July 2023 arXiv papers — page 90

Giacomo Arcieri, Cyprien Hoelzl, Oliver Schwery, Daniel Straub

Partially Observable Markov Decision Processes (POMDPs) can model complex sequential decision-making problems under stochastic and uncertain environments. A main reason hindering their broad adoption in real-world applications is the lack of availability of a suitable POMDP model or a simulator thereof. Available solution algorithms, such as Reinforcement Le

Amílcar Branquinho, Ana Foulquié-Moreno, Manuel Mañas

Banded bounded matrices, which represent non normal operators, of oscillatory type that admit a positive bidiagonal factorization are considered. To motivate the relevance of the oscillatory character the Favard theorem for Jacobi matrices is revisited and it is shown that after an adequate shift of the Jacobi matrix one gets an oscillatory matrix. In this w

Yulin Wang, Chihao Zhang, Zihan Zhang

We prove that the single-site Glauber dynamics for sampling proper $q$-colorings mixes in $O_\Delta(n\log n)$ time on line graphs with $n$ vertices and maximum degree $\Delta$ when $q>(1+o(1))\Delta$. The main tool in our proof is the matrix trickle-down theorem developed by Abdolazimi, Liu and Oveis Gharan (FOCS, 2021).

Likun Zhang, Xiaoyu Ma, Christopher K. Wikle, Raphaël Huser

Many real-world processes have complex tail dependence structures that cannot be characterized using classical Gaussian processes. More flexible spatial extremes models exhibit appealing extremal dependence properties but are often exceedingly prohibitive to fit and simulate from in high dimensions. In this paper, we aim to push the boundaries on computation

Bin Fan

In this paper, we consider a numerical method for the multi-term Caputo-Fabrizio time-fractional diffusion equations (with orders $\alpha_i\in(0,1)$, $i=1,2,\cdots,n$). The proposed method employs a fast finite difference scheme to approximate multi-term fractional derivatives in time, requiring only $O(1)$ storage and $O(N_T)$ computational complexity, wher

José Antonio Carrillo, Pierre Roux, Susanne Solem

A system of partial differential equations representing stochastic neural fields was recently proposed with the aim of modelling the activity of noisy grid cells when a mammal travels through physical space. The system was rigorously derived from a stochastic particle system and its noise-driven pattern-forming bifurcations have been characterised. However,

Shuo-Yen Lin, Ernie Chu, Che-Hsien Lin, Jun-Cheng Chen

Many physical adversarial patch generation methods are widely proposed to protect personal privacy from malicious monitoring using object detectors. However, they usually fail to generate satisfactory patch images in terms of both stealthiness and attack performance without making huge efforts on careful hyperparameter tuning. To address this issue, we propo

Itsaso Fernández-Irisarri, Manuel Mañas

In this paper, the authors investigate the case of discrete multiple orthogonal polynomials with two weights on the step line, which satisfy Pearson equations. The discrete multiple orthogonal polynomials in question are expressed in terms of tau functions, which are double Wronskians of generalized hypergeometric series. The shifts in the spectral parameter

Longyue Wang, Zefeng Du, Donghuai Liu, Deng Cai

Modeling discourse -- the linguistic phenomena that go beyond individual sentences, is a fundamental yet challenging aspect of natural language processing (NLP). However, existing evaluation benchmarks primarily focus on the evaluation of inter-sentence properties and overlook critical discourse phenomena that cross sentences. To bridge the gap, we propose D

Yumeng Xue, Patrick Paetzold, Rebecca Kehlbeck, Bin Chen

Line-based density plots are used to reduce visual clutter in line charts with a multitude of individual lines. However, these traditional density plots are often perceived ambiguously, which obstructs the user's identification of underlying trends in complex datasets. Thus, we propose a novel image space coloring method for line-based density plots that enh

I. Mullyadzhanov, A. Gudko, R. Mullyadzhanov, A. Gelash

We consider the model of the focusing one-dimensional nonlinear Schr\"odinger equation (fNLSE) in the presence of an unstable constant background, which exhibits coherent solitary wave structures -- breathers. Within the inverse scattering transform (IST) method, we study the problem of the scattering data numerical computation for a broad class of breathers

Kalika Prasad, Munesh Kumari, Rabiranjan Mohanta, Hrishikesh Mahato

In this article, we introduce and study a new integer sequence referred to as the higher order Mersenne sequence. The proposed sequence is analogous to the higher order Fibonacci numbers and closely associated with the Mersenne numbers. Here, we discuss various algebraic properties such as Binet's formula, Catalan's identity, d'Ocagne's identity, generating

