March 2023 arXiv papers — page 126

Bogomila S. Nikolova, Peter A. Ivanov

We propose a laser-free method for creation of a phonon two-mode squeezed state and a beam-splitter transformation, using time-varying electric fields and non-linear couplings between the normal modes in a linear ion crystal. Such non-linear Coulomb-mediated interactions between the collective vibrational modes arise under specific trap-frequency conditions

Xilong Wang, Yaofei Wang, Kejiang Chen, Jinyang Ding

Nowadays, social media has become the preferred communication platform for web users but brought security threats. Linguistic steganography hides secret data into text and sends it to the intended recipient to realize covert communication. Compared to edit-based linguistic steganography, generation-based approaches largely improve the payload capacity. Howev

Jia-Xing Zhang, Wei Chen

We study the anomalous Hall effect (AHE) in tilted Weyl metals with Gaussian disorder due to the crossed X and {\Psi} diagrams in this work. The importance of such diagrams to the AHE has been demonstrated recently in two dimensional (2D) massive Dirac model and Rashba ferromagnets. It has been shown that the inclusion of such diagrams dramatically changes t

Nikolas Adaloglou, Felix Michels, Tim Kaiser, Markus Kollmann

We present a comprehensive experimental study on pretrained feature extractors for visual out-of-distribution (OOD) detection, focusing on adapting contrastive language-image pretrained (CLIP) models. Without fine-tuning on the training data, we are able to establish a positive correlation ($R^2\geq0.92$) between in-distribution classification and unsupervis

Alain Deville, Yannick Deville

As a consequence of the place ascribed to measurements in the postulates of quantum mechanics, if two differently prepared systems are described with the same density operator \r{ho}, they are said to be in the same quantum state. For more than fifty years, there has been a lack of consensus about this postulate. In a 2011 paper, considering variances of spi

Vishal Kumar, Subhendu Das, Promita Roy, Purba Bhattacharyab

Gas electron multipliers (GEM) detectors are gaseous detectors widely used for tracking and imaging applications due to their good position resolution, high efficiency at high irradiation rates, among other factors. In the present work, position resolution, charge spread, energy resolution and gain uniformity have been investigated experimentally for single

Ling Liang, Defeng Sun, Kim-Chuan Toh

This paper proposes a squared smoothing Newton method via the Huber smoothing function for solving semidefinite programming problems (SDPs). We first study the fundamental properties of the matrix-valued mapping defined upon the Huber function. Using these results and existing ones in the literature, we then conduct rigorous convergence analysis and establis

Phillip Semler, Martin Weiser

In a task where many similar inverse problems must be solved, evaluating costly simulations is impractical. Therefore, replacing the model $y$ with a surrogate model $y_s$ that can be evaluated quickly leads to a significant speedup. The approximation quality of the surrogate model depends strongly on the number, position, and accuracy of the sample points.

Guillaume Dujardin, Ingrid Lacroix-Violet

This paper considers the numerical integration of semilinear evolution PDEs using the high order linearly implicit methods developped in a previous paper in the ODE setting. These methods use a collocation Runge--Kutta method as a basis, and additional variables that are updated explicitly and make the implicit part of the collocation Runge--Kutta method onl

Olli Järviniemi, Joni Teräväinen

We show that almost all sectors of the disc $\{z \in \mathbb{C}: |z|^2\leq X\}$ of area $(\log X)^{15.1}$ contain products of exactly two Gaussian primes, and that almost all sectors of area $(\log X)^{1 + \varepsilon}$ contain products of exactly three Gaussian primes. The argument is based on mean value theorems, large value estimates and pointwise bounds

G. L. Deçordi, A. Vidiella-Barranco

In this work, we investigate the influence of a minimal, phase-sensitive environment on a system of two coupled qubits. The environment is constituted by a single-mode field initially prepared in a type of Schr\"odinger cat state, a quantum superposition of two squeezed coherent states. We present an analytical solution to the model and investigate the degra

Renate Mauland, Øystein Elgarøy, David Fonseca Mota, Hans Arnold Winther

Massive neutrinos and $f(R)$ modified gravity have degenerate observational signatures that can impact the interpretation of results in galaxy survey experiments, such as cosmological parameter estimations and gravity model tests. Because of this, it is important to investigate astrophysical observables that can break these degeneracies. Cosmic voids are sen

Gueffier Jérémy, Gheusi François, Lothon Marie, Pont Véronique

Atmospheric composition measurements taken at many high-altitude stations around the world, aim to collect data representative of the free troposphere and of an intercontinental scale. However, the high-altitude environment favours vertical mixing and the transportation of air masses at local or regional scales, which has a potential influence on the composi

