November 2025 arXiv papers — page 45

E. Alfonso-Pita, D. Baxter, E. Behnke, J. Corbett

The Scintillating Bubble Chamber (SBC) Collaboration is designing a new generation of low background, noble liquid bubble chamber experiments with sub-keV nuclear recoil threshold. These experiments combine the electronic recoil blindness of a bubble chamber with the energy resolution of noble liquid scintillation, and maintain electron recoil discrimination

Saif M. Mohammad

Factor analysis studies have shown that the primary dimensions of word meaning are Valence (V), Arousal (A), and Dominance (D). Existing lexicons such as the NRC VAD Lexicon, published in 2018, include VAD association ratings for words. Here, we present a complement to it, which has human ratings of valence, arousal, and dominance for 10k English Multiword E

Fabian Barras, Andreas Aspaas, Einat Aharonov, François Renard

In the context of global climate change, geological materials are increasingly destabilized by water flow and infiltration. We study the creeping dynamics of a densely monitored landslide in Western Norway to decipher the role of fluid flow in destabilizing this landslide. In {\AA}knes, approximately 50 million cubic meter of rock mass continuously creeps ov

Wenyuan Li, David Nadler, Vivek Shende

In exact symplectic manifolds whose Liouville flow is gradientlike for a proper Morse function, one can associate conic microsheaves to eventually conic exact Lagrangians. Here we study how this 'microsheaf quantization' interacts with composition of Lagrangian correspondences. In particular: these operations commute when the composition is embedded. As an i

Jiaxin Li, Shanjun Mao

Identifying key driver genes governing biological processes such as development and disease progression remains a challenge. While existing methods can reconstruct cellular trajectories or infer static gene regulatory networks (GRNs), they often fail to quantify time-resolved regulatory effects within specific temporal windows. Here, we present Time-varying

Hao Wu, Bocong Chen, Guanghui Zhang, Hongwei Liu

We address an open problem posed by Chen-Cheng-Qi (IEEE Trans.\ Inf.\ Theory, 2025): can the decoding of binary sum-rank-metric codes $\SR(C_1,C_2)$ with $2\times2$ matrix blocks be reduced entirely to decoding the constituent Hamming-metric codes $C_1$ and $C_2$ without the additional requirement $d_1\ge\tfrac{2}{3}d_{\mathrm{sr}}$ used in their fast decode

Andrew S. Cassidy, Guillaume Garreau, Jay Sivagnaname, Mike Grassi

We show for invertible problems that transform data from a source domain (for example, Logic Condition Tables (LCTs)) to a destination domain (for example, Hardware Description Language (HDL) code), an approach of using Large Language Models (LLMs) as a lossless encoder from source to destination followed by as a lossless decoder back to the source, comparab

Debin Meng, Chen Jin, Zheng Gao, Yanran Li

Image diversity remains a fundamental challenge for text-to-image diffusion models. Low-diversity generation often leads to repetitive outputs, increasing sampling redundancy and hindering both creative exploration and downstream applications. A key factor is the tendency of diffusion models to collapse toward strong modes in the learned distribution. Existi

Divyansh Chaurasia, Manoj Daram, Roshan Kumar, Nihal Thukarama Rao

We present a case study for the calibration of Low-cost air-quality (LCAQ) CO sensors from one of the largest multi-site-multi-season-multi-sensor-multi-pollutant mobile air-quality monitoring network deployments in India. LCAQ sensors have been shown to play a critical role in the establishment of dense, expansive air-quality monitoring networks and combati

Rahul Gulia, Feyisayo Favour Popoola, Ashish Sheikh

Reliable modeling of block error rate in vehicle-to-everything wireless networks is critical for designing robust communication systems under dynamic mobility and diverse channel conditions. Traditional machine learning approaches, such as deep neural networks, achieve high predictive accuracy but lack interpretability and impose significant computational co

Marzi Heidari, Hanping Zhang, Yuhong Guo

The challenge of learning with noisy labels is significant in machine learning, as it can severely degrade the performance of prediction models if not addressed properly. This paper introduces a novel framework that conceptualizes noisy label correction as a reinforcement learning (RL) problem. The proposed approach, Reinforcement Learning for Noisy Label Co

R. Negrello, M. Romagnoni, A. Sytov, N. Canale

We present an investigation into beam steering and radiation emission by sub-GeV electrons traversing bent silicon crystals. Using 855, 600, and 300~MeV electron beams at the Mainz Microtron (MAMI), we explored orientational coherent effects and particle dynamics in a 15~$μ$m-thick crystal bent along the (111) planes. Combined experimental and simulation ana

