December 2020 arXiv papers — page 138

Simin Nie, Yuting Qian, Jiacheng Gao, Zhong Fang

The recently developed theory of topological quantum chemistry (TQC) has built a close connection between band representations in momentum space and orbital characters in real space. It provides an effective way to diagnose topological materials, leading to the discovery of lots of topological materials after the screening of all known nonmagnetic compounds.

Qi-Yu Liang, Dimitris Trypogeorgos, Ana Valdés-Curiel, Junheng Tao

We quantum-simulated the 2D Harper-Hofstadter (HH) lattice model in a highly elongated tube geometry -- three sites in circumference -- using an atomic Bose-Einstein condensate. In addition to the usual transverse (out-of-plane) magnetic flux, piercing the surface of the tube, we threaded a longitudinal flux $Φ_{\rm L}$ down the axis of the tube This geometr

Corentin Cadiou, Andrew Pontzen, Hiranya V. Peiris

The angular momentum of dark matter haloes controls their spin magnitude and orientation, which in turn influences the galaxies therein. However, the process by which dark matter haloes acquire angular momentum is not fully understood; in particular, it is unclear whether angular momentum growth is stochastic. To address this question, we extend the genetic

Liliana Apolinário, André Cordeiro, Korinna Zapp

The physics program of ultra-relativistic heavy-ion collisions at the Large Hadron Collider (LHC) and Relativistic Heavy-Ion Collider (RHIC) has brought a unique insight into the hot and dense QCD matter created in such collisions, the Quark-Gluon Plasma (QGP). Jet quenching, a collection of medium-induced modifications of the jets' internal structure th

Michael Zhang, Heather A. Knutson, Lile Wang, Fei Dai

We search for escaping helium from the hot super Earth 55 Cnc e by taking high-resolution spectra of the 1083 nm line during two transits using Keck/NIRSPEC. We detect no helium absorption down to a 90\% upper limit of 250 ppm in excess absorption or 0.27 milli-Angstrom in equivalent width. This corresponds to a mass loss rate of less than $\sim10^9$ g/s ass

Alex Yu, Vickie Ye, Matthew Tancik, Angjoo Kanazawa

We propose pixelNeRF, a learning framework that predicts a continuous neural scene representation conditioned on one or few input images. The existing approach for constructing neural radiance fields involves optimizing the representation to every scene independently, requiring many calibrated views and significant compute time. We take a step towards resolv

Matthew Tancik, Ben Mildenhall, Terrance Wang, Divi Schmidt

Coordinate-based neural representations have shown significant promise as an alternative to discrete, array-based representations for complex low dimensional signals. However, optimizing a coordinate-based network from randomly initialized weights for each new signal is inefficient. We propose applying standard meta-learning algorithms to learn the initial w

Paul D. Nelson

Let $(\pi,\sigma)$ traverse a sequence of pairs of cuspidal automorphic representations of a unitary Gan--Gross--Prasad pair $({\rm U}_{n+1},{\rm U}_n)$ over a number field, with ${\rm U}_n$ anisotropic. We assume that at some distinguished archimedean place, the pair stays away from the conductor dropping locus, while at every other place, the pair has boun

Bianka Mecaj, Matthias Neubert

Leptoquarks enter in several extensions of the Standard Model as possible solutions to a number of observed anomalies. We work within the soft-collinear effective theory framework to present a detailed analysis of the decay rates of the three leptoquarks that appear the most in literature, the scalars $S_1$ and $S_3$ and the vector $U_1^{\mu}$. Using renorma

Jakub Jankowski, Syo Kamata, Mauricio Martinez, Michał Spaliński

It is frequently supposed that quark-gluon plasma created in heavy-ion collisions undergoes free streaming at early times. We examine this issue based on the assumption that a universal attractor dominates the dynamics already at the earliest stages, which offers a way to connect the initial state with the start of the hydrodynamic expansion in an approximat

Evgeny A. Bespalov, Denis S. Krotov

Extended $1$-perfect codes in the Hamming scheme $H(n,q)$ can be equivalently defined as codes that turn to $1$-perfect codes after puncturing in any coordinate, as completely regular codes with certain intersection array, as uniformly packed codes with certain weight coefficients, as diameter perfect codes with respect to a certain anticode, as distance-$4$

V. Fernández Becerra, Mircea Trif, Timo Hyart

Spin pumping consists in the injection of spin currents into a non-magnetic material due to the precession of an adjacent ferromagnet. In addition to the pumping of spin the precession always leads to pumping of heat, but in the presence of spin-orbital entanglement it also leads to a charge current. We investigate the pumping of charge, spin and heat in a d

