December 2025 arXiv papers — page 10

Eleni Grigoriou, Manos Kamarianakis, George Papagiannakis

The purpose of this review article is to provide a bibliographical as well as evidence-based visual guide regarding the effect of ``Uncanny Valley'' (UV) and how it profoundly influences medical virtual reality simulation-based training. The phenomenon, where increasingly realistic virtual humans elicit discomfort due to subtle imperfections, is crucial to u

Yingzhuo Liu, Shuodi Liu, Weijun Luo, Liuyu Xiang

Policy Space Response Oracles (PSRO) combines game-theoretic equilibrium computation with learning and is effective in approximating Nash Equilibrium in zero-sum games. However, the computational cost of PSRO has become a significant limitation to its practical application. Our analysis shows that game simulation is the primary bottleneck in PSRO's runtime.

Robert Hanson

Using geometric Eisenstein series, foundational work of Arinkin and Gaitsgory constructs cuspidal-Eisenstein decompositions for ind-coherent nilpotent sheaves on the de Rham moduli of local systems. This article extends these constructions to coherent (not ind-coherent) nilpotent sheaves on the Dolbeault, Hodge and twistor moduli from non-abelian Hodge theor

Sungmin Lee, Kichang Lee, Gyeongmin Han, JeongGil Ko

Many location-based services rely on a point-in-polygon test (PiP), checking whether a point or a trajectory lies inside a geographic zone. Since geometric operations are expensive in zero-knowledge proofs, privately performing the PiP test is challenging. In this paper, we answer the research questions of how different ways of encoding zones affect accuracy

Samet Ünsal

We introduce the Quantum State Continuity Problem (QSCP), a security objective orthogonal to identity authentication that captures whether a systems current execution is a legitimate continuation of a unique past execution. We show that classical and stateless quantum authentication mechanisms fail to enforce continuity and remain vulnerable to fork attacks.

Guillaume Riviere

The investigation of tangible user interfaces commenced approximately thirty years ago. Questions on its commercial potential become more pressing as the field becomes mature. To take the field one step further -- as the emergence of components contributed to the commercial development of graphical user interfaces -- this article suggests that applicative ta

Lynn Heller, Sebastian Heller, Claudio Meneses

We investigate the Hitchin hyperk\"ahler metric on the moduli space of strongly parabolic $\mathfrak{sl}(2,\C)$-Higgs bundles on the $n$-punctured Riemann sphere and its degeneration obtained by scaling the parabolic weights $t\alpha$ as $t\to0$. Using the parabolic Deligne--Hitchin moduli space, we show that twistor lines of hyperpolygon spaces arise as lim

Hongyuan Rui

In this paper, we investigate the parity of three class of Hurwitz-type cyclotomic Euler sums using the methods of contour integration and residue computation, and derive explicit parity formulas for linear, quadratic, and some higher-order cases. Based on their connection with cyclotomic multiple Hurwitz polylogarithm functions, we further obtain certain pa

Huang Junyao, Situ Ruimin, Ye Renqin

As artificial intelligence systems increasingly mediate consumer information discovery, brands face algorithmic invisibility. This study investigates Cultural Encoding in Large Language Models (LLMs) -- systematic differences in brand recommendations arising from training data composition. Analyzing 1,909 pure-English queries across 6 LLMs (GPT-4o, Claude, G

May Bashendy, Walid Massoud, Sohaila Eltanbouly, Salam Albatarni

Automated Essay Scoring (AES) has gained increasing attention in recent years, yet research on Arabic AES remains limited due to the lack of publicly available datasets. To address this, we introduce LAILA, the largest publicly available Arabic AES dataset to date, comprising 7,859 essays annotated with holistic and trait-specific scores on seven dimensions:

Chengxiang Zhang, Xu Zhang

We investigate the existence of nonnegative bump solutions to the sublinear elliptic equation \[ \begin{cases} -\Delta v - K(x)v + |v|^{q-2}v = 0 & \text{in } \mathbb{R}^N, \\ v(x) \to 0 & \text{as } |x| \to \infty, \end{cases} \] where $q \in (1,2)$, $ N \geq 2$, and the potential $K \in L^p_{\mathrm{loc}}(\mathbb{R}^N)$ with $p > N/2$ is a function without

Sang-Shin Baak

It is shown that the sound wave in the backreaction affected dynamical spacetime follows the equations for a massive scalar field in a analogue spacetime using number-conserving approach. Even with backreaction, the analogue metric is in the same form to the case without backreaction. The sound velocity, fluid density, and fluid velocity are defined with sma

