July 2022 arXiv papers — page 9

Elise van der Pol, Ian Gemp, Yoram Bachrach, Richard Everett

Large graphs commonly appear in social networks, knowledge graphs, recommender systems, life sciences, and decision making problems. Summarizing large graphs by their high level properties is helpful in solving problems in these settings. In spectral clustering, we aim to identify clusters of nodes where most edges fall within clusters and only few edges fal

Elena Pierro

Polymers are ultra-versatile materials that adapt to a myriad of applications, as they can be designed appropriately for specific needs. The realization of new compounds, however, requires the appropriate experimental characterizations, also from the mechanical point of view, which is typically carried out by analyzing the vibrations of beams, but which stil

Alessandro Goffi

We establish a priori Lipschitz estimates for equations with mixed local and nonlocal diffusion, coercive gradient terms and unbounded right-hand side in Lebesgue spaces through an integral refinement of the Bernstein method. This relies on a nonlinear, nonlocal and variational version of the Bochner identity that involves the adjoint equation of the lineari

Hunter Waldron

We provide new Schmidt-type results through an investigation of two bijections, which are results involving partitions with parts counted only at given indices. Mork's bijection, the first of these, was originally given as a proof of Schmidt's theorem. We show that a version of Sylvester's bijection is equivalent to Mork's bijection applied to 2-modular diag

Kshitij Agarwal

The CBM experiment at the Facility for Antiproton and Ion Research (FAIR) aims to explore the QCD phase diagram in the region of high net-baryon densities using nucleus-nucleus collisions ($\sqrt{s_{NN}}$ = 2.9 - 4.9 GeV). CBM will be utilizing peak interaction rates of up to 10 MHz and an advanced triggerless data acquisition scheme to provide it with an un

Dragi Kimovski, Sasko Ristov, Radu Prodan

The introduction of electronic personal health records (EHR) enables nationwide information exchange and curation among different health care systems. However, the current EHR systems do not provide transparent means for diagnosis support, medical research or can utilize the omnipresent data produced by the personal medical devices. Besides, the EHR systems

Julián López-Gómez, Eduardo Muñoz-Hernández, Fabio Zanolin

This paper studies the global structure of the set of nodal solutions of a generalized Sturm--Liouville boundary value problem associated to the quasilinear equation $$ -(\phi(u'))'= \lambda u + a(t)g(u), \quad \lambda\in {\mathbb R}, $$ where $a(t)$ is non-negative with some positive humps separated away by intervals of degeneracy where $a\equiv 0$. When $\

Paolo Acampora, Emanuele Cristoforoni

In this paper, we generalize the notion of relative $p$-capacity of $K$ with respect to $\Omega$, by replacing the Dirichlet boundary condition with a Robin one. We show that, under volume constraints, our notion of $p$-capacity is minimal when $K$ and $\Omega$ are concentric balls. We use the $H$-function and a derearrangement technique.

Zaiquan Yang, Yang Liu, Wenjia Xu, Chong Huang

Zero-shot learning (ZSL) aims to recognize unseen classes by exploiting semantic descriptions shared between seen classes and unseen classes. Current methods show that it is effective to learn visual-semantic alignment by projecting semantic embeddings into the visual space as class prototypes. However, such a projection function is only concerned with seen

Oluwadara Adedeji, Peter Owoade, Opeyemi Ajayi, Olayiwola Arowolo

This study proposes the use of generative models (GANs) for augmenting the EuroSAT dataset for the Land Use and Land Cover (LULC) Classification task. We used DCGAN and WGAN-GP to generate images for each class in the dataset. We then explored the effect of augmenting the original dataset by about 10% in each case on model performance. The choice of GAN arch

Anton V. Proskurnikov, Alexander Davydov, Francesco Bullo

The celebrated S-Lemma was originally proposed to ensure the existence of a quadratic Lyapunov function in the Lur'e problem of absolute stability. A quadratic Lyapunov function is, however, nothing else than a squared Euclidean norm on the state space (that is, a norm induced by an inner product). A natural question arises as to whether squared non-Euclidea

Peng Shen, Xugang Lu, Hisashi Kawai

For Mandarin end-to-end (E2E) automatic speech recognition (ASR) tasks, compared to character-based modeling units, pronunciation-based modeling units could improve the sharing of modeling units in model training but meet homophone problems. In this study, we propose to use a novel pronunciation-aware unique character encoding for building E2E RNN-T-based Ma

Sebastian Göndör, Hakan Yildiz, Martin Westerkamp, Axel Küpper

Decentralized services and applications provide a multitude of advantages for their users, such as improved privacy, control, and independence from third parties. Anyhow, decentralization comes at the cost of certain disadvantages, such as increased application complexity or communication overhead. This aggravates the development and deployment of decentrali

