August 2022 arXiv papers — page 75

Subhasish Bag, Ramita Sarkar, Prasanta K. Panigrahi

We study the reciprocal of the mean quantum Fisher information (RMQFI), $\chi^2$ for general three qubit states, having graph and hypergraph states as special cases, for identifying genuine multi party entanglement characterized by $\chi^2 <1$. We demonstrate that the most symmetric graph state and the GHZ state have the lowest RMQFI values leading to the hi

Emilio Corso, Davide Ravotti

We consider circles of common centre and increasing radius on a compact hyperbolic surface and, more generally, on its unit tangent bundle. We establish a precise asymptotics for their rate of equidistribution. Our result holds for translates of any circle arc by arbitrary elements of $\text{SL}_2(\mathbb{R})$. Our proof relies on a spectral method pioneered

F. Köpp, J. E. Horvath, D. Hadjimichef, C. A. Z. Vasconcellos

The cooling of neutron stars (hereafter NS) has the potential to reveal important features of superdense matter. Their surface temperatures are known for a fair sample of NS with ages $\leq 10^{6} \, {\it{yr}}$, and with a few exceptions, can be accommodated by standard cooling mechanisms (neutrino+photon emission without internal heating). However, for the

Xiaofeng Liu, Chaehwa Yoo, Fangxu Xing, C. -C. Jay Kuo

Unsupervised domain adaptation (UDA) has been widely used to transfer knowledge from a labeled source domain to an unlabeled target domain to counter the difficulty of labeling in a new domain. The training of conventional solutions usually relies on the existence of both source and target domain data. However, privacy of the large-scale and well-labeled dat

Simone Marchi, Carol A. Raymond, Christopher T. Russell

The NASA Dawn spacecraft took off from Cape Canaveral in September 2007 atop a Delta II rocket starting an ambitious journey to Vesta and Ceres, the two most massive worlds in the largest reservoir of asteroids in the Solar System, the Main Belt. Prior to the Dawn launch, Earth-bound observations of Vesta and Ceres revealed intriguing features--from Vesta's

Gabriel F. Barros, Malú Grave, José J. Camata, Alvaro L. G. A. Coutinho

Modern computational science and engineering applications are being improved by the advances in scientific machine learning. Data-driven methods such as Dynamic Mode Decomposition (DMD) can extract coherent structures from spatio-temporal data generated from dynamical systems and infer different scenarios for said systems. The spatio-temporal data comes as s

Keyu Nie, Zezhong Zhang, Bingquan Xu, Tao Yuan

eBay's experimentation platform runs hundreds of A/B tests on any given day. The platform integrates with the tracking infrastructure and customer experience servers, provides the sampling service for experiments, and has the responsibility to monitor the progress of each A/B test. There are many challenges especially when it is required to ensure experiment

Taewoo Kim, Chaeyeon Chung, Yoonseo Kim, Sunghyun Park

Editing hairstyle is unique and challenging due to the complexity and delicacy of hairstyle. Although recent approaches significantly improved the hair details, these models often produce undesirable outputs when a pose of a source image is considerably different from that of a target hair image, limiting their real-world applications. HairFIT, a pose-invari

Raiean Banerjee, Michel Gaspar

In this work we study the uncountable Borel chromatic numbers, defined by Geschke (2011) as cardinal characteristics of the continuum, of low complexity graphs. We show that a strong form of locally countable graphs with compact totally disconnected set of vertices have Borel chromatic number bounded by the continuum of the ground model in the model obtained

Mirko Hu, Guido Caldarelli, Tommaso Gili

Inflammatory bowel diseases (IBD) are complex diseases in which the gut microbiota is attacked by the immune system of genetically predisposed subjects when they are exposed to yet unclear environmental factors. The complexity of this class of diseases makes them suitable to be represented and studied with network science. In the project, the metagenomic dat

Michael Ebersold, Shubhanshu Tiwari, Leigh Smith, Yeong-Bok Bae

Dense astrophysical environments like globular clusters and galactic nuclei can host hyperbolic encounters of black holes which can lead to gravitational-wave driven capture. There are several astrophysical models which predict a fraction of binary black hole mergers to come from these radiation-driven capture scenarios. In this paper we present the sensitiv

M. Kulyk, M. Persson, D. Polishchuk, V. Korenivski

We study magnetic multilayers, incorporating dilute ferromagnetic spacers between strongly-ferromagnetic layers exhibiting a proximity-enhanced magnetocaloric effect. Using magnetometry and direct measurements of the adiabatic temperature change based on a nanomembrane-calorimetry, we find that the magnetocaloric effect in the studied multilayer is indeed en