Peiyu Liu, Zikang Liu, Ze-Feng Gao, Dawei Gao

Despite the superior performance, Large Language Models~(LLMs) require significant computational resources for deployment and use. To overcome this issue, quantization methods have been widely applied to reduce the memory footprint of LLMs as well as increasing the inference rate. However, a major challenge is that low-bit quantization methods often lead to

Deblina Bhattacharjee, Sabine Süsstrunk, Mathieu Salzmann

In this paper, we develop a MultiTask Learning (MTL) model to achieve dense predictions for comics panels to, in turn, facilitate the transfer of comics from one publication channel to another by assisting authors in the task of reconfiguring their narratives. Our MTL method can successfully identify the semantic units as well as the embedded notion of 3D in

M. Zakaria Kurdi

Objective: this study has a twofold goal. First, it aims to improve the understanding of the impact of Dementia of type Alzheimer's Disease (AD) on different aspects of the lexicon. Second, it aims to demonstrate that such aspects of the lexicon, when used as features of a machine learning classifier, can help achieve state-of-the-art performance in automati

Ernest van Wijland, Hang Zhou

In the Euclidean $k$-traveling salesman problem ($k$-TSP), we are given $n$ points in the $d$-dimensional Euclidean space, for some fixed constant $d\geq 2$, and a positive integer $k$. The goal is to find a shortest tour visiting at least $k$ points. We give an approximation scheme for the Euclidean $k$-TSP in time $n\cdot 2^{O(1/\varepsilon^{d-1})} \cdot(\

Rainer Spurzem, Francesco Rizzuto, Manuel Arca Sedda, Albrecht Kamlah

The evolution of dense star clusters is followed by direct high-accuracy N-body simulation. The problem is to first order a gravitational N-body problem, but stars evolve due to astrophysics and the more massive ones form black holes or neutron stars as compact remnants at the end of their life. After including updates of stellar evolution of massive stars a

Howard Baer, Vernon Barger, Juhi Dutta, Dibyashree Sengupta

Supersymmetric models with low electroweak finetuning are expected to be more prevalent on the string landscape than finetuned models. We assume a fertile patch of landscape vacua containing the minimal supersymmetric standard model (MSSM) as low energy/weak scale effective field theory (LE-EFT). Then, a statistical pull by the landscape to large soft terms

Mei Si, Linliang Song

In this paper, we compute Gram determinants associated to all cell modules of quantized walled Brauer algebras $\mathscr B_{r, t}(\rho, q)$ over an arbitrary field $\kappa$. Suppose $e$ is the quantum characteristic of $q^2$. We classify the blocks of $\mathscr B_{r, t}(\rho, q)$ when $e>\max\{r,t\}$ and $\rho^2=q^{2n}$, $n\in\mathbb Z$. As an application, w

Mohanad Odema, Halima Bouzidi, Hamza Ouarnoughi, Smail Niar

Graph Neural Networks (GNNs) are becoming increasingly popular for vision-based applications due to their intrinsic capacity in modeling structural and contextual relations between various parts of an image frame. On another front, the rising popularity of deep vision-based applications at the edge has been facilitated by the recent advancements in heterogen

Nikolai Larkin

We formulate on rectangles and on the right horizontal half-strip initial-boundary value problems for a two-dimensional Benney-Lin type equation. Existence and uniqueness of a regular solution as well as the exponential decay rate for the norm of a regular solution have been established.

Óscar Ciaurri, Luis M. Navas, Francisco J. Ruiz, Juan L. Varona

We present some simple proofs of the well-known expressions for \[ \zeta(2k) = \sum_{m=1}^\infty \frac{1}{m^{2k}}, \qquad \beta(2k+1) = \sum_{m=0}^\infty \frac{(-1)^m}{(2m+1)^{2k+1}}, \] where $k = 1,2,3,\dots$, in terms of the Bernoulli and Euler polynomials. The computation is done using only the defining properties of these polynomials and employing teles

Rui Guo, Yingwei Fan, Bowei Liu, Xiaofeng Qian

Purpose: To develop and evaluate a cardiovascular magnetic resonance sequence (MyoFold) for rapid myocardial tissue and movement characterization. Method: MyoFold sequentially performs joint T1/T2 mapping and cine for one left-ventricle slice within a breathing-holding of 12 heartbeats. MyoFold uses balanced Steady-State-Free-Precession (bSSFP) with 2-fold a

Hebing Rui, Linliang Song

A strict monoidal category referred to as affine Brauer category $\mathcal{AB}$ is introduced over a commutative ring $\kappa$ containing multiplicative identity $1$ and invertible element $2$. We prove that morphism spaces in $\mathcal{AB}$ are free over $\kappa$. The cyclotomic (or level $k$) Brauer category $\mathcal{CB}^f(\omega)$ is a quotient category

