lee, Jeongsoo Park, Hyungui Lim

Most of existing audio fingerprinting systems have limitations to be used for high-specific audio retrieval at scale. In this work, we generate a low-dimensional representation from a short unit segment of audio, and couple this fingerprint with a fast maximum inner-product search. To this end, we present a contrastive learning framework that derives from th

Navid Naderializadeh

We propose a new approach for power control in wireless networks using self-supervised learning. We partition a multi-layer perceptron that takes as input the channel matrix and outputs the power control decisions into a backbone and a head, and we show how we can use contrastive learning to pre-train the backbone so that it produces similar embeddings at it

Torben C. Frost, Volker Perlick

The C-metric is a solution to Einstein's vacuum field equation that describes an accelerating black hole. In this paper we discuss the propagation of light rays and the resulting lensing features in this metric. We first solve the lightlike geodesic equation using elliptic integrals and Jacobi elliptic functions. Then we fix a static observer in the region o

Takeshi Nakamori, Yuga Ouchi, Risa Ogihara, Toshio Terasawa

We have developed a sensor system based on an optical photon-counting imager with high timing resolution, aiming for highly time-variable astronomical phenomena. The detector is a monolithic Geiger-mode avalanche photodiode array customized in a Multi-Pixel Photon Counter with a response time on the order of nanoseconds. This paper evaluates the basic perfor

Stefano Catani, Simone Devoto, Massimiliano Grazzini, Stefan Kallweit

We report on the first fully differential calculation of the next-to-next-to-leading-order (NNLO) QCD radiative corrections to the production of bottom-quark pairs at hadron colliders. The calculation is performed by using the $q_T$ subtraction formalism to handle and cancel infrared singularities in real and virtual contributions. The computation is impleme

Ryan M. Dreifuerst, Samuel Daulton, Yuchen Qian, Paul Varkey

Wireless cellular networks have many parameters that are normally tuned upon deployment and re-tuned as the network changes. Many operational parameters affect reference signal received power (RSRP), reference signal received quality (RSRQ), signal-to-interference-plus-noise-ratio (SINR), and, ultimately, throughput. In this paper, we develop and compare two

Ik Soo Lim

Trusting in others and reciprocating that trust with trustworthy actions are crucial to successful and prosperous societies. The Trust Game has been widely used to quantitatively study trust and trustworthiness, involving a sequential exchange between an investor and a trustee. The deterministic evolutionary game theory predicts no trust and no trustworthine

S. Aiola, L. Bandiera, G. Cavoto, F. De Benedetti

Electromagnetic dipole moments of short-lived particles are sensitive to physics within and beyond the Standard Model of particle physics but have not been accessible experimentally to date. To perform such measurements it has been proposed to exploit the spin precession of channeled particles in bent crystals at the LHC. Progress that enables the first meas

Michela Egidi, Albrecht Seelmann

We provide an abstract framework for a Logvinenko-Sereda type theorem, where the classical compactness assumption on the support of the Fourier transform is replaced by the assumption that the functions under consideration belong to a spectral subspace associated with a finite energy interval for some lower semibounded self-adjoint operator on a Euclidean $L

Yuki Nagai, Akinori Tanaka, Akio Tomiya

In this paper, we develop the self-learning Monte-Carlo (SLMC) algorithm for non-abelian gauge theory with dynamical fermions in four dimensions to resolve the autocorrelation problem in lattice QCD. We perform simulations with the dynamical staggered fermions and plaquette gauge action by both in HMC and SLMC for zero and finite temperature to examine the v

Anna Dawid, Michał Tomza

We theoretically investigate the magnetic properties and nonequilibrium dynamics of two interacting ultracold polar and paramagnetic molecules in a one-dimensional harmonic trap in external electric and magnetic fields. The molecules interact via a multichannel two-body contact potential, incorporating the short-range anisotropy of intermolecular interaction

Franziska Hagelstein, Vladimir Pascalutsa

The proton-polarizability contribution to the muonic-hydrogen Lamb shift is a major source of theoretical uncertainty in the extraction of the proton charge radius. An empirical evaluation of this effect, based on the proton structure functions, requires a systematically improvable calculation of the "subtraction function", possibly using lattice QCD. We con

Wen-Long Sang, Feng Feng, Yu Jia

Within the nonrelativistic QCD (NRQCD) factorization framework, we compute the ${\mathcal O}(\alpha_s v^2)$ corrections to the hadronic decay rate of vector quarkonia, exemplified by $J/\psi$ and $\Upsilon$. Setting both the renormalization and NRQCD factorization scales to be $m_Q$, we obtain $\Gamma(J/\psi\to {\rm LH})= 0.0716\frac{\alpha_s^3}{m_c^2} \lang

Frankbelson dos S. Azevedo, José Diêgo M. de Lima, Antônio de Pádua Santos, Fernando Moraes

We examine the optical properties of two different configurations of an ordered liquid crystal film on a catenoid forming coreless disclinations. We find the effective optical metric from which we obtain the geodesics and wave modes characterizing thus the propagation of light on this surface. We show that the optical metric describes a two-dimensional secti

