January 2022 arXiv papers — page 123

Ting Hua, Yilin Shen, Changsheng Zhao, Yen-Chang Hsu

Domain classification is the fundamental task in natural language understanding (NLU), which often requires fast accommodation to new emerging domains. This constraint makes it impossible to retrain all previous domains, even if they are accessible to the new model. Most existing continual learning approaches suffer from low accuracy and performance fluctuat

Asei Inoue, Yusuke Kobayashi

We study the problem of efficiently and fairly allocating a set of indivisible goods among agents with identical and additive valuations for the goods. The objective is to maximize the Nash social welfare, which is the geometric mean of the agents' valuations. While maximizing the Nash social welfare is NP-hard, a PTAS for this problem is presented by Ng

Alessandro Paduano, Arash Bahramian, James C. A. Miller-Jones, Adela Kawka

The Galactic globular cluster NGC 3201 is the first Galactic globular cluster observed to host dynamically-confirmed stellar-mass black holes, containing two confirmed and one candidate black hole. This result indicates that globular clusters can retain black holes, which has important implications for globular cluster evolution. NGC 3201 has been observed a

Chinmay Ghosh, Subhadip Khan, Anirban Bandyopadhyay

In this paper we have studied the growth of meromorphic solutions of higher order homogeneous and non-homogeneous linear difference equations with entire and meromorphic coefficients. We have extended and improved some results of Zhou and Zheng (2017), Belaidi and Benkarouba (2019) by using (p,q)-order and (p,q)-type.

UJu Gim, YeongHyeon Park

Deep learning methods can classify various unstructured data such as images, language, and voice as input data. As the task of classifying anomalies becomes more important in the real world, various methods exist for classifying using deep learning with data collected in the real world. As the task of classifying anomalies becomes more important in the real

S. Ouahouah, J. Prados, T. Taleb, C. Benzaid

Several solutions have been proposed in the literature to address the Unmanned Aerial Vehicles (UAVs) collision avoidance problem. Most of these solutions consider that the ground controller system (GCS) determines the path of a UAV before starting a particular mission at hand. Furthermore, these solutions expect the occurrence of collisions based only on th

Jingwei Song, Mitesh Patel, Maani Ghaffari

This paper proposes a new image-based localization framework that explicitly localizes the camera/robot by fusing Convolutional Neural Network (CNN) and sequential images' geometric constraints. The camera is localized using a single or few observed images and training images with 6-degree-of-freedom pose labels. A Siamese network structure is adopted to

R. A. Addad, D. L. C. Dutra, M. Bagaa, T. Taleb

The use cases of the upcoming 5G mobile networks introduce new and complex user demands that will require support for fast reconfiguration of network resources. Software Defined Network (SDN) is a key technology that can address these requirements, as it decouples the control plane from the data plane of the network devices and logically centralizes the cont

Yuan Yao, Bei Ding, Jun Liu, Jinjing Liang

A special cross-tie (SCT) domain wall was discovered in the helimagnet MnCoSi alloy via the magnetic vector field tomography in Lorentz transmission electron microscopy (LTEM). Different to the traditional cross-tie (TCT) domain wall where the convergent/divergent magnetic moment configuration line up one by one, the relative large Bloch type sub-walls emerg

Ramón G. Plaza, José Manuel Valdovinos

This paper studies the dissipative structure of the system of equations that describes the motion of a compressible, isothermal, viscous-capillar fluid of Korteweg type in one space dimension. It is shown that the system satisfies the genuine coupling condition of Humpherys (J. Hyperbolic Differ. Equ. 2, 2005, no. 4, 963-974), which is, in turn, an extension

Hsi-An Pan, Eva Schinnerer, Annie Hughes, Adam Leroy

The relative distribution of molecular gas and star formation in galaxies gives insight into the physical processes and timescales of the cycle between gas and stars. In this work, we track the relative spatial configuration of CO and H$α$ emission at high resolution in each of our galaxy targets, and use these measurements to quantify the distributions of r

Guangshen Ma, Weston Ross, Patrick J. Codd

This paper focuses on a research problem of robotic controlled laser orientation to minimize errant overcutting of healthy tissue during the course of pathological tissue resection. Laser scalpels have been widely used in surgery to remove pathological tissue targets such as tumors or other lesions. However, different laser orientations can create various ti