Jihan Yao, Achin Kulshrestha, Nathalie Rauschmayr, Reed Roberts

As VLMs are deployed in safety-critical applications, their ability to abstain from answering when uncertain becomes crucial for reliability, especially in Scene Text Visual Question Answering (STVQA) tasks. For example, OCR errors like misreading "50 mph" as "60 mph" could cause severe traffic accidents. This leads us to ask: Can VLMs know when they can't s

Y. A. Rouzoumka, E. Terreaux, C. Morisseau, J. -P. Ovarlez

We investigate complex-valued Variational AutoEncoders (CVAE) for radar Out-Of-Distribution (OOD) detection in complex radar environments. We proposed several detection metrics: the reconstruction error of CVAE (CVAE-MSE), the latent-based scores (Mahalanobis, Kullback-Leibler divergence (KLD)), and compared their performance against the classical ANMF-Tyler

Aoxi Chen, Xinlin Chen, Siyuan Rao, Hui An

The dual-fiber optical trap, owing to its high sensitivity and facile miniaturization, holds significant actual application value in fields such as high-precision metrology of mechanical quantities and biological manipulation. The positional stability of the trapped particle is pivotal to system performance, directly setting the measurement noise floor and o

Sibo Ma, Julian Nyarko

Data attribution seeks to trace model behavior back to the training examples that shaped it, enabling debugging, auditing, and data valuation at scale. Classical influence-function methods offer a principled foundation but remain impractical for modern networks because they require expensive backpropagation or Hessian inversion at inference. We propose a dat

Guanming Liang

We present a novel candidate for cold dark matter consisting of condensed Cooper pairs in a theory of interacting fermions with broken chiral symmetry. Establishing the thermal history from the early radiation era to the present, the fermions are shown to behave like standard radiation at high temperatures, but then experience a critical era decaying faster

Olivia Liebman, Jonathan B. Curtis, Emily Been, Prineha Narang

We investigate the emergence of an exciton condensate and associated collective modes in a bilayer configuration of $\text{MnBi}_2\text{Te}_4$, an antiferromagnetic topological insulator and van der Waals material, recognized for hosting axion physics. Utilizing a minimal low-energy Hamiltonian for the two layer system which is gapped by the intrinsic N\'eel

Christopher S. Goodrich, Gabriel Nakhl

We investigate a class of variable growth nonlocal differential equations of Kirchhoff-type having the general form \(-A\!\left(\int_0^1 b(1-s)\,\big(u(s)\big)^{p(s)}\,ds\right)\,u''(t) = λ\,f(t,u(t))\) for \(t\in(0,1)\), where \(A\) is a possibly sign-changing function. Our analysis is carried out in the variable-exponent Lebesgue space \(L^{p(\cdot

Simon Hacks

"Train While You Fight" (TWYF) advocates for continuous learning that occurs during operations, not just before or after. This paper examines the technical requirements that advanced distributed learning (ADL) platforms must meet to support TWYF, and how existing software engineering patterns can fulfill these requirements. Using a Design Science Res

Emma Daggett, Christian M. Lange, Bennet Windt, Arshag Danageozian

The preparation and control of quantum states lie at the heart of quantum information science (QIS). Recent advances in solid-state quantum emitters (QEs) and nanophotonics have transformed the landscape of quantum photonic technologies, enabling scalable generation of quantum states of light and matter. A new frontier in solid-state quantum photonics is the

Tadele Mengesha, Miriam Abbate

The goal of this paper is to study the $L^p$-solvability of the strongly-coupled nonlocal system \[ \mathbb{L} \mathbf{u} (\mathbf{x}) + λ\mathbf{u}(\mathbf{x})= \mathbf{f}(\mathbf{x}) \quad \text{in $\mathbb{R}^{d}$ } \] where $\mathbb{L}$ is a linear nonlocal coupled vector-valued operator associated with a kernel $K$ comparable to $|\mathbf{y}|^{-(d+2s)}$

E. Gatuzz, J. ZuHone, J. S. Sanders, A. Fabian

We present a systematic comparison between {\it XMM-Newton} velocity maps of the Virgo, Centaurus, Ophiuchus and A3266 clusters and synthetic velocity maps generated from the Illustris TNG-300 simulations. Our goal is to constrain the physical conditions and dynamical states of the intracluster medium (ICM) through a data-driven approach. We employ a Siamese

