March 2025 arXiv papers — page 6

ATLAS Collaboration

Anisotropic flow and radial flow are two key probes of the expansion dynamics and properties of the quark-gluon plasma (QGP). While anisotropic flow has been extensively studied, radial flow, which governs the system's radial expansion, has received less attention. Notably, experimental evidence for the global and collective nature of radial flow has been la

Dou Liu, Ying Long, Sophia Zuoqiu, Tian Tang

Effective physician-patient communications in pre-diagnostic environments, and most specifically in complex and sensitive medical areas such as infertility, are critical but consume a lot of time and, therefore, cause clinic workflows to become inefficient. Recent advancements in Large Language Models (LLMs) offer a potential solution for automating conversa

Nelson Hua, Francesco Petocchi, Henry G. Bell, Gabriel Aeppli

Controlled stacking of van der Waals materials is a powerful tool for exploring the physics of quantum condensed matter. Given the small binding between layers, exploitation for engineering will require a breakthrough in stacking methodology, or an ability to take advantage of thicker defective stacks. Here we describe computational groundwork for the latter

Seewon Choi, Alaia Solko-Breslin, Rajeev Alur, Eric Wong

Many computational tasks benefit from being formulated as the composition of neural networks followed by a discrete symbolic program. The goal of neurosymbolic learning is to train the neural networks using end-to-end input-output labels of the composite. We introduce CTSketch, a novel, scalable neurosymbolic learning algorithm. CTSketch uses two techniques

Dipesh K. Singh, P. K. Mohanty

We design a thermal bath that preserves the conservation of a system's angular momentum or allows it to fluctuate around a specified nonzero mean while maintaining a Boltzmann distribution of energy in the steady state. We demonstrate that classical particles immersed in such baths exhibit position-momentum uncertainties with a strictly positive lower bound

Valentin Boussot, Cédric Hémon, Jean-Claude Nunes, Jason Dowling

Image registration is fundamental in medical imaging, enabling precise alignment of anatomical structures for diagnosis, treatment planning, image-guided interventions, and longitudinal monitoring. This work introduces IMPACT (Image Metric with Pretrained model-Agnostic Comparison for Transmodality registration), a novel similarity metric designed for robust

Yong Ma, Xuedong Zhang, Yuchong Zhang, Morten Fjeld

User satisfaction plays a crucial role in user experience (UX) evaluation. Traditionally, UX measurements are based on subjective scales, such as questionnaires. However, these evaluations may suffer from subjective bias. In this paper, we explore the acoustic and prosodic features of speech to differentiate between positive and neutral UX during interactive

J. H. Khushvaktov, M. A. Demichev, D. L. Demin, S. A. Evseev

Bremsstrahlung fluxes for irradiating tantalum samples were formed by irradiating a tungsten converter with an electron beam with energy up to 130 MeV. The relative yields and flux-averaged cross-sections of multinucleon photonuclear reactions with the emission of up to 9 neutrons in 181Ta nuclei were determined. Monte Carlo simulations to study the yields o

Bryan Adams, Valentín Vergara Hidd, Daniel Stimpson, Miesha Purcell

Most of the modeling approaches used to understand organizational worker mobility are highly stylized, using idealizations such as structureless organizations, indistinguishable workers, and a lack of social bonding of the workers. In this article, aided by a decade of precise, temporally resolved data of a large civilian organization of the US Army in which

Anna Shopova, Cristoph Lippert, Leslee J. Shaw, Eugenia Alleva

Menstrual health is a critical yet often overlooked aspect of women's healthcare. Despite its clinical relevance, detailed data on menstrual characteristics is rarely available in structured medical records. To address this gap, we propose a novel Natural Language Processing pipeline to extract key menstrual cycle attributes -- dysmenorrhea, regularity, flow

Zhiming Ma, Peidong Wang, Minhua Huang, Jingpeng Wang

The detection of telecom fraud faces significant challenges due to the lack of high-quality multimodal training data that integrates audio signals with reasoning-oriented textual analysis. To address this gap, we present TeleAntiFraud-28k, the first open-source audio-text slow-thinking dataset specifically designed for automated telecom fraud analysis. Our d

Sebastian Gurriaran

We prove the precise asymptotics of the spin $-2$ Teukolsky field in the interior and along the Cauchy horizon of a subextremal Kerr black hole. Together with the oscillatory blow-up asymptotics of the spin $+2$ Teukolsky field proven in our previous work arXiv:2409.02670, our result suggests that generic perturbations of a Kerr black hole build up to form a