Yujie Zhao, Yang Zhao, Cheng Wan, Yingyan Lin

Environmental sustainability is crucial for Integrated Circuits (ICs) across their lifecycle, particularly in manufacturing and use. Meanwhile, ICs using 3D/2.5D integration technologies have emerged as promising solutions to meet the growing demands for computational power. However, there is a distinct lack of carbon modeling tools for 3D/2.5D ICs. Addressi

Haonan Yin, Guanlong Jiao, Qianhui Wu, Borje F. Karlsson

In the context of flexible manufacturing systems that are required to produce different types and quantities of products with minimal reconfiguration, this paper addresses the problem of unsupervised multi-class anomaly detection: develop a unified model to detect anomalies from objects belonging to multiple classes when only normal data is accessible. We fi

Evangelos G. Filothodoros

I point out that the $U(N)$ Chern-Simons $3d$ theory coupled to fermions at finite temperature and at a specific mean field approximation and the $3d$ Gross-Neveu model at finite temperature and imaginary chemical potential can give us the same results for the thermodynamic values of the free-energy and the saddle point equation for the thermal mass. I furth

Yuming Liu, Lleonard Rubio y Degrassi, Can Wen

In a previous paper arXiv:2211.05435 we have compared the Hochschild cohomology groups of finite dimensional monomial algebras under gluing two idempotents. In the present paper, we compare the Hochschild cohomology groups of finite dimensional monomial algebras under gluing two arrows.

Luyining Gan, Jie Han, Jie Hu

A $K_r$-factor of a graph $G$ is a collection of vertex-disjoint $r$-cliques covering $V(G)$. We prove the following algorithmic version of the classical Hajnal--Szemer\'edi Theorem in graph theory, when $r$ is considered as a constant. Given $r, c, n\in \mathbb{N}$ such that $n\in r\mathbb N$, let $G$ be an $n$-vertex graph with minimum degree at least $(1-

Dominik Schäffner, Tobias Schreiber, Fabian Lenz, Malte Schlosser

We implement a scalable platform for quantum sensing comprising hundreds of sites capable of holding individual laser-cooled atoms and demonstrate the applicability of this single-quantum-system sensor array to magnetic-field mapping on a two-dimensional grid. With each atom being confined in an optical tweezer within an area of 0.5 micrometer^2 at mutual se

Mengmeng Gao, Hebing Rui, Linliang Song

Let $\mathcal B(\delta)$ be the Brauer category over the complex field $\mathbb C$ with the parameter $\delta$. In non-semisimple case, $\delta$ is an integer, and each weight space of $(\frac{\delta}2-1)$th semi-infinite wedge space corresponds to either a single block or a union of two different blocks of $\mathcal B(\delta)$-lfdmod, the category of the lo

Zhonghua Sun, Cunsheng Ding, Tingfang Chen

The classical way of extending an $[n, k, d]$ linear code $\C$ is to add an overall parity-check coordinate to each codeword of the linear code $\C$. This extended code, denoted by $\overline{\C}(-\bone)$ and called the standardly extended code of $\C$, is a linear code with parameters $[n+1, k, \bar{d}]$, where $\bar{d}=d$ or $\bar{d}=d+1$. This is one of t

Shuang Du, Tingting Lin, Shujin Hou, Renxin Xu

It seems that the wealth of information revealed by the multi-messenger observations of the binary neutron star (NS) merger event, GW170817/GRB 170817A/kilonova AT2017gfo, places irreconcilable constraints to models of the prompt emission of this gamma-ray burst (GRB). The observed time delay between the merger of the two NSs and the trigger of the GRB and t

Dipankar Das

With a novel search algorithm or assortment planning or assortment optimization algorithm that takes into account a Bayesian approach to information updating and two-stage assortment optimization techniques, the current research provides a novel concept of competitiveness in the digital marketplace. Via the search algorithm, there is competition between the

Lisa Willemsen, Anne Remke, Erika Ábrahám

Different stochastic extensions of hybrid automata have been proposed in the past, with unclear expressivity relations between them. To structure and relate these modeling languages, in this paper we formalize two alternative approaches to extend hybrid automata with stochastic choices of discrete events and their time points. The first approach, which we ca

Zhenqi He, Mathias Unberath, Jing Ke, Yiqing Shen

Nuclei appear small in size, yet, in real clinical practice, the global spatial information and correlation of the color or brightness contrast between nuclei and background, have been considered a crucial component for accurate nuclei segmentation. However, the field of automatic nuclei segmentation is dominated by Convolutional Neural Networks (CNNs), mean

