December 2025 arXiv papers — page 34

Congrui Bai, Zhenting Du, Weibang Bai

This paper introduces a novel variable stiffness mechanism termed Helically Wound Structured Electrostatic Layer Jamming (HWS-ELJ) and systematically investigates its potential applications in variable stiffness robotic finger design. The proposed method utilizes electrostatic attraction to enhance interlayer friction, thereby suppressing relative sliding an

Long Zhang, Wei-neng Chen

The increasing integration of Large Language Models (LLMs) into decision-making frameworks has exposed significant vulnerabilities to social compliance, specifically sycophancy and conformity. However, a critical research gap exists regarding the fundamental mechanisms that enable external social cues to systematically override a model's internal parametric

Yuya Maeda, Toshiki Kobayashi, Takuma Ueno, Kentaro Shibata

The growing demand for high-capacity quantum communication and large-scale quantum computing underscores the importance of networking quantum processing units via multiplexed photonic channels. A neutral atom array with multiplexed atom-photon entanglement is a promising platform for its realization. Here, we demonstrate a key multiplexed photonic interface

Hiroshi Matsuzoe, Asuka Takatsu

The Kullback--Leibler divergence together with exponential families establishes the foundation of information geometry and is widely generalized. Among the generalization, we focus on the $(h,\tau)$-divergence and $(h,\tau)$-exponential families. We present a sufficient condition for the $(h,\tau)$-divergence to induce a Hessian structure on an $(h,\tau)$-ex

Guokan Chen, Yao Xiao, Bin Fan, Meixin Xionga

PINNs enhance scientific computing by incorporating physical laws into neural network structures, leading to significant advancements in scientific computing. However, PINNs struggle with multi-scale and high-frequency problems due to pathological gradient flow and spectral bias, which severely limit their predictive power. By combining an enhanced network a

Baiting Xie, Chenglong Yu

We study the homology groups of the complement of a complexified real line arrangement with coefficients in complex rank-one local systems. Using Borel--Moore homology, we establish an algorithm computing their dimensions via the real figures of the arrangement. It enables us to give a new upper bound. We further consider the case where the arrangement conta

Icey Siyi Ai, Maria Chudnovsky, Julien Codsi

For a graph $H$, we say that $H$ has the Erdős-Pósa property for subdivisions with function $f$, if, for every nonnegative integer $k$ and every graph $G$, either $G$ contains (as a subgraph) $k+1$ pairwise vertex-disjoint subdivisions of $H$ or there exists a set $X\subseteq V(G)$ such that $G\setminus X$ contains no $H$-subdivision and $|X|\leq f(k)$. We s

Jiayu Li, Rajesh Gangireddy, Samet Akcay, Wei Cheng

Vision-Language Models (VLMs) learn powerful multimodal representations through large-scale image-text pretraining, but adapting them to hierarchical classification is underexplored. Standard approaches treat labels as flat categories and require full fine-tuning, which is expensive and produces inconsistent predictions across taxonomy levels. We propose an

Qianqian Qi, Peter G. M. van der Heijden

Across fields such as machine learning, social science, geography, considerable attention has been given to models that factorize a nonnegative matrix into the product of two or three matrices, subject to nonnegative or row-sum-to-1 constraints. Although these models are to a large extend similar or even equivalent, they are presented under different names,

Radost Waszkiewicz, Franciszek Myck, Łukasz Białas, Maria Puciata-Mroczynska

The sensory richness of coffee is widely recognised and arises from the complex chemistry and immersion in cultural practices of coffee preparation. In contrast, the physical complexity of espresso has received less attention. The multiphase reactive flow through a dissolving, elastic porous medium remains challenging to describe. Using a controlled experime

Zhaojiang Lin, Yong Xu, Kai Sun, Jing Zheng

Wearable devices such as AI glasses are transforming voice assistants into always-available, hands-free collaborators that integrate seamlessly with daily life, but they also introduce challenges like egocentric audio affected by motion and noise, rapid micro-interactions, and the need to distinguish device-directed speech from background conversations. Exis

Aoyang Qin, Deqian Kong, Wei Wang, Ying Nian Wu

Conventional Reinforcement Learning (RL) algorithms, typically focused on estimating or maximizing expected returns, face challenges when refining offline pretrained models with online experiences. This paper introduces Generative Actor Critic (GAC), a novel framework that decouples sequential decision-making by reframing \textit{policy evaluation} as learni

Shanglin Yang, Zhan Shi

Large language models provide rich semantic priors and strong reasoning capabilities, making them promising auxiliary signals for recommendation. However, prevailing approaches either deploy LLMs as standalone recommender or apply global knowledge distillation, both of which suffer from inherent drawbacks. Standalone LLM recommender are costly, biased, and u

