October 2025 arXiv papers — page 29

V. Madurga-Favieres, A. Martin-Carrillo, C. M. Diez, F. Fürst

Vela X-1 is a well-studied accreting X-ray pulsar, with a distinctive pulse profile that has been found to be very similar in different observations spread out over decades. On the other hand, significant variations down to the timescale of individual pulses have been observed. The physical mechanisms leading to the energy-resolved pulse profile and its vari

Iancu Andrei, Marius Kloetzer, Cristian Mahulea, Catalin Dosoftei

In this paper, we propose a computationally efficient quadratic programming (QP) approach for generating smooth, $C^1$ continuous paths for mobile robots using piece-wise quadratic Bezier (PWB) curves. Our method explicitly incorporates safety margins within a structured optimization framework, balancing trajectory smoothness and robustness with manageable n

E. Kammoun, T. Kawamuro, K. Murakami, S. Bianchi

We present the first high-resolution X-ray spectrum of NGC 7213 obtained with XRISM/Resolve, supported by simultaneous XMM-Newton, NuSTAR, and SOAR optical data. The XRISM spectrum resolves the neutral Fe\,K$\alpha$ into two components: a narrow core ($\rm FWHM = 650_{-220}^{+240}\,\rm km\,s^{-1}$) consistent with emission at the dust sublimation radius, and

Israel Kellersztein, Mathieu Desgranges, Chiara Daraio

Achieving damage tolerance in composite materials remains a central challenge in materials science. Conventional strategies often rely on filler incorporation or chemical modification, which can limit energy dissipation and constrain structural stability. Here, we leverage the unique morphology of Spirulina trichomes to investigate a reinforcement mechanism

Mario Hernández Vera

Efficient computation of molecular integrals and Hartree-Fock energy remains a central topic in quantum-chemistry algorithm development. Although many sophisticated open-source packages are available, understanding their implementations from first principles can be difficult for students and developers alike. In this work, we present a concise overview and a

Nick Tsipinakis, Panos Parpas, Matthias Voigt

Newton's method may exhibit slower convergence than vanilla Gradient Descent in its initial phase on strongly convex problems. Classical Newton-type multilevel methods mitigate this but, like Gradient Descent, achieve only linear convergence near the minimizer. We introduce an adaptive multilevel Newton-type method with a principled automatic switch to full

Noah Golowich, Allen Liu, Abhishek Shetty

A major problem in the study of large language models is to understand their inherent low-dimensional structure. We introduce an approach to study the low-dimensional structure of language models at a model-agnostic level: as sequential probabilistic models. We first empirically demonstrate that a wide range of modern language models exhibit low-rank structu

Arjun Karuvally, Pichsinee Lertsaroj, Terrence J. Sejnowski, Hava T. Siegelmann

The energy paradigm, exemplified by Hopfield networks, offers a principled framework for memory in neural systems by interpreting dynamics as descent on an energy surface. While powerful for static associative memories, it falls short in modeling sequential memory, where transitions between memories are essential. We introduce the Exponential Dynamic Energy

Shihao Zhou, Yujie Zhu, Chunli Tang, Rui Sun

We demonstrate a pump-probe strobe light spectroscopy for sensitive detection of magneto-optical dynamics in the context of hybrid magnonics. The technique uses a combinatorial microwave-optical pump-probe scheme, leveraging both the high-energy resolution of microwaves and the high-efficiency detection using optical photons. In contrast to conventional stro

James A. Michaelov, Roger P. Levy, Benjamin K. Bergen

We show that across architecture (Transformer vs. Mamba vs. RWKV), training dataset (OpenWebText vs. The Pile), and scale (14 million parameters to 12 billion parameters), autoregressive language models exhibit highly consistent patterns of change in their behavior over the course of pretraining. Based on our analysis of over 1,400 language model checkpoints

Zhiqi Qi, Runxin Zhao, Hanyang Zhuang, Chunxiang Wang

LiDAR-based roadside perception is a cornerstone of advanced Intelligent Transportation Systems (ITS). While considerable research has addressed optimal LiDAR placement for infrastructure, the profound impact of differing LiDAR scanning patterns on perceptual performance remains comparatively under-investigated. The inherent nature of various scanning modes

Christian Klein, Iryna Petrenko, Svetlana Roudenko, Nikola Stoilov

We consider the one dimensional 4th order, or bi-harmonic, nonlinear Schr\"odinger (NLS) equation, namely, $i u_t - \Delta^2 u - 2a \Delta u + |u|^{\alpha} u = 0, ~ x,a \in \R$, $\alpha>0$, and investigate the dynamics of its solutions for various powers of $\alpha$, including the ground state solutions and their perturbations, leading to scattering or blow-

