November 2025 arXiv papers — page 131

Minbo Gao, Zhengfeng Ji, Chenghua Liu

Simulation of open quantum systems is an area of active research in quantum algorithms. In this work, we revisit the connection between Markovian open-system dynamics and averages of Hamiltonian real-time evolutions, which we refer to as Hamiltonian twirling channels. By applying the L\'evy-Khintchine representation theorem, we clarify when and how a dissipa

Davide Giacopello, Maddalena Bonanzinga, Piotr Szewczak

A topological space is totally paracompact if any base of this space contains a locally finite subcover. We focus on a problem of Curtis whether in the class of regular Lindel\"of spaces total paracompactness is equivalent to the Menger covering property. To this end we consider topological spaces with certain dense subsets. It follows from our results that

Oliver Dippel, Alexei Lisitsa, Bei Peng

Transformers have demonstrated exceptional in-context learning (ICL) capabilities, enabling applications across natural language processing, computer vision, and sequential decision-making. In reinforcement learning, ICL reframes learning as a supervised problem, facilitating task adaptation without parameter updates. Building on prior work leveraging transf

Yongji Zhang, Siqi Li, Yue Gao, Yu Jiang

Action Quality Assessment (AQA) aims to evaluate and score sports actions, which has attracted widespread interest in recent years. Existing AQA methods primarily predict scores based on features extracted from the entire video, resulting in limited interpretability and reliability. Meanwhile, existing AQA datasets also lack fine-grained annotations for acti

Fabian Ihle, Moritz Flüchter, Michael Menth

Time-sensitive networking (TSN) is a set of IEEE standards that extends Ethernet with real-time capabilities. Among its mechanisms, the time-aware shaper (TAS) periodically opens and closes egress queues to protect scheduled traffic from lower-priority flows, ensuring low latency and bounded delay. Deterministic networking (DetNet), standardized by the IETF,

Rinieri Lorenzo, Gori Giacomo, Melis Andrea, Girau Roberto

The OPC UA protocol is becoming the de facto standard for Industry 4.0 machine-to-machine communication. It stands out as one of the few industrial protocols that provide robust security features designed to prevent attackers from manipulating and damaging critical infrastructures. However, prior works showed that significant challenges still exists to set u

Liu Yang, Ryomei Takabayashi, Hiroki Moriguchi, Hikaru Kodama

Ultraprecision machining offers a powerful route to dispersion control in crystalline microresonators, allowing the design of waveguide geometries for tailoring the spectrum of microresonator frequency combs. By precisely designing the geometry, both group-velocity and higher-order dispersions can be engineered across a broad wavelength range. However, despi

Chao-Fan Wang, Han Ge, Jun-Yang Chen, Liusuo Wu

The quantum geometric tensor (QGT) unifies the Berry curvature (its imaginary part) and the quantum metric (its real part), yet Raman studies of chiral phonons have so far accessed only the former. We perform circularly polarized Raman spectroscopy on the quantum magnet K2Co(SeO3)2, where the field-odd chiral splitting and the field-even center-frequency shi

Rizal Khoirul Anam

The proliferation of digital media necessitates robust methods for copyright protection and content authentication. This paper presents a comprehensive comparative study of digital image watermarking techniques implemented using the spatial domain (Least Significant Bit - LSB), the frequency domain (Discrete Fourier Transform - DFT), and a novel hybrid (LSB+

Vincent Schilling, Akshat Dubey, Georges Hattab

Peptide classification tasks, such as predicting toxicity and HIV inhibition, are fundamental to bioinformatics and drug discovery. Traditional approaches rely heavily on handcrafted encodings of one-dimensional (1D) peptide sequences, which can limit generalizability across tasks and datasets. Recently, protein language models (PLMs), such as ESM-2 and ESMF

Hongzheng Wu, Ge Sun, Jing Lu, Lan Zhou

We study the single-photon scattering in a one-dimensional (1D) waveguide coupled to one transition of a $V$-type giant atom (GA), whose other transition is coherently driven by an classical field. The inelastic scattering of single photons by the GA realizes the single-photon frequency conversion. By applying the Lippmann-Schwinger equation, the scattering

Ruizhi Wang, Weibing Deng

This paper presents a space-time finite element method (FEM) based on an unfitted mesh for solving parabolic problems on moving domains. Unlike other unfitted space-time finite element approaches that commonly employ the discontinuous Galerkin (DG) method for time-stepping, the proposed method employs a fully coupled space-time discretization. To stabilize t