Krishnendu Samanta, Azeem Ahmad, Jean-Claude Tinguely, Balpreet Singh Ahluwalia

We present experimental demonstration of tilt-mirror assisted transmission structured illumination microscopy (tSIM) that offers a large field of view super resolution imaging. An assembly of custom-designed tilt-mirrors are employed as the illumination module where the sample is excited with the interference of two beams reflected from the opposite pair of

Zhiyu Li, Xikui Ma, Amir Bahrami, Zoé-Lise Deck-Léger

Recent research developments in the area of spacetime metamaterial structures and systems have raised new questions as to how the physics of fundamental phenomena is altered in the presence of spacetime modulation. In this context, we present a generalized and comparative description of the phenomenon of total internal reflection (TIR) at different dynamic i

Jordan R. Stone, Xiyuan Lu, Gregory Moille, Kartik Srinivasan

Optical parametric oscillators are widely used to generate coherent light at frequencies not accessible by conventional laser gain. However, chip-based parametric oscillators operating in the visible spectrum have suffered from pump-to-signal conversion efficiencies typically less than 0.1 %. Here, we demonstrate efficient optical parametric oscillators base

Sayantani Datta, M. Saleem, K. G. Arun, B. S. Sathyaprakash

Principal Component Analysis (PCA) is an efficient tool to optimize the multiparameter tests of general relativity (GR) where one tests for simultaneous deviations in multiple post-Newtonian (PN) phasing coefficients by introducing fractional deformation parameters. We use PCA to construct the `best-measured' linear combinations of the PN deformation paramet

Zesen Liu, Meng Guo, Zhongkui Li

Multi-agent systems can be extremely efficient when solving a team-wide task in a concurrent manner. However, without proper synchronization, the correctness of the combined behavior is hard to guarantee, such as to follow a specific ordering of sub-tasks or to perform a simultaneous collaboration. This work addresses the minimum-time task planning problem f

Wentao Jiang, Sheng Jin, Wentao Liu, Chen Qian

Human pose estimation aims to accurately estimate a wide variety of human poses. However, existing datasets often follow a long-tailed distribution that unusual poses only occupy a small portion, which further leads to the lack of diversity of rare poses. These issues result in the inferior generalization ability of current pose estimators. In this paper, we

Xiaofeng Liu, Fangxu Xing, Jia You, Jun Lu

Unsupervised domain adaptation (UDA) has been successfully applied to transfer knowledge from a labeled source domain to target domains without their labels. Recently introduced transferable prototypical networks (TPN) further addresses class-wise conditional alignment. In TPN, while the closeness of class centers between source and target domains is explici

Qingxu Fu, Tenghai Qiu, Jianqiang Yi, Zhiqiang Pu

SOTA multiagent reinforcement algorithms distinguish themselves in many ways from their single-agent equivalences. However, most of them still totally inherit the single-agent exploration-exploitation strategy. Naively inheriting this strategy from single-agent algorithms causes potential collaboration failures, in which the agents blindly follow mainstream

Jan Sbierski

Given a function $f : A \to \mathbb{R}^n$ of a certain regularity defined on some open subset $A \subseteq \mathbb{R}^m$, it is a classical problem of analysis to investigate whether the function can be extended to all of $\mathbb{R}^m$ in a certain regularity class. If an extension exists and is continuous, then certainly it is uniquely determined on the cl

Yanqing Wang, Yulin Ye, Huan Yu

In this paper, we consider the 2-D generalized surface quasi-geostrophic equation with the velocity $v$ determined by $v=\mathcal{R}^{\perp}\Lambda^{\gamma-1}\theta$. It is shown that the $L^p$ type energy norm of weak solutions is conserved provided $\theta\in L^{p+1}(0,T; {B}^{\frac{\gamma}{3}}_{p+1, c(\mathbb{N})})$ for $0<\gamma<\frac32$ or $\theta\in L^

Liang Lv, Yi Fang, Lin Dai, Yonghui Li

To achieve reliable and efficient transmissions in free-space optical (FSO) communication, this paper designs a new protograph low-density parity-check (PLDPC) coded generalized spatial multipulse position modulation (GSMPPM) system over weak turbulence channels. Specifically, we investigate the PLDPC code, generalized space shift keying (GSSK) modulation, a

Galina Deeva, Johannes De Smedt, Cecilia Saint-Pierre, Richard Weber

A growing number of universities worldwide use various forms of online and blended learning as part of their academic curricula. Furthermore, the recent changes caused by the COVID-19 pandemic have led to a drastic increase in importance and ubiquity of online education. Among the major advantages of e-learning is not only improving students' learning experi

