April 2026 arXiv papers — page 25

D. Pukazhselvan, Ihsan Caha, Francisco J. A. Loureiro, Francis Leonard Deepak

This study investigates the lithium conversion behavior of a hydrogen storage material based on vanadium oxide added magnesium hydride. To understand the chemical interaction between vanadium oxide and magnesium hydride, detailed X ray diffraction and X ray photoelectron spectroscopy analyses were performed on ball milled composites with varying compositions

Xinjie Dai, Xingyu Liu, Diancong Jin, Liying Sun

The generalized Langevin equation (GLE) constitutes a fundamental model for describing nonequilibrium dynamics with memory effects. To overcome the numerical challenges arising from superquadratically growing potentials and degenerate noise, we propose and analyze a structure-preserving splitting averaged vector field (AVF) method for a quasi-Markovian GLE.

Shirin Alanova, Bogdan Minko, Sabrina Sadiekh, Evgeniy Kokuykin

Safety mechanisms for large language models (LLMs) remain predominantly English-centric, creating systematic vulnerabilities in multilingual deployment. Prior work shows that translating malicious prompts into other languages can substantially increase jailbreak success rates, exposing a structural cross-lingual security gap. We investigate whether such atta

John P. T. Stenger, C. Stephen Hellberg, Daniel Gunlycke

We find the ground-state energy of the Ising model using the Cascaded Variational Quantum Eigensolver (CVQE) algorithm with the Guided-Sampling Ansatz (GSA) using up to 63 qubits on a quantum computer. We study a heavy-hex lattice to match the qubit architecture, allowing us to perform calculations in the quantum utility regime. We study both a homogeneous a

Shawqi Al-Maliki, Ammar Gharaibeh, Mohamed Rahouti, Mohammad Ruhul Amin

Large Language Models (LLMs) have revolutionized the field of natural language processing. However, they exhibit some limitations, including a lack of reliability and transparency: they may hallucinate and fail to provide sources that support the generated output. Retrieval-Augmented Generation (RAG) was introduced to address such limitations in LLMs. One po

Léa Loisel, Tristan Monrocq, Vincent Raquin, Pauline Ezanno

Mosquito vector competence is usually represented as a process in which once virus is detected in saliva, mosquitoes are assumed to remain infectious for life, implying an irreversible transition to the transmitting state. However, some experiments report declines in the proportion of transmitting mosquitoes at late times post-exposure, suggesting transmissi

Zeming Dong, Yuejun Guo, Qiang Hu, Yao Zhang

Source code and its accompanying comments are complementary yet naturally aligned modalities-code encodes structural logic while comments capture developer intent. However, existing vulnerability detection methods mostly rely on single-modality code representations, overlooking the complementary semantic information embedded in comments and thus limiting the

Marina Vicini, Martin Rudorfer, Zhuangzhuang Dai, Ahmad Beltagui

Gait speed is a vital health indicator for older adults, as changes in gait speed can reflect physiological and functional decline. Ambient sensors offer a promising, privacy-preserving solution for continuous in-home monitoring of gait speed; although it is often limited by methods requiring a home floor plan, which is frequently unfeasible. This paper prop

Xianghao Meng, James L. Beck, Yong Huang, Hui Li

In the last few decades, Markov chain Monte Carlo (MCMC) methods have been widely applied to Bayesian updating of structural dynamic models in the field of structural health monitoring. Recently, several MCMC algorithms have been developed that incorporate neural networks to enhance their performance for specific Bayesian model updating problems. However, a

Zhang Kai, He Xinyue, Yao Jingang

Generative search engines increasingly determine whether online information is merely discoverable, cited as a source, or actually absorbed into generated answers. This paper proposes a two-stage measurement framework for Generative Engine Optimization (GEO): citation selection, where a platform triggers search and chooses sources, and citation absorption, w

Andrew C. Burgess, David D. O'Regan

The Density Functional Theory plus Hubbard $U$ (DFT+$U$) technique is one of the most widely used tools by condensed matter physicists and solid state chemists for the simulation of transition-metal and lanthanide bearing crystals, and increasingly of much more diverse chemistries. Although often synonymous with the corrective functionals of Dudarev et al. a

Yuan-De Jin, Zheng-Fei Ye, Wen-Long Ma

We propose a general method to fully characterize a classical stochastic noise process causing qubit dephasing through repetitive Ramsey interferometry measurements (RIMs) on the qubit. Compared to filter-function-based spectroscopy, our method does not require complicated dynamical decoupling pulses and can directly detect arbitrary-order correlation functi