Kelvin C. K. Chan, Xintao Wang, Ke Yu, Chao Dong

Video super-resolution (VSR) approaches tend to have more components than the image counterparts as they need to exploit the additional temporal dimension. Complex designs are not uncommon. In this study, we wish to untangle the knots and reconsider some most essential components for VSR guided by four basic functionalities, i.e., Propagation, Alignment, Agg

Veit Elser

Recent experiments by Springer and Kenyon have shown that a deep neural network can be trained to predict the action of $t$ steps of Conway's Game of Life automaton given millions of examples of this action on random initial states. However, training was never completely successful for $t>1$, and even when successful, a reconstruction of the elementary r

George K. Atia, Andre Beckus, Ismail Alkhouri, Alvaro Velasquez

The planning domain has experienced increased interest in the formal synthesis of decision-making policies. This formal synthesis typically entails finding a policy which satisfies formal specifications in the form of some well-defined logic. While many such logics have been proposed with varying degrees of expressiveness and complexity in their capacity to

Arda Düzçeker, Silvano Galliani, Christoph Vogel, Pablo Speciale

We propose an online multi-view depth prediction approach on posed video streams, where the scene geometry information computed in the previous time steps is propagated to the current time step in an efficient and geometrically plausible way. The backbone of our approach is a real-time capable, lightweight encoder-decoder that relies on cost volumes computed

Martin Müller, Marcel Salathé

Social media analysis has become a common approach to assess public opinion on various topics, including those about health, in near real-time. The growing volume of social media posts has led to an increased usage of modern machine learning methods in natural language processing. While the rapid dynamics of social media can capture underlying trends quickly

Josef Schlittenlacher, Thomas Baer

Text-to-speech (TTS) systems offer the opportunity to compensate for a hearing loss at the source rather than correcting for it at the receiving end. This removes limitations such as time constraints for algorithms that amplify a sound in a hearing aid and can lead to higher speech quality. We propose an algorithm that restores loudness to normal perception

Phanuel Mariano, Hugo Panzo

We prove a central limit theorem (CLT) for the product of a class of random singular matrices related to a random Hill's equation studied by Adams$\unicode{x2013}$Bloch$\unicode{x2013}$Lagarias. The CLT features an explicit formula for the variance in terms of the distribution of the matrix entries and this allows for exact calculation in some examples.

Abhishek Kumar, Colin Benjamin

One can use light to tune certain materials, from a trivial to a topological phase. A prime example of such materials, classified as Floquet topological insulators (FTI), is epitaxial graphene. In this paper, we probe the topological phase transition of an FTI via the efficiency and work output of quantum Otto and quantum Stirling heat engines. A maximum/min

Jo Bovy

Klioner et al. have used the Gaia EDR3 data to directly measure the solar system's acceleration within the Milky Way using the apparent proper motions of quasars. Here I show that this single absolute acceleration measurement in combination with relative accelerations obtained from pulsar orbital decay allows one to determine all of the parameters descri

Axel Osmond

This second part comes to the construction of the spectrum associated to a situation of multi-adjunction. Exploiting a geometric understanding of its multi-versal property, the spectrum of an object is obtained as the spaces of local units equipped with a topology provided by orthogonality aspects. After recalling Diers original construction, this paper intr

Hanjia Lyu, Junda Wang, Wei Wu, Viet Duong

The current development of vaccines for SARS-CoV-2 is unprecedented. Little is known, however, about the nuanced public opinions on the vaccines on social media. We adopt a human-guided machine learning framework using more than six million tweets from almost two million unique Twitter users to capture public opinions on the potential vaccines for SARS-CoV-2

Mirela Silva, Fabrício Ceschin, Prakash Shrestha, Christopher Brant

Misinformation entails the dissemination of falsehoods that leads to the slow fracturing of society via decreased trust in democratic processes, institutions, and science. The public has grown aware of the role of social media as a superspreader of untrustworthy information, where even pandemics have not been immune. In this paper, we focus on COVID-19 misin

Brian Kim, Yalin E. Sagduyu, Tugba Erpek, Kemal Davaslioglu

We consider a wireless communication system that consists of a background emitter, a transmitter, and an adversary. The transmitter is equipped with a deep neural network (DNN) classifier for detecting the ongoing transmissions from the background emitter and transmits a signal if the spectrum is idle. Concurrently, the adversary trains its own DNN classifie

John Haslegrave, Jaehoon Kim, Hong Liu

We prove an asymptotically tight bound on the extremal density guaranteeing subdivisions of bounded-degree bipartite graphs with a mild separability condition. As corollaries, we answer several questions of Reed and Wood on embedding sparse minors. Among others, $\bullet$ $(1+o(1))t^2$ average degree is sufficient to force the $t\times t$ grid as a topologic

Valentin Burcea

It is constructed a Formal Normal Form for a Special Class of Real-Smooth Submanfolds in $\mathbb{C}^{2N}$.