Giuseppe Tudisco, Fabio Vitello, Eva Sciacca, Ugo Becciani

The field of astrophysics is continuously advancing, with an ever-growing influx of data requiring robust and efficient analysis tools. As the Square Kilometre Array (SKA) radio telescopes come fully operational, we anticipate the generation of hundreds of petabytes of data annually, characterized by unprecedented resolution and detail. In this context, scie

George Tomanov

The goal of the present paper is to characterize the norm and quasi-norm forms defined over an arbitrary number field F in terms of their values at the S-integer points, where S is a finite set of valuations of F containing the archimedean ones. In this way we generalize the main result of the recent paper [T5], where the notion of a quasi-norm form is intro

Arthur M. Faria, Ignacio F. Graña, Savvas Varsamopoulos

Quantum Graph Neural Networks (QGNNs) offer a promising approach to combining quantum computing with graph-structured data processing. While classical Graph Neural Networks (GNNs) are scalable and robust, existing QGNNs often lack flexibility due to graph-specific quantum circuit designs, limiting their applicability to diverse real-world problems. To addres

Sreenath Vemula, Filippo Gatti, Pierre Jehel

Increasing flood frequency and severity due to climate change threatens infrastructure and demands improved susceptibility mapping techniques. While traditional machine learning (ML) approaches are widely used, they struggle to capture spatial dependencies and poor boundary delineation between susceptibility classes. This study introduces the first applicati

H. Y. Zhang

This paper shows that on the Bergman space of the open unit disk, the slant Toeplitz operator $T_{p+\varphi}$ and $T_{p+\psi}$ commute if and only if $\varphi=\psi$ ,where $\varphi$ and $\psi$ are both bounded analytic functions, and $p$ is ananalytic polynomial.

François Olivier, Zied Bouraoui

Despite advances in embodied AI, agent reasoning systems still struggle to capture the fundamental conceptual structures that humans naturally use to understand and interact with their environment. To address this, we propose a novel framework that bridges embodied cognition theory and agent systems by leveraging a formal characterization of image schemas, w

Shijie Bao, Qi'an Guan

In this note, we demonstrate the convergence of the Demailly approximation of a general (weakly) upper semi-continuous weight.

Anwesa Choudhuri, Zhongpai Gao, Meng Zheng, Benjamin Planche

Early detection, accurate segmentation, classification and tracking of polyps during colonoscopy are critical for preventing colorectal cancer. Many existing deep-learning-based methods for analyzing colonoscopic videos either require task-specific fine-tuning, lack tracking capabilities, or rely on domain-specific pre-training. In this paper, we introduce P

Taisei Takabayashi, Naoki Maruyama, Takuma Yoshihara, Renichiro Haba

Column generation (CG) has been used to solve constrained 0-1 quadratic programming problems. The pricing problem, which is iteratively solved in CG, can be reduced to an unconstrained 0-1 quadratic programming problem, allowing for the efficient application of quantum annealing (QA). The solutions obtained by CG are continuous relaxations, which cannot be p

Luc Brisson, Salomon Ofman

Some of the most challenging problems in Timaeus' cosmology arise from the geometry of a universe without any void. On the one hand, the universe is spherical in shape; on the other hand, it must be entirely filled with the four basic particles that make up all bodies in the universe, each shaped like one of four regular polyhedra (cubes, tetrahedra, octahed

LHCb Collaboration

A second major upgrade of the LHCb experiment is necessary to allow full exploitation of the High Luminosity LHC for flavour physics. The new experiment will operate in Run 5 of the LHC at a luminosity up to $1.5\times 10^{34}cm^{-2}s^{-1}$. The experiment will therefore experience extremely high particle fluences and data rates, posing a high challenge not

Giulio Fattore, Maria Elena Valcher

In this paper, we assume that an autonomous exosystem generates a reference output, and we consider the problem of designing a distributed data-driven control law for a family of discrete-time heterogeneous LTI agents, connected through a directed graph, in order to synchronize the agents' outputs to the reference one. The agents of the network are split int

Chiaki Kojima, Yuya Muto, Hikaru Akutsu, Rinnosuke Shima

In regions with heavy snowfall, the living environment is becoming a serious problem due to heavy snow accumulation. A road heating is an electrical device which promotes snow melting by burying a heating cable as a thermal source underground in such regions. When integrating the road heating into power distribution systems, we need to optimize the flow of e

Tom De Medts, Louis Olyslager

In 2021, Maurice Chayet and Skip Garibaldi provided an explicit construction of a commutative non-associative algebra on the second smallest representation of $E_8$ (of dimension $3875$) adjoined with a unit. In fact, they define such an algebra $A(\mathfrak{g})$ for each simple Lie algebra $\mathfrak{g}$, in terms of explicit but ad-hoc formulas. We discove