Konstantin Batygin, Ian R. Brunton, Alessandro Morbidelli

Mean-motion resonances are expected to frequently arise at the inner edges of protoplanetary disks, where planet-disk interactions facilitate large-scale orbital convergence. Under certain conditions, however, the same dissipative forces that promote resonant capture can drive resonant librations overstable, ultimately breaking commensurabilities. Here we ex

Deng-Shan Wang, Yingmin Yang

In 1978, A. C. Newell [SIAM J. Appl. Math. 35(4) (1978) 650-664] proposed an exactly solvable model called Newell equation, which simulates the investigation of significant interaction mechanism between long and short waves. Nearly fifty years have passed, yet the long-time asymptotics of the Newell equation remains an open problem to date, with no results r

Manaka Okuyama, Masayuki Ohzeki

We consider a class of gauge glass models with Gaussian disorder on the Nishimori line, including the Ising spin glass, the $XY$ gauge glass, the $Z_q$ gauge glass, and the gauge-invariant Potts model. We prove that the first and second Griffiths inequalities hold for these models on arbitrary lattice structures. As a consequence, both the pressure and the c

Georgy Sofronov, Joanna Rymaszewska, Krzysztof J. Szajowski

Our research is closely related to ontological studies in mathematics. It provides crucial insights into the nature of decisions and strategies characterized by Markov moments. In a stopping game, a holistic decision-maker would evaluate comprehensive information by assessing the probabilities of various outcomes and their associated payoffs. This involves u

Yefan Zhi, Yao Lu, Masoud Akbarzadeh

Symmetry is an implicit objective in structural form-finding that often reconciles efficiency and aesthetics. This paper identifies the symmetry of polyhedral diagrams in three-dimensional graphic statics (3DGS) as point groups and formulates them as constraints, enabling the optimization and manipulation of polyhedral diagrams that preserve such symmetry. 3

Nitin Kaloya, Kuldeep Suthar

We examine the two-dimensional spin-orbit-coupled bosons in the presence of an anisotropic dipolar interaction in square lattices. The spin-orbit coupling leads to finite-momentum superfluid and supersolid states, while the nearest-neighbour interaction induces crystalline characteristics in the quantum phases of soft-core bosons. We employ site-decoupled Gu

Kerstin Jordaan, Vikash Kumar

We investigate completed interlacing of zeros for pairs of polynomial sequences that fail to interlace by exactly two points. Using suitable mixed recurrence relations, we identify two additional points, called the completion points, required to obtain completed interlacing and establish general results for polynomials with real zeros. We also show that comp

Leonie Heller, Christopher Taube, Gledson Rodrigo Tondo, Guido Morgenthal

The time-dependent deformation of concrete, particularly creep, remains a key challenge for reliable and material-efficient design. Experimental results show that tailored preloading, short-term loads exceeding the subsequent sustained load, can reduce both the magnitude and variability of creep strains which may be associated with beneficial microstructural

Thomas A. Grossman, Yuan Chen, Sopiko Datuashvili

This paper investigates how GPT-based tools can assist in building reusable analytical spreadsheet models. After a screening, we evaluate five GPT extensions and select Excel AI by pulsrai.com for detailed testing. Through structured experiments on simple problem statements, we assess Excel AI's performance against the ERFR criteria (each input in a cell; ce

Dewei Bai, Hongxiang Peng, Jiajun Mei, Yang Ren

Binary spike coding enables sparse and event-driven computation in spiking neural networks (SNNs), yet its 1-bit-per-timestep representation fundamentally limits information throughput. This bottleneck becomes increasingly restrictive in deep architectures under short simulation horizons. We propose the Quantized Burst-LIF (QB-LIF) neuron, which reformulates

Christophe Parisel

We present a unified quantitative analysis of the Currier A/B language distinction in the Voynich Manuscript, proceeding in two stages. First, we confirm that the distinction is genuine: a Beta-Binomial mixture model applied to character-pair substitution ratios across 185 folios, without access to Currier's labels, selects 2 by BIC and predicts held-out fol

Shih-Jie Huang, Meng-Ru Wu

In dense neutrino gas, pairing correlations between neutrinos and antineutrinos with opposite momenta can be nonzero in generalized neutrino quantum kinetic equations at the mean-field level. In this Letter, we investigate for the first time the condition under which collective neutrino-antineutrino ($\nu\bar\nu$) pairing instabilities can occur, using simpl

Noe Angelo Caruso

This article contains the first steps in a general analysis of the problem of Krylov solvability of the inverse linear problem in a Banach space. In contrast to the well-studied Hilbert space setting, the Banach space setting presents particular difficulties in creating the connection between Krylov solvability and structural properties of the Krylov subspac

Sanghati Basu

Foundation segmentation models such as the Segment Anything Model (SAM) have demonstrated strong generalization across natural images; however, their robustness under clinically realistic medical imaging domain shifts remains insufficiently quantified. We present a systematic slice-level robustness audit of SAM (ViT-B) for spleen segmentation in abdominal CT