Jiaxin Lyu, Guanghui He

We investigate random spatially coupled low-density parity-check (SC-LDPC) code ensembles over finite fields. Under different variable-node edge-spreading rules, the random Tanner graphs of several coupled ensembles are defined by multiple independent, uniformly random monomial maps. The two main coupled ensembles considered are referred to as the standard c

Rahul Medicharla, Alper Yilmaz

In this paper, we introduce MotivNet, a generalizable facial emotion recognition model for robust real-world application. Current state-of-the-art FER models tend to have weak generalization when tested on diverse data, leading to deteriorated performance in the real world and hindering FER as a research domain. Though researchers have proposed complex archi

Yang Yang, Shaofeng Rao, Yuxuan Hou, Jiabo Liu

Kagome metals AV$_3$Sb$_5$ (A = K, Rb, Cs) have recently emerged as a promising platform for exploring correlated and topological quantum states, yet their potential for optoelectronic applications remains largely unexplored. Here, we report high-performance photodetectors based on van der Waals KV$_3$Sb$_5$/WSe$_2$ heterojunctions. A high-quality Schottky i

H. E. S. S. collaboration

PKS 0346-27 is a Low Synchrotron Peaked (LSP) blazar at redshift 0.991. The very-high-energy (VHE, E > 100 GeV) spectra of blazars are always affected by $\gamma\gamma$ absorption by the Extragalactic Background Light (EBL) and subsequently, no blazars have been detected in VHE $\gamma$-rays at redshifts exceeding 1. Extending the redshift range of VHE-detec

Shuyun Wang, Haiyang Sun, Bing Wang, Hangjun Ye

Vision-centric autonomous driving systems rely on diverse and scalable training data to achieve robust performance. While video object editing offers a promising path for data augmentation, existing methods often struggle to maintain both high visual fidelity and temporal coherence. In this work, we propose \textbf{Mirage}, a one-step video diffusion model f

M. C. Araújo, J. Furtado, J. G. Lima, T Mariz

In this work, we investigate vacuum polarization in the Rarita-Schwinger model within the framework of Very Special Relativity. We examine both massive and massless spin-3/2 fields coupled to the Maxwell field. The Mandelstam-Leibbrandt prescription is applied in order to evaluate the one-loop integrals, and we work within the SIM(2) limit.

Ziquan Liu, Zhewei Zhu, Xuyang Shi

Open-vocabulary semantic segmentation (OVSS) is fundamentally hampered by the coarse, image-level representations of CLIP, which lack precise pixel-level details. Existing training-free methods attempt to resolve this by either importing priors from costly external foundation models (e.g., SAM, DINO) or by applying static, hand-crafted heuristics to CLIP's i

Yuanhui Luo, Xinzhou Guo, Yuqi Gu

Subgroup analysis evaluates treatment effects across multiple sub-populations. When subgroups are defined by latent memberships inferred from imperfect measurements, the analysis typically involves two inter-connected models, a latent class model and a subgroup outcome model. The classical one-stage framework, which models the joint distribution of the two m

Tuhin Subhra Mahato, Subhra Sankar Dhar

This article studies the robust version of persistent homology based on trimming methodology to capture the geometric feature through support of the data in presence of outliers. Precisely speaking, the proposed methodology works when the outliers lie outside the main data cloud as well as inside the data cloud. In the course of theoretical study, it is esta

Nuttanon Songsuwan

Node-Kayles is a well-known impartial combinatorial game played on graphs, where players alternately select a vertex and remove it along with its neighbors. By the Sprague-Grundy theorem, every position of an impartial game corresponds to a non-negative integer called its Grundy value. In this paper, we investigate the Grundy value sequences of $n$-regular t

Li-Qun Shen, Hao-Jin Wang, Mengzhao Sun, Yang Xiang

Interfacial reconstruction between two-dimensional (2D) materials and metal substrates fundamentally governs heterostructure properties, yet conventional flat substrates fail to capture the continuous crystallographic landscape. Here, we overcome this topological limitation using non-Euclidean interfaces-curved 2D graphene-copper surfaces as a model system-t

Manju Kumari, Dilip Sasmal, Suresh Chandra Baral, Maneesha P

Tuning the valence state and electronic structure of catalytically active sites is crucial for improving Fenton and Fenton-like reactions, which rely on the efficient activation of the H2O2 molecule. Pure TiO2, however, has inadequate activity towards the H2O2 activation and is often constrained by the intrinsic electronic limitations of pristine TiO2. Herei

Yuhki Hosoya

This paper examines the simplest case of total differential equations that appears in the theory of foliation structures, without imposing the smoothness assumptions. This leads to a peculiar asymmetry in the differentiability of solutions. To resolve this asymmetry, this paper focuses on the differentiability of the integral manifold. When the system is loc

