March 2026 arXiv papers — page 116

Jason Burton

We introduce a method for detecting regularity loss in solutions to the three-dimensional Navier-Stokes equations using the approximation error of Sinusoidal Representation Networks (SIRENs). SIRENs use sin() activations, producing C-infinity outputs that cannot represent non-smooth features. By classical spectral approximation theory, the SIREN error is bou

Marc Besson, Jiuzu Hong, Huanhuan Yu

Given a simply-connected simple algebraic group $G$, we determine the tangent space of any Finkelberg-Mirkovi\'c Schubert scheme at the base point of the affine Grassmannian of $G$. As a consequence, we exhibit non-reduced Finkelberg-Mirkovi\'c Schubert schemes when $G$ is of type $E_6,E_7$ and $E_8$.

Abhijeet Sahu, Shuva Paul, Richard Macwan

Cyber deception assists in increasing the attacker's budget in reconnaissance or any early phases of threat intrusions. In the past, numerous methods of cyber deception have been adopted, such as IP address randomization, the creation of honeypots and honeynets mimicking an actual set of services, and networks deployed within an enterprise or operational tec

Hengrui Luo, Xiaoye S. Li, Yang Liu, Marcus Noack

Gaussian process (GP) regression is widely used for uncertainty quantification, yet the standard formulation assumes noise-free covariates. When inputs are measured with error, this errors-in-variables (EIV) setting can lead to optimistically narrow posterior intervals and biased decisions. We study GP regression under input measurement uncertainty by repres

Zehan Lin, Xiaowei Wu, Shengwei Zhou

In a web-based review platform, papers from various research fields must be assigned to a group of reviewers. Each paper has an inherent cost, which represents the effort required for reading and evaluating it (e.g., the paper's length). Reviewers can bid on papers they are interested in, and if they are assigned a paper they have bid on, no cost is incurred

Athul S. Rema, Adrián E. Rubio López, Felipe Herrera

Quantum emitters near the surface of silver nanoparticles undergo Rabi oscillations in electronic population dynamics due to strong coupling with near-field multipole modes that are not radiative. Low-frequency nanoparticle dipole modes are radiative but do not couple strong enough to quantum emitters. These features limit the observation of strong coupling.

Shuang Miao, Siqi Ren, Zhifei Zhang

In this paper, we establish the asymptotic linear stability of a class of Coriolis-driven columnar vortices for the 3-D axisymmetric Euler equations. This result represents a critical step toward proving the nonlinear asymptotic stability of such vortices. The key and widely applicable strategy is to construct a distorted Fourier basis, which is achieved by

Lu Dong, Xiao Wang, Mark Frank, Srirangaraj Setlur

Recognizing and localizing student confusion from video is an important yet challenging problem in educational AI. Existing confusion datasets suffer from noisy labels, coarse temporal annotations, and limited expert validation, which hinder reliable fine-grained recognition and temporally grounded analysis. To address these limitations, we propose a practic

Ivana Clairine Irsan, Ratnadira Widyasari, Ting Zhang, Huihui Huang

Attacks can exploit zero-day or one-day vulnerabilities that are not publicly disclosed. To detect these vulnerabilities, security researchers monitor development activities in open-source repositories to identify unreported security patches. The sheer volume of commits makes this task infeasible to accomplish manually. Consequently, security patch detectors

Inbum Heo, Taewook Hwang, Jeesu Jung, Sangkeun Jung

Recent advances in Large Language Models (LLMs) and Large Multimodal Models (LMMs) have improved Document Layout Analysis (DLA), yet structural errors such as region merging, splitting, and omission remain persistent. Conventional overlap-based metrics (e.g., IoU, mAP) fail to capture such logical inconsistencies. To overcome this limitation, we propose Layo

Kunihiko Kaneko

Biological systems are generally complicated and/or complex. In the former approach, one sets up a model with a large number of parameters to describe the system in detail. The latter approach focuses on understanding the universal aspects of biological systems. In this case, an appropriate simple model represents a universality class. The extraction of univ

Ronald L. Kam, Shilong Wang, Gerbrand Ceder

Disordered rock-salt with Li-excess (DRX) cathode phases within the Li-Mn-Ti-O (LMTO) composition space have recently been extensively studied, as they promise to deliver exceptional energy density at low cost in Li-ion batteries. The continued development of LMTO DRX with improved power density and cycling stability requires optimization of the composition

Shihan Zhang, Bing Han, Chuanyong Tian, Ruisheng Shi

Privacy protection mechanisms are a fundamental aspect of security in cryptocurrency systems, particularly in decentralized networks such as Bitcoin. Although Bitcoin addresses are not directly associated with real-world identities, this does not fully guarantee user privacy. Various deanonymization solutions have been proposed, with network layer deanonymiz