Kristian Bjørn Hessellund, Ganggang Xu, Yongtao Guan, Rasmus Waagepetersen

This paper introduces a new approach to inferring the second order properties of a multivariate log Gaussian Cox process (LGCP) with a complex intensity function. We assume a semi-parametric model for the multivariate intensity function containing an unspecified complex factor common to all types of points. Given this model we exploit the availability of sev

Kartik Singhal

As quantum computers become real, it is high time we come up with effective techniques that help programmers write correct quantum programs. Inspired by Hoare Type Theory in classical computing, we propose Quantum Hoare Type Theory (QHTT), in which precise specifications about the modification to the quantum state can be provided within the type of computati

Tanmoy Bhattacharya, Alexander J. Buser, Shailesh Chandrasekharan, Rajan Gupta

We provide strong evidence that the asymptotically free (1+1)-dimensional non-linear O(3) sigma model can be regularized using a quantum lattice Hamiltonian, referred to as the "Heisenberg-comb", that acts on a Hilbert space with only two qubits per spatial lattice site. The Heisenberg-comb consists of a spin-half anti-ferromagnetic Heisenberg-chain

Paul Maxwell, David Niblick, Daniel C. Ruiz

Cybersecurity continues to be a difficult issue for society especially as the number of networked systems grows. Techniques to protect these systems range from rules-based to artificial intelligence-based intrusion detection systems and anti-virus tools. These systems rely upon the information contained in the network packets and download executables to func

Tiffany Yau, Saber Malekmohammadi, Amir Rasouli, Peter Lakner

One of the most crucial yet challenging tasks for autonomous vehicles in urban environments is predicting the future behaviour of nearby pedestrians, especially at points of crossing. Predicting behaviour depends on many social and environmental factors, particularly interactions between road users. Capturing such interactions requires a global view of the s

V. Pierro, V. Fiumara, F. Chiadini, V. Granata

Multimaterial optical coatings are a promising viable option to meet the challenging requirements (in terms of transmittance, absorbance and thermal noise) of next generation gravitational wave detector mirrors. In this paper we focus on ternary coatings consisting of quarter-wavelength thick layers, where a third material (H') is added to the two presen

Riccardo Muolo, Timoteo Carletti, James P. Gleeson, Malbor Asllani

Synchronization is an important behavior that characterizes many natural and human made systems composed by several interacting units. It can be found in a broad spectrum of applications, ranging from neuroscience to power-grids, to mention a few. Such systems synchronize because of the complex set of coupling they exhibit, the latter being modeled by comple

Vasco Brattka

Matthias Schr\"oder has asked the question whether there is a weakest discontinuous problem in the continuous version of the Weihrauch lattice. Such a problem can be considered as the weakest unsolvable problem. We introduce the discontinuity problem, and we show that it is reducible exactly to the effectively discontinuous problems, defined in a suitable wa

Matheus Hostert, Maxim Pospelov

We point out kaon decays to multiple charged leptons as a novel probe of light dark particles $X$. Previously neglected channels, such as $K^+\to π^+ \left(XX \to 2(e^+e^-)\right)$, $K_L\to π^0 \left( XX \to 2(e^+e^-)\right)$, and $K_S\to \left(XX \to 2(e^+e^-)\right)$ may have very large rates, exceeding not only the Standard Model expectations but also pos

J. V. Gomes, M. C. de Sousa, R. L. Viana, I. L. Caldas

We analyze nonlinear aspects of the self-consistent wave-particle interaction using Hamiltonian dynamics in the single wave model, where the wave is modified due to the particle dynamics. This interaction plays an important role in the emergence of plasma instabilities and turbulence. The simplest case, where one particle (N = 1) is coupled with one wave (M

Hendrik Roch, Nicolas Borghini

We investigate the fluctuations of anisotropic transverse flow due to the finite number of scatterings in a two-dimensional system of massless particles. Using a set of initial geometries from a Monte Carlo Glauber model, we study how flow coefficients fluctuate about their mean value at the corresponding eccentricity, for several values of the scattering cr