Soni D. Prajapati, Kusum Seervi, Akshay Bhatnagar, Anupam Gupta

We investigate the collective dynamics of active Brownian particles (ABPs) subjected to a steady two-dimensional four-roll-mill flow using numerical simulations. By varying the packing fraction ($\phi$), we uncover a novel flow-induced phase separation (FIPS) that emerges beyond a critical density ($\phi \geq 0.6$). The mean-square displacement (MSD) exhibit

Andrea C. Burgess, Nancy E. Clarke, Shannon L. Fitzpatrick, Melissa A. Huggan

The deduction game may be thought of as a variant on the classical game of cops and robber in which the cops (searchers) aim to capture an invisible robber (evader); each cop is allowed to move at most once, and cops situated on different vertices cannot communicate to co-ordinate their strategy. In this paper, we extend the deduction game to allow each sear

Guido Ivetta, Pietro Palombini, Sofía Martinelli, Marcos J Gomez

The evaluation of societal biases in NLP models is critically hindered by a geo-cultural gap, This leaves regions such as Latin America severely underserved, making it impossible to adequately assess or mitigate the perpetuation of harmful regional stereotypes in language technologies. This paper presents LACES, a stereotype association dataset, for 15 Latin

R. Abbasi, M. Ackermann, J. Adams, S. K. Agarwalla

Neutrinos oscillate over cosmic distances. Using 11.4 years of IceCube data, the flavor composition of the all-sky neutrino flux from 5\,TeV--10\,PeV is studied. We report the first measurement down to the $\mathcal{O}$(TeV) scale using events classified into three flavor-dependent morphologies. The best fit flavor ratio is $f_e:f_{\mu}:f_{\tau}\,=\,0.30:0.3

Akash Gupta, Haiyang Luo, Jie Deng, Adam Burrows

Hydrogen, helium, silicates, and iron are key building blocks of rocky and gas-rich planets, yet their chemical interactions remain poorly constrained. Using first-principles molecular dynamics and thermodynamic integration, we quantify hydrogen and helium partitioning between molten silicate mantles and metallic cores for Earth-to-Neptune-mass planets. Hydr

Aaron I. Plex Sulá, Krishna Keshav, Ashish Adhikari, Romaric A. Mouafo-Tchinda

Mapping habitat suitability, based on factors like host availability and environmental suitability, is a common approach to determining which locations are important for the spread of a species. Mapping habitat connectivity takes geographic analyses a step further, evaluating the potential roles of locations in biological invasions, pandemics, or species con

Aaron Bernstein, Henry Fleischmann, Maximilian Probst Gutenberg, Bernhard Haeupler

We aim to revive Thorup's conjecture [Thorup, WG'92] on the existence of reachability shortcuts with ideal size-diameter tradeoffs. Thorup originally asked whether, given any graph $G=(V,E)$ with $m$ edges, we can add $m^{1+o(1)}$ ``shortcut'' edges $E_+$ from the transitive closure $E^*$ of $G$ so that $\text{dist}_{G_+}(u,v) \leq m^{o(1)}$ for all $(u,v)\i

Steven Carlip

Standard quantum field theory arguments predict an enormous cosmological constant. But what would this mean observationally? For a homogeneous universe the answer is clear, but if the universe is inhomogeneous at the Planck scale, the question becomes more subtle: for a large class of initial data, rapidly expanding and contracting regions coexist and give a

Arsalan Hashemi, Nima Ghafari Cherati, Sadegh Ghaderzadeh, Yanzhou Wang

When two-dimensional atomic layers of different materials are brought into close proximity to form van der Waals (vdW) heterostructures, interactions between adjacent layers significantly influence their physicochemical properties. These effects seem particularly pronounced when the interface exhibits local order and near-perfect structural alignment, leadin

Bernhard Klein

While modern machine learning has transformed numerous application domains, its growing computational demands increasingly constrain scalability and efficiency, particularly on embedded and resource-limited platforms. In practice, neural networks must not only operate efficiently but also provide reliable predictions under distributional shifts or unseen dat

Samuel Alperin

Quantum correlations are the singular, defining resource of quantum information science and metrology, forming the basis of every operational advantage that quantum systems hold over classical ones. Yet exact bounds on these correlations-such as the Lieb-Robinson bound on entanglement propagation and the Heisenberg limit on metrological precision-are known o

Anil Yildiz, Sarah M. Thornton, Carl Hildebrandt, Sreeja Roy-Singh

Assessing scenario coverage is crucial for evaluating the robustness of autonomous agents, yet existing methods rely on expensive human annotations or computationally intensive Large Vision-Language Models (LVLMs). These approaches are impractical for large-scale deployment due to cost and efficiency constraints. To address these shortcomings, we propose SCO