Aditya Sreevatsa K, Arun Kumar Raveendran, Jesrael K Mani, Prakash G Shigli

SmartFlow is a multi-layered framework that integrates Reinforcement Learning and Agentic AI to address the dynamic rebalancing problem in urban bike-sharing services. Its architecture separates strategic, tactical, and communication functions for clarity and scalability. At the strategic level, a Deep Q-Network (DQN) agent, trained in a high-fidelity simula

Masatoshi Noumi, Takashi Takebe

The operators in the Zakharov-Shabat equations of integrable hierarchies are usually defined from the Lax operators. In this article it is shown that the Zakharov-Shabat equations themselves recover the Lax operators under suitable change of independent variables in the case of the KP hierarchy and the modified KP hierarchy (in the matrix formulation).

Sina Jahromi, Farshid Hajati, Alireza Rezaee, Javaher Nourian

The challenge of imbalanced data is prominent in medical image classification. This challenge arises when there is a significant disparity in the number of images belonging to a particular class, such as the presence or absence of a specific disease, as compared to the number of images belonging to other classes. This issue is especially notable during pande

Hongwei Tan, Kui Xiao, Rong-zhen Guo, Shoucheng Wang

In this paper, we investigate the evaporation of the quantum Oppenheimer-Snyder black hole. Within a semiclassical framework, we compute the energy emission of Hawking radiation by introducing a massless scalar field as a test field, considering both minimally and non-minimally coupled cases. For the minimally coupled case, we find that loop quantum gravity

Giuseppe Canale, Kashyap Thimmaraju

Large Language Models (LLMs) are rapidly transitioning from conversational assistants to autonomous agents embedded in critical organizational functions, including Security Operations Centers (SOCs), financial systems, and infrastructure management. Current adversarial testing paradigms focus predominantly on technical attack vectors: prompt injection, jailb

Ming-Ming Yu, Yi Chen, Börje F. Karlsson, Wenjun Wu

Efficient target localization and autonomous navigation in complex environments are fundamental to real-world embodied applications. While recent advances in multimodal foundation models have enabled zero-shot object goal navigation, allowing robots to search for arbitrary objects without fine-tuning, existing methods face two key limitations: (1) heavy reli

Thevesh Thevananthan, Danesh Prakash Chacko

Electoral boundaries in Malaysia are not publicly available in machine-readable form. This prevents rigorous analysis of geography-centric issues such as malapportionment and gerrymandering, and constrains spatial perspectives on electoral outcomes. We present the second component of the Malaysian Election Corpus (MECo), an open-access collection of digital

Ruoshi Wen, Guangzeng Chen, Zhongren Cui, Min Du

Vision-language-action (VLA) models have enabled language-conditioned, long-horizon robot manipulation, but most existing systems are limited to grippers. Scaling VLA policies to bimanual robots with high degree-of-freedom (DoF) dexterous hands remains challenging due to the expanded action space, frequent hand-object occlusions, and the cost of collecting r

Rohit Kumar Meena, Akhil Tayal, Andrei Gloskovskii, Mukul Gupta

Fe4N is a well-known anti-perovskite compound exhibiting high magnetization, high chemical stability, low coercivity, high Curie temperature, and high spin-polarization ratio. Therefore, it is a viable candidate for applications in spintronic and magnetic storage devices. However, the Fe4N phase is formed in a narrow substrate temperature (Ts)-N concentratio

Shivani Saini, Ramesh Kumar Vats, Arup Kumar Sahoo

Recent advancements in physics-informed neural networks (PINNs) and their variants have garnered substantial focus from researchers due to their effectiveness in solving both forward and inverse problems governed by differential equations. In this research, a modified Auxiliary physics-informed neural network (A-PINN) framework with balanced adaptive optimiz

Chi Zhang, Mingqian Yao

This paper explores computational methods for solving the Longest Vector Problem (LVP) and Closest Vector Problem (CVP) in $p$-adic fields. Leveraging the non-Archimedean property of $p$-adic norms, we propose a polynomial time algorithm to compute orthogonal bases for $p$-adic lattices when the $p$-adic field is given by a minimal polynomial. The method uti

Deeparaj Bhat, Zhenkun Li, Fan Ye

We prove that the unreduced singular instanton homology $I^\sharp(Y,K;\mathbb{Z})$ has $2$-torsion for any null-homologous fibered knot $K$ of genus $g>0$ in a closed $3$-manifold $Y$ except for $\#^{2g}S^1\times S^2$. The main technical result is a formula of $I^\sharp(Y,K;\mathbb{C})$ via sutured instanton theory, by which we can compare the dimensions of