Hieu Le, Hans Walker, Dung Tran, Peter Chin

Although deep neural networks have achieved great performance on classification tasks, recent studies showed that well trained networks can be fooled by adding subtle noises. This paper introduces a new approach to improve neural network robustness by applying the recovery process on top of the naturally trained classifier. In this approach, images will be i

Xu Feng, Taku Izubuchi, Luchang Jin, Maarten Golterman

We report a first principle lattice calculation of the pion electric polarizability $α_π$ at the physical pion mass. First, we derive the master formula, which relates the pion polarizabilities with the position space hadronic Compton tensor, $\langle π| J_μ(x) J_ν(0) | π\rangle$. The finite volume error of the master formula is exponentially suppressed by t

Martin A. Mojahed, Tomáš Brauner

We systematically explore the landscape of nonrelativistic effective field theories with a local $S$-matrix and enhanced symmetries and soft behavior. The exploration is carried out using both conventional quantum field theory methods based on symmetry arguments, and recently developed on-shell recursion relations. We show that, in contrary to relativistic t

F. Nisa Bostancı, Ataberk Olgun, Lois Orosa, A. Giray Yağlıkçı

Random number generation is an important task in a wide variety of critical applications including cryptographic algorithms, scientific simulations, and industrial testing tools. True Random Number Generators (TRNGs) produce truly random data by sampling a physical entropy source that typically requires custom hardware and suffers from long latency. To enabl

Yan Pang, Chao Liu

Dynamic graph neural networks have been widely used in modeling and representation learning of graph structure data. Current dynamic representation learning focuses on either discrete learning which results in temporal information loss or continuous learning that involves heavy computation. In this work, we proposed a novel dynamic graph neural network, Spar

Susana Mondschein, Felipe Subiabre, Natalia Yankovic, Camila Estay

Colorectal cancer (CRC) is the third most frequent malignant disease in the world. In some countries with established screening programs, its incidence and mortality have decreased, and survival has improved. AIMS: To obtain reliable data about the epidemiology of CRC in Chile, we analyzed the trends in the last ten years and the influence of observable fact

Mikhaylo Antipov, Danila Cherkashin

We apply the bound on independence number via Lov{\'a}sz theta function to eventown problem and its generalizations over $\mathbb{Z}_n$.

Blake Chellew, Timothy D. Brandt, Brandon S. Hensley, Bruce T. Draine

We present a spectrum of the diffuse Galactic light (DGL) between 3700 and 10,000 A, obtained by correlating optical sky intensity with far-infrared dust emission. We use nearly 250,000 blank-sky spectra from BOSS/SDSS-III together with IRIS-reprocessed maps from the IRAS satellite. The larger sample size compared to SDSS-II results in a factor-of-two increa

Niclas Bernhoff

The linearized collision operator of the Boltzmann equation for single species can be written as a sum of a positive multiplication operator, the collision frequency, and a compact integral operator. This classical result has more recently, been extended to multi-component mixtures and polyatomic single species with the polyatomicity modeled by a discrete in

Bibandhan Poudyal, Diogo Pacheco, Marcos Oliveira, Zexun Chen

Human travelling behaviours are markedly regular, to a large extent, predictable, and mostly driven by biological necessities (\eg sleeping, eating) and social constructs (\eg school schedules, synchronisation of labour). Not surprisingly, such predictability is influenced by an array of factors ranging in scale from individual (\eg preference, choices) and

Gino V. Graziano, Mohit Gupta, Mihir Pendharkar, Jason T. Dong

The Andreev bound state spectra of multi-terminal Josephson junctions form an artificial band structure, which is predicted to host tunable topological phases under certain conditions. However, the number of conductance modes between the terminals of multi-terminal Josephson junction must be few in order for this spectrum to be experimentally accessible. In

Wanli Xing, T. C. Ralph

We derive analytic solutions for Heisenberg evolution under the trilinear parametric Hamiltonian which are correct to second order in the interaction strength but are valid for all pump amplitudes. The solutions allow pump depletion effects to be incorporated in the description of parametric amplification in experimentally relevant scenarios and the resultin

Noel Jakse, Johannes Sandberg, Leon F. Granz, Anthony Saliou

In studying solidification process by simulations on the atomic scale, the modeling of crystal nucleation or amorphisation requires the construction of interatomic interactions that are able to reproduce the properties of both the solid and the liquid states. Taking into account rare nucleation events or structural relaxation under deep undercooling conditio