Soumya Sankar, Libby Taylor

We study derived equivalences of certain stacks over genus $1$ curves, which arise as connected components of the Picard stack of a genus $1$ curve. To this end, we develop a theory of integral transforms for these algebraic stacks. We use this theory to answer the question of when two stacky genus $1$ curves are derived equivalent. We use integral transform

Pranay Tankala, Abiy Tasissa, James M. Murphy, Demba Ba

We propose K-Deep Simplex(KDS) which, given a set of data points, learns a dictionary comprising synthetic landmarks, along with representation coefficients supported on a simplex. KDS employs a local weighted $\ell_1$ penalty that encourages each data point to represent itself as a convex combination of nearby landmarks. We solve the proposed optimization p

Tianfang Zhang, Rasmus Bokrantz, Jimmy Olsson

We present a new nonparametric mixture-of-experts model for multivariate regression problems, inspired by the probabilistic k-nearest neighbors algorithm. Using a conditionally specified model, predictions for out-of-sample inputs are based on similarities to each observed data point, yielding predictive distributions represented by Gaussian mixtures. Poster

Lianna A. Akopyan, Dmitrii A. Trunin

Nonlinear terms in the equations of motion can induce secularly growing loop corrections to correlation functions. Recently such corrections were shown to affect the particle production by a nonuniformly moving ideal mirror. We extend this conclusion to the cases of ideal vibrating cavity and single semitransparent mirror. These models provide natural IR and

Walter O. Krawec, Rotem Liss, Tal Mor

Semiquantum key distribution (SQKD) allows two parties (Alice and Bob) to create a shared secret key, even if one of these parties (say, Alice) is classical. However, most SQKD protocols suffer from severe practical security problems when implemented using photons. The recently developed "Mirror protocol" [Boyer, Katz, Liss, and Mor, Phys. Rev. A 96, 062335

Nicolas Dirr, Benjamin Fehrman, Benjamin Gess

In this paper, we provide a continuum model for the fluctuations of the symmetric simple exclusion process about its hydrodynamic limit. The model is based on an approximating sequence of stochastic PDEs with nonlinear, conservative noise. In the small-noise limit, we show that the fluctuations of the solutions are to first-order the same as the fluctuations

Vidya Muthukumar, Soham Phade, Anant Sahai

We study the limiting behavior of the mixed strategies that result from optimal no-regret learning strategies in a repeated game setting where the stage game is any 2 by 2 competitive game. We consider optimal no-regret algorithms that are mean-based and monotonic in their argument. We show that for any such algorithm, the limiting mixed strategies of the pl

Hazem Rashed, Eslam Mohamed, Ganesh Sistu, Varun Ravi Kumar

Object detection is a comprehensively studied problem in autonomous driving. However, it has been relatively less explored in the case of fisheye cameras. The standard bounding box fails in fisheye cameras due to the strong radial distortion, particularly in the image's periphery. We explore better representations like oriented bounding box, ellipse, and gen

Tommaso Marchetti

The early third data release (EDR3) of the European Space Agency satellite Gaia provides coordinates, parallaxes, and proper motions for ~1.47 billion sources in our Milky Way, based on 34 months of observations. The combination of Gaia DR2 radial velocities with the more precise and accurate astrometry provided by Gaia EDR3 makes the best dataset available

Nir Keret, Malka Gorfine

Massive sized survival datasets are becoming increasingly prevalent with the development of the healthcare industry. Such datasets pose computational challenges unprecedented in traditional survival analysis use-cases. A popular way for coping with massive datasets is downsampling them to a more manageable size, such that the computational resources can be a

R. Frezzotti, M. Garofalo, V. Lubicz, G. Martinelli

We present a comparison of existing experimental data for the radiative leptonic decays $P\to\ellν_\ellγ$, where $P=K$ or $π$ and $\ell=e$ or $μ$, from the KLOE, PIBETA, E787, ISTRA+ and OKA collaborations with theoretical predictions based on the recent non-perturbative determinations of the structure-dependent vector and axial-vector form factors, $F_V$ an

Ainesh Bakshi, Ilias Diakonikolas, He Jia, Daniel M. Kane

We give a polynomial-time algorithm for the problem of robustly estimating a mixture of $k$ arbitrary Gaussians in $\mathbb{R}^d$, for any fixed $k$, in the presence of a constant fraction of arbitrary corruptions. This resolves the main open problem in several previous works on algorithmic robust statistics, which addressed the special cases of robustly est