Keshav Sinha, Sumitra, Richa Kumari, Akashdeep Bhardwaj

In todays security landscape, every user wants to access large amounts of data with confidentiality and authorization. To maintain confidentiality, various researchers have proposed several techniques. However, to access secure data, researchers use access control lists to grant authentication and provide authorization. The above several steps will increase

Lichao Wu, Mohamadreza Rostami, Huimin Li, Nikhilesh Singh

Modern hardware systems, driven by demands for high performance and application-specific functionality, have grown increasingly complex, introducing large surfaces for bugs and security-critical vulnerabilities. Fuzzing has emerged as a scalable solution for discovering such flaws. Yet, existing hardware fuzzers suffer from limited semantic awareness, ineffi

Yue Huang, Ling Xue, Kun Zhao, Xiaoming Zheng

Inspired by Carrillo-Li-Wang's work [Proc. London Math. Soc., 2021] on stationary solutions to the singular Keller-Segel system, this paper presents a novel family of explicit steady-state solutions for the same model on a bounded interval, expressed in terms of trigonometric and hyperbolic functions. Under Dirichlet boundary conditions and within a biologic

Adharsh Kamath, Sishen Zhang, Calvin Xu, Shubham Ugare

LLM-based agents are deployed in safety-critical applications, yet current guardrail systems fail to prevent violations of temporal safety policies, requirements that govern the ordering and sequencing of agent actions. For instance, agents may access sensitive data before authenticating users or process refunds to unauthorized payment methods, violations th

Alireza Sepehri, Muhammad Al-Zafar Khan

Recently, Padmanabhan has argued that a difference between the number of degrees of freedom on the surface and the number in a bulk causes the expansion of the universe. We can reconsider this idea in a BIon system. A Bion is formed from two branes that are connected by a wormhole. Our universe may live on one of these branes. Each brane could be formed by j

Egor Shulgin, Grigory Malinovsky, Sarit Khirirat, Peter Richtárik

Federated Learning (FL) enables collaborative training on decentralized data. Differential privacy (DP) is crucial for FL, but current private methods often rely on unrealistic assumptions (e.g., bounded gradients or heterogeneity), hindering practical application. Existing works that relax these assumptions typically neglect practical FL features, including

Taeyoon Kim

The super-exponential growth of generative AI has intensified the institutional mismatch between the pace of technological diffusion and the speed of institutional adaptation. This study proposes the Socio-Institutional Asynchrony Model, or SIAM, to quantitatively evaluate the relative effectiveness of two policy levers: intervention timing and enforcement e

Varshith Gudur

Modern AI systems rely on vector embeddings stored and searched using floating-point arithmetic. While effective for approximate similarity search, this design introduces fundamental non-determinism: identical models, inputs, and code can produce different memory states and retrieval results across hardware architectures (e.g., x86 vs. ARM). This prevents re

Xiao Guo, Zhoujian Cao, Zhiwei Chen

The recent discovery of M31 UCXB-1, the first extragalactic ultracompact X-ray binary (UCXB) with an orbital period of $T_{\rm orb} \sim 465$ s, presents a unique laboratory for studying close binary evolution and an unprecedented target for continuous gravitational wave (GW) searches. Its identification as a strong candidate black hole-white dwarf (BH-WD) s

Chandrasekhar Gokavarapu, D Madhusudhana Rao

Aim. This paper (Paper D) unifies the ideal-theoretic, computational, and homological layers developed in Papers A (Rao 2025), B (Rao 2025), and C (Rao 2025) into a geometric framework that includes fuzzy and computational geometries on the spectrum Spec_G(T) and derived invariants in TGMod. Scope. We construct structure sheaves and Grothendieck topologies a

Kentaro Saji, Masaaki Umehara, Kotaro Yamada

We give explicit real-analytic functions whose zero sets characterize the images of the standard maps of wave-front singularities. Such functions are realizations of the main-analytic sets in the sense of Ishikawa-Koike-Shiota (1984). More concretely, a subset of Euclidean space is called a global main-analytic set if it can be described, up to a set of smal

Thomas Schürmann

Let $(M,g)$ be a compact $n$-dimensional Riemannian manifold with nonempty boundary and $n\geq 2$. Assume that ${\mathrm{Ric}(M)\ge (n-1)K}$ for some ${K>0}$ and that $\partial M$ has nonnegative mean curvature with respect to the outward unit normal. Denote by $\lambda$ the first Dirichlet eigenvalue of the Laplacian. Ling's gradient-comparison method (Ling