Matthieu Dussaule, Marc Peigné, Samuel Tapie

We construct random walks on free products of the form Z 3 * Z d , with d = 5 or 6 which are divergent and not spectrally positive recurrent. We then derive a local limit theorem for these random walks, proving that $\mu$ * n (e) $\sim$ CR --n n --5/3 if d = 5 and $\mu$ * n (e) $\sim$ CR --n n --3/2 log(n) --1/2 if d = 6, where $\mu$ * n is the nth convoluti

Alexandre Bohyn, Eric D. Schoen, Chee Ping Ng, Kristina Bishard

Experiments using multi-step protocols often involve several restrictions on the randomization. For a specific application to in vitro testing on microplates, a design was required with both a split-plot and a strip-plot structure. On top of two-level treatment factors and the factors that define the randomization restrictions, a multi-level fixed blocking f

Ami S. Koshikawa, Justin Llandro, Masayuki Ohzeki, Shunsuke Fukami

Three-dimensional magnetic metamaterials feature interesting phenomena that arise from a delicate interplay of material properties, local anisotropy, curvature, and connectivity. A particularly interesting magnetic lattice that combines these aspects is that of nanoscale gyroids, with a highly-interconnected chiral network with local three-connectivity remin

Julian Vill

Given a linear map on the vector space of symmetric matrices, every fiber intersected with the set of positive semidefinite matrices is a spectrahedron. Using the notion of the fiber body we can build the average over all such fibers and thereby construct a compact, convex set, the fiber body. We show how to determine the dimensions of faces and normal cones

Nour Kerraoui

In this paper we investigate the spectrum of the Dirac operator posed in a tubular neighborhood of a planar loop with infinite mass boundary conditions. We show that when thewidth of the tubular neighborhood goes to zero the asymptotic expansion of the eigenvalues isdriven by a one dimensional operator of geometric nature involving the curvature of the loop.

Anirban Biswas, Arpan Kar, Bum-Hoon Lee, Hocheol Lee

We use the Weakly Interacting Massive Particle (WIMP) thermal decoupling scenario to probe Cosmologies in dilatonic Einstein Gauss-Bonnet (dEGB) gravity, where the Gauss-Bonnet term is non-minimally coupled to a scalar field with vanishing potential. We put constraints on the model parameters when the ensuing modified cosmological scenario drives the WIMP an

Koby Bibas, Oren Sar Shalom, Dietmar Jannach

Complementary item recommendations are a ubiquitous feature of modern e-commerce sites. Such recommendations are highly effective when they are based on collaborative signals like co-purchase statistics. In certain online marketplaces, however, e.g., on online auction sites, constantly new items are added to the catalog. In such cases, complementary item rec

Alexandre Bohyn, Eric D. Schoen, Peter Goos

Designs for screening experiments usually include factors with two levels only. Adding a few four-level factors allows for the inclusion of multi-level categorical factors or quantitative factors with possible quadratic or third-order effects. Three examples motivated us to generate a large catalog of designs with two-level factors as well as four-level fact

Enderson Falcón-Gomez, Vittorio De Falco, Kerlos Atia Abdalmalak, Adrián Amor-Martín

We study the interaction among gravitational and electromagnetic plane waves by means of an analogue electromagnetic model of gravity, where the gravitational properties are encoded in the electromagnetic properties of a material in flat space-time. In this setup, the variations in the metric tensor produced by the gravitational waves are codified as space-t

Soumya Suvra Ghosal, Yixuan Li

Modern machine learning models may be susceptible to learning spurious correlations that hold on average but not for the atypical group of samples. To address the problem, previous approaches minimize the empirical worst-group risk. Despite the promise, they often assume that each sample belongs to one and only one group, which does not allow expressing the

Emigdio Chavez-Angel, Polychronis Tsipas, Peng Xiao, Mohammad Taghi Ahmadi

Artificially engineered 2D materials offer unique physical properties for thermal management, surpassing naturally occurring materials. Here, using van der Waals epitaxy, we demonstrate the ability to engineer extremely insulating ultra-thin thermal metamaterials based on crystalline lattice-mismatched Bi2Se3/MoSe2 superlattices and graphene/PdSe2 heterostru

Ziteng Cui, Lin Gu, Xiao Sun, Xianzheng Ma

Common capture low-light scenes are challenging for most computer vision techniques, including Neural Radiance Fields (NeRF). Vanilla NeRF is viewer-centred simplifies the rendering process only as light emission from 3D locations in the viewing direction, thus failing to model the low-illumination induced darkness. Inspired by the emission theory of ancient