Yewei Song, Lujun Li, Cedric Lothritz, Saad Ezzini

Low-resource languages (LRLs) lack sufficient linguistic resources and are underrepresented in benchmark datasets, resulting in persistently lower translation quality than high-resource languages, especially in privacy-sensitive and resource-limited contexts. Firstly, this study systematically evaluates state-of-the-art smaller Large Language Models in 200 l

Margarida M. Telo da Gama, Rodrigo C. V. Coelho

Mixtures of nematic liquid crystals and isotropic fluids display a diverse range of phase behaviors, arising from the coupling between orientational order and concentration fluctuations. In this review, we introduce a simplified mathematical framework that integrates the Landau-de Gennes free energy for nematic ordering with the Cahn-Hilliard free energy for

Jaekwon Lee, Fabrizio Pastore, Lionel Briand

Mutation testing can help minimize the delivery of faulty software. Therefore, it is a recommended practice for developing embedded software in safety-critical cyber-physical systems (CPS). However, state-of-the-art mutation testing techniques for C and C++ software, which are common languages for CPS, depend on symbolic execution. Unfortunately, symbolic ex

Florian Rupp, Kai Eckert

Balancing games, especially those with asymmetric multiplayer content, requires significant manual effort and extensive human playtesting during development. For this reason, this work focuses on generating balanced levels tailored to asymmetric player archetypes, where the disparity in abilities is balanced entirely through the level design. For instance, w

Tuan Pham, Sidney Redner, Lourens Waldorp, Jay Armas

Explanations of polarization often rely on one of the three mechanisms: homophily, bounded confidence, and community-based interactions. Models based on these mechanisms consider the lack of interactions as the main cause of polarization. Given the increasing connectivity in modern society, this explanation of polarization may be insufficient. We aim to show

Qiyue Qian, Hongjing Yang, Weicheng Zang, Yoon-Hyun Ryu

To exhume the buried signatures of free-floating planets (FFPs) with small angular Einstein radius $\theta_{\rm E}$, we build a new full-frame difference image pipeline for the Korean Microlensing Telescope Network (KMTNet) survey based on the newly optimized pySIS package. We introduce the detailed processes of the new pipeline, including frame registration

Adrienne Deganutti, Simon Hadfield, Andrew Gilbert

Audio Description is a narrated commentary designed to aid vision-impaired audiences in perceiving key visual elements in a video. While short-form video understanding has advanced rapidly, a solution for maintaining coherent long-term visual storytelling remains unresolved. Existing methods rely solely on frame-level embeddings, effectively describing objec

Raphael Meier

Images of war are almost as old as war itself. From cave paintings to photographs of mobile devices on social media, humans always had the urge to capture particularly important events during a war. Images provide visual evidence. For armed forces, they may serve as the output of a sensor (e.g. in aerial reconnaissance) or as an effector on cognition (e.g. i

Ilja Gogić, Mateo Tomašević

Let $M_n(\mathbb{F})$ be the algebra of $n \times n$ matrices over a field $\mathbb{F}$ of characteristic not equal to $2$. If $n\ge 2$, we show that an arbitrary map $\phi : M_n(\mathbb{F}) \to M_n(\mathbb{F})$ is Jordan multiplicative, i.e.\ it satisfies the functional equation $$ \phi(XY+YX)=\phi(X)\phi(Y)+\phi(Y)\phi(X), \quad \text{for all } X,Y \in M_n

Panagiotis Gavriilidis, Deepak Mishra, Besma Smida, Ertugrul Basar

Reconfigurable Intelligent Surfaces (RISs) constitute a promising emerging technology that enables wireless systems to control the propagation environment to enhance diverse communication objectives. To mitigate double-fading attenuation in RIS-aided links, the paradigm of active metamaterials capable of amplifying their incident wave has emerged. In this pa

Xiangyuan Peng, Miao Tang, Huawei Sun, Kay Bierzynski

Intelligent transportation systems require accurate and reliable sensing. However, adverse environments, such as rain, snow, and fog, can significantly degrade the performance of LiDAR and cameras. In contrast, 4D mmWave radar not only provides 3D point clouds and velocity measurements but also maintains robustness in challenging conditions. Recently, resear

Dario Melegari, Rabia Abdul Razaq, Giovanni Minuto, Paolo Solinas

We present a comparative study of two implementations of a variational quantum algorithm aimed at minimizing the energy of a complex quantum system. In one implementation, we extract the information of the energy gradient by projective measurements. In the second implementation, called the Non-Demolition approach, the gradient information is stored in a quan

Le Liu, Yu Kawano, Antai Xie, Ming Cao

In this paper, we investigate initial state privacy protection for discrete-time nonlinear closed systems. By capturing Riemannian geometric structures inherent in such privacy challenges, we refine the concept of differential privacy through the introduction of an initial state adjacency set based on Riemannian distances. A new differential privacy conditio