Hongqing He, Jie Xu, Wenyuan Yang, Yonghua Zhu

Recently, contrastive learning (CL) plays an important role in exploring complementary information for multi-view clustering (MVC) and has attracted increasing attention. Nevertheless, real-world multi-view data suffer from data incompleteness or noise, resulting in rare-paired samples or mis-paired samples which significantly challenges the effectiveness of

Lei Liu, Hao Zhu, Yue Shen, Zhixuan Chu

Continual Pre-training (CPT) serves as a fundamental approach for adapting foundation models to domain-specific applications. Scaling laws for pre-training define a power-law relationship between dataset size and the test loss of an LLM. However, the marginal gains from simply increasing data for CPT diminish rapidly, yielding suboptimal data utilization and

Henglin Liu, Huijuan Huang, Jing Wang, Chang Liu

Reinforcement learning (RL), particularly GRPO, improves image generation quality significantly by comparing the relative performance of images generated within the same group. However, in the later stages of training, the model tends to produce homogenized outputs, lacking creativity and visual diversity, which restricts its application scenarios. This issu

Amgad Ahmed Ali Ibrahim, Hein Htet, Ryoji Asahi

Radiation-induced grafting (RIG) enables precise functionalization of polymer films for ion-exchange membranes, CO2-separation membranes, and battery electrolytes by generating radicals on robust substrates to graft desired monomers. However, reproducibility remains limited due to unreported variability in base-film morphology (crystallinity, grain orientati

Puyun Wang, Kaimin Yu, Huayang He, Xianyu Wu

Polarization-based underwater 3D imaging exploits polarization cues to suppress background scattering, exhibiting distinct advantages in turbid water. Although data-driven polarization-based underwater 3D reconstruction methods show great potential, existing public datasets lack sufficient diversity in scattering and observation conditions, hindering fair co

Deep Pankajbhai Mehta

When AI systems explain their reasoning step-by-step, practitioners often assume these explanations reveal what actually influenced the AI's answer. We tested this assumption by embedding hints into questions and measuring whether models mentioned them. In a study of over 9,000 test cases across 11 leading AI models, we found a troubling pattern: models almo

Md Ashik Khan, Arafat Alam Jion

AI image generators create both photorealistic images and stylized art, necessitating robust detectors that maintain performance under common post-processing transformations (JPEG compression, blur, downscaling). Existing methods optimize single metrics without addressing deployment-critical factors such as operating point selection and fixed-threshold robus

Takuto Kawamoto, Yoshiki Higo

"Extract Method" refactoring is a technique for consolidating code clones. Parameterization approaches are used to extract a single method from multiple code clones that contain differences. This approach parameterizes expressions and behaviors within a method. In particular, behavior parameterization has been extensively studied in Java programs, but little

Jie Xu, Wenyuan Yang, Yazhou Ren, Lifang He

Real-world multi-view data often exhibit highly inconsistent missing patterns, posing significant challenges for incomplete multi-view clustering (IMVC). Although existing IMVC methods have made progress from both imputation-based and imputation-free routes, they largely overlook the issue of pair underutilization. Specifically, inconsistent missing patterns

Yuichiro Nakai, Hajime Otsuka, Yoshihiro Shigekami, Zhihao Zhang

We investigate a framework of the Minimal Supersymmetric Standard Model (MSSM) in which the quark and lepton flavor structure and suppression of flavor-changing neutral currents (FCNCs) are governed by non-invertible selection rules. By implementing such non-group-like fusion rules for matter fields, arising from gauging the outer automorphism $\mathbb{Z}_2$

Md Ashik Khan, Md Nahid Siddique

Multimodal chest X-Ray analysis often fine-tunes large vision-language models, which is computationally costly. We study parameter-efficient training (PET) strategies, including frozen encoders, BitFit, LoRA, and adapters for multi-label classification on the Indiana University Chest X-Ray dataset (3,851 image-report pairs; 579 test samples). To mitigate dat

Hussain Alasmawi, Numan Saeed, Mohammad Yaqub

The growing demand for prenatal ultrasound imaging has intensified a global shortage of trained sonographers, creating barriers to essential fetal health monitoring. Deep learning has the potential to enhance sonographers' efficiency and support the training of new practitioners. Vision-Language Models (VLMs) are particularly promising for ultrasound interpr

Wenshuo Peng, Gongxuan Wang, Tianmeng Yang, Chuanhao Li

Recent text-to-video generation models have made remarkable progress in visual realism, motion fidelity, and text-video alignment, yet they still struggle to produce socially coherent behavior. Unlike humans, who readily infer intentions, beliefs, emotions, and social norms from brief visual cues, current models often generate literal scenes without capturin