SuJeong Ji, Maxim Virta, Teemu Kallio, SangHoon Lim

Long-range correlations for pairs of charged particles with two-particle angular correlations are studied in $pp$ at ${\sqrt{{\textit s}}}=13$~TeV with various Monte Carlo generators. The correlation functions are constructed as functions of relative azimuthal angle $\Delta\varphi$ and pseudorapidity separation $\Delta\eta$ for pairs of different particle sp

Jun Hu, Rui Ma, Yuanxun Sun

This paper constructs the first mixed finite element for the linear elasticity problem in 3D using $P_3$ polynomials for the stress and discontinuous $P_2$ polynomials for the displacement on tetrahedral meshes under some mild mesh conditions. The degrees of freedom of the stress space as well as the corresponding nodal basis are established by characterizin

Daniil Provorchenko, Dmitry Tregubov, Denis Mishin, Mikhail Yaushev

Deep laser cooling of atoms, ions, and molecules facilitates the study of fundamental physics as well as applied research. In this work, we report on the narrow-line laser cooling of thulium atoms at the wavelength of $506.2\,\textrm{nm}$ with the natural linewidth of $7.8\,\textrm{kHz}$, which widens the limits of atomic cloud parameters control. Temperatur

Ali Taheri, Vahideh Vahidifar

This article presents new parabolic and elliptic type gradient estimates for positive smooth solutions to a nonlinear parabolic equation involving the Witten Laplacian in the context of smooth metric measure spaces. The metric and potential here are time dependent and evolve under a super Perelman-Ricci flow. The estimates are derived under natural lower bou

Giampaolo Co'

Random Phase Approximation (RPA) is the theory most commonly used to describe the excitations of many-body systems. In this article, the secular equations of the theory are obtained by using three different approaches: the equation of motion method, the Green's function perturbation theory and the time-dependent Hartree--Fock theory. Each approach emphasizes

Yuval Meir, Yarden Tzach, Ronit D. Gross, Ofek Tevet

Learning classification tasks of (2^nx2^n) inputs typically consist of \le n (2x2) max-pooling (MP) operators along the entire feedforward deep architecture. Here we show, using the CIFAR-10 database, that pooling decisions adjacent to the last convolutional layer significantly enhance accuracies. In particular, average accuracies of the advanced-VGG with m

Thierry Lecroq

String matching is the problem of finding all the occurrences of a pattern in a text. We propose improved versions of the fast family of string matching algorithms based on hashing $q$-grams. The improvement consists of considering minimal values $q$ such that each $q$-grams of the pattern has a unique hash value. The new algorithms are fastest than algorith

Clément Bonet, Benoît Malézieux, Alain Rakotomamonjy, Lucas Drumetz

When dealing with electro or magnetoencephalography records, many supervised prediction tasks are solved by working with covariance matrices to summarize the signals. Learning with these matrices requires using Riemanian geometry to account for their structure. In this paper, we propose a new method to deal with distributions of covariance matrices and demon

Marco Inversi

In this paper we consider the transport--Stokes system, which describes the sedimentation of particles in a viscous fluid in inertialess regime. We show existence of Lagrangian solutions to the Cauchy problem with $L^1$ initial data. We prove uniqueness of solutions as a corollary of a stability estimate with respect to the 1-Wasserstein distance for solutio

Bertrand Charpentier, Chenxiang Zhang, Stephan Günnemann

Accurate and efficient uncertainty estimation is crucial to build reliable Machine Learning (ML) models capable to provide calibrated uncertainty estimates, generalize and detect Out-Of-Distribution (OOD) datasets. To this end, Deterministic Uncertainty Methods (DUMs) is a promising model family capable to perform uncertainty estimation in a single forward p

Koji Ando

Potential energy surfaces of electron dynamics (ePES) are constructed from a model of localized electron wave packets (eWP) with non-orthogonal valence-bond (VB) spin coupling and applied to quantum dynamics simulations of high harmonic generation (HHG) spectra of hydrogen and helium atoms induced by intense laser pulses. The dynamics of the single electron

Zhengxiao Li, Yifan Huang, Yang Cao

Healthcare cost prediction is a challenging task due to the high-dimensionality and high correlation among covariates. Additionally, the skewed, heavy-tailed, and often multi-modal nature of cost data can complicate matters further due to unobserved heterogeneity. In this study, we propose a novel framework for finite mixture regression models that incorpora