Eranga Bandara, Ross Gore, Asanga Gunaratna, Sachini Rajapakse

The rapid deployment of autonomous AI agents across enterprise, healthcare, and safety-critical environments has created a fundamental governance gap. Existing approaches, runtime guardrails, training-time alignment, and post-hoc auditing treat governance as an external constraint rather than an internalized behavioral principle, leaving agents vulnerable to

Chen Yifei, Tian Zhixing, Wang Chenyang, Cheng Ziguang

This paper targets e-commerce search relevance. While Large Language Models (LLMs) have demonstrated significant potential in this field, they often encounter performance bottlenecks in persistent 'corner cases' within complex industrial scenarios. Existing research primarily focuses on optimizing reasoning trajectories via Reinforcement Learning. However, r

Damir Latypov

Antenna miniaturization remains a critical technological challenge across frequency scales - from microwave RF links in phones and wearables to VLF for underwater-to-air communications and ionospheric probing. At deeply subwavelength scales conventional antennas require complex and lossy matching circuits due to absent intrinsic material resonances, motivati

Ashutosh Dhamaniya, Anup Kumar Gupta, Trishna Saikia, Puneet Gupta

Unaddressed pain in neonates can lead to adverse effects, including delayed development and slower weight gain, emphasising the need for more objective and reliable pain assessment methods. Hence, automated methods using behavioural and physiological pain indicators have been developed to aid healthcare professionals in the Neonatal ICU. Traditional contact-

CMS Collaboration

A measurement of the eight angular polarization coefficients, $A_0$ to $A_7$, in the cross section for the Drell$-$Yan production of two muons is presented. The analysis is based on proton-proton (pp) collision data recorded with the CMS detector at the LHC at a center-of-mass energy of $\sqrt{s}$ = 13 TeV, corresponding to an integrated luminosity of 140 fb

Nayeon Lee, Jiwoo Song, Byeongcheol Kang

Multilingual retrieval-augmented generation (mRAG) is often implemented within a fixed retrieval space, typically via query or document translation or multilingual embedding vector representations. However, this approach may be inadequate for culturally grounded queries, in which retrieval-condition misalignment may occur. Even strong retrievers and generato

Benjamin Buralli, Mamadou N'Diaye, Raphaël Pourcelot, Marcel Carbillet

We investigate the stability of a segmented deformable mirror (DM) on high-contrast testbeds and its impact on the images produced with coronagraphs. Segmented apertures are promising to obtain large primary mirrors for future missions with starlight suppression capabilities. Cophased at the sub-nanometer level, segments can be slightly misaligned by small d

Yuqing Zhang, Ecesu Ürker, Tessa Verhoef, Gemma Boleda

Modeling the emergence of human-like lexicons in computational systems has advanced through the use of interacting neural agents, which simulate both learning and communicative pressures. The NeLLCom-Lex framework (Zhang et al., 2025) allows neural agents to develop pragmatic color naming behavior and human-like lexicons through supervised learning (SL) from

Yu-Xuan Bai, Jin Hao, Zhi-Hui Guo

In this work we explore the semileptonic $\tau$ decays into the axion-like particle ($a$)-meson final states within chiral effective field theory. The next-to-leading-order mixing matrix for the $\pi^0$-$\eta$-$\eta'$-$a$ system with the linear isospin-breaking effects, is exploited and then implemented to calculate the hadronic form factors relevant to the

Kieran Maguire, Srinandan Dasmahapatra

Prior work on node classification has shown that Graph Neural Networks (GNNs) can learn representations that transfer across graphs, when underlying graph properties are shared. For a fixed graph, one would then expect GNNs trained for link prediction to learn a representation consistent with that learnt for node classification. We show this intuition does n

Namita Behera, Dilli Ram Chhetri, Raj Bhawan Yadav

In this paper, we investigate arithmetical structures on Cartesian product graphs, particularly, ladder graph of the form P2\square Pm and grid graph of the form Pn \square Pm. An arithmetical structure on a finite and connected graph G is a pair (d, r) of positive integer vectors such that r is primitive (the gcd of its entries is 1) and (diag(d) - A)r = 0,

Miroljub Mihailovic, Luca Tonin, Stefano Tortora, Emanuele Menegatti

Reliable estimation of neuromuscular activation is a key enabler for adaptive and personalized control in wearable robotics. However, surface electromyography (EMG) remains difficult to deploy robustly outside laboratory settings due to electrode sensitivity, signal non-stationarity, and strong subject dependence. In this work, we propose an adaptive IMU-to-