Jinxuan Li, Yi Zhang, Jian-Fang Hu, Chaolei Tan

Spatio-Temporal Video Grounding (STVG) aims to localize a spatio-temporal tube that corresponds to a given language query in an untrimmed video. This is a challenging task since it involves complex vision-language understanding and spatiotemporal reasoning. Recent works have explored weakly-supervised setting in STVG to eliminate reliance on fine-grained ann

Minbae Park, Hyemin Yang, Jeonghyun Kim, Kunsoo Park

Large Language Models (LLMs) demonstrate strong reasoning capabilities but struggle with hallucinations and limited transparency. Recently, KG-enhanced LLMs that integrate knowledge graphs (KGs) have been shown to improve reasoning performance, particularly for complex, knowledge-intensive tasks. However, these methods still face significant challenges, incl

Reza Rahimi Baghbadorani, Sergio Grammatico, Peyman Mohajerin Esfahani

We propose an adaptive accelerated smoothing technique for a nonsmooth convex optimization problem where the smoothing update rule is coupled with the momentum parameter. We also extend the setting to the case where the objective function is the sum of two nonsmooth functions. With regard to convergence rate, we provide the global (optimal) sublinear converg

Y. R. Lin, S. M. Wang, W. Nazarewicz

Nuclear radius is a fundamental structural observable that informs many properties of atomic nuclei and nuclear matter. Experimental studies of radii in drip line nuclei are in the forefront of research with radioactive ion beams. Of particular interest are charge radii of proton-unbound nuclei that will soon be approached in laser spectroscopy. In this Lett

Carina Boyallian, Jose I. Liberati

We define a functor from the category of Lie conformal algebras to the category of differential Lie coalgebras, which associates to any Lie conformal algebra $L$ a differential Lie coalgebra $L^{\,0}$, defined as the maximal good $\mathbb{C}[\partial]$-submodule of the conformal dual $L^{*c}$. We show that the contravariant functor ${ }^{0}$ is right adjoint

Nobuhisa Tateno, Yue Zhu, Suzuyo Komeda, Mahiro Ishikawa

Optical coherence tomography (OCT) microscope (OCM) uses a high-numerical-aperture objective to achieve cellular-level lateral resolution. However, its practical imaging depth range is limited by the depth of focus (DOF). Although computational refocusing can potentially provide sharp images outside the DOF, signal reduction by the confocal effect still limi

Jianghan Zhu, Yaoxin Wu, Zhuoyi Lin, Zhengyuan Zhang

Recent advances in Neural Combinatorial Optimization (NCO) methods have significantly improved the capability of neural solvers to handle synthetic routing instances. Nonetheless, existing neural solvers typically struggle to generalize effectively from synthetic, uniformly-distributed training data to real-world VRP scenarios, including widely recognized be

Yuhao Wang, Ziyang Cheng, Heyang Liu, Ronghua Wu

Current end-to-end spoken language models (SLMs) have made notable progress, yet they still encounter considerable response latency. This delay primarily arises from the autoregressive generation of speech tokens and the reliance on complex flow-matching models for speech synthesis. To overcome this, we introduce VocalNet-M2, a novel low-latency SLM that int

Niklas Miller

We make the observation that certain group automorphisms that fix a large subgroup of an abelian group cannot be multipliers in any non-trivial abelian difference sets, with the single exception of an involution that can be a multiplier in Hadamard difference sets, provided that the difference set contains a sub-difference set of the same type. We use this o

Samuel Humeau, Mamadou Moustapha Kanté, Daniel Mock, Timothé Picavet

In property testing, a tester makes queries to (an oracle for) a graph and, on a graph having or being far from having a property P, it decides with high probability whether the graph satisfies P or not. Often, testers are restricted to a constant number of queries. While the graph properties for which there exists such a tester are somewhat well characteriz

Yangfan Ye, Xiaocheng Feng, Xiachong Feng, Lei Huang

Joint multilingual instruction tuning is a widely adopted approach to improve the multilingual instruction-following ability and downstream performance of large language models (LLMs), but the resulting multilingual capability remains highly sensitive to the composition and selection of the training data. Existing selection methods, often based on features l

Seid H. Pourtakdoust, Amir H. Khodabakhsh

This study presents a novel deep learning approach aimed at enhancing stochastic Gust Load Alleviation (GLA) specifically for compliant wings. The approach incorporates the concept of smooth wing camber variation, where the camber of the wing's chord is actively adjusted during flight using a control signal to achieve the desired aerodynamic loading. The pro

Thanasis Lianeas, Marios Mertzanidis, Aikaterini Nikolidaki

In Facility Location problems there are agents that should be connected to facilities and locations where facilities may be opened so that agents can connect to them. We depart from Uncapacitated Facility Location and by assuming that the connection costs of agents to facilities are congestion dependent, we define a novel problem, namely, Facility Location f