Mona Alfayez, Ohoud Alharbi

Autonomous vehicles (AVs) are emerging as a transformative innovation in transportation, offering potential benefits in safety, sustainability, and efficiency. Saudi Arabian adoption of AVs aligns with Vision 2030, emphasizing smart mobility through initiatives such as the Riyadh Autonomous Metro and self-driving cars. This study explores Saudi citizens perc

Aiwei Zhang, Arvind Pillai, Andrew Campbell, Nicholas C. Jacobson

As wearable sensing becomes increasingly pervasive, a key challenge remains: how can we generate natural language summaries from raw physiological signals such as actigraphy - minute-level movement data collected via accelerometers? In this work, we introduce MotionTeller, a generative framework that natively integrates minute-level wearable activity data wi

Sanjeev Kumar Verma

Neutrino energy reconstruction on nuclear targets underlies oscillation measurements and precision tests of weak interactions. Inclusive charged--current data have long exhibited degeneracies commonly attributed to axial-mass tuning, multinucleon dynamics, and final-state interactions. This work shows that, even in the idealized limit of perfect detectors an

Xiaoda Xu, Jun Xian

We present two main contributions to the expected star discrepancy theory. First, we derive a sharper expected upper bound for jittered sampling, improving the leading constants and logarithmic terms compared to the state-of-the-art [Doerr, 2022]. Second, we prove the strong partition principle for star discrepancy, showing that any equal-measure stratified

Chokri Manai

In this work, we consider general exchangeable quantum mean-field Hamiltonian such as the prominent quantum Curie-Weiss model under the influence of a random external field. Despite being arguably the simplest class of disordered quantum systems, the random external field breaks the symmetry of the mean-field Hamiltonian and hence standard quantum de Finetti

Huiran Li, Qiucheng Li, Baozhu Feng

In search engine advertising (SEA) market, where competition among retailers is intense and multifaceted, channel coordination between retailers and manufacturers emerges as a critical factor, which significantly influences the effectiveness of advertising strategies. This research attempts to provide managerial guidelines for cooperative advertising in the

Yu-Heng Sheng, De-Fu Bu, Xiao-Hong Yang, Yi-Ren Chang

Tidal Disruption Events (TDEs) have recently been proposed as potential probes for Population III stars. However, the properties of the accretion flow and the wind from the Pop III star TDE system are not clear. By performing radiative hydrodynamic simulations, we study the 'circularized' accretion flow of the Pop III star TDE system. The masses of the black

Christian Janos Lebeda, Aleksandar Nikolov, Haohua Tang

We revisit the task of releasing marginal queries under differential privacy with additive (correlated) Gaussian noise. We first give a construction for answering arbitrary workloads of weighted marginal queries, over arbitrary domains. Our technique is based on releasing queries in the Fourier basis with independent noise with carefully calibrated variances

Jyh-Haur Teh

Let $Conf^{lf}_{\infty}(\C)$ and $C^{lf}_{\infty}(\C)$ denote the locally finite infinite ordered and unordered configuration spaces of the complex plane. We prove that both $Conf^{lf}_{\infty}(\C)$ and $C^{lf}_{\infty}(\C)$ are aspherical. We further obtain a locally finite analogue of the braid exact sequence, \[ 1\longrightarrow H^{lf}(\infty)\longrightar

Siddhartha Upadhyay, Ratnangshu Das, Pushpak Jagtap

In this work, we extend the Spatiotemporal Tube (STT) framework to address Probabilistic Temporal Reach-Avoid-Stay (PrT-RAS) tasks in dynamic environments with uncertain obstacles. We develop a real-time tube synthesis procedure that explicitly accounts for time-varying uncertain obstacles and provides formal probabilistic safety guarantees. The STT is formu

Haiping Fu, Yao Lu

Using Bochner techniques, we prove that a compact Einstein manifold of dimension $n \ge 4$ has constant curvature provided that the curvature operator of the second kind satisfies a cone condition that is strictly weaker than nonnegativity. Furthermore, employing a result of Li \cite{Li5}, we establish that any closed Einstein manifold of dimension $n \ge 4$

Xinzhe Xie, Buyu Guo, Bolin Li, Shuangyan He

Multi-focus image fusion aims to generate an all-in-focus image from a sequence of partially focused input images. Existing fusion algorithms generally assume that, for every spatial location in the scene, there is at least one input image in which that location is in focus. Furthermore, current fusion models often suffer from edge artifacts caused by uncert