Kanaya Malakar, Albert Countryman, Bulbul Chakraborty

Force transmission at large length scales is crucial for such biological functions as cell motility and morphogenesis. The networks that transmit these forces are malleable, patterned by active forces generated at the microscale by biological motors. In this paper we explore a simple model of a non-linear fiber network which has only two modes of deformation

Panayiotis Danassis, Naman Goel

The rapid proliferation of Large Language Models (LLMs) has revolutionized AI-assisted code generation. This rapid development of LLMs has outpaced our ability to properly benchmark them. Prevailing benchmarks emphasize unit-test pass rates and syntactic correctness. Such metrics understate the difficulty of many real-world problems that require planning, op

Horacio Salomone, Nicolás Grandi

We test on Saturn's rings whether the Hurst exponent is a "robust" observable, in the sense that it returns consistent values for different observations of the same object. We calculate the exponent of the series corresponding to the optical depth as a function of the radius, as obtained from the grayscale value of Cassini pictures, as well as fr

I. Morel, D. Schaerer, R. Marques-Chaves, N. Prantzos

JWST observations have revealed rare galaxies with UV spectra exhibiting intense lines of nitrogen, indicative of super-solar N/O abundances at low metallicity. To better understand these enigmatic objects and provide new constraints on proposed scenarios, we have undertaken a systematic search for galaxies with UV emission lines of nitrogen. Using public JW

Vladimir M. Krasnov

Josephson junctions are key elements in superconducting electronics. The most common type is the overlap (sandwich-type) junction, formed by vertically stacking two superconducting layers. In contrast, planar junctions are fabricated without overlap, at the edge of two superconducting films within a single plane. This geometric distinction has a significant

Roman Kochnev, Waleed Khalid, Tolgay Atinc Uzun, Xi Zhang

Building self-improving AI systems remains a fundamental challenge in the AI domain. We present NNGPT, an open-source framework that turns a large language model (LLM) into a self-improving AutoML engine for neural network development, primarily for computer vision. Unlike previous frameworks, NNGPT extends the dataset of neural networks by generating new mo

Max J. Ruckriegel, Christoph Adam, Rebecca Bolt, Chuyao Tong

Bilayer graphene is a maturing material platform for gate-defined quantum dots that hosts long-lived spin and valley states. Implementing solid-state qubits in bilayer graphene requires a fundamental understanding of such confined electronic systems. In particular, states of two and three carriers, for which the exchange interaction between particles plays a

Huu Tuong Tu, Ha Viet Khanh, Tran Tien Dat, Vu Huan

Mispronunciation Detection and Diagnosis (MDD) is crucial for language learning and speech therapy. Unlike conventional methods that require scoring models or training phoneme-level models, we propose a novel training-free framework that leverages retrieval techniques with a pretrained Automatic Speech Recognition model. Our method avoids phoneme-specific mo

Reiji Okada, Francesco Buscemi

Virtual maps allow the simulation of quantum operations by combining physical processes with classical post-processing. Recent work on virtual unitary covariant broadcasting has shown, however, that such maps remain impractical for observable estimation tasks due to poor sample efficiency. Here we investigate whether relaxing the symmetry requirements can im

Zhihao Chen, Chun Sum Brian Pang, Meng Yang, Yuxin Wang

The sensitivity of low dimensional superconductors to fluctuations gives rise to emergent behaviors beyond the conventional Bardeen Cooper Schrieffer framework. Anisotropy is one such manifestation, often linked to spatially modulated electronic states and unconventional pairing mechanisms. Pronounced in plane anisotropy recently reported at KTaO3 based oxid

Zhichen Pu, Xiaojie Wu, Yuanheng Wang, Cheng Fan

Calculating excited-state gradients and derivative couplings using time-dependent density functional theory (TDDFT) remains a computationally demanding task. An efficient variant, TDDFT with resolution of the identity and a minimal auxiliary basis (TDDFT-ris), has been developed to accelerate excitation energy calculations. However, the formulation and imple

Ilia S. Dedov, Andrey A. Katanin, Evgeny A. Stepanov

We consider the electronic and magnetic properties of the Hubbard model on a square lattice with the Fermi level near van Hove singularity and the ratio of the next-nearest-neighbor and nearest-neighbor hoppings $t'/t=-0.45$, which favours the ferromagnetic instability. We find, that a self-consistent consideration of the ferromagnetic fluctuations withi

Lorenzo Luperi Baglini, Marcello Mamino, Rosario Mennuni, Mariaclara Ragosta

Given an ordered structure, we study a natural way to extend the order to preorders on type spaces. For definably complete, linearly ordered structures, we give a characterisation of the preorder on the space of 1-types. We apply these results to the divisibility preorder on the space of ultrafilters on the set of natural numbers, giving an independence resu