Wei Chen, Giacomo Dimarco, Lorenzo Pareschi

Plasma kinetic equations exhibit pronounced sensitivity to microscopic perturbations in model parameters and data, making reliable and efficient uncertainty quantification (UQ) essential for predictive simulations. However, the cost of uncertainty sampling, the high-dimensional phase space, and multiscale stiffness pose severe challenges to both computationa

Pavel Slepov

The jet quenching phenomenon in an anisotropic quark-gluon plasma is studied using gauge-gravity duality. We consider a more general orientation of the contour of a lightlike Wilson loop in the boundary field theory. The Nambu-Goto action for a two-dimensional worldsheet, whose boundary is this contour, is evaluated in a five-dimensional bulk. We present the

Sohini Kayal, P. Gayatri, Mridweeka Singh, Kuntal Misra

Using the 1D Monte Carlo-based radiative transfer code TARDIS, we investigate the spectral evolution of the Type Iax supernova (SN) 2020rea from -7 days before to +21 days after maximum light. Our best-fit models indicate stratified, velocity-dependent abundances at early times, successfully reproducing most observed spectral features. As the SN evolves, the

Guillaume Chagnaud, Chris M Taylor, Lawrence S Jackson, Anne Barber

Soil moisture is a key ingredient of humid heat through supplying moisture and modifying boundary layer properties. Soil moisture heterogeneity due to e.g., antecedent rainfall, can strongly influence weather patterns; yet, its effect on humid heat is poorly understood. Idealized numerical simulations are performed with a cloud-resolving ($\Delta x$=500 m),

Yating Cai, Yanghui Xu, Zehua Hu, Jiazhou Chen

Accurate segmentation of the tooth point cloud is of great significance for diagnosis clinical assisting and treatment planning. Existing methods mostly employ semantic segmentation, focusing on the semantic feature between different types of teeth. However, due to the tightly packed structure of teeth, unclear boundaries, and the diversity of complex cases

Yujie Yang, Zhichao Zhang, Jiazhou Chen, Zichao Wu

Existing text-driven 3D human motion editing methods have demonstrated significant progress, but are still difficult to precisely control over detailed, part-specific motions due to their global modeling nature. In this paper, we propose PartMotionEdit, a novel fine-grained motion editing framework that operates via part-level semantic modulation. The core o

Shuhei Mano

We discuss a class of discrete Gaussian free fields on Hamming graphs, where interactions are determined solely by the Hamming distance between vertices. The purpose of examining this class is that it differs significantly from the commonly discussed spin system on the integer lattice with nearest-neighbour interactions. After introducing general results on

Krzysztof Sienicki

This note is a friendly technical check of Jeffrey Bub's There is No Quantum World (arXiv:2512.18400v2). I flag one unambiguous mathematical slip (a cardinality identity that implicitly assumes the Continuum Hypothesis) and then point out a few places where the discussion of infinite tensor products, ``sectorization,'' and measurement updates would benefit f

David Fuentes-Jimenez, Daniel Pizarro, Álvaro Hernández, Adin Bartoli

Digital humanities are significantly transforming how Egyptologists study ancient Egyptian texts. The OCR-PT-CT project proposes a recognition method for hieroglyphs based on images of Coffin Texts (CT) from Adriaan de Buck (1935-1961) and Pyramid Texts (PT) from Middle Kingdom coffins (James Allen, 2006). The system identifies hieroglyphs and transcribes th

Yijie Lin

We introduce a notion of restricted pyramid configurations for computing the 1-leg Donaldson-Thomas $\mathbb{Z}_2\times\mathbb{Z}_2$-vertex. We study a special type of restricted pyramid configurations with the prescribed 1-leg partitions, and find one unique class of them satisfying the symmetric interlacing property. This leads us to obtain an explicit for

Jichao Zhang, Baohua Sun, Isao Tanihata, Zilun Shen

We present a statistical method for detecting and analysing state changes in experimental measurements using the Cuscore statistic and its special case, the Centred Cuscore statistic. These statistics are designed to identify deviations in detector responses using sequential hypothesis testing relative to a defined reference state. Applications to charge-cha

Yonglak Son, Suhyeok Kim, Seungryong Kim, Young Geun Kim

Diffusion transformer (DiT) achieves remarkable performance in visual generation, but its iterative denoising process combined with larger capacity leads to a high inference cost. Recent works have demonstrated that the iterative denoising process of DiT models involves substantial redundant computation across steps. To effectively reduce the redundant compu

A. C. Khunt, K. Yavuz Ekşi, P. C. Vinodkumar

We investigate the impact of pressure anisotropy on the structural and geometric properties of neutron stars within general relativity, focusing primarily on the phenomenological Bowers-Liang (BL) model, and comparing selected results with a quasi-local prescription. Using the SLy equation of state, we explore how anisotropic stresses modify global observabl