Yue Chen, Jianfeng Lu, Shuqing Cao, Wei Wang

While semi-asynchronous federated learning (SAFL) combines the efficiency of synchronous training with the flexibility of asynchronous updates, it inherently suffers from participation bias, which is further exacerbated by non-IID data distributions. More importantly, hierarchical architecture shifts participation from individual clients to client groups, th

Zhang Xu, Wei Zhao

This paper characterizes the set of feasible posterior distributions subject to graph-based inferential privacy constraint, including both differential and inferential privacy. This characterization can be done through enumerating all extreme points of the feasible posterior set. A connection between extreme posteriors and strongly connected semi-chains is t

Claudio Dappiaggi, Andrea Parpinel

We study Dirac fields on AdS$_n$ in both global and Poincar\'e charts and, for each mass window, we classify the boundary conditions at conformal infinity that ensure the existence of advanced and retarded propagators. We distinguish the well-known MIT--bag class from a generalized family, thereby extending to arbitrary dimensions the procedure initiated by

Udvas Das, Binayak Dutta, Satyabrata Jana, Debabrata Pal

Given a simple polygon $\mathscr{P}$, two points $x$ and $y$ within $\mathscr{P}$ are {\em visible} to each other if the line segment between $x$ and $y$ is contained in $\mathscr{P}$. The {\em visibility region} of a point $x$ includes all points in $\mathscr{P}$ that are visible from $x$. A point set $Q$ within a polygon $\mathscr{P}$ is said to be a \emph

Yudong Yang, Xuezhen Zhang, Zhifeng Han, Siyin Wang

Recent progress in LLMs has enabled understanding of audio signals, but has also exposed new safety risks arising from complex audio inputs that are inadequately handled by current safeguards. We introduce SACRED-Bench (Speech-Audio Composition for RED-teaming) to evaluate the robustness of LLMs under complex audio-based attacks. Unlike existing perturbation

Tânia Paulista

Let $X$ be a finite set. We determine the diameter of the commuting graph of the partial transformation semigroup $\mathcal{P}(X)$ on $X$ and show that it coincides with the diameter of the commuting graph of the transformation semigroup $\mathcal{T}(X)$ on $X$, which was previously determined by Ara\'ujo, Kinyon and Konieczny. This proves the existence of a

Yohei Nishino, Tomotada Akutsu, Yoichi Aso, Munetake Otsuka

We present the first experimental implementation of a polarization-circulation speed meter. In our experiment, the interferometer was reduced to a single-cavity configuration with all mirrors fixed. A green-locking scheme was employed to stabilize the polarization circulation cavity, and a lock-acquisition procedure was demonstrated to realize speed-meter op

Wiktor Ejsmont, Patrycja Hęćka-Jędraszczyk

The double Fock space of type B was introduced in 2023 by Bo\.zejko and Ejsmont (\cite{BE23}). In this article, we show the acting of Poisson type operators in that space. For this purpose, we define the double gauge operators (analogous to \cite{Ans01}, \cite{Ejsmont1}) and compute the multidimensional moments of a joint distribution of Poisson operators. W

Haolong Xiang, Peisi Wang, Xiaolong Xu, Kun Yi

With rapid urbanization in the modern era, traffic signals from various sensors have been playing a significant role in monitoring the states of cities, which provides a strong foundation in ensuring safe travel, reducing traffic congestion and optimizing urban mobility. Most existing methods for traffic signal modeling often rely on the original data modali

Huimei Wang, Xue-Bing Wu, Nanyu Yao, Bing Lyu

Changing-look active galactic nuclei (CLAGNs) are a unique population of AGNs that exhibit the appearance (turn-on) or disappearance (turn-off) of broad emission lines. This study aims to explore the intrinsic mechanisms of CLAGNs by investigating their photometric variability using data from the Zwicky Transient Facility (ZTF), which has provided high-caden

LHCb collaboration, R. Aaij, A. S. W. Abdelmotteleb, C. Abellan Beteta

Charged-hadron distributions in heavy-flavor jets are measured in proton-proton collisions at a center-of-mass energy of $\sqrt{s}$ = 13 TeV collected by the LHCb experiment. Distributions of the longitudinal momentum fraction, transverse momentum, and radial profile of charged hadrons are measured separately in beauty and charm jets. The distributions are c

Guanrong Li, Xinyu Liu, Zhen Wu, Xinyu Dai

Personalized dialogue generation aims to leverage persona profiles and dialogue history to generate persona-relevant and consistent responses. Mainstream models typically rely on token-level language model training with persona dialogue data, such as Next Token Prediction, to implicitly achieve personalization, making these methods tend to neglect the given

