October 2025 arXiv papers — page 16

Jingran Zhang, Ning Li, Justin Cui

OpenAI's ChatGPT Atlas introduces new capabilities for web interaction, enabling the model to analyze webpages, process user intents, and execute cursor and keyboard inputs directly within the browser. While its capacity for information retrieval tasks has been demonstrated, its performance in dynamic, interactive environments remains less explored. In this

Angelos Alexopoulos, Agorakis Bompotas, Nikitas Rigas Kalogeropoulos, Panagiotis Kechagias

Modern manufacturing demands high flexibility and reconfigurability to adapt to dynamic production needs. Model-based Engineering (MBE) supports rapid production line design, but final reconfiguration requires simulations and validation. Digital Twins (DTs) streamline this process by enabling real-time monitoring, simulation, and reconfiguration. This paper

Luting Wang, Yinghao Xiang, Hongliang Huang, Dongjun Li

Agile Earth Observation Satellites (AEOSs) constellations offer unprecedented flexibility for monitoring the Earth's surface, but their scheduling remains challenging under large-scale scenarios, dynamic environments, and stringent constraints. Existing methods often simplify these complexities, limiting their real-world performance. We address this gap with

Yi Ran, Zhichang Guo, Kehan Shi, Qirui Zhou

Nonlocal equations effectively preserve textures but exhibit weak regularization effects in image denoising, whereas local equations offer strong denoising capabilities yet fail to protect textures. To integrate the advantages of both approaches, this paper investigates a coupled local-nonlocal total variation flow for image despeckling. We establish the exi

Ya-Xin Xiang, Weibin Li, Zhengyang Bai, Yu-Qiang Ma

The predator-prey cycle is a paradigmatic example of self-organized population oscillations in far-from-equilibrium systems, yet testing its underlying mechanism in natural ecosystems is often precluded by uncontrollable microscopic parameters. Here, we propose a quantum analogue of predator-prey dynamics using a tunable two-dimensional Rydberg atom array. T

Fernando Alonso-Fernandez, Kevin Hernandez-Diaz, Jose Maria Buades Rubio, Josef Bigun

We focus on ocular biometrics, specifically the periocular region (the area around the eye), which offers high discrimination and minimal acquisition constraints. We evaluate three Convolutional Neural Network architectures of varying depth and complexity to assess their effectiveness for periocular recognition. The networks are trained on 1,907,572 ocular c

Arefeh Kazemi, Hamza Qadeer, Joachim Wagner, Hossein Hosseini

We introduce SynBullying, a synthetic multi-LLM conversational dataset for studying and detecting cyberbullying (CB). SynBullying provides a scalable and ethically safe alternative to human data collection by leveraging large language models (LLMs) to simulate realistic bullying interactions. The dataset offers (i) conversational structure, capturing multi-t

J. J. Gálvez-Viruet, M. Gómez-Rocha, F. J. Llanes-Estrada

Quantum computers are coming online and will quickly impact hadron physics once certain fidelity, decoherence and memory thresholds are met, quite possibly within a decade. We review a selected number of topics where ab-initio QCD-level information about hadrons can be obtained with this computational tool that is hard to come by from other methods. This inc

Lin Liu, Guanyi Yu, Ziying Song, Junqiao Li

Planning is a critical component of end-to-end autonomous driving. However, prevailing imitation learning methods often suffer from mode collapse, failing to produce diverse trajectory hypotheses. Meanwhile, existing generative approaches struggle to incorporate crucial safety and physical constraints directly into the generative process, necessitating an ad

Angelos Alexopoulos, Agorakis Bompotas, Nikitas Rigas Kalogeropoulos, Panagiotis Kechagias

Robotic systems have become integral to smart environments, enabling applications ranging from urban surveillance and automated agriculture to industrial automation. However, their effective operation in dynamic settings - such as smart cities and precision farming - is challenged by continuously evolving topographies and environmental conditions. Traditiona

Marc Chamberland, Karl Dilcher

We show that the alternating sum of the floor function of $\sqrt{jn}$, with $j$ ranging from 1 to $n$, has an easy evaluation for all odd integers $n\geq 1$. This is in contrast to known non-alternating sums of the same type which hold only for a class of primes. The proof is elementary and was suggested by an AI model. To put this result in perspective, we

Rui Zhang, Yue-Yang Fei, Zhenhuan Liu, Xingjian Zhang

In quantum networks, after passing through noisy channels or information processing, residual states may lack sufficient entanglement for further tasks, yet they may retain hidden quantum resources that can be recycled. Efficiently recycling these states to extract entanglement resources such as genuine multipartite entanglement or Einstein-Podolsky-Rosen pa