Soichiro Murakami, Hidetaka Kamigaito, Hiroya Takamura, Manabu Okumura

Humor is a salient testbed for human-like creative thinking in large language models (LLMs). We study humor using the Japanese creative response game Oogiri, in which participants produce witty responses to a given prompt, and ask the following research question: What makes such responses funny to humans? Previous work has offered only limited reliable means

Toshio Horiuchi

We study the Caffarelli-Kohn-Nirenberg type inequalities in the case of $p=1$ and generalize them adopting weight functions $w(|x|)$ on $R^n$ with $w(t)$ in ${W}(R_+)$. Here ${W}(R_+)$ is a general class of weight functions on $R_+$ including non-doubling weights like $e^{1/t}$ and $e^{-1/t}$.

Hikaru Sasaki

We show how to identify generators of bosonic VOAs associated with $T_{[n-1,1]}^{[1^n]}(SU(n))$ and $T_{[n-1,1^2]}^{[2,1^{n-1}]}(SU(n+1))$, and conjecture that the algebraic structure of these VOAs can be constructed by these generators. We also find out that the boundary VOA associated with $T_{[n-1,1]}^{[1^n]}(SU(n))$ naturally includes the bosonic VOA.

Bohan Zhang, Biyuan Liu, Penghua Ying, Zherui Chen

Graphene oxide (GO) exhibits rich chemical heterogeneity that strongly influences its structural, thermal, and mechanical properties, yet quantitatively linking reduction chemistry to heat transport remains challenging. In this work, we develop a machine-learned neuroevolution potential (NEP) trained on an existing density functional theory dataset (\textit{

Iskandar Raufov, Dilshod Nematov, Saidjafar Murodzoda, Sakhidod Sattorzoda

This study presents a first principles investigation of the structural, thermodynamic, electronic, optical and thermoelectric properties of aluminum antimonide (AlSb) in its cubic (F-43m) and hexagonal (P63mc) phases. Both structures are dynamically and mechanically stable, as confirmed by phonon calculations and the Born Huang criteria. The lattice constant

Dinh Dũng

We investigate the approximation of generalized Laguerre- or Laplace-weighted integrals over $\mathbb{R}^d_+$ or $\mathbb{R}^d$ of functions from generalized Laguerre- or Laplace-weighted Sobolev spaces of mixed smoothness, respectively. We prove upper and lower bounds of the convergence rate of optimal quadratures with respect to $n$ integration nodes for f

H. Susanto, N. Karjanto

We study the $\phi^{6}$ model and derive two broad classes of lattice discretizations that admit static, translationally invariant kinks; that is, stationary kink profiles that can be centered at an arbitrary position relative to the lattice. These discretizations are constructed using a one-dimensional map, $\phi_{n+1}=F(\phi_{n})$, which provides a direct

Liang Geng, Wei He, Rongwei Yang

The Prime Number Theorem asserts that the density of primes less than or equal to $N$ is asymptotically equal to $1/\log N$. The density of prime triples in coprime triples in $\mathbb{Z}^3_+$ is determined to be $3\zeta (3)/\log N$, where $\zeta$ is the Riemann zeta function. In this paper, we prove that the density of prime triples in coprime triples in th

Dingyu Wang, Zimu Yuan, Jiajun Liu, Shanggui Liu

Background: The rapid integration of foundation models into clinical practice and public health necessitates a rigorous evaluation of their true clinical reasoning capabilities beyond narrow examination success. Current benchmarks, typically based on medical licensing exams or curated vignettes, fail to capture the integrated, multimodal reasoning essential

Xinglin Pan, Shaohuai Shi, Wenxiang Lin, Yuxin Wang

The mixture-of-experts (MoE) architecture scales model size with sublinear computational increase but suffers from memory-intensive inference due to KV caches and sparse expert activation. Recent disaggregated expert parallelism (DEP) distributes attention and experts to dedicated GPU groups but lacks support for shared experts and efficient task scheduling,

Siyuan Li, Shikai Fang, Lei Cheng, Feng Yin

Functional tensor decomposition can analyze multi-dimensional data with real-valued indices, paving the path for applications in machine learning and signal processing. A limitation of existing approaches is the assumption that the tensor rank-a critical parameter governing model complexity-is known. However, determining the optimal rank is a non-determinist

Toshihiko Masuda

Gelaki-Naidu-Nikshych and Turaev-Virelizier showed the existence of $G$-braiding on the relative Drinfeld center of a $G$-graded tensor category. We will explain this concept from the viewpoint of Longo-Rehren inclusions.