Hanxuan Ye, Zachary Qian, Hongzhe Li

Recent advances in high-resolution sequencing have paved the way for population-scale analysis in single-cell RNA-sequencing (scRNA-seq) data. scRNA-seq data, in particular, have proven to be extremely powerful in profiling a variety of outcomes such as disease and aging. The abundance of scRNA-seq data makes it possible to model each individual's gene expre

R. M. de A. Cruz

Let $M$ be the disk or a compact, connected surface without boundary different from the sphere $S^2$ and the real projective plane $\mathbb{R}P^2$, and let $N$ be a compact, connected surface (possibly with boundary). It is known that the pure braid groups $P_n(M)$ of $M$ are bi-orderable, and, for $n\geq 3$, that the full braid groups $B_n(M)$ of $M$ are no

Aditya Singh, Zihang Wen, Srujananjali Medicherla, Adam Karvonen

OthelloGPT, a transformer trained to predict valid moves in Othello, provides an ideal testbed for interpretability research. The model is complex enough to exhibit rich computational patterns, yet grounded in rule-based game logic that enables meaningful reverse-engineering. We present an automated approach based on decision trees to identify and interpret

Toshihiko Kawano, Amy E. Lovell, Patrick Talou, Lee A. Bernstein

We calculate fission $\gamma$ rays for neutron-induced reactions on $^{239}$Pu with the Hauser-Feshbach fission fragment decay model. By applying the calculated fission $\gamma$ rays as a background contribution, the historical $^{239}$Pu(n,$x$n$\gamma$) reaction cross section data measured by the GEANIE (GErmanium Array for Neutron Induced Excitations) spec

Paul Alexander Bilokon

We present a unifying representation of computation as a two-player game between an \emph{Algorithm} and \emph{Nature}, grounded in domain theory and game theory. The Algorithm produces progressively refined approximations within a Scott domain, while Nature assigns penalties proportional to their distance from the true value. Correctness corresponds to equi

Haoyuan Shi, Christopher J. Mundy, Gregory K. Schenter, Jaehun Chun

Understanding the contact dynamics of nonspherical particles beyond the microscale is crucial for accurately modeling colloidal and granular systems, where shape anisotropy dictates structural organization and transport properties. In this paper, we introduce an energy-conserving contact dynamics framework for arbitrary convex rigid-body particles, integrati

Tong Wu, Humberto Godinez, Vitaliy Gyrya, James M. Hyman

Sparse sensor networks in weather and ocean modeling observe only a small fraction of the system state, which destabilizes standard nudging-based data assimilation. We introduce Interpolated Discrepancy Data Assimilation (IDDA), which modifies how discrepancies enter the governing equations. Rather than adding observations as a forcing term alone, IDDA also

Alfonso Ladino-Rincon, Stephen W. Nesbitt

We introduce Radar DataTree, the first dataset-level framework that extends the WMO FM-301 standard from individual radar volume scans to time-resolved, analysis-ready archives. Weather radar data are among the most scientifically valuable yet structurally underutilized Earth observation datasets. Despite widespread public availability, radar archives remain

Xiutian Zhao, Rochelle Choenni, Rohit Saxena, Ivan Titov

Despite their impressive performance, vision-language models (VLMs) still struggle on culturally situated inputs. To understand how VLMs process culturally grounded information, we study the presence of culture-sensitive neurons, i.e., neurons whose activations show preferential sensitivity to inputs associated with particular cultural contexts. We examine w

Zihan Pengmei, Costas Mavromatis, Zhengyuan Shen, Yunyi Zhang

Chain-of-thought (CoT) supervision can substantially improve transformer performance, yet the mechanisms by which models learn to follow and benefit from CoT remain poorly understood. We investigate these learning dynamics through the lens of grokking by pretraining transformers on symbolic reasoning tasks with tunable algorithmic complexity and controllable

Yinhan He, Wendy Zheng, Yaochen Zhu, Zaiyi Zheng

The verbosity of Chain-of-Thought (CoT) reasoning hinders its mass deployment in efficiency-critical applications. Recently, implicit CoT approaches have emerged, which encode reasoning steps within LLM's hidden embeddings (termed ``implicit reasoning'') rather than explicit tokens. This approach accelerates CoT by reducing the reasoning length and bypassing

Zhexin Zhao, Yiqi Fang, Mevlana Yunus Uludağ, Peter Hommelhoff

Modulating the free-electron wave function with light brings new opportunities to create attosecond electron pulse trains, to probe the quantum coherence of systems with significantly improved spatial resolution, and to generate classical and non-classical states of light with wide tunability. It is therefore crucial to efficiently generate free-electron wav