Miguel Pérez-Torres, José Francisco Gómez, José Luis Ortiz, Paolo Leto

We present results from the most comprehensive radio monitoring campaign towards the closest star to our Sun, Proxima Centauri. We report 1.1 to 3.1 GHz observations with the Australian Telescope Compact Array over 18 consecutive days in April 2017. We detect radio emission from Proxima Centauri for most of the observing sessions, which spanned $\sim$1.6 orb

Tom Leinster

This book brings new mathematical rigour to the ongoing vigorous debate on how to quantify biological diversity. The question "what is diversity?" has surprising mathematical depth, and breadth too: this book involves parts of mathematics ranging from information theory, functional equations and probability theory to category theory, geometric measure theory

Marta Maria Marchese, Alessio Belenchia, Stefano Pirandola, Mauro Paternostro

Quantum Hypothesis Testing has shown the advantages that quantum resources can offer in the discrimination of competing hypothesis. Here, we apply this framework to optomechanical systems and fundamental physics questions. In particular, we focus on an optomechanical system composed of two cavities employed to perform quantum channel discrimination. We show

Tae Soo Kim, Gregory D. Hager

We present a general framework for compositional action recognition -- i.e. action recognition where the labels are composed out of simpler components such as subjects, atomic-actions and objects. The main challenge in compositional action recognition is that there is a combinatorially large set of possible actions that can be composed using basic components

Ritwik Gupta, Eric T. Heim, Edoardo Nemni

These are the "proceedings" of the 2nd AI + HADR workshop which was held virtually on December 12, 2020 as part of the Neural Information Processing Systems conference. These are non-archival and merely serve as a way to collate all the papers accepted to the workshop.

Xiaoding Yuan, Adam Kortylewski, Yihong Sun, Alan Yuille

Analyzing complex scenes with Deep Neural Networks is a challenging task, particularly when images contain multiple objects that partially occlude each other. Existing approaches to image analysis mostly process objects independently and do not take into account the relative occlusion of nearby objects. In this paper, we propose a deep network for multi-obje

Benjamin Paassen, Irena Koprinska, Kalina Yacef

Machine learning on trees has been mostly focused on trees as input to algorithms. Much less research has investigated trees as output, which has many applications, such as molecule optimization for drug discovery, or hint generation for intelligent tutoring systems. In this work, we propose a novel autoencoder approach, called recursive tree grammar autoenc

Michael Dennis, Natasha Jaques, Eugene Vinitsky, Alexandre Bayen

A wide range of reinforcement learning (RL) problems - including robustness, transfer learning, unsupervised RL, and emergent complexity - require specifying a distribution of tasks or environments in which a policy will be trained. However, creating a useful distribution of environments is error prone, and takes a significant amount of developer time and ef

R. G. Forbes, E. O. Popov, A. G. Kolosko, S. V. Filippov

For field electron emission (FE), an empirical equation for measured current I_m as a function of measured voltage V_m has the form I_m = C*(V_m)^k*exp[-B/(V_m)], where B is a constant and C and k are constants or vary weakly with V_m. Values for k can be extracted (a) from simulations based on some specific FE theory, and in principle (b) from current-volta

Admir Greljo, Nudzeim Selimovic

When a TeV-scale leptoquark has a sizeable Yukawa coupling, its dominant production mechanism at hadron colliders is the partonic-level lepton-quark fusion. Even though the parton distribution functions for leptons inside the proton are minuscule, they get compensated by the resonant enhancement. We present the first computation of higher order radiative cor

Kisung Kang, Kexin Yang, Krithik Puthalath, David G. Cahill

Antiferromagnetic metals attract tremendous interest for memory applications due to their expected fast response dynamics in the terahertz frequency regime. Reading from and writing information into these materials is not easily achievable using magnetic fields, due to weak high-order magneto-optical signals and robustness of the magnetic structure against e

Ivan Arzhantsev, Roman Avdeev

Given a connected reductive algebraic group $G$ and a Borel subgroup $B \subseteq G$, we study $B$-normalized one-parameter additive group actions on affine spherical $G$-varieties. We establish basic properties of such actions and their weights and discuss many examples exhibiting various features. We propose a construction of such actions that generalizes

Mohamed Sayed, Robert Cinca, Enrico Costanza, Gabriel Brostow

The job of a camera operator is challenging, and potentially dangerous, when filming long moving camera shots. Broadly, the operator must keep the actors in-frame while safely navigating around obstacles, and while fulfilling an artistic vision. We propose a unified hardware and software system that distributes some of the camera operator's burden, freeing t