Zijing Xu, Yunfeng Kou, Kunming Wu, Hong Liu

Multimodal learning faces two major challenges: modality imbalance and data noise, which significantly affect the robustness and generalization ability of models. Existing methods achieve modality balance by suppressing dominant modalities, but they neglect the inherent differences in the information value between modalities, potentially leading to convergen

Hua Chai, Zhenyu Cheng, Qinxin Hu, Zhongbing Huang

We investigate the nonequilibrium dynamics of charge density waves in a pumped one-dimensional Hubbard superlattice with staggered onsite Coulomb interactions at half-filling, using time-dependent exact diagonalization. In equilibrium, the system exhibits commensurate charge correlations consistent with the superlattice periodicity. Under laser excitation, t

Guochang Li, Yuchen Liu, Zhen Qin, Yunkun Wang

Repository-level software engineering tasks require large language models (LLMs) to efficiently navigate and extract information from complex codebases through multi-turn tool interactions. Existing approaches face significant limitations: training-free, in-context learning methods struggle to guide agents effectively in tool utilization and decision-making

Rakesh Arora, Jacques Giacomoni, Hichem Hajaiej, Arshi Vaishnavi

In this paper, we derive a new $p$-Logarithmic Sobolev inequality and optimal continuous and compact embeddings into Orlicz-type spaces of the function space associated with the logarithmic $p$-Laplacian. As an application of these results, we study a class of Dirichlet boundary value problems involving the logarithmic $p$-Laplacian and critical growth nonli

Michal Štefánik, Timothee Mickus, Marek Kadlčík, Bertram Højer

Prior work has shown that large language models (LLMs) often converge to accurate input embedding for numbers, based on sinusoidal representations. In this work, we quantify that these representations are in fact strikingly systematic, to the point of being almost perfectly universal: different LLM families develop equivalent sinusoidal structures, and numbe

Xia Jiang, Rong J. B. Zhu

Multi-task learning in contextual bandits has attracted significant research interest due to its potential to enhance decision-making across multiple related tasks by leveraging shared structures and task-specific heterogeneity. In this article, we propose a novel hierarchical Bayesian framework for learning in various bandit instances. This framework captur

Dongyu Li, Ziqun Zhang, Hongyi Wang, Yukang Jia

We present a dual-domain microwave photonic radar system for multi-parameter vital sign monitoring, utilizing ultra-wideband radiofrequency signals to achieve high-precision chest displacement measurements, while high-frequency optical signals enable accurate Doppler detection of pulse-induced micro-motions. We experimentally validated the system by simultan

Fernando Alonso-Fernandez, Kevin Hernandez Diaz, Jose M. Buades, Kiran Raja

We study the complementarity of different CNNs for periocular verification at different distances on the UBIPr database. We train three architectures of increasing complexity (SqueezeNet, MobileNetv2, and ResNet50) on a large set of eye crops from VGGFace2. We analyse performance with cosine and chi2 metrics, compare different network initialisations, and ap

James Brister, Bingwei Long, Longjie Ran, Muhammad Shahzad

In addition to the well-known quantum chromodynamical theta angle, we show that the Standard Model has another theta angle which is invariant under arbitrary chiral rotations of quarks and leptons. The new theta angle can be identified with the quantum electrodynamical theta angle, which should be viewed as an independent parameter of the Standard Model, and

Fuying Li, Yajun Wang, Zhuxian Lian, Wen Chen

Driven by the growing demand for higher spectral efficiency in wireless communications, intelligent reflecting surfaces (IRS) have attracted considerable attention for their ability to dynamically reconfigure the propagation environment. This work addresses the spectral efficiency maximization problem in IRS-assisted multiple-input multiple-output (MIMO) sys

Kim Yong Tan, Yueming Lyu, Ivor Tsang, Yew-Soon Ong

Diffusion models have been successful in learning complex data distributions. This capability has driven their application to high-dimensional multi-objective black-box optimization problem. Existing approaches often employ an external optimization loop, such as an evolutionary algorithm, to the diffusion model. However, these approaches treat the diffusion

Kang Chen, Yaoning Wang, Kai Xiong, Zhuoka Feng

Large language models (LLMs) commonly boost reasoning via sample-evaluate-ensemble decoders, achieving label free gains without ground truth. However, prevailing strategies score candidates using only external outputs such as token probabilities, entropies, or self evaluations, and these signals can be poorly calibrated after post training. We instead analyz