Yiran Li, Mobin Alipour, Amir Pahlavan

Predicting and controlling the transport of colloids in porous media is essential for a broad range of applications, from drug delivery to contaminant remediation. Chemical gradients are ubiquitous in these environments, arising from reactions, precipitation/dissolution, or salinity contrasts, and can drive particle motion via diffusiophoresis. Yet our curre

Jieyu Zhou

We introduce OrchVis, a multi-agent orchestration framework that visualizes, verifies, and coordinates goal-driven collaboration among LLM-based agents. Through hierarchical goal alignment, task assignment, and conflict resolution, OrchVis enables humans to supervise complex multi-agent workflows without micromanaging each step. The system parses user intent

Melissa A. Huggan, Svenja Huntemann, Brett Stevens

The game Nofil is a two-player combinatorial game in which players take turns marking points of a design such that the set of marked points does not contain a block. Equivalently, we can think of the points as being deleted from the design and points that are on singleton sets can no longer be marked. Every game play eventually results in the design becoming

James A. Michaelov, Catherine Arnett

Language models generally produce grammatical text, but they are more likely to make errors in certain contexts. Drawing on paradigms from psycholinguistics, we carry out a fine-grained analysis of those errors in different syntactic contexts. We demonstrate that by disaggregating over the conditions of carefully constructed datasets and comparing model perf

Joseph E. Marrow

A strong Gelfand pair $(G, H)$ is a finite group $G$ and a subgroup $H$ where every irreducible character of $H$ induces to a multiplicity-free character of $G$. We determine the strong Gelfand pairs of the sporadic groups, their automorphism groups, and their covering groups. We also find the (strong) Gelfand pairs of the generalized Mathieu groups, the Tit

Chams Eddine Mballo, Donggun Lee, Claire J. Tomlin

Traditional reachability methods provide formal guarantees of safety under bounded disturbances. However, they strictly enforce state constraints as inviolable, which can result in overly conservative or infeasible solutions in complex operational scenarios. Many constraints encountered in practice, such as bounds on battery state of charge in electric vehic

Deepon Halder, Alan Saji, Thanmay Jayakumar, Ratish Puduppully

Large Language Models have demonstrated strong performance on many established reasoning benchmarks. However, these benchmarks primarily evaluate structured skills like quantitative problem-solving, leaving a gap in assessing flexible, multifaceted reasoning abilities that are central to human intelligence. These abilities require integrating logical deducti

Shama Sidiqui, Indrakshi Dey

Efficient management of heterogeneous traffic with varying priorities is critical in Wireless Body Area Networks (WBANs). The priority mechanisms embedded in Media Access Control (MAC) schemes largely govern the performance of WBAN in terms of reliability, delay and energy efficiency. Minimizing the delay between packet generation and reception is critical f

Yamin Ben-Shimon, Barak Hirshberg, Yohai Bar-Sinai

Thermodynamic phase transitions, a central concept in physics and chemistry, are typically controlled by an interplay of enthalpic and entropic contributions. In most cases, the estimation of the enthalpy in simulations is straightforward but evaluating the entropy is notoriously hard. As a result, it is common to induce transitions between the metastable st

Yuya Hikima, Akiko Takeda

Stochastic optimization problems with unknown decision-dependent distributions have attracted increasing attention in recent years due to its importance in applications. Since the gradient of the objective function is inaccessible as a result of the unknown distribution, various zeroth-order methods have been developed to solve the problem. However, it remai

Anwar Ahmed Khan, Farid Nait-Abdesselam, Indrakshi Dey

Next Generation Media Access Control (NGMA) techniques have been designed to support diverse applications with heterogeneous priorities. In industrial cyber-physical systems (CPS), the number of connected devices and systems is expected to grow significantly, demanding dependable and prompt network services. In this work, we present a novel scheme, Dynamic F

Joel Frank Huarayo Quispe, Lilian Berton, Didier Vega-Oliveros

Link prediction in bipartite graphs is crucial for applications like recommendation systems and failure detection, yet it is less studied than in monopartite graphs. Contrastive methods struggle with inefficient and biased negative sampling, while non-contrastive approaches rely solely on positive samples. Existing models perform well in transductive setting

Zesheng Liu, YoungHyun Koo, Maryam Rahnemoonfar

We introduce KAN-GCN, a fast and accurate emulator for ice sheet modeling that places a Kolmogorov-Arnold Network (KAN) as a feature-wise calibrator before graph convolution networks (GCNs). The KAN front end applies learnable one-dimensional warps and a linear mixing step, improving feature conditioning and nonlinear encoding without increasing message-pass