Xionghong He, Shusu Shi, Nu Xu

In this article we will review recent measurements of directed flow $v_1$ and elliptic flow $v_2$ in Au+Au collisions from the STAR Beam Energy Scan (BES) program. We systematically analyze the $v_1$ distributions for identified hadrons ($\pi^\pm$, $K^\pm$, $p/\bar{p}$) and $\Lambda$ hyperon as functions of rapidity ($y$), with particular focus on the mid-ce

Xiaochen Li, Sicong Liu, Bin Guo, Yu Ouyang

GB-scale large apps like on-device LLMs and rich media editors are becoming the next-generation trend, but their heavy memory and I/O demands, especially during multitasking, cause devices to reclaim or kill processes, turning warm apps into cold launches. The challenge lies not in storing them, but in fast, accurate launching. For users, 1s is the usability

Jingruo Chen, Yibo Meng, Kexin Nie

Adults with ADHD often face challenges with task management, not due to a lack of willpower, but because of emotional and relational misalignments between cognitive needs and normative infrastructures. Existing productivity tools, designed for neurotypical users, often assume consistent self-regulation and linear time, overlooking these differences. We condu

Jian Ding, Cheng Wang, Haifeng Yu, Hongju Li

Disjunctive Hierarchical Secret Sharing (DHSS) scheme is a secret sharing scheme in which the set of all participants is partitioned into disjoint subsets. Each disjoint subset is said to be a level, and different levels have different degrees of trust and different thresholds. If the number of cooperating participants from a given level falls to meet its th

Yiming Yu, Yuan Qiu, Xinyu Zhao, Ye-Hong Chen

Longitudinal coupling offers a compelling pathway for quantum nondemolition (QND) readout, but pulse design is constrained by hardware limitations such as the coupling strength and the photon number required to stay within the linear regime. We develop a reinforcement learning framework to optimize the longitudinal coupling waveform under such constraints. B

Haoliang Sun, Qi Wei, Lei Feng, Yupeng Hu

Label noise has been broadly observed in real-world datasets. To mitigate the negative impact of overfitting to label noise for deep models, effective strategies (\textit{e.g.}, re-weighting, or loss rectification) have been broadly applied in prevailing approaches, which have been generally learned under the meta-learning scenario. Despite the robustness of

Dong-Sheng Li, Yi-Hao Kang, Zhi-Cheng Shi, Yang Xiao

The NOON states play a critical role as physical resources in quantum information processing and quantum metrology, yet their preparation efficiency and applicability are often constrained by complicated operational procedures or the requirement for nonlinear interactions. In this paper, we propose an efficient protocol to generate the NOON states within two

Akshey Sigdel, Rista Baral

Tool-using automation systems, from scripts and CI bots to agentic assistants, fail in recurring patterns. Common failures include unsafe side effects, invalid arguments, uncontrolled retries, and leakage of sensitive outputs. Many mitigations are model-centric and prompt-dependent, so they are brittle and do not generalize to non-LLM callers. We present Pol

Tatyana Barron, Kai Boisvert, Noah Vale

We obtain a standard local presentation for a vector-valued multisymplectic form on a smooth manifold, generalizing the known proof for polysymplectic forms. We show that vector-valued multisymplectic forms on a finite-dimensional real vector space form a non-unital operad. We prove an entropy inequality for partial compositions.

Victor Reys, Marco Giulini, Alexandre M. J. J. Bonvin

Glycans are structurally diverse and flexible biomolecules that play key roles in many biological processes. Their conformational variability makes the modeling of their interactions with proteins particularly challenging. This chapter presents a step-by-step protocol for modeling protein-glycan interactions using HADDOCK3, an integrative modeling platform t

Dong-Sheng Li, Yang Xiao, Yu Wang, Yang Liu

The binomial code is renowned for its parity-mediated loss immunity and loss-error recoverability, while geometric phases are widely recognized for their intrinsic resilience against noise. Capitalizing on their complementary merits, we propose a noise-resilient protocol to realize Nonadiabatic geometric quantum computation with binomial codes in a supercond

Alexandros Efstratiou, Giuseppe Russo, Luca Luceri

Online discussions of science involve complex interactions among experts, news media, and social media users as they interpret and disseminate scientific findings. While prior work has examined these actors in isolation, their interplay in shaping science communication remains poorly understood. Using the COVID-19 pandemic as a case study, we analyze 1.24M t