Fabrizio Esposito, Sante Carloni, Stefano Vignolo

Making use of the $1 + 3$ covariant formalism, we show explicitly the effect that nonmetricity has on the dynamics of the universe. Then, using the Dynamical System Approach, we analyze the evolution of Bianchi type-I cosmologies within the framework of $f(\mathcal{Q})$ gravity. We consider several models of function $f(\mathcal{Q})$, each of them manifestin

Jiale Bai, Hui-Ming Wang, Peng Liu

In this paper, we propose a robust secrecy transmission scheme for intelligent reflecting surface (IRS) aided communication systems. Different from all the existing works where IRS has already been deployed at a fixed location, we take the location of IRS as a variable to maximize the secrecy rate (SR) under the outage probability constraint by jointly optim

Raphael Yuster

For a graph $G$, let $c_k(G)$ be the number of spanning trees of $G$ with maximum degree at most $k$. For $k \ge 3$, it is proved that every connected $n$-vertex $r$-regular graph $G$ with $r \ge \frac{n}{k+1}$ satisfies $$ c_k(G)^{1/n} \ge (1-o_n(1)) r \cdot z_k $$ where $z_k > 0$ approaches $1$ extremely fast (e.g. $z_{10}=0.999971$). The minimum degree re

Cem Altun, Ercan Gürses, Hüsnü Dal

This work focuses on planar growth-induced instabilities in three-dimensional bilayer structures, i.e., thick stiff film on a compliant substrate. Growth-induced instabilities are examined for a different range of fiber stiffness with a five-field Hu-Washizu type mixed variational formulation. The quasi-incompressible and quasiinextensible limits of transver

Benedek Kovács, Zoltán Lóránt Nagy

In this paper we continue the study of a natural generalization of Tur\'an's forbidden subgraph problem and the Ruzsa-Szemer\'edi problem. Let $ex_F(n,G)$ denote the maximum number of edge-disjoint copies of a fixed simple graph $F$ that can be placed on an $n$-vertex ground set without forming a subgraph $G$ whose edges are from different $F$-copies. The ca

Jinyu Yang, Zhe Li, Feng Zheng, Aleš Leonardis

Multi-modal tracking gains attention due to its ability to be more accurate and robust in complex scenarios compared to traditional RGB-based tracking. Its key lies in how to fuse multi-modal data and reduce the gap between modalities. However, multi-modal tracking still severely suffers from data deficiency, thus resulting in the insufficient learning of fu

Mingquan Wei, Dunyan Yan

In this paper, by using the rotation method, we calculate that the sharp bound for $n$-dimensional Hardy operator $\mathcal{H}$ on mixed radial-angular spaces. Furthermore, we also obtain the sharp bound for $n$-dimensional fractional Hardy operator $\mathcal{H}_\beta$ from $L^p_{|x|}L_{\theta}^{\bar{p}}({\Bbb R}^n)$ to $L^q_{|x|}L_{\theta}^{\bar{q}}({\Bbb R

Jean Bérard

In this paper, we revisit a classic example of probabilistic cellular automaton (PCA) on {0, 1} Z , namely, addition modulo 2 of the states of the left-and right-neighbouring cells, followed by either preserving the result of the addition, with probability p, or flipping it, with probability 1 -- p. It is well-known that, for any value of p $\in$]0, 1[, this

Da-rong Liu, Po-chun Hsu, Yi-chen Chen, Sung-feng Huang

ASR has been shown to achieve great performance recently. However, most of them rely on massive paired data, which is not feasible for low-resource languages worldwide. This paper investigates how to learn directly from unpaired phone sequences and speech utterances. We design a two-stage iterative framework. GAN training is adopted in the first stage to fin

Andrea Giusti, Gian Carlo Maffettone, Davide Fiore, Marco Coraggio

Geometric pattern formation is crucial in many tasks involving large-scale multi-agent systems. Examples include mobile agents performing surveillance, swarm of drones or robots, or smart transportation systems. Currently, most control strategies proposed to achieve pattern formation in network systems either show good performance but require expensive senso

Furen Deng, Yan Gong, Yougang Wang, Shuting Dong

The cross-correlation of optical galaxies with the neutral hydrogen (HI) radiation intensity can enhance the signal-to-noise ratio (SNR) of the HI intensity measurement. In this paper, we investigate the cross-correlation of the galaxy samples obtained by the spectroscopic survey of the China Space Station Telescope (CSST) with the HI Intensity mapping (IM)

