December 2025 arXiv papers — page 105

Yu. A. Shibanov, A. V. Karpova, D. A. Zyuzin, M. R. Gilfanov

Using the data from the all-sky survey in soft X-rays performed by the eROSITA telescope onboard the Spectrum-Roentgen-Gamma observatory we identified known radio and $\gamma$-ray pulsars in the eastern half of the sky. As a result, new candidate counterparts were found for twelve pulsars of different ages and types at a $\gtrsim$ 3$\sigma$ confidence level.

Zehan Zhu, Heng Zhao, Yan Huang, Joey Tianyi Zhou

In this paper, we propose a Differentially Private Stochastic Gradient Push with Compressed communication (termed DP-CSGP) for decentralized learning over directed graphs. Different from existing works, the proposed algorithm is designed to maintain high model utility while ensuring both rigorous differential privacy (DP) guarantees and efficient communicati

Paul G. Beck

Red giants are increasingly used as stellar population tracers due to their well-understood evolution and the availability of asteroseismic observables. However, stellar binarity can alter observable properties and introduce strong biases. We aim to provide a holistic picture of the binary population and its evolution in the red giant phase by characterizing

Michael Williams de la Bastida, Thomas M. Bickley, Peter V. Coveney

Simulation of fermionic Hamiltonians with gate-based quantum computers requires the selection of an encoding from fermionic operators to quantum gates, the most widely used being the Jordan-Wigner transform. Many alternative encodings exist, with quantum circuits and simulation results being sensitive to choice of encoding, device connectivity and Hamiltonia

Mathias Hilfiker, Leonardo Medrano Sandonas, Alexandre Tkatchenko, Ola Engkvist

Free energy calculations are widely used tools in computational chemistry, but their dependence on the assignment of partial charges during force field parametrization reduces their accuracy and reproducibility. In this work, we highlight the direct connection between the low accuracy of AM1-BCC charges on polar species and the poor accuracy of corresponding

Lokendra Kumar, Neelesh S. Upadhye, Kannan Piedy

The efficient allocation of human resources is a critical concern in software development and other industries. This paper introduces a rigorous mathematical methodology for task assignment, employing Mixed Integer Linear Programming (MILP) to ensure both balanced workloads and cost minimization. The proposed model systematically integrates individual employ

Dorian Koch, Albert Zeyer, Nick Rossenbach, Ralf Schlüter

Denoising language models (DLMs) have been proposed as a powerful alternative to traditional language models (LMs) for automatic speech recognition (ASR), motivated by their ability to use bidirectional context and adapt to a specific ASR model's error patterns. However, the complexity of the DLM training pipeline has hindered wider investigation. This paper

Habibollah Safari, Mona Bavarian

Predicting monomer reactivity ratios is crucial for controlling monomer sequence distribution in copolymers and their properties. Traditional experimental methods of determining reactivity ratios are time-consuming and resource-intensive, while existing computational methods often struggle with accuracy or scalability. Here, we present a method that combines

Mauricio Cataldo, Antonella Cid, Pedro Labraña

This article explores the cosmological scenario in which our Universe contains a hidden thin-shell configuration. We investigate a degenerate modification of the Friedmann-Robertson-Walker metric obtained through a coordinate transformation applied to the radial coordinate, analogous to recent approaches that address the Big Bang singularity via spacetime de

Payaswinee Arvikar, Sakshi Gautam, Anagh Venneti, Sarmistha Banik

We perform a comparative Bayesian analysis of fermionic and bosonic dark matter admixed neutron stars (DMANS) by incorporating a comprehensive set of theoretical, experimental, and astrophysical constraints. The hadronic matter equation of state (EoS) is modeled using a relativistic mean-field approach, constrained by chiral effective field theory ($\chi$EFT

Tao Zhang, Ziqi Zhang, Zongyang Ma, Yuxin Chen

The ability to perform multi-modal multi-hop reasoning by iteratively integrating information across various modalities and external knowledge is critical for addressing complex real-world challenges. However, existing Multi-modal Large Language Models (MLLMs) are predominantly limited to single-step reasoning, as existing benchmarks lack the complexity need

I. I. Gimazov, D. E. Zhelezniakova, R. B. Zaripov, Yu. I. Talanov

We report results of electron spin resonance (ESR) measurements in single crystals of EuSn$_2$As$_2$. In the temperature range of antiferromagnetic (AFM) ordering of Eu atoms, $T \leq T_N\approx 24$\,K, the ESR signal splits into two resonance lines, one of which, at high-field (or low-frequency), is the conventional acoustic AFM resonance mode that occurs a