Sven Gronauer, Matthias Kissel, Luca Sacchetto, Mathias Korte

In this work, we propose a data-driven approach to optimize the parameters of a simulation such that control policies can be directly transferred from simulation to a real-world quadrotor. Our neural network-based policies take only onboard sensor data as input and run entirely on the embedded hardware. In extensive real-world experiments, we compare low-lev

Won Kyung Do, Monroe Kennedy

Increasing the performance of tactile sensing in robots enables versatile, in-hand manipulation. Vision-based tactile sensors have been widely used as rich tactile feedback has been shown to be correlated with increased performance in manipulation tasks. Existing tactile sensor solutions with high resolution have limitations that include low accuracy, expens

Yuhao Zhu

Neighbor search is of fundamental important to many engineering and science fields such as physics simulation and computer graphics. This paper proposes to formulate neighbor search as a ray tracing problem and leverage the dedicated ray tracing hardware in recent GPUs for acceleration. We show that a naive mapping under-exploits the ray tracing hardware. We

Niclas Bernhoff

The linearized collision operator of the Boltzmann equation can in a natural way be written as a sum of a positive multiplication operator, the collision frequency, and an integral operator. Compactness of the integral operator for monatomic single species is a classical result, while corresponding result for mixtures is more recently obtained. In this work

James M Parks

The objective here is to find the maximum polygon, in area, which can be enclosed in a given triangle, for the polygons: parallelograms, rectangles and squares. It will initially be assumed that the choices are inscribed polygons, that is all vertices of the polygon are on the sides of the triangle. This concept will be generalized later to include wedged po

Luciana Ferrer, Diego Castan, Mitchell McLaren, Aaron Lawson

Spoken language recognition (SLR) refers to the automatic process used to determine the language present in a speech sample. SLR is an important task in its own right, for example, as a tool to analyze or categorize large amounts of multi-lingual data. Further, it is also an essential tool for selecting downstream applications in a work flow, for example, to

Mário Bessa, Gianluigi Del Magno, João Lopes Dias, José Pedro Gaivão

We show that there exists a $C^2$ open dense set of convex bodies with smooth boundary whose billiard map exhibits a non-trivial hyperbolic basic set. As a consequence billiards in generic convex bodies have positive topological entropy and exponential growth of the number of periodic orbits.

G. A. Bochkin, E. B. Fel'dman, I. D. Lazarev, A. N. Pechen

In this work, we study transfer of coherence matrices along spin-1/2 chains of various length. Unlike higher order coherence matrices, 0-order coherence matrix can be perfectly transferred if its elements are properly fixed. In certain cases, to provide the perfect transfer, an extended receiver together with optimized its unitary transformation has to be in

Max Goplerud, Kosuke Imai, Nicole E. Pashley

Estimation of heterogeneous treatment effects is an active area of research. Most of the existing methods, however, focus on estimating the conditional average treatment effects of a single, binary treatment given a set of pre-treatment covariates. In this paper, we propose a method to estimate the heterogeneous causal effects of high-dimensional treatments,

Daniel Pfrommer, Nikolai Matni

We introduce Variational State-Space Filters (VSSF), a new method for unsupervised learning, identification, and filtering of latent Markov state space models from raw pixels. We present a theoretically sound framework for latent state space inference under heterogeneous sensor configurations. The resulting model can integrate an arbitrary subset of the sens

Ken Ono, Sudhir Pujahari, Larry Rolen

Heim, Neuhauser, and Tr\"oger recently established some inequalities for MacMahon's plane partition function $\mathrm{PL}(n)$ that generalize known results for Euler's partition function $p(n)$. They also conjectured that $\mathrm{PL}(n)$ is log-concave for all $n\geq 12.$ We prove this conjecture. Moreover, for every $d\geq 1$, we prove their speculation th

Wojciech Młotkowski

We characterize positive definiteness for some family of matrices. As an application we derive explicit value of the quadratic embedding constants of the path graphs.