Federica Ferrarese

In this work, we provide an overview of various control strategies aimed at steering plasma toward desired configurations using an external magnetic field. From a modeling perspective, we focus on the Vlasov equation in a two-dimensional bounded domain, accounting for both a self-induced electric field and a strong external magnetic field. The results are pr

Xi Yang, Han Zhang, Zhijian Lin, Yibiao Hu

Out-of-context misinformation (OOC) is a low-cost form of misinformation in news reports, which refers to place authentic images into out-of-context or fabricated image-text pairings. This problem has attracted significant attention from researchers in recent years. Current methods focus on assessing image-text consistency or generating explanations. However

Ashutosh Anshul, Shreyas Gopal, Deepu Rajan, Eng Siong Chng

Recent multimodal deepfake detection methods designed for generalization conjecture that single-stage supervised training struggles to generalize across unseen manipulations and datasets. However, such approaches that target generalization require pretraining over real samples. Additionally, these methods primarily focus on detecting audio-visual inconsisten

Yueran Zhao, Zhang Zhang, Chao Sun, Tianze Wang

Vehicle-to-Everything (V2X) collaborative perception extends sensing beyond single vehicle limits through transmission. However, as more agents participate, existing frameworks face two key challenges: (1) the participating agents are inherently multi-modal and heterogeneous, and (2) the collaborative framework must be scalable to accommodate new agents. The

Zhikang Xie, Weilin Wan, Peizhu Gong, Weizhong Zhang

Black-box tuning is an emerging paradigm for adapting large language models (LLMs) to better achieve desired behaviors, particularly when direct access to model parameters is unavailable. Current strategies, however, often present a dilemma of suboptimal extremes: either separately train a small proxy model and then use it to shift the predictions of the fou

Yuetian Zou, Hanlei Zhang, Hua Xu, Songze Li

Textual open intent classification is crucial for real-world dialogue systems, enabling robust detection of unknown user intents without prior knowledge and contributing to the robustness of the system. While adaptive decision boundary methods have shown great potential by eliminating manual threshold tuning, existing approaches assume isotropic distribution

Wenzhe He, Xiaojun Chen, Ruiqi Wang, Ruihui Li

3D LiDAR scene completion from point clouds is a fundamental component of perception systems in autonomous vehicles. Previous methods have predominantly employed diffusion models for high-fidelity reconstruction. However, their multi-step iterative sampling incurs significant computational overhead, limiting its real-time applicability. To address this, we p

Cheng Kevin Qu, Andrew Ly, Pulin Gong

Attention mechanisms underpin the computational power of Transformer models, which have achieved remarkable success across diverse domains. Yet understanding and extending the principles underlying self-attention remains a key challenge for advancing artificial intelligence. Drawing inspiration from the multiscale dynamics of biological attention and from dy

Johannes Autenrieb, Ole Ostermann

Modern aerospace defense systems increasingly rely on autonomous decision-making to coordinate large numbers of interceptors against multiple incoming threats. Conventional weapon-target assignment (WTA) algorithms, including mixed-integer programming and auction-based methods, show limitations in dynamic and uncertain tactical environments where human-like

Eugene Seong

This paper introduces a heuristic framework for the Best Secretary Problem, where one item must be selected using rank information only. We develop five data-responsive rules extending classical fixed-cutoff methods: an expected-record threshold, an adaptive deviation correction, a probabilistic early-accept rule, a two-phase relaxation, and a local dynamic

Tali Orlev Shapira, Itzik Klein

Visual-inertial SLAM systems often exhibit suboptimal performance due to multiple confounding factors including imperfect sensor calibration, noisy measurements, rapid motion dynamics, low illumination, and the inherent limitations of traditional inertial navigation integration methods. These issues are particularly problematic in drone applications where ro

Martin J. W. Schubert

This document proposes binomial integer parameters for the cascaded Delta-Sigma-modulator structure with distributed feedback and distributed feedforward input and multi-bit output. It is demonstrated that high orders can be achieved with these coefficients. Accuracy requirements concerning the coefficients are discussed.