Thomas Giletti, Ho-Youn Kim

In this paper we address the large-time behavior of solutions of bistable and multistable reaction-diffusion equations with discontinuities around the stable steady states. We show that the solution always converges to a special solution, which may either be a traveling wave in the bistable case, or more generally a terrace (i.e. a collection of stacked trav

Olivier Roustant, Nora Lüthen, Fabrice Gamboa

Motivated by uncertainty quantification of complex systems, we aim at finding quadrature formulas of the form $\int_a^b f(x) d\mu(x) = \sum_{i=1}^n w_i f(x_i)$ where $f$ belongs to $H^1(\mu)$. Here, $\mu$ belongs to a class of continuous probability distributions on $[a, b] \subset \mathbb{R}$ and $\sum_{i=1}^n w_i \delta_{x_i}$ is a discrete probability dis

Piotr T. Chruściel, Erwann Delay

We construct families of asymptotically locally hyperbolic Riemannian metrics with constant scalar curvature (i.e., time symmetric vacuum general relativistic initial data sets with negative cosmological constant), with prescribed topology of apparent horizons and of the conformal boundary at infinity, and with controlled mass. In particular we obtain new cl

J. Cheraghalizadeh, M. A. Seifi MirJafarlou, M. N. Najafi

This paper considers a sandpile model subjected to a sinusoidal external drive with the time period $T$. We develop a theoretical model for the Green function in a large $T$ limit, which predicts that the avalanches are anisotropic and elongated in the oscillation direction. We track the problem numerically and show that the system shows additionally a regim

Yuki Kadokawa, Lingwei Zhu, Yoshihisa Tsurumine, Takamitsu Matsubara

Deep reinforcement learning with domain randomization learns a control policy in various simulations with randomized physical and sensor model parameters to become transferable to the real world in a zero-shot setting. However, a huge number of samples are often required to learn an effective policy when the range of randomized parameters is extensive due to

T. Mehta, K. Jain, S. C. Tripathy, R. Kiefer

We investigated the solar cycle dependency on the presence and periodicity of the Quasi-Biennial Oscillation (QBO). Using helioseismic techniques, we used solar oscillation frequencies from the Global Oscillations Network Group (GONG), Michelson Doppler Imager (MDI) and Helioseismic & Magnetic Imager (HMI) in the intermediate-degree range to investigate the

Morenikeji Neri, Thomas Powell

We examine the convergence properties of sequences of nonnegative real numbers that satisfy a particular class of recursive inequalities, from the perspective of proof theory and computability theory. We first establish a number of results concerning rates of convergence, setting out conditions under which computable rates are possible, and when not, providi

Chi Ho Wong

The superior electronic, optical and magnetic properties of carbyne have been called for optoelectronic and magnetoelectronic applications. However, manufacturing a monoatomic chain of more than 6000 carbon atoms presents a huge technical challenge. In order to predict the optimal chain length in different environments, we develop a Monte Carlo model in whic

Joachim Herrmann

This paper pursues the hypothesis that the tangent bundle (TB) with the central extended little groups of the SO(3,1) group as gauge group is the underlying geometric structure for a unified theory of the fundamental physical interactions. Based on this hypothesis as a first step recently I presented a generalized theory of electroweak interaction which incl

Seyed Amir Tafrishi, Ankit A. Ravankar, Yasuhisa Hirata

Quantifying the safety of the human body orientation is an important issue in human-robot interaction. Knowing the changing physical constraints on human motion can improve inspection of safe human motions and bring essential information about stability and normality of human body orientations with real-time risk assessment. Also, this information can be use

Benjamin Fehrman

We prove that diffusion equations with a space-time stationary and ergodic, divergence-free drift homogenize in law to a deterministic stochastic partial differential equation with Stratonovich transport noise. In the absence of spatial ergodicity, the drift is only partially absorbed into the skew-symmetric part of the flux through the use of an appropriate

Jakub Rydzewski, Ming Chen, Tushar K. Ghosh, Omar Valsson

Enhanced sampling methods are indispensable in computational physics and chemistry, where atomistic simulations cannot exhaustively sample the high-dimensional configuration space of dynamical systems due to the sampling problem. A class of such enhanced sampling methods works by identifying a few slow degrees of freedom, termed collective variables (CVs), a

Woowon Byun, Jongwan Ko, Yunjong Kim, Kwang-Il Seon

In a $\Lambda$CDM universe, most galaxies evolve by mergers and accretions, leaving faint and/or diffuse structures, such as tidal streams and stellar halos. Although these structures are a good indicator of galaxies' recent mass assembly history, they have the disadvantage of being difficult to observe due to their low surface brightness (LSB). To recover t