Siran Li

We show that finite-energy weak solutions to the incompressible Navier--Stokes equations on a three-dimensional bounded smooth domain are regular up to the boundary, provided that the $L^4_tL^4_x$-norm of the solution is smaller than a constant depending only on the domain. This answers a problem raised in [D. Albritton, T. Barker, and C. Prange, J. Math. Fl

Johannes Brutsche, Lukas Riepl

Based on discrete observations, we develop a test to infer if the volatility function $\sigma(\cdot)$ within the nonparametric Gaussian white noise model $dY_t = \sigma(t)dW_t$ is constant. The testing procedure is shown to be minimax-optimal and adaptive for infill asymptotics and these results entail that a deviation from the null hypothesis of constancy i

Jesper Larsson Träff

Parallel scan primitives compute element-wise inclusive or exclusive prefix sums of input vectors contributed by $p$ consecutively ranked processors under an associative, possibly expensive, binary operator $\oplus$. In message-passing systems with bounded, one-ported communication capabilities, at least $\lceil\log_2 p\rceil$ or $\lceil\log_2 (p-1)\rceil$ s

Jinyi Liu, Lijun Liu, Shuming Cheng, Xiaomin Hu

Single-photon light detection and ranging (LiDAR) extends active three-dimensional sensing at the fundamental level and has found applications in extreme environments involving long-range operation, low-reflectance targets, and adverse visibility. However, the acquired measurements often give rise to single-photon point clouds that are sparse, spatially non-

Sharmin Afroz, Brendan Ames

Sparse Optimal Scoring (SOS) reformulates linear discriminant analysis to enable feature selection through elastic net regularization, making it well-suited for high-dimensional settings where the number of features exceeds observations. Most existing SOS methods use deflation-based strategies that compute discriminant vectors sequentially, which can propaga

Dimitrios Maroulakos, Andrzej Wal, Marcin Kowalik, Czesław Jasiukiewicz

Entropic uncertainty relations are universal quantifiers of fundamental uncertainties of quantum measurements and are widely discussed in the quantum metrology literature. Quantum memory is a phenomenon related to the specific type of quantum correlations that allows for reducing fundamental uncertainties of quantum measurements. In the present work, the mod

Roman Novikov, Tianli Xu

We continue studies on phase retrieval for continuous and discrete Fourier transforms in multidimensions. Using finite difference operators, we give a large class of unexpected examples of non-uniqueness for this problem, including examples with the sparsity condition. A prototype of this construction in the continuous case is given in the work Novikov, Xu (

Wenzhi Bai, Yituo Guo, Bhaskar Basu, Andrew Weightman

Robot-assisted Transcranial Magnetic Stimulation (Robo-TMS) is an image-guided robotic intervention that enhances the accuracy and reproducibility of conventional Transcranial Magnetic Stimulation (TMS), a widely used non-invasive brain stimulation procedure in clinical treatment and neuroscience research. Despite its potential, the development of Robo-TMS r

P. Alsina-Bolívar, I. Iriarte-Zendoia, D. B. Bucher, J. Casanova

To meet the growing demand for nanoscale surface analysis, nitrogen-vacancy (NV) centers offer a high-sensitivity alternative by leveraging their ability to operate in immediate proximity to the sample. In this work, we propose a quantum control protocol designed to overcome the inherent challenges of solid-state environments, specifically by mitigating anis

Nilavra Pathak, Olivier Jeunen, Eric Lambert

Organizations routinely make strategic budget allocations under operational constraints, but often lack a principled way to assess whether realized allocations were close to the best feasible choices in hindsight. We present a retrospective auditing framework based on hindsight regret, defined as the opportunity cost of the realized allocation relative to a

Wei Ma, Dengpan Ma, Zhiheng Lv, Zhifeng Liu

Electrical control of spin and magnetic sublattice degrees of freedom is essential for multifunctional and low-power spintronic devices. Bipolar altermagnetic semiconductors (BAMSs)-characterized by opposite spin polarizations at the valence and conduction band edges-offer such control, yet known systems require external strain and sizable valley polarizatio

Sijia Liu, Hoi Ching Silvester Mok, Long Ling, Tobias Klein

Chinese ceramic-making involves complex and interdependent steps, making it technically demanding. Digital fabrication methods attempt to make the process more accessible, but for craft-creators, technical challenges such as CAD and CAM skills remain major obstacles. To address this, we designed a hybrid workflow that integrates Generative AI with clay 3D pr

Jiaye Wu, Xuanyi Liu, Marco Clementi, Shuang Qiu

Epsilon-near-zero (ENZ) photonic media exhibit extreme optical dispersion that enables unconventional light-matter interactions and enhanced optical nonlinearities. Recent studies suggested that thermo-optic effects, traditionally regarded as slow and secondary, can be strongly modified under the ENZ condition. Here we establish thermo-optic reconfiguration