Pieter M. Blok, Haozhou Wang, Hyun Kwon Suh, Peicheng Wang

Potato yield is a key indicator for optimizing cultivation practices in agriculture. Potato yield can be estimated on harvesters using RGB-D cameras, which capture three-dimensional (3D) information of individual tubers moving along the conveyor belt. However, point clouds reconstructed from RGB-D images are incomplete due to self-occlusion, leading to syste

Wei Qu, Yiming Ma, Fei Ye, Chan Lu

We present SeedProteo, a diffusion-based model for de novo all-atom protein design. We demonstrate how to repurpose a cutting-edge folding architecture into a powerful generative design framework by effectively integrating self-conditioning features. Extensive benchmarks highlight the model's capabilities across two distinct tasks: in unconditional generatio

Pietro Carrara, Franck Fortuna, Renaud Delaunay, Joan Vila-Comamala

The paper presents a comprehensive description of a new setup implemented and commissioned at the SEXTANTS beamline of the SOLEIL synchrotron for absorption and scattering experiments with x-ray beams carrying an orbital angular momentum, also known as twisted x-ray beams. Two alternative methods have been implemented, based on the use of either spiral zone

Himanshu Mishra, Anubhab Roy

We study the translation and orientation dynamics of an anisotropic particle settling in monochromatic linear surface gravity waves. Recent work has shown that a neutrally buoyant spheroid attains a preferred mean orientation in such wave fields, independent of its initial state and determined solely by its aspect ratio. Comparing the settling parameter $\ma

Yankai Jiang, Wenjie Lou, Lilong Wang, Zhenyu Tang

We introduce SCP: the Science Context Protocol, an open-source standard designed to accelerate discovery by enabling a global network of autonomous scientific agents. SCP is built on two foundational pillars: (1) Unified Resource Integration: At its core, SCP provides a universal specification for describing and invoking scientific resources, spanning softwa

Yu Cheng, Shuailiang Ge

We study the impact of background-induced forces on dark matter (DM) annihilation and their implications for indirect detection. In the presence of a finite number density of background particles, loop-level interactions can generate an effective force that is significantly enhanced relative to the vacuum case. We construct a two-component DM model in which

Susanna Bisogni, Giustina Vietri, Andrea Travascio, Adriana Gargiulo

We outline a science case for next-generation wide-field spectroscopic surveys aimed at connecting the physics of the accretion disc and X-ray corona in active galactic nuclei (AGN) with the properties of their nebular regions and circumgalactic medium (CGM). We focus on the non-linear Lx-Luv relation and on deviations from this canonical coupling encoded in

Felix Zahner, Tim Drevelow, Roberto Lo Conte, Roland Wiesendanger

Topological spin structures such as magnetic skyrmions are of fundamental interest and promising for various types of applications in spintronics. Skyrmions have been predicted to emerge also in antiferromagnetic materials where they exhibit superior transport properties. They were experimentally revealed in synthetic antiferromagnets, however, still remain

Ping Li, Wen-Ping Liao, Sheng-Bang Qian, Li-Ying Zhu

Tidally tilted pulsators (TTPs), whose pulsation axis aligns with the binary's semi-major axis, represent a newly established class of oscillators in binary systems. While all previously known TTPs are either $\delta$ Scuti or subdwarf B-type stars, their existence has remained unidentified in more massive $\beta$ Cephei variables. Here, we report the discov

Kai Tao Huang, X. S Wang

Magnons are bosonic quasiparticles in magnetically ordered systems. Bosonic Bott index has been affirmed as a real-space topological invariant for a two-band ferromagnetic model. In this work,we theoretically investigate the topology and transport of magnons in a multi-band bosonic Kagome ferromagnetic model. We demonstrate the validity of the bosonic Bott i

Nan Jia, Wangchao Sang, Pengfei Lin, Xiangping Chen

The localization of code hallucinations aims to identify specific lines of code containing hallucinations, helping developers to improve the reliability of AI-generated code more efficiently. Although recent studies have adopted several methods to detect code hallucination, most of these approaches remain limited to coarse-grained detection and lack speciali

Qipeng Wang, Rui Sheng, Yafei Li, Huamin Qu

Recent advancements in Large Language Models (LLMs) have demonstrated significant promise in clinical diagnosis. However, current models struggle to emulate the iterative, diagnostic hypothesis-driven reasoning of real clinical scenarios. Specifically, current LLMs suffer from three critical limitations: (1) generating hallucinated medical content due to wea

Vladimir A. Vdovin, Ivan I. Pyataikin

To examine the process of native corrosion of ultrathin (about 10 nm) copper films deposited on quartz glass substrates $(SiO_2)$ with and without a germanium sublayer, the time dependences of the microwave reflection coefficient $R$ and direct current electrical resistivity $\rho$ of such samples exposed to air at room temperature have been studied. Under t