Huimin Huang, Shiao Xie1, Lanfen Lin, Yutaro Iwamoto

Recently, a variety of vision transformers have been developed as their capability of modeling long-range dependency. In current transformer-based backbones for medical image segmentation, convolutional layers were replaced with pure transformers, or transformers were added to the deepest encoder to learn global context. However, there are mainly two challen

Javier Ortega Julia, Daniel Ortega, Jonathan Leliaert

Understanding and predicting the heat released by magnetic nanoparticles is central to magnetic hyperthermia treatment planning. These nanoparticles tend to form aggregates when injected in living tissues, which alters their response to the applied alternating magnetic field and prevents predicting the released heat accurately. We performed an in silico anal

Taira Tsuchiya, Shinji Ito, Junya Honda

This study considers the partial monitoring problem with $k$-actions and $d$-outcomes and provides the first best-of-both-worlds algorithms, whose regrets are favorably bounded both in the stochastic and adversarial regimes. In particular, we show that for non-degenerate locally observable games, the regret is $O(m^2 k^4 \log(T) \log(k_{\Pi} T) / \Delta_{\mi

U. Ozdem

We systematically study the electromagnetic properties of multiquark states. In this study, inspired by the recent series of studies that showed the likely existence of a $ D \bar D^* K$ state, we examine the magnetic moment of $ D \bar D^* K$ hexaquark state in three-meson molecular structure, as well as having isospin and spin-parity quantum numbers $I(J^P

Jiaqi Liao, Mengyu Cao, Mei Lu

Let $t$, $r$, $k$ and $n$ be positive integers and $\mathcal{F}$ a family of $k$-subsets of an $n$-set $V$. The family $ \CF $ is $ r $-wise $ t $-intersecting if for any $ F_1, \ldots, F_r \in \CF $, we have $ \abs{\cap_{i = 1}^{r}F_i}\gs t $. An $ r $-wise $ t $-intersecting family of $ r + 1 $ sets $ \{T_1, \ldots, T_{r + 1}\} $ is called an $ (r + 1,t) $

Luis Torrijos-Morán, Cristina Catalá-Lahoz, Daniel Pérez-López, Li Xu

The linearization of a microwave photonic link based on a dual-parallel Mach-Zehnder modulator is theoretically described and experimentally demonstrated. Up to four different radio frequency tones are considered in the study, which allow us to provide a complete mathematical description of all third-order distortion terms that arise at the photodetector. Si

N. Takka

This work completes a serie of two papers devoted to the extension of the fundamental laws of electrodynamics in the context of Fock's nonlinear relativity (FNLR). Indeed, after having established in the previous study the exact generalizations of both Maxwell's equations and Dirac magnetic monopole, we present here the remaining exact Lorentz force. As in k

Yanchen Li, Qingzhong Ai, Fumihiko Ino

Recently, tile pruning has been widely studied to accelerate the inference of deep neural networks (DNNs). However, we found that the loss due to tile pruning, which can eliminate important elements together with unimportant elements, is large on trained DNNs. In this study, we propose a one-shot reparameterization method, called TileTrans, to reduce the los

Henri Mühle, Eleni Tzanaki

It is well known that the set of $m$-Dyck paths with a fixed height and a fixed amount of valleys is counted by the Fu{\ss}-Narayana numbers. In this article, we consider the set of $m$-Dyck paths that start with at least $t$ north steps. We give exact formulas for the number of such paths with fixed height, fixed number of returns and (i) fixed number of va

Lanchao Wang, Yaojun Chen

Consider two graphs $X$ and $Y$, each with $n$ vertices. The friends-and-strangers graph $\mathsf{FS}(X,Y)$ of $X$ and $Y$ is a graph with vertex set consisting of all bijections $\sigma :V(X) \mapsto V(Y)$, where two bijections $\sigma$, $\sigma'$ are adjacent if and only if they differ precisely on two adjacent vertices of $X$, and the corresponding mappin

V. Chithiika Ruby, V. K. Chandrasekar, M. Lakshmanan

In this paper, we discuss the quantum dynamics of a nonlinear system that admits temporally localized solutions at the classical level. We consider a general ordered position-dependent mass Hamiltonian in which the ordering parameters of the mass term are treated as arbitrary. The mass function here is singular at the origin. We observe that the quantum syst

Nibir Chandra Mandal, G. M. Shahariar, Md. Tanvir Rouf Shawon

The Internet of Things (IoT) is an emerging concept that directly links to the billions of physical items, or "things", that are connected to the Internet and are all gathering and exchanging information between devices and systems. However, IoT devices were not built with security in mind, which might lead to security vulnerabilities in a multi-device syste