Chiara Barà, Yuri Antonacci, Laura Sparacino, Ariosky Areces Gonzalez

Complex networks often exhibit emergent behaviors, where simple dyadic interactions yield collective dynamics that cannot be explained by examining the system's units individually or in pairs. Understanding how redundant and synergistic interaction emerges from elementary connectivity patterns is important in characterizing the behavior of physical, biologic

Suvas Chandra Chaudhary, Raj Prince, Brian van Soelen, I. P. van der Westhuizen

In the innermost regions of active galactic nuclei, where the accretion disk, corona, and jet processes are closely coupled, X-ray observations offer a direct probe to study the physics of disk-jet coupling and the mechanisms driving relativistic outflows. We present a comprehensive analysis of the X-ray timing and spectral variability of 16 Narrow Line Seyf

Leonard Bereska, Zoe Tzifa-Kratira, Reza Samavi, Efstratios Gavves

Neural networks achieve remarkable performance through superposition: encoding multiple features as overlapping directions in activation space rather than dedicating individual neurons to each feature. This challenges interpretability, yet we lack principled methods to measure superposition. We present an information-theoretic framework measuring a neural re

Henry Phillip Fried, Daniel Barragan-Yani, Ludger Wirtz

We present a detailed study of common intrinsic defects in CuInS$_2$ and CuGaS$_2$ using the Heyd, Scuseria and Ernzerhof (HSE) hybrid functional scheme. The impact of the two HSE parameters, $\alpha$ and $\omega$ on the band gap and compliance with the generalized Koopmans' theorem is investigated. Using the formation energy formalism and calculated thermod

Dor Minzer

We show a procedure that, given oracle access to a function $f\colon \{0,1\}^n\to\{0,1\}$, produces oracle access to a function $f'\colon \{0,1\}^{n'}\to\{0,1\}$ such that if $f$ is monotone, then $f'$ is monotone, and if $f$ is $\varepsilon$-far from monotone, then $f'$ is $\Omega(1)$-far from monotone. Moreover, $n' \leq n 2^{O(1/\varepsilon)}$ and each or

Junye Du, Zhenghao Li, Zhutong Gu, Long Feng

This paper tackles the problem of feature selection in a highly challenging setting: $\mathbb{E}(y | \boldsymbol{x}) = G(\boldsymbol{x}_{\mathcal{S}_0})$, where $\mathcal{S}_0$ is the set of relevant features and $G$ is an unknown, potentially nonlinear function subject to mild smoothness conditions. Our approach begins with feature selection in deep neural

Yuyang Hu, Shichun Liu, Yanwei Yue, Guibin Zhang

Memory has emerged, and will continue to remain, a core capability of foundation model-based agents. As research on agent memory rapidly expands and attracts unprecedented attention, the field has also become increasingly fragmented. Existing works that fall under the umbrella of agent memory often differ substantially in their motivations, implementations,

Ugo de Noyers, Björn Herrmann

We present an exploratory study of the freeze-in mechanism within a scotogenic framework, where dark matter can either be a scalar singlet or a fermion singlet. Based on a random parameter scan, we show that large portions of the parameter space feature a dark matter relic density in agreement with the limits derived by Planck. Moreover, constraints related

Li-Wei Shih, Ruo-Syuan Mei, Jesse Heidrich, Hui-Ping Wang

Near-field perception is essential for the safe operation of autonomous mobile robots (AMRs) in manufacturing environments. Conventional ranging sensors such as light detection and ranging (LiDAR) and ultrasonic devices provide broad situational awareness but often fail to detect small objects near the robot base. To address this limitation, this paper prese

Shun Maeda, Chunzhi Gu, Koichiro Kamide, Katsuya Hotta

Human-centric anomaly detection (AD) has been primarily studied to specify anomalous behaviors in a single person. However, as humans by nature tend to act in a collaborative manner, behavioral anomalies can also arise from human-human interactions. Detecting such anomalies using existing single-person AD models is prone to low accuracy, as these approaches

Gibson Nkhata, Uttamasha Anjally Oyshi, Quan Mai, Susan Gauch

Verifying rumors on social media is critical for mitigating the spread of false information. The stances of conversation replies often provide important cues to determine a rumor's veracity. However, existing models struggle to jointly capture semantic content, stance information, and conversation strructure, especially under the sequence length constraints

Miguel G. Rodriguez, Yun-Pil Shim

Pairwise exchange couplings have long been the standard mechanism for entangling spin qubits in semiconductor systems. However, implementing quantum circuits based on pairwise exchange gates often requires a lengthy sequence of elementary gate operations. In this work, we present an alternative approach: multi-qubit entangling gate operations that simultaneo