Bayezid Al Hossain Onee, Kaniz Fatema Antora, Omar Sharif Rajme, Nafees Mansoor

The COVID-19 pandemic has caused a surge in the use of online delivery services, which rely on user-generated content to promote collaborative consumption. Although Online Food Delivery (OFD) is a popular delivery system in Bangladesh, it has yet to ensure item authenticity, especially with the increasing demand for lightweight commodity delivery services ac

Catherine E. A. Mulligan, Phil Godsiff

The increasing use of data in various parts of the economic and social systems is creating a new form of monopoly: data monopolies. We illustrate that the companies using these strategies, Datalists, are challenging the existing definitions used within Monopoly Capital Theory (MCT). Datalists are pursuing a different type of monopoly control than traditional

Tejashwini P S, Thriveni J, Venugopal K R

Brain tumor is deliberated as one of the severe health complications which lead to decrease in life expectancy of the individuals and is also considered as a prominent cause of mortality worldwide. Therefore, timely detection and prediction of brain tumors can be helpful to prevent death rates due to brain tumors. Biomedical image analysis is a widely known

Jonas O. Brown, Maedeh Taheri, Fariborz Kargar, Ruben Salgado

We investigated the temperature dependence of the conductance fluctuations in thin films of the quasi-two-dimensional 1T-TaS$_2$ van der Waals material. The conductance fluctuations, determined from the derivative current-voltage characteristics of two-terminal 1T-TaS$_2$ devices, appear prominently at the electric fields that correspond to the transitions b

Kingman Cheung, C. J. Ouseph, Po-Yan Tseng

This study investigates the classical Higgs inflation model with a modified Higgs potential featuring a dip. We examine the implications of this modification on the generation of curvature perturbations, stochastic gravitational wave production, and the potential formation of primordial black holes (PBHs). Unlike the classical model, the modified potential a

Xuyang Guo, Zhao Song, Xin Yang, Ruizhe Zhang

As large language models (LLMs) demonstrate outstanding performance across various tasks, attention-driven models have profoundly transformed the field of machine learning. Since attention computations account for the primary computational overhead in both model inference and training, efficiently computing attention matrices has become one of the core chall

Hyunjun Lee, Junhyun Lee, Taehwa Choi, Jaewoo Kang

Time-to-event analysis, also known as survival analysis, aims to predict the time of occurrence of an event, given a set of features. One of the major challenges in this area is dealing with censored data, which can make learning algorithms more complex. Traditional methods such as Cox's proportional hazards model and the accelerated failure time (AFT) model

Han Xiao, Xiaoyan Hu, Ang Li, Wenjie Wang

This paper investigates the utilization of simultaneously transmitting and reflecting RIS (STAR-RIS) in supporting joint physical layer security (PLS) and covert communications (CCs) in a multi-antenna millimeter wave (mmWave) system, where the base station (BS) communicates with both covert and security users while defeating eavesdropping by wardens with th

Ranjani Seshadri, T. Pereg-Barnea

The effect of a time-periodic perturbation, such as radiation, on a system otherwise at equilibrium has been studied in the context of Floquet theory with stationary states replaced by Floquet states and the energy replaced by quasienergy. These quasienergy bands in general differ from the energy bands in their dispersion and, especially in the presence of s

Yuying Ge, Yixiao Ge, Ziyun Zeng, Xintao Wang

We present SEED, an elaborate image tokenizer that empowers Large Language Models (LLMs) with the emergent ability to SEE and Draw at the same time. Research on image tokenizers has previously reached an impasse, as frameworks employing quantized visual tokens have lost prominence due to subpar performance and convergence in multimodal comprehension (compare

Ozan Candogan, Manxi Wu

In this paper, we study platforms where resources and jobs are spatially distributed, and resources have the flexibility to strategically move to different locations for better payoffs. The price of the service at each location depends on the number of resources present and the market size, which is modeled as a random state. Our focus is on how the platform

Licheng Zhang, Yuanqiu Huang

A cactus is a connected graph in which each edge is contained in at most one cycle. We generalize the concept of cactus graphs, i.e., a $k$-cactus is a connected graph in which each edge is contained in at most $k$ cycles where $k\ge 1$. It is well known that every cactus with $n$ vertices has at most $\lfloor\frac{3}{2}(n-1) \rfloor$ edges. Inspired by it,