Jiyue Tao, Tongsheng Shen, Dexin Zhao, Feitian Zhang

The target defense problem (TDP) for unmanned surface vehicles (USVs) concerns intercepting an adversarial USV before it breaches a designated target region, using one or more defending USVs. A particularly challenging scenario arises when the attacker exhibits superior maneuverability compared to the defenders, significantly complicating effective intercept

Vladimir Lazić, Zhixin Xie

We show that for pseudoeffective projective pairs the termination of one sequence of flips implies the termination of all flips, assuming a natural conjecture on the behaviour of the Nakayama-Zariski decomposition under the operations of a Minimal Model Program.

Z. Ossoulian, T. Golanbari, Kh. Saaidi

The latest CMB data from ACT DR6, combined with Planck, DESI, and BICEP/Keck, indicate a slight upward shift in the scalar spectral index, placing several previously favored inflationary models under tension. We study an inflationary scenario within the framework of $f(R, T)$ gravity, featuring a nonminimal matter-curvature coupling, where the inflaton is a

C. R. Das

Strange quark matter (SQM) is considered a possible true ground state of QCD at high densities. This idea motivates research on exotic compact objects and certain cosmic-ray phenomena. For instance, the remnant HESS J1731-347 contains a low-mass neutron star, about $0.77^{+0.20}_{-0.17}$ $M_\odot$ and $10.4^{+0.86}_{-0.78}$ km in radius, making it a strong c

Weizhi Liu, Xi Chen, Zekun Jiang, Liang Zhao

Knee osteoarthritis (KOA) affects more than 600 million individuals globally and is associated with significant pain, functional impairment, and disability. While personalized multidisciplinary interventions have the potential to slow disease progression and enhance quality of life, they typically require substantial medical resources and expertise, making t

Linqi Zhou, Mathias Parger, Ayaan Haque, Jiaming Song

We propose Terminal Velocity Matching (TVM), a generalization of flow matching that enables high-fidelity one- and few-step generative modeling. TVM models the transition between any two diffusion timesteps and regularizes its behavior at its terminal time rather than at the initial time. We prove that TVM provides an upper bound on the $2$-Wasserstein dista

Stevenson Bolivar, Rong Chen, Yuefeng Han

This paper proposes a new Threshold Tensor Factor Model in Canonical Polyadic (CP) form for tensor time series. By integrating a thresholding autoregressive structure for the latent factor process into the tensor factor model in CP form, the model captures regime-switching dynamics in the latent factor processes while retaining the parsimony and interpretabi

Pierre Godfard

We prove the rigidity of Witten-Reshetikhin-Turaev $\mathrm{SU}(2)$ and $\mathrm{SO}(3)$ quantum representations of mapping class groups at all prime levels for closed surfaces of genus at least $7$. The proof relies on Ocneanu rigidity of modular categories and harmonic representatives in Hodge theory.

Wenzhang Du

Recent machine learning papers often report 1-2 percentage point improvements from a single run on a benchmark. These gains are highly sensitive to random seeds, data ordering, and implementation details, yet are rarely accompanied by uncertainty estimates or significance tests. It is therefore unclear when a reported +1-2% reflects a real algorithmic advanc

Xie Chen

The Landau paradigm is a central dogma for understanding phase and phase transitions in condensed matter systems, yet for decades it has been known that a variety of quantum phases exist beyond the framework. Is there a more general framework that provides a systematic understanding of phase and phase transitions in quantum many-body systems? Recent developm

Minhui Zhang, Prahar Ijner, Yoav Wald, Elliot Creager

Large Language Models (LLMs) often exhibit systematic errors on specific subsets of data, known as error slices. For instance, a slice can correspond to a certain demographic, where a model does poorly in identifying toxic comments regarding that demographic. Identifying error slices is crucial to understanding and improving models, but it is also challengin

Inti Cruz Diaz

Let $f$ be a pseudo-Anosov homeomorphism on a closed, oriented surface. We give an effective construction of Markov partitions for $f$ based on a simple combinatorial criterion deciding when an immersed graph bounds a Markov partition. This yields an explicit algorithm: from a point $z$ at the intersection of stable and unstable separatrices of a singularity

Sen Zhang, Lingjun Xiong, Yipie Liu, Brian L. Mark

Quantum computing has made substantial progress in recent years; however, its scalability remains constrained on a monolithic quantum processing unit (QPU). Distributed quantum computing (DQC) offers a pathway by coordinating multiple QPUs to execute large-scale circuits. Yet, DQC still faces practical barriers, as its realization depends on advances in hard