Gabriel Ellemund, Thomas Hübner, Quentin Lété, Stefano Bracco

Bidding flexibility in day-ahead and intraday auctions would enable decentralized flexible resources, such as electric vehicles and heat pumps, to efficiently align their consumption with the intermittent generation of renewable energy. However, because these resources are individually too small to participate in those auctions directly, an aggregator (e.g.,

Sadie Lipman

In 2006, Boyarchenko and Drinfeld conjectured that for a unipotent algebraic group over a field of positive characteristic, every geometric point is contained in the neutral connected component of its centralizer if and only if its $\mathbb{L}$-packets of character sheaves are singletons. In 2013, Boyarchenko proved the "only if" direction for $\overline{\ma

Daniel Galicer, Julián Haddad, Joaquín Singer

The classical Busemann-Petty problem asks whether smaller central hyperplane sections of origin-symmetric convex bodies necessarily imply smaller total volume. Zvavitch studied this question for arbitrary measures with continuous even densities, providing sufficient conditions for affirmative cases in terms of the distributional behavior of the ratio between

Paul Ophardt, Francesca Badaracco, Katharina-Sophie Isleif

Newtonian noise (NN) from seismic density fluctuations is expected to limit the low-frequency sensitivity of third-generation gravitational-wave detectors, in particular the Einstein Telescope (ET). Current NN mitigation relies on seismometer arrays and Wiener filtering, while distributed acoustic sensing (DAS) offers a complementary, low-cost means of obtai

Thomas Mutschler, Greta Villa, Oded Zilberberg

Recent topological tools offer a powerful way to classify how phases of nonlinear bosonic resonators are organized. Yet, they remain incomplete. In particular, self-sustained oscillations in the form of limit cycles act as robust organizing centers in phase space that are not captured by existing fixed-point-based approaches. In this work, we extend the flow

Ramin Rezvani Gilkolae

This paper presents a hardware-conscious analysis of the quantum acceleration of the classical 3-round Keccak-256 preimage attack using Grover's Algorithm. While the theoretical quantum speed-up from T_cl=2^{57.8} (classical) to T_qu = 2^{28.9} (quantum) is mathematically sound, the practical implementation overhead is so extreme that attacks remain wholly i

Hour Kaing, Raj Dabre, Haiyue Song, Van-Hien Tran

This work introduces {\it PrahokBART}, a compact pre-trained sequence-to-sequence model trained from scratch for Khmer using carefully curated Khmer and English corpora. We focus on improving the pre-training corpus quality and addressing the linguistic issues of Khmer, which are ignored in existing multilingual models, by incorporating linguistic components

Meng Sun, Hongbo Xia, Seth Gossage, Vicky Kalogera

We present a systematic comparison between the tidal secular evolution timescales predicted by the direct numerical method and those given by the commonly used semi-analytic prescriptions implemented in 1-D hydrostatic binary evolution codes. Our study focuses on binary systems with intermediate- to high-mass primaries ($M_1 = 5$-$50\,M_\odot$), companion ma

Juan Felipe Huan Lew-Yee, Ion Mitxelena, Jorge M. del Campo, and Mario Piris

In this work, we present the second version of the Donostia Natural Orbital Functional Software, an open-source program for natural orbital functional calculations. The new release incorporates improved optimization algorithms, capabilities for excited-state computations, support for ab initio molecular dynamics, and integration with the libcint library. DoN

Hidetaka Manabe, Takanori Sugimoto, Keisuke Fujii

Verifying quantum advantage for practical problems, particularly the ground state energy estimation (GSEE) problem, is one of the central challenges in quantum computing theory. For that purpose, dequantization algorithms play a central role in providing a clear theoretical framework to separate the complexity of quantum and classical algorithms. However, ex

Nghia Nguyen-Trung, Quoc Tran-Dinh

In this paper, we develop a novel accelerated fixed-point-based framework using delayed inexact oracles to approximate a fixed point of a nonexpansive operator (or equivalently, a root of a co-coercive operator), a central problem in scientific computing. Our approach leverages both Nesterov's acceleration technique and the Krasnosel'skii-Mann (KM) iteration

Cong Zhang, Yin-Kai Yu, Shao-Hang Shi, Zi-Xiang Li

We present the sign-problem-free quantum Monte Carlo study of the half-filled Hubbard model on two-dimensional quasicrystals, revealing how specific aperiodic geometries fundamentally dictate quantum criticality. By comparing the Penrose and Thue-Morse quasicrystals, we demonstrate that the nature of the magnetic phase transition is controlled by the electro

