November 2025 arXiv papers — page 128

Reginald Zhiyan Chen, Heng-Sheng Chang, Prashant G. Mehta

Hidden Markov Models (HMMs) are fundamental for modeling sequential data, yet learning their parameters from observations remains challenging. Classical methods like the Baum-Welch algorithm are computationally intensive and prone to local optima, while modern spectral algorithms offer provable guarantees but may produce probability outputs outside valid ran

Farid Diaf, Abderrahim Mesbah, Nathaniel Sagman

Motivated by work of various authors on domination between surface group representations, harmonic maps, and $3$-dimensional anti-de Sitter geometry, we study a new domination problem between non-Fuchsian representations of closed surface groups. We solve the problem for representations that admit branched harmonic immersions, and we show that, outside of th

Theophilus Gera, Amit Sharma

This paper refines the relationship between centrally quasi-morphic and centrally morphic modules, correcting earlier equivalences and extending them to a broader module-theoretic framework. We prove that if a module \(M\) is image-projective and generates its kernels, then the following are equivalent: \(M\) is centrally morphic, \(M\) is centrally quasi-mo

Nicolas Fayard, Marc Pirlot, Alexis Tsoukiàs

This paper proposes a new framework for evaluating capability sets by incorporating individual preferences over the diversity of accessible options. Building on the Capability Approach, we introduce a compromise method that balances between the notions of negative and positive freedom, effectively capturing the intrinsic and instrumental values of diverse ch

Cynthia Maldonado, Francisco Nettel, Pedro A. Sánchez

Relations between the kinematical tensors (the expansion, the shear, and the vorticity) and the polarization modes of gravitational waves are studied within the context of metric theories of gravity by considering freely falling test particles. After analyzing exact relations, we consider slowly moving particles under the influence of a weak gravitational fi

Rishi Singhal, Jung-Eun Kim

Layer Normalization (LayerNorm) is one of the fundamental components in transformers that stabilizes training and improves optimization. In recent times, Pre-LayerNorm transformers have become the preferred choice over Post-LayerNorm transformers due to their stable gradient flow. However, the impact of LayerNorm on learning and memorization across these arc

Rahul Krishnan, Ashley Samuelson, Emily Yao, Ethan Cecchetti

Non-Interactive Zero Knowledge (NIZK) proofs, such as zkSNARKS, let one prove knowledge of private data without revealing it or interacting with a verifier. While existing tooling focuses on specifying the predicate to be proven, real-world applications optimize predicate definitions to minimize proof generation overhead, but must correspondingly transform p

Reuben Drogin, Charles K Smart

We prove delocalization for the Anderson model on an infinite regular tree (or Cayley graph or Bethe lattice) at low disorder. This extends earlier results of Klein and Aizenman--Warzel by filling in the previously missing parts of the spectrum. Our argument generalizes to any disorder with small fourth moment and sufficiently regular density. We prove conti

Seyed Hadi Mirfarshbafan, Christoph Studer

Massive multiuser multiple-input multiple-output (MIMO) and millimeter-wave (mmWave) communication are key physical layer technologies in future wireless systems. Their deployment, however, is expected to incur excessive baseband processing hardware cost and power consumption. Beamspace processing leverages the channel sparsity at mmWave frequencies to reduc

Emmanuel Asiedu Brempong, Mohammed Alewi Hassen, MohamedElfatih MohamedKhair, Vusumuzi Dube

Accurate precipitation estimation is critical for hydrological applications, especially in the Global South where ground-based observation networks are sparse and forecasting skill is limited. Existing satellite-based precipitation products often rely on the longwave infrared channel alone or are calibrated with data that can introduce significant errors, pa

Benjamin Yu, Vincenzo Lordi, Daniel Schwalbe-Koda

Machine learning interatomic potentials (MLIPs) balance high accuracy and lower costs compared to density functional theory calculations, but their performance often depends on the size and diversity of training datasets. Large datasets improve model accuracy and generalization but are computationally expensive to produce and train on, while smaller datasets

Haosong Peng, Hao Li, Yalun Dai, Yushi Lan

General 3D foundation models have started to lead the trend of unifying diverse vision tasks, yet most assume RGB-only inputs and ignore readily available geometric cues (e.g., camera intrinsics, poses, and depth maps). To address this issue, we introduce OmniVGGT, a novel framework that can effectively benefit from an arbitrary number of auxiliary geometric

Navin McGinnis

We study the interplay between crossing symmetry and entanglement in $2 \to 2$ scattering within local quantum field theories that possess an $SU(N)$ global symmetry. In particular, we recast scattering amplitudes of fixed helicity as quantum operations on the Hilbert space of internal quantum numbers, where the external states play the role of qudits. The e