J Weick, F Dachs, P Riedler, M Vicente Barreto Pinto

The MALTA CMOS monolithic silicon pixel sensors has been developed in the Tower 180 nm CMOS imaging process. It includes an asynchronous readout scheme and complies with the ATLAS inner tracker requirements for the HL-LHC. Several 4-chip MALTA modules have been built using Al wedge wire bonding to demonstrate the direct transfer of data from chip-to-chip and

Matteo Losacco, Alberto Fossà, Roberto Armellin

This paper introduces a novel method for the automatic detection and handling of nonlinearities in a generic transformation. A nonlinearity index that exploits second order Taylor expansions and polynomial bounding techniques is first introduced to rigorously estimate the Jacobian variation of a nonlinear transformation. This index is then embedded into a lo

Hao Liang, Sizhuo Yan, Jianting Yang, Lihong Zhi

Klep and Schweighofer asked whether the Nirgendsnegativsemide-finitheitsstellensatz holds for a symmetric noncommutative polynomial whose evaluations at bounded self-adjoint operators on any nontrivial Hilbert space are not negative semidefinite. We provide an example to show the open problem has a negative answer.

Aminul Huq, Md Tanzim Reza, Shahriar Hossain, Shakib Mahmud Dipto

Class imbalance is a pervasive issue in the field of disease classification from medical images. It is necessary to balance out the class distribution while training a model for decent results. However, in the case of rare medical diseases, images from affected patients are much harder to come by compared to images from non-affected patients, resulting in un

Zhengding Luo, Dongyuan Shi, Xiaoyi Shen, Junwei Ji

Due to the slow convergence and poor tracking ability, conventional LMS-based adaptive algorithms are less capable of handling dynamic noises. Selective fixed-filter active noise control (SFANC) can significantly reduce response time by selecting appropriate pre-trained control filters for different noises. Nonetheless, the limited number of pre-trained cont

I. D. Karachentsev, N. A. Tikhonov

Images of 10 galaxies in F814W and F606W filters obtained on the Hubble Space Telescope (HST) are used to construct color-magnitude diagrams for the star population of these galaxies. The distances to the galaxies are estimated from the luminosity of the tip of the red giant branch. The galaxies examined here have radial velocities from 250 to 760 km/s relat

Peihua Mai, Yan Pang

Conventional recommender systems are required to train the recommendation model using a centralized database. However, due to data privacy concerns, this is often impractical when multi-parties are involved in recommender system training. Federated learning appears as an excellent solution to the data isolation and privacy problem. Recently, Graph neural net

Ho Hin Lee, Quan Liu, Shunxing Bao, Qi Yang

With the inspiration of vision transformers, the concept of depth-wise convolution revisits to provide a large Effective Receptive Field (ERF) using Large Kernel (LK) sizes for medical image segmentation. However, the segmentation performance might be saturated and even degraded as the kernel sizes scaled up (e.g., $21\times 21\times 21$) in a Convolutional

Jonas Oppenlaender, Aku Visuri, Ville Paananen, Rhema Linder

Generative AI is an emerging technology that will have a profound impact on society and individuals. Only a decade ago, it was thought that creative work would be among the last to be automated - yet today, we see AI encroaching on creative domains. In this paper, we present the key findings of a survey study on people's perceptions of text-to-image generati

Xianlin Jin, Shuonan Wu

In this paper, we propose two families of nonconforming finite elements on $n$-rectangle meshes of any dimension to solve the sixth-order elliptic equations. The unisolvent property and the approximation ability of the new finite element spaces are established. A new mechanism, called the exchange of sub-rectangles, for investigating the weak continuities of

Guanxing Fu, Paul P. Hager, Ulrich Horst

We consider a novel class of portfolio liquidation games with market drop-out ("absorption"). More precisely, we consider mean-field and finite player liquidation games where a player drops out of the market when her position hits zero. In particular round-trips are not admissible. This can be viewed as a no statistical arbitrage condition. In a model with o

Peng Zong, Jian-Ning Fu, Jiaxin Wang, Tian-Qi Cang

Homogeneous metallicities and continuous high-precision light curves play key roles in studying the pulsation properties of RR Lyrae stars. By cross-matching with LAMOST DR6, we have determined 7 and 50 Non-Blazhko RRab stars in the Kepler and K2 fields, respectively, who have homogeneous metallicities determined from low-resolution spectra of the LAMOST-Kep