Domenico Amalfitano, Andreas Metzger, Marco Autili, Tommaso Fulcini

Generative AI (GenAI) is rapidly transforming software engineering (SE) practices, influencing how SE processes are executed, as well as how software systems are developed, operated, and evolved. This paper applies design science research to build a roadmap for GenAI-augmented SE. The process consists of three cycles that incrementally integrate multiple sou

Haohua Duan, Liyao Xiang, Xin Zhang

Watermarking schemes for large language models (LLMs) have been proposed to identify the source of the generated text, mitigating the potential threats emerged from model theft. However, current watermarking solutions hardly resolve the trust issue: the non-public watermark detection cannot prove itself faithfully conducting the detection. We observe that it

Nathan Torelli, Jonas Willmann, Katja Daehler, Madalyne Day

Background and Purpose: Reirradiation for non-small cell lung cancer (NSCLC) is commonly delivered using coplanar techniques. In this study, we developed a beam orientation optimization algorithm for reirradiation planning to investigate whether the selection of favorable non-coplanar beam orientations may limit cumulative doses to critical organs-at-risk (O

Sukrit Sriratanawilai, Jhayahgrit Thongwat, Romrawin Chumpu, Patomporn Payoungkhamdee

Vision-language models (VLMs) exhibit uneven performance across languages, a problem that is often exacerbated when the model size is reduced. While Knowledge distillation (KD) demonstrates promising results in transferring knowledge from larger to smaller VLMs, applying KD in multilingualism is an underexplored area. This paper presents a controlled empiric

Peter Scholze

These are lecture notes for a course in Winter 2022/23, updated and completed in October 2025. The goal of the lectures is to present some recent developments around six-functor formalisms, in particular: the abstract theory of 6-functor formalisms; the 2-category of cohomological correspondences, and resulting simplifications in the proofs of Poincar\'e--Ve

Lin Guo, Xiaoqing Luo, Wei Xie, Zhancheng Zhang

Existing infrared and visible image fusion methods often face the dilemma of balancing modal information. Generative fusion methods reconstruct fused images by learning from data distributions, but their generative capabilities remain limited. Moreover, the lack of interpretability in modal information selection further affects the reliability and consistenc

Zhiyuan Ning, Jiawei Shao, Ruge Xu, Xinfei Guo

Speculative decoding has become a widely adopted as an effective technique for lossless inference acceleration when deploying large language models (LLMs). While on-the-fly self-speculative methods offer seamless integration and broad utility, they often fall short of the speed gains achieved by methods relying on specialized training. Cascading a hierarchy

Amartya Sengupta, Dejan Stojkovic, L. C. R. Wijewardhana

Only two gauge symmetries remain unbroken today: $SU(3)_c$ and $U(1)_{\rm EM}$. Both are crucial to our universe as it is and to our form of life. Unless we are special observers at the end of the cosmological symmetry-breaking chain, there is no reason they must remain unbroken forever. We investigate the cosmological signatures of late-time $SU(3)_c$ break

Frederik Möbius Rygaard, Shen Zhu, Yinzhu Jin, Søren Hauberg

The geometry of generative models serves as the basis for interpolation, model inspection, and more. Unfortunately, most generative models lack a principal notion of geometry without restrictive assumptions on either the model or the data dimension. In this paper, we construct a general geometry compatible with different metrics and probability distributions

Aleks Žigon Tankosič

In this paper we introduce and study two generalizations of Lah numbers, analogous to the Stirling numbers with higher level - a combinatorial one (Lah numbers with higher level) and an algebraic one (Lah numbers of order $s$). We define the Lah numbers with higher level following a combinatorial approach and the Lah numbers of order $s$ following an algebra

Ling-Long Zou, Qiang Tong, Er-Xia Luo, Sen-Zhe Xu

Redirected walking utilizes gain adjustments within perceptual thresholds to allow natural navigation in large scale virtual environments within confined physical environments. Previous research has found that when users are distracted by some scene elements, they are less sensitive to gain values. However, the effects on detection thresholds have not been q

Tomasz Kociumaka, Jakub Radoszewski

A central task in string processing is text indexing, where the goal is to preprocess a text (a string of length $n$) into an efficient index (a data structure) supporting queries about the text. Cole, Gottlieb, and Lewenstein (STOC 2004) proposed $k$-errata trees, a family of text indexes supporting approximate pattern matching queries of several types. In

Duaa Abdullah, Jasem Hamoud

In this paper we provide a good overview of the problems and the background of mathematics education in Syrian schools. We aimed to study the effect of using popular mathematical puzzles on the mathematical thinking of schoolchildren, by conducting a paired experimental study (pre-test and post-test control group design) of the data we obtained through a sam