Freddie Wallwork

We study the $(p,q)$-Maker Breaker Crossing game introduced by Day and Falgas Ravry in 'Maker-Breaker percolation games I: crossing grids'. The game described in their paper involves two players Maker and Breaker who take turns claiming p and q as yet unclaimed edges of the graph respectively. Maker aims to make a horizontal path from a leftmost vert

Hengbo Ma, Bike Zhang, Masayoshi Tomizuka, Koushil Sreenath

Control barrier functions (CBFs) have become a popular tool to enforce safety of a control system. CBFs are commonly utilized in a quadratic program formulation (CBF-QP) as safety-critical constraints. A class $\mathcal{K}$ function in CBFs usually needs to be tuned manually in order to balance the trade-off between performance and safety for each environmen

George Panagopoulos, Michalis Vazirgiannis

International academic collaborations cultivate diversity in the research landscape and facilitate multiperspective methods, as the scope of each country's science depends on its needs, history, wealth etc. Moreover the quality of science differ significantly amongst nations\cite{king2004scientific}, which renders international collaborations a potential

Sabine Storandt, Johannes Zink

Given a polyline on $n$ vertices, the polyline simplification problem asks for a minimum size subsequence of these vertices defining a new polyline whose distance to the original polyline is at most a given threshold under some distance measure, usually the local Hausdorff or the local Fr\'echet distance. Here, local means that, for each line segment of the

C. D. Fosco, F. C. Lombardo, F. D. Mazzitelli

We study quantum dissipative effects due to the non-relativistic, bounded, accelerated motion of a single neutral atom in the presence of a planar perfect mirror, i.e. a perfect conductor at all frequencies. We consider a simplified model whereby a moving `scalar atom' is coupled to a quantum real scalar field, subjected to either Dirichlet or Neumann bo

Eya Ben Amar, Nadhir Ben Rached, Abdul-Lateef Haji-Ali, Raúl Tempone

Estimating the expectations of functionals applied to sums of random variables (RVs) is a well-known problem encountered in many challenging applications. Generally, closed-form expressions of these quantities are out of reach. A naive Monte Carlo simulation is an alternative approach. However, this method requires numerous samples for rare event problems. T

Hannes Bartz, Sven Puchinger

We construct $s$-interleaved linearized Reed--Solomon (ILRS) codes and variants and propose efficient decoding schemes that can correct errors beyond the unique decoding radius in the sum-rank metric. The proposed interpolation-based scheme for ILRS codes can be used as a list decoder or as a probabilistic unique decoder that corrects errors of sum-rank up t

Alexandre Alcoforado, Thomas Palmeira Ferraz, Rodrigo Gerber, Enzo Bustos

Traditional text classification approaches often require a good amount of labeled data, which is difficult to obtain, especially in restricted domains or less widespread languages. This lack of labeled data has led to the rise of low-resource methods, that assume low data availability in natural language processing. Among them, zero-shot learning stands out,

Marco Fabris, Daniel Zelazo

This paper investigates the problem of communication relay establishment for multiple agent-based mobile units using a relay vehicle. The objective is to drive autonomously the relay vehicle to attain a position for communication relay establishment while maintaining the other vehicles inside of its field-of-view. A bearing-based control law is proposed for

Glennys R. Farrar

The neutral, flavor singlet scalar uuddss bound state -- the sexaquark, S -- may have a low enough mass to be stable or extremely long-lived. Here we review mass estimates and production expectations and show that laboratory experiments to date do not rule out such a long-lived state. An S with mass below 2054 MeV is either absolutely stable or has a lifetim

Richard J. Martin

The notion of a credit spread curve is fundamental in fixed income investing, but in practice it is not `given' and needs to be constructed from bond prices either for a particular issuer, or for a sector rating-by-rating. Rather than attempting to fit spreads -- and as we discuss here, the Z-spread is unsuitable -- we fit parametrised survival curves. By de

Bruno Mera, Nikola Paunković, Syed Tahir Amin, Vítor R. Vieira

We analyze the thermodynamical limit of the quantum metric along critical submanifolds of theory space. Building upon various results previously known in the literature, we relate its singular behavior to normal directions, which are naturally associated with relevant operators in the renormalization group sense. We formulate these results in the language of

Dan A. Lee, Martin Lesourd, Ryan Unger

For manifolds with a distinguished asymptotically flat end, we prove a density theorem which produces harmonic asymptotics on the distinguished end, while allowing for points of incompleteness (or negative scalar curvature) away from this end. We use this to improve the "quantitative" version of the positive mass theorem (in dimensions $3\leq n\leq 7$), obta

Anton Kapustin, Nikita Sopenko

We study generalizations of the Berry phase for quantum lattice systems in arbitrary dimensions. For a smooth family of gapped ground states in d dimensions, we define a closed (d+2)-form on the parameter space which generalizes the curvature of the Berry connection. Its cohomology class is a topological invariant of the family. When the family is equivarian