Yuxin Yang, Hang Zhou, Hourong Song, Branislav Hredzak

Ever since R.D.Middlebrook proposed the state space averaging notion. The small signal model has been widely used as a design tool to tune control parameters. As Moore's law is continuing and the AI chip's high demand for power consumption and dynamic response, the control bandwidth needs to be boosted. However, the average model has two basic assumptions: t

Adam Smith, Maria Mylova, Carsten van de Bruck, C. P. Burgess

Axio-dilaton cosmology provides a minimal benchmark model for both Dark Matter (DM) and Dark Energy (DE) that is well motivated by fundamental physics. The axion and dilaton arise as pseudo-Goldstone modes of symmetries that predict particle masses depend on the dilaton, and therefore to evolve cosmologically, leading to correlated modifications of recombina

Ricardo E. da Silva, Hartmut Bartelt, Cristiano M. B. Cordeiro

We experimentally demonstrate laser-driven deposition of single-walled carbon nanotubes (CNTs) in suspended core fibers (SCFs) for the first time. Two samples for each SCF type with three (SCF1) and four (SCF2) air holes are individually inserted in a syringe loaded with a 0.5 mL solution of CNTs dispersed in methanol, and a high-power laser at 980 nm is inj

Tom Anders, Hiten Prakash Kothari, R. Michael Buehrer

In many signal processing applications, including communications, sonar, radar, and localization, a fundamental problem is the detection of a signal of interest in background noise, known as signal detection [1] [2]. A simple version of this problem is the detection of a signal of interest with unknown parameters in Additive White Gaussian Noise (AWGN). When

Núria Navarro, Ana-Maria Raclariu

We revisit the quantization of a free scalar in 4-dimensional (4d) Lorentzian Anti-de-Sitter spacetime (AdS$_4$). We derive solutions to the wave equation that diagonalize time translations in a foliation of AdS$_4$ with null cones. We show that time-translation eigenmodes of arbitrary mass fields that admit a flat space limit must contain both normalizable

A. S. Moskvin, Yu. D. Panov

The insulator-quasi-metal (bad metal) transition observed in Jahn-Teller (JT) magnets orthonickelates RNiO$_3$ (R = rare earth, or yttrium Y) is considered a canonical example of the Mott transition, traditionally described in the framework of Hubbard's $U-t$ model. However, in reality, the insulating phase of nickelates is the result of charge disproportion

Saghar Vosough, Gian Candrian, Johannes Kasper, Hossam Abdel Rehim

Attention-deficit/hyperactivity disorder (ADHD) is characterized by executive dysfunction and difficulties in processing emotional facial expressions, yet the large-scale neural dynamics underlying these impairments remain insufficiently understood. This study applied network-based EEG source analysis to examine oscillatory cortical activity during cognitive

Victor Khomenko, Maciej Koutny, Alex Yakovlev

Being able to find small Petri nets with the same behaviour as formal specifications of concurrent systems benefits both effective verification and practical implementation of such systems. This paper considers specifications given in the form of compositionally defined safe nets. The paper discusses a novel concept of distributed place which implements the

Dylan Bansard-Tresse

We study quantitative recurrence to rare events in Countable Markov Shifts with recurrent potentials, focusing on return-time statistics to natural target sets for every point. In the positive recurrent case, return-time processes associated with non-periodic points converge to a standard Poisson process, while those for periodic points converge to a compoun

Antonin Chodron de Courcel

We establish local-in-time existence and uniqueness results for nonlocal conservation laws with a nonlinear mobility, in several space dimensions, under weak assumptions on the kernel, which is assumed to be bounded and of finite total variation. Contrary to the linear mobility case, solutions may develop shocks in finite time, even when the kernel is smooth

Marianne Rakic, Siyu Gai, Etienne Chollet, John V. Guttag

A single biomedical image can be meaningfully segmented in multiple ways, depending on the desired application. For instance, a brain MRI can be segmented according to tissue types, vascular territories, broad anatomical regions, fine-grained anatomy, or pathology, etc. Existing automatic segmentation models typically either (1) support only a single protoco

Hiten Prakash Kothari, R. Michael Buehrer

Building on the previous work on interference mitigation, this paper introduces a modular recommender system that automatically selects the most effective interference mitigation strategy based on the interference characteristics present in the received signal. The system integrates three key stages: an SPS classifier module, a SIR predictor, and a bank of s

Anshima Singh, David J. Silvester

An adaptive sampling approach for efficient detection of bifurcation boundaries in parametrized fluid flow problems is presented herein. The study extends the machine-learning approach of Silvester~(J. Comput. Phys., 553 (2026), 114743), where a classifier network was trained on preselected simulation data to identify bifurcated and nonbifurcated flow regime