Ashutosh Dumka, Raghupathi Kandiboina, Skylar Knickerbocker, Neal Hawkins

Seat belt use remains one of the most effective measures for reducing vehicle occupant fatalities and injuries. Yet, seat-belt compliance across different locales demands far more granular data than traditional, roadside surveys can provide. These surveys are spatially sparse, temporally intermittent, and costly to administer, often providing coarse-grained

A. Sanny, L. Labadie, S. Gross, K. Barjot

The NOTT visitor instrument at the VLTI will characterize hot exozodiacal dust and young Jupiter-like planets at the water snowline via L' band nulling interferometry. The beam combination will be achieved by a four-telescope integrated optics beam combiner (IOBC) that fulfills specific requirements. Our goal was to manufacture the mid-infrared IOBC for NOTT

Ilya Kudrov, Vitaly Bornyakov, Vladimir Goy

We present new results on properties of $SU(2)$ QCD in lattice regularization. Our main goal is to find the transition line confinement - deconfinement in $\mu - T$ plane. We compute the Polyakov loop and the string tension to determine this line.

Dmitry A. Ryndyk, Olga Guskova, Marina Saphiannikova

In this study, we apply, for the first time, the fully atomistic force field approach to modeling light-induced deformations of azo-polymers, thereby establishing a relationship between macroscopic parameters and the microscopic molecular architecture of the used azo-polymers. We apply an orientation potential to mimic the illumination of the sample, in whic

Maureen Herbert, Katie Sun, Angelica Lim, Yasaman Etesam

The rapid advancement of large language models (LLMs) and their growing integration into daily life underscore the importance of evaluating and ensuring their fairness. In this work, we examine fairness within the domain of emotional theory of mind, investigating whether LLMs exhibit gender biases when presented with a description of a person and their envir

Benoît Bonnet-Weill, Nastassia Pouradier Duteil

In this article, we develop a comprehensive ODE-theory for structured continuity equations in fibred probability spaces, which represent a class of heterogeneous PDEs arising as the meanfield limit nonexchangeable particle systems. After investigating in depth the topologies induced by the so-called fibred and classical Wasserstein metrics on such probabilit

Derek Aoki

Local-order-invariant (first-order) logic is an extension of first-order logic where formulae have access to a ternary local order relation on the Gaifman graph, provided that the truth value does not depend on the specific order relation chosen. Weinstein asked a number of questions about the expressive power of order-invariant and local-order-invariant log

Osamu Fujino, Nao Moriyama

We propose a new formulation of a vanishing theorem for surfaces. Although this vanishing theorem follows easily from the well-known Kawamata--Viehweg vanishing theorem, it turns out to be remarkably useful. In particular, it is sufficient for the minimal model theory of log surfaces, and it allows one to carry out both the minimal model program and the abun

Yueyao Fan, Xiao-Wei Zhang, Yusen Ye, Xiaoyu Liu

We introduce a generalizable, physics informed strategy for generating training data that enables a machine learning force field accurate over a broad range of twist angles and stacking layer numbers in moire systems. Applying this to multilayer twisted MoTe2 (tMoTe2), we identify a structural and electronic stratification: the two moire interface (MI) layer

Benoît Bonnet-Weill, Alberto Domínguez Corella, Hélène Frankowska

In this article, we establish necessary and sufficient viability conditions for continuity inclusions over the 1-Wasserstein space. Depending on the regularity properties of the dynamics, we derive two results which are based on fairly different proof strategies. When the admissible velocities are Lipschitz in the measure variable, we show that it is necessa

F. Ciavattini, A. Della Corte, C. Lucamarini

In a compact topological dynamical system $(X,f)$, we associate to every pair $(x,y)$ a canonical order-theoretic invariant, its emergent order spectrum $Ω(x,y)$. We first prove that, if $x$ and $y$ are chain-related, one can always build families of nested and acyclic $\varepsilon_n$-chains ($\varepsilon_n \to 0$). The order spectrum $Ω(x,y)$ is then define

Davide Gaiotto

We review categorical aspects of 't Hooft's large $N$ expansion, which is expected to map any Quantum Field Theory of large matrices to a string theory. Our goal is to describe a general strategy to derive the string theory dual to given QFT, at least at the leading order in the 't Hooft expansion. The basic idea is to characterize the underlying worldsheet