Youssef Youssef, Jitin Singla

Reconstructing a 12-lead electrocardiogram (ECG) from a reduced lead set is an ill-posed inverse problem due to anatomical variability. Standard deep learning methods often ignore underlying cardiac pathology losing vital morphology in precordial leads. We propose Pathology-Aware Multi-View Contrastive Learning, a framework that regularizes the latent space

Truong-Son Hy

We propose Q-BIOLAT, a framework for modeling and optimizing protein fitness landscapes in binary latent spaces. Starting from protein sequences, we leverage pretrained protein language models to obtain continuous embeddings, which are then transformed into compact binary latent representations. In this space, protein fitness is approximated using a quadrati

David Restrepo, Miguel L Martins, Chenwei Wu, Luis Filipe Nakayama

Vision-Language Models (VLMs) exhibit a characteristic "cone effect" in which nonlinear encoders map embeddings into highly concentrated regions of the representation space, contributing to cross-modal separation known as the modality gap. While this phenomenon has been widely observed, its practical impact on supervised multimodal learning -- particularly i

Mounir Nisse

We investigate higher--order variation of Hodge structure for families of smooth hypersurfaces and complete intersections through the notion of $I$--maximal variation. Using Griffiths' description of primitive cohomology, we interpret the infinitesimal variation of Hodge structure and the $n$--fold Yukawa coupling as graded multiplication maps in the Jacobia

Young Bin Park

While individual components for AI agent memory exist in prior systems, their architectural synthesis and formal grounding remain underexplored. We present Kumiho, a graph-native cognitive memory architecture grounded in formal belief revision semantics. The structural primitives required for cognitive memory -- immutable revisions, mutable tag pointers, typ

Isqeel Ogunsola, Abosede Akintunde, Kehinde Yusuff, Basirat Adetona

Lately, a New Transmuted Logistic-exponential (NTLE) distribution was introduced and studied as an extension of the Logistic-Exponential Distribution (LED) with wider applicability in lifetime modelling. However, the maximum likelihood estimates (MLE) of NTLE are not in closed form, and the consistency of the estimates was not examined. Furthermore, some oth

Mounir Nisse

We study the infinitesimal variation of Hodge structure for families of algebraic curves and extend the classical theory from smooth curves to singular and non--planar settings. Using the deformation space $\mathrm{Ext}^1(\Omega_X,\mathcal O_X)$ and the dualizing sheaf, we define a singular analogue of maximal infinitesimal variation. For equisingular famili

Yuandeng Shen, Reetika Tiwari

We report the stereoscopic observations of two recurrent streamer waves in a single streamer structure, utilizing coordinated observations from the SOHO, STEREO, and SDO missions. Contrary to the long-held view that fast coronal mass ejections (CMEs) are necessary drivers, we demonstrate that these recurrent waves were excited by two consecutive slow CMEs (<

Angen Ye, Boyuan Wang, Chaojun Ni, Guan Huang

World-Action Models (WAM) initialized from pre-trained video generation backbones have demonstrated remarkable potential for robot policy learning. However, existing approaches face two critical bottlenecks that hinder performance and deployment. First, jointly reasoning over future visual dynamics and corresponding actions incurs substantial inference overh

Hammad Atta, Ken Huang, Kyriakos Rock Lambros, Yasir Mehmood

Agentic LLM systems equipped with persistent memory, RAG pipelines, and external tool connectors face a class of attacks - Logic-layer Prompt Control Injection (LPCI) - for which no automated red-teaming instrument existed. We present LAAF (Logic-layer Automated Attack Framework), the first automated red-teaming framework to combine an LPCI-specific techniqu

Dongyu Bai, Ri He, Junxian Liu, Liangzhi Kou

Ferroelectric materials with switchable spontaneous polarization underpin non-volatile memories, transistors, sensors, and emerging neuromorphic chips. Their performance and stability are governed by polarization dynamics and domain kinetics, making a microscopic understanding of these processes and precise atomic level control of polarization domains key ch

Jinhui Guo, Jia Liu, Chenhao Peng, Xiao-Ping Wang

Ultralight dark matter can behave as a coherent background field and induce time-dependent modifications of Standard Model parameters. We study a scenario in which a real ultralight scalar $\phi$ couples off-diagonally to down-type quarks, linking ultralight dark sectors to flavor physics. Working within an effective field theory, we diagonalize the quark ma

Rui-Chang Shen, Jie Li

A recent paper, Phys. Rev. Research 8, 013261 (2026), claims that the polaromechanical normal-mode splitting (NMS) measured in Nat. Commun. 16, 5652 (2025) is not true based on their two results: $i$) there is no true splitting in the linear-scale spectrum; $ii$) the total or intrinsic decay rate of the cavity-magnon polariton, set by the imaginary part of t