Yuhe Bai, Chengli Tan, Jiaqi Li, Xiangjun Wang

Nonlinear dynamical systems with regime transitions are typically described by ordinary differential equations with jumping parameters parameters. Traditional methods often treat change-point detection and parameter estimation as separate tasks, ignoring the inherent coupling between them. To address this, we propose residual-loss anomaly analysis of physics

António Branco, João Silva, Nuno Marques, Luis Gomes

Although the cultural (mis)alignment of Large Language Models (LLMs) has attracted increasing attention -- often framed in terms of cultural bias -- until recently there has been limited work on the design and development of datasets for cultural assessment. Here, we review existing approaches to such datasets and identify their main limitations. To address

B. Y. Irureta-Goyena, B. Altieri, J. -P. Kneib, M. Pöntinen

The Euclid Ecliptic Survey was conducted during the calibration phase of the mission, 23-31 December 2023, as a campaign to study Solar System objects. We used data from this survey to analyse more than 23 000 appeareances of 2321 known asteroids. Due to their high apparent angular motion relative to the background stars (5-$60^{\prime\prime}\,\mathrm{h}^{-1

Shakeel Gavioli-Akilagun, Yining Chen, Flavio Ziegelmann

We study the problem of estimating locations in time at which the level of technology in an economy changes when given a sequence of time ordered inputs and outputs. We approach the problem through the lens of nonparametric frontier analysis with frontiers that expand sharply and globally over time, and develop an offline change point detection procedure whi

Abdullah Mughees, Gaadha Sudheerbabu, Tanwir Ahmad, Dragos Truscan

We propose a human in the loop approach for black-box testing of Functional Mock-up Units (FMUs) using Large Language Models (LLMs). The goal is to reduce the manual effort in defining test scenarios for dynamic simulation models and to improve the interpretability of results. The approach takes the functional and interface specifications of an FMU as input,

Chloé Desvaux, Rania Abdelghani, Pierre-Yves Oudeyer, Hélène Sauzéon

This chapter examines the relationship between curiosity and metacognition as critical drivers of autonomous and self-regulated learning. We synthesize recent research to propose a unified framework integrating behavioral, computational, and psychoeducational dimensions, arguing that curiosity, i.e. the intrinsic drive to acquire new knowledge, relies fundam

Ténéman Keita, Renaud Belmont, Thierry Stolarczyk

Defined as the magnetic field permeating cosmic voids, the Intergalactic Magnetic Field (IGMF) is thought to be a relic of the Big Bang, tracing a primordial magnetic seed at the origin of all astrophysical fields. Yet, it has thus far escaped detection. Lower limits on the IGMF strength can be established by observing very high-energy (VHE) photons from ext

Arkadev Ghosh, S. S. Kannan

Let $G=PSL(n,\mathbb{C})$. Let $T$ be a maximal torus of $G$. Let $\omega_{r}$ denote the $r^{th}$ fundamental weight. Let $\mathcal{L}(n\omega_{r})$ denote the line bundle on the Grassmannian $G_{r,n}$ associated to the character $n\omega_{r}$ of $T$. In an earlier work of Kannan and Sardar, it is proved that there is a unique minimal dimensional Schubert v

Alessandro Berti, Francesco Ghisoni

Efficient quantum state preparation is a critical component in quantum algorithms that process large classical data, and it is fundamental to realizing quantum advantage in domains such as machine learning, quantum linear algebra, and quantum finance. Building on the framework of~\cite{berti2025efficient}, which integrates Bucket Brigade QRAM (BBQRAM) with a

Tobias Breiten, Justus Ramme, Jesper Schröder

A polynomial approximation of the minimum energy estimator, also called Mortensen observer, is discussed. The method relies on successive differentiations of an underlying value function and the Hamilton-Jacobi-Bellman equation, respectively. By means of neglecting higher order derivatives of the value function along the unknown observer trajectory, a couple

Chengsheng Zhang, Chenghao Sun, Xinyan Jiang, Wei Li

Large Vision-Language Models (LVLMs) have achieved remarkable progress in visual-textual understanding, yet their reliability is critically undermined by hallucinations, i.e., the generation of factually incorrect or inconsistent responses. While recent studies using steering vectors demonstrated promise in reducing hallucinations, a notable challenge remain

Yunyun Feng, Chenhong Cao, Si Chen, Wei Gong

5G backscatter communication presents an emerging energy-efficient IoT connectivity solution with enhanced availability and data rate advantages over traditional wireless networks. For 5G backscatter, synchronization is crucial as it ensures high-quality transmission. Popular synchronization methods employ autocorrelation and cross-correlation for accurate t