Xiangqing Kong, Tao Wang, Zeyuan Gao, Liu Zhao

The recently proposed restricted phase space thermodynamics is shown to be applicable to a large class of higher dimensional higher curvature gravity models coupled to Maxwell field, which are known as black hole scan models and are labeled by the spacetime dimension $d$ and the highest order $k$ of the Lanczos-Lovelock densities appearing in the action. Thr

X. Zhu, M. Broccardo, B. Sudret

Within the performance-based earthquake engineering (PBEE) framework, the fragility model plays a pivotal role. Such a model represents the probability that the engineering demand parameter (EDP) exceeds a certain safety threshold given a set of selected intensity measures (IMs) that characterize the earthquake load. The-state-of-the art methods for fragilit

Miguel A. Mendez

Dimensionality reduction is the essence of many data processing problems, including filtering, data compression, reduced-order modeling and pattern analysis. While traditionally tackled using linear tools in the fluid dynamics community, nonlinear tools from machine learning are becoming increasingly popular. This article, halfway between a review and a tuto

Riccardo Zuffetti

Let X be an orthogonal Shimura variety, and let C_r(X) be the cone generated by the cohomology classes of orthogonal Shimura subvarieties in X of dimension r. We investigate the asymptotic properties of the generating rays of C_r(X) for large values of r. They accumulate towards rays generated by wedge products of the K\"ahler class of X and the fundamental

Lai Wei, Kezhi Wang, Cunhua Pan, Maged Elkashlan

In this letter, we analyze the secrecy performance of a reconfigurable intelligent surface (RIS)-aided communication system with spatially random unmanned aerial vehicles (UAVs) acting as eavesdroppers. We consider the scenarios where the base station (BS) is equipped with single and multiple antennas.The signal-to-noise ratios (SNRs) of the legitimate user

Tomas Geffner, Justin Domke

Many methods that build powerful variational distributions based on unadjusted Langevin transitions exist. Most of these were developed using a wide range of different approaches and techniques. Unfortunately, the lack of a unified analysis and derivation makes developing new methods and reasoning about existing ones a challenging task. We address this givin

Dong Li, Li-fang Chen

Three new Arnoldi-type methods are presented to accelerate the modal analysis and critical speed analysis of the damped rotor dynamics finite element (FE) model. They are the linearized quadratic eigenvalue problem (QEP) Arnoldi method, the QEP Arnoldi method, and the truncated generalized standard eigenvalue problem (SEP) Arnoldi method. And, they correspon

François Michel, Alejandro Cohen, Derya Malak, Quentin De Coninck

Packet losses are common events in today's networks. They usually result in longer delivery times for application data since retransmissions are the de facto technique to recover from such losses. Retransmissions is a good strategy for many applications but it may lead to poor performance with latency-sensitive applications compared to network coding. Althou

Yanqi Wu, Hossein S. Aghamiry, Stephane Operto, Jianwei Ma

Frequency-domain simulation of seismic waves plays an important role in seismic inversion, but it remains challenging in large models. The recently proposed physics-informed neural network (PINN), as an effective deep learning method, has achieved successful applications in solving a wide range of partial differential equations (PDEs), and there is still roo

Afshin Yaghoubi

In statistics and probability theory, one the most important statistics is the sums of random variables. After introducing a probability distribution, determining the sum of n independent and identically distributed random variables is one of the interesting topics for authors. This paper presented the probability density function for the sum of n independen

Yansong Zhang, Bo Shen, Yingsi Zhao

Generally, system failures, such as crash failures, Byzantine failures and so on, are considered as common reasons for the inconsistencies of distributed consensus and have been extensively studied. In fact, strategic manipulations by rational agents do not be ignored for reaching consensus in distributed system. In this paper, we extend the game-theoretic a

Yuting Ding, Di Wu

Missing data is an inevitable and common problem in data-driven intelligent transportation systems (ITS). In the past decade, scholars have done many research on the recovery of missing traffic data, however how to make full use of spatio-temporal traffic patterns to improve the recovery performance is still an open problem. Aiming at the spatio-temporal cha

Lucien Hennecart, Nikolai Perry

An unresolved conjecture by Graham Higman states that for all $n\geq 1$ the number of conjugacy classes of the group of $n \times n$ unitriangular matrices with entries in the finite field $\mathbb{F}_q$ is a polynomial in $q$. In this paper we introduce a new quiver generalization of the conjecture. Motivated by this generalization, we prove that certain op