Hebing Rui, Linliang Song

We study representations of the locally unital and locally finite dimensional algebra $B$ associated to the Brauer category $\mathcal B(\delta_0)$ with defining parameter $\delta_0$ over an algebraically closed field $K$ with characteristic $p\neq 2$. The Grothendieck group $K_0(B\text{-mod}^\Delta)$ will be used to categorify the integrable highest weight $

Pratik Nag, Ying Sun, Brian J Reich

High spatial resolution wind data are essential for a wide range of applications in climate, oceanographic and meteorological studies. Large-scale spatial interpolation or downscaling of bivariate wind fields having velocity in two dimensions is a challenging task because wind data tend to be non-Gaussian with high spatial variability and heterogeneity. In s

M. Godsi, A. Golombek, M. Balasubrahmaniyam, T. Schwartz

Recently, we predicted theoretically that in cavities that support several longitudinal modes, strong coupling can occur in very different manners, depending on the system parameters. Distinct longitudinal cavity modes are either entangled with each other via the material or independently coupled to the exciton mode. Here we experimentally demonstrate the tr

Nicos Isaak

Textual content around us is growing on a daily basis. Numerous articles are being written as we speak on online newspapers, blogs, or social media. Similarly, recent advances in the AI field, like language models or traditional classic AI approaches, are utilizing all the above to improve their learned representation to tackle NLP challenges with human-like

Yaorui Tan, Maolin Bo

In this paper, the electronic structure and bond properties of MoS2, MoSe2 and MoTe2 are studied. Density functional theory (DFT) calculates combined with the binding energy and bond-charge (BBC) model to obtain electronic structure, binding energy shift and bond properties. It is found that electrostatic shielding by electron exchange is the main cause of d

Kazuki Watanabe, Clovis Eberhart, Kazuyuki Asada, Ichiro Hasuo

Following our recent development of a compositional model checking algorithm for Markov decision processes, we present a compositional framework for solving mean payoff games (MPGs). The framework is derived from category theory, specifically that of monoidal categories: MPGs (extended with open ends) get composed in so-called string diagrams and thus organi

Hongyu Ding, Yuanze Tang, Qing Wu, Bo Wang

Goal-conditioned reinforcement learning (RL) is an interesting extension of the traditional RL framework, where the dynamic environment and reward sparsity can cause conventional learning algorithms to fail. Reward shaping is a practical approach to improving sample efficiency by embedding human domain knowledge into the learning process. Existing reward sha

Tim S. Lyon, Eugenio Orlandelli

This paper studies nested sequents for quantified modal logics. In particular, it considers extensions of the propositional modal logics definable by the axioms D, T, B, 4, and 5 with varying, increasing, decreasing, and constant domains. Each calculus is proved to have good structural properties: weakening and contraction are height-preserving admissible an

Marcelo V. Flamarion, Efim Pelinovsky

This study investigates the numerical evolution of an initially internal random wave field characterized by a Gaussian spectrum shape using the Benjamin-Ono (BO) equation. The research focuses on analyzing various properties associated with the BO random wave field, including the transition to a steady state of the spectra, statistical moments, and the distr

Yuming Qin, Xiuqing Wang

In this paper, we consider the 3D Prandtl equation in a periodic domain and prove the local existence and uniqueness of solutions by the energy method in a polynomial weighted Sobolev space. Compared to the existence and uniqueness of solutions to the classical Prandtl equations where the Crocco transform has always been used with the general outer flow $U\n

Yuchen Hu, Chen Chen, Ruizhe Li, Qiushi Zhu

With recent advances of diffusion model, generative speech enhancement (SE) has attracted a surge of research interest due to its great potential for unseen testing noises. However, existing efforts mainly focus on inherent properties of clean speech, underexploiting the varying noise information in real world. In this paper, we propose a noise-aware speech

Domingos Djinja, Sergei Silvestrov, Alex Behakanira Tumwesigye

Representations of polynomial covariance commutation relations by pairs of linear integral and differential operators are constructed in the space of infinitely continuously differentiable functions. Representations of polynomial covariance commutation relations by pairs consisting of a differential and linear integral operator are considered including condi

Sadra Safadoust, Fatma Güney

Recent work in unsupervised multi-object segmentation shows impressive results by predicting motion from a single image despite the inherent ambiguity in predicting motion without the next image. On the other hand, the set of possible motions for an image can be constrained to a low-dimensional space by considering the scene structure and moving objects in i

Derya Malak

We consider the problem of distributed lossless computation of a function of two sources by one common user. To do so, we first build a bipartite graph, where two disjoint parts denote the individual source outcomes. We then project the bipartite graph onto each source to obtain an edge-weighted characteristic graph (EWCG), where edge weights capture the fun