Martin Bullinger, Warut Suksompong, Alexandros A. Voudouris

Schelling's model is an influential model that reveals how individual perceptions and incentives can lead to residential segregation. Inspired by a recent stream of work, we study welfare guarantees and complexity in this model with respect to several welfare measures. First, we show that while maximizing the social welfare is NP-hard, computing an assignmen

Gabriele Grillo, Giulia Meglioli, Fabio Punzo

We consider the porous medium equation with a power-like reaction term, posed on Riemannian manifolds. Under certain assumptions on $p$ and $m$ in (1.1), and for small enough nonnegative initial data, we prove existence of global in time solutions, provided that the Sobolev inequality holds on the manifold. Furthermore, when both the Sobolev and the Poincaré

Zohreh Davoudi, Saurabh V. Kadam

Neutrinoless double-$β$ ($0νββ$) decay of certain atomic isotopes, if observed, will have significant implications for physics of neutrinos and models of physics beyond the Standard Model. In the simplest scenario, if the mass of the light neutrino of the Standard Model has a Majorana component, it can mediate the decay. Systematic theoretical studies of the

Zhongzheng Xiong, Jialin Sun, Xiaojun Mao, Jian Wang

Recent years, local differential privacy (LDP) has been adopted by many web service providers like Google \cite{erlingsson2014rappor}, Apple \cite{apple2017privacy} and Microsoft \cite{bolin2017telemetry} to collect and analyse users' data privately. In this paper, we consider the problem of discrete distribution estimation under local differential privacy c

O. Gamayun, N. Iorgov, Yu. Zhuravlev

We introduce effective form factors for one-dimensional lattice fermions with arbitrary phase shifts. We study tau functions defined as series of these form factors. On the one hand we perform the exact summation and present tau functions as Fredholm determinants in the thermodynamic limit. On the other hand simple expressions of form factors allow us to pre

Ben Green, Aled Walker

We prove that if $A \subseteq [X, 2X]$ and $B \subseteq [Y, 2Y]$ are sets of integers such that $\gcd(a,b) \geq D$ for at least $δ|A||B|$ pairs $(a,b) \in A \times B$ then $|A||B| \ll_{\varepsilon} δ^{-2 - \varepsilon} XY/D^2$. This is a new result even when $δ= 1$. The proof uses ideas of Koukoulopoulos and Maynard and some additional combinatorial argument

Eduardo Rodriguez, Amitava Bhattacharjee

The stellarator as a concept of magnetic confinement fusion requires careful design to confine particles effectively. A design possibility is to equip the magnetic field with a property known as quasisymmetry. Though it is generally believed that a steady-state quasisymmetric equilibrium can only be exact locally (unless the system has a direction of continu

Jinhuan Duan, Xianxian Li, Shiqi Gao, Jinyan Wang

With the vigorous development of artificial intelligence technology, various engineering technology applications have been implemented one after another. The gradient descent method plays an important role in solving various optimization problems, due to its simple structure, good stability and easy implementation. In multi-node machine learning system, the

Xinyue Qi, Shouhao Zhou, Martyn Plummer

Just Another Gibbs Sampling (JAGS) is a convenient tool to draw posterior samples using Markov Chain Monte Carlo for Bayesian modeling. However, the built-in function dinterval() to model censored data misspecifies the computation of deviance function, which may limit its usage to perform likelihood based model comparison. To establish an automatic approach

Andreas Karch, Zhu-Xi Luo, Hao-Yu Sun

We extend the holographic duality between 3d pure gravity and the 2d Ising CFT proposed in [Phys. Rev. D 85 (2012) 024032] to CFTs with boundaries. Besides the usual asymptotic boundary, the dual bulk spacetime now has a real cutoff, on which live branes with finite tension, giving Neumann boundary condition on the metric tensor. The strongly coupled bulk th

Antoine Honet, Luc Henrard, Vincent Meunier

A computationally efficient Green's function approach is developed to evaluate the optical properties of nanostructures using a GW formalism applied on top of a tight-binding and mean-field Hubbard model. The use of the GW approximation includes key parts of the many-body physics that govern the optical response of nanostructures and molecules subjected to a

Víctor Blanco, Ricardo Gázquez, Marina Leal

In this paper we provide a mathematical programming based decision tool to optimally reallocate and share equipments between different units in emergency situations under lack of resources. The approach is motivated by the COVID-19 pandemic in which many Heath National Systems were not able to satisfy the demand of ventilators, sanitary individual protection

Anibal M. Medina-Mardones, Andrea Pizzi, Paolo Salvatore

This paper presents a generalization to multisimplicial sets of previously defined $E_\infty$-coalgebra structures on the chains of simplicial and cubical sets. We focus on the surjection chain complexes of McClure--Smith as a main example and construct a zig-zag of complexity preserving quasi-isomorphisms of $E_\infty$-coalgebras relating these to both the