Massimo Fornasier, Lukang Sun, Rachel Ward

In this work, we take a step towards understanding overdamped Langevin dynamics for the minimization of a general class of objective functions $\mathcal{L}$. We establish well-posedness and regularity of the law $\rho_t$ of the process through novel a priori estimates, and, very importantly, we characterize the large-time behavior of $\rho_t$ under truly min

Emily I. Mason, Kara L. Kniezewski

The study of solar active regions (ARs) is of central importance to a range of fundamental science, as well as the practical applications of space weather. Active region emergence and life cycles are two areas of particular interest, yet the lack of consistent full-Sun observations has made long-term studies of active regions difficult. Here, we present resu

Seth Benzell, Kyle Myers

An increasingly large number of experiments study the labor productivity effects of automation technologies such as generative algorithms. A popular question in these experiments relates to inequality: does the technology increase output more for high- or low-skill workers? The answer is often used to anticipate the distributional effects of the technology a

Yukun Guo, An-Lun Wu, Tristan T. Hormel, Liqin Gao

Geographic atrophy (GA) is a key biomarker of dry age-related macular degeneration (AMD) traditionally identified through color fundus photography. Hyper-transmission defects (hyperTDs), a feature highly correlated with GA, have recently gained prominence in optical coherence tomography (OCT) research. OCT offers cross-sectional imaging of the retina, leadin

Zhicheng Wang, Theo Käufer, Khemraj Shukla, Michael Triantafyllou

We present a body-free simulation framework for three-dimensional turbulent cylinder wakes, in which the upstream cylinder is not explicitly resolved. Instead, the incompressible Navier--Stokes equations are solved in a simplified rectangular domain, and the inflow is prescribed using velocity profiles extracted from experimental measurements or pre-computed

Ivan Dimitrov, Khoa Nguyen

We study two categories of ${U}(\mathfrak h)$-free $\mathfrak{sl}(m|n)$-modules of total rank 2: $\mathcal{M}_{\mathfrak{sl}(m|n)}(2)$, whose objects are free of rank 2 over ${U}(\mathfrak h)$ which are not necessarily $\mathbb Z_2$-graded, and $\mathcal{M}_{\mathfrak{sl}(m|n)}(1|1)$, whose objects are supermodules with even and odd parts each isomorphic to

Elizabeth Lin, Jonah Ghebremichael, William Enck, Yasemin Acar

Software supply chains, while providing immense economic and software development value, are only as strong as their weakest link. Over the past several years, there has been an exponential increase in cyberattacks specifically targeting vulnerable links in critical software supply chains. These attacks disrupt the day-to-day functioning and threaten the sec

Hossein R. Nowdeh, Jie Ji, Xiaolong Ma, Fatemeh Afghah

In multimodal learning, dominant modalities often overshadow others, limiting generalization. We propose Modality-Aware Sharpness-Aware Minimization (M-SAM), a model-agnostic framework that applies to many modalities and supports early and late fusion scenarios. In every iteration, M-SAM in three steps optimizes learning. \textbf{First, it identifies the dom

Biyi Fang, Truong Vo, Kripa Rajshekhar, Diego Klabjan

Traditional topic models such as Latent Dirichlet Allocation (LDA) have been widely used to uncover latent structures in text corpora, but they often struggle to integrate auxiliary information such as metadata, user attributes, or document labels. These limitations restrict their expressiveness, personalization, and interpretability. To address this, we pro

G. A. Bougas, G. C. Katsimiga, S. Mossman, P. Engels

We report the experimental observation of vector extensions of Peregrine solitons in highly particle-imbalanced, pairwise immiscible three-component repulsive Bose-Einstein condensates (BECs). The possibility of an effectively attractive character of the minority components is established by constructing a generalized reduction scheme for an imbalanced N-com

Fabio Bertolotti, Kyle Myers, Wei Yang Tham

We develop a method to estimate producers' productivity beliefs when output quantities and input prices are unobservable, and we use it to evaluate the market for science. Our model of researchers' labor supply shows how their willingness to pay for inputs reveals their productivity beliefs. We estimate the model's parameters using data from a nationally rep

Akash Unnikrishnan, Vinod Narayanan

Despite extensive experimental evidence of turbulence in Hagen Poiseuille flow, linear stability analysis has not yet confirmed its instability. One challenge is the singularity introduced by the term 1/r in the center of the pipe, which complicates traditional stability approaches. In this study, we explore a global stability analysis using a meshless frame

Laurent Massoulié

In this article we consider the graph alignment problem from the perspective of high-dimensional statistics: we aim to estimate an unknown permutation $\pi^*$ from the observation of two correlated random adjacency matrices $A_1$, $A_2$. We establish the following computational thresholds. For $A_1$, $A_2$ the adjacency matrices of two correlated Erd\H{o}s-R