Satvik Singh

We present an alternative approach to unveil a different kind of entanglement in bipartite quantum states whose diagonal zero patterns in suitable matrix representations admit a nice description in terms of triangle-free graphs. Upon application of a local averaging operation, the separability of such states transforms into a simple matrix positivity conditi

Qiang Hu, Wen He, Jiong Qiu, A. Vourlidas

We develop an optimization approach to model the magnetic field configuration of magnetic clouds, based on a linear-force free formulation in three dimensions. Such a solution, dubbed the Freidberg solution, is kin to the axi-symmetric Lundquist solution, but with more general "helical symmetry". The merit of our approach is demonstrated via its application

Golam Ali Sekh, Benoy Talukdar

The stationary bright solitons that appear in the ground state of the spin-orbit coupled Bose-Einstein condensate (SOC-BEC) exhibit nodes. We consider SOC-BEC in combined linear and nonlinear optical lattices and study their effects on the matter-wave bright soliton and find that the parameters of the nonlinear lattice or atomic scattering length can be judi

Maria I. Gorinova, Andrew D. Gordon, Charles Sutton, Matthijs Vákár

A central goal of probabilistic programming languages (PPLs) is to separate modelling from inference. However, this goal is hard to achieve in practice. Users are often forced to re-write their models in order to improve efficiency of inference or meet restrictions imposed by the PPL. Conditional independence (CI) relationships among parameters are a crucial

Paul C Bressloff

In this paper we extend our recent work on two-dimensional (2D) diffusive search-and-capture processes with multiple small targets (narrow capture problems) by considering an asymptotic expansion of the Laplace transformed probability flux into each target. The latter determines the distribution of arrival or capture times into an individual target, conditio

Matías Berdakin, Esteban A. Rodríguez-Mena, L. E. F. Foa Torres

Harnessing the unique features of topological materials for the development of a new generation of topological based devices is a challenge of paramount importance. Using Floquet scattering theory combined with atomistic models we study the interplay between laser illumination, spin and topology in a two-dimensional material with spin-orbit coupling. Startin

Gregory Benton, Marc Finzi, Pavel Izmailov, Andrew Gordon Wilson

Invariances to translations have imbued convolutional neural networks with powerful generalization properties. However, we often do not know a priori what invariances are present in the data, or to what extent a model should be invariant to a given symmetry group. We show how to \emph{learn} invariances and equivariances by parameterizing a distribution over

Sparsh Sharma, Thomas F. Geyer, Jens Giesler

This paper investigates the effect of the geometric parameters -- rod diameter and the distance between the rod and the airfoil -- on the noise generated by rod-airfoil configuration using experimental and numerical techniques. The numerical simulations are carried out using the low-dissipation up-wind scheme and the Delayed-Detached-Eddy Simulation (DDES) a

Fabio Tonini

Given a quasi-compact category fibered in groupoids $\mathcal{X}$ and a monoidal subcategory $\mathcal{C}$ of its category of locally free sheaves $\text{Vect}(\mathcal{X})$, we are going to introduce the stack of fiber functors $\text{Fib}_{\mathcal{X},\mathcal{C}}$ with source $\mathcal{C}$, which comes equipped with a map $\mathcal{P}_{\mathcal{C}}\colon\

Renchi Yang, Xiaokui Xiao

Given a graph $G$ with $n$ nodes and two nodes $u,v\in G$, the {\em CoSimRank} value $s(u,v)$ quantifies the similarity between $u$ and $v$ based on graph topology. Compared to SimRank, CoSimRank is shown to be more accurate and effective in many real-world applications, including synonym expansion, lexicon extraction, and entity relatedness in knowledge gra

Jose Carlos Diaz-Ramos, Miguel Dominguez-Vazquez, Takahiro Hashinaga

We classify holomorphic isometric actions on complex space forms all whose orbits are Lagrangian submanifolds, up to orbit equivalence. The only examples are Lagrangian affine subspace foliations of complex Euclidean spaces, and Lagrangian horocycle foliations of complex hyperbolic spaces.

Yochai Yemini, Ethan Fetaya, Haggai Maron, Sharon Gannot

Neural networks (NNs) have been widely applied in speech processing tasks, and, in particular, those employing microphone arrays. Nevertheless, most existing NN architectures can only deal with fixed and position-specific microphone arrays. In this paper, we present an NN architecture that can cope with microphone arrays whose number and positions of the mic

Homin Lee

We prove that any smooth volume-preserving action of a lattice $\Gamma$ in $\textrm{SL}(n,\mathbb{R})$, $n\ge 3$, on a closed $n$-manifold which possesses one element that admits a dominated splitting should be standard. In other words, the manifold is the $n$-flat torus and the action is smoothly conjugate to an affine action. Note that an Anosov diffeomorp