G. Esplugues, J. C. Loison, M. Agúndez, G. Molpeceres

We report the first detection in space of propadienone, the linear isomer (l-H$_2$C$_3$O) of cyclopropenone (c-H$_2$C$_3$O). We also report the first detection of the isotopologue c-H$_2$$^{13}$CCCO, and c-HDCCCO of c-H$_2$C$_3$O. The astronomical observations are part of QUIJOTE, a line survey of TMC-1 in the frequency range 31.0-50.3 GHz, complemented with

Inti Cruz Diaz

Every pseudo-Anosov homeomorphism $f$ admits infinitely many Markov partitions. A \textit{geometric Markov partition} is a Markov partition $\mathcal{R}$ in which each rectangle is equipped with a vertical orientation. To each pair $(f, \mathcal{R})$, consisting of a pseudo-Anosov homeomorphism $f$ and a geometric Markov partition $\mathcal{R}$, there is a n

Meng Lu, Ran Xu, Yi Fang, Wenxuan Zhang

While recent vision-language models (VLMs) demonstrate strong image understanding, their ability to "think with images", i.e., to reason through multi-step visual interactions, remains limited. We introduce VISTA-Gym, a scalable training environment for incentivizing tool-integrated visual reasoning capabilities in VLMs. VISTA-Gym unifies diverse real-world

Daniel R. MacLean, Dean R. Edstrom

The Fermilab Accelerator Science and Technology (FAST) Facility at FNAL is a dedicated research and development center focused on advancing particle accelerator technologies for future applications worldwide. Currently, a key objective of FAST Operations is to commission the 2.5 MeV IOTA Proton Injector (IPI) and enable proton injection into the Integr

Wenjie Lan, Jerome P. Reiter

The Gini index is a widely reported measure of income inequality. In some settings, the underlying data used to compute the Gini index are confidential. The organization charged with reporting the Gini index may be concerned that its release could leak information about the underlying data. We present an approach for bounding this information leakage by rele

Peter Iwer Hoedt Karstensen, Roberto Galeazzi

Autonomous robots relying on radio frequency (RF)-based localization such as global navigation satellite system (GNSS), ultra-wide band (UWB), and 5G integrated sensing and communication (ISAC) are vulnerable to spoofing and sensor manipulation. This paper presents a resilient navigation architecture that combines multi-hypothesis estimation with a Poisson b

Noah Frahm, Prakrut Patel, Yue Zhang, Shoubin Yu

Large vision-language models (VLMs) have improved embodied question answering (EQA) agents by providing strong semantic priors for open-vocabulary reasoning. However, when used directly for step-level exploration, VLMs often exhibit frontier oscillations, unstable back-and-forth movements caused by overconfidence and miscalibration, leading to inefficient na

Dragan Miličić, Anna Romanov

Harish-Chandra classified discrete series representations of real semisimple Lie groups by describing their characters as tempered distributions with an explicit formula on the elliptic set. His approach was inspired by Weyl's proof of the character formula for irreducible representations of compact Lie groups. Hecht, Mili\v{c}i\'{c}, Schmid and Wolf gave an

Bixing Qiao

Motivated by the recent interests in asymmetric mean field games, this paper provides a general framework of Heterogeneous Mean Field Game (HMFG) that subsumes different formulations of graphon mean field games. The key feature of the HMFG is that the players interact with the population through the density ensemble. In this case, the HMFG system becomes an

José Camacho

The validation of a data-driven model is the process of assessing the model's ability to generalize to new, unseen data in the population of interest. This paper proposes a set of general rules for model validation. These rules are designed to help practitioners create reliable validation plans and report their results transparently. While no validation sche

Ali Torabi, Sanjog Gaihre, Yaqoob Majeed

Weakly supervised semantic segmentation (WSSS) must learn dense masks from noisy, under-specified cues. We revisit the SegFormer decoder and show that three small, synergistic changes make weak supervision markedly more effective-without altering the MiT backbone or relying on heavy post-processing. Our method, CrispFormer, augments the decoder with: (1) a b

Ayaka Yorihiro, Griffin Berlstein, Pedro Pontes García, Kevin Laeufer

Accelerator design languages (ADLs), high-level languages that compile to hardware units, help domain experts quickly design efficient application-specific hardware. ADL compilers optimize datapaths and convert software-like control flow constructs into control paths. Such compilers are necessarily complex and often unpredictable: they must bridge the wide s

Bat-Od Battseren, Bayarmagnai Gombodorj

We use Zagier's one-sentence proof approach to show that a prime number $p$ admits a form $p=a^2+ab+b^2$ for some integers $a$ and $b$ if and only if $p=3$ or $p\equiv 1 \pmod{3}$.