Gijs Vermariën, Tommaso Grassi, Marie Van de Sande, Serena Viti

Since the first observations of interstellar molecules, astrochemical simulations have been employed to model and understand its formation and destruction path- ways. With the advent of high-resolution telescopes such as JWST and ALMA, the number of detected molecules has increased significantly, thereby creating a need for increasingly complex chemical reac

Liangyu Chen, Zhengyuan Du, Wei Song

We use symmetries to define a new class of operators and compute their correlation functions in the $J\bar{T}$-deformed conformal field theory on the plane, following the strategy developed in [1]. The symmetry algebra of the deformed theory consists of a local Virasoro-Kac-Moody algebra in the left-moving sector and a non-local counterpart in the right-movi

Yen-Ju Chen, Chun-Yuan Cheng, Tien-Dat Pham, Tzu-An Chen

Quantum fluctuation plays a key role in the parametric down-conversion in the Langevin regime. In this paper, we report the experimental realization of optical parametric down-conversion in the Langevin regime on a chip. By precisely controlling the loss inherently tied to fluctuation, we observe the asymmetric Hong-Ou-Mandel dip - a hallmark of quantum fluc

Huijie Liu, Shuhao Cui, Haoxiang Cao, Shuai Ma

Innovative visual stylization is a cornerstone of artistic creation, yet generating novel and consistent visual styles remains a significant challenge. Existing generative approaches typically rely on lengthy textual prompts, reference images, or parameter-efficient fine-tuning to guide style-aware image generation, but often struggle with style consistency,

Lingzhi Wang, Vinod Yegneswaran, Xinyi Shi, Ziyu Li

Provenance-based intrusion detection is an increasingly popular application of graphical machine learning in cybersecurity, where system activities are modeled as provenance graphs to capture causality and correlations among potentially malicious actions. Graph Neural Networks (GNNs) have demonstrated strong performance in this setting. However, traditional

Mónica Clapp, Benedetta Pellacci, Angela Pistoia

Let $(M, g)$ be a compact Riemannian manifold with boundary. The Yamabe problem concerning the existence of a metric conformally equivalent to $g$ having constant scalar curvature on $M$ and constant mean curvature on its boundary is equivalent, in analytic terms, to finding a positive solution to a nonlinear boundary-value problem with critical growth. Whil

Yongxin Shi, Jiapeng Wang, Zeyu Shan, Dezhi Peng

Recent multimodal large language models (MLLMs) still struggle with long document understanding due to two fundamental challenges: information interference from abundant irrelevant content, and the quadratic computational cost of Transformer-based architectures. Existing approaches primarily fall into two categories: token compression, which sacrifices fine-

Suzanne Schlich

We study a generalization of the $BQ$-conditions, introduced by Bowditch and further developed by Tan-Wong-Zhang, for representations of the free group of rank two into isometry groups of Gromov-hyperbolic spaces. We show the existence of an explicit constant $K_\delta$, depending only on the hyperbolicity constant $\delta$ of the space, such that the hyperb

Navin McGinnis

We study scattering of particles which obey an $SU(N)$ global symmetry through the lens of quantum computation and quantum algorithms. We show that for scattering between particles which transform in the fundamental or anti-fundamental representations, i.e. qudits, all 2-2 scattering amplitudes can be constructed from only three quantum gates. Further, for a

Jack Allsop, Daniel Kotlar, Ian Wanless

A Young diagram is \emph{Latin} if there is an assignment of integers to its cells so that each row $i$ of length $l_i$ is populated by the numbers $1,\ldots,l_i$, and the numbers in each column are distinct. A Young diagram is called \emph{wide} if any subdiagram, formed by a subset of its rows, dominates its conjugate. Chow et al. [Advances in Applied Math

Isabela Albuquerque, Ira Ktena, Olivia Wiles, Ivana Kajić

Despite advances in generation quality, current text-to-image (T2I) models often lack diversity, generating homogeneous outputs. This work introduces a framework to address the need for robust diversity evaluation in T2I models. Our framework systematically assesses diversity by evaluating individual concepts and their relevant factors of variation. Key cont

Natasha Johnson

Though the concept of genre has been a subject of discussion for millennia, the relatively recent emergence of genre fiction has added a new layer to this ongoing conversation. While more traditional perspectives on genre have emphasized form, contemporary scholarship has invoked both formal and institutional characteristics in its taxonomy of genre, genre f