Lars Möllenbrok, Behnood Rasti, Begüm Demir

Continual self-supervised learning (CSSL) methods have gained increasing attention in remote sensing (RS) due to their capability to learn new tasks sequentially from continuous streams of unlabeled data. Existing CSSL methods, while learning new tasks, focus on preventing catastrophic forgetting. To this end, most of them use regularization strategies to re

Long, Zhang, Shijun, Chen

Self-regulated learning (SRL) and Artificial-Intelligence (AI) literacy are becoming key competencies for successful human-AI interactive learning, vital to future education. However, despite their importance, students face imbalanced and underdeveloped SRL and AI literacy capabilities, inhibiting effective using AI for learning. This study analyzed data fro

Kun Hu, Zhiyuan Yu, Taotao Qiu, Zhongkun Hu

We study the dynamics of the non-relativistic spinning test body (STB) in the framework of Einstein-Cartan theory(ECT), in which the weak equivalence principle is violated by the spin-gravitational interaction. We derive the general equation of geodesic in terms of comoving tetrads. More concretely, we consider the case of the quadratic form of the lagrangia

Xinliang Dai, Yuning Jiang, Yi Guo, Colin N. Jones

This paper introduces a novel distributed optimization framework for large-scale AC Optimal Power Flow (OPF) problems, offering both theoretical convergence guarantees and rapid convergence in practice. By integrating smoothing techniques and the Schur complement, the proposed approach addresses the scalability challenges and reduces communication overhead i

Karthik Shivashankar

The prospect of 4D video in Extended Reality (XR) platform is huge and exciting, it opens a whole new way of human computer interaction and the way we perceive the reality and consume multimedia. In this thesis, we have shown that feasibility of rendering 4D video in Microsoft mixed reality platform. This enables us to port any 3D performance capture from CV

Lorenz Zwick, János Takátsy, Pankaj Saini, Kai Hendriks

We present the first overview of the expected quantity of signals which will showcase significant gravitational wave phase shifts caused by astrophysical environments, considering the upcoming A+ and A\# LIGO/Virgo/KAGRA, Cosmic Explorer and Einstein Telescope detectors. We construct and analyse two general families of dephasing prescriptions with extensions

Danilo Naiff, Bernardo P. Schaeffer, Gustavo Pires, Dragan Stojkovic

Note: The final version of this article was published in Computers and Geosciences, Volume 206, January 2026, 106038. DOI: 10.1016/j.cageo.2025.106038. Readers should refer to the published version for the most up-to-date content. Three-dimensional digital reconstruction of porous media presents a fundamental challenge in geoscience, requiring simultaneous r

C. Houarner, A. Boujrad, M. Tripon, M. Bezard

NUMEXO2 is a 16 channels 14bit/200MHz digitizer and processing board initially developed for gamma-ray spectroscopy (for EXOGAM: EXOtic nuclei GAMma ray). Numexo2 has been gradually extended and improved as a general purpose digitizer to fulfill various needs in nuclear physics detection at GANIL. This was possible thanks to reprogrammable components like FP

Yunlu Xiao, Marina Petrova, Ljiljana Simić

While cell-free massive MIMO (CF-mMIMO) offers high network-wide throughput in static networks, especially for the worst-served users, its performance in mobile networks is not yet fully addressed. In this paper, we evaluate the performance of a mobile CF-mMIMO network under a comprehensive throughput model and show that it suffers from large performance deg

Marco Gallo, Jacopo Schino

In this paper, we search for normalized solutions to a fractional, nonlinear, and possibly strongly sublinear Schr\"odinger equation $$(-\Delta)^s u + \mu u = g(u) \quad \hbox{in $\mathbb{R}^N$},$$ under the mass constraint $\int_{\mathbb{R}^N} u^2 \, \mathrm{d}x = m>0$; here, $N\geq 2$, $s \in (0,1)$, and $\mu$ is a Lagrange multiplier. We study the case of

Daniela Silva, Raquel Menezes, Gonçalo Araújo, Renato Rosa

Accurately identifying spatial patterns of species distribution is crucial for scientific insight and societal benefit, aiding our understanding of species fluctuations. The increasing quantity and quality of ecological datasets present heightened statistical challenges, complicating spatial species dynamics comprehension. Addressing the complex task of inte

Zining Cao

In this paper, we present a complete mental temporal logic, called BPICTL, which generalizes CTL by introducing mental modalities. A sound and complete inference system of BPICTL is given. We prove the finite model property of BPICTL. Furthermore, we present a model checking algorithm for BPICTL.

Kundan Kadam, Eduard