Jorge Alcalde-Unzu, Oihane Gallo, Marc Vorsatz

We analyze the problem of locating a public facility in a domain of single-peaked and single-dipped preferences when the social planner knows the type of preference (single-peaked or single-dipped) of each agent. Our main result characterizes all strategy-proof rules and shows that they can be decomposed into two steps. In the first step, the agents with sin

Conghao Xiong, Yi Lin, Hao Chen, Hao Zheng

Transferring knowledge from a source domain to a target domain can be crucial for whole slide image classification, since the number of samples in a dataset is often limited due to high annotation costs. However, domain shift and task discrepancy between datasets can hinder effective knowledge transfer. In this paper, we propose a Target-Aware Knowledge Tran

Yun-Hao Liu, Tao Liu, Yimeng Huang, Han Ding

Supply chain management is aimed to keep going long-term performance of the supply chain and minimize the costs. Backscatter technology provides a more efficient way of being able to identify items and real-time monitoring. Among the backscatter systems, the ambient backscatter communication (AmBC) system provides a prospect of ultra-low energy consumption a

Weichao Yu

Coupling between spatially separated magnets can be mediated by excitations such as photons and phonons, which can be characterized as coherent coupling and dissipative coupling with real and imaginary coupling rate. We theoretically predict the existence of dynamic exchange coupling in a closed magneto-elastic system mediated by attenuating elastic waves an

Jiacheng Wang, Kathleen E. Larson, Ipek Oguz

Accuracy validation of cortical thickness measurement is a difficult problem due to the lack of ground truth data. To address this need, many methods have been developed to synthetically induce gray matter (GM) atrophy in an MRI via deformable registration, creating a set of images with known changes in cortical thickness. However, these methods often cause

Avijit Das, Andrew K. Brown, Merlin L. Mah, Joseph J. Talghader

This paper presents a theoretical and experimental investigation of photon diffusion in highly absorbing microscale graphite. An Nd:YAG continuous wave (CW) laser is used to heat the graphite samples with thicknesses of 40 microns and 100 microns. Optical intensities of 10 kW/cm^2 and 20 kW/cm^2 are used in laser heating. The graphite samples are heated to t

Jiayang Bai, Letian Huang, Wen Gong, Jie Guo

Recently, Neural Radiance Fields (NeRF) have emerged as a potent method for synthesizing novel views from a dense set of images. Despite its impressive performance, NeRF is plagued by its necessity for numerous calibrated views and its accuracy diminishes significantly in a few-shot setting. To address this challenge, we propose Self-NeRF, a self-evolved NeR

Brian Szekely, Christian Sinnott, Savannah Halow, Gregory Ryan

The National Football League (NFL) Scouting Combine serves as a tool to evaluate the skills of prospective players and assess their readiness to play in the NFL. The development of machine learning brings new opportunities in assessing the utility of the Scouting Combine. Using machine and statistical learning, it may be possible to predict future success of

Hélène Esnault

Those notes rest on the Samuel Eilenberg Lectures I gave at Columbia University, NY, in the fall 2022. I thank all the mathematicians who participated in their elaboration, directly or indirectly. They are meant to be published as a Springer Lecture Notes. This arXiv version is not identical with the final version.

Xiang Li, Guoqi Li, Leitao Gao, Beibei Li

In this paper, we propose to study on sufficient control of complex networks which is to control a sufficiently large portion of the network, where only the quantity of controllable nodes matters. To the best of our knowledge, this is the first time that such a problem is investigated. We prove that the sufficient controllability problem can be converted int

Jie Zhu, Lingwei Li, Li Yang, Xiaoxiao Ma

Method names are crucial to program comprehension and maintenance. Recently, many approaches have been proposed to automatically recommend method names and detect inconsistent names. Despite promising, their results are still sub-optimal considering the three following drawbacks: 1) These models are mostly trained from scratch, learning two different objecti

Kazuki Hiroe, Haru Negami

The Long-Moody construction is a method to obtain representations of braid groups introduced by Long and Moody. Also the Katz middle convolution is known to be a method to construct local systems on $\mathbb{C}\backslash\{n\text{-points}\}$ introduced by Katz. In this paper, we explain that these two methods are naturally unified and define a new functor whi

Keisuke Fujioka, Ryota Kogawa, Jizhou Li, Akira Shudo

We derive a sufficient condition for topological horseshoe and uniform hyperbolicity of a 4-dimensional symplectic map, which is introduced by coupling the two 2-dimensional H\'enon maps via linear terms. The coupled H\'enon map thus constructed can be viewed as a simple map modeling the horseshoe in higher dimensions. We show that there are two different ty