Hinata Yokoyama, Kengo Anzai, Dina Syverud-Lindland, Yoshihito Kuno

We study a random unitary quantum circuit with only reset channels, which has high feasibility for real quantum devices. In particular, we investigate the many-body statistical physics properties, "reset-induced" entanglement phase transitions comparing the classical statistical picture in the large "$d$" limit of qudits. In the property of the reset-induced

Harry Collins, Hartmut Grote, Paul Newbury, Patrick Sutton

This paper is under review in AI and Ethics This study examines whether large language models (LLMs) can reliably answer scientific questions and demonstrates how easily they can be influenced by fringe scientific material. The authors modified custom LLMs to prioritise knowledge in selected fringe papers on the Fine Structure Constant and Gravitational Wave

Xuanchi Zhou, Xiaohui Yao, Wentian Lu, Chunwei Yao

Deciphering the complicated interplay between collective and separate behaviors lies at the heart of first-order metal-insulator transition (MIT) in correlated electron systems, enabling the rational design of exotic electronic states and functionalities. The critical balance between collective and separate behaviors defines a fundamental collective length s

Jiayi Guo, Linqing Wang, Jiangshan Wang, Yang Yue

Unified multimodal models (UMMs) integrate visual understanding and generation within a single framework. For text-to-image (T2I) tasks, this unified capability allows UMMs to refine outputs after their initial generation, potentially extending the performance upper bound. Current UMM-based refinement methods primarily follow a refinement-via-editing (RvE) p

Jax Wysong, Samara Overvaag, Hyun Lim, Jung-Han Kimn

We explore the nonlinear dynamics of classical field theories containing ghost degrees of freedom, focusing on two coupled scalar fields with opposite kinetic terms in (1+1) and (2+1) dimensional Minkowski spacetime. Using a spacetime finite element formulation, we perform a systematic numerical study across a broad class of initial data. We find that ghost-

Alex Bogdan, Adrian de Valois-Franklin

We report a striking statistical regularity in frontier LLM outputs that enables a CPU-only scoring primitive running at 2.6 microseconds per token, with estimated latency up to 100,000$\times$ (five orders of magnitude) below existing sampling-based detectors. Across six contemporary models from five independent vendors, two generation sizes, and five held-

Qiong Li, Christopher J. Conselice, Lewi Westcott, Duncan Austin

We study how environment affects the mass-metallicity relation (MZR) at $z=4$-$10$ using deep imaging and spectroscopy from the James Webb Space Telescope (JWST). Combining CEERS and JADES, we compile a sample of 225 galaxies with stellar masses, star-formation rates, and gas-phase metallicities. We characterize environment using the projected fifth-nearest-

Sreeraj Rajindran Nair, Christopher Ferrie

A key bottleneck in quantum machine learning is the computational cost of repeated quantum circuit evaluations during the inference phase. To address this, we present a framework for constructing fast, cheap, provably accurate classical tensor-train surrogates of fully trained quantum machine learning models within local patches of their input data space. Th

Si-Wei Liu, Wen-Tao Lyu, Ju-Jun Xie

We investigate the femtoscopic correlation functions of systems associated with the $\Omega(2012)$, $\Omega(2380)$, and $\Omega_c(3120)$ resonances, with the aim of elucidating their internal structures. By employing effective potential models that incorporate both $s$-wave and $d$-wave interactions, we calculate the correlation functions for the relevant co

Faizuddin Ahmed, Edilberto O. Silva

We investigate the thermodynamics, criticality, and selected radiative and optical properties of an Euler-Heisenberg AdS black hole surrounded by quintessence, perfect fluid dark matter, and a cloud of strings. Within the extended phase-space formalism, we derive the thermodynamic quantities, verify the modified first law and Smarr relation, and analyze the

Jessica Newman, Benjamin Plummer

We study positional properties in the context of game-based reactive synthesis. Our motivation stems from having a usable specification logic, for which tractable synthesis is guaranteed. We demonstrate that every $ω$-regular positional property (with respect to state- or edge-labelled game graphs), is expressible in linear-time temporal logic. Additionally,

Alessandro Razza, Guillermo A. Blanc, Brent Groves, Enrico Congiu

We present PHANGS-H{\alpha}, a narrow-band imaging survey that maps H{\alpha} emission over a sample of 65 nearby massive star-forming galaxies. The data were obtained using the MPG-ESO 2.2-meter telescope at La Silla and the du Pont 2.5-meter telescope at Las Campanas Observatory, in the framework of the multi-wavelength cloud-scale (50-100 pc) resolution m