Théo Dessertaine, Jean-Philippe Bouchaud

We consider a simple model for multidimensional cone-wise linear dynamics around cusp-like equilibria. We assume that the local linear evolution is either $\mathbf{v}^\prime=\mathbb{A}\mathbf{v}$ or $\mathbb{B}\mathbf{v}$ (with $\mathbb{A}$, $\mathbb{B}$ independently drawn a rotationally invariant ensemble of $N \times N$ matrices) depending on the sign of

Antonio F. Peralta, János Kertész, Gerardo Iñiguez

Opinions are an integral part of how we perceive the world and each other. They shape collective action, playing a role in democratic processes, the evolution of norms, and cultural change. For decades, researchers in the social and natural sciences have tried to describe how shifting individual perspectives and social exchange lead to archetypal states of p

Nicola Guglielmi, Mattia Manucci

In this paper we discuss a projection model order reduction (MOR) method for a class of parametric linear evolution PDEs, which is based on the application of the Laplace transform. The main advantage of this approach consists in the fact that, differently from time stepping methods, like Runge-Kutta integrators, the Laplace transform allows to compute the s

Evan Randles

The local (central) limit theorem precisely describes the behavior of iterated convolution powers of a probability distribution on the $d$-dimensional integer lattice, $\mathbb{Z}^d$. Under certain mild assumptions on the distribution, the theorem says that the convolution powers are well-approximated by a single scaled Gaussian density which we call an attr

Prathyush P. Poduval, Abhisek Samanta, Prashant Gupta, Nandini Trivedi

We study the two-particle spectral functions and collective modes of weakly disordered superconductors using a disordered attractive Hubbard model on square lattice. We show that the disorder induced scattering between collective modes leads to a finite subgap spectral weight in the long wavelength limit. In general, the spectral weight is distributed betwee

Jaehyun Lee, Taysun Kimm, Jérémy Blaizot, Harley Katz

We investigate the formation of jellyfish galaxies using radiation-hydrodynamic simulations of gas-rich dwarf galaxies with a multi-phase interstellar medium (ISM). We find that the ram-pressure-stripped (RPS) ISM is the dominant source of molecular clumps in the near wake within 10 kpc from the galactic plane, while in-situ formation is the major channel fo

Nicolas F. Martin, Rodrigo A. Ibata, Else Starkenburg, Zhen Yuan

We use the photometric metallicities provided by the panoramic Pristine survey to study the veracity and derive the metallicities of the numerous stellar streams found by the application of the STREAMFINDER algorithm to the Gaia EDR3 data. All 26 streams present in Pristine show a clear metallicity distribution function, which provides an independent check o

S. Gandolfi, G. Palkanoglou, J. Carlson, A. Gezerlis

We report ab initio calculations of the S wave pairing gap in neutron matter calculated using realistic nuclear Hamiltonians that include two- and three-body interactions. We use a trial state, properly optimized to capture the essential pairing correlations, from which we extract ground state properties by means of auxiliary field diffusion Monte Carlo simu

Digvijay Wadekar, Leander Thiele, Francisco Villaescusa-Navarro, J. Colin Hill

Complex astrophysical systems often exhibit low-scatter relations between observable properties (e.g., luminosity, velocity dispersion, oscillation period). These scaling relations illuminate the underlying physics, and can provide observational tools for estimating masses and distances. Machine learning can provide a fast and systematic way to search for ne

Bartlomiej Czech

Topological phases of matter are often described using auxiliary systems in one extra dimension. I review the one-dimensional cluster state--the simplest quantum state with Symmetry-Protected Topological (SPT) order--as a toy model of holographic duality, and inspect it for clues about defining holographic complexity. Group cohomology, which classifies SPT o

Vijay Varma, Sylvia Biscoveanu, Tousif Islam, Feroz H. Shaik

The final black hole left behind after a binary black hole merger can attain a recoil velocity, or a "kick", reaching values up to 5000 km/s. This phenomenon has important implications for gravitational wave astronomy, black hole formation scenarios, testing general relativity, and galaxy evolution. We consider the gravitational wave signal from the binary b

Francisco Villaescusa-Navarro, Shy Genel, Daniel Anglés-Alcázar, Lucia A. Perez

The Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project was developed to combine cosmology with astrophysics through thousands of cosmological hydrodynamic simulations and machine learning. CAMELS contains 4,233 cosmological simulations, 2,049 N-body and 2,184 state-of-the-art hydrodynamic simulations that sample a vast volume in pa