Haiming Yao, Wenyong Yu, Wei Luo, Zhenfeng Qiang

This paper presents a novel framework, named Global-Local Correspondence Framework (GLCF), for visual anomaly detection with logical constraints. Visual anomaly detection has become an active research area in various real-world applications, such as industrial anomaly detection and medical disease diagnosis. However, most existing methods focus on identifyin

Sayan Goswami, Wen Huang, XiaoSheng Wu

An positive even number is said to be a Kronecker number if it can be written in infinitely many ways as the difference between two primes, and it is believed that all even numbers are Kronecker numbers. We will study the division and multiplication of Kronecker numbers to study the largeness of the set of Kronecker numbers. A numerical lower bound for the d

Aminul Huq, Mst Tasnim Pervin

Deep learning based models are used regularly in every applications nowadays. Generally we train a single model on a single task. However, we can train multiple tasks on a single model under multi-task learning settings. This provides us many benefits like lesser training time, training a single model for multiple tasks, reducing overfitting, improving perfo

Li Cai, Yangyu Fan

In this short note, we compute higher extension groups for all irreducible representations and deduce the multiplicity formula for finite length representations in triple product case.

Z. Araghi Rostami, M. Parvizi, P. Niroomand

U. Jezernik and P. Moravec have shown that if $G$ is a finite group with a subgroup $H$ of index $n$, then nth power of the Bogomolov multiplier of $G$, $\tilde{B_0}(G)^n$ is isomorphic to a subgroup of $\tilde{B_0}(H)$. In this paper we want to prove a similar result for the center by center by $w$ variety of groups, where $w$ is any outer commutator word.

Taeyeong Choi, Dario Guevara, Zifei Cheng, Grisha Bandodkar

In agricultural environments, viewpoint planning can be a critical functionality for a robot with visual sensors to obtain informative observations of objects of interest (e.g., fruits) from complex structures of plant with random occlusions. Although recent studies on active vision have shown some potential for agricultural tasks, each model has been design

Edward Whittaker, Masashi Tanaka, Ikuo Kitagishi

We describe the development of a real-time smartphone app that allows the user to digitize paper receipts in a novel way by "waving" their phone over the receipts and letting the app automatically detect and rectify the receipts for subsequent text recognition. We show that traditional computer vision algorithms for edge and corner detection do not robustly

Weixin Chen, Dawn Song, Bo Li

Diffusion models have achieved great success in a range of tasks, such as image synthesis and molecule design. As such successes hinge on large-scale training data collected from diverse sources, the trustworthiness of these collected data is hard to control or audit. In this work, we aim to explore the vulnerabilities of diffusion models under potential tra

Wolfgang Fuhl, Susanne Zabel, Kay Nieselt

Modern high throughput sequencing technologies like metagenomic sequencing generate millions of sequences which have to be classified based on their taxonomic rank. Modern approaches either apply local alignment and comparison to existing data sets like MMseqs2 or use deep neural networks as it is done in DeepMicrobes and BERTax. Alignment-based approaches a

Igor A. Dmitriev, Evgeny A. Kochurin, Nikolay M. Zubarev

Direct numerical simulation of threedimensional chaotic motion of a dielectric liquid with a free surface under the action of external horizontal electric field is carried out. The numerical model takes into account the effects of surface tension, viscosity, and external isotropic random forcing acting at large scales. A transition from dispersive capillary

Zhiyu Huang, Haochen Liu, Chen Lv

Autonomous vehicles operating in complex real-world environments require accurate predictions of interactive behaviors between traffic participants. This paper tackles the interaction prediction problem by formulating it with hierarchical game theory and proposing the GameFormer model for its implementation. The model incorporates a Transformer encoder, whic

Chengwei Wei, Yun-Cheng Wang, Bin Wang, C. -C. Jay Kuo

Language modeling studies the probability distributions over strings of texts. It is one of the most fundamental tasks in natural language processing (NLP). It has been widely used in text generation, speech recognition, machine translation, etc. Conventional language models (CLMs) aim to predict the probability of linguistic sequences in a causal manner, wh

Aminul Huq, Weiyi Zhang, Xiaolin Hu

Automatic speech recognition (ASR) systems based on deep neural networks are weak against adversarial perturbations. We propose mixPGD adversarial training method to improve the robustness of the model for ASR systems. In standard adversarial training, adversarial samples are generated by leveraging supervised or unsupervised methods. We merge the capabiliti