Nishanth Kumar, Willie McClinton, Rohan Chitnis, Tom Silver

An effective approach to solving long-horizon tasks in robotics domains with continuous state and action spaces is bilevel planning, wherein a high-level search over an abstraction of an environment is used to guide low-level decision-making. Recent work has shown how to enable such bilevel planning by learning abstract models in the form of symbolic operato

Robert A. Marsden, Mario Döbler, Bin Yang

Experiencing domain shifts during test-time is nearly inevitable in practice and likely results in a severe performance degradation. To overcome this issue, test-time adaptation continues to update the initial source model during deployment. A promising direction are methods based on self-training which have been shown to be well suited for gradual domain ad

Tao Yan, Mingyue Li, Bin Li, Yang Yang

Existing deraining methods focus mainly on a single input image. However, with just a single input image, it is extremely difficult to accurately detect and remove rain streaks, in order to restore a rain-free image. In contrast, a light field image (LFI) embeds abundant 3D structure and texture information of the target scene by recording the direction and

Jaemin Yoo, Tiancheng Zhao, Leman Akoglu

Self-supervised learning (SSL) has emerged as a promising alternative to create supervisory signals to real-world problems, avoiding the extensive cost of manual labeling. SSL is particularly attractive for unsupervised tasks such as anomaly detection (AD), where labeled anomalies are rare or often nonexistent. A large catalog of augmentation functions has b

Mehri KianMehr, Farshid Saeedi

We introduce a novel concept Frattinian nilpotent Lie algebra. Along with some examples, we show that every Frattinian nilpotent Lie algebra has a central decomposition of its ideals.

Wesley Roberts, Michael Vogl, Gregory A. Fiete

Motivated by rapid developments in the field of quantum computing and the increasingly diverse nature of qubits, we theoretically study the influence that quenched outside disturbances have in an intermediately long time limit. We consider localized imperfections, uniform fields, noise, and couplings to an environment which we study in a unified framework us

Shizhe Jiao, Jielan Li, Xinming Qin, Lingyun Wan

K-means clustering, as a classic unsupervised machine learning algorithm, is the key step to select the interpolation sampling points in interpolative separable density fitting (ISDF) decomposition. Real-valued K-means clustering for accelerating the ISDF decomposition has been demonstrated for large-scale hybrid functional enabled \textit{ab initio} molecul

Hao Wu

We revisit the direct sum questions in communication complexity which asks whether the resource needed to solve $n$ communication problems together is (approximately) the sum of resources needed to solve these problems separately. Our work starts with the observation that Dinur and Meir's fortification lemma can be generalized to a general fortification lemm

Nicolas Tancogne-Dejean, Angel Rubio, Carsten A. Ullrich

We present a semilocal exchange-correlation energy functional for noncollinear spin density functional theory based on short-range expansions of the spin-resolved exchange hole and the two-body density matrix. Our functional is explicitly derived for noncollinear magnetism, U(1) and SU(2) gauge invariant, and gives rise to nonvanishing exchange-correlation t

Seokhwan Choi, Hanpil Kang, Dongjae Lim

Erd\H{o}s-Ginzburg-Ziv theorem is a famous theorem in additive number theory, which states any sequence of $2n-1$ integers contains a subsequence of $n$ elements, with their sum being a multiple of $n$. In this article, we provide an algorithm finding a solution of Erd\H{o}s-Ginzburg-Ziv theorem in $\mathcal{O}(n \log n)$ time. This is the first known determ

Leilei Zhang

Let $G$ be a connected graph. The resistance distance between any two vertices of $G$ is equal to the effective resistance between them in the corresponding electrical network constructed from $G$ by replacing each edge with a unit resistor. The Kirchhoff index is defined as the sum of resistance distances between all pairs of the vertices. Recently, Yang an

Marilena Moruz

We study hypersurfaces in the pseudo-Euclidean space $\mathbb{E}^{n+1}_s$, which write as a warped product of a $1$-dimensional base with an $(n-1)$-manifold of constant sectional curvature. We show that either they have constant sectional curvature or they are contained in a rotational hypersurface. Therefore, we first define rotational hypersurfaces in the

Or Katz, Meirav Pinkas, Nitzan Akerman, Ming Li

Quantum effects in chemical reactions are most pronounced at ultracold temperatures, where only a few partial waves contribute. While interference among many partial waves is theoretically expected to persist at higher temperatures, direct evidence for such quantum effects in reactive processes has been lacking. Here, we report the first observation of quant

Richard French, Christophe Mandy, Richard Hunter, Ehson Mosleh

Regular, low-cost Decadal-class science missions to planetary destinations will be enabled by high-{\Delta}V small spacecraft, such as the high-energy Photon, and small launch vehicles, such as Electron, to support expanding opportunities for scientists and to increase the rate of science return. The Rocket Lab mission to Venus is a small direct entry probe