Francesco Verde, Donatella Darsena, Marco Di Renzo, Vincenzo Galdi

This paper deals with the optimal synthesis of aperture fields for (radiating) near-field communications in obstructed environments. A physically consistent model based on knife-edge diffraction is used to formulate the problem as a maximization in Hilbert space. The optimal solution is obtained as a matched filter that ``matches" the shape of a diffraction-

Enrico Le Donne, Sebastiano Nicolussi Golo, Nicola Paddeu

We consider Lie groups equipped with left-invariant subbundles of their tangent bundles and norms on them. On these sub-Finsler structures, we study the normal curves in the sense of control theory. We revisit the Pontryagin Maximum Principle using tools from convex analysis, expressing the normal equation as a differential inclusion involving the subdiffere

D. Gigli, P. Gorai, C. Y. Law, J. C. Tan

During massive star formation, dense gas undergoes chemical evolution, producing both simple and complex organic molecules (COMs) characteristic of hot molecular cores. How this evolution depends on protostellar physical properties remains unclear. We investigate the chemical content of 22 well-studied massive protostars from the SOFIA Massive (SOMA) Star Fo

V. Kozhuharov

The PADME experiment was originally designed to test dark matter theories predicting the existence of a ''Dark Sector'' composed of particles that interact with Standard Model ones exclusively through the exchange of a new, massive mediator. The confirmation of the X17 anomaly, observed in nuclear decays at the ATOMKI in Debrecen, sparked considerable intere

Hanzhi Chen, Chuyue Zheng, Yong Xia

The classical Dinkelbach method (1967) solves fractional programming via a parametric approach, generating a decreasing upper bound sequence that converges to the optimum. Its important variant, the interval Dinkelbach method (1991), constructs convergent upper and lower bound sequences that bracket the solution and achieve quadratic and superlinear converge

Geng Sun, Siyi Chen, Zemin Sun, Long He

Vehicular fog computing (VFC) has emerged as a promising paradigm, which leverages the idle computational resources of nearby fog vehicles (FVs) to complement the computing capabilities of conventional vehicular edge computing. However, utilizing VFC to meet the delay-sensitive and computation-intensive requirements of the FVs poses several challenges. First

Satyaki Manna

The usefulness of entanglement in quantum channel discrimination is a central topic in quantum information theory. A landmark result in this direction was established by Piani and Watrous [$Phys. Rev. Lett.102, 250501 (2009)$] who proved that all entangled states are useful for discrimination of quantum channels. We pose the same question in the context of a

Mérilin Sousa Silva, Sina Ahmadi

Throughout language history, words are borrowed from one language to another and gradually become integrated into the recipient's lexicon. Speakers can often differentiate these loanwords from native vocabulary, particularly in bilingual communities where a dominant language continuously imposes lexical items on a minority language. This paper investigates w

Navid Ashrafi, Philipp Graf, Manuela Marquardt, Francesco Vona

The appearance of a virtual avatar significantly influences its perceived appropriateness and the user's experience, particularly in healthcare applications. This study analyzed interactions with six avatars of varying characteristics in a patient-reported outcome measures (PROMs) application to investigate correlations between avatar ratings and user prefer

Zhongyang Liu, C. Simon Jeffery, Xianfei Zhang, Shaolan Bi

We present theoretical predictions of the born-again scenario for post-asymptotic giant-branch stars. An extensive model grid for born-again objects has been constructed, particularly including models for the Very Late Thermal Pulse with and without convective overshooting, and also including models for the Late Thermal Pulse. We constructed a large paramete

Rémi Jaoui, Jonathan Kirby

We develop techniques at the interface between differential algebra and model theory to study the following problems of exponential algebraicity: Does a given algebraic differential equation admits an exponentially algebraic solution, that is, a holomorphic solution which is definable in the structure of restricted elementary functions? Do solutions of a giv

Jackson R. Fliss, Andrew Rolph

We derive new families of quantum null energy inequalities (QNEIs), i.e. bounds on integrated null energy, in quantum field theories in two and higher dimensions. These are universal, state-independent lower bounds on semi-local integrals of $\langle T_{vv} \rangle$, the energy-momentum flux in a null direction, and the first of this kind for interacting the

Alcides Gomes Andrade Júnior, Akira Matsubayashi

The Maximum Matching problem has a quantum query complexity lower bound of $\Omega(n^{3/2})$ for graphs on $n$ vertices represented by an adjacency matrix. The current best quantum algorithm has the query complexity $O(n^{7/4})$, which is an improvement over the trivial bound $O(n^2)$. Constructing a quantum algorithm for this problem with a query complexity