Johas Morales, Yuri Bonder

One of the main technical obstacles in constructing a consistent theory of quantum gravity is that the metric itself defines the causal structure required for quantization. This motivates implementing quantum aspects of gravity through an independent connection. Moreover, the experimentally confirmed violation of Bell inequalities, together with the natural

Shih-Ni Prim, Kevin R. Quinlan, Paul Hawkins, Jagadeesh Movva

Contour location---the process of sequentially training a surrogate model to identify the design inputs that result in a pre-specified response value from a single computer experiment---is a well-studied active learning problem. Here, we tackle a related but distinct problem: identifying the input configuration that returns pre-specified values of multiple c

Raj Sahu, Saumen Maiti

Enhanced lithological interpretation from well logs plays a key role in geological resource exploration and mapping, as well as in geo-environmental modeling studies. Core and cutting information is useful for making sound interpretations of well logs; however, these are rarely collected at each depth due to high costs. Moreover, well log interpretation usin

Jialong Deng

We prove that every locally conformally flat metric on a closed, oriented hyperbolic 4-manifold with scalar curvature bounded below by -12 satisfies Schoen's conjecture. We also classify all closed Riemannian 4-manifolds of positive scalar curvature that arise as total spaces of fibre bundles. For a closed locally conformally flat 4-manifold with scalar curv

Mohammed S. M. Elbaz

Purpose: To develop DarkSPARC, a retrospective, training-free, self-calibrated spectral reconstruction method that converts routine bright-blood 3D left atrial (LA) late gadolinium enhancement (LGE) MRI into a dark-blood image, and to quantify its impact on LA scar-pool CNR, SNR, effective CNR (eCNR), and scar quantification accuracy. Methods: DarkSPARC embe

Asa Cooper Stickland, Jan Michelfeit, Arathi Mani, Charlie Griffin

LLM-based software engineering agents are increasingly used in real-world development tasks, often with access to sensitive data or security-critical codebases. Such agents could intentionally sabotage these codebases if they were misaligned. We investigate asynchronous monitoring, in which a monitoring system reviews agent actions after the fact. Unlike syn

Zhexiang Zhang, Ye Wang, Yumiao Zhao, Jiayu Xiao

Serving large Mixture-of-Experts (MoE) models is challenging because of their large memory footprints, heterogeneous resource demands, and highly dynamic inference workloads. Most existing MoE inference systems deploy the entire model as a monolithic unit, forcing attention and MoE layers to share the same resource configuration despite their different scali

Kishan Kumar Ganguly, Tim Menzies

Much of Software Engineering (SE) research assumes that progress depends on massive datasets and CPU-intensive optimizers. Yet has this assumption been rigorously tested? The counter-evidence presented in this paper suggests otherwise. For over 100 optimization tasks from recent SE papers (including software configuration, performance tuning, product line en

Alonso Beaumont

Let $f$ be a dominant endomorphism of the projective line, which is not conjugate to a power map $z\mapsto z^{\pm d}$. We consider the centralizers of the iterates of $f$, $C(f^{n}):=\{\textrm{dominant}\;g:\mathbb{P}^{1}\rightarrow\mathbb{P}^{1}\;|\; g\circ f^{n}=f^{n}\circ g\}$, $n\geq1$, and prove that their union is equal to $C(f^{N})$ for some $N\geq1$.

Abhishek Ghadai, Sayantan Majumdar

Materials driven far from equilibrium can encode memories of past deformations through long-lived structural reorganisations. Such memory effects-reflecting parameters such as deformation direction, magnitude, and duration have been widely explored in soft amorphous solids. Here, we report a Kovacs-like memory effect manifested as a non-monotonic stress rela

Ian J. Maquignaz

Accurate environment maps are a key component for rendering photorealistic outdoor scenes with coherent illumination. They enable captivating visual arts, immersive virtual reality, and a wide range of engineering and scientific applications. Recent works have extended sky-models to be more comprehensive and inclusive of cloud formations but, as we demonstra

Amadou Sy, Masseye Gaye

The topological dynamics of the horocyclic flow $h_{\mathbb{R}}$ on the unit tangent bundle of a geometrically finite hyperbolic surface is well known. In particular, on such a surface, the flow $h_{\mathbb{R}}$ is minimal, or the minimal sets are the periodic orbits. When the surface is geometrically infinite, the situation is more complex, and the presence

Lavakumar Addepalli

Multi-photon lasing has been realized in systems with strong nonlinear interactions between emitters and cavity modes, where single-photon processes are suppressed. Coherence between the internal states of a quantum emitter, or among multiple emitters, plays a key role. Such continuous nonclassical sources of light can find applications in quantum computatio