P. Chang, S. Ramezanpour, A. Helmy

The growing complexity of integrated photonics necessitates compact, low-power devices that transcend traditional, material-centric design approaches. In this study, we harness non-Hermitian physics to uncover novel properties of coupled plasmonic waveguide modes exhibiting exceptional point (EP) degeneracy. Our hybrid plasmonic waveguide architecture, capab

Shahab Ramezanpour, Amr Helmy

As photonic systems progress toward enhanced miniaturization, dynamic reconfigurability, and improved energy efficiency, a central challenge endures: the accurate and independent control of optical losses and resonant properties on scalable, CMOS-compatible platforms. To address this challenge, we present a hybrid plasmonic dimer that functions in a non-Herm

Alessandro Santini, Stefano Barison, Filippo Vicentini

We introduce a hybrid classical-quantum algorithm to compute dynamical correlation functions and excitation spectra in many-body quantum systems, with a focus on molecular systems. The method combines classical preparation of a perturbed ground state with short-time quantum evolution of product states sampled from it. The resulting quantum samples define an

Kunal Mittal

We show equivalences between several high-dimensional problems in extremal combinatorics and parallel repetition of multiplayer (multiprover) games over large answer alphabets. This extends the forbidden-subgraph technique, previously studied by Verbitsky (Theoretical Computer Science 1996), Feige and Verbitsy (Combinatorica 2002), and H\k{a}z{\l}a , Holenst

Vik Pant, Eric Yu

Modern socio-technical systems increasingly involve multi-stakeholder environments where actors simultaneously cooperate and compete. These coopetitive relationships exhibit dynamic trust evolution based on observed behavior over repeated interactions. While conceptual modeling languages like i* represent trust relationships qualitatively, they lack computat

Shahab Ramezanpour, Amr Helmy

Current progress in electro-optical modulation within silicon integrated photonics, driven by the unique capabilities of advanced functional materials, has led to significant improvements in device performance. However, inherent constraints in dimensionality and tunability still pose challenges for further innovation. In this work, we propose a strategy that

Michal Stary, Julien Gaubil, Ayush Tewari, Vincent Sitzmann

Multi-view transformers such as DUSt3R are revolutionizing 3D vision by solving 3D tasks in a feed-forward manner. However, contrary to previous optimization-based pipelines, the inner mechanisms of multi-view transformers are unclear. Their black-box nature makes further improvements beyond data scaling challenging and complicates usage in safety- and relia

Mikołaj Czarnecki, Michał Korniak, Oskar Skibski, Piotr Skowron

We consider the problem of payoff division in indivisible coalitional games, where the value of the grand coalition is a natural number. This number represents a certain quantity of indivisible objects, such as parliamentary seats, kidney exchanges, or top features contributing to the outcome of a machine learning model. The goal of this paper is to propose

Bianca Y. S. Ishikawa, José F. Fontanari

The Inspection Game is the canonical model for the strategic conflict between law enforcement (inspectors) and citizens (potential criminals). Its classical Mixed-Strategy Nash Equilibrium (MSNE) is afflicted by a paradox: the equilibrium crime rate is independent of both the penalty size ($p$) and the crime gain ($g$), undermining the efficacy of deterrence

Prabhanjana Ghuriki, S. Chanti

This study develops a personalized accessibility framework that integrates exponential decay functions with user-customizable weighting systems. The framework enables real-time, personalized urban evaluation based on individual priorities and lifestyle requirements. The methodology employs grid-based discretization and a two-stage computational architecture

Qiucheng Wu, Handong Zhao, Zhixin Shu, Jing Shi

Although recent text-to-video generative models are getting more capable of following external camera controls, imposed by either text descriptions or camera trajectories, they still struggle to generalize to unconventional camera motions, which is crucial in creating truly original and artistic videos. The challenge lies in the difficulty of finding suffici

Robert Ferydouni, Daniel D. Spiegel

We aim to give a self-contained and detailed yet simplified account of the foundations of the theory of double operator integrals, in order to provide an accessible entry point to the theory. We make two new contributions to these foundations: (1) a new proof of the existence of the product of two projection-valued measures, which allows for the definition o

Alejandro de Haro García, Joaquín J. Torres

In this work, we examine the conditions for the emergence of chimera-like states in Ising systems. We study an Ising chain with periodic boundaries in contact with a thermal bath at temperature T, that induces stochastic changes in spin variables. To capture the non-locality needed for chimera formation, we introduce a model setup with non-local diffusion of

H Mhatre, M Vyas, A Mittal

Traffic congestion is becoming a challenge in the rapidly growing urban cities, resulting in increasing delays and inefficiencies within urban transportation systems. To address this issue a comprehensive methodology is designed to optimize traffic flow and minimize delays. The framework is structured with three primary components: (a) vehicle detection, (b)