Connor Armstrong, Arthur E. Lipstein, Jiajie Mei

In flat space, the color/kinematics duality states that perturbative Yang-Mills amplitudes can be written in such a way that kinematic numerators obey the same Jacobi relations as their color factors. This remarkable duality implies BCJ relations for Yang-Mills amplitudes and underlies the double copy to gravitational amplitudes. In this paper, we find analo

Jinbang Yang, Kang Zuo

Given a proper smooth $p$-adic variety, we show a comparison theorem for the $p$-adic Simpson correspondence constructed by Faltings and Riemann-Hilbert correspondence constructed by Scholze. As an application we formulate a sufficient condition for $\overline{\mathbb Q}_p$-local system being de Rham. We study a $p$-adic analogue of Simpson's $\mathbb C^

Andrzej Grzesik, Joonkyung Lee, Bernard Lidický, Jan Volec

A graph H is common if the number of monochromatic copies of H in a 2-edge-colouring of the complete graph is minimised by the random colouring. Burr and Rosta, extending a famous conjecture by Erdos, conjectured that every graph is common. The conjectures by Erdos and by Burr and Rosta were disproved by Thomason and by Sidorenko, respectively, in the late 1

Sathwik Bharadwaj, Ashwin Ramasubramaniam, L. R. Ram-Mohan

Increasing demands for renewable sources of energy has been a major driving force for developing efficient thermoelectric materials. Two-dimensional (2D) transition-metal dichalcogenides (TMDC) have emerged as promising candidates for thermoelectric applications due to their large effective mass and low thermal conductivity. In this article, we study the the

A. de Oliveira Junior, M. C de Oliveira

At the heart of quantum thermodynamics lies a fundamental question about what is genuine "quantum" in quantum heat engines and how to seek this quantumness, so that thermodynamical tasks could be performed more efficiently compared with classical protocols. Here, using the concept of $P$-representability, we define a function called classicality, which quant

Xingran Zhou, Bo Zhang, Ting Zhang, Pan Zhang

We present the full-resolution correspondence learning for cross-domain images, which aids image translation. We adopt a hierarchical strategy that uses the correspondence from coarse level to guide the fine levels. At each hierarchy, the correspondence can be efficiently computed via PatchMatch that iteratively leverages the matchings from the neighborhood.

Meike Nauta, Ron van Bree, Christin Seifert

Prototype-based methods use interpretable representations to address the black-box nature of deep learning models, in contrast to post-hoc explanation methods that only approximate such models. We propose the Neural Prototype Tree (ProtoTree), an intrinsically interpretable deep learning method for fine-grained image recognition. ProtoTree combines prototype

Lukas Burgholzer, Robert Wille, Richard Kueng

In this work, we consider error detection via simulation for reversible circuit architectures. We rigorously prove that reversibility augments the performance of this simple error detection protocol to a considerable degree. A single randomly generated input is guaranteed to unveil a single error with a probability that only depends on the size of the error,

Hiroki Kondo, Yutaka Akagi

We propose magnonic analogs of topological crystalline insulators which possess Dirac surface states protected by the combined symmetry of time-reversal and half translation. Constructing models of the topological magnon systems, we demonstrate that the energy current flows through the systems in response to an electric field, owing to the Dirac surface stat

Lyubov V. Kotova, Maxim V. Rakhlin, Aidar I. Galimov, Ilya A. Eliseyev

We investigated multilayer plates made by exfoliation from a high-quality MoS$_2$ crystal and reveal that they represent a new object - van der Waals homostructure consisting of a bulk core and a few detached monolayers on its surface. This architecture comprising elements with different electron band structure leads to specific luminescence, when the broad

Kenta Ando, Vincent Vennin

We compute the power spectrum of curvature perturbations in stochastic inflation. This combines the distribution of first crossing times through the end-of-inflation surface, which has been previously studied, with the distribution of the fields value at the time when a given scale crosses out the Hubble radius during inflation, which we show how to compute.