Juyeop Kim, Hyejin Shin, Sohee Kim, Ilmu Byun

This study analyzes the performance of positioning techniques based on configuration changes of 5G New Radio signals. In 5G networks, a terminal position is determined from the Time of Arrival of Positioning Reference Signals transmitted by base stations. We propose an algorithm that improves TOA accuracy under low sampling rate constraints and implement 5G

Minho Kim, Dat Q. Tran, Plamen P. Paskov, U. Choi

We investigate the influence of AlN buffer thickness on the structural, electrical, and thermal properties of AlGaN/GaN high-electron mobility transistors (HEMTs) grown on semi-insulating SiC substrates by metal-organic chemical vapor deposition. X-ray diffraction and atomic force microscopy reveal that while thin AlN layers (120 nm) exhibit compressive stra

Hieu M. Vu, Tan M. Nguyen

Controlling specific behaviors in large language models while preserving their general capabilities is a central challenge for safe and reliable artificial intelligence deployment. Current steering methods, such as vector addition and directional ablation, are constrained within a two-dimensional subspace defined by the activation and feature direction, maki

Xinhang Li, Qing Guo, Junyu Chen, Zheng Guo

With increasing urban traffic complexity, Traffic Signal Control (TSC) is essential for optimizing traffic flow and improving road safety. Large Language Models (LLMs) emerge as promising approaches for TSC. However, they are prone to hallucinations in emergencies, leading to unreliable decisions that may cause substantial delays for emergency vehicles. More

Shiho Matta, Lis Kanashiro Pereira, Peitao Han, Fei Cheng

Modern vision-language models (VLMs) excel at many multimodal tasks, yet their grasp of temporal information in video remains weak and has not been adequately evaluated. We probe this gap with a deceptively simple but revealing challenge: judging the arrow of time (AoT)-whether a short clip is played forward or backward. We introduce AoT-PsyPhyBENCH, a psych

Marek Napiórkowski, Pawel Jakubczyk

We study the thermal Casimir effect in ideal Bose gases with spin-orbit (S-O) coupling of Rashba type below the critical temperature for Bose-Einstein condensation. In contrast to the standard situation involving no S-O coupling, the system exhibits long-ranged Casimir forces both in two and three dimensions ($d=2$ and $d=3$). We identify the relevant scalin

Davide Fiorina, Elisabetta Baracchini, Giorgio Dho, Paolo Soffitta

We report on the development of a large-volume, wide field-of-view time projection chamber (TPC) for X-ray polarimetry, featuring a triple-GEM amplification stage and optical readout. Originally developed within the CYGNO program for directional dark matter searches, the system employs a scientific CMOS (sCMOS) camera and a photomultiplier tube (PMT) to coll

Duc-Hai Nguyen, Vijayakumar Nanjappan, Barry O'Sullivan, Hoang D. Nguyen

Millions of people take surveys every day, from market polls and academic studies to medical questionnaires and customer feedback forms. These datasets capture valuable insights, but their scale and structure present a unique challenge for large language models (LLMs), which otherwise excel at few-shot reasoning over open-ended text. Yet, their ability to pr

Harri Niemi, Jussi Auvinen, Kari J. Eskola, Henry Hirvonen

We present a novel saturation and leading order collinear factorization based Monte-Carlo implementation of the EKRT model for computing QCD matter initial states in high-energy nuclear collisions. As new features the MC implementation gives a full 3-dimensional initial state event-by-event, introduces new event-by-event fluctuating spatially dependent nucle

Yonghua Wang, Wei Chao

Traditional seesaw mechanisms provide an elegant theoretical framework for explaining the small yet non-zero masses of neutrinos. Nevertheless, they face significant experimental challenges, primarily because the energy scale associated with the seesaw mechanism is too high to be directly probed in terrestrial experiments. In this paper, we explore the gravi

Mathis Engelbart, Mike Kosek, Lars Eggert, Jörg Ott

The DNS is a key component of the Internet. Originally designed to facilitate the resolution of host names to IP addresses, its scope has continuously expanded over the years, today covering use cases such as load balancing or service discovery. While DNS was initially conceived as a rather static directory service in which resource records (RR) only change

Na Chen, Yurui Tang

The circumference denoted by $c(G)$ of a graph $G$ is the length of its longest cycle. Let $\delta(G)$ and $\omega(G)$ denote the minimum degree and the clique number of a graph $G$, respectively. In [\emph{Electron. J. Combin.} 31(4)(2024) $\#$P4.65], Yuan proved that if $G$ is a 2-connected graph of order $n$, then $c(G)\geq \min\{n,\omega(G)+\delta(G)\}$