Jeremy Sakstein, Bhuvnesh Jain

On August 17$^{\rm th}$ 2017, observatories worldwide made a landmark detection: gravitational waves and light from a binary neutron star merger. This event revolutionized our understanding of astrophysics, cosmology, and gravitation. In this proceeding of the 2025 International Congress of Basic Science, we describe how it transformed our view of cosmic acc

Michael Hellstern, Ali Shojaie

Vector autoregressive (VAR) processes are ubiquitously used in economics, finance, and biology. Order selection is an essential step in fitting VAR models. While many order selection methods exist, all come with weaknesses. Order selection by minimizing AIC is a popular approach but is known to consistently overestimate the true order for processes of small

Linxin Hua, Jianghua Deng, Ye Lu

Point cloud reconstruction of damage offers an effective solution to image-based methods vulnerable to background noise, yet its application is constrained by the high volume of 3D data. This study proposes a new feature, relative angle, computed as the angle between the normal vector of a point and the average normal vector of its parent point cloud. This s

Jiaqi Guo, Mingzhen Li, Hanyu Su, Keigo Healy

Semi-supervised learning (SSL) has emerged as an efficient paradigm for medical image segmentation, reducing the reliance on extensive expert annotations. Vision-language models (VLMs) have demonstrated strong generalization and few-shot capabilities across diverse visual domains. In this work, we integrate a VLM into a semi-supervised medical image segmenta

Colton Casto, Anna Ivanova, Evelina Fedorenko, Nancy Kanwisher

Language understanding entails not just extracting the surface-level meaning of the linguistic input, but constructing rich mental models of the situation it describes. Here we propose that because processing within the brain's core language system is fundamentally limited, deeply understanding language requires exporting information from the language system

Carolina Sole Panella, Wolfgang Wieland

We consider the phase space of the Maxwell field as a simplified framework to study the quantisation of holonomies (Wilson line operators) on lightlike (null) surfaces. Our results are markedly different from the spacelike case. On a spacelike surface, electric and magnetic fluxes each form a commuting subalgebra. This implies that the holonomies commute. On

Badih Ghattas, Alvaro Sanchez San-Benito

Clustering is widely used in unsupervised learning to find homogeneous groups of observations within a dataset. However, clustering mixed-type data remains a challenge, as few existing approaches are suited for this task. This study presents the state-of-the-art of these approaches and compares them using various simulation models. The compared methods inclu

Qimeng Yu, Simge Küçükyavuz

L$^\natural$ (natural)-convex functions encompass a large class of nonlinear functions over general integer domains and arise in a wide range of real-world applications. We explore the minimization of L$^\natural$-convex functions, of multiple L$^\natural$-convex functions with common variables, and of a mixed-integer extension of L$^\natural$-convex functio

Muchang Bahng, Charlie Berens, Jon Donnelly, Eric Chen

Species detection is important for monitoring the health of ecosystems and identifying invasive species, serving a crucial role in guiding conservation efforts. Multimodal neural networks have seen increasing use for identifying species to help automate this task, but they have two major drawbacks. First, their black-box nature prevents the interpretability

Abdul Rahman Diab, Emily E. Karn, Renchin Wu, Emily S. Ruiz

Despite the promise of computational pathology foundation models, adapting them to specific clinical tasks remains challenging due to the complexity of whole-slide image (WSI) processing, the opacity of learned features, and the wide range of potential adaptation strategies. To address these challenges, we introduce PathFMTools, a lightweight, extensible Pyt

Julien T. T. Vignoud, Valérian Rousset, Hugo El Guedj, Ignacio Aleman

Data is often impractical to share for a range of well considered reasons, such as concerns over privacy, intellectual property, and legal constraints. This not only fragments the statistical power of predictive models, but creates an accessibility bias, where accuracy becomes inequitably distributed to those who have the resources to overcome these concerns

Farzan Karimi-Malekabadi, Pooya Razavi, Sonya Powers

As educational systems evolve, ensuring that assessment items remain aligned with content standards is essential for maintaining fairness and instructional relevance. Traditional human alignment reviews are accurate but slow and labor-intensive, especially across large item banks. This study examines whether Large Language Models (LLMs) can accelerate this p

T. Rouabhia, A. Boumali

This work presents exact solutions of the Kemmer equation for spin-1 particles in $(1+1)$-dimensional Rindler spacetime, motivated by the need to understand vector bosons under uniform acceleration, including non-inertial effects and the Unruh temperature, which distinguish them from spin-0 and spin-1/2 systems. Starting from the free Kemmer field in an acce