Xubo Luo, Zhaojin Li, Xue Wan, Wei Zhang

Accurate and real-time 6-DoF localization is mission-critical for autonomous lunar landing, yet existing approaches remain limited: visual odometry (VO) drifts unboundedly, while map-based absolute localization fails in texture-sparse or low-light terrain. We introduce KANLoc, a monocular localization framework that tightly couples VO with a lightweight but

Emma Kun, Santiago del Palacio, Imre Bartos, Francis Halzen

The origin and production mechanisms of high-energy astrophysical neutrinos remain open questions in multimessenger astronomy. Previous studies have hinted at a possible linear correlation between the hard X-ray and high-energy neutrino emission in active galactic nuclei. New \textit{NuSTAR} observations, first presented here, reveal that blazar PKS 1424+240

Yun-Xuan Lu, An-Wei Zhu, Christine E. Frank, Xin-Yi Huang

We report a compact setup with in-series two-dimensional magneto-optical traps (2D MOTs) that provides high-flux cold lithium and rubidium atoms. Thanks to the efficient short-distance Zeeman slowing, the maximum 3D MOT loading rate of lithium atoms reaches a record value of $6.6\times 10^{9}$ atoms/s at a moderate lithium-oven temperature of 372 degrees Cel

Xingyu Zhou, Qifan Li, Xiaobin Hu, Hai Chen

The diffusion model presents a powerful ability to capture the entire (conditional) data distribution. However, due to the lack of sufficient training and data to learn to cover low-probability areas, the model will be penalized for failing to generate high-quality images corresponding to these areas. To achieve better generation quality, guidance strategies

Sergio Testón-Martínez, Carlos Gutierrez-Ariza, Francisco J. Ocaña, Rafael Rubio de Casas

Seed dispersal is a fundamental process that allows offspring to reach suitable habitats and colonize new environments. While most plants rely on external vectors, some have evolved mechanisms that employ the buildup of liquid pressure in a closed compartment and its explosive release to disperse their seeds. This form of energy storage, reinvented by humans

Jui-Ting Lu, Henrique Ennes, Chih-Kang Huang, Ali Abbassi

Quantum brushes are computational arts software introduced by Ferreira et al (2025) that leverage quantum behavior to generate novel artistic effects. In this outreach paper, we introduce the mathematical framework and describe the implementation of two quantum brushes based on variational quantum algorithms, Steerable and Chemical. While Steerable uses quan

Yu-Tang Chang, Pin-Wei Chen, Shih-Fang Chen

Hyperspectral imaging (HSI) analysis faces computational bottlenecks due to massive data volumes that exceed available memory. While foundation models pre-trained on large remote sensing datasets show promise, their learned representations often fail to transfer to domain-specific applications like close-range agricultural monitoring where spectral signature

Alena Mufazalova

We present the recent results on charm baryon production and decays at Belle and Belle II experiments using a 1.4 ab$^{-1}$ data sample of $e^+ e^-$ collision collected at center-of-mass energies near the $\Upsilon(nS)$ resonances. The collected data contain a large number of $e^+ e^- \to c \bar{c}$ events that produce charmed baryons. We report on several s

Naoto Deguchi

This paper concerns the large-time behavior of perturbations around a time-periodic solution to the Navier-Stokes-Fourier system in the three-dimensional whole space. The time-periodic solution exists when a given external force is small enough. We derive the time-decay estimate of the perturbation under the assumption that an initial perturbation is suffici

Dzmitry Dudko

In this Note, we present recent developments in the Renormalization Theory of quadratic polynomials and discuss their applications, with an emphasis on the MLC conjecture, the problem of local connectivity of the Mandelbrot set, and on its geometric counterparts.

Hartmut Führ, Max Getter

Phase retrieval seeks to reconstruct a signal from phaseless intensity measurements and, in applications where measurements contain errors, demands stable reconstruction. We study local stability of phase retrieval in reproducing kernel Hilbert spaces. Motivated by Grohs-Rathmair's Cheeger-type estimate for Gabor phase retrieval, we introduce a kernel Cheege

Clemens Damke, Eyke Hüllermeier

Graphs are commonly used in machine learning to model relationships between instances. Consider the task of predicting the political preferences of users in a social network; to solve this task one should consider, both, the features of each individual user and the relationships between them. However, oftentimes one is not interested in the label of a single