Gianmarco Caldini

We prove that every mod 2 integral cycle $T$ in a Riemannian manifold $\mathcal{M}$ can be approximated in flat norm by a cycle which is a smooth submanifold $\Sigma$ of nearly the same area, up to a singular set of codimension 3; in addition, this estimate on the singular set can be refined depending on the codimension of the cycle. Moreover, if the mod 2 h

Stefano Maria Iacus, Giuseppe Porro

Using 2.6 billion geolocated social-media posts (2014-2022) and a fine-tuned generative language model, we construct county-level indicators of life satisfaction and happiness for the United States. We document an apparent rural-urban paradox: rural counties express higher life satisfaction while urban counties exhibit greater happiness. We reconcile this by

Eve Shaw

In this paper, we extend the result of arXiv:2409.13662 by showing that the set on which every pseudotangent is obtained on a Lipschitz curve can be any compact, uniformly disconnected set in Euclidean space which admits any Lipschitz capture. We do not obtain a characterization of such sets however, indeed we leave open the very strong question of whether o

Deniz Yilmaz, Liangyu Wu, Julia Gonski, Dylan Rankin

Drift chambers have long been central to collider tracking, but future machines like a Higgs factory motivate higher granularity and cluster counting for particle ID, posing new data processing challenges. Machine learning (ML) at the "edge", or in cell-level readout, can dramatically reduce the off-detector data rate for high-granularity drift chambers by p

Wenqing Wang, Haosen Yang, Josef Kittler, Xiatian Zhu

Reconstructing dynamic humans interacting with real-world environments from monocular videos is an important and challenging task. Despite considerable progress in 4D neural rendering, existing approaches either model dynamic scenes holistically or model scenes and backgrounds separately aim to introduce parametric human priors. However, these approaches eit

Jiajun Wang

In this paper, we prove the restriction estimates for 2D surfaces S:= {(xi1, xi2, xi1^3 +/- xi2^3) : (xi1, xi2) in [0,1]^2} by reducing to Wang-Wu's result on the perturbed paraboloid and to the results on the perturbed hyperboloid obtained by Buschenhenke, M\"uller, and Vargas, as well as by Guo and Oh. The method is based on the rescaling technique develop

A. Acharyya, F. Aharonian, H. Ashkar, M. Backes

Microquasars have emerged as promising candidates to explain the cosmic-ray flux at petaelectronvolt energies. LHAASO observations revealed V4641~Sgr as the most extreme example so far. Using $\approx$100~h of H.E.S.S. data, we performed a spectro-morphological study of the gamma-ray emission around V4641~Sgr. We employed HI and dedicated CO observations of

Bhavay Luthra, N. J. Upadhyay

The precise calculation of alpha-induced neutron-emission ($\alpha$,n) reaction rates is fundamental to understanding nucleosynthesis in diverse stellar environments. This study investigates the nuclear reaction rates for various non-resonant alpha-induced neutron-emission reactions by employing analytical, theoretical, and computational methods. We have ado

Giordano Viviani, Richard I. Anderson

We present a novel framework for accurately reconstructing radial velocity (RV) curves of classical Cepheids (Cepheids) from sparsely sampled time-series data suitable for application in large spectroscopic surveys. The framework provides a set of priors for the principal components of RV curves established based on high-precision measurements from the VELOC

Yuval Frid, Liron Barak

We investigate photon--pion discrimination in regimes where electromagnetic showers overlap at the scale of calorimeter granularity. Using full detector simulations with fine-grained calorimeter segmentation of approximately $0.025\times0.025$ in $(\eta,\phi)$, we benchmark three approaches: boosted decision trees (BDTs) on shower-shape variables, dense neur

Jose Berengueres

Repetitive strain injury (RSI) affects roughly one in five computer users and remains largely unresolved despite decades of ergonomic mouse redesign. All such devices share a fundamental limitation: they still require fine-motor motion to operate. This work investigates whether predictive, AI-assisted input can reduce that motion by replacing physical pointi

Øyvind Solberg, Kent B. Vashaw, Sarah Witherspoon

We initiate a program aimed at classifying thick ideals, Balmer spectra, and submodule categories of various stable categories of bimodules and modules for finite dimensional selfinjective algebras, and at clarifying the relationship between the universal Balmer support and the Hochschild cohomology support. In this paper, we focus mostly on the case of a un

Bruno Martelli

We know from previous work with Italiano and Migliorini that there exists some hyperbolic 5-manifold that fibers over the circle. Here we build one example where the monodromy is a "pseudo-Anosov homeomorphism" of the 4-dimensional fiber, in a way that is surprisingly similar to the familiar and beautiful two-dimensional picture of Nielsen and Thurston for s