Lanyi Xie, Bai Song

Isotope effects on heat conduction and convection have been known for decades. However, whether thermal radiation can be isotopically engineered remains an open question. Here, we predict over 3-orders-of-magnitude variation of radiative heat flow with varying isotopic compositions for polar dielectrics at room temperature. We reveal this as an isotope mass

Daiki Matsumoto, Tomonari Mizoguchi, Yasuhiro Hatsugai

Notion of square-root topological insulators have been recently generalized to higher-order topological insulators. In two-dimensional square-root higher-order topological insulators, emergence of in-gap corner states are inherited from the squared Hamiltonian which hosts higher-order topology. In this paper, we propose that the martini lattice model serves

Yan Lin, Huaiyu Wan, Shengnan Guo, Jilin Hu

Spatio-temporal trajectories provide valuable information about movement and travel behavior, enabling various downstream tasks that in turn power real-world applications. Learning trajectory embeddings can improve task performance but may incur high computational costs and face limited training data availability. Pre-training learns generic embeddings by me

Lorenzo Stasi, Gaëtan Gras, Riad Berrazouane, Matthieu Perrenoud

Photon-number resolving (PNR) single-photon detectors are an enabling technology in many areas such as photonic quantum computing, non-classical light source characterisation and quantum imaging. Here, we demonstrate high-efficiency PNR detectors using a parallel superconducting nanowire single-photon detector (P-SNSPD) architecture that does not suffer from

Abdelmajid Ben Yahya, Nick Van Oosterwyck, Jan Herregodts, Stijn Herregodts

Design optimization of mechanisms is a promising research area as it results in more energy-efficient machines without compromising performance. However, machine builders do not actually use the potential described in the literature as these methods require too much theoretical analysis. This paper introduces a convenient optimization workflow allowing wide

Xiao Fang, Yuta Koike

Let $X_1,\dots,X_n$ be i.i.d. log-concave random vectors in $\mathbb R^d$ with mean 0 and covariance matrix $\Sigma$. We study the problem of quantifying the normal approximation error for $W=n^{-1/2}\sum_{i=1}^nX_i$ with explicit dependence on the dimension $d$. Specifically, without any restriction on $\Sigma$, we show that the approximation error over rec

Heng Ee Tay, Mei Kuan Lim, Chun Yong Chong

Conventional approaches to identify depression are not scalable, and the public has limited awareness of mental health, especially in developing countries. As evident by recent studies, social media has the potential to complement mental health screening on a greater scale. The vast amount of first-person narrative posts in chronological order can provide in

Shivangi Aneja, Cise Midoglu, Duc-Tien Dang-Nguyen, Sohail Ahmed Khan

Cheapfake is a recently coined term that encompasses non-AI (``cheap'') manipulations of multimedia content. Cheapfakes are known to be more prevalent than deepfakes. Cheapfake media can be created using editing software for image/video manipulations, or even without using any software, by simply altering the context of an image/video by sharing the media al

Changji Xu, Fan Yang, Horng-Tzer Yau, Jun Yin

We consider Hermitian random band matrices $H=(h_{xy})$ on the $d$-dimensional lattice $(\mathbb Z/L \mathbb Z)^d$, where the entries $h_{xy}=\overline h_{yx}$ are independent centered complex Gaussian random variables with variances $s_{xy}=\mathbb E|h_{xy}|^2$. The variance matrix $S=(s_{xy})$ has a banded profile so that $s_{xy}$ is negligible if $|x-y|$

Jie-Wen Chen, Mian Zhu, Sheng-Feng Yan, Qing-Qing Wang

The non-singular bouncing cosmology is an alternative paradigm to inflation, wherein the background energy density vanishes at the bounce point, in the context of Einstein gravity. Therefore, the non-linear effects in the evolution of density fluctuations ($\delta \rho$) may be strong in the bounce phase, which potentially provides a mechanism to enhance the

N. Takka, A. Bouda

On the basis of all commutation relations of the k-deformed phase space incorporating the k-Minkowski space-time, we have derived in this paper an extended first approximation of both Maxwell's equations and Lorentz force in doubly (or deformed) special relativity (DSR). For this purpose, we have used our approach of the special relativistic version of Feynm

Sebastian Falkner, Alessandro Coretti, Salvatore Romano, Phillip Geissler

Understanding the dynamics of complex molecular processes is often linked to the study of infrequent transitions between long-lived stable states. The standard approach to the sampling of such rare events is to generate an ensemble of transition paths using a random walk in trajectory space. This, however, comes with the drawback of strong correlations betwe