Harvey Mannering

This work presents a novel strategy to measure bias in text-to-image models. Using paired prompts that specify gender and vaguely reference an object (e.g. "a man/woman holding an item") we can examine whether certain objects are associated with a certain gender. In analysing results from Stable Diffusion, we observed that male prompts generated objects such

Chengmin Zhou, Chao Wang, Haseeb Hassan, Himat Shah

Bayesian inference has many advantages in robotic motion planning over four perspectives: The uncertainty quantification of the policy, safety (risk-aware) and optimum guarantees of robot motions, data-efficiency in training of reinforcement learning, and reducing the sim2real gap when the robot is applied to real-world tasks. However, the application of Bay

Nagendra Kumar

High energies emissions observed in X-ray binaries (XRBs), active galactic nuclei (AGNs) are linearly polarized. The prominent mechanism for X-ray is the Comptonization process. We revisit the theory for polarization in Compton scattering with unpolarized electrons, and note that the ($k \times k'$)-coordinate (in which, ($k \times k'$) acts as a $z$-axis, h

Antoine Boivin

A toric variety is a normal complex variety which is completely described by combinatorial data, namely by a fan of strongly convex rational (with respect to a lattice) cones. Due to this rationality condition, toric varieties are (equivariantly) rigid since a deformation of the lattice can make it dense. A solution to this problem consists in considering qu

Fangzhou Cai

In [D. Feng, W. Huang, Variational principle for weighted topological pressure. J. Math. Pures Appl. (2016)], the authors studied weighted topological pressure and established a variational principle for it. In this paper, we introduce the notion of local weighted topological pressure and generalize Feng and Huang's main results to localized version.

Thomas O. Rot, Lauran Toussaint

We classify non-linear proper Fredholm maps between Hilbert spaces, up to proper homotopy, in terms of the stable homotopy groups of spheres. We show that there is a surjective map from the stable homotopy groups of spheres to the set of non-linear proper Fredholm maps up to proper homotopy and determine the non-trivial kernel. We also discuss the case of or

Raj S. Srivastava, A. Aravinda De Chinnu, Aakash C. Rai

Residential heating and cooling currently account for approximately 7% of electricity consumption of India. A warming climate will increase residential cooling requirements, while heating needs will decrease which is an alarming consequence for India, which has predominantly cooling requirements. Thus, to reduce the energy and carbon footprint of Indian buil

Panagiotis Sioulas, Ioannis Mytilinis, Anastasia Ailamaki

Analytical tools often require real-time responses for highly concurrent parameterized workloads. A common solution is to answer queries using materialized subexpressions, hence reducing processing at runtime. However, as queries are still processed individually, concurrent outstanding computations accumulate and increase response times. By contrast, shared

Kotaro Shimizu, Shun Okumura, Yasuyuki Kato, Yukitoshi Motome

The emergent electric field (EEF) is a fictitious electric field acting on conduction electrons through the Berry phase mechanism. The EEF is generated by the dynamics of noncollinear spin configurations and becomes nonzero even in one dimension. Although the EEF has been studied for several one-dimensional chiral magnets, most of the theoretical studies wer

Ruipu Luo, Jiwen Zhang, Zhongyu Wei

Vision language decision making (VLDM) is a challenging multimodal task. The agent have to understand complex human instructions and complete compositional tasks involving environment navigation and object manipulation. However, the long action sequences involved in VLDM make the task difficult to learn. From an environment perspective, we find that task epi

Yujiao Shi, Fei Wu, Akhil Perincherry, Ankit Vora

Image retrieval-based cross-view localization methods often lead to very coarse camera pose estimation, due to the limited sampling density of the database satellite images. In this paper, we propose a method to increase the accuracy of a ground camera's location and orientation by estimating the relative rotation and translation between the ground-level ima

Bin Yan, C. -P. Yuan, Shu-Run Yuan

The determination of the $Zb\bar{b}$ coupling in experiments has been a long-standing challenge, as the limited precision of off $Z$-pole measurements at the LEP has resulted in two degenerate solutions remained to be resolved. In this paper, we propose a novel method to probe the $Zb\bar{b}$ coupling by measuring the forward-backward asymmetry of the bottom

Haobo Song, Soumajit Majumder, Tao Lin

Implicit models such as Deep Equilibrium Models (DEQs) have garnered significant attention in the community for their ability to train infinite layer models with elegant solution-finding procedures and constant memory footprint. However, despite several attempts, these methods are heavily constrained by model inefficiency and optimization instability. Furthe