Mustapha Kaci, Sonia Radjef

In this paper, we present a new geometric approach for sensitivity analysis in linear programming that is computationally practical for a decision-maker to study the behavior of the optimal solution of the linear programming problem under changes in program data. First, we fix the feasible domain (fix the linear constraints). Then, we geometrically formulate

Elif Güngör, Hayriye Sundu, Jale Y. Süngü, Elşen V. Veliev

The BESIII collaboration has discovered a new state with hidden charm-strange. Its mass is intriguingly close to the $ D_s\bar{D}_{s1} $ threshold and does not have the properties of the charmonium states. Working with the QCD sum rules (QCDSR) approach, we test if the charmonium-like structure $ Y (4500) $, detected in the invariant mass spectrum $ K^+ K^-J

Woocheol Choi

In this paper, we consider the decentralized gradinet descent (DGD) given by \begin{equation*} x_i (t+1) = \sum_{j=1}^m w_{ij} x_j (t) - \alpha (t) \nabla f_i (x_i (t)). \end{equation*} We find a sharp range of the stepsize $\alpha (t)>0$ such that the sequence $\{x_i (t)\}$ is uniformly bounded when the aggregate cost $f$ is assumed be strongly convex with

Hyungjin Chung, Suhyeon Lee, Jong Chul Ye

Krylov subspace, which is generated by multiplying a given vector by the matrix of a linear transformation and its successive powers, has been extensively studied in classical optimization literature to design algorithms that converge quickly for large linear inverse problems. For example, the conjugate gradient method (CG), one of the most popular Krylov su

Jeremy L. Smallwood, Chao-Chin Yang, Zhaohuan Zhu, Rebecca G. Martin

Spiral arms are observed in numerous protoplanetary discs. These spiral arms can be excited by companions, either on bound or unbound orbits. We simulate a scenario where an unbound perturber, i.e. a flyby, excites spiral arms during a periastron passage. We run three-dimensional hydrodynamical simulations of a parabolic flyby encountering a gaseous protopla

Christopher Andreassen, Saul Fuster, Helga Hardardottir, Emiel A. M. Janssen

Northern Europe has the second highest mortality rate of melanoma globally. In 2020, the mortality rate of melanoma rose to 1.9 per 100 000 habitants. Melanoma prognosis is based on a pathologist's subjective visual analysis of the patient's tumor. This methodology is heavily time-consuming, and the prognosis variability among experts is notable, drastically

Milan Haiman, Yuan Yao

We study generalized permutohedra and supermodular functions. Specifically we analyze decomposability and irreducibility for these objects and establish some asymptotic behavior. We also study a related problem on irreducibility for multisets.

V. Nam Do

We briefly review the advanced mathematical language of fiber bundle structures and how they can be used to classify two-level quantum systems based on the analysis of the topological properties of their sets of state vectors. The topological classes of quantum electronic states and matter phases are characterized by topological invariants, which can be defi

Huimin Zhang, Qiang Zou, Lian Li

A two dimensional topological insulator exhibits helical edge states topologically protected against single particle backscattering. Such protection breaks down, however, when electron electron interactions are significant or when edge reconstruction occurs, leading to suppressed density of states (DOS) at Fermi level that follows universal scaling with temp

Manh-Huong Phan

The recent discovery of two-dimensional (2D) van der Waals (vdW) magnetic materials has provided new, unprecedented opportunities for both fundamental science and technological applications. Unlike three-dimensional (3D) magnetic systems, the electric manipulation of vdW magnetism (e.g., magnetization state, magnetic anisotropy, magnetic ordering temperature

Mostafa Sharifzadeh, Habib Benali, Hassan Rivaz

Phase aberration is one of the primary sources of image quality degradation in ultrasound, which is induced by spatial variations in sound speed across the heterogeneous medium. This effect disrupts transmitted waves and prevents coherent summation of echo signals, resulting in suboptimal image quality. In real experiments, obtaining non-aberrated ground tru

Tongkeun Chang, Kyungkeun Kang

We prove that there exists a weak solution of the Stokes system with a non-zero external force and no-slip boundary conditions in a half space of dimensions three and higher so that its normal derivatives are unbounded near boundary. A localized and divergence free singular force causes, via non-local effect, singular behaviors of normal derivatives for the

Minghui Zhang, Yangqian Wu, Hanxiao Zhang, Yulei Qin

Open international challenges are becoming the de facto standard for assessing computer vision and image analysis algorithms. In recent years, new methods have extended the reach of pulmonary airway segmentation that is closer to the limit of image resolution. Since EXACT'09 pulmonary airway segmentation, limited effort has been directed to quantitative comp