H. Thankful Cromartie, Matthew Kerr, Scott M. Ransom, Paul S. Ray

We present 15 years of Nan\c{c}ay and Green Bank radio telescope timing observations for PSR J1231$-$1411. This millisecond pulsar is a primary science target for the Neutron Star Interior Composition Explorer telescope (NICER, which discovered its X-ray pulsations), has accumulated near-continuous $\gamma$-ray data since the Fermi-Large Area Telescope's lau

Vijay Kumar, Martin Siegele-Brown, Matthew Aylett, Sebastian Weidt

We investigate the surface flashover voltage threshold for SiO$_2$, SiN, and AlN thin films over micrometre scale lengths. Furthermore, we test the effects of different etching chemistries on SiO$_2$ layers. We find that there is little significant difference between untreated SiO$_2$ samples and those that have been etched with hydrogen fluoride or Transene

Dario Beraldo, Massimo Pippi

We categorify the localized intersection product on arithmetic schemes defined by Kato--Saito in \cite{katosaito04}. As an application, we prove a generalization of Bloch conductor conjecture.

Paul Schwarzbach, Andrea Jung

Radio-based localization systems conventionally require stationary reference points (e.g. anchors) with precisely surveyed positions, making deployment time-consuming and costly. This paper presents an empirical evaluation of collaborative self-calibration for Ultra-Wideband (UWB) networks, extending a discrete Bayesian approach based on grid-based uncertain

Maksim E. Eren, Dorianis M. Perez

Artificial intelligence (AI) is reshaping how research is conceived, conducted, and communicated across fields from chemistry to biomedicine. This commentary examines how AI is transforming the research workflow. AI systems now help researchers manage the information deluge, filtering the literature, surfacing cross-disciplinary links for ideas and collabora

Egor Pakhomov, Erik Nijkamp, Caiming Xiong

We introduce a comprehensive benchmark for conversational memory evaluation containing 75,336 question-answer pairs across diverse categories including user facts, assistant recall, abstention, preferences, temporal changes, and implicit connections. While existing benchmarks have advanced the field, our work addresses fundamental challenges in statistical p

Jooheon Yoo, Michael Boyle, Nils Deppe

Accurate modeling of gravitational waveforms from compact binary coalescences remains central to gravitational-wave (GW) astronomy. Post-Newtonian (PN) approximations capture the early inspiral dynamics analytically but break down near merger, while numerical relativity (NR) provides the accurate yet computationally expensive waveforms over limited parameter

Wei Tao, Ju Kang, Wenxiu Yang, Yiyuan Niu

Explaining how competing species coexist remains a central question in ecology. The well-known competitive exclusion principle (CEP) states that two species competing for the same resource cannot stably coexist, and more generally, that the number of consumer species is bounded by the number of resource species at steady state. However, the remarkable specie

Srikant Panda, Avinash Rai

Large Language Models (LLMs) are commonly evaluated for robustness against paraphrased or semantically equivalent jailbreak prompts, yet little attention has been paid to linguistic variation as an attack surface. In this work, we systematically study how linguistic styles such as fear or curiosity can reframe harmful intent and elicit unsafe responses from

Wei Li, Renshan Zhang, Rui Shao, Zhijian Fang

Vision-Language-Action (VLA) models have advanced in robotic manipulation, yet practical deployment remains hindered by two key limitations: 1) perceptual redundancy, where irrelevant visual inputs are processed inefficiently, and 2) superficial instruction-vision alignment, which hampers semantic grounding of actions. In this paper, we propose SemanticVLA,

Félix Foutel-Rodier, Emmanuel Schertzer

We consider a class of Crump-Mode-Jagers processes with interaction, constructed by removing a newly born offspring with a probability that depends on the age structure of the population at its birth time. We prove a law of large numbers for the tree structure of the process in a local topology, and show how this result condenses several other limit theorems

Josep Domingo-Ferrer

In several jurisdictions, the regulatory framework on the release and sharing of personal data is being extended to machine learning (ML). The implicit assumption is that disclosing a trained ML model entails a privacy risk for any personal data used in training comparable to directly releasing those data. However, given a trained model, it is necessary to m

Dong-Shan Jian, Xiang Li, Chen-Xu Yan, Hui-Wen Zheng

Olympiad-level physics problem-solving significantly challenges both humans and artificial intelligence (AI), as it requires integrating appropriate modeling, application of physical principles, and precise calculation within long reasoning processes. In this paper, we introduce LOCA (LOgical Chain Augmentation), an AI agent framework designed for complex ph