Antoine Marot, Alexandre Rozier, Matthieu Dussartre, Laure Crochepierre

Power grids are becoming more complex to operate in the digital age given the current energy transition to cope with climate change. As a result, real-time decision-making is getting more challenging as the human operator has to deal with more information, more uncertainty, more applications, and more coordination. While supervision has been primarily used t

Danton Freire-Flores, Nyna Llanovarced-Kawles, Anamaria Sanchez-Daza, Álvaro Olivera-Nappa

Non-pharmaceutical interventions (NPIs) have played a crucial role in controlling the spread of COVID-19. Nevertheless, NPI efficacy varies enormously between and within countries, mainly because of population and behavioural heterogeneity. In this work, we adapted a multi-group SEIRA model to study the spreading dynamics of COVID-19 in Chile, representing g

Vincent Guedj, Henri Guenancia, Ahmed Zeriahi

In this note, we investigate some regularity aspects for solutions of degenerate complex Monge-Ampère equations (DCMAE) on singular spaces. First, we study the Dirichlet problem for DCMAE on singular Stein spaces, showing a general continuity result. A consequence of our results is that Kähler-Einstein potentials are continuous at isolated singularities. Nex

Qi Zhang, Xiao-Huang Hu, Bing-Ran He, Jia-Lun Ping

With the discovery of some hidden-charm pentaquark resonances by the LHCb Collaboration, investigations of pentaquark states containing heavy quarks have aroused the interest of theorists. We study herein $qqq\bar{q}Q$ ($q = u$ or $d$, $Q=c$ or $b$) pentaquark system, in the framework of the chiral quark model. In consequence, some charmed and bottomed penta

R. A. Riffel, O. L. Dors, M. Armah, T. Storchi-Bergmann

We present maps for the electron temperature in the inner kpc of three luminous Seyfert galaxies: Mrk 79, Mrk 348, and Mrk 607 obtained from Gemini GMOS-IFU observations at spatial resolutions of 110-280 pc. We study the distributions of electron temperature in active galaxies and find temperatures varying in the range from 8000 to >30000 K. Shocks due to ga

Tomas Pippia, Jesus Lago, Roel De Coninck, Bart De Schutter

State-of-the-art Model Predictive Control (MPC) applications for building heating adopt either a deterministic controller together with a nonlinear model or a linearized model with a stochastic MPC controller. However, deterministic MPC only considers one single realization of the disturbances and its performance strongly depends on the quality of the foreca

Song Fang, Quanyan Zhu

In this paper, we analyze the fundamental stealthiness-distortion tradeoffs of linear Gaussian dynamical systems under data injection attacks using a power spectral analysis, whereas the Kullback-Leibler (KL) divergence is employed as the stealthiness measure. Particularly, we obtain explicit formulas in terms of power spectra that characterize analytically

Jiabao Zhang, Shenghua Liu, Wenting Hou, Siddharth Bhatia

How can we track synchronized behavior in a stream of time-stamped tuples, such as mobile devices installing and uninstalling applications in the lockstep, to boost their ranks in the app store? We model such tuples as entries in a streaming tensor, which augments attribute sizes in its modes over time. Synchronized behavior tends to form dense blocks (i.e.

R. Nourafkan, A. -M. S. Tremblay

Certain classes of strongly correlated systems promise high thermopower efficiency, but a full understanding of correlation effects on the Seebeck coefficient is lacking. This is partly due to limitations of Boltzmann-type approaches. One needs a formula for the thermopower that allows separate investigations of the kinetic and potential energy contributions

Basile Audoly, Claire Lestringant

We propose a method for deriving equivalent one-dimensional models for slender non-linear structures. The approach is designed to be broadly applicable, and can handle in principle finite strains, finite rotations, arbitrary cross-sections shapes, inhomogeneous elastic properties across the cross-section, arbitrary elastic constitutive laws (possibly with lo

Pablo Arratia, Matias Courdurier, Evelyn Cueva, Axel Osses

This second version of the manuscript includes, in the appendices, an erratum that points out an error on the published version and offers alternative results for the Lipschitz stability analysis of the backward heat propagation problem and its applications to light sheet fluorescence microscopy. Abstract of the first version: In this work, we study a Lipsch

John A. ZuHone, Maxim Markevitch, Rainer Weinberger, Paul Nulsen

Radio relics in galaxy clusters are extended synchrotron sources produced by cosmic-ray electrons in the $μ$G magnetic field. Many relics are found in the cluster periphery and have a cluster-centric, narrow arc-like shape, which suggests that the electrons are accelerated or re-accelerated by merger shock fronts propagating outward in the intracluster plasm

Dan Betea, Jérémie Bouttier, Harriet Walsh

We study two families of probability measures on integer partitions, which are Schur measures with parameters tuned in such a way that the edge fluctuations are characterized by a critical exponent different from the generic $1/3$. We find that the first part asymptotically follows a "higher-order analogue" of the Tracy-Widom GUE distribution, previo