Md Ashraful Alam, Md Abdul Hadi Shah, F. Parvin, S. H. Naqib

In this work, a comprehensive first-principles investigation of the structural, hydrogen storage potential, electronic, elastic, mechanical, thermophysical, superconducting, and optical properties of Mg2TmH6 (Tm = Rh, Pd, Ir, Pt) hydrides is presented. Obtained results demonstrate that Mg2TmH6 hydrides combine favorable hydrogen storage, mechanical robustnes

Aaron Dayton, Kiana Gallagher, Sarah E. Huber, Thomas E. Baker

Making new methods for quantum problems often relies on using basic operations in linear algebra. Often these routines are hidden behind well-known libraries that have been optimized over decades. Attempting to improve on those basic routines would be highly time-consuming. We aim in this article to review those basic routines and provide a knowledge foundat

Chong-Xin Gan, Peter Bell, Man-Wai Mak, Zhe Li

The joint training of speech enhancement and speaker embedding networks for speaker recognition is widely adopted under noisy acoustic environments. While effective, this paradigm often fails to leverage the generalization and robustness benefits inherent in large-scale speech enhancement pre-training. Moreover, maintaining the speaker information in the den

Paula Apollonia Wunderlich, Gledson Rodrigo Tondo, Guido Morgenthal

With the rapid advancement of computer technologies enabling fast calculations of complex structures, numerical methods have become a central tool in engineering sciences, while physical models have increasingly receded into the background. Nevertheless, owing to their clarity and comprehensibility, these former engineering tools remain of great value and th

Alexander Hock, Olivier Marchal, Nicolas Orantin

One of the most important applications of topological recursion concerns spectral curves for which the functions $(x,y)$ defining the spectral curve are allowed to have logarithmic singularities. This occurs for instance for Seiberg-Witten curves and mirror curves computing Gromov--Witten invariants of toric Calabi--Yau threefolds. A recently introduced exte

Zhenxing Dai, Menglin Huang, Xin-Gao Gong, Shiyou Chen

Platinum (Pt) is widely used for carrier-lifetime control in silicon power devices, yet the microscopic nonradiative recombination mechanism of the substitutional platinum ($\text{Pt}_\text{Si}$) dopant remains debated. Using first-principles calculations combined with nonradiative multiphonon theory, we systematically investigate the electronic structures a

Daria Ruzhitskaya, Irina Zhluktova, Anastasiya Ponosova, Fedor Ushakov

The security of quantum key distribution (QKD) systems relies on the physical integrity of their components. While laser-damage attacks (LDAs) using high-power continuous-wave (cw) lasers have been well studied, the threat posed by pulsed lasers at alternative wavelengths remains underestimated. Here, we experimentally investigated the stability of four type

Zhaoyan Pan, Hengyang Zhou, Xiangdong Li, Yuning Wang

Conversational multimodal understanding aims to infer the meaning or label of the current utterance from its preceding dialogue context together with textual, acoustic, and visual signals. Existing methods mainly strengthen contextual modeling through enhanced encoding, fusion, or propagation, but rarely abstract the context-utterance dependency into an expl

Archisman Ghosh, Avimita Chatterjee, Swaroop Ghosh

Fault-tolerant quantum computing (FTQC) is emerging as the architectural regime in which practical large-scale quantum workloads will execute. In this setting, however, multiprogramming is no longer a matter of partitioning a flat pool of qubits. Quantum error correction exposes a structured floorplan of data tiles, ancilla tiles, and magic-state service res

Amirali Shateri, Zhiyin Yang, Yuying Yan, Manosh C. Paul

Recent advances in combustion science have led to the generation of large volumes of data from high-fidelity simulations, detailed chemical-kinetic calculations and engine-relevant measurements and create new opportunities for data-driven modelling across interacting physical and chemical scales. Among these approaches, artificial intelligence has emerged as

Fulin Chen, Binyong Sun, Chuyun Wang

In a previous paper, we introduce and study formal manifolds, which generalize smooth manifolds. In this paper, we establish the basic theory of formal Lie groups, which are group objects in the category of formal manifolds. In particular, extending the classical formal Lie theory theorem, we prove that the category of formal Lie groups is equivalent to the

Thibaut Pollet, Victor Guilloux, Duc-Duy Tran, Anton Pishchagin

Scalable optical quantum technologies require interference between large numbers of indistinguishable single-photons emitted by independent sources. Semiconductor quantum dots are known to be excellent on-demand sources of single-photons. They show record efficiency when inserted into optical cavities to control their spontaneous emission and generate trains

Yafeng Wu, Yunyao Zhang, Liliang Ye, Guiyi Zeng

Online comments play a crucial role in shaping public sentiment and opinion dynamics on social media. However, evaluating their popularity remains challenging, not only because it depends on linguistic quality, originality, and emotional resonance, but also because stylistic preferences vary widely across platforms and user groups, causing the same comment t