Adam Dai, Shubh Gupta, Grace Gao

Autonomous vehicles such as the Mars rovers currently lead the vanguard of surface exploration on extraterrestrial planets and moons. In order to accelerate the pace of exploration and science objectives, it is critical to plan safe and efficient paths for these vehicles. However, current rover autonomy is limited by a lack of global maps which can be easily

Jun Ishizuka, Youichi Yanase

We theoretically study angle-resolved magnetoresistance under rotated magnetic field in the normal state of a spin-triplet superconductor UTe$_2$. The Wannier model derived from a GGA+$U$ calculation shows quasi-two-dimensional Fermi surfaces with warping in the $k_z$ direction, consistent with quantum oscillation measurements in the high magnetic field regi

Jane Wang, Timothy Keyes, April S Liang, Stephen P Ma

Surgical co-management (SCM) is an evidence-based model in which hospitalists jointly manage medically complex perioperative patients alongside surgical teams. Despite its clinical and financial value, SCM is limited by the need to manually identify eligible patients. To determine whether SCM triage can be automated, we conducted a prospective, unblinded stu

Mousa Salah, Amgad Muneer

Extended reasoning models represent a transformative shift in Large Language Model (LLM) capabilities by enabling explicit test-time computation for complex problem solving. However, the optimal configuration of sampling temperature and prompting strategy for these systems remains largely underexplored. We systematically evaluate chain-of-thought and zero-sh

Zhiyu Ni, Zheng Liang, Liangcheng Song, Chenrui Cao

Auto-formalization (AF) translates natural-language reasoning problems into solver-executable programs, enabling symbolic solvers to perform sound logical deduction. In practice, however, AF pipelines are currently brittle: programs may fail to execute, or execute but encode incorrect semantics. While prior work largely mitigates syntactic failures via repai

Adam Dai, Asta Wu, Keidai Iiyama, Guillem Casadesus Vila

We present a modular, full-stack autonomy system for lunar surface navigation and mapping developed for the Lunar Autonomy Challenge. Operating in a GNSS-denied, visually challenging environment, our pipeline integrates semantic segmentation, stereo visual odometry, pose graph SLAM with loop closures, and layered planning and control. We leverage lightweight

Xiutian Zhao, Ismail Rasim Ulgen, Philipp Koehn, Björn Schuller

Large audio-language models (LALMs) can produce expressive speech, yet reliable emotion control remains elusive: conversions often miss the target affect and may degrade linguistic fidelity through refusals, hallucinations, or paraphrase. We present, to our knowledge, the first neuron-level study of emotion control in speech-generative LALMs and demonstrate

Sohaib Errabii, Olivier Sentieys, Marcello Traiola

Kolmogorov-Arnold Networks (KANs) have gained attention for their potential to outperform Multi-Layer Perceptrons (MLPs) in terms of parameter efficiency and interpretability. Unlike traditional MLPs, KANs use learnable non-linear activation functions, typically spline functions, expressed as linear combinations of basis splines (B-splines). B-spline coeffic

Adam Dai, Guillem Casadesus Vila, Grace Gao

Future lunar missions will require autonomous rovers capable of traversing tens of kilometers across challenging terrain while maintaining accurate localization and producing globally consistent maps. However, the absence of global positioning systems, extreme illumination, and low-texture regolith make long-range navigation on the Moon particularly difficul

Boyong Wu, Sanghwan Kim, Zeynep Akata

Multimodal Large Language Models (MLLMs) are increasingly applied to pixel-level vision tasks, yet their intrinsic capacity for spatial understanding remains poorly understood. We investigate segmentation capacity through a layerwise linear probing evaluation across the entire MLLM pipeline: vision encoder, adapter, and LLM. We further conduct an interventio

Dip Roy, Rajiv Misra, Sanjay Kumar Singh

Extreme neural network sparsification (90% activation reduction) presents a critical challenge for mechanistic interpretability: understanding whether interpretable features survive aggressive compression. This work investigates feature survival under severe capacity constraints in hybrid Variational Autoencoder--Sparse Autoencoder (VAE-SAE) architectures. W

Yanhong Liu, Fengyi Song, Long Feng

We consider estimation of high-dimensional long-run covariance matrices for time series with nonconstant means, a setting in which conventional estimators can be severely biased. To address this difficulty, we propose a difference-based initial estimator that is robust to a broad class of mean variations, and combine it with hard thresholding, soft threshold

Jianchao Zheng, Tuo Wu, Kai-Kit Wong, Baiyang Liu

This paper presents a comprehensive physical layer security (PLS) framework for fluid antenna system (FAS)-aided short-packet communications under the variable block-correlation model (VBCM). We consider a downlink wiretap scenario in which a base station transmits confidential short packets to a legitimate receiver user (RU) in the presence of an eavesdropp