Xiangyu Lyu, En-Kun Li, Changfu Shi, Yi-Ming Hu

Massive black holes surrounded by a gaseous disk have been a prevailing model to explain a wide spectrum of astrophysical phenomena related to active galactic nucle (AGNs). However, direct and precise measurements of the disk density profiles remain elusive for current telescopes. In this work, we demonstrate that it is possible to pinpoint the gas density i

Stephane Da Silva Martins, Emanuel Aldea, Sylvie Le Hégarat-Mascle

Multi-agent trajectory prediction is crucial for autonomous systems operating in dense, interactive environments. Existing methods often fail to jointly capture agents' long-term goals and their fine-grained social interactions, which leads to unrealistic multi-agent futures. We propose VISTA, a recursive goal-conditioned transformer for multi-agent trajecto

Athanasios L. Konstantinidis, Charis Papadopoulos, Georgios Velissaris

A hedge graph is a graph whose edge set has been partitioned into groups called hedges. Here we consider a generalization of the well-known \textsc{Cluster Deletion} problem, named \textsc{Hedge Cluster Deletion}. The task is to compute the minimum number of hedges of a hedge graph so that their removal results in a graph that is isomorphic to a disjoint uni

Junquan Huang, Haotian Wu, Yubo Gao, Yibo Yan

Large language models (LLMs) with Chain-of-Thought (CoT) prompting achieve strong reasoning but often produce unnecessarily long explanations, increasing cost and sometimes reducing accuracy. Fair comparison of efficiency-oriented approaches is hindered by fragmented evaluation practices. We introduce EffiReason-Bench, a unified benchmark for rigorous cross-

Jieting Wang, Huimei Shi, Feijiang Li, Xiaolei Shang

Time series forecasting is an important task that involves analyzing temporal dependencies and underlying patterns (such as trends, cyclicality, and seasonality) in historical data to predict future values or trends. Current deep learning-based forecasting models primarily employ Mean Squared Error (MSE) loss functions for regression modeling. Despite enabli

Hao Huang, Yuming Lin, Jiazhen Liu

The spatial heterogeneity of cities -- the uneven distribution of population and activities -- is fundamental to urban dynamics and related to critical issues such as infrastructure overload, housing affordability, and social inequality. Despite sharing similar scaling laws of population and mobility, cities exhibit vastly different spatial patterns. This pa

Alan J. Barr

High-energy particle decays naturally realise informationally weak measurements of quantum spin. Decay kinematics act as continuous pointer variables whose overlapping angular distributions encode partial, non-projective information about the parent spin state. Ensemble averages of these pointers yield weak values, linking collider spin-density reconstructio

Oliver Long, Harald P. Pfeiffer, Lawrence E. Kidder, Mark A. Scheel

The asymptotic nature of unbound binary-black-hole encounters provides a clean method for comparing different approaches for modeling the two-body problem in general relativity. In this work, we use numerical relativity simulations of black-hole scattering, generated using the Spectral Einstein Code, to explore the self-force and post-Minkowskian expansions

Hefan Li, Masashi Chiba, Xiang-Xiang Xue, Gang Zhao

To unravel the formation history of the Milky Way, we estimate the accretion times of six phase-space substructures in the stellar halo, using the orbital frequencies toward two spatial directions ($r, \phi$) in spherical coordinates. These substructures, identified in our previous studies, are located in the solar neighbourhood and therefore have high-preci

Siyu He, Qin Li, Minyu Feng, Attila Szolnoki

Keeping a high reputation, by contributing to common efforts, plays a key role in explaining the evolution of collective cooperation among unrelated agents in a complex society. Nevertheless, it is not necessarily an individual feature, but may also reflect the general state of a local community. Consequently, a person with a high reputation becomes attracti

Qifeng Cai, Hao Liang, Chang Xu, Tao Xie

The data-centric paradigm has emerged as a pivotal direction in artificial intelligence (AI), emphasizing the role of high-quality training data. This shift is especially critical in the Text-to-SQL task, where the scarcity, limited diversity, and structural simplicity of existing datasets constrain model performance. To address these challenges, we propose

Josias Old, Juval Bechar, Markus Müller, Sascha Heußen

Quantum low-density parity check (qLDPC) codes are among the leading candidates to realize error-corrected quantum memories with low qubit overhead. Potentially high encoding rates and large distance relative to their block size make them appealing for practical suppression of noise in near-term quantum computers. In addition to increased qubit-connectivity

Eklavya Sarkar, Mathew Magimai. -Doss

Animal vocalizations contain sequential structures that carry important communicative information, yet most computational bioacoustics studies average the extracted frame-level features across the temporal axis, discarding the order of the sub-units within a vocalization. This paper investigates whether discrete acoustic token sequences, derived through vect

Gertian Roose, Erez Zohar

It is well known that all physically relevant states of gauge theories lie in the sectors of the Hilbert space which satisfy the Gauss law. On the lattice, the manifeslty gauge invariant subspace is known to be exactly spanned by gauged tensor networks. In this work, we demonstrate that the continuum limit of certain types of gauged tensor networks is well d