Mohammed Mouçouf

Using $\mathcal{P}$-canonical forms of matrices, we derive the minimal polynomial of the Kronecker product of a given family of matrices in terms of the minimal polynomials of these matrices. This, allows us to prove that the product $\prod\limits_{i=1}^{m}L(P_{i})$, $L(P_{i})$ is the set of linear recurrence sequences over a field $F$ with characteristic po

Robert Laugwitz, Chelsea Walton

This paper is a contribution to the construction of non-semisimple modular categories. We establish when M\"uger centralizers inside non-semisimple modular categories are also modular. As a consequence, we obtain conditions under which relative monoidal centers give (non-semisimple) modular categories, and we also show that examples include representation ca

Hideyuki Tachibana

In neural network-based monaural speech separation techniques, it has been recently common to evaluate the loss using the permutation invariant training (PIT) loss. However, the ordinary PIT requires to try all $N!$ permutations between $N$ ground truths and $N$ estimates. Since the factorial complexity explodes very rapidly as $N$ increases, a PIT-based tra

Lei Xu, Ivan Ramirez, Kalyan Veeramachaneni

Most adversarial attack methods that are designed to deceive a text classifier change the text classifier's prediction by modifying a few words or characters. Few try to attack classifiers by rewriting a whole sentence, due to the difficulties inherent in sentence-level rephrasing as well as the problem of setting the criteria for legitimate rewriting. In th

Jacob L. Bean, Sean N. Raymond, James E. Owen

Planets intermediate in size between the Earth and Neptune, and orbiting closer to their host stars than Mercury does the Sun, are the most common type of planet revealed by exoplanet surveys over the last quarter century. Results from NASA's Kepler mission have revealed a bimodality in the radius distribution of these objects, with a relative underabundance

Sabit Bekov, Kairat Myrzakulov, Ratbay Myrzakulov, Diego Sáez-Chillón Gómez

Slow-roll inflation is analyzed in the context of modified gravity within the Palatini formalism. As shown in the literature, inflation in this framework requires the presence of non-traceless matter, otherwise it does not occur just as a consequence of the non-linear gravitational terms of the action. Nevertheless, by including a single scalar field that pl

Alejandro G. Calvet, Mukul Dave, Jennifer A. Franck

An unsupervised machine learning strategy is developed to automatically cluster the vortex wakes of bio-inspired propulsors into groups of similar propulsive thrust and efficiency metrics. A pitching and heaving foil is simulated via computational fluid dynamics with $121$ unique kinematics by varying the frequency, heaving amplitude, and pitching amplitude.

Yairon Cid-Ruiz, Jonathan Montaño

We show the existence (and define) the mixed multiplicities of arbitrary graded families of ideals under mild assumptions. In particular, our methods and results are valid for the case of arbitrary $\mathfrak{m}$-primary graded families. Furthermore, we provide a far-reaching "Volume = Multiplicity formula" for the mixed multiplicities of graded families of

Malú Grave, Alvaro L. G. A. Coutinho

The outbreak of COVID-19 in 2020 has led to a surge in the interest in the mathematical modeling of infectious diseases. Disease transmission may be modeled as compartmental models, in which the population under study is divided into compartments and has assumptions about the nature and time rate of transfer from one compartment to another. Usually, they are

Nikolay Bogoychev

Transformers are widely used in state-of-the-art machine translation, but the key to their success is still unknown. To gain insight into this, we consider three groups of parameters: embeddings, attention, and feed forward neural network (FFN) layers. We examine the relative importance of each by performing an ablation study where we initialise them at rand

Akari Asai, Jungo Kasai, Jonathan H. Clark, Kenton Lee

Multilingual question answering tasks typically assume answers exist in the same language as the question. Yet in practice, many languages face both information scarcity -- where languages have few reference articles -- and information asymmetry -- where questions reference concepts from other cultures. This work extends open-retrieval question answering to

Pratik Jawanpuria, N T V Satyadev, Bamdev Mishra

Optimal transport (OT) is a powerful geometric tool for comparing two distributions and has been employed in various machine learning applications. In this work, we propose a novel OT formulation that takes feature correlations into account while learning the transport plan between two distributions. We model the feature-feature relationship via a symmetric

Samuel I. Watson

Clusters form the basis of a number of research study designs including survey and experimental studies. Cluster-based designs can be less costly but also less efficient than individual-based designs due to correlation between individuals within the same cluster. Their design typically relies on \textit{ad hoc} choices of correlation parameters, and is insen

A. P. Vinogradov, V. Yu. Shishkov, I. V. Doronin, E. S. Andrianov

We develop a quantum theory of atomic Rayleigh scattering. Scattering is considered as a relaxation of incident photons from a selected mode of free space to the reservoir of the other free space modes. Additional excitations of the reservoir states which appear are treated as scattered light. We show that an entangled state of the excited atom and the incid

Philipp Brockmann, Jeanette Hussong

In the present study we demonstrate for the first time how Astigmatism Particle Tracking Velocimetry (APTV) can be utilized to measure suspensions dynamics. Measurements were successfully performed in monodisperse, refractive index matched suspensions of up to a volume fraction of $\Phi=19.9\%$. For this, a small percentage of the particles is labeled with f