Jason Shin, Jiwon Chang, Fatemeh Nargesian

Semantic operators abstract large language model (LLM) calls in SQL clauses. It is gaining traction as an easy method to analyze semi-structured, unstructured, and multimodal datasets. While a plethora of recent works optimize various semantic operators, existing methods for semantic ORDER BY (full sort) and LIMIT K (top-K) remain lackluster. Our ListK frame

Roberto da Silva

This study investigates how visibility graphs constructed from Monte Carlo Markov Chain time series of spin models capture the critical behavior of the system. More precisely, we show that this approach identifies continuous phase transitions as well as important nuances, such as crossover effects occurring in the transition from a critical line to a first-o

Jerry Li

In binary stellar evolution, the orbital response to mass transfer depends on how angular momentum is redistributed. We introduce a one-parameter family of prescriptions characterized by $η$, the fractional weight of the donor velocity in the effective velocity of the transferred mass: $v_{\rm trans} = η\, v_1 + (1-η) \, v_2$. We derive a closed-form express

Jay Jay Tsui, Tom Kirchner

Electron emission from hydrogen atoms induced by antiproton impact at intermediate energies is investigated using the one-centre Basis Generator Method within a semi-classical impact-parameter framework. The formulation employs a single-centre expansion of the time-dependent Schrödinger equation with a pseudostate basis consisting of hydrogenic orbitals acte

Kai-Chi Chang, Murat Can Sarihan, Nicky Kai Hong Li, Florian Kanitschar

High-dimensional photonic entanglement holds significant promise for advancing quantum communication, computation, and metrology. For example, large-alphabet quantum communication protocols are known to benefit from enhanced noise resilience and information capacity via multi-bit time-bin encoding. Yet, characterizing high-dimensional entangled states is cha

Deepasika Dayananda, Chueng-Ryong Ji

The interplay between quantum orientation entanglement and Wigner rotation plays a fundamental role in understanding the behavior of spin angular momentum in quantum states. To analyze the quantum orientation entanglement of the relativistic helicity states interpolating between the Jacob-Wick helicity and the light-front helicity, we examine the relative an

Dario Fiore Mosca, Lorenzo Celiberti, Leonid V. Pourovskii, Cesare Franchini

We investigate how doping-induced small polarons impact the low-temperature multipolar orders of the $5d^2$ double perovskite Ba$_2$CaOsO$_6$. By computing intersite exchange interactions between 5d$^1$ localized hole polarons and 5d$^2$ magnetic ions from first principles, we demonstrate the reversal of the dominant octupolar exchange from ferromagnetic to

Marco Palla, Alessio Mucciarelli, Donatella Romano, Samuele Anoardo

Context. In the context of galactic archaeology, the study of the Small Magellanic Cloud (SMC) is of crucial importance, as it represents a unique opportunity to study a nearby massive dwarf system. However, theoretical studies of the chemical evolution of this galaxy are strikingly lacking. Aims. In this study, we investigate the chemical enrichment of the

Thomas Webb, Arthur Apostel, Milena Büchs, Richard Bärnthaler

Wealth taxes are a frequently proposed policy within the post-growth literature, but evaluations of their alignment with post-growth goals, and empirical estimates of their potential effects, are lacking. We contribute to this literature by examining the extent to which different wealth-tax designs can contribute to four goals of a post-growth transition: re

Elizabeth H. Krenkel, Makariy A. Tanatar, Romain Grasset, Marcin Kończykowski

The Remeika series superconductor, $(\text{Ca}_x\text{Sr}_{1-x})_3\text{Rh}_4\text{Sn}_{13}$, shows a rare nonmagnetic quantum critical point (QCP) associated with the continuous charge-density wave (CDW) and structural transition under the ``dome&#39;&#39; of superconductivity achieved by tuning composition and applying pressure. Here we use a nonmagnetic p

Wanjun Du, Zifeng Yuan, Tingting Chen, Fucai Ke

Existing vision-language models (VLMs) have demonstrated impressive performance in reasoning-based segmentation. However, current benchmarks are primarily constructed from high-quality images captured under idealized conditions. This raises a critical question: when visual cues are severely degraded by adverse weather conditions such as rain, snow, or fog, c

O. Azzolini, J. W. Beeman, F. Bellini, M. Beretta

Sterile neutrinos are well-motivated extensions of the Standard Model, introduced to address fundamental questions such as the origin of neutrino masses and the nature of dark matter. Exploiting the precise data reconstruction achieved by the CUPID-0 experiment, we searched for spectral distortions in the double $β$-decay of $^{82}$Se compatible with the emi

The VERITAS Collaboration, A. Archer, P. Bangale, J. T. Bartkoske

Significant gamma-ray emission between 1 TeV and 20 TeV from a point source, 1LHAASO J1219+2915, consistent with the location of the LINER/LLAGN galaxy NGC 4278 was recently reported by the LHAASO collaboration. These data were later split into active and quasi-quiet states, with most of the LHAASO significance coming from the active state (MJD 59449-59589).