Yue Song, Jichao Zhang, Nicu Sebe, Wei Wang

Generative Adversarial Networks (GANs), especially the recent style-based generators (StyleGANs), have versatile semantics in the structured latent space. Latent semantics discovery methods emerge to move around the latent code such that only one factor varies during the traversal. Recently, an unsupervised method proposed a promising direction to directly u

Evan Friedman, Duarte Gonçalves

Quantal response equilibrium (QRE), a statistical generalization of Nash equilibrium, is a standard benchmark in the analysis of experimental data. Despite its influence, nonparametric characterizations and tests of QRE are unavailable beyond the case of finite games. We address this gap by completely characterizing the set of QRE in a class of binary-action

Marco Cappiello, Luigi Rodino, Patrik Wahlberg

We show results on propagation of anisotropic Gabor wave front sets for solutions to a class of evolution equations of Schr\"odinger type. The Hamiltonian is assumed to have a real-valued principal symbol with the anisotropic homogeneity $a(\lambda x, \lambda^\sigma \xi) = \lambda^{1+\sigma} a(x,\xi)$ for $\lambda > 0$ where $\sigma > 0$ is a rational anisot

E. S. Vernova, M. I. Tyasto, D. G. Baranov

Variations of the weak magnetic fields of the photosphere with periods of the order of the solar magnetic cycle were investigated. Synoptic maps of the photospheric magnetic field produced by NSO Kitt Peak for the period from 1978 to 2016 were used as initial data. In order to study weak magnetic fields, the saturation threshold for synoptic maps was set at

Peter Bürgisser, Gorav Jindal

The problem $\textrm{PosSLP}$ involves determining whether an integer computed by a given straight-line program is positive. This problem has attracted considerable attention within the field of computational complexity as it provides a complete characterization of the complexity associated with numerical computation. However, non-trivial lower bounds for $\

Adrián Barahona-Ríos, Tom Collins

Controllable neural audio synthesis of sound effects is a challenging task due to the potential scarcity and spectro-temporal variance of the data. Differentiable digital signal processing (DDSP) synthesisers have been successfully employed to model and control musical and harmonic signals using relatively limited data and computational resources. Here we pr

Louis Lagardère, Lise Maurin, Olivier Adjoua, Krystel El Hage

We introduce an efficient and robust method to compute alchemical free energy differences, resulting from the application of multiple walker Adaptive Biasing Force (ABF) in conjunction with strongly damped Langevin $\lambda$-dynamics. Unbiased alchemical free energy surfaces are naturally recovered by Thermodynamic Integration (TI). No manual optimization of

Huiying Song, Yihao Luo, Yuma Fukuzawa

We propose a self-supervised deep learning-based decoding scheme that enables one-shot decoding of polar codes. In the proposed scheme, rather than using the information bit vectors as labels for training the neural network (NN) through supervised learning as the conventional scheme did, the NN is trained to function as a bounded distance decoder by leveragi

Mahbub Ul Alam, Jaakko Hollmén, Jón Rúnar Baldvinsson, Rahim Rahmani

The interpretability of deep neural networks has become a subject of great interest within the medical and healthcare domain. This attention stems from concerns regarding transparency, legal and ethical considerations, and the medical significance of predictions generated by these deep neural networks in clinical decision support systems. To address this mat

D. I. Krotkov, V. P. Spiridonov

We derive finite difference equations of infinite order for theta hypergeometric series and investigate the space of their solutions. In general, such infinite series diverge, we describe some constraints on the parameters when they do converge. In particular, we lift the Hardy-Littlewood criterion on the convergence of $q$-hypergeometric series for $|q|=1,

Wenxiang Dong, H. Vicky Zhao

It is critical to understand and model the behavior of individuals in a pandemic, as well as identify effective ways to guide people's behavior in order to better control the epidemic spread. However, current research fails to account for the impact of users' irrationality in decision-making, which is a prevalent factor in real-life scenarios. Additionally,

Yuanyuan Yang, Claire Birnie, Tariq Alkhalifah

Microseismic event detection and location are two primary components in microseismic monitoring, which offers us invaluable insights into the subsurface during reservoir stimulation and evolution. Conventional approaches for event detection and location often suffer from manual intervention and/or heavy computation, while current machine learning-assisted ap

Yuyang Dong, Yuto Kinoshita, Masayuki Ochi, Ryu Nakachi

Skyrmions in noncentrosymmetric materials are believed to occur due to the Dzyaloshinskii-Moriya interaction. By contrast, the skyrmion formation mechanism in centrosymmetric materials remains elusive. Here, we reveal the intrinsic electronic structure of the centrosymmetric GdRu2Si2 by selectively measuring magnetic domains using angle-resolved photoemissio