Cole Miles, Benjamin Cohen-Stead, Owen Bradley, Steven Johnston

We present a method to facilitate Monte Carlo simulations in the grand canonical ensemble given a target mean particle number. The method imposes a fictitious dynamics on the chemical potential, to be run concurrently with the Monte Carlo sampling of the physical system. Corrections to the chemical potential are made according to time-averaged estimates of t

Wele Gedara Chaminda Bandara, Vishal M. Patel

This paper presents a transformer-based Siamese network architecture (abbreviated by ChangeFormer) for Change Detection (CD) from a pair of co-registered remote sensing images. Different from recent CD frameworks, which are based on fully convolutional networks (ConvNets), the proposed method unifies hierarchically structured transformer encoder with Multi-L

Lionel Cheng, Nicolas Barleon, Olivier Vermorel, Benedicte Cuenot

A new unstructured, massively parallel code dedicated to low temperature plasmas, AVIP, is presented to simulate plasma discharges in interaction with combustion. The plasma species are modeled in a drift-diffusion formulation and the Poisson equation is solved consistently with the charged species. Plasma discharges introduce stiff source terms on the react

Wenwu Zhu, Xin Wang, Pengtao Xie

Conventional machine learning (ML) relies heavily on manual design from machine learning experts to decide learning tasks, data, models, optimization algorithms, and evaluation metrics, which is labor-intensive, time-consuming, and cannot learn autonomously like humans. In education science, self-directed learning, where human learners select learning tasks

Xin Wang, Ziwei Zhang, Haoyang Li, Wenwu Zhu

Graph machine learning has been extensively studied in both academic and industry. However, as the literature on graph learning booms with a vast number of emerging methods and techniques, it becomes increasingly difficult to manually design the optimal machine learning algorithm for different graph-related tasks. To tackle the challenge, automated graph mac

Jiequn Han, Xu-Hui Zhou, Heng Xiao

Developing robust constitutive models is a fundamental and longstanding problem for accelerating the simulation of complicated physics. Machine learning provides promising tools to construct constitutive models based on various calibration data. In this work, we propose a neural operator to develop nonlocal constitutive models for tensorial quantities throug

Dominik Kempa, Tomasz Kociumaka

The suffix array $SA[1..n]$ of a text $T$ of length $n$ is a permutation of $\{1,\ldots,n\}$ describing the lexicographical ordering of suffixes of $T$, and it is considered to be among of the most important data structures in string algorithms, with dozens of applications in data compression, bioinformatics, and information retrieval. One of the biggest dra

Nicholas S. Caros, Xiaotong Guo, Jinhua Zhao

Many studies of the effect of remote work on travel demand assume that remote work takes place entirely at home. Recent evidence, however, shows that in the United States, remote workers are choosing to spend approximately one third of their remote work hours outside of the home at cafes, co-working spaces or the homes of friends and family. Commutes to thes

Adam Bertsch, Michael R. Collette, Shawn A. Dawson, Si D. Hammond

Power is an often-cited reason for the move to advanced architectures on the path to Exascale computing. This is due to practical considerations related to delivering enough power to successfully site and operate these machines, as well as concerns about energy usage while running large simulations. Since obtaining accurate power measurements can be challeng

Alexander Morozov

When subjected to sufficiently strong velocity gradients, solutions of long, flexible polymers exhibit flow instabilities and chaotic motion, often referred to as elastic turbulence. Its mechanism differs from the familiar, inertia-driven turbulence in Newtonian fluids, and is poorly understood. Here, we demonstrate that the dynamics of purely elastic pressu

Melvyn B. Nathanson

Preliminary results from Nathanson [5] are used to prove the Muirhead and Rado inequalities.