Gerard van Belle, Tabetha Boyajian, Michelle Creech-Eakman, John Elliott

The lunar surface is a compelling location for large, distributed optical facilities, with significant advantages over orbital facilities for high spatial resolution astrophysics. The serious development of mission concepts is timely because of the confluence of multiple compelling factors. Lunar access technology is maturing rapidly, in the form of both US-

Samane Raji, Ignacio Trujillo, Fernando Buitrago, Giulia Golini

Thanks to new advances in astronomical imaging, we can now routinely explore disk galaxy profiles about two magnitudes deeper than the data available 20 years ago. In this regard, it is an opportune time to reevaluate the past classifications of different surface brightness Types. In this paper, we explore the stellar mass profiles of a sample of disk galaxi

Jason Godfrey, Trisha Banerjee

This study applies an optimized XGBoost regression model to estimate district-level expenditures on high-dosage tutoring from incomplete administrative data. The COVID-19 pandemic caused unprecedented learning loss, with K-12 students losing up to half a grade level in certain subjects. To address this, the federal government allocated \$190 billion in relie

Xincheng Cao, Haochong Chen, Levent Guvenc, Bilin Aksun-Guvenc

With the rapid growth of autonomous vehicle technologies, effective path-tracking control has become a critical component in ensuring safety and efficiency in complex traffic scenarios. When a high level decision making agent generates a collision free path, a robust low level controller is required to precisely follow this trajectory. However, connected aut

Pierre Gosselin, Aïleen Lotz

We present a unified field-theoretic framework for the dynamics of activity and connectivity in interacting neuronal systems. Building upon previous works, where a field approach to activity--connectivity dynamics, formation of collective states and effective fields of collective states were successively introduced, the present paper synthesizes and extends

Hongshun Yao, Jingu Xie, Xuanqiang Zhao, Chengkai Zhu

Monogamy of entanglement, which limits how entanglement can be shared among multiple parties, is a fundamental feature underpinning the privacy of quantum communication. In this work, we introduce a novel operational framework to quantify the unshareability or unextendibility of entanglement via a virtual state-extension task. The virtual extension cost is d

Raúl A. Briceño, Maxwell T. Hansen, Andrew W. Jackura, Robert G. Edwards

This work presents a lattice quantum chromodynamics (QCD) determination of $\pi\pi\pi$ scattering amplitudes for the isospin-2 channel with angular momentum and parity $J^{P} = 1^+$. The calculation is performed using unphysically heavy light-quark masses, corresponding to a pion mass of $m_{\pi} \approx 400$~MeV, for which the $\rho$ meson manifests as a na

María Angélica Benítez, Rocío Candela Ceballos, Karina Del Valle Molina, Sofía Mundo Araujo

The growing integration of artificial intelligence (AI) into human cognition raises a fundamental question: does AI merely improve efficiency, or does it alter how we think? This study experimentally tested whether short-term exposure to narrow AI tools enhances core cognitive abilities or simply optimizes task performance. Thirty young adults completed stan

H-W S. Huang, S. Agrawal, D. Bhattacharya, H. G. Xing

Better wall plug efficiency of deep-ultraviolet light emitting diodes (DUV-LEDs) requires simultaneous low resistivity p-type and n-type contacts, which is a challenging problem. In this study, the co-optimization of p-InGaN and n- AlGaN contacts for DUV LEDs are investigated. We find that using a thin 7%InGaN cap is effective in achieving ohmic p-contacts w

Dilara Aktas, Ozgur B. Akan

Molecular communication (MC) enables biocompatible and energy-efficient information transfer through chemical signaling, forming a foundational paradigm for emerging applications in the Internet of Nano Things (IoNT) and intrabody healthcare systems. The realization of this vision critically depends on developing advanced receiver architectures that merge na

Shakeel Abdulkareem, Bora Yimenicioglu, Khartik Uppalapati, Aneesh Gudipati

Rapid triage of suspected stroke needs accurate, bedside-deployable tools; EEG is promising but underused at first contact. We present an adaptive multitask EEG classifier that converts 32-channel signals to power spectral density features (Welch), uses a recurrent-convolutional network (GRU-TCN) to predict stroke type (healthy, ischemic, hemorrhagic), hemis

Siddharth Verma, Alankar Alankar

High-energy materials (HEMs) are critical for propulsion and defense domains, yet their discovery remains constrained by experimental data and restricted access to testing facilities. This work presents a novel approach toward high-energy molecules by combining Long Short-Term Memory (LSTM) networks for molecular generation and Attentive Graph Neural Network