Giada Basile, Dario Benedetto

We introduce a ``two-particle factorization'' condition which allows us to formulate the homogeneous Boltzmann equation for non-reversible collision kernels in terms of an entropy inequality. This formulation yields an H-Theorem. We provide some examples of non-reversible binary collision models with a concentration/dispersion mechanism, as in opinion dynami

Oleg Grynets, Vasyl Lyashkevych, Dmytro Baran, Maksym Orliansky

The study presents the outcomes of research and experimental validation in the domain of automated codebase migration, with a focus on addressing challenges in transitioning SQL-based systems. The proposed method for migration essentially appears as a framework that leverages the best aspects of traditional software engineering techniques and provides an ite

Aman Arora, Matteo El-Hariry, Miguel Olivares-Mendez

Autonomous free-flyers play a critical role in intravehicular tasks aboard the International Space Station (ISS), where their precise docking under sensing noise, small actuation mismatches, and environmental variability remains a nontrivial challenge. This work presents a reinforcement learning (RL) framework for six-degree-of-freedom (6-DoF) docking of JAX

Akshansh Mishra

Accurate prediction of temperature evolution is essential for understanding thermomechanical behavior in friction stir welding. In this study, molecular dynamics simulations were performed using LAMMPS to model aluminum friction stir welding at the atomic scale, capturing material flow, plastic deformation, and heat generation during tool plunge, traverse, a

Chandrasekhar Gokavarapu

Classical spectral graph theory relies on the symmetry of the adjacency and Laplacian operators, which guarantees orthogonal eigenbases and energy-preserving Fourier transforms. However, real-world networks are intrinsically directed and asymmetric, resulting in non-normal operators where standard orthogonality assumptions fail. In this paper, we develop a r

Huaiyuan Xiao, Fadi Dornaika, Jingjun Bi

The advent of graph convolutional network (GCN)-based multi-view learning provides a powerful framework for integrating structural information from heterogeneous views, enabling effective modeling of complex multi-view data. However, existing methods often fail to fully exploit the complementary information across views, leading to suboptimal feature represe

Piyush Bagad, Andrew Zisserman

Our objective is to build an embedding model that captures the nuanced relationship between a search query and candidate videos. We cover three aspects of nuanced retrieval: (i) temporal, (ii) negation, and (iii) multimodal. For temporal nuance, we consider chiral actions that need distinguishing between temporally opposite actions like "opening a door&#

Linjie Mu, Yannian Gu, Zhongzhen Huang, Yakun Zhu

Large language models with reasoning capabilities have demonstrated impressive performance across a wide range of domains. In clinical applications, a transparent, step-by-step reasoning process provides physicians with strong evidence to support decision-making. While reinforcement learning has effectively enhanced reasoning performance in medical contexts,

Rodrigo F. Saliba, Raphael C. Drumond

In recent years, the quantum Mpemba effect (QME), which occurs when an out-of-equilibrium system reaches equilibrium faster than another that is closer to equilibrium, has attracted significant attention from the scientific community as an intriguing and counterintuitive phenomenon. It generalizes its classical counterpart by extending the concept beyond tem

A. Behring, J. Blümlein, A. De Freitas, A. von Manteuffel

The twist-2 heavy-quark and antiquark distributions, as defined in the variable flavor number scheme, turn out to be different due to QCD corrections from three-loop onward. This is caused by terms containing the color factor $d_{abc} d^{abc}$ in the heavy-flavor massive pure-singlet operator matrix elements (OMEs) $A^{\rm PS, s, (3)}_{Qq}$ for odd moments i

Team Seedance, Heyi Chen, Siyan Chen, Xin Chen

Recent strides in video generation have paved the way for unified audio-visual generation. In this work, we present Seedance 1.5 pro, a foundational model engineered specifically for native, joint audio-video generation. Leveraging a dual-branch Diffusion Transformer architecture, the model integrates a cross-modal joint module with a specialized multi-stage

Henry Prakken, Wijnand van Woerkom

In recent years, hierarchical case-based-reasoning models of precedential constraint have been proposed. In various papers, Trevor Bench-Capon criticised these models on the grounds that they would give incorrect outcomes in some cases. In particular, the models would not account for the possibility that intermediate factors are established with different st

Ankit Anand, Kimet Jusufi, Spyros Basilakos, Emmanuel N. Saridakis

We investigate how deviations from the Bekenstein-Hawking entropy modify black-hole spacetimes through the recently proposed entropy-geometry correspondence. For four representative modified entropies, namely Barrow, R\'enyi, Kaniadakis, and logarithmic, we derive the corresponding effective metrics and analyze their thermodynamic and topological classificat