Paul Mercat

For any primitive substitution whose Perron eigenvalue is Pisot unit, we construct a domain exchange measurably conjugated to the subshift. And we give a condition for the subshift to be a finite extension of a torus translation. For the particular case of weakly irreducible Pisot substitution, we show that the subshift is either a finite extension of a toru

Devojyoti Kansabanik, Surajit Mondal, Divya Oberoi, Ayan Biswas

Sensitive radio instruments are optimized for observing faint astronomical sources, and usually need to attenuate the received signal when observing the Sun. There are only a handful of flux density calibrators which can comfortably be observed with the same attenuation setup as the Sun. Additionally, for wide field-of-view (FoV) instruments like the Murchis

Jérémy Auffinger

Primordial black holes (PBHs) are convenient candidates to explain the elusive dark matter (DM). However, years of constraints from various astronomical observations have constrained their abundance over a wide range of masses, leaving only a narrow window open at $10^{17}\,{\rm g} \lesssim M \lesssim 10^{22}\,$g for all DM in the form of PBHs. We reexamine

Hugo Henck, Diego Mauro, Daniil Domaretskiy, Marc Philippi

Light-emitting electronic devices are ubiquitous in key areas of current technology, such as data communications, solid-state lighting, displays, and optical interconnects. Controlling the spectrum of the emitted light electrically, by simply acting on the device bias conditions, is an important goal with potential technological repercussions. However, ident

Jonathan Rosenberg, Shmuel Weinberger

This paper is about positive scalar curvature on a compact manifold $X$ with non-empty boundary $\partial X$. In some cases, we completely answer the question of when $X$ has a positive scalar curvature metric which is a product metric near $\partial X$, or when $X$ has a positive scalar curvature metric with positive mean curvature on the boundary, and more

Roberto La Scala, Sergio Polese, Sharwan K. Tiwari, Andrea Visconti

In this paper we study the security of the Bluetooth stream cipher E0 from the viewpoint it is a "difference stream cipher", that is, it is defined by a system of explicit difference equations over the finite field GF(2). This approach highlights some issues of the Bluetooth encryption such as the invertibility of its state transition map, a special set of 1

Niall L. Williams, Aniket Bera, Dinesh Manocha

We present a novel metric to analyze the similarity between the physical environment and the virtual environment for natural walking in virtual reality. Our approach is general and can be applied to any pair of physical and virtual environments. We use geometric techniques based on conforming constrained Delaunay triangulations and visibility polygons to com

Wentao Liu, Xiongjun Fang, Jiliang Jing, Anzhong Wang

In this paper, the gauge choices in general spherically symmetric spacetimes have been explored. We construct the gauge invariant variables and the master equations for both the Detweiler easy gauge and the Regge-Wheeler gauge, respectively. The particular cases for $l=0,1$ are also been investigated. Our results provide analytical calculations of metric per

Erdal Mutlu, Ajay Panyala, Nitin Gawande, Abhishek Bagusetty

Tensor contraction operations in computational chemistry consume significant fractions of computing time on large-scale computing platforms. The widespread use of tensor contractions between large multi-dimensional tensors in describing electronic structure theory has motivated the development of multiple tensor algebra frameworks targeting heterogeneous com

E. D. Hunter, C. Amsler, H. Breuker, S. Chesnevskaya

The ASACUSA collaboration produces a beam of antihydrogen atoms by mixing pure positron and antiproton plasmas in a strong magnetic field with a double cusp geometry. The positrons cool via cyclotron radiation inside the cryogenic trap. Low positron temperature is essential for increasing the fraction of antihydrogen atoms which reach the ground state prior

Jens Tuyls, Shunyu Yao, Sham Kakade, Karthik Narasimhan

Text adventure games present unique challenges to reinforcement learning methods due to their combinatorially large action spaces and sparse rewards. The interplay of these two factors is particularly demanding because large action spaces require extensive exploration, while sparse rewards provide limited feedback. This work proposes to tackle the explore-vs

Piero Deidda, Mario Putti, Francesco Tudisco

Inspired by the linear Schr\"odinger operator, we consider a generalized $p$-Laplacian operator on discrete graphs and present new results that characterize several spectral properties of this operator with particular attention to the nodal domain count of its eigenfunctions. Just like the one-dimensional continuous $p$-Laplacian, we prove that the variation

Hanhan Zhou, Tian Lan, Vaneet Aggarwal

Value function factorization via centralized training and decentralized execution is promising for solving cooperative multi-agent reinforcement tasks. One of the approaches in this area, QMIX, has become state-of-the-art and achieved the best performance on the StarCraft II micromanagement benchmark. However, the monotonic-mixing of per agent estimates in Q

Tong Dou, Guofeng Zhang, Wei Cui

Recent work has begun to explore the potential of parametrized quantum circuits (PQCs) as general function approximators. In this work, we propose a quantum-classical deep network structure to enhance classical CNN model discriminability. The convolutional layer uses linear filters to scan the input data. Moreover, we build PQC, which is a more potent functi

J. M. Gómez-Ros, R. Bedogni, C. Domingo, J. S. Eakins

This paper summarizes the results obtained from an international comparison exercise on neutron spectra unfolding in Bonner spheres spectrometry, organized within the activities of EURADOS working group 6: computational dosimetry. Four realistic situations were considered: a medical accelerator, a workplace field, an irradiation room and a skyshine scenario.