Ryan O'Donnell, Noah G. Singer

We study the Kaufman--Oppenheim coset complexes (STOC 2018, Eur. J. Comb. 2023), which have an elementary and strongly explicit description. Answering an open question of Kaufman, Oppenheim, and Weinberger (STOC 2025), we show that they support sparse direct-product testers in the low soundness regime. Our proof relies on the HDX characterization of agreemen

Moncef Ghazel, Inès Saihi, Walid Taamallah

The notion of Kan extendable subcategories was initially introduced to define the category of compactly generated fibrewise topological spaces over a T1 base space and to establish its cartesian closure. In this paper, we show that the same framework can likewise be applied to define the category of compactly generated strongly Hausdorff locales and to prove

Ana Vieira, Thais Nascimento, Juan Cruz, Willer Costa

In recent years, the study of the $T$-space of central polynomials of an algebra $A$ has become an object of great interest in the PI-theory. Such interest has been extended to the context of algebras with additional structures. The main goal of this paper is to present information about the central graded codimensions and the central graded cocharacters of

Jun Liu

We present verifiable conditions for synthesizing a single smooth Lyapunov function that certifies both asymptotic stability and safety under bounded controls. These sufficient conditions ensure the strict compatibility of a control barrier function (CBF) and a control Lyapunov function (CLF) on the exact safe set certified by the barrier. An explicit smooth

Alexander Logunov, Dmitrii Zakharov

We show that for every $n \in \mathbb N$ there is a collection of points $p_1, \ldots, p_n$ and lines $\ell_1, \ldots, \ell_n$ in the unit square such that for any $i$ we have $p_i \in \ell_i$ and the distance from $p_i$ to any other line $\ell_j$ is at least $c n^{\gamma-1}$ for some universal constants $c, \gamma>0$. This is better than a trivial construct

Steven A. Silber, Mikko Karttunen

We present SymPhas 2.0, a major update of the compile-time symbolic algebra simulation framework SymPhas for phase-field and reaction-diffusion models. This release introduces significant expansions and enhancements that enable the definition of a phase-field model directly from the free-energy functional via compile-time evaluated functional differentiation

Yun He, Wenzhe Li, Hejia Zhang, Songlin Li

Recent progress in large language models (LLMs) has led to impressive performance on a range of tasks, yet advanced instruction following (IF)-especially for complex, multi-turn, and system-prompted instructions-remains a significant challenge. Rigorous evaluation and effective training for such capabilities are hindered by the lack of high-quality, human-an

L. H. Ford, Brian Fu

This paper will deal with isolated laser pulses, those which last for a finite time interval and whose envelope function is strictly zero outside of this interval. We numerically calculate the Fourier transform of this function and study its asymptotic behavior at high frequencies. This work is motivated by recent results on the probability distributions of

Reza Pirmoradian, M. Hossein Bek-Khoshnevis, Sadaf Ebadi, M. Reza Tanhayi

Nonlocal interactions are known to generate volume-law entanglement entropy. However, their deeper impact on the fine structure of quantum correlations remains a key open question. In this work, we explore a bosonic nonlocal field theory, examining correlation measures beyond entanglement entropy, namely, mutual information and tripartite information. Using

Daryl Noupa Yongueng, Hamidou Tembine

Normalization is a key point in transformer training . In Dynamic Tanh (DyT), the author demonstrated that Tanh can be used as an alternative layer normalization (LN) and confirmed the effectiveness of the idea. But Tanh itself faces orthogonality, linearity and distortion problems. Due to that, his proposition cannot be reliable. So we propose a Holonorm (h

Mateo Cárdenes Wuttig, Andrew J. Millis

A large variety of materials can be approximately described by means of spin-1/2 Heisenberg ladders. Here, the Density Matrix Renormalization Group (DMRG) algorithm together with a previously established numerical self-consistent mean-field approximation is used to investigate the magnetic properties of spin ladders coupled in a second dimension. The full gr

Georgios Chalkiadakis, Charilaos Akasiadis, Gerasimos Koresis, Stergios Plataniotis

This paper provides a comprehensive review of mainly GNN, DRL, and PTM methods with a focus on their potential incorporation in strategic multiagent settings. We draw interest in (i) ML methods currently utilized for uncovering unknown model structures adaptable to the task of strategic opponent modeling, and (ii) the integration of these methods with Game T