Sehi L'Yi, John Conroy, Priya Misner, David Kouřil

Analysis of genomics data is central to nearly all areas of modern biology. Despite significant progress in artificial intelligence (AI) and computational methods, these technologies require significant human oversight to generate novel and reliable biological insights. Consequently, the genomics community has developed a substantial number of diverse visual

Claire Dalmazzone, Mathieu Guigue, Boris Popov, Stefano Russo

We present the results obtained by applying, in real-time, a correction method to precisely synchronize a time base generated from a free-running atomic clock with the Coordinated Universal Time (UTC). The method uses the Global Navigation Satellite System (GNSS) signals to have regular time comparisons between the atomic clock generated time base and the GP

Daniele L. V. dos Santos, Thiago B. Pereira, Carlos Eduardo G. R. Alves, Richard J. M. G. Tello

This paper examines the feasibility of utilizing lightweight body landmark detection for recognizing isolated signs in Brazilian Sign Language (LIBRAS). Although the use of skeleton-image representation has enabled substantial improvements in recognition performance, the use of OpenPose for landmark extraction hindered time performance. In a preliminary inve

Sidharth Rai, Rahul Harsha Cheppally, Benjamin Vail, Keziban Yalçın Dokumacı

Maturity estimation of fruits and vegetables is a critical task for agricultural automation, directly impacting yield prediction and robotic harvesting. Current deep learning approaches predominantly treat maturity as a discrete classification problem (e.g., unripe, ripe, overripe). This rigid formulation, however, fundamentally conflicts with the continuous

Olawale Salaudeen, Haoran Zhang, Kumail Alhamoud, Sara Beery

Benchmarks for out-of-distribution (OOD) generalization frequently show a strong positive correlation between in-distribution (ID) and OOD accuracy across models, termed "accuracy-on-the-line." This pattern is often taken to imply that spurious correlations - correlations that improve ID but reduce OOD performance - are rare in practice. We find that this po

Marc T. Pudelko

Classical studies of the Fibonacci sequence focus on its periodicity modulo $m$ (the Pisano periods) with canonical initialization. We investigate instead the complete periodic structure arising from all $m^2$ possible initializations in $(\mathbb{Z}/m\mathbb{Z})^2$. We discover perfect mirror symmetry between the Fibonacci recurrence $a_n = a_{n-1} + a_{n-2

Daniela Portillo del Valle

A random walk with echoed steps (RWES) is a process $\{\tilde{S}_n\}_{n\geq1}=\{\tilde{X}_1+\cdots+\tilde{X}_n\}_{n\geq1}$ that inserts memory and echo into an ordinary random walk (ORW) with i.i.d. steps, $X_1+\cdots+X_n$. The RWES is defined recursively as follows. Let $\tilde{S}_1=X_1$. With probability $1-p$, the $n$-th increment of the RWES follows that

Lucas Z. Brito, Ryan P. Cabeen, David H. Laidlaw

Diffusion magnetic resonance imaging (MRI) has revealed important insights into white matter microstructure, but its application to gray matter remains comparatively less explored. Here, we investigate whether global patterns of gray-matter microstructure can be captured through neurite orientation dispersion and density imaging (NODDI) and whether such patt

Guido D'Amico, Alexandre Refregier, Leonardo Senatore, Pierre Zhang

We analyze the Dark Energy Survey (DES) Year 3 data using predictions from the Effective Field Theory of Large-Scale Structure (EFTofLSS). Specifically, we fit three two-point observables (3$\times$2pt), galaxy clustering, galaxy-galaxy lensing, and cosmic shear, using the one-loop expressions for the projected angular correlation functions. We validate our

Jingqing Wang, Jiaxing Shang, Rong Xu, Fei Hao

Fake news detection has been a long-standing research focus in social networks. Recent studies suggest that incorporating sentiment information from both news content and user comments can enhance detection performance. However, existing approaches typically treat sentiment features as auxiliary signals, overlooking role differentiation, that is, the same se

David R. Miller, Ilaria Caiazzo, Jeremy Heyl, Harvey B. Richer

The initial-final mass relation (IFMR) links a star's birth mass to the mass of its white dwarf (WD) remnant, providing key constraints on stellar evolution. Open clusters offer the most straightforward way to empirically determine the IFMR, as their well-defined ages allow for direct progenitor lifetime estimates. We construct the most comprehensive open cl

Abhishek Chaudhary

We study an optimal control problem for the stochastic wave equation driven by affine multiplicative noise, formulated as a stochastic linear-quadratic (SLQ) problem. By applying a stochastic Pontryagin's maximum principle, we characterize the optimal state-control pair via a coupled forward-backward SPDE system. We propose an implementable discretization us