Yuanfang Yue, Yuetao Wang

The higgsino-like neutralino is a compelling dark matter candidate motivated by both cosmology and naturalness considerations. While a pure higgsino typically requires a mass of around $1.1~\mathrm{TeV}$ to satisfy the observed thermal relic abundance, the presence of light sleptons can significantly alter this requirement. In this work, we revisit higgsino

Khanh Chau Le

This study utilizes the variational-asymptotic method to establish a one-dimensional theory for functionally graded rods characterized by general anisotropy from the three-dimensional elasticity theory. A distinctive feature of this dimension reduction procedure is the numerical solution of dual cross-sectional problems, which provide rigorous upper and lowe

Fanwei Zeng, Changtao Miao, Jing Huang, Zhiya Tan

Sophisticated text-centric forgeries, fueled by rapid AIGC advancements, pose a significant threat to societal security and information authenticity. Current methods for text-centric forgery analysis are often limited to coarse-grained visual analysis and lack the capacity for sophisticated reasoning. Moreover, they typically treat detection, grounding, and

Sunith Vallabhaneni, Thomas Berkane, Maimuna Majumder

Many research areas rely on data from the web to gain insights and test their methods. However, collecting comprehensive research datasets often demands manually reviewing many web pages to identify and record relevant data points, which is labor-intensive and susceptible to error. While the emergence of large language models (LLM)-powered web agents has beg

Jiapeng Li, Changsheng You, Chao Zhou, Yong Zeng

The prior works on near-field target localization have mostly assumed ideal hardware models and thus suffer from two limitations in practice. First, extremely large-scale arrays (XL-arrays) usually face a variety of hardware impairments (HIs) that may introduce unknown phase and/or amplitude errors. Second, the existing block coordinate descent (BCD)-based m

Michael Wissmann, Joseph Dufouleur, Louis Veyrat, Anna Isaeva

Intrinsic magnetic topological insulators can host quantum states with quantized magneto-electric responses, such as the axion and Chern insulators states evidenced in ultra-thin MnBi2Te4 films. Yet, whereas quantization is investigated thoroughly, transport properties related to the phase of charge carriers remains unexplored. Here, we study quantum coheren

Wenhao Ou

Assume that $X$ is a compact complex analytic variety which has quotient singularities in codimension 2, and that $\mathcal{F}$ is a reflexive sheaf on $X$. Using orbifold modifications, we can define first and second homological Chern classes for $\mathcal{F}$. If in addition $X$ has a K\"ahler form $\omega$ and $\mathcal{F}$ is $\omega$-stable, then we ded

Brani Vidakovic

The nondecimated or translation-invariant wavelet transform (NDWT) is a central tool in classical multiscale signal analysis, valued for its stability, redundancy, and shift invariance. This paper develops two complementary quantum formulations of the NDWT that embed these classical properties coherently into quantum computation. The first formulation is bas

Ethan Andersson, Valeri Frumkin

Topological phenomena typically govern the behavior of delocalized waves, giving rise to robust transport in electronic, photonic, and mechanical systems. Whether similar principles can directly control the motion of a localized particle, particularly one dynamically coupled to the field that guides it, has remained largely unexplored. Here we show that topo

Suncheng Xiang, Xiaoyang Wang, Junjie Jiang, Hejia Wang

Colonoscopic Polyp Re-Identification aims to match the same polyp from a large gallery with images from different views taken using different cameras, which plays an important role in the prevention and treatment of colorectal cancer in computer-aided diagnosis. However, the coarse resolution of high-level features of a specific polyp often leads to inferior

Xiaoqian Qi, Haoye Chai, Yue Wang, Zhaocheng Wang

The Reference Signal Received Power (RSRP) is a crucial factor that determines communication performance in mobile networks. Accurately predicting the RSRP can help network operators perceive user experiences and maximize throughput by optimizing wireless resources. However, existing research into RSRP prediction has limitations in accuracy and verisimilitud

Shota Ono

Carbon exhibits both a layered ground state structure that produces two-dimensional (2D) nanosheets and a non-layered diamond structure created under high pressure conditions. Motivated by this metastability relationship, we revisit the ground state structure of metal dichalcogenides that are known to have non-layered pyrite-type structure. Ultrathin films o

Chencheng Deng, Weiling Yang, Jianbin Fang, Dezun Dong

General Matrix Multiplication (GEMM) is a critical kernel in high-performance computing and deep learning. While modern architectures like ARM's Scalable Matrix Extension (SME) introduce dedicated hardware for matrix operations, existing linear algebra libraries fail to fully exploit its potential, particularly for large matrices. This paper presents MpGEMM,