Shuhua Deng, Shoukang Yang, Zixuan Zeng, Bo Yan

Precision measurements of the electron's electric dipole moment (eEDM) are critical for testing fundamental symmetries in particle physics, and heavy polar molecules-such as barium monofluoride (BaF)-have emerged as promising candidates for advancing the sensitivity. However, the achievement of a 3D magneto-optical trap (MOT) required slowing BaF molecules t

Sotirios Panagiotis Chytas, Vikas Singh

Large language models (LLMs) often map semantically related prompts to similar internal representations at specific layers, even when their surface forms differ widely. We show that this behavior can be explained through Iterated Function Systems (IFS), where layers act as contractive mappings toward concept-specific Attractors. We leverage this insight and

Boya Sun, Haotian Shi, Ying Ni, Shaocheng Jia

Increasing autonomous vehicles (AVs) in transportation systems makes effective interactions between AVs and pedestrians indispensable. External human--machine interface (eHMI), which employs visual or auditory cues to explicitly convey vehicle behaviors can compensate for the loss of human-like interactions and enhance AV--pedestrian cooperation. To facilita

Zefeng He, Xiaoye Qu, Yafu Li, Tong Zhu

While recent Multimodal Large Language Models (MLLMs) have attained significant strides in multimodal reasoning, their reasoning processes remain predominantly text-centric, leading to suboptimal performance in complex long-horizon, vision-centric tasks. In this paper, we establish a novel Generative Multimodal Reasoning paradigm and introduce DiffThinker, a

Reza Ramazani-Sharifabadi, Iman Ziaeian

A recently developed three-dimensional formalism for the nucleon-deuteron breakup channel initially considered only the leading-order term of the Faddeev equations, using the nucleon-nucleon T-matrix to compute the breakup amplitude. In the present study, we extend that formalism by solving the full three-nucleon Faddeev equation without three-nucleon-force

Hao-Yi Liu, Jin-Lei Yang, Ke-Sheng Sun, Tai-Fu Feng

The Minimal R-symmetric Supersymmetric Standard Model with Seesaw (MRSSMSeesaw) extends the MRSSM by incorporating right-handed neutrinos to generate neutrino masses via the Type-I seesaw mechanism. This work presents a detailed analysis of lepton flavor violation (LFV) processes, including $\ell_i \rightarrow \ell_j \gamma$, $\ell_i \rightarrow 3\ell_j$, an

Anton Adelöw, Matteo Gamba, Atsuto Maki

Supervised training of deep neural networks for classification typically relies on hard targets, which promote overconfidence and can limit calibration, generalization, and robustness. Self-distillation methods aim to mitigate this by leveraging inter-class and sample-specific information present in the model's own predictions, but often remain dependent on

Satoshi Jinnouchi

This short note includes three results: $(1)$ If a reflexive sheaf $\mathcal{E}$ on a log terminal K\"{a}hler-Einstein variety $(X,\omega)$ is slope stable with respect to a singular K\"{a}hler-Einstein metric $\omega$, then $\mathcal{E}$ admits an $\omega$-admissible Hermitian-Yang-Mills metric. $(2)$ If a K-stable log terminal projective variety with big a

TsaiChing Ni, ZhenQi Chen, YuanFu Yang

We present IMDD-1M, the first large-scale Industrial Multimodal Defect Dataset comprising 1,000,000 aligned image-text pairs, designed to advance multimodal learning for manufacturing and quality inspection. IMDD-1M contains high-resolution real-world defects spanning over 60 material categories and more than 400 defect types, each accompanied by expert-veri

Natalia Garanina, Vladimir Zyubin, Igor Anureev

Using an AI assistant, we developed a method for systematically constructing controlled natural language for requirements based on formal specification patterns containing logical attributes. The method involves three stages: 1) compiling a generalized natural language requirement pattern that utilizes all attributes of the formal specification template; 2)

Xinzhang Liu, Chao Wang, Zhihao Yang, Zhuo Jiang

TeleChat3-MoE is the latest series of TeleChat large language models, featuring a Mixture-of-Experts (MoE) architecture with parameter counts ranging from 105 billion to over one trillion,trained end-to-end on Ascend NPU cluster. This technical report mainly presents the underlying training infrastructure that enables reliable and efficient scaling to fronti

Evgenii Rudakov, Jonathan Shock, Benjamin Ultan Cowley

We present a training-free graph-based approach for solving interactive reasoning tasks in the ARC-AGI-3 benchmark. ARC-AGI-3 comprises game-like tasks where agents must infer task mechanics through limited interactions, and adapt to increasing complexity as levels progress. Success requires forming hypotheses, testing them, and tracking discovered mechanics