Kamiokande Collaboration, S. Jung, K. Abe, S. Abe

We present the results of searches for nucleon decays via $p\rightarrow\nu\pi^{+}$ and $n\rightarrow\nu\pi^{0}$ using a 0.484 Mt$\cdot$yr exposure of Super-Kamiokande I-V data covering the entire pure water phase of the experiment. Various improvements on the previous 2014 nucleon decay search, which used an exposure of 0.173 Mt$\cdot$yr, are incorporated. T

Haochen Chen, Qi Huang, Anan Wu, Wenhao Zhang

Automatic structure elucidation is essential for self-driving laboratories as it enables the system to achieve truly autonomous. This capability closes the experimental feedback loop, ensuring that machine learning models receive reliable structure information for real-time decision-making and optimization. Herein, we present DiSE, an end-to-end diffusion-ba

Minyi Peng, Darian Gunamardi, Ivan Tjuawinata, Kwok-Yan Lam

As a new and promising approach, existing machine unlearning (MU) works typically emphasize theoretical formulations or optimization objectives to achieve knowledge removal. However, when deployed in real-world scenarios, such solutions typically face scalability issues and have to address practical requirements such as full access to original datasets and m

Geert Brethouwer

We study the stability of plane Poiseuille flow (PPF) and plane Couette flow (PCF) subject to streamwise system rotation using linear stability analysis and direct numerical simulations. The linear stability analysis reveals two asymptotic regimes depending on the non-dimensional rotation rate ($Ro$): a low-$Ro$ and a high-$Ro$ regime. In the low-$Ro$ regime

Nikolas Anic, Andrea Barbon, Ralf Seiz, Carlo Zarattini

This paper investigates whether large language models (LLMs) can improve cross-sectional momentum strategies by extracting predictive signals from firm-specific news. We combine daily U.S. equity returns for S&P 500 constituents with high-frequency news data and use prompt-engineered queries to ChatGPT that inform the model when a stock is about to enter a m

Guanyu Pan, Jianing Zhou, Xiaotong Liu, Yunqing Huang

Inverse source localization from Helmholtz boundary data collected over a narrow aperture is highly ill-posed and severely undersampled, undermining classical solvers (e.g., the Direct Sampling Method). We present a modular framework that significantly improves multi-source localization from extremely sparse single-frequency measurements. First, we extend a

Do Hyun Kim, Hua Zhou, Brendon Chau, Aubrey Jensen

Characterizing the genetic basis of survival traits, such as age at disease onset, is critical for risk stratification, early intervention, and elucidating biological mechanisms that can inform therapeutic development. However, time-to-event outcomes in human cohorts are frequently right-censored, complicating both the estimation and partitioning of total he

Naufa Nazar, Mashhoor A. Al-Wardat, Ahmad Abushattal, Hassan B. Haboubi

In this study, we applied Al-Wardat's method to analyze the subgiant system HIP72217 for which we obtained accurate parameters including stellar masses, effective temperatures ($T_{\text{eff}}$) and system age.For the primary component we determined a stellar mass of $M_A = 1.14 \pm 0.15\,M_{\odot}$ and effective temperature $T_{\text{eff,A}} = 6125 \pm 50$\

Soumya Satpathi, Suparna Sarkar, Swapan K. Pati

We investigate the phases and phase-transitions in one-dimensional alternating mixed-spin (1/2-1) chain in the presence of both frustration and anisotropy. Frustration is introduced via next-nearest-neighbor interactions, while single-ion anisotropy is incorporated at each lattice site. Our results show that moderate frustration can drive a phase transition

Vladimir U. Nazarov, E. K. U. Gross

We revisit the problem of deceleration of a charge moving in a medium. Going beyond the traditional approach, which relies on Ehrenfest dynamics, we treat the projectile fully quantum mechanically, on the same footing as the electrons of the target. In order to separate the dynamics of the projectile from that of the electrons, we employ the Exact Factorizat

Pushpendra Yadav

The bound electron-hole pairs known as excitons govern the optical properties of insulating solids. While their behavior in equilibrium is well-understood theoretically, the nonequilibrium regime at high excitation densities-where phenomena like electron-hole liquids emerge - is less explored. This thesis presents a first-principles study of excitons in two-

J. Philidet, K. Belkacem

The inclusion of convection in stellar evolution models lacks realism, especially near convective-radiative interfaces. Furthermore, the interaction of convection with oscillations prevent us from accurately predicting seismic frequencies, and therefore from fully exploiting the asteroseismic data of low-mass stars. We aim to develop a new formalism to model