Sinya Aoki

This short report is dedicated to the 40th anniversary of International Journal of Modern Physics A (IJMPA) and Modern Physics Letters A (MPLA). While the report is based on a series of papers[1-8], its content reflects my personal viewpoints. Therefore I am solely responsible for all the statements in the report. In this report we discuss conservation of en

B. Guo, F. Yan, Th. Henning, L. Nortmann

Ground-based high-resolution spectroscopy has identified various chemical species in the atmospheres of ultra-hot Jupiters, including neutral and ionized metals, providing key insights into planet formation through refractory element abundances. We observed the dayside thermal emission spectrum of the UHJ HAT-P-70b using the high-resolution spectrographs CAR

A. Gando, K. Ichimura, K. Ishidoshiro, T. Kikuchi

We propose and evaluate a source-as-detector search for the de-excitation of the long-lived isomer $^{180\mathrm{m}}\mathrm{Ta}$ in natural tantalum (Ta), using a $\gamma$-ray transition-edge-sensor (TES) array. We exploit two capabilities not available in conventional high-purity germanium (HPGe) searches: (i) near-unity containment of low-energy secondarie

P. Rajguru, I. R. Churchill, G. Graham

The Peter Principle posits that organizations promoting their best performers risk elevating employees to roles where their competence no longer translates, thereby degrading overall efficiency. We investigate when this dynamic emerges and how to mitigate it using a large-scale agent-based model (ABM) of a five-level hierarchy. Results show the Peter Princip

Paul Caucal, Zhong-Bo Kang, Piotr Korcyl, Farid Salazar

We present a detailed numerical investigation of semi-inclusive forward di-hadron production in proton-nucleus collisions employing the Color Glass Condensate effective theory. We focus on the regime where di-hadrons are produced nearly back-to-back in the transverse plane, thereby justifying a transverse-momentum-dependent factorization approach in terms of

Yiwei Yan, Hao Li, Hua He, Gong Kai

Online medical consultations generate large volumes of conversational health data that often embed protected health information, requiring robust methods to classify data categories and assign risk levels in line with policies and practice. However, existing approaches lack unified standards and reliable automated methods to fulfill sensitivity classificatio

Kenzo Imamura, Suguru Otani, Tohya Sugano, Koji Yokote

Chiappori et al. (2025) study several indices of assortativeness in matching, including the aggregate likelihood ratio and the odds ratio. We provide a counterexample showing that their axiomatization of the aggregate likelihood ratio is not valid as stated. We identify the exact class of indices characterized by the axioms in Chiappori et al. (2025). We the

Ho Yun, Yoav Zemel

We explore the geometry of the Bures-Wasserstein space for potentially degenerate Gaussian measures on a separable Hilbert space. In this general setting, the optimal transport map is formally the subgradient of a convex function that is infinite almost everywhere, rendering conventional duality-based variational methods ineffective. We overcome this analyti

Atreyee Bhattacharya, Satyajit Maity, Kashyap Rajeevsarathy

Let $S_g$ be a closed, connected, and oriented smooth surface of genus $g\geq 2$. Let the mapping class group of $S_g$ be denoted by $\mathrm{Mod}(S_g)$ and the Teichm\"{u}ller space of $S_g$ by $\mathrm{Teich}(S_g)$. It is known that $\mathrm{Mod}(S_g)$ acts by isometries on $\mathrm{Teich}(S_g)$ with respect to the Weil-Petersson metric. In this paper, we

Amirehsan Alizadehherfati, Yuxi Jiang, Nils von den Driesch, Christine Falter

Electrons bound to shallow donors in ZnSe quantum wells are promising candidates for optically addressable spin qubits and single-photon sources. However, their optical coherence and indistinguishability are often limited by spectral broadening arising from charge fluctuations in the local environment. Here, we report electrical control of single donor qubit

Kyosuke Maeda, Tomohiro Okuma, Kei-ichi Watanabe, Ken-ichi Yoshida

In this paper, we show that for any rational surface singularity $A$, the canonical trace ideal $\mathrm{Tr}_A(K_A)$ is an integrally closed ideal, which is represented by the minimal anti-nef cycle $F$ on the minimal resolution of singularities so that $K_X+F$ is anti-nef. Then $F \ge Z_f$ if $A$ is not Gorenstein, where $Z_f$ is the fundamental cycle. As a

Masaya Nishihata, Suguru Otani

We examine whether team affinity differs across skill dimensions in team production. Using a novel nonparametric framework that accommodates task-level structure, role asymmetry, and latent affinity, we decompose team performance into skill-specific productivity and unobserved match affinity. As an illustrative application, we analyze elite women's bobsleigh

Xiao Jin, Liang Diao, Qixin Xiao, Yifan Hu

Anomaly detection holds considerable industrial significance, especially in scenarios with limited anomalous data. Currently, reconstruction-based and unsupervised representation-based approaches are the primary focus. However, unsupervised representation-based methods struggle to extract robust features under domain shift, whereas reconstruction-based metho

Jiaxin Huang, Youlin Li, Zaiting Xu

In this paper, we present a complete coarse classification of non-loose Legendrian and transverse torus knots in any contact structure on $S^1\times S^2$.