Tanmay Gupta, Benoit Forget

OpenMC can be used to computationally model depletion and produce estimates of decay heat. As an input to depletion simulations, OpenMC requires a depletion chain that details nuclide transmutation pathways. The simplified CASL depletion chain was designed to track relatively few nuclides while still accurately modeling the effective neutron multiplication f

Martin Monperrus

A coding agent can bootstrap itself. Starting from a 926-word specification and a first implementation produced by an existing agent (Claude Code), a newly generated agent re-implements the same specification correctly from scratch. This reproduces, in the domain of AI coding agents, the classical bootstrap sequence known from compiler construction, and inst

Pieter van Goor, Chiara Gabellieri, Antonio Franchi

This work considers the problem of using multiple aerial carriers to hold a cable-suspended load while remaining in periodic motion at all times. Using a novel differential geometric perspective, it is shown that the problem may be recast as that of finding an immersion of the unit circle into the smooth manifold of admissible configurations. Additionally, t

Fucai Ke, Zhixi Cai, Boying Li, Long Chen

Multi-view visual reasoning is essential for intelligent systems that must understand complex environments from sparse and discrete viewpoints, yet existing research has largely focused on single-image or temporally dense video settings. In real-world scenarios, reasoning across views requires integrating partial observations without explicit guidance, while

Jiakang Chen, Sufia Hashim, Carla Figueira de Morisson Faria

We develop an unsupervised physics-informed neural network to solve saddle-point equations (SPEs) governing direct above-threshold ionization (ATI) within the strong-field approximation. This setting provides a well-understood testbed in which the saddle-point structure is known for tailored driving fields, enabling systematic validation of the proposed solv

James A. A. Trussler, Daniel J. Eisenstein, Andrew J. Bunker, Alex J. Cameron

JWST is beginning to uncover a population of extremely metal-poor galaxies (EMPGs, $Z < 1\%~\mathrm{Z}_\odot$) at $z > 3$, mostly through serendipitous NIRSpec discoveries and blind slitless spectroscopy. To accelerate our understanding of pristine star formation, we further develop a methodology to identify EMPG candidates from photometry, using the extensi

Francisco Asensio-Rivera, Nils Schöneberg, Héctor Gil-Marín, Licia Verde

Analyses of baryon acoustic oscillations (BAO) commonly employ template-based methods to extract compressed parameters from the clustering of dark-matter tracers, which are then interpreted in terms of ratios of the sound-horizon scale and cosmological distances relative to a fiducial cosmology. A small mismatch between the sound-horizon scale derived from t

John Bamberg, Lukas Klawuhn

We investigate generalisations of 1-factorisations and hyperfactorisations of the complete graph $K_{2n}$. We show that they are special subsets of the association scheme obtained from the Gelfand pair $(S_{2n},S_2 \wr S_n)$. This unifies and extends results by Cameron (1976) and gives rise to new existence and non-existence results. Our methods involve work

Coline Emprin, Alex Takeda

We define a properad $Y^{(n)}_\infty$ that encodes $n$-pre-Calabi--Yau algebras with vanishing copairing. These algebras include chains on the based loop space of any space $X$ endowed with a fundamental class $[X]$ such that $(X,[X])$ satisfies Poincaré duality of degree $n \geqslant 1$ with local system coefficients, such as an oriented manifold. Extending

Lucas Mioranci

We generalize techniques by Coskun, Riedl, and Yeong, and obtain an almost optimal bound on the degree for the algebraic hyperbolicity of very general hypersurfaces in rational homogeneous varieties. As examples, we work out the cases of very general hypersurfaces in Grassmannians and products therefore, orthogonal and symplectic Grassmannians, and flag vari

Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang

Language is essentially a complex, intricate system of human expressions governed by grammatical rules. It poses a significant challenge to develop capable AI algorithms for comprehending and grasping a language. As a major approach, language modeling has been widely studied for language understanding and generation in the past two decades, evolving from sta

Shiva Azimi, Arash Tavakoli

Cycling plays an important role in sustainable urban mobility, yet how people perceive cycling infrastructure varies widely and remains challenging to assess at large spatial scales. Existing research has mainly relied on surveys or short-form social media data and has often focused on individual cities, leaving limited insight into how cycling discussions u