Federica Baccini, Lucio Barabesi, Eugenio Petrovich

We introduce a methodology based on averaging similarity matrices with the aim of integrating the layers of a multiplex network into a single monoplex network. Multiplex networks are adopted for modelling a wide variety of real-world frameworks, such as multi-type relations in social, economic and biological structures. More specifically, multiplex networks

Subhajit Sarkar, Ieng Wai Un, Yonatan Sivan

Many low electron density Drude (LEDD) materials such as transparent conductive oxide or nitrides have recently attracted interest as alternative plasmonic materials and future nonlinear optical materials. However, the rapidly growing number of experimental studies has so far not been supported by a systematic theory of the electronic, thermal and optical re

Ying Sun, Jianbo Wang

Let $X$ be a finitistic space with the mod 2 cohomology of the product space of a projective space and a 4-sphere. Assume that $X$ admits a free involution. In this paper we study the mod 2 cohomology algebra of the quotient of $X$ by the action of the free involution and derive some consequences regarding the existence of $\mathbb{Z}_2$-equivariant maps bet

Stefano Teso, Öznur Alkan, Wolfang Stammer, Elizabeth Daly

Explanations have gained an increasing level of interest in the AI and Machine Learning (ML) communities in order to improve model transparency and allow users to form a mental model of a trained ML model. However, explanations can go beyond this one way communication as a mechanism to elicit user control, because once users understand, they can then provide

Tejas Srinivasan, Xiang Ren, Jesse Thomason

Aligning image and text encoders from scratch using contrastive learning requires large amounts of paired image-text data. We alleviate this need by aligning individually pre-trained language and vision representation models using a much smaller amount of paired data, augmented with a curriculum learning algorithm to learn fine-grained vision-language alignm

Hongjiu Yu, Qiancheng Sun, Jin Hu, Xingyuan Xue

Learned image compression has achieved extraordinary rate-distortion performance in PSNR and MS-SSIM compared to traditional methods. However, it suffers from intensive computation, which is intolerable for real-world applications and leads to its limited industrial application for now. In this paper, we introduce neural architecture search (NAS) to designin

Evelia R. García Barroso, Arkadiusz Płoski

Given an algebroid plane curve $f=0$ over an algebraically closed field of characteristic $p\geq 0$ we consider the Milnor number $\mu(f)$, the delta invariant $\delta(f)$ and the number $r(f)$ of its irreducible components. Put $\bar \mu(f)=2\delta(f)-r(f)+1$. If $p=0$ then $\bar \mu (f)=\mu(f)$ (the Milnor formula). If $p>0$ then $\mu(f)$ is not an invaria

Chayan Chatterjee, Manoj Kovalam, Linqing Wen, Damon Beveridge

The mergers of neutron star-neutron star and neutron star-black hole binaries are the most promising gravitational wave events with electromagnetic counterparts. The rapid detection, localization and simultaneous multi-messenger follow-up of these sources is of primary importance in the upcoming science runs of the LIGO-Virgo-KAGRA Collaboration. While promp

Qingkai Yang, Fan Xiao, Jingshuo Lyu, Bo Zhou

This paper studies the problem of controlling a multi-robot system to achieve a polygon formation in a self-organized manner. Different from the typical formation control strategies where robots are steered to satisfy the predefined control variables, such as pairwise distances, relative positions and bearings, the foremost idea of this paper is to achieve p

Soohwan Oh, Yoonjin Yoon

One of the challenges of Unmanned Aircraft System (UAS) operations is to operate an unmanned aircraft with minimal risk to people on the ground. The purpose of this study is to define and measure such risks as population risk, by incorporating spatiotemporal changes in population density. Unlike previous studies, we use high-resolution de facto population da

Yang Xiao, Jin Min Yang, Yang Zhang

We study the dilution of dark matter (DM) relic density caused by the electroweak first-order phase transition (FOPT) in the singlet extension models, including the singlet extension of the standard model (xSM), of the two-Higgs-doublet model (2HDM+S) and the next-to-minimal supersymmetric standard model (NMSSM). We find that in these models the entropy rele

Haowu Wang, Brandon Williams

In this paper we consider several problems in the theory of automorphic products and generalized Kac--Moody algebras proposed by Borcherds in 1995. We show that the denominator of the fake monster algebra defines the unique holomorphic Borcherds product of singular weight on a maximal lattice. We give a full classification of symmetric holomorphic Borcherds

Chao-Jun Feng, Ao Guo, Zhong-Ming Xie, Miao Li

When a gravitational wave or a graviton travels through an electric or magnetic background, it could convert into a photon with some probability. In this paper, a dipole magnetic field is considered as this kind of background in both the Minkowski spacetime and the curved spacetime in the near-zone of a neutron star. In the former case, we find that the grav