Dana Avramescu, Virgil Băran, Vincenzo Greco, Andreas Ipp

We study the impact of the Glasma fields, used to describe the very early stage of heavy-ion collisions, on the transport of hard probes, namely heavy quarks and jets. We perform numerical simulations of the strong classical fields using techniques from real-time lattice gauge theory. The resulting fields are used as background for the classical transport of

Tomáš Chobola, Gesine Müller, Veit Dausmann, Anton Theileis

The process of acquiring microscopic images in life sciences often results in image degradation and corruption, characterised by the presence of noise and blur, which poses significant challenges in accurately analysing and interpreting the obtained data. This paper proposes LUCYD, a novel method for the restoration of volumetric microscopy images that combi

Tejumade Afonja, Dingfan Chen, Mario Fritz

The potential of realistic and useful synthetic data is significant. However, current evaluation methods for synthetic tabular data generation predominantly focus on downstream task usefulness, often neglecting the importance of statistical properties. This oversight becomes particularly prominent in low sample scenarios, accompanied by a swift deterioration

M. Yu. Levichev, I. Yu. Pashenkin, N. S. Gusev, D. Yu. Vodolazov

Normally in superconductors, as in conductors, in the state with zero current $I$ the momentum of superconducting electrons $\hbar q =0$. Here we demonstrate theoretically and present experimental evidences that in superconducting/normal metal (SN) hybrid strip placed in in-plane magnetic field $B_{in}$ finite momentum state ($\hbar q \neq 0$) is realized wh

Hieu Le, Jingyi Xu, Nicolas Talabot, Jiancheng Yang

Accurate 3D models of the human heart require not only correct outer surfaces but also realistic inner structures, such as the ventricles, atria, and myocardial layers. Approaches relying on implicit surfaces, such as signed distance functions (SDFs), are primarily designed for single watertight surfaces, making them ill-suited for multi-layered anatomical s

Baiping Xiong, Zaichen Zhang, Yingmeng Ge, Haibo Wang

In this paper, we consider the channel modeling of a heterogeneous vehicular integrated sensing and communication (ISAC) system, where a dual-functional multi-antenna base station (BS) intends to communicate with a multi-antenna vehicular receiver (MR) and sense the surrounding environments simultaneously. The time-varying complex channel impulse responses (

Jinfeng Zhou, Zhuang Chen, Bo Wang, Minlie Huang

Emotional support conversation (ESC) aims to provide emotional support (ES) to improve one's mental state. Existing works stay at fitting grounded responses and responding strategies (e.g., question), which ignore the effect on ES and lack explicit goals to guide emotional positive transition. To this end, we introduce a new paradigm to formalize multi-turn

Yongle Jia, Sufen Guo, Chunhua Zhu, Lin Li

Symbiotic stars are interacting binary systems, making them valuable for studying various astronomical phenomena, such as stellar evolution, mass transfer, and accretion processes. Despite recent progress in the discovery of symbiotic stars, a significant discrepancy between the observed population of symbiotic stars and the number predicted by theoretical m

Sanju Mandal, Molla Basir Ahamed

In this paper, utilizing Nevanlinna theory, we study existence and forms of the entire solutions $ f $ of the quadratic trinomial-type partial differential-difference equations in $ \mathbb{C}^n $ \begin{align*} a\left(\alpha\dfrac{\partial f(z)}{\partial z_i} + \beta\dfrac{\partial f(z)}{\partial z_j}\right)^2 + 2 \omega \left(\alpha\dfrac{\partial f(z)}{\p

Qizheng You, Jiawen Zhang

In this note, we present examples of non-quasi-geodesic metric spaces which are hyperbolic (i.e., satisfying the Gromov's $4$-point condition) while the intersection of any two metric balls therein does not either "look like" a ball or has uniformly bounded eccentricity. This answers an open question posed in [2].

Ziyuan Chen, Xueliang Wu, Shiming Zhou, Jiakang Zhang

Exotic quantum states arise from the interplay of various degrees of freedom such as charge, spin, orbital, and lattice. Recently, a novel short-ranged charge order (CO) was discovered deep inside the antiferromagnetic phase of Kagome magnet FeGe, exhibiting close relationships with magnetism. Despite extensive investigations, the CO mechanism remains contro

Bhavin Jawade, Deen Dayal Mohan, Dennis Fedorishin, Srirangaraj Setlur

Face recognition from image sets acquired under unregulated and uncontrolled settings, such as at large distances, low resolutions, varying viewpoints, illumination, pose, and atmospheric conditions, is challenging. Face feature aggregation, which involves aggregating a set of N feature representations present in a template into a single global representatio