Kenji Tokuo

A modal logic based on quantum logic is formalized in its simplest possible form. Specifically, a relational semantics and a sequent calculus are provided, and the soundness and the completeness theorems connecting both notions are demonstrated. This framework is intended to serve as a basis for formalizing various modal logics over quantum logic, such as qu

Outongyi Lv, Yewei Yuan, Nana Liu

Reinforcement learning (RL) with limited samples is common in real-world applications. However, offline RL performance under this constraint is often suboptimal. We consider an alternative approach to dealing with limited samples by introducing the Quantum Metric Encoder (QME). In this methodology, instead of applying the RL framework directly on the origina

P. I. Pavlova, S. A. Khaibrakhmanov, A. M. Sobolev

We analyze observational data on methanol masers in the disks of young massive stellar objects in the massive star formation regions: NGC6334I, G33.641-0.228, G12.89+0.49. Special attention is paid to analysis of the magnetic fields and their possible connection with maser flares. For this purpose, we estimate the distance from star to maser, the magnetosphe

M. Tahir Abbas, M. Szymczak, D. Szymanski, M. Drozd

In this work, a dual-mode luminescent thermometer operating via both ratiometric and lifetime-based readout strategies was developed, enabled by the coexistence of two thermally driven effects: a structural phase transition in LiYO2 and a phonon-assisted energy transfer from Yb3+ to Nd3+. As demonstrated, changes in the shape of the emission band of Yb3+ ion

Tanuman Ghosh, Shiv Sethi, Gulab Chand Dewangan, Matteo Bachetti

We present the first broadband spectral analysis of NGC 470 HLX1, a hyperluminous X-ray source that exhibits significant flux variability over different epochs. We investigate the feasibility of synchrotron radiation with varying latitude from a magnetized neutron star to explain the source's spectra. Although the statistical quality of the data does not all

Yiran Zhang, Mingyang Lin, Mark Dras, Usman Naseem

Recent research has increasingly focused on the reasoning capabilities of Large Language Models (LLMs) in multi-turn interactions, as these scenarios more closely mirror real-world problem-solving. However, analyzing the intricate reasoning processes within these interactions presents a significant challenge due to complex contextual dependencies and a lack

Eeshan Modak, Mayank Bakshi, Bikash Kumar Dey, Vinod M. Prabhakaran

We study the adversarial binary hypothesis testing problem in the sequential setting. Associated with each hypothesis is a closed, convex set of distributions. Given the hypothesis, each observation is generated according to a distribution chosen (from the set associated with the hypothesis) by an adversary who has access to past observations. In the sequent

Tao Tang, Youfu Jiang, Yingbo Cui, Jianbin Fang

Sparse matrix ordering is a vital optimization technique often employed for solving large-scale sparse matrices. Its goal is to minimize the matrix bandwidth by reorganizing its rows and columns, thus enhancing efficiency. Conventional methods for algorithm selection usually depend on brute-force search or empirical knowledge, lacking the ability to adjust t

Rabimba Karanjai, Hemanth Hegadehalli Madhavarao, Lei Xu, Weidong Shi

We present QuCoWE a framework that learns quantumnative word embeddings by training shallow hardwareefficient parameterized quantum circuits PQCs with a contrastive skipgram objective Words are encoded by datareuploading circuits with controlled ring entanglement similarity is computed via quantum state fidelity and passed through a logitfidelity head that a

Chandrima Thakur, Priyanka Ghosh, Rashmita Badhai, Sumit Kundu

This paper analyzes a NOMA-enabled dual-Intelligent Reflecting Surface (IRS) relay network integrated with Ambient Backscatter (BS) communication. The system comprises a source, an energy-constrained relay with energy harvesting (EH) and BS capabilities, two NOMA users, and a BS node. The relay adopts a time-switching relaying (TSR) protocol to harvest energ

Tishya Chhabra, Manisha Bajpai, Walter Zesk, Skylar Tibbits

We present an initial evaluation of NASA and IBM's Prithvi-EO-2.0 geospatial foundation model on shoreline delineation of small sandy islands using satellite images. We curated and labeled a dataset of 225 multispectral images of two Maldivian islands, which we publicly release, and fine-tuned both the 300M and 600M parameter versions of Prithvi on training

Ming-Zhong Ai, Kang-Yuan Liu, Biao Zhang, Weng-Hang Leong

Measurement of the magnetization in the bulk of thin-film or two-dimensional materials is important for understanding their intrinsic properties without the complications from edges or domain walls. However, the stray fields from the bulk vanish or are very weak, which limits the application of direct measurement methods. Here, we develop a non-destructive a