Ruslan Seifullaev, André M. H. Teixeira

This paper investigates the performance of networked control systems subject to multiplicative routing transformations that alter measurement pathways without directly injecting signals. Such transformations, arising from faults or adversarial actions, modify the feedback structure and can degrade performance while remaining stealthy. An $H_2$-norm framework

Emmanuel Dartois, Jennifer A. Noble, Jennifer B. Bergner, Klaus M. Pontoppidan

Edge-on discs offer a unique opportunity to probe radial and vertical dust and gas distributions in the protoplanetary phase. This study aims to investigate the distribution of micron-sized dust particles in the Flying Saucer (BKLT J162813-243139) in Rho Ophiuchi, leveraging the unique observational conditions of a bright infrared background that enables the

MohammadJavad Kazemi, MohammadHossein Barati, Ghadir Jafari, S. Shajidul Haque

The question of how to interpret and compute arrival-time distributions in quantum mechanics remains unsettled, reflecting the longstanding tension between treating time as a quantum observable or as a classical parameter. Most previous studies have focused on the single-particle case in the far-field regime, where both approaches yield very similar arrival-

Sabrine Ennaji, Elhadj Benkhelifa, Luigi Vincenzo Mancini

Machine learning based intrusion detection systems are increasingly targeted by black box adversarial attacks, where attackers craft evasive inputs using indirect feedback such as binary outputs or behavioral signals like response time and resource usage. While several defenses have been proposed, including input transformation, adversarial training, and sur

Li Qiwei, Katelyn Kennon, Nicole Bedera, Asia A. Eaton

Non-consensual intimate imagery (NCII), also known as image-based sexual abuse (IBSA), is mediated through online platforms. Victim-survivors must turn to platforms to collect evidence and request content removal. Platforms act as the crime scene, judge, and jury, determining whether perpetrators face consequences and if harmful material is removed. We prese

Jan W. Cholewa, Anibal Rodriguez-Bernal

We consider evolution equation with fractional Schr\"odinger operators in Morrey spaces. We prove order preserving properties of the associated semigroup in Morrey scale. We prove monotonicity of the semigroup with respect to Morrey's potentials and give some precise estimates of its exponential growth. We show that Arendt and Batty's type condition on the p

E. F. Lewis, M. A. McLaughlin, J. K. Swiggum, H. Blumer

We present the timing solutions for three radio pulsars discovered with the Green Bank North Celestial Cap (GBNCC) and 350-MHz Green Bank Telescope drift-scan surveys. These pulsars were initially discovered through their single-pulse emission and therefore designated as rotating radio transients (RRATs). Follow-up timing campaigns yielded a number of higher

Haoyu Ren, Kay Koehle, Kirill Dorofeev, Darko Anicic

In modern manufacturing, Visual Anomaly Detection (VAD) is essential for automated inspection and consistent product quality. Yet, increasingly dynamic and flexible production environments introduce key challenges: First, frequent product changes in small-batch and on-demand manufacturing require rapid model updates. Second, legacy edge hardware lacks the re

Jiangning Zhang, Junwei Zhu, Zhenye Gan, Donghao Luo

We propose a multimodal-driven framework for high-fidelity long-term digital human animation termed $\textbf{Soul}$, which generates semantically coherent videos from a single-frame portrait image, text prompts, and audio, achieving precise lip synchronization, vivid facial expressions, and robust identity preservation. We construct Soul-1M, containing 1 mil

Yu-Chen Lu, Sheng-Feng Yu, Hui-Hsien Weng, Pei-Shuo Wang

Large language models (LLM) have achieved remarkable performance across a wide range of tasks. However, their substantial parameter sizes pose significant challenges for deployment on edge devices with limited computational and memory resources. Low-rank compression is a promising approach to address this issue, as it reduces both computational and memory co

Soojeong Lee, Michael States, Keegan R. Bunker, Ryan J. Caverly

This paper presents prototype testing and a control allocation algorithm for the Cable-Actuated Bio-inspired Lightweight Elastic Solar Sail (CABLESSail) concept aimed at performing momentum management of a solar sail. CABLESSail uses actuated cables routed along the structural booms of the solar sail to control the shape of the solar sail and changes the sol

Jiangning Zhang, Junwei Zhu, Teng Hu, Yabiao Wang

Native 4K (2160$\times$3840) video generation remains a critical challenge due to the quadratic computational explosion of full-attention as spatiotemporal resolution increases, making it difficult for models to strike a balance between efficiency and quality. This paper proposes a novel Transformer retrofit strategy termed $\textbf{T3}$ ($\textbf{T}$ransfor