Jia-Rou Liou, Alvina Y. L. On, H. -Y. Karen Yang, J. A. ZuHone

Recent observations of the Fornax cluster show depolarization signatures on megaparsec scales, which may be associated with shocks and/or sloshing motions during cluster merger and/or in-fall. To investigate the possible reasons behind the depolarization, we carry out analytical and full polarized radiative transfer (PRT) calculations of radio point sources

Tao Jin, Stuart Florescu, Heyu, Jin

We address finance-native collateral optimization under ISDA Credit Support Annexes (CSAs), where integer lots, Schedule A haircuts, RA/MTA gating, and issuer/currency/class caps create rugged, legally bounded search spaces. We introduce a certifiable hybrid pipeline purpose-built for this domain: (i) an evidence-gated LLM that extracts CSA terms to a normal

Fanhao Kong, Haiyi Wang

We extend the functional Breuer-Major theorem for Gaussians to the Poisson case, where the stationary sequence arises from a Poisson point process. We use the $L^p$ spectral gap inequality of Poisson point process as a tool to prove tightness.

Daniel Siebel-Cortopassi, Pei Liu

We analyze single-core and split-core defect structures in nematic liquid crystals within the Landau-de Gennes framework by studying minimizers of the associated energy functional. A bifurcation occurs at a critical temperature threshold, below which both split-core and single-core configurations are solutions to the Euler-Lagrange equation, with the split-c

Krishna Kingkar Pathak

Hydrogen bonds play a pivotal role in chemistry, biology, and condensed-matter physics, where quantum tunnelling can strongly influence structure and dynamics. Isotope substitution (H $\rightarrow$ D) provides a sensitive probe of such tunnelling, but theoretical descriptions often rely on purely numerical models or simplified potentials that obscure physica

Yu. D. Fomin

In the present study we investigate the phase diagram of silicon within the framework of SNAP machine learning potential model. We show that the melting line of diamond phase of silicon is a linear function of pressure, which is in good agreement with experimental data. At the same time the melting temperature is strongly underestimated. Also, this model fai

Hengrui Kang, Zhuangcheng Gu, Zhiyuan Zhao, Zichen Wen

Document AI has advanced rapidly and is attracting increasing attention. Yet, while most efforts have focused on document layout analysis (DLA), its generative counterpart, layout generation, remains underexplored. Distinct from traditional graphic layout design and room layout planning, document layout generation typically involves a larger number of elemen

Yifeng Cai, Ziming Wang, Zhaomeng Deng, Mengyu Yao

AI agents capable of GUI understanding and Model Context Protocol are increasingly deployed to automate mobile tasks. However, their reliance on over-privileged, static permissions creates a critical vulnerability: instruction injection. Malicious instructions, embedded in otherwise benign content like emails, can hijack the agent to perform unauthorized act

Yuwei Ou, Yunying Wang

The regular $n$-gon elliptic relative equilibrium (ERE) is a Kepler homographic solution generated by the regular $n$-gon central configuration, and its linear stability depends on the eccentricity $\mathfrak{e}\in[0,1)$. While Moeckel \cite{Moe1} established the spectral instability for this solution at $\mathfrak{e}=0$ for all $n\geq3$, it remained unknown

Junlin Liu, Zhaomeng Deng, Ziming Wang, Mengyu Yao

Super apps are the cornerstones of modern digital life, embedding financial transactions into nearly every aspect of daily routine. The prevailing security paradigm for these platforms is overwhelmingly focused on pre-transaction authentication, preventing unauthorized payments before they occur. We argue that a critical vulnerability vector has been largely

Habtamu Menberu Tedila, Di Li, Pei Wang, Rai Yuen

We present a detailed single-pulse study of the long-period pulsar PSR J2129+4119 using high-sensitivity FAST observations. Despite locating well below the traditional death line, the pulsar exhibits sustained and multi-modal emission behavior, including nulls, weak pulses, regular emission, and occasional bright pulses. The nulling fraction is measured to b

Ping Li, Chengyuan Cai, Tao Yu

Conventional spin pumping, driven by magnetization dynamics, is longitudinal since the pumped spin current flows normal to the interface between the ferromagnet and the conductor. We predict \textit{Hall-type/transverse} and \textit{unidirectional} spin pumping into conductors by near-field electromagnetic radiation emitted by, \textit{e.g.}, magnetization d

Luis Fredes, Jean-François Marckert

Let $M$ be an irreducible transition matrix on a finite state space $V$. For a Markov chain $C=(C_k,k\geq 0)$ with transition matrix $M$, let $\tau^{\geq 1}_u$ denote the first positive hitting time of $u$ by $C$, and $\rho$ the unique invariant measure of $M$. Kemeny proved that if $X$ is sampled according to $\rho$ independently of $C$, the expected value