Aryan Pandita, SK Firoz Islam

We study the magnetotransport properties of a two-dimensional electronic system with unconventional Rashba spin-orbit coupling in which the system is described by a pair of chiral spin texture in each spin branch, and the chirality is opposite in two spin branches. We obtain the Landau levels analytically and find that intra-spin and/or inter-spin Landau lev

Steven Huysecom, Francisco Bevilacqua, Roger Bresoli Obach, Sudipta Seth

Fast, volumetric imaging that integrates multiple imaging modalities is essential for probing dynamic, heterogeneous soft and biological matter. Here, we present the M3Scope, a simple yet versatile multiplane microscope that extends widefield detection with a modular multimode cube to enable dual color fluorescence, polarization-resolved, and correlative bri

Ahmed Jaheen, Islam Hassan, Mohanad Abouserie, Abdelaty Rehab

Accurate localization of cephalometric landmarks from 2D lateral skull X-rays is vital for orthodontic diagnosis and treatment. Manual annotation is time-consuming and error-prone, whereas automated approaches often struggle with low contrast and anatomical complexity. This paper introduces CephRes-MHNet, a multi-head residual convolutional network for robus

Zishuo Lan, Qionghuan Zeng, Weilong Ma, Xiangju Liang

Phase-field (PF) simulation provides a powerful framework for predicting microstructural evolution but suffers from prohibitive computational costs that severely limit accessible spatiotemporal scales in practical applications. While data-driven methods have emerged as promising approaches for accelerating PF simulations, existing methods require extensive t

Ashutosh Shukla, Sneha Boby, Rahul Chand, G. V. Pavan Kumar

Plasmonic Optical matter (OM), composed of optically bound metallic particles, can be rotated by transferring the spin angular momentum (SAM) of chiral light to the assembly. Rotating OM is a promising platform for optical micromachines, with potential applications in plasmofluidics and soft robotics. Understanding the dynamic states of such Brownian, micro-

Pedro Tartaj, Yurena Luengo, Pedro Moronta, Luisina Forzani

Earth-abundant materials exhibiting Mie resonances across the visible and near-infrared offer opportunities for efficient and sustainable sensing, thermal regulation, and sunlight harvesting. For anatase TiO$_2$, a broadband optical and abundant material, Mie calculations indicate that robust resonances require size tunability and monodispersity (standard de

Ilai Zaidel, Sharon Gannot

In this work, we propose a deep beamforming framework for speech enhancement in dynamic acoustic environments. The framework learns time-varying beamformer weights from noisy multichannel signals via a deep neural network, guided by a continuously tracked relative transfer function (RTF) of a moving target speaker. We analyze the network's spatial behavior o

Mark Kamsma

Positive logic is a generalisation of full first-order logic that does not have negation built in. Still, many model-theoretic ideas, tools and techniques work perfectly fine in positive logic. Importantly, there is a compactness theorem. With some care, many classical results hold in the generality of positive logic without giving up any strength. In these

Hu Gao, Xiaoning Lei, Xichen Xu, Depeng Dang

Although image restoration has advanced significantly, most existing methods target only a single type of degradation. In real-world scenarios, images often contain multiple degradations simultaneously, such as rain, noise, and haze, requiring models capable of handling diverse degradation types. Moreover, methods that improve performance through module stac

Yuancheng Sun, Yuxuan Ren, Zhaoming Chen, Xu Han

Accurate exploration of protein conformational ensembles is essential for uncovering function but remains hard because molecular-dynamics (MD) simulations suffer from high computational costs and energy-barrier trapping. This paper presents Energy Preference Optimization (EPO), an online refinement algorithm that turns a pretrained protein ensemble generator

Periklis Mantenoglou, Luigi Bonassi, Enrico Scala, Pedro Zuidberg Dos Martires

We study planning in a fragment of PDDL with qualitative state-trajectory constraints, capturing safety requirements, task ordering conditions, and intermediate sub-goals commonly found in real-world problems. A prominent approach to tackle such problems is to compile their constraints away, leading to a problem that is supported by state-of-the-art planners

Matthias Huemmer, Theophile Shyiramunda, Franziska Durner, Michelle J. Cummings-Koether

This article presents the results and their discussion for the third wave (with n=23 participants) within a multinational longitudinal study that investigates the evolving paradigm of human-AI collaboration in problem-solving contexts. Building upon previous waves, our findings reveal the consolidation of a hybrid problem-solving culture characterized by str

Yixin Ma, Chao Xu, Shenghan Jiang

Two-dimensional topological insulators, characterized by symmetry-protected anomalous boundary modes, have been generalized to the strongly correlated regime for both bosonic and fermionic systems. As correlated topological insulators (TI) approach experimental realization in quantum simulators, conventional probes, such as transport measurements, are not ea