Tenyo Takahashi

We present a new method, the Subdivision Construction, for proving the finite model property (the fmp) for broad classes of modal logics and modal rule systems. The construction builds on the framework of stable canonical rules, and produces a finite modal space, dually, a finite modal algebra, that serves as a finite countermodel of such rules, yielding the

Renaude Girard, Carl Lévesque, Normand Mousseau, François Schiettekatte

We use a recently-developed machine-learned Moment Tensor Potential (MTP) trained on data generated with the density functional theory (DFT) and tailored to amorphous silicon coupled with the Activation-Relaxation Technique nouveau (ARTn) to identify and classify two-level systems (TLS). The samples generated using MTP recover experimental results and provid

Ivan Hetman

Whereas Steiner systems $S(2,k,v)$ with block length $k \le 5$ have large amount of examples and the existence is established for all admissible $v$, for $k\ge 6$ only few examples are known even for decided cases. In this paper the existence of $S(2,9,369)$ is established and some new examples for other admissible pairs $(k,v)$ are given. In particular, lot

Yassine Afif, Mohammed Almekhlafi, Antoine Lesage-Landry, Gunes Karabulut Kurt

In satellite constellation-based communication systems, continuous user coverage requires frequent handoffs due to the dynamic topology induced by the Low Earth Orbit (LEO) satellites. Each handoff between a satellite and ground users introduces additional signaling and power consumption, which can become a significant burden as the size of the constellation

Stephen McKean

A Toda prime of an integer $n$ is an odd prime $p$ such that $4n=(p-1)k$ with $k$ coprime to $p$. We conjecture that every positive integer admits at least two Toda primes. We give a partial proof that every positive integer admits at least one Toda prime. We conclude by discussing connections to denominators of Bernoulli numbers and a generalization of Soph

Alexandru Hening, Siddharth Sabharwal

We look at the interaction of dispersal and environmental stochasticity in $n$-patch models. We are able to prove persistence and extinction results even in the setting when the dispersal rates are stochastic. As applications we look at Beverton-Holt and Hassell functional responses. We find explicit approximations for the total population size at stationari

Nathaniel Dyrkton, Shomoita Alam, Susan Shepherd, Ibrahim Sana

While conducting probabilistic surveys is the gold standard for assessing vaccine coverage, implementing these surveys poses challenges for global health. There is a need for more convenient option that is more affordable and practical. Motivated by childhood vaccine monitoring programs in rural areas of Chad and Niger, we conducted a simulation study to eva

Tergel Molom-Ochir, Benjamin F. Morris, Mark Horton, Chiyue Wei

Transformers face scalability challenges due to the quadratic cost of attention, which involves dense similarity computations between queries and keys. We propose CAMformer, a novel accelerator that reinterprets attention as an associative memory operation and computes attention scores using a voltage-domain Binary Attention Content Addressable Memory (BA-CA

Richard J. Young, Alice M. Matthews

Domain-specific text embeddings are critical for clinical natural language processing, yet systematic comparisons across model architectures remain limited. This study evaluates ten transformer-based embedding models adapted for cardiology through Low-Rank Adaptation (LoRA) fine-tuning on 106,535 cardiology text pairs derived from authoritative medical textb

Mahsa Jahangiri, Afrooz Jouzdani, Hamid Reza Khalesifard

Dust layers have already been reported to have negative impacts on the radiation budget of the atmosphere. But the questions are: How does the atmospheric surface temperature change during a dust outbreak, and what is its temporal correlation with variations of the dust outbreak strength? We investigated these at selected AERONET sites, including Bahrain, IA

Ella J. Mayfield, Adam J. McKay, Michael S. P. Kelley, Anita L. Cochran

Observing [O I] emission to calculate an "oxygen line ratio" has been proposed as a potential proxy for direct CO$_2$ measurement in comets. However, the photochemistry governing [O I] release into the coma is not well understood, and using theoretical release rates often yields different results than using empirical release rates determined in conjunction w

Christos G. Tsagas

The James Webb Space Telescope has recently detected massive, fully formed, galaxies at redshifts corresponding to few hundred million years after the Big-Bang. However, our current cosmological model cannot produce such massive systems so early in the lifetime of the universe. A number of theoretical solutions have been proposed, but they all appeal to exot

Shu Yang, Margaret Gamalo, Haoda Fu

Randomized controlled trials (RCTs)have been the cornerstone of clinical evidence; however, their cost, duration, and restrictive eligibility criteria limit power and external validity. Studies using real-world data (RWD), historically considered less reliable for establishing causality, are now recognized as an important source of real-world evidence (RWE).