Michele Ronco, Damien Delforge, Wiebke S. Jäger, Christina Corbane

Subnational location data of disaster events are critical for risk assessment and disaster risk reduction. Disaster databases such as EM-DAT often report locations in unstructured textual form, with inconsistent granularity or spelling, that make it difficult to integrate with spatial datasets. We present a fully automated LLM-assisted workflow that processe

Jun Kitagawa, Cecilia Mikat

We develop a new framework for branched transport between probability measures which are allowed to vary in time. This framework can be used to model problems where the underlying transportation network displays a branched structure, but the source and target mass distributions can change cyclically over time, such as road networks or circulatory systems. We

Simona Boyadzhiyska, Shagnik Das, Thomas Lesgourgues, Kalina Petrova

The odd-Ramsey number $r_{{\text odd}}(n,H)$ of a graph $H$, as introduced by Alon in his work on graph-codes, is the minimum number of colours needed to edge-colour $K_n$ so that every copy of $H$ intersects some colour class in an odd number of edges. In this paper, we determine the odd-Ramsey number of Hamilton cycles up to a small multiplicative factor,

François Clément, Linhang Huang, Woorim Lee, Cole Smidt

The construction of low-discrepancy sets, used for uniform sampling and numerical integration, has recently seen great improvements based on optimization and machine learning techniques. However, these methods are computationally expensive, often requiring days of computation or access to GPU clusters. We show that simple gradient descent-based techniques al

F. S. Benanti, A. Valenti

Let $F$ be a field of characteristic zero and let $ \mathcal V^* $ be a variety of associative $F$-algebras with involution *. Associated to $ \mathcal V^* $ are three sequences: the sequence of \(*\)-codimensions \( c^{*}_n(\mathcal V^*) \), the sequence of central \(*\)-codimensions \( c^{*,z}_n(\mathcal V^*) \) and the sequence of proper central \(*\)-cod

Stanislav Selitskiy

We propose loss function week enforcement of the velocity relations between time-series points in the Kinematic-Informed artificial Neural Networks (KINN) for long-term stock prediction. Problems of the series volatility, Out-of-Distribution (OOD) test data, and outliers in training data are addressed by (Artificial Neural Networks) ANN's learning not only f

K. Xhani, G. Del Pace, N. Grani, D. Hernández-Rajkov

We combine numerical and experimental approaches to study how impurities affect the maximum superflow in an annular Bose-Einstein condensate. By tuning the impurity density, we achieve precise control over the stability of persistent currents which increases with the impurity number. In the unstable regime, the complex vortex motion within the impurity lands

Yunkai Zhang, Qiang Zhang, Feng Lin, Ruizhong Qiu

Optimizing recommender systems for objectives beyond accuracy, such as diversity, novelty, and personalization, is crucial for long-term user satisfaction. To this end, industrial practitioners have accumulated vast amounts of structured domain knowledge, which we term human priors (e.g., item taxonomies, temporal patterns). This knowledge is typically appli

Khwahish Kushwah, Caio V. P. de Brito, Gabriel S Denicol

We derive relativistic resistive magnetohydrodynamics for a two-component ultrarelativistic plasma directly from kinetic theory. Starting with the Boltzmann--Vlasov equation and using the 14-moment approximation in the Landau frame, we obtain coupled evolution equations for the charge diffusion four-current and the shear-stress tensor. Benchmarking against t

Thierry Appourchaux

The Luminosity Oscillations Imager (LOI) of the Variability of Solar Irradiance and Gravity Oscillations (VIRGO) instrument aboard the SoHO mission has been operating for almost the past 30 years. I report on the effect of solar activity upon mode frequencies, linewidths, height and energy rate. I report on the variation as a function of frequency for freque

Matías G. Gonzalez, Johannes Reuther

The tetratrillium lattice has recently been proposed as responsible for the dynamical properties observed in the $S=1$ langbeinite compound K$_2$Ni$_2$(SO$_4$)$_3$. Here, we study in detail the classical spin liquid properties of this lattice of tri-coordinated tetrahedra using classical Monte Carlo and large-$N$ theory calculations. In the large-$N$ limit,

Oded Schlesinger, Amirhossein Farzam, J. Matias Di Martino, Guillermo Sapiro

While Vision Transformers (ViT) have demonstrated remarkable performance across diverse tasks, their computational demands are substantial, scaling quadratically with the number of processed tokens. Compact attention representations, reflecting token interaction distributions, can guide early detection and reduction of less salient tokens prior to attention

Clemens Werthmann, Iurii Karpenko, Pasi Huovinen

In multi-fluid description of heavy-ion collisions, the primary scatterings and particle production are described in terms of interaction between fluids, so called friction. These friction terms can be derived from kinetic theory, but they are not unique. We compare different approaches to derive the friction terms, introduce a new ``charge transfer" frictio