Kedeng Tong, Yaojun Wu, Yue Li, Kai Zhang

Learned image compression has exhibited promising compression performance, but variable bitrates over a wide range remain a challenge. State-of-the-art variable rate methods compromise the loss of model performance and require numerous additional parameters. In this paper, we present a Quantization-error-aware Variable Rate Framework (QVRF) that utilizes a u

Ataru Tanikawa, Savannah Cary, Minori Shikauchi, Long Wang

Gaia BHs, black hole (BH) binaries discovered from database of an astrometric telescope Gaia, pose a question to the standard binary evolution model. We have assessed if Gaia BHs can be formed through dynamical capture in open clusters rather than through isolated binary evolution. We have performed gravitational $N$-body simulations of $100$ open clusters w

Kerem Akdogan, Lucas Heger, Andrew Iskauskas, Friedemann Neuhaus

The June software package is an open-source framework for the detailed simulation of epidemics based on social interactions in a virtual population reflecting age, gender, ethnicity, and socio-economic indicators in England. In this paper, we present a new version of the framework specifically adapted for Germany, which allows the simulation of the entire Ge

Ze-Cheng Zou, Yong-Feng Huang, Cheng-Ming Li, He-Rui Zheng

The accumulation of gluons inside nucleons, i.e., the gluon condensation, may lead to a characteristic broken power-law gamma-ray spectrum in high-energy nucleon collisions. Here we show that the observed spectra of at least 25 sources in the second Fermi Large Area Telescope Catalog of Gamma-ray Pulsars can be well fitted by such a broken power-law function

Bing Liu, Furan Xie, Li Chai

With the rapid development of distributed energy resources, increasing number of residential and commercial users have been switched from pure electricity consumers to prosumers that can both consume and produce energy. To properly manage these emerging prosumers, a peer-to-peer electricity market has been explored and extensively studied. In such an electri

Phi Vu Tran

Few-shot object detection (FSOD) is a challenging problem aimed at detecting novel concepts from few exemplars. Existing approaches to FSOD all assume abundant base labels to adapt to novel objects. This paper studies the new task of semi-supervised FSOD by considering a realistic scenario in which both base and novel labels are simultaneously scarce. We exp

Yuxi Han, Jiwoong Jang

We study the rate of convergence in periodic homogenization for convex Hamilton--Jacobi equations with multiscales, where the Hamiltonian $H=H(x, y, p): \mathbb{R}^n \times \mathbb{T}^n \times \mathbb{R}^n \to \mathbb{R }$ depends on both of the spatial variable and the oscillatory variable. In particular, we show that for the Cauchy problem, the rate of con

Joel Shor, Ruyue Agnes Bi, Subhashini Venugopalan, Steven Ibara

Automatic Speech Recognition (ASR) in medical contexts has the potential to save time, cut costs, increase report accuracy, and reduce physician burnout. However, the healthcare industry has been slower to adopt this technology, in part due to the importance of avoiding medically-relevant transcription mistakes. In this work, we present the Clinical BERTScor

Huizhi Wang, Zhiqiang Xiao, Yong Zeng

Mobile communication networks were designed to mainly support ubiquitous wireless communications, yet they are also expected to achieve radio sensing capabilities in the near future. However, most prior studies on radio sensing usually rely on far-field assumption with uniform plane wave (UPW) models. With the ever-increasing antenna size, together with the

Muhammad Husnain Mubarik, Ramakrishna Kanungo, Tobias Zirr, Rakesh Kumar

Rendering and inverse-rendering algorithms that drive conventional computer graphics have recently been superseded by neural representations (NR). NRs have recently been used to learn the geometric and the material properties of the scenes and use the information to synthesize photorealistic imagery, thereby promising a replacement for traditional rendering

Zhongying Deng, Da Li, Junjun He, Yi-Zhe Song

Target domain pseudo-labelling has shown effectiveness in unsupervised domain adaptation (UDA). However, pseudo-labels of unlabeled target domain data are inevitably noisy due to the distribution shift between source and target domains. This paper proposes a Generative model-based Noise-Robust Training method (GeNRT), which eliminates domain shift while miti

Honghao Wei, Arnob Ghosh, Ness Shroff, Lei Ying

We study model-free reinforcement learning (RL) algorithms in episodic non-stationary constrained Markov Decision Processes (CMDPs), in which an agent aims to maximize the expected cumulative reward subject to a cumulative constraint on the expected utility (cost). In the non-stationary environment, reward, utility functions, and transition kernels can vary