Ashish Patwari, Sanjeeva Reddy S, G Ramachandra Reddy

Modern sparse arrays are maximally economic in that they retain just as many sensors required to provide a specific aperture while maintaining a hole-free difference coarray. As a result, these are susceptible to the failure of even a single sensor. Contrarily, two-fold redundant sparse arrays (TFRSAs) and robust minimum redundancy arrays (RMRAs) ensure robu

Amir Khosravanizadeh, François Nédélec, Serge Dmitrieff

The mechanical properties of actin filaments are essential to their biological functions. Here, we introduce a highly coarse-grained model of actin filaments that preserves helicity and chirality while enabling mesoscale simulations. The framework is implemented in Cytosim, an open-source cytoskeleton simulation platform. We can predict and finely control th

Weilong Guo, Lianguo Li, Qingjun Tong, Ci Li

This paper focuses on the study of linear exciton Hall and Nernst effects in monolayer two-dimensional (2D) semiconductors, employing the semi-classical transport theory. By deriving the exciton Berry curvature in momentum space for a general inhomogeneous 2D system, we establish its dependence on the Berry curvature and the effective mass of electron and ho

Ziqiang Feng

We prove that any $C^{1+\alpha}$ transitive conservative partially hyperbolic diffeomorphism of a closed 3-manifold with virtually solvable fundamental group is ergodic. Consequently, in light of \cite{FP-classify}, this establishes the equivalence between transitivity and ergodicity for $C^{1+\alpha}$ conservative partially hyperbolic diffeomorphisms in \em

Jack A. Smith, Michael J. Strain

Spectral complexity is a useful resource in physical device identification, disorder-enhanced spectroscopy, and machine learning, but is often achieved in chip-scale devices at the expense of propagation loss, scalability, or reconfigurability. In this work, we demonstrate that device specific spectral complexity can be achieved using completely standardized

Yassine Otmani, Hacene Belbachir

Let $ p \ge 5 $ be a prime and let $ b, c \in \mathbb{Z} $. Denote by $ T_k(b,c) $ the generalized central trinomial coefficient, i.e., the coefficient of $ x^k $ in $ (x^2 + bx + c)^k $. In this paper, we establish congruences modulo $ p^3 $ and $ p^4 $ for sums of the form $$ \sum_{k=0}^{p-1} (2k+1)^{2a+1}\,\varepsilon^{k}\,\frac{T_k(b,c)^4}{d^{2k}}, $$ wh

Zikang Dong, Ruihua Wang, Weijia Wang, Hao Zhang

We study large values of quadratic character sums with summation lengths exceeding the square root of the modulus. Assuming the Generalized Riemann Hypothesis, we obtain a new Omega result.

Chubin Chen, Sujie Hu, Jiashu Zhu, Meiqi Wu

Recent studies have demonstrated significant progress in aligning text-to-image diffusion models with human preference via Reinforcement Learning from Human Feedback. However, while existing methods achieve high scores on automated reward metrics, they often lead to Preference Mode Collapse (PMC)-a specific form of reward hacking where models converge on nar

Udit Sharma

Machine learning systems appear stochastic but are deterministically random, as seeded pseudorandom number generators produce identical realisations across repeated executions. Standard evaluation practice typically treats runs across alternatives as independent and does not exploit shared sources of randomness. This paper analyses the statistical structure

Markus J. Buehler

We introduce materiomusic as a generative framework linking the hierarchical structures of matter with the compositional logic of music. Across proteins, spider webs and flame dynamics, vibrational and architectural principles recur as tonal hierarchies, harmonic progressions, and long-range musical form. Using reversible mappings, from molecular spectra to

Hassan Alshal, Elias C. Vagenas, Thomas Van Kortryk

We revisit the structure of higher-derivative spin-2 theories from the perspective of the Generalized Uncertainty Principle (GUP). We show that a minimal GUP deformation of the Fierz-Pauli (FP) action induces a higher-derivative kinetic operator equivalent, at quadratic order, to the spin-2 sector of Stelle's curvature-squared gravity. Via an auxiliary-field

Adi Shnaidman, Erin Feiglin, Osher Yaari, Efrat Mentel

Masked diffusion language models (MDLMs) generate text via iterative masked-token denoising, enabling mask-parallel decoding and distinct controllability and efficiency tradeoffs from autoregressive LLMs. Yet, efficient representation-level mechanisms for inference-time control in MDLMs remain largely unexplored. To address this gap, we introduce an activati

Lorenzo Sciacca, Alex Minetto, Andrea Nardin, Fabio Dovis

The use of Global Navigation Satellite Systems (GNSS) to increase spacecraft autonomy for orbit determination has gained renewed momentum following the Lunar GNSS Receiver Experiment (LuGRE), which demonstrated feasible onboard GPS and Galileo signal reception and tracking at lunar distances. This work processes in-phase and quadrature (IQ) snapshots collect