Ryu Tomonaga

A $d$-silting object is a silting object whose derived endomorphism algebra has global dimension $d$ or less. We give an equivalent condition, which can be stated in terms of dg quivers, for silting mutations to preserve the $d$-siltingness under a mild assumption. Moreover, we show that this mild assumption is always satisfied by $ν_d$-finite algebras. As a

Qi Luo, Xiaonan Li, Tingshuo Fan, Xinchi Chen

Retrieval-augmented generation (RAG) has emerged as a leading approach to reducing hallucinations in large language models (LLMs). Current RAG evaluation benchmarks primarily focus on what we call local RAG: retrieving relevant chunks from a small subset of documents to answer queries that require only localized understanding within specific text chunks. How

Ashish Bhoopesh Gulaguli, Shashwat Singh, Rakesh Kumar Bansal

In this work we extend the results developed in 2022 for a sequential change detection algorithm making use of Page's CUSUM statistic, the empirical distribution as an estimate of the pre-change distribution, and a universal code as a tool for estimating the post-change distribution, from the i.i.d. case to the Markov setup.

Mehdi Khaleghi, Sobhan Sheykhivand, Nastaran Khaleghi, Sebelan Danishvar

The sustainability of supply chain plays a key role in achieving optimal performance in controlling the supply chain. The management of risks that occur in a supply chain is a fundamental problem for the purpose of developing the sustainability of the network and elevating the performance efficiency of the supply chain. The correct classification of products

Rajiv Movva, Smitha Milli, Sewon Min, Emma Pierson

Human feedback can alter language models in unpredictable and undesirable ways, as practitioners lack a clear understanding of what feedback data encodes. While prior work studies preferences over certain attributes (e.g., length or sycophancy), automatically extracting relevant features without pre-specifying hypotheses remains challenging. We introduce Wha

Yinghang Jiang, Jiguo Wu, Junfan Zhu, Rongchun Ge

We propose a fundamentally new design strategy of light-pulsed atom interferometry (LPAI) with a single atomic beam splitter. A traditional $\pi/2$-pulse Raman beam is employed to render a small momentum transfer at the initial state. After a short period of evolution during which physical relevant information can be loaded, a quantum weak measurement is app

Woojin Kim, Jaeyoung Do

While diffusion language models (DLMs) enable fine-grained refinement, their practical controllability remains fragile. We identify and formally characterize a central failure mode called update forgetting, in which uniform and context agnostic updates induce token level fluctuations across timesteps, erasing earlier semantic edits and disrupting the cumulat

Yaotian Guo, Fei Jiang, Takeshi Tsuji, Yoshitake Kato

Permeability characterizes the capacity of porous formations to conduct fluids, thereby governing the performance of carbon capture, utilization, and storage (CCUS), hydrocarbon extraction, and subsurface energy storage. A reliable assessment of rock permeability is therefore essential for these applications. Direct estimation of permeability from low-resolu

Kangkang Sun, Jun Wu, Minyi Guo, Jianhua Li

Federated Learning (FL) enables collaborative model training without data sharing, yet participants face a fundamental challenge, e.g., simultaneously ensuring fairness across demographic groups while protecting sensitive client data. We introduce a differentially private fair FL algorithm (FedPF) that transforms this multi-objective optimization into a zero

Riya Samanta

Generating structurally valid and behaviorally diverse synthetic event logs for interaction-aware models is a challenging yet crucial problem, particularly in settings with limited or privacy constrained user data. Existing methods such as heuristic simulations and LLM based generators often lack structural coherence or controllability, producing synthetic d

Li Wang, Yiyu Zhuang, Yanwen Wang, Xun Cao

3D human pose estimation from sketches has broad applications in computer animation and film production. Unlike traditional human pose estimation, this task presents unique challenges due to the abstract and disproportionate nature of sketches. Previous sketch-to-pose methods, constrained by the lack of large-scale sketch-3D pose annotations, primarily relie

Armin Ilg

The electron-positron stage of the Future Circular Collider (FCC-ee) provides exciting opportunities that are enabled by next generation particle physics detectors. This contribution presents IDEA, a detector concept optimised for FCC-ee and composed of a vertex detector based on MAPS, a very light drift chamber, a silicon wrapper, a high resolution dual-rea

Aaron Brown, Homin Lee, Davi Obata, Yuping Ruan

We find conditions for stationary measures of random dynamical systems on surfaces having dissipative diffeomorphisms to be absolutely continuous. These conditions involve a uniformly expanding on average property in the future (UEF) and past (UEP). Our results can cover random dynamical systems generated by "very dissipative" diffeomorphisms and perturbatio