Antara Titikhsha, Om Kulkarni, Dharun Muthaiah

Text-to-image diffusion models generate highly detailed textures, yet they often rely on surface appearance and fail to follow strict geometric constraints, particularly when those constraints conflict with the style implied by the text prompt. This reflects a broader semantic gap between human perception and current generative models. We investigate whether

Faeq Abed, Asmaa AlMellah, Gaber Faisel

This study presents a sensitivity analysis of exotic Higgs boson decays at the electron--positron stage of the Future Circular Collider (FCC-ee), performed within the FCCAnalyses framework. The analysis investigates Higgs boson production in association with a Z boson in electron--positron collisions at a center-of-mass energy of 240~GeV. The Higgs boson is

Alexander Vinogradov

Generative image models have recently shown significant progress in image realism, leading to public concerns about their potential misuse for document forgery. This paper explores whether contemporary open-source and publicly accessible diffusion-based generative models can produce identity document forgeries that could realistically bypass human or automat

Sukanya Krishna, Marie-Laure Charpignon, Maimuna Majumder

Substance overdose mortality in the United States claimed over 80,000 lives in 2023, with the COVID-19 pandemic exacerbating existing trends through healthcare disruptions and behavioral changes. Estimating excess mortality, defined as deaths beyond expected levels based on pre-pandemic patterns, is essential for understanding pandemic impacts and informing

Sean Campbell, Courtney C. White, Amanda M. Alexander, William Ott

Delay is an inherent feature of genetic regulatory networks. It represents the time required for the assembly of functional regulator proteins. The protein production process is complex, as it includes transcription, translocation, translation, folding, and oligomerization. Because these steps are noisy, the resulting delay associated with protein production

Anton Feeney-Johansson, Yuri Aikawa, Shigehisa Takakuwa, Nagayoshi Ohashi

As part of the ALMA Large Program "Early Planet Formation in Embedded Disks" (eDisk), 12CO (2 - 1) was observed towards 19 nearby low-mass protostars. Of these objects, 15 sources are found to show molecular outflow emission. Based on their morphological and kinematical structures, the CO outflows are classified into three types: a wind-driven shell, where a

Yi Xie, Ning Wang, Zhongzhou Ren

A phenomenological model is proposed for a systematic description of the spontaneous fission (SF) half-lives $T_{\rm SF}$ of heavy and super-heavy nuclei. Based on the effective tunneling barrier (ETB), the proposed approach reproduces the SF half-lives of 79 known nuclei with an average deviation of 0.8, which is $17\%$ smaller than that of the linear corre

Haotian Lv, Yuhui Zhang, Jiangbo Dai, Hanli Wu

Ground Penetrating Radar (GPR) has emerged as a pivotal tool for non-destructive evaluation of subsurface road defects. However, conventional GPR image interpretation remains heavily reliant on subjective expertise, introducing inefficiencies and inaccuracies. This study introduces a comprehensive framework to address these limitations: (1) A DCGAN-based dat

Bing Cheng, Howell Tong

Being infinite dimensional, non-parametric information geometry has long faced an "intractability barrier" due to the fact that the Fisher-Rao metric is now a functional incurring difficulties in defining its inverse. This paper introduces a novel framework to resolve the intractability with an Orthogonal Decomposition of the Tangent Space ($T_fM = S \oplus

Lei Zhao, Zihao Ma, Boyu Lin, Yuhe Liu

We present an RL-central framework for Language and Vision Assistants (RLLaVA) with its formulation of Markov decision process (MDP). RLLaVA decouples RL algorithmic logic from model architecture and distributed execution, supporting researchers in implementing new RL algorithms with minimal code, and to plug in a broad family of RL methods and vision-langua

Xinmin Li, Chuanfei Dong, Liang Wang, Sae Aizawa

Mercury's magnetotail hosts a thin and highly dynamic current sheet (CS), where magnetic reconnection and strong fluctuations frequently occur. Here, we statistically analyze magnetic field power spectra across 370 magnetotail CSs observed by MESSENGER. About 20% of the events are quasi-laminar, showing single power-law spectra, whereas 80% are turbulent