Peter Fiebig

We show that tilting modules for quantum groups over local Noetherian domains exist and that the indecomposable tilting modules are parametrized by their highest weight. For this we introduce a model category ${\mathcal X}={\mathcal X}_{\mathscr A}(R)$ associated with a Noetherian ${\mathbb Z}[v,v^{-1}]$-domain ${\mathscr A}$ and a root system $R$. We show t

Bowen Wang, Kai Wang, Hanying Xiong

Precision measurement of quark Yukawa couplings is a crucial aspect of Higgs property study. Proposed as a future upgrade of the Large Hadron Collider (LHC), the Large Hadron electron Collider (LHeC) provides opportunities to probe quark Yukawa couplings with a high precision because of relatively low rate from QCD background as compared with that of the Hig

Dirk Tasche

Factorizable joint shift (FJS) was recently proposed as a type of dataset shift for which the complete characteristics can be estimated from feature data observations on the test dataset by a method called Joint Importance Aligning. For the multinomial (multiclass) classification setting, we derive a representation of factorizable joint shift in terms of the

Caixia Zhou, Yaping Huang

Automatic action quality assessment (AQA) has attracted increasing attention due to its wide applications. However, most existing AQA methods employ deterministic models to predict the final score for each action, while overlooking the subjectivity and diversity among expert judges during the scoring process. In this paper, we propose a novel probabilistic m

Fateme Eslami, Hossein Hamzehpour, Sanaz Derikvandi, S. Amir Bahrani

The interaction acoustic radiation force in a standing plane wave applied to each small solid sphere in a two-particle system immersed in a viscoelastic fluid is studied in a framework based on perturbation theory. In this work, the first- and second-order perturbation theories are used in the governing equations with considering the upper-convected maxwell

H. M. Schmid

Many spectacular polarimetric images have been obtained in recent years with adaptive optics (AO) instruments at large telescopes because they profit significantly from the high spatial resolution. This paper summarizes some basic principles for AO polarimetry, discusses challenges and limitations of these systems, and describes results which illustrate the

Yannick Kluth, Daniel Litim, Manuel Reichert

We investigate spectral functions of matter-gauge theories that are asymptotically free in the ultraviolet and display a Banks-Zaks conformal fixed point in the infrared. Using perturbation theory, Callan-Symanzik resummations, and UV-IR connecting renormalisation group trajectories, we analytically determine the gluon, quark, and ghost propagators in the en

Jia Wang, Hui Hu, Xia-Ji Liu

We present a full microscopic many-body calculation of a recently-proposed nonlinear two-dimensional spectroscopy for Fermi polarons, and show that the quantum coherence between the attractive and repulsive polarons, which has never been experimentally examined, can be unambiguously revealed via quantum beats at the two off-diagonal crosspeaks in the two-dim

Jonas Dippel, Matthias Lenga, Thomas Goerttler, Klaus Obermayer

It is common practice to reuse models initially trained on different data to increase downstream task performance. Especially in the computer vision domain, ImageNet-pretrained weights have been successfully used for various tasks. In this work, we investigate the impact of transfer learning for segmentation problems, being pixel-wise classification problems

Andrea Montibeller, Cecilia Pasquini, Giulia Boato, Stefano Dell'Anna

Video stabilization is an in-camera processing commonly applied by modern acquisition devices. While significantly improving the visual quality of the resulting videos, it has been shown that such operation typically hinders the forensic analysis of video signals. In fact, the correct identification of the acquisition source usually based on Photo Response n

Pedro V. P. Cunha, Carlos A. R. Herdeiro, João P. A. Novo

The motion of particles on spherical $1 + 3$ dimensional spacetimes can, under some assumptions, be described by the curves on a 2-dimensional manifold, the optical and Jacobi manifolds for null and timelike curves, respectively. In this paper we resort to auxiliary 2-dimensional metrics to study circular geodesics of generic static, spherically symmetric, a

Rufat Badal, Manuel Friedrich, Joscha Seutter

We consider atomistic systems consisting of interacting particles arranged in atomic lattices whose quasi-static evolution is driven by time-dependent boundary conditions. The interaction of the particles is modeled by classical interaction potentials where we implement a suitable irreversibility condition modeling the breaking of atomic bonding. This leads

Berndt Müller, Di-Lun Yang

We study the important, yet widely overlooked, role of gluons for spin transport with a connection to local parity violation in quark gluon plasmas. We extend the newly developed quantum kinetic theory for relativistic fermions to the case coupled with non-Abelian chromo-electromagnetic fields and employ this formalism to investigate the spin polarization of