Tamara Koletic, Rachel Pillsworth, Ralph E. Pudritz

There is abundant observational evidence for the hierarchical, interconnected nature of filaments in the interstellar medium (ISM) extending from galactic down to sub-parsec scales. New JWST images of NGC 628 in particular, show clusters forming along the two spiral arms of this galaxy. In this paper we investigate filament and cluster properties in an NGC 6

Tejas Sudharshan Mathai, Anisa V. Prasad, Xinya Wang, Praveen T. S. Balamuralikrishna

Type 2 Diabetes Mellitus (T2DM) is a chronic metabolic disease that affects millions of people worldwide. Early detection is crucial as it can alter pancreas function through morphological changes and increased deposition of ectopic fat, eventually leading to organ damage. While studies have shown an association between T2DM and pancreas volume and fat conte

Corey Ford, Elizabeth Wilson, Shuoyang Zheng, Gabriel Vigliensoni

This third international workshop on explainable AI for the Arts (XAIxArts) brought together a community of researchers in HCI, Interaction Design, AI, explainable AI (XAI), and digital arts to explore the role of XAI for the Arts. Workshop held at the 17th ACM Conference on Creativity and Cognition (C&C 2025), online.

Ruxi Deng, Wenxuan Bao, Tianxin Wei, Jingrui He

Pretrained VLMs exhibit strong zero-shot classification capabilities, but their predictions degrade significantly under common image corruptions. To improve robustness, many test-time adaptation (TTA) methods adopt positive data augmentation (PDA), which generates multiple views of each test sample to reduce prediction variance. However, these methods suffer

Feng Wu, Jingzhe Guo, Tian Xia, Linghang Kong

Quantum computing is transitioning from laboratory research to industrial deployment, yet significant challenges persist: system scalability and performance, fabrication yields, and the advancement of algorithms and applications. We emphasize that in building quantum computers -- spanning quantum chips, system integration, instruction sets, algorithms, and m

Paul Ruelloux, Christian Bongiorno, Damien Challet

We enhance the Universal Portfolio Shrinkage Approximator (UPSA) of Kelly et al. (2023) by making it more robust with respect to estimation noise and covariate shift. UPSA optimizes the realized Sharpe ratio using a relatively small calibration window, leveraging ridge penalties and cross-validation to yield better portfolios. Yet, it still suffers from the

Ivan Cheltsov, Antoine Pinardin, Yuri Prokhorov

We show that the alternating groups $\mathfrak{A}_5$ and $\mathfrak{A}_6$ are the only finite simple non-abelian subgroups of the group of birational selfmaps of the real three-dimensional projective space.

Moncef Derouich, Saleh Qutub

Context: The scattering polarization of the infrared (IR) triplet of neutral oxygen (O\,\textsc{i}) near 777\,nm provides a powerful diagnostic of solar atmospheric conditions. However, interpreting such polarization requires a rigorous treatment of isotropic depolarizing collisions between O\,\textsc{i} atoms and neutral hydrogen. Aims: We aim to investigat

Çağrı Eser, Zeynep Sonat Baltacı, Emre Akbaş, Sinan Kalkan

Imbalance in classification tasks is commonly quantified by the cardinalities of examples across classes. This, however, disregards the presence of redundant examples and inherent differences in the learning difficulties of classes. Alternatively, one can use complex measures such as training loss and uncertainty, which, however, depend on training a machine

Sascha H. Hauck, Vladimir M. Stojanovic

In view of the compelling need for coherent atom transport as a prerequisite for a variety of emerging quantum technologies, we investigate such transport on the example of an adjustable family of two-dimensional optical lattices [L. Tarruell {\em et al.}, Nature (London) {\bf 483}, 302 (2012)] that includes square, honeycomb, dimerized, and 1D-chains lattic

Soumya Sankar, Xingkai Cheng, Xinyu Chen, Xizhi Fu

Crystalline symmetries determine the linear and nonlinear response of materials to external stimuli such as mechanical pressure and electromagnetic fields, governing phenomena such as piezoelectricity, optical activity, and multiple wave mixing with wide ranging technological applications. Altermagnets present a new class of materials with magnetic crystalli

Atta ur Rahman, Ao-xiang Liu, M. Y. Abd-Rabbou, Cong-feng Qiao

We prove a simple dynamical law for excitation-preserving interactions: the {sum of local Wigner negativities} is upper-bounded by a fixed budget set by the initially excited state. For the single-excitation sector of the XY model (and its beam-splitter analogue), this convexity bound equals the negativity of the seed state and is saturated only when the exc