J. Javier Alonso-Ramos, Ignacio Aguilera-Martos, Francisco Herrera, Andrés Herrera-Poyatos

In the Data-Centric Artificial Intelligence (AI) paradigm, improving data quality is essential for robust machine learning. However, many denoising methods rely on rigid statistical assumptions or require clean reference data, which limits their applicability in real-world scenarios. In this work, we propose DenoGrad, a gradient-based framework for data refi

Ashutosh S. Wadge, Alexander Kazakov, Xujia Gong, Daniel Jastrzebski

We investigate the single crystals of Ni$_{0.19}$NbSe$_2$, revealing that Ni intercalation profoundly alters the physical properties of NbSe$_2$. Magnetic measurements clearly show that the system is magnetically frustrated with antiferromagnetic ordering below 23.5\,K, with an irreversibility temperature near 10\,K, and a magnetic hysteresis with a small ne

Miguel Sánchez de la Rosa, Francisco J. andújar, Jesus Escudero-Sahuquillo, José L. Sánchez

The demand for computer in our daily lives has led to the proliferation of Datacenters that power indispensable many services. On the other hand, computing has become essential for some research for various scientific fields, that require Supercomputers with vast computing capabilities to produce results in reasonable time. The scale and complexity of these

Jeppe H. Mikkelsen, Thomas T. Enevoldsen, Bugge T. Jensen, Michael Jeppesen

Vessels navigating in confined waters are subject to banking effects, which are hydrodynamic forces and moments arising from pressure differentials between the vessel sides, significantly affecting manoeuvrability and safety. Existing numerical approaches such as computational fluid dynamics (CFD) can accurately capture these effects but are computationally

Koh Matsuura, Toshiki Nakashima

For the quiver Hecke algebra $R$, let $R\hbox{-gmod}$ be the category of finite-dimensional graded $R$-modules, and let $\widetilde{R\hbox{-gmod}[w]}$ be the localization of $R\hbox{-gmod}$. Kashiwara and the second author showed the set of equivalence classes of simple objects up to grading shifts $\mathrm{Irr}(\widetilde{R\hbox{-gmod}[w]})$ in $\widetilde{

S Rahul, A Harshitha

Phase transitions in one-dimensional lattice systems are well established and have been extensively studied within both Hermitian and non-Hermitian frameworks. In this work, we extend this understanding to a more general setting by investigating localization and delocalization transitions and the behavior of the non-Hermitian skin effect (NHSE) using a tight

Tomasz Paterek, Arseni Goussev

Quantum backflow is a counterintuitive phenomenon in which the probability density of a quantum particle propagates opposite to its momentum. Experimental observation of backflow has remained elusive due to two main challenges: (i) the effect is intrinsically small, with less than 4% of the probability able to flow backward, and (ii) it requires wave packets

Hao Zou, Runqing Zhang, Xue Zhou, Jianxiao Zou

Text-to-Image Person Retrieval (TIPR) aims to retrieve person images based on natural language descriptions. Although many TIPR methods have achieved promising results, sometimes textual queries cannot accurately and comprehensively reflect the content of the image, leading to poor cross-modal alignment and overfitting to limited datasets. Moreover, the inhe

Yuya Koike, Shintaro Kuroki

We introduce the notion of a locally standard $T$-pseudomanifold, a class that generalizes both complete toric varieties and locally standard $T$-manifolds. The main goal of this paper is to show that locally standard $T$-pseudomanifolds over topological stratified pseudomanifolds satisfying certain conditions are completely classified, up to (weakly) equiva

Bastien Laville, Benjamin Aymard

In this article, we present novel and effective methods for reducing chromatic aberrations in cemented lens systems. We derive an analytical solution coined the pentachromat, which corrects five distinct colors. This method can naturally be extended to accommodate an arbitrary number of lenses and to correct for a customized selection of spectral lines. Sinc

Alfio M. Bonanno, Samuele Silveravalle, Andrea Spina

We investigate a class of horizonless solutions in Einstein-Weyl gravity, corresponding to the so-called attractive naked singularities of the (-2,2) type. In contrast to General Relativity, where naked singularities are generically unstable and excluded by the cosmic censorship conjecture, we show that these configurations are linearly stable under tensor p

Feng Ding, Wenhui Yi, Yunpeng Zhou, Xinan He

Fairness is a core element in the trustworthy deployment of deepfake detection models, especially in the field of digital identity security. Biases in detection models toward different demographic groups, such as gender and race, may lead to systemic misjudgments, exacerbating the digital divide and social inequities. However, current fairness-enhanced detec