Bruce A. Corliss, Taylor R. Brown, Tingting Zhang, Kevin A. Janes

Statistical insignificance does not suggest the absence of effect, yet scientists must often use null results as evidence of negligible (near-zero) effect size to falsify scientific hypotheses. Doing so must assess a result's null strength, defined as the evidence for a negligible effect size. Such an assessment would differentiate strong null results that s

Nikolay Kutev, Sonia Tabakova

The steady Poiseuille flow of Carreau-Yasuda fluid in a pipe, caused by constant pressure gradient, is studied theoretically. It is proved that at some values of the viscosity model parameters, the problem has a classical solution, while at others - generalized solution. For the latter, a necessary and sufficient condition is found, which depends on the pres

Mathieu Anel, Georg Biedermann, Eric Finster, André Joyal

We revisit the work of To\"en--Vezzosi and Lurie on Grothendieck topologies, using the new tools of acyclic classes and congruences. We introduce a notion of extended Grothendieck topology on any $\infty$-topos, and prove that the poset of extended Grothendieck topologies is isomorphic to that of topological localizations, hypercomplete localizations, Lawver

Fabio Brau, Giulio Rossolini, Alessandro Biondi, Giorgio Buttazzo

Although Deep Neural Networks (DNNs) have shown incredible performance in perceptive and control tasks, several trustworthy issues are still open. One of the most discussed topics is the existence of adversarial perturbations, which has opened an interesting research line on provable techniques capable of quantifying the robustness of a given input. In this

Johannes Anschütz, Ian Gleason, João Lourenço, Timo Richarz

We prove the Scholze--Weinstein conjecture on the existence and uniqueness of local models for local Shimura varieties, as well as the test function conjecture of Haines--Kottwitz in this framework. To this end, we establish a specialization principle for well-behaved $p$-adic kimberlites, show that these include the v-sheaf local models, determine their spe

Ting Dang, Jing Han, Tong Xia, Dimitris Spathis

Recent work has shown the potential of using audio data (eg, cough, breathing, and voice) in the screening for COVID-19. However, these approaches only focus on one-off detection and detect the infection given the current audio sample, but do not monitor disease progression in COVID-19. Limited exploration has been put forward to continuously monitor COVID-1

Cornelius Fritz, Giacomo De Nicola, Martje Rave, Maximilian Weigert

Over the course of the COVID-19 pandemic, Generalised Additive Models (GAMs) have been successfully employed on numerous occasions to obtain vital data-driven insights. In this paper we further substantiate the success story of GAMs, demonstrating their flexibility by focusing on three relevant pandemic-related issues. First, we examine the interdepency amon

Anton Glushchenko, Konstantin Lastochkin

A new method of direct adaptive pole placement control (APPC) is developed for plants with unmatched uncertainty, which linearly depends on a state vector. It guarantees the exponential stability of a control system and exponential convergence of control law adjustable parameters to their true values when the regressor is finitely exciting. Considering the k

Farshad Noravesh

One of the reasons that higher order moment portfolio optimization methods are not fully used by practitioners in investment decisions is the complexity that these higher moments create by making the optimization problem nonconvex. Many few methods and theoretical results exists in the literature, but the present paper uses the method of successive convex ap

A. C. Quillen, Max Neiderbach, Bingcheng Suo, Juliana South

We carry out experiments of low velocity normal impacts into granular materials that fill an approximately cylindrical 42 litre tub. Motions in the granular medium are tracked with an array of 7 embedded accelerometers. Longitudinal pulses excited by the impact attenuate and their shapes broaden and become smoother as a function of travel distance from the s

Domingos M. Cardoso, Inês Serôdio Costa, Rui Duarte

Sharp bounds on the least eigenvalue of an arbitrary graph are presented. Necessary and sufficient (just sufficient) conditions for the lower (upper) bound to be attained are deduced using edge clique partitions. As an application, we prove that the least eigenvalue of the $n$-Queens' graph $\mathcal{Q}(n)$ is equal to $-4$ for every $n \ge 4$ and it is