Rakesh Arora, Sergey Shmarev

We consider the homogeneous Dirichlet problem for the anisotropic parabolic equation \[ u_t-\sum_{i=1}^ND_{x_i}\left(|D_{x_i}u|^{p_i(x,t)-2}D_{x_i}u\right)=f(x,t) \] in the cylinder $\Omega\times (0,T)$, where $\Omega\subset \mathbb{R}^N$, $N\geq 2$, is a parallelepiped. The exponents of nonlinearity $p_i$ are given Lipschitz-continuous functions. It is show

Jingru Zhu, Ya Guo, Geng Sun, Libo Yang

Semantic segmentation is a key technique involved in automatic interpretation of high-resolution remote sensing (HRS) imagery and has drawn much attention in the remote sensing community. Deep convolutional neural networks (DCNNs) have been successfully applied to the HRS imagery semantic segmentation task due to their hierarchical representation ability. Ho

A. I. Breev, D. M. Gitman

We consider a model for describing a QED system consisting of a photon beam interacting with quantized charged spinless particles. We restrict ourselves by a photon beam that consists of photons with two different momenta moving in the same direction. Photons with each moment may have two possible linear polarizations. The exact solutions correspond to two i

E. J. Snowdon, L. J. A. Scott, C. S. Jeffery, V. M. Woolf

BPS CS 22940-0009 is a helium-rich B-star that shares characteristics with both helium-rich B subdwarfs and extreme helium stars. The optical spectrum of BPS CS 22940-0009 has been analysed from SALT observations. The atmospheric parameters were found to be $T_{\rm eff} = 34970 \pm 370$ K, $\log g/{\rm cm \, s^{-2}} = 4.79 \pm 0.17$, $n_{\rm H}/n_{\rm He} \s

Wenjin Zhao, Guiyu Cao, Jianchun Wang, Kun Xu

High-order gas-kinetic scheme (HGKS) with 5th-order non-compact reconstruction has been well implemented for implicit large eddy simulation (ILES) in nearly incompressible turbulent channel flows. In this study, the HGKS with higher-order non-compact reconstruction and compact reconstruction will be validated in turbulence simulation. For higher-order non-co

Shihurong Yao, Yizhan Huang, Xiaogang Xu

In the realm of Low-Light Image Enhancement (LLIE), existing research primarily focuses on enhancing images globally. However, many applications require local LLIE, where users are allowed to illuminate specific regions using an input mask, such as creating a protagonist stage or spotlight effect. However, this task has received limited attention currently.

Gyanendra K. Verma, Astha Agrawal, R. K. Sharma

In this article, first we present a method for constructing many Hermitian LCD codes from a given Hermitian LCD code, and then provide several methods which utilize either a given [n, k, d] linear code or a given [n, k, d] Galois LCD code to construct new Galois LCD codes with different parameters. Using these construction methods, we construct several new [

Petr Knobloch

Algebraically stabilized finite element discretizations of scalar steady-state convection-diffusion-reaction equations often provide accurate approximate solutions satisfying the discrete maximum principle (DMP). However, it was observed that a deterioration of the accuracy and convergence rates may occur for some problems if meshes without local symmetries

Arnaud Doucet, Will Grathwohl, Alexander G. D. G. Matthews, Heiko Strathmann

More than twenty years after its introduction, Annealed Importance Sampling (AIS) remains one of the most effective methods for marginal likelihood estimation. It relies on a sequence of distributions interpolating between a tractable initial distribution and the target distribution of interest which we simulate from approximately using a non-homogeneous Mar

Felix Jakob Segerer, Katharina Nekolla, Lorenz Rognoni, Ansh Kapil

Generative Adversarial Networks (GANs) are state of the art for image synthesis. Here, we present dapi2ck, a novel GAN-based approach to synthesize cytokeratin (CK) staining from immunofluorescent (IF) DAPI staining of nuclei in non-small cell lung cancer (NSCLC) images. We use the synthetic CK to segment epithelial regions, which, compared to expert annotat

Shanghua Zheng

In this paper, we first introduce the unlacing of Hurwitz series, which can be viewed as an inverse of interlacing, and develop the basic properties of unlacing, interlacing and integral of Hurwitz series. We then show that the multiplication of interlacing of Hurwitz series by basis elements can be also rewritten as an interlacing, and provide the explicit