Arnab Seth, Fay Borhani, Itamar Kimchi

In this work we extend our study of the effect of certain crystallographic defects on the spin-1/2 Kitaev honeycomb spin liquid (arXiv:2511.19409), focusing on its gapless phase and contrasting with the gapped phase. We identify a Stone-Wales (SW) local defect consisting of a 90$^\circ$ bond rotation that preserves Kitaev bond labels for edge-sharing octahed

A. D. Schwope, T. R. Marsh, S. G. Parsons, J. Vogel

We present an analysis of high-speed u- and r-band photometry of the eclipsing polar HU Aquarii that was obtained with ULTRACAM mounted on the VLT. The observations were performed during a low state, permitting us for the first time to determine the contact points of the white dwarf. Using LCURVE we could determine its size, and hence mass, with a direct met

Lei Qu, Lianhai Ren, Peng Cheng, Rui Gao

An increasing variety of AI accelerators is being considered for large-scale training. However, enabling large-scale training on early-life AI accelerators faces three core challenges: frequent system disruptions and undefined failure modes that undermine reliability; numerical errors and training instabilities that threaten correctness and convergence; and

Ayon Roy, Risat Rahaman, Sadat Shibly, Udoy Saha Joy

Bangla is the sixth most widely spoken language globally, with approximately 234 million native speakers. However, progress in open-source Bangla machine translation remains limited. Most online resources are in English and often remain untranslated into Bangla, excluding millions from accessing essential information. Existing research in Bangla translation

Yao Xie, Walter Cullen

Major AI ethics guidelines and laws, including the EU AI Act, call for effective human oversight, but do not define it as a distinct and developable capacity. This paper introduces human oversight as a well-being capacity, situated within the emerging Well-being Efficacy framework. The concept integrates AI literacy, ethical discernment, and awareness of hum

Julia Lamprecht, Izzy L. Garland, Daniel Jadlovsky, Jiri Zak

In this white paper we focus on compact stellar systems, star clusters, nuclear star clusters (NSCs), stripped nuclei, and ultra-compact dwarfs (UCDs), as engines of galaxy evolution and black-hole growth. We show how the same capability also enables transformative science in active galactic nucleus (AGN) fuelling, stellar surfaces and interacting binaries,

Andreas Zmija, Gisela Anton, Christopher Ingenhuett, Alison Mitchell

The closure phase, the sum of the three Fourier phases in a telescope triangle, is an important tool in astronomical interferometry, helping to reconstruct the geometries of the observed objects. While already established in amplitude interferometry, for the recently expanding field of intensity interferometers the closure phase enables recovering informatio

K. B. Alkalaev, V. S. Khiteev

We show that Feynman diagrams in AdS$_2$ space can be decomposed into infinite series of matrix elements of Wilson line network operators. The case of the 3-point scalar Feynman diagram with endpoints in the bulk is studied in detail. The resulting decomposition is similar to the conformal block decomposition of Witten diagrams, i.e. it comprises a single-tr

Ruslan Seifullaev, André Teixeira

Networked control systems (NCSs) are vulnerable to faults and hidden malfunctions in communication channels that can degrade performance or even destabilize the closed loop. Classical metrics in robust control and fault detection typically treat impact and detectability separately, whereas the output-to-output gain (OOG) provides a unified measure of both. W

Wenyi Liu, R. Sharma, W. "Grace" Guo, J. Yi

Digital twin (DT) enables smart manufacturing by leveraging real-time data, AI models, and intelligent control systems. This paper presents a state-of-the-art analysis on the emerging field of DTs in the context of milling. The critical aspects of DT are explored through the lens of virtual models of physical milling, data flow from physical milling to virtu

Arnav Ramamoorthy, Shrey Dhorajiya, Ojas Pungalia, Rashi Upadhyay

Envy shapes competitiveness and cooperation in human groups, yet its role in large language model interactions remains largely unexplored. As LLMs increasingly operate in multi-agent settings, it is important to examine whether they exhibit envy-like preferences under social comparison. We evaluate LLM behavior across two scenarios: (1) a point-allocation ga

Maksymilian Szorc

Fully connected layers are a primary source of memory and computational overhead in deep neural networks due to their dense, often redundant parameterization. While various compression techniques exist, they frequently introduce complex engineering trade-offs or degrade model performance. We propose the Parametrized Random Projection (PRP) layer, a novel app

Kunal Pai, Harshil Patel, Erin Le, Noah Krim

Reproducibility in simulation-based computer architecture research requires coordinating artifacts like disk images, kernels, and benchmarks, but existing workflows are inconsistent. We improve gem5, an open-source simulator with over 1600 forks, and gem5 Resources, a centralized repository of over 2000 pre-packaged artifacts, to address these issues. While