Sayantan Pramanik, M Girish Chandra

In this paper, we resolve an open question in the field of optimization algorithms for training parametrized quantum circuits: Does the popular Rotosolve algorithm converge? Until now, interpolation-based coordinate descent methods such as Rotosolve have mostly been treated as heuristics, lacking any formal convergence guarantees. We rigorously analyze Rotos

Sherzod Turaev, Mary John, Jaloliddin Rustamov, Zahiriddin Rustamov

Understanding learners' cognitive and affective states underpins adaptive educational systems and effective teaching. Although research links nonverbal cues to internal states, no framework calibrates them to evidence. We present the Nonverbal Syntax Framework, drawn from a systematic review of 908 studies and 17,043 cue-state mappings (Turaev et al., 2026).

Erfan Ramezani, Mohammad Mahdi Giahi, Mohammad Erfan Zarabadipour, Amir Reza Yosefian

Real-time automatic speech recognition (ASR) systems face a fundamental trade-off between transcription accuracy and computational efficiency, particularly when deploying large-scale transformer models like Whisper. Existing streaming approaches either sacrifice accuracy through aggressive chunking or incur prohibitive memory costs through unbounded context

Luis Mantilla Calderón, Jérôme F. Gonthier, Ignacio Gustin, Varinia Bernales

Artificial intelligent language-model based coding agents have significantly changed the way we interact with computers in our day-to-day, as it is common to use them to create, improve, and run programming scripts only using natural language. Agent code updates can be better guided when such programs can be executed and scored automatically rather than judg

P. Adhikari, M. G. Boulay, R. Crampton, D. Gallacher

Radon is one of the most important sources of background in rare event search experiments, such as those searching for Dark Matter and neutrinos, due to its unavoidable production from natural uranium. In low-background experiments, radon emanation from detector materials and components accounts for a major portion of contamination. To investigate this, a ra

Victor Mangeleer, Luc Vandenbulcke, Marilaure Grégoire, Gilles Louppe

Coastal hypoxia (O_2 < 63 [mmol / m^3]) threatens ocean health worldwide. On continental shelves, summer stratification prevents bottom oxygen consumed by respiration from being renewed, making monitoring essential to protect vulnerable ecosystems and reduce biodiversity loss. Although satellite observations are increasingly available, their potential to inf

Yun-Hua Chen, Meng-Lin Du, Feng-Kun Guo

We present a unified analysis of the $Z_c(3900)$ and $Z_{cs}(3985)$ states considering both experimental and lattice data. The study simultaneously includes the processes $e^+e^- \rightarrow J/\psi \pi^+\pi^-, J/\psi K^+ K^-, D^0 D^{\ast-} \pi^+, (D^{\ast 0} D_s^{-}+D^0 D_s^{\ast -}) K^+$, together with finite-volume energy levels from recent lattice QCD sim

CMS Collaboration

A search for supersymmetric electroweakinos is performed using events with a low-momentum (soft) isolated track and large missing transverse momentum, targeting nearly mass-degenerate higgsino-like charginos and neutralinos. For mass splittings of 0.3$-$1 GeV, the chargino decays to the lightest neutralino and a low-momentum pion, which can produce a soft, p

Jakub Martinka, Mahesh Kumar Sit, Pavlo O. Dral, Jiří Pittner

Surface hopping (SH) methods are typically employed to simulate ultrafast nonadiabatic processes, but long timescales often remain beyond their reach. To address this, accelerated SH scheme mitigate this limitation by scaling the driving forces of such process, either nonadiabatic couplings (NACs) in case of internal conversion or spin-orbit couplings (SOCs)

Junxing Hu, Tianlong Li, Lei Yu, Ai Han

Deploying production-ready multi-agent systems (MAS) in complex industrial environments remains challenging due to limitations in scalability, observability, and autonomous evolution. We present OxyGent, an open-source framework driven by two core novelties: a unified Oxy abstraction and the OxyBank evolution engine. The unified abstraction encapsulates agen

Lara Vartziotis, Tina Vartziotis, Frank Beutenmueller, Stella Salta

In remote and hybrid work contexts, the integration of physical and digital environments is revolutionizing spatial experiences, collaboration, and interpersonal interactions. This study examines three fundamental spatial conditions: the physical environment, characterized by material and sensory attributes; the virtual environment, influenced by immersive t

Sagy Ephrati, Erik Jansson

The minimum-enstrophy theory of Bretherton and Haidvogel postulates that two-dimensional turbulent systems evolve to a state that minimises enstrophy at a fixed energy level. We extend this to the rotating spherical quasi-geostrophic setting, accounting for bottom topography and the fully nonlinear Coriolis effect, resulting in latitude-dependent effects not