Simon Kristensen, Oskar Mathiasen

We provide a simple way of searching for formulas of the Bailey--Borwein--Plouffe type together with an algorithm and an implementation in \texttt{sage}. Aside from rediscovering some already known formulas, the method has been used in the discovery of a new BBP-type formula for $\sqrt{3}\pi$. In addition, the implementation is very flexible and allows us to

Stupka A. A., Kopteva E. M., Saliuk M. A., Bormotova I. M

A hydrodynamic model for small acoustic oscillations in a cloud of stars is built, taking into account the self-consistent gravitational field in equilibrium with a non-zero second correlation moment. It is assumed that the momentum flux density tensor should include the analog of the anisotropic pressure tensor and the second correlation moment of both long

Prasiddha Arunachalam, John P. Hughes, Luke Hovey, Kristoffer Eriksen

Using HST narrow-band H{\alpha} images of supernova remnant 0509-67.5 taken {\sim}10 years apart, we measure the forward shock (FS) proper motions (PMs) at 231 rim locations. The average shock radius and velocity are 3.66 {\pm} 0.036 pc and 6315 {\pm} 310 km s{^{-1}}. Hydrodynamic simulations, recast as similarity solutions, provide models for the remnant's

Gilberto B. Almeida Filho, Matheus Bernardini

In this paper, we bring the terminology of the Kunz coordinates of numerical semigroups to gapsets and we generalize this concept to $m$-extensions. It allows us to identify gapsets and, in general, $m$-extensions with tilings of boards. As a consequence, we prove a version of Bras-Amor\'{o}s conjecture for $m$-extensions. Besides, we obtain a lower bound fo

Samer Al Ghour, Zanyar A. Ameen

In various articles, it is said that the class of all soft topologies on a common universe forms a complete lattice, but in this paper, we prove that it is a complete lattice. Some soft topologies are maximal and some are minimal with respect to certain soft topological properties. We study the properties of soft compact and soft connected topologies that ar

Mohamed Ben Alaya, Walid Ben Aribi, Slimane Ben Miled

The primary goal of this research is to investigate the impact of delay on the dynamics of the Susceptible-Exposed-Infected-Recovered-Death and Susceptible (SEIRDS) model, to which we add a stochastic term to account for uncertainty in COVID-19 parameter estimations. We run two models, one deterministic and one stochastic, and show that their solutions exist

Marcin Markiewicz, Janusz Przewocki

It is a well-established fact in quantum information theory, that uniform averaging over the collective action of a unitary group on a multipartite quantum state projects the state to a form equivalent to a permutation operator of the subsystems. Hence states equivalent to permutation operators are untouched by collective unitary noise. A trivial observation

Leonardo De Carlo, W. David Wick

From the point of view of Schr\"odingerism, a wavefunction-only philosophy, thermodynamics must be recast in terms of an ensemble of wavefunctions, rather than classical particle configurations or "found" values of Copenaghen Quantum Mechanics. Recapitulating the historical sequence, we consider here several models of magnets that classically can exhibit a p

Jan Van den Berghe, Bruno R. B. Dias, Yann Bartosiewicz, Miguel A. Mendez

We propose a 1D unsteady model for supersonic single-phase ejectors. The model treats an ejector as a pipe network with two inputs and one output and combines a 1D gas dynamics formulation in each `pipe' with a junction model for entrainment and mixing. The model is calibrated and validated on experimental data in steady-state conditions and used to analyze

Fatema Al Mukhaini, Shaikhah Al Abdoulie, Aisha Al Kharuosi, Amal El Ahmad

Fake news existed ever since there was news, from rumors to printed media then radio and television. Recently, the information age, with its communications and Internet breakthroughs, exacerbated the spread of fake news. Additionally, aside from e-Commerce, the current Internet economy is dependent on advertisements, views and clicks, which prompted many dev

Timo Dimitriadis, Tobias Fissler, Johanna Ziegel

Given a statistical functional of interest such as the mean or median, a (strict) identification function is zero in expectation at (and only at) the true functional value. Identification functions are key objects in forecast validation, statistical estimation and dynamic modelling. For a possibly vector-valued functional of interest, we fully characterise t

Ulaş Özdem

In this study, we discuss the magnetic moment of $P_{cs}(4338)$ and $P_{cs}(4459)$ hidden-charmed pentaquarks, which are closely related to their substructures. The magnetic moments of these states are calculated with the help of the QCD light-cone sum rules method with quantum numbers $I(J^P) = 0(1/2^-)$ and $I(J^P) = 0(3/2^-)$ for $P_{cs}(4338)$ and $P_{cs