Michael Thies

We reconsider the two-flavor version of the massive, chiral Gross-Neveu model in 1+1 dimensions. Its phase diagram as a function of baryon chemical potential, isospin chemical potential and temperature has previously been explored. We recapitulate the results, adding the missing tricritical curves. They can be determined exactly by extending the standard sta

Patrick Haluptzok, Matthew Bowers, Adam Tauman Kalai

Recent Language Models (LMs) achieve breakthrough performance in code generation when trained on human-authored problems, even solving some competitive-programming problems. Self-play has proven useful in games such as Go, and thus it is natural to ask whether LMs can generate their own instructive programming problems to improve their performance. We show t

A. S. Baltenkov, I. Woiciechowski

The article discusses the correctness of the assumption about the similarity of molecular continuum electron functions with wave functions in electron-atom scattering. The elastic scattering of slow particles by pair of non-overlapping short-range potentials has been studied. The continuum wave function of particle is represented as a combination of a plane

Guangmiao Zeng, Wanneng Yu, Rongjie Wang, Anhui Lin

Marine vessel re-identification technology is an important component of intelligent shipping systems and an important part of the visual perception tasks required for marine surveillance. However, unlike the situation on land, the maritime environment is complex and variable with fewer samples, and it is more difficult to perform vessel re-identification at

Saptarshi Sinha, Hiroki Ohashi, Katsuyuki Nakamura

Long-tailed datasets are very frequently encountered in real-world use cases where few classes or categories (known as majority or head classes) have higher number of data samples compared to the other classes (known as minority or tail classes). Training deep neural networks on such datasets gives results biased towards the head classes. So far, researchers

Taorong Liu, Liang Liao, Zheng Wang, Shin'ichi Satoh

Existing learning-based image inpainting methods are still in challenge when facing complex semantic environments and diverse hole patterns. The prior information learned from the large scale training data is still insufficient for these situations. Reference images captured covering the same scenes share similar texture and structure priors with the corrupt

Andrew P. C. Underwood, Andrew J. Groszek, Xiaoquan Yu, P. B. Blakie

A two-dimensional (2D) spin-1 Bose gas exhibits two Berezenskii-Kosterlitz-Thouless (BKT) transitions in the easy-plane ferromagnetic phase. The higher temperature transition is associated with superfluidity of the mass current determined predominantly by a single spin component. The lower temperature transition is associated with superfluidity of the axial

Christoph Schwarzmeier, Ulrich Rüde

Simulating mobile liquid-gas interfaces with the free-surface lattice Boltzmann method (FSLBM) requires frequent re-initialization of fluid flow information in computational cells that convert from gas to liquid. The corresponding algorithm, here referred to as the refilling scheme, is crucial for the successful application of the FSLBM in terms of accuracy

Octavio A. Agustín-Aquino

Wang and Sun proved a certain summatory formula involving derangements and primitive roots of the unit. We study such a formula but for the particular case of the set of affine derangements in $\overrightarrow{GL}(\mathbb{Z}/2k\mathbb{Z})$ and its subset of involutive affine derangements in particular; in this last case its value is relatively simple and it

Yue Cao, Hao Li, Shengguo Zhu

We consider the initial-boundary value problem (IBVP) for the isentropic compressible Navier-Stokes equations (\textbf{CNS}) in the domain exterior to a ball in $\mathbb R^d$ $(d=2\ \text{or} \ 3)$. When viscosity coefficients are given as a constant multiple of the mass density $\rho$, based on some analysis of the nonlinear structure of this system, we pro

Cheng Cheng, Wei Shyy, Lin Fu

We develop a new methodology to assess the streamwise inclination angles (SIAs) of the wall-attached eddies populating the logarithmic region with a given wall-normal height. To remove the influences originating from other scales on the SIA estimated via two-point correlation, the footprints of the targeted eddies in the vicinity of the wall and the correspo

Adela Gherga, Samir Siksek

A Thue-Mahler equation is a Diophantine equation of the form $$F(X,Y) = a\cdot p_1^{z_1}\cdots p_v^{z_v}, \qquad \gcd(X,Y)=1$$ where $F$ be an irreducible homogeneous binary form of degree at least $3$ with integer coefficients, $a$ is a non-zero integer and $p_1, \dots, p_v$ are rational primes. Existing algorithms for resolving such equations require compu

Chaerin Kong, Nojun Kwak

The capacity to learn incrementally from an online stream of data is an envied trait of human learners, as deep neural networks typically suffer from catastrophic forgetting and stability-plasticity dilemma. Several works have previously explored incremental few-shot learning, a task with greater challenges due to data constraint, mostly in classification se