Prajwal Panth, Agniva Maiti

The rapid proliferation of Large Language Models (LLMs) has created a profound digital divide, effectively excluding indigenous languages of the Global South from the AI revolution. The Tharu language, an Indo-Aryan vernacular spoken by approximately 1.7 million people across the Terai belt of Nepal and India, exemplifies this crisis. Despite a rich oral tra

Ishrith Gowda, Chunwei Liu

Multi-site neuroimaging analysis is fundamentally confounded by scanner-induced covariate shifts, where the marginal distribution of voxel intensities $P(\mathbf{x})$ varies non-linearly across acquisition protocols while the conditional anatomy $P(\mathbf{y}|\mathbf{x})$ remains constant. This is particularly detrimental to radiomic reproducibility, where a

Federico Albanese, Pablo Ronco, Nicolás D'Ippolito

Responsible use of AI demands that we protect sensitive information without undermining the usefulness of data, an imperative that has become acute in the age of large language models. We address this challenge with an on-premise, LLM-driven substitution pipeline that anonymizes text by replacing personally identifiable information (PII) with realistic, type

Ziyang Cai, Amir Saeidi, Harkirat Behl

With the advent of AI agents, automated scientific discovery is becoming an increasingly plausible goal. However, training agents to autonomously execute the engineering-heavy labor of machine learning (ML) research requires massive, process-level supervision. Existing static benchmarks omit critical intermediate steps such as debugging and incremental reaso

Darmindra Arumugam

Rydberg-state hopping is demonstrated in a wavemeter-locked two-photon rubidium system (Rb D2 probe at 780 nm and 480 nm coupler), enabling rapid and repeatable switching between the 65S1/2 and 63D5/2 states without cavity or frequency-comb stabilization. A Fizeau-interferometer wavemeter provides the error signal for a digital feedback loop that simultaneou

Tae Gwan Park, Xufan Li, Kyungnam Kang, David B. Geohegan

Rapid exciton-exciton annihilation (EEA) in two-dimensional semiconductors limits access to high-density excitonic regimes essential for efficient optoelectronic operation under strong excitation. Here, we show that EEA is suppressed by repulsive dipole-dipole interactions between interlayer excitons polarized by the spontaneous polarization intrinsic to rho

Mohammad Javad Sekonji, Ali Mahani, Maryam Mirsadeghi, Mahdi Taheri

Spiking Neural Networks (SNNs) offer high energy efficiency and event-driven computation, ideal for low-power edge AI. Their hardware implementation on FPGAs, however, faces challenges due to heavy computation, large memory use, and limited flexibility. This paper proposes a compact System-on-Chip (SoC) architecture for temporal-coding SNNs, integrating a RI

Mario Alberto Ruiz Caballero

We prove that given a symmetric completely non-selfadjoint operator $B$ with finite deficiency indices $(n,n)$ on a Hilbert space and a boundary triplet $\left(\mathbb{C}^{n},\Gamma_{1},\Gamma_{2}\right)$ for $B^{*}$, the set of points in the spectrum of $A_{1}$ (the self-adjoint extension with domain $Ker\;\Gamma_{1}$) which are not eigenvalues of maximum m

Danial Monachan, Samira Nazari, Mahdi Taheri, Ali Azarpeyvand

Deploying deep neural networks (DNNs) on edge devices requires strong compression with minimal accuracy loss. This paper introduces Mix-and-Match Pruning, a globally guided, layer-wise sparsification framework that leverages sensitivity scores and simple architectural rules to generate diverse, high-quality pruning configurations. The framework addresses a k

Audrey Gaymann, Juan M. Cardenas, Sung Min Jo, Marco Panesi

This paper presents the development of an algorithm, termed the Global-Local Hybrid Surrogate (GLHS), designed to efficiently compute the probability of rare failure events in complex systems. The primary goal is to enhance the accuracy of reliability analysis while minimizing computational cost, particularly for high-dimensional problems where traditional m

Zhenlin Zhu, Mark R. Morris, Gabriele Ponti, Ping Zhou

The Sagittarius C (Sgr C) complex, located on the western edge of the Central Molecular Zone (CMZ), hosts a mixture of star-forming and non-thermal activity whose X-ray properties remain poorly understood. Using deep archival Chandra and XMM-Newton observations, we resolve the diffuse X-ray emission in Sgr C into two components: an H II region coincident wit

Zhiwei Zhao, Changqing Liu, Jie Lin, Fan Yang

Efficient and accurate prediction of Multiphysics evolution across diverse cell geometries is fundamental to the design, management and safety of lithium-ion batteries. However, existing computational frameworks struggle to capture the coupled electrochemical, thermal, and mechanical dynamics across diverse cell geometries and varying operating conditions. H