A. M. Krol, K. Mesman, A. Sarkar, M. Möller

Near term quantum devices have the potential to outperform classical computing through the use of hybrid classical-quantum algorithms such as Variational Quantum Eigensolvers. These iterative algorithms use a classical optimiser to update a parameterised quantum circuit. Each iteration, the circuit is executed on a physical quantum processor or quantum compu

Silvia Cascianelli, Vittorio Pippi, Martin Maarand, Marcella Cornia

Handwritten Text Recognition (HTR) is an open problem at the intersection of Computer Vision and Natural Language Processing. The main challenges, when dealing with historical manuscripts, are due to the preservation of the paper support, the variability of the handwriting -- even of the same author over a wide time-span -- and the scarcity of data from anci

Chong Zhang, Lizhi Yang

Terrain-aware locomotion has become an emerging topic in legged robotics. However, it is hard to generate diverse, challenging, and realistic unstructured terrains in simulation, which limits the way researchers evaluate their locomotion policies. In this paper, we prototype the generation of a terrain dataset via terrain authoring and active learning, and t

Gregor Diezemann

The dielectric response of non-interacting dipoles is discussed in the framework of the classical model of stochastic reorientations in an asymmetric double well potential (ADWP). In the nonlinear regime, this model exhibits some pecularities in the static response. We find that the saturation behavior of the symmetric double well potential model does not fo

Yuki Okamoto, Keisuke Imoto, Shinnosuke Takamichi, Takahiro Fukumori

Although several methods of environmental sound synthesis have been proposed, there has been no discussion on how synthesized environmental sounds should be evaluated. Only either subjective or objective evaluations have been conducted in conventional evaluations, and it is not clear what type of evaluation should be carried out. In this paper, we investigat

Yu Cao, Yancheng Wang, Yifei Xue, Huiqing Zhang

Segmentation from point cloud data is essential in many applications such as remote sensing, mobile robots, or autonomous cars. However, the point clouds captured by the 3D range sensor are commonly sparse and unstructured, challenging efficient segmentation. In this paper, we present a fast solution to point cloud instance segmentation with small computatio

Ming Hu, Zhihao Yue, Zhiwei Ling, Xian Wei

As a promising privacy-preserving machine learning method, Federated Learning (FL) enables global model training across clients without compromising their confidential local data. However, existing FL methods suffer from the problem of low inference performance for unevenly distributed data, since most of them rely on Federated Averaging (FedAvg)-based aggre

Rijubrata Kundu, Tushar Kanta Naik, Anupam Singh

A result of Barnea and Isaacs states that if $L$ is a finite dimensional nilpotent Lie algebra with exactly two distinct centralizer dimensions, then nilpotency class of $L$ is either $2$ or $3$. In this article, we classify all such finite dimensional $3$-step nilpotent Lie algebras over a finite field.

Priya Mehta, Sandeep Kumar, Ravi Kumar, Ch. Sobhan Babu

Outlier detection is a challenging activity. Several machine learning techniques are proposed in the literature for outlier detection. In this article, we propose a new training approach for bidirectional GAN (BiGAN) to detect outliers. To validate the proposed approach, we train a BiGAN with the proposed training approach to detect taxpayers, who are manipu

Yakov Veryovkin

The lower central series of the rgiht-angled Coxeter group $RC_\mathcal K$ and the corresponding graded Lie algebra $L(RC_\mathcal K)$ associated with the lower central series of a right-angled Coxeter group are studied. Relations are obtained in the graded components of the Lie algebra $L(RC_\mathcal K)$. A basis of the fourth graded component $L(RC_\mathca

Yaqian Zhang, Yi Zhang, Frede Blaabjerg, Jianzhong Zhang

This paper proposes a non-invasive fault location method for modular multilevel converters (MMC) considering light load conditions. The prior-art fault location methods of the MMC are often developed and verified under full load conditions. However, it is revealed that the faulty arm current will be suppressed to be unipolar when the open-circuit fault happe

B. Müller, B. M. Giuliano, A. Vasyunin, G. Fedoseev

Context. The gas and ice-grain chemistry of the pre-stellar core L1544 has been the subject of several observations and modelling studies conducted in the past years. The chemical composition of the ice mantles reflects the environmental physical changes along the temporal evolution. The investigation outcome hints at a layered structure of interstellar ices

Lixin Zou, Changying Hao, Hengyi Cai, Suqi Cheng

Extracting query-document relevance from the sparse, biased clickthrough log is among the most fundamental tasks in the web search system. Prior art mainly learns a relevance judgment model with semantic features of the query and document and ignores directly counterfactual relevance evaluation from the clicking log. Though the learned semantic matching mode