David Hume, John M. Mackay

We strengthen the connection between the Ahlfors-regular (AR) conformal dimension Confdim$(Z)$ of a compact AR metric space $Z$ and a certain critical exponent of the Poincar\'e profiles $p_{\Lambda}$ of its hyperbolic cone $X$ in the sense of Bonk--Schramm. We prove that the two values are equal in two situations: firstly, when $Z$ is a product $C\times [0,

Lorenzo Calibbi, Jiangyi Yi

We investigate the phenomenological implications of the bosons associated with the $SU(2)_F$ subgroup in a simple and realistic $U(2)_F$ flavor model. While the Nambu-Goldstone boson of the $U(1)_F$ factor behaves as a standard QCD axion (an axiflavon) with suppressed flavor-violating couplings, the three degrees of freedom from $SU(2)_F$ have not been studi

Hanting Yan, Pan Mu, Shiqi Zhang, Yuchao Zhu

Tropical Cyclone (TC) estimation aims to accurately estimate various TC attributes in real time. However, distribution shifts arising from the complex and dynamic nature of TC environmental fields, such as varying geographical conditions and seasonal changes, present significant challenges to reliable estimation. Most existing methods rely on multi-modal fus

Maharshi Pathak, SungKu Kang, Vanessa C. Whittem, Katherine Bassett

The expansion of renewable electricity generation, growing demands due to electrification, greater prevalence of working from home, and increasing frequency and severity of extreme weather events, will place new demands on the electric supply and distribution grid. Broader adoption of demand response programs (DRPs) for the residential sector may help meet t

Giovanni Cabass, Digvijay Wadekar, Matias Zaldarriaga, Zihan Zhou

Matched filtering for signal detection in noisy data requires template banks that capture variation in signal waveforms while minimizing computational cost. Dimensionality reduction of signal waveforms can be important for building efficient template banks. In various domains of physics, dimensionality reduction is very commonly performed using linear method

Yunzhe Xu, Zhuosheng Zhang, Zhe Liu

While prompt optimization has emerged as a critical technique for enhancing language model performance, existing approaches primarily focus on elicitation-based strategies that search for optimal prompts to activate models' capabilities. These methods exhibit fundamental limitations when addressing knowledge-intensive tasks, as they operate within static kno

Almond Kiruthu Murimi

This research paper investigates how machine learning-driven data replication strategies can enhance fault tolerance in large-scale distributed systems. Traditional replication methods, which rely on static configurations, often struggle to adapt to dynamic workloads and unexpected failures, leading to inefficient resource utilization and prolonged downtime.

Megh Bahadur KC, Ziqi Song, Keunhyun Park, Keith Christensen

Despite the growing recognition of the importance of inclusive transportation policies nationwide, there is still a gap, as the existing transportation models often fail to capture the unique travel behavior of people with disabilities. This research study focuses on understanding the mode choice behavior of individuals with travel-limited disabilities and c

Yujin Tong

We study the space of $A_\infty$-natural transformations between braiding functors acting on the Fukaya category associated to the Coulomb branch $\mathcal{M}(\bullet,1)$ of the $\mathfrak{sl}_2$ quiver gauge theory. We compute all cohomologically distinct $A_\infty$-natural transformations $\mathrm{Nat}(\mathrm{id}, \mathrm{id})$ and $\mathrm{Nat}(\mathrm{i

Simon Donike, Cesar Aybar, Julio Contreras, Luis Gómez-Chova

We present OpenSR-SRGAN, an open and modular framework for single-image super-resolution in Earth Observation. The software provides a unified implementation of SRGAN-style models that is easy to configure, extend, and apply to multispectral satellite data such as Sentinel-2. Instead of requiring users to modify model code, OpenSR-SRGAN exposes generators, d

Isaac M. Lopez, Rio Schillmoeller

We introduce a dynamical energy functional on compact ancient asymptotically Ricci-flat Ricci flows with modest decay using limits of conjugate heat flows. This functional satisfies a steady Ricci breather-type rigidity and provides an upper bound for the ordinary $\lambda$-functional while retaining many of its properties. In addition, motivated by work of

Zihan Gao, Yifei Xu, Jacob Thebault-Spieker

Large language models (LLMs) have been widely evaluated on macro-scale geographic tasks, such as global factual recall, event summarization, and regional reasoning. Yet, their ability to handle hyper-local knowledge remains poorly understood. This gap is increasingly consequential as real-world applications, from civic platforms to community journalism, dema