Prashanth Vijayaraghavan, Apoorva Nitsure, Luyao Shi, Charles Mackin

Register-Transfer Level (RTL) synthesis and summarization are central to hardware design automation but remain challenging for Large Language Models (LLMs) due to rigid HDL syntax, limited supervision, and weak alignment with natural language. Existing prompting and retrieval-augmented generation (RAG) methods have not incorporated symbolic planning, limitin

Carlos E. Beltrán, José A. Zapata

There is an error in our recent preprint ``The EPRL amplitude is supported on flat connections''. The error is in Section 3. Here we leave the original text unchanged, but add a note in Section 3 pointing out exactly what the error is. We apologize for the false alarm. After one month, this preprint will be withdrawn from the arxiv. {\bf Original Abstract:}

Juan Carlos Obeso Jureidini, Michael Reitz, Piper Fowler-Wright, Arghadip Koner

We investigate the effect of nonrelativistic motion on the emission dynamics of a dipole emitter moving next to a reflecting interface. Within the formalism of macroscopic QED, we obtain a general equation of motion for the dipole amplitude in terms of the dyadic Green's function, yielding a dynamical extension of the Drexhage effect. At short dipole-surface

Che-Ming Chang, Prashanth Vijayaraghavan, Ashutosh Jadhav, Charles Mackin

Optimizing Register Transfer Level (RTL) code is a critical step in Electronic Design Automation (EDA) for improving power, performance, and area (PPA). We present CODMAS (Collaborative Optimization via a Dialectic Multi-Agent System), a framework that combines structured dialectic reasoning with domain-aware code generation and deterministic evaluation to a

Tianyu Qiu, Filippos Fotiadis, Xinjie Liu, Christian Ellis

Linear-quadratic Gaussian games provide a framework for modeling strategic interactions in multi-agent systems, where agents must estimate system states from noisy observations while also making decisions to optimize a quadratic cost. However, these formulations usually require agents to utilize the full set of available observations when forming their state

Soudabeh Mohammadhashemi, Shishir Gopinath, Kimia Khabiri, Parsa Hosseininejad

Visual SLAM systems combine visual tracking with global loop closure to maintain a consistent map and accurate localization. Loop closure is a computationally expensive process as we need to search across the whole map for matches. This paper presents FastLoop, a GPU-accelerated loop closing module to alleviate this computational complexity. We identify key

W. A. Zúñiga-Galindo

We present a new p-adic version of the Jackiw-Rebbi model. In the new model, the real numeric line is replaced by a p-adic line (the field of p-adic numbers Q_{p}), and the Dirac Hamiltonian is replaced by a non-local operator acting on complex-valued functions defined on Q_{p}. These Hamiltonians admit localized wavefunctions and allow long-range interactio

Parsa Mirtaheri, Mikhail Belkin

Large language models (LLMs) can produce chains of thought (CoT) that do not accurately reflect the actual factors driving their answers. In multiple-choice settings with an injected hint favoring a particular option, models may shift their final answer toward the hinted option and produce a CoT that rationalizes the response without acknowledging the hint -

Daniel Ralston, Xu Yang, Ruimeng Hu

In competitive games with private objectives, actions can reveal information about hidden parameters. However, quantifying such information revelation is nontrivial, since it depends not only on the opponent&#39;s hidden parameter but also on the opponent&#39;s model of the game. We study this problem via a two-player linear-quadratic stochastic differential

Tynan Perez, Rafael Gomez-Bombarelli

The success of large-scale pretraining in NLP and computer vision has catalyzed growing efforts to develop analogous foundation models for the physical sciences. However, pretraining strategies using atomistic data remain underexplored. To date, large-scale supervised pretraining on DFT force-energy labels has provided the strongest performance gains to down

Linn E. J. Eriksson, Ziyan Xu, Jeonghoon Lim, Chao-Chin Yang

Strong dust clumping by streaming instability (SI) is the leading proposed mechanism for forming planetesimals, the building blocks of terrestrial planets and giant-planet cores. The critical dust-to-gas density ratio above which the SI leads to dust concentration strong enough to result in gravitational collapse depends on local dust properties and disk con

Cristóbal Méndez, Tomás A. Arias

Two-level systems (TLS) in native Nb and Ta oxides limit superconducting-qubit coherence and SRF-cavity quality factors in the microwave frequency range, yet their microscopic origin remains unclear. We combine MLIP-accelerated sampling of hydrogen configurations and diffusion pathways in amorphous Nb and Ta pentoxides with targeted $\textit{ab initio}$ vali