Xing Wu, Guangyuan Ma, Meng Lin, Zijia Lin

Dense passage retrieval aims to retrieve the relevant passages of a query from a large corpus based on dense representations (i.e., vectors) of the query and the passages. Recent studies have explored improving pre-trained language models to boost dense retrieval performance. This paper proposes CoT-MAE (ConTextual Masked Auto-Encoder), a simple yet effectiv

Tom Zelazny, Haoze Wu, Clark Barrett, Guy Katz

With the increasing application of deep learning in mission-critical systems, there is a growing need to obtain formal guarantees about the behaviors of neural networks. Indeed, many approaches for verifying neural networks have been recently proposed, but these generally struggle with limited scalability or insufficient accuracy. A key component in many sta

Anita Behme, David Oechsler

A distributional equation as a criterion for invariant measures of Markov processes associated to L\'evy-type operators is established. This is obtained via a characterization of infinitesimally invariant measures of the associated generators. Particular focus is put on the one-dimensional case where the distributional equation becomes a Volterra-Fredholm in

Ignacio F. Ranea-Sandoval, Octavio M. Guilera, Mauro Mariani, Germán Lugones

Multi-messenger astronomy with gravitational waves is a blooming area whose limits are not clear. After the first detection of binary black hole merger and the famous event GW170817 and its electromagnetic counterpart, the compact-object astrophysical community is starting to grasp the physical implications of such event and trying to improve numerical model

Yasushi Kawase, Hanna Sumita, Yu Yokoi

We investigate the problem of random assignment of indivisible goods, in which each agent has an ordinal preference and a constraint. Our goal is to characterize the conditions under which there always exists a random assignment that simultaneously satisfies efficiency and envy-freeness. The probabilistic serial mechanism ensures the existence of such an ass

Hanson Bharth, Edward James Brambley

This paper provides an analytical solution for the deformation of an elastic half-space caused by a cylindrical roller. The roller is considered rigid, and is forced into the half space and rolls across its surface, with contact modelled by Coulomb friction. In general, portions of the surface of the roller in contact with the half space may slip across the

Simone Bottoni, Anwitaman Datta, Federico Franzoni, Emanuele Ragnoli

Limited scalability and transaction costs are, among others, some of the critical issues that hamper a wider adoption of distributed ledger technologies (DLT). That is particularly true for the Ethereum blockchain, which, so far, has been the ecosystem with the highest adoption rate. Quite a few solutions, especially on the Ethereum side of things, have been

Shuo Liu, Weize Quan, Ming Zhou, Sihong Chen

Videos contain multi-modal content, and exploring multi-level cross-modal interactions with natural language queries can provide great prominence to text-video retrieval task (TVR). However, new trending methods applying large-scale pre-trained model CLIP for TVR do not focus on multi-modal cues in videos. Furthermore, the traditional methods simply concaten

Kristian Hauser A. Villegas, Reginald Christian Bernardo

Black holes exert quantum pressure coming from the nonlocal gravity correction. We investigate this nonlocal correction for black holes in anti-de Sitter (AdS) spacetime and its dual boundary field theory. We show that the second order curvature and the nonlocal actions do not backreact on the AdS black hole metric. Thus, the interpretation of quantum pressu

J. Ruohotie, E. K. J. Kilpua, S. W. Good, M. Ala-Lahti

Sheath regions of interplanetary coronal mass ejections (ICMEs) are formed when the upstream solar wind is deflected and compressed due to the propagation and expansion of the ICME. Small-scale flux ropes found in the solar wind can thus be swept into ICME-driven sheath regions. They may also be generated locally within the sheaths through a range of process

Ahmed Jellal, Dariush Jahani, Omid Akhavan

We study the energy levels of Dirac-Weyl fermions in graphene subject to a magnetic field with Rashba contribution in the minimal length situation. The exact solution for the energy dispersion of Dirac-like charge carriers coupled to the magnetic moments in a (2+1)-dimension is obtained by the use of the momentum space representation. Moreover, as it comes t

Priya Mehta, Sanat Bhargava, M. Ravi Kumar, K. Sandeep Kumar

Circular trading is a form of tax evasion in Goods and Services Tax where a group of fraudulent taxpayers (traders) aims to mask illegal transactions by superimposing several fictitious transactions (where no value is added to the goods or service) among themselves in a short period. Due to the vast database of taxpayers, it is infeasible for authorities to

Mikhail Freer, Hassan Nosratabadi

An observer wants to understand a decision-maker's welfare from her choice. She believes that decisions are made under limited attention. We argue that the standard model of limited attention cannot help the observer greatly. To address this issue, we study a family of models of choice under limited attention by imposing an attention floor in the decision pr