December 2025 arXiv papers — page 93

Jiaqing Lu, Ziqi Li, Lei Han, Qianwen Guo

This study applies a Geospatial Explainable AI (GeoXAI) framework to analyze the spatially heterogeneous and nonlinear determinants of traffic crash density in Florida. By combining a high-performing machine learning model with GeoShapley, the framework provides interpretable, tract-level insights into how roadway characteristics and socioeconomic factors co

Ni-Shi Lu, Ping Zhou

Currently, the progress of quantum secure direct communication (QSDC) is impeded by a fundamental trade off among control efficiency, security, and scalability. This study proposes an innovative controlled QSDC protocol based on a collaborative unitary sequence decoding paradigm to break this deadlock.Leveraging four dimensional single particle states, the p

Roberto Vila, Helton Saulo

In this paper, we derive a general representation for the expectation of the Gini coefficient estimator in terms of the Laplace transform of the underlying distribution, together with the mean and the Gini coefficient of its exponentially tilted version. This representation leads to a new characterization of the gamma family within the class of nonnegative s

Yaniv Leviathan, Matan Kalman, Yossi Matias

When not using reasoning, repeating the input prompt improves performance for popular models (Gemini, GPT, Claude, and Deepseek) without increasing the number of generated tokens or latency.

Matthew Kerr, Zorawar Wadiasingh, Adrien Laviron, Constantinos Kalapotharakos

Radio pulsar timing array (PTA) experiments using millisecond pulsars (MSPs) are beginning to detect nHz gravitational waves (GWs). MSPs are bright GeV gamma-ray emitters, and all-sky monitoring of about 100 MSPs with the Fermi Large Area Telescope (LAT) has enabled a gamma-ray Pulsar Timing Array. The GPTA provides a complementary view of nHz GWs because it

Qi Wang, Uday V. Shanbhag, Yue Xie

Most existing rate and complexity guarantees for stochastic gradient methods in $L$-smooth settings mandates that such sequences be non-adaptive, non-increasing, and upper bounded by $\tfrac{a}{L}$ for $a > 0$. This requires knowledge of $L$ and may preclude larger steps. Motivated by these shortcomings, we present an Armijo-enabled stochastic linesearch fra

Eric Gilbertson, Kathryn E. Stanchak, Scott Hotaling

Pico Cristobal Colon and Pico Simon Bolivar are the highest peaks in Colombia and were last accurately surveyed in 1939. This historical survey measured Cristobal Colon, Colombia's recognized highpoint, at 5775m and Simon Bolivar at 5773m. Both peaks have permanent icecaps at their summits. For this study, multiple differential GPS units and an Abney level w

Stuart Winby, Wei Xu

Human-centered artificial intelligence (HCAI) is an approach to AI design, development, and deployment that prioritizes human needs, values, and experiences, ensuring that technology enhances human capabilities, well-being, and workforce empowerment. While HCAI has gained prominence in academic discourse and organizational practice, its implementation remain

Yong-Geun Oh

The notion of \emph{contact triad connection} on contact triads $(Q,λ,J_ξ)$ was introduced by Wang and the present author in early 2010's from scratch as the contact analog to the canonical connection of an almost Kähler manifolds. The connection facilitates the study of analysis of the contact instanton equation which ranges from local elliptic priori e

M. A. Blatnik, S. M. Clayton, S. A. Currie, B. W. Filippone

The cryogenic approach to the search for the neutron electric dipole moment--performing the experiment in superfluid liquid helium--holds promise for a substantial increase in sensitivity, potentially enabling a sensitivity level of $10^{-28}$ e-cm. A crucial component in realizing such an experiment is the high voltage and electrode system capable of provid

Md Shahriar Sajid, Abhijit Kumar Ghosh, Fariha Nusrat

Electroencephalography (EEG) signals contain rich temporal-spectral structure but are difficult to model due to noise, subject variability, and multi-scale dynamics. Lightweight deep learning models have shown promise, yet many either rely solely on local convolutions or require heavy recurrent modules. This paper presents PaperNet, a compact hybrid architec

Marek Jankola, Freya Behrens, Cédric Koller, Lenka Zdeborová

We investigate how much bias in the initial configuration is required to drive global agreement in synchronous, deterministic majority dynamics on large random $d$-regular graphs. Nodes take values $\pm 1$ and update their states at each discrete time step to align with the majority of their neighbors. Using the backtracking dynamical cavity method (BDCM), w

Robert Stephany, William Michael Anderson, Youngsoo Choi

Solving complex partial differential equations is vital in the physical sciences, but often requires computationally expensive numerical methods. Reduced-order models (ROMs) address this by exploiting dimensionality reduction to create fast approximations. While modern ROMs can solve parameterized families of PDEs, their predictive power degrades over long t

Enrique Rodríguez-Miranda, Pablo Otálora, José González-Hernández, José Luis Guzmán

This paper presents a benchmarking framework to evaluate process control strategies in outdoor microalgae raceway reactors, integrating four key control regulation tasks: pH, dissolved oxygen (DO), culture volume through coordinated harvest-dilution actions, and temperature via a sump-mounted spiral heat exchanger. The benchmark is built upon a high-fidelity

Omima Osman, Gabriella De Lucia, Fabio Fontanot, Lizhi Xie

For many decades, dust has been recognised as an important ingredient in galaxy formation and evolution. This paper presents a novel self-consistent implementation of dust formation by stars, destruction by supernova shocks and hot gas, and growth within the dense interstellar medium (ISM) in the GAEA state-of-the-art galaxy formation model. Our new model, D

Fernando Valenciano, Jorge Martin Camalich, Arianna Di Cintio, Julio F. Navarro

We investigate constraints on the inner stellar density profile from photometric data of dwarf spheroidal and ultra-faint dwarf galaxies. Our aim is to clarify under what conditions cored stellar profiles require dark matter halos that are also cored, deviating from the cuspy profiles expected for cold dark matter halos. We consider a variety of spherically

Beatrice Magni, Markus Heinrich, Lorenzo Leone, Xhek Turkeshi

We investigate the statistical properties of orthogonal, or real, Clifford circuits doped with magic and imaginary resources. By developing the Weingarten calculus for the real Clifford group, we derive the exact overlap distribution of real stabilizer states, identifying a new universality class: the orthogonal Clifford Porter-Thomas distribution. We prove

Markus Niese, Michele Masseroni, Clara Scherm, Christoph Adam

We investigate electronic transport through gate-defined quantum dots in molybdenum disulfide MoS$_2$ using an integrated charge detector. We observe a crossover from two weakly coupled single dots to a strongly coupled double quantum dot. In the regime of extremely weak dot-lead coupling, where the direct transport current is below the detection limit, we m

Benedict Short, Ian McInerney, John Wickerson

With the push towards Exascale computing and data-driven methods, problem sizes have increased dramatically, increasing the computational requirements of the underlying algorithms. This has led to a push to offload computations to general purpose hardware accelerators such as GPUs and TPUs, and a renewed interest in designing problem-specific accelerators us

Marcos Rubín-Osanz, Laura Bersani, Simone Chicco, Giuseppe Allodi

Molecular spin qudits based on lanthanide complexes offer a promising platform for quantum technologies, combining chemical tunability with multi-level encoding. However, experimental demonstrations of their envisaged capabilities remain scarce, posing the difficulty of achieving precise control over coherences between qudit states in long pulse sequences. H

Lewis T. Cole, Ben Hoare

We show how to construct 2d field theories with holomorphic integrability from defect setups in 4d holomorphic BF. In a simple example setup, we explicitly construct the 2d theory and perform an initial classical analysis. Making use of the symmetries, we are able to write down an infinite family of solutions to the equations of motion. Comparing with more t

Thomas Rooijakkers, Anne Nijsten, Cristian Daniele, Erieke Weitenberg

Many business processes currently depend on web services, often using REST APIs for communication. REST APIs expose web service functionality through endpoints, allowing easy client interaction over the Internet. To reduce the security risk resulting from exposed endpoints, thorough testing is desired. Due to the generally vast number of endpoints, automated

Run-ze Hu, Yang Yang, Yi-hang Yang, Jing-qi Kong

Background: Motivational interviewing (MI) is an effective counseling approach for promoting health behavior change, but its impact is constrained by the need for highly trained human counselors. Objective: This study aimed to explore a scalable alternative by developing and evaluating Large Language Models for Motivational Interviewing (MI-LLMs). Methods: W

Mohammed Asheruddin Nazeeruddin, Ruihe Li, Simon E. J. OKane, Monica Marinescu

Designing lithium-ion batteries for long service life remains a challenge, as most cells are optimized for beginning-of-life metrics such as energy density, often overlooking how design and operating conditions shape degradation. This work introduces a degradation-aware design framework built around finite, interacting reservoirs (lithium, porosity, and elec

Rakesh Saini, Jukka Kiukas, Daniel Burgarth, Alexei Gilchrist

Informationally complete measurements form the foundation of universal quantum state reconstruction, while quantum parameter estimation is based on the local structure of the manifold of quantum states. Here we establish a general link between these two aspects, in the context of a single informationally complete measurement, by employing a suitably adapted

Hyakka Nakada, Shu Tanaka

Random matrix theory has played an important role in various areas of pure mathematics, mathematical physics, and machine learning. From a practical perspective of data science, input data are usually normalized prior to processing. Thus, this study investigates the statistical properties of min-max normalized eigenvalues in random matrices. Previously, the

Julian Oelhaf, Mehran Pashaei, Georg Kordowich, Christian Bergler

The growing penetration of renewable and distributed generation is transforming power systems and challenging conventional protection schemes that rely on fixed settings and local measurements. Machine learning (ML) offers a data-driven alternative for centralized fault classification (FC) and fault localization (FL), enabling faster and more adaptive decisi

Robert Denk, Floris B. Roodenburg

We characterise the trace spaces arising from intersections of weighted, vector-valued Sobolev spaces, where the weights are powers of the distance to the boundary. These weighted function spaces are particularly suitable for treating boundary value problems where derivatives of the solution blow up at the boundary. As an application of our trace theory, we

Feihu Liu, Guoce Xin

MacMahon introduced partition analysis in his book ``Combinatory Analysis'' as a computational technique for solving problems related to systems of linear Diophantine equations and inequalities. This paper aims to develop a fundamental computational method for MacMahon's partition analysis. As applications, we present simplified computations for

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

Using $(10087\pm44)\times10^6$ $J/ψ$ events collected with the BESIII detector, we study the semileptonic decay $Ξ^{-}\rightarrow Λe^- \barν_{e}$ for the first time at an electron-positron collider. The absolute branching fraction is determined for the first time to be $(3.60\pm0.40_{\mathrm{stat}}\pm0.10_{\mathrm{syst}})\times10^{-4}$, which is 3.9 standard

Tetsuro Ueno, Yasuo Takeichi, Masaki Mizuguchi, Hideaki Iwasawa

X-ray detected ferromagnetic resonance (XFMR) spectroscopy is an experimental technique for element-specific spin dynamics in the GHz regime and has been utilized to study spintronic materials. The XFMR signal is usually obtained by detecting X-ray excited optical luminescence (XEOL) emitted from a sample substrate. Here, we report the development of an XFMR

Armin Ulrich, Mason Haberle, Alan A. Kaptanoglu

Permanent magnets provide an attractive path for shaping university-scale stellarator magnetic fields. Previous work has shown that greedy permanent magnet optimization (GPMO) can produce sparse, grid-aligned arrays that match target surfaces with high accuracy under an ideal rigid-remanence model. Here we extend this approach to a greedy permanent magnet op

Yuto Moritake, Nozomi Ogawa, Issei Takeda, Yusuke Ohinata

Non-Hermitian point gap (NHPG) is a unique phenomenon in non-Hermitian systems and induces non-Hermitian skin effect (NHSE). In photonic crystals, NHPG and the NHSE have previously been explored mainly through material loss, where the typically low $Q$ factors make direct observation of complex frequencies challenging. Here, we demonstrate the direct experim

Yuki Uchino, Qianxiang Ma, Toshiyuki Imamura, Katsuhisa Ozaki

Modern computing architectures feature low-precision matrix multiplication units that achieve substantially higher throughput than their high-precision counterparts. Motivated by this architectural trend, the emulation of high-precision matrix multiplication using low-precision hardware has attracted significant interest in the high-performance computing com

Vaisakh Mannalath, Víctor Zapatero, Marcos Curty

We use a simple method to derive two concentration bounds on the hypergeometric distribution. Comparison with existing results illustrates the advantage of these bounds across different regimes.

Riccardo Muolo, Yuzuru Kato

Controlling the behavior of nonlinear systems on networks is a paramount task in control theory, in particular the control of synchronization, given its vast applicability. In this work, we focus on pinning control and we examine two different approaches: the first, more common in engineering applications, where the control is implemented through an external

Francesc Sabater, Ouns El Harzli, Geert-Jan Besjes, Marvin Erdmann

Optimization via decoded quantum interferometry (DQI) has recently gained a great deal of attention as a promising avenue for solving optimization problems using quantum computers. In this paper, we apply DQI to an industrial optimization problem in the automotive industry: the vehicle option-package pricing problem. Our main contributions are 1) formulating

Beno Učakar

We present the class of semi-admissible subsets of an open Riemann surface on which Carleman approximation by non-critical holomorphic functions is possible. In particular we characterize closed sets with empty interior on which continuous functions can be approximated by non-critical holomorphic ones. We also consider a different approach, which in some cas

Qimin Yan, Tongcang Li, Xingyu Gao, Sumukh Vaidya

Two-dimensional (2D) materials have emerged as a versatile and powerful platform for quantum technologies, offering atomic-scale control, strong quantum confinement, and seamless integration into heterogeneous device architectures. Their reduced dimensionality enables unique quantum phenomena, including optically addressable spin defects, tunable single-phot

Balreet Grewal, James Graham, Jeff Muizelaar, Jan Honza Odvarko

Browser rendering bugs can be challenging to detect for browser developers, as they may be triggered by very specific conditions that are exhibited on only a very small subset of websites. Cross-browser inconsistencies (XBIs), variations in how a website is interpreted and displayed on different browsers, can be helpful guides to detect such rendering bugs.

Mohamed Naeem

The innovative agriculture system is revolutionizing how we farm, making it one of the most critical innovations of our time! Yet it faces significant connectivity challenges, particularly with the sensors that power this technology. An efficient sensor deployment solution is still required to maximize the network's detection capabilities and efficiency whil

A. V. Kitaev

This paper proposes a new approach to the asymptotic analysis of Painlev\'e equations. The approach is based on representing solutions of the Painlev\'e equations using formal series in two variables, $\sum_{k=0}^{\infty}y^kA_k(x)$, with rational functions $A_k(x)$. The approach is applied to the asymptotic analysis of the third degenerate Painlev\'e equatio

Daniel Björkegren

Market expectations about AI's economic impact may influence interest rates. Previous work has shown that US bond yields decline around the release of a sample of mostly proprietary AI models (Andrews and Farboodi 2025). I extend this analysis to include also open weight AI models that can be freely used and modified. I find long-term bond yields shift in op

Ziyi Yang, Sakshi Gupta, Jehan Shalabi, Leif Bauer

Analog bolometers based on temperature-dependent phase-transition materials such as vanadium oxide (VOx) and barium titanate (BTO) represent the state of the art in uncooled infrared detectors. Recently, the first room-temperature spintronic Poisson bolometer based on magnetic tunnel junctions (MTJs) was proposed and demonstrated as a promising infrared dete

Bruno de Mendonça Braga, Chris Gartland, Gilles Lancien, Pavlos Motakis

We consider the problem of whether there is a sequence of homeomorphisms $(F_k)_k$ between the unit spheres of the $k$-dimensional Banach spaces $\ell_\infty^k$ and $\ell_1^k$ which is also equi-uniformly continuous. We prove that this cannot be the case if the sequence $(F_k)_k$ either (1) does not increase support sizes (which is a property strictly weaker

Renkai Ma, Dominique Geissler, Stefan Feuerriegel, Tobias Lauinger

Social media platforms have faced increasing scrutiny over whether and how they protect youth online. While online risks to children have been well-documented by prior research, how social media platforms communicate about these risks and their efforts to improve youth safety have not been holistically examined. To fill this gap, we analyzed N=352 press rele

Seyed Moein Abtahi, Majid Fekri, Tara Khani, Akramul Azim

Modern semantic search and retrieval-augmented generation (RAG) systems rely predominantly on in-memory approximate nearest neighbor (ANN) indexes over high-precision floating-point vectors, resulting in escalating operational cost and inherent trade-offs between latency, throughput, and retrieval accuracy. This paper analyzes the architectural limitations o

Sourav Das, Aiman Khan, Elnaz Darsheshdar, Francesco Albarelli

We analytically derive the quantum state of a single-photon pulse scattered from a single quantum two-level emitter interacting with a vibrational bath. This solution for the quadripartite system enables an information-theoretic characterization of vibrational effects in quantum light spectroscopy. We show that vibration-induced dephasing reduces the quantum

Apurva Shet, Izzat Alsmadi

Zero-day vulnerabilities represent some of the most critical threats in cybersecurity, as they correspond to previously unknown flaws in software or hardware that are actively exploited before vendors can develop and deploy patches. During this exposure window, affected systems remain defenseless, making zero-day attacks particularly damaging and difficult t

Edward Y. Chang

Large Language Models exhibit sycophancy: prioritizing agreeableness over correctness. Current remedies evaluate reasoning outcomes: RLHF rewards correct answers, self-correction critiques outputs. All require ground truth, which is often unavailable at inference time and vulnerable to the same biases. We explore evaluating the reasoning process instead. Reg

Jonathan Marbey, Michael Dreyer, R. E. Butera

We present a simple home made solution enabling in-situ RF reflectometry measurements with a millikelvin scanning tunneling microscope (mk-STM). The additions described below were made using RF best practices following similar detection schemes commonly employed in the quantum information science (QIS) community. Using a Niobium STM tip to form a superconduc

Aref Farhadipour, Teodora Vukovic, Volker Dellwo, Petr Motlicek

Person identification systems often rely on audio, visual, or behavioral cues, but real-world conditions frequently present with missing or degraded modalities. To address this challenge, we propose a multimodal person identification framework incorporating upper-body motion, face, and voice. Experimental results demonstrate that body motion outperforms trad

G. Schepers, A. Belias, R. Dzhygadlo, A. Gerhardt

The Barrel DIRC counter will serve as the primary particle identification detector in the PANDA experiment, enabling high-precision hadron physics studies through antiproton-proton annihilations across a momentum range of 1.5 GeV/c to 15 GeV/c. It is designed to distinguish charged pions from kaons with a separation of at least 3 standard deviations up to 3.

Martin Bladt, Kristian Vilhelm Dinesen

We study the conditional expert Kaplan-Meier estimator, an extension of the classical Kaplan--Meier estimator designed for time-to-event data subject to both right-censoring and contamination. Such contamination, where observed events may not reflect true outcomes, is common in applied settings, including insurance and credit risk, where expert opinion is of

Hop Le, Izzat Alsmadi

The Internet of Vehicles (IoV) has evolved modern transportation through enhanced connectivity and intelligent systems. However, this increased connectivity introduces critical vulnerabilities, making vehicles susceptible to cyber-attacks such Denial-ofService (DoS) and message spoofing. This project aims to develop a machine learning-based intrusion detecti

Casey Crane, Ziad Ghanem

We investigate symmetry-breaking phenomena in semilinear elliptic systems on the unit ball in $\mathbb{R}^3$, focusing on the emergence of non-radial solution branches with prescribed spatial and internal symmetries. Extending previous scalar results, we develop a framework for systems equivariant under $G := O(3) \times \Gamma \times \mathbb{Z}_2$, where $\

Julia E. Bergner, Maxine E. Calle, David Chan, Angélica M. Osorno

We show that various categories of trees can be modeled by Grothendieck constructions on categories of trees with a fixed set of leaves. We prove this result for the dendroidal category $\Omega$, the category $\Omega^G$ of trees with a $G$-action for a finite group $G$, and finally for the category of genuine equivariant trees $\Omega_G$ that has played an i

Tetsutaro Shibata

The one-dimensional nonlocal Kirchhoff type bifurcation problems which are derived from logistic equation of population dynamics are studied. We obtain the precise asymptotic shapes of $L^2$ bifurcation curves $\lambda = \lambda(\alpha)$ as $\alpha \to \infty$, where $\alpha:= \Vert u_\lambda \Vert_2$.

Srishti Gupta, Riccardo Balia, Daniele Angioni, Fabio Brau

Recent years have witnessed significant progress in the development of machine learning models across a wide range of fields, fueled by increased computational resources, large-scale datasets, and the rise of deep learning architectures. From malware detection to enabling autonomous navigation, modern machine learning systems have demonstrated remarkable cap

Buu Phan, Ashish Khisti, Karen Ullrich

Computing next-token likelihood ratios between two language models (LMs) is a standard task in training paradigms such as knowledge distillation. Since this requires both models to share the same probability space, it becomes challenging when the teacher and student LMs use different tokenizers, for instance, when edge-device deployment necessitates a smalle

Jiawei Chen, Yifei Yu, Chaoqun Liu

Accurate subgrid-scale (SGS) modeling remains a major challenge in large eddy simulation (LES), particularly for wall-bounded turbulent flows with strong near-wall anisotropy. This study proposes a novel SGS model based on Liutex theory, featuring a dynamically adaptive model coefficient and a physics-based length-scale formulation. The magnitude of the Liut

Iddo Yehoshua Wald, Amber Maimon, Shiyao Zhang, Dennis Küster

Embodiment of users within robotic systems has been explored in human-robot interaction, most often in telepresence and teleoperation. In these applications, synchronized visuomotor feedback can evoke a sense of body ownership and agency, contributing to the experience of embodiment. We extend this work by employing embreathment, the representation of the us

Nick E. Mavromatos, Panagiotis Dorlis, Sarben Sarkar, Sotirios-Neilos Vlachos

We review a novel scenario for the emergence of spin-polarisation entangled squeezed graviton states from superradiant axionic clouds in the neighborhood of astrophysical rotating black holes (BHs). The entangled squeezed graviton states are produced by both, conventional General-Relativity (GR) type axion-gravity interactions, and gravitational Chern-Simons

Bingxue An, Tiffany M. Tang

A plethora of dimension reduction methods have been developed to visualize high-dimensional data in low dimensions. However, different dimension reduction methods often output different and possibly conflicting visualizations of the same data. This problem is further exacerbated by the choice of hyperparameters, which may substantially impact the resulting v

Geshuo Wang, Jingwei Hu

The numerical solution of kinetic equations is challenging due to the high dimensionality of the underlying phase space. In this paper, we develop a dynamical low-rank method based on the projector-splitting integrator in tensor-train (TT) format. The key idea is to discretize the three-dimensional velocity variable using tensor trains while treating the spa

Tomasz Kania, Jarosław Swaczyna

We revisit Bourgain's 1981 counterexample to the sequential completeness of the `pointwise plus domination' convergence on $\ell_1$ from the perspective of vector lattices. In this setting, we show that for sequences the associated notion of Bourgain--uo convergence coincides with ordinary order convergence. Motivated by Bourgain's construction, we introduce

Taro Hayashi, Keika Shimahara

For $a,b\geq 3$, we calculate the orders of automorphisms of smooth curves with bidegree $(a,b)$ in the product $\pp$ of the projective line $\mathbb P^1$. We identify smooth curves in $\pp$ which have automorphisms with the largest orders. In addition, we study the relationship between symmetry and geometric structure of curves. We provide a sufficient cond

Leif Albers, Jan-Malte Michaelsen, Roman Schnabel

Optical quantum computing, as well as quantum communication and sensing technology based on quantum correlations are in preparation. These require photodiodes for the detection of about 10^16 photons per second with close to perfect quantum efficiency. Already the radiometric calibration is a challenge. Here, we provide the theoretical description of the qua

Zoran Milosavljevic

MRI radiofrequency (RF) coils are ultimately limited by conductor loss, thermal noise, and reciprocity constraints associated with conventional metallic boundary conditions. These limitations become more severe at higher static fields, where operating frequencies increase and current distributions are governed by surface impedance and electromagnetic couplin

Shaoting Feng, Yuhan Liu, Hanchen Li, Xiaokun Chen

Reusing KV cache is essential for high efficiency of Large Language Model (LLM) inference systems. With more LLM users, the KV cache footprint can easily exceed GPU memory capacity, so prior work has proposed to either evict KV cache to lower-tier storage devices, or compress KV cache so that more KV cache can be fit in the fast memory. However, prior work m

David Wittman, Rodrigo Stancioli, Faik Bouhrik, Reinout van Weeren

The galaxy cluster RXC J0032.1+1808 has been well-studied with optical imaging and gravitational lensing mass maps, both of which reveal an elongated morphology in the north-south direction. We find that its X-ray morphology is bimodal, suggesting that it is in the process of merging; combined with a previously reported detection of a radio relic, we suggest

Ahmadreza Jeddi, Hakki Can Karaimer, Hue Nguyen, Zhongling Wang

RL post-training with verifiable rewards (RLVR) has become a practical route to eliciting chain-of-thought reasoning in vision--language models (VLMs), but scaling it in the visual domain remains challenging due to costly or noisy supervision and reliance on external verifiers. Puzzle-based RLVR is a promising alternative, yet existing approaches often treat

Théo Reymermier, Oleg Brandt, Anna Mullin, Paul Swallow

Despite the success of the Standard Model (SM) there remains behaviour it cannot describe, in particular the presence of non-interacting Dark Matter. Many models that describe dark matter can generically introduce exotic Long-Lived Particles (LLPs). The proposed ANUBIS experiment is designed to search for these LLPs within the ATLAS detector cavern, located

Conor Rowan, Kai Hampleman, Kurt Maute, Alireza Doostan

Since their advent nearly a decade ago, physics-informed neural networks (PINNs) have been studied extensively as a novel technique for solving forward and inverse problems in physics and engineering. The neural network discretization of the solution field is naturally adaptive and avoids meshing the computational domain, which can both improve the accuracy

Philip Korman, Yi Li

In this note we unify the results of A.C. Lazer and P.O. Frederickson [3], A.C. Lazer [6], A.C. Lazer and D.E. Leach [7], J.M. Alonso and R. Ortega [1], and P. Korman and Y. Li [4] on periodic oscillations and unbounded solutions of nonlinear equations with linear part at resonance and periodic forcing. We give conditions for the existence and non-existence

Zhenzhi Wang, Jian Wang, Ke Ma, Dahua Lin

We introduce TalkVerse, a large-scale, open corpus for single-person, audio-driven talking video generation designed to enable fair, reproducible comparison across methods. While current state-of-the-art systems rely on closed data or compute-heavy models, TalkVerse offers 2.3 million high-resolution (720p/1080p) audio-video synchronized clips totaling 6.3k

Qiaohong Wang, Mario Motta, Ruhee D'Cunha, Kevin J. Sung

Accurately and efficiently describing strongly correlated electronic systems is a central challenge in quantum computational chemistry, with classical and quantum computers. The localized active space self-consistent field method (LASSCF) uses a product of fragment active spaces as a variational space, with the Schr\"odinger equation solved exactly in each f

Nnamdi Philip Okonkwo, Lubna Luxmi Dhirani

Cloud Security Operations Center (SOC) enable cloud governance, risk and compliance by providing insights visibility and control. Cloud SOC triages high-volume, heterogeneous telemetry from elastic, short-lived resources while staying within tight budgets. In this research, we implement an AI-Augmented Security Operations Center (AISOC) on AWS that combines

Henry Adams, Florian Frick

Brouwer's fixed point theorem states that any continuous function from a closed $n$-dimensional ball to itself has a fixed point. In 1961, Klee showed that if such a function has discontinuities that are bounded, then it has a point that is close to being fixed. We improve upon Klee's results in any finite-dimensional Euclidean space, and prove that our boun

Caitlin Smith, Guillaume Renaud, Kasper van Wijk, Jami Shepherd

In this study, we develop vector flow imaging techniques for multi-layered models with a high wavespeed contrast using photoacoustic and ultrasonic imaging. We use refraction-corrected delay-and-sum image reconstruction (RC-DAS), which enforces Snell's law to accurately calculate time delays within each layer. We compare RC-DAS against conventional delay-and

Daniel Gomes de Pinho Zanco, Leszek Szczecinski, Jacob Benesty, Eduardo Vinicius Kuhn

In this work, we propose a method to efficiently find the regularization parameter for low-rank MMSE filters based on a Kronecker-product representation. We show that the regularization parameter is surprisingly linked to the problem of rank selection and, thus, properly choosing it, is crucial for low-rank settings. The proposed method is validated through

Felix Brandt, Matthias Hieber, Lin Ma, Tarek Zöchling

It is shown that a model coupling the heat-conducting compressible Navier-Stokes equations to a micro-physics model of moisture in air is locally strongly well-posed for large data in suitable function spaces and strongly well-posed on $[0,\tau]$ for every $\tau > 0$ for small initial data. This seems to be the first result on $[0,\tau]$ for arbitrary $\tau

Jaume Anguera Peris, Songtao Cheng, Hanzhao Zhang, Wei Ouyang

High-content screening microscopy generates large amounts of live-cell imaging data, yet its potential remains constrained by the inability to determine when and where to image most effectively. Optimally balancing acquisition time, computational capacity, and photobleaching budgets across thousands of dynamically evolving regions of interest remains an open

Paul J. Weiser, Jiye Kim, Jongho Lee, Amirmohammad Shamaei

Purpose: Magnetic Resonance Spectroscopic Imaging (MRSI) maps endogenous brain metabolism while suppressing the overwhelming water signal. Water-unsuppressed MRSI (wu-MRSI) allows simultaneous imaging of water and metabolites, but large water sidebands cause challenges for metabolic fitting. We developed an end-to-end deep-learning pipeline to overcome these

Ramesh Kudalippalliyalil, Gyan Prakash, Christopher Munley, Karen E. Grutter

We present an ultrasensitive technique for probing transient optical changes in atomically thin molybdenum disulfide (MoS$_2$) layers integrated onto silicon nitride (Si$_3$N$_4$) ring resonators. The MoS$_2$ is illuminated by a femtosecond laser, while a tunable near-infrared (NIR) continuous-wave laser probes the microresonator resonance. The NIR light pol

Giuseppe Buttazzo, Simone Cito, Francesco Solombrino

We consider the torsional rigidity and the principal eigenvalue related to the Laplace operator with Dirichlet and Robin boundary conditions. The goal is to find upper and lower bounds to products of suitable powers of the quantities above in the class of Lipschitz domains. The threshold exponent for the Robin case is explicitly recovered and shown to be str

Caner Erden

The quadratic computational complexity of MultiHead SelfAttention (MHSA) remains a fundamental bottleneck in scaling Large Language Models (LLMs) for longcontext tasks. While sparse and linearized attention mechanisms attempt to mitigate this, they often compromise the representation of global dependencies or fail to capture multiscale semantic granularity e

Jonas Stricker, Konstantin Gaul, Paul Fischer, Lennard M. Arndt

Multiply charged actinide molecules provide a unique platform to study fundamental physics and the chemical bond under extreme conditions. Beyond the inherently large relativistic effects associated with a high proton number $Z$, an increased molecular charge can further enhance the electronic sensitivity to symmetry-violating nuclear effects, including nucl

David Sims, Benjamin Sims, Brian Wright, John W. Lewellen

3D-printing of radiofrequency (RF) cavity resonators could provide a cost-effective solution that enables rapid prototyping and design flexibility compared to traditional fabrication of full-metal cavities. In this work, the feasibility of fabrication of a useful multi-mode GHz cavity is explored. Two kinds of plastics, two slicing approaches and two metal c

Joshua L. Ebbert, Dennis Della Corte

Artificial intelligence foundation models are increasingly deployed for prostate cancer Gleason grading, where GP3/GP4 distinction directly impacts treatment decisions. However, these models may achieve high validation accuracy by learning specimen-specific artifacts rather than generalizable biological features, limiting real-world clinical utility. We intr

Miguel Megevand

In previous work, we introduced the $\ell$-boson stars, a generalization of standard boson stars, which are parameterized by an angular momentum number $\ell$, while still preserving the spacetime's spherical symmetry. In this article, we present and study the properties of $\ell$-boson stars in spacetimes with a negative cosmological constant, such that the

Alexey Kazakov, Vladislav Koryakin, Klim Safonov, Andrey L. Shilnikov

The Lorenz attractor is the first example of a robustly chaotic non-hyperbolic attractor. Each orbit of such an attractor has a positive top Lyapunov exponent, and this property persists under small perturbations despite possible bifurcations of the attractor. In this paper, we study the boundary of the Lorenz attractor existence region in the Shimizu-Moriok

Vladimir Manuilov

We show that the inverse group of equivalence classes of metrics on two copies of a metric space is fundamental.

Changshu Liu, Alireza Ghazanfari, Yang Chen, Reyhaneh Jabbarvand

Code reasoning tasks are becoming prevalent in large language model (LLM) assessments. Yet, there is a dearth of studies on the impact of real-world complexities on code reasoning, e.g., inter- or intra-procedural dependencies, API calls, deeply nested constructs, and non-primitive complex types. Evaluating LLMs under such a simplistic setting poses a signif

Mohammed El Abdioui

This study investigates climate change impacts on Moroccan Atlantic coastal upwelling (21$^{\circ}$--35$^{\circ}$N), analyzing interrelationships among the North Atlantic Oscillation (NAO), Coastal Upwelling Index (CUI), and Sea Surface Temperature (SST) from 1978--2024 using ERA5 reanalysis data. Methods include index calculations, seasonal correlations, Gr

Gerald V. Dunne

A dispersion integral representation of the Heisenberg-Euler QED effective lagrangian is derived, with Faddeev's quantum dilogarithm as a generalized Borel kernel. The nonperturbative imaginary part of the effective lagrangian is expressed as the quantum dilogarithm, while the real part has the form of a dispersion integral involving both the quantum dilogar

Federico Achini, Paola Causin, Sara Vanini, Ke Chen

The Fast Fourier Transform (FFT) is widely used in applications such as MRI, CT, and interferometry; however, because of its dependence on uniformly sampled data, it requires the use of gridding techniques for practical implementation. The performance of these algorithms strongly depends on the choice of the gridding kernel, with the first prolate spheroidal

J. Zeng, T. Aramaki, D. Ames, K. Aoyama

The Gamma-Ray and AntiMatter Survey (GRAMS) is a next-generation experiment using a Liquid Argon Time Projection Chamber (LArTPC) detector to measure MeV gamma rays and antiparticles. MeV gamma-ray observations are important for understanding multi-messenger and time-domain astronomy, enabling exploration of the universe's most potent events, such as superno

Kleuton A. L. Lima, José A. dos S. Laranjeira, Neymar J. N. Cavalcante, Nicolas F. Martins

We present a comprehensive first-principles investigation of a novel carbon allotrope characterized by quasi-tetragonal atomic motifs and quasi-two-dimensional structural behavior. Structural analysis reveals an open framework composed of alternating diamond-like and square units, while thermodynamic assessments indicate a negative formation energy, suggesti

Nadine Angela Cantonjos, Arpita Biswas

Agricultural regions in rural areas face damage from climate-related risks, including droughts, heavy rainfall, and shifting weather patterns. Prior research calls for adaptive risk-management solutions and decision-making strategies. To this end, artificial intelligence (AI), particularly agentic AI, offers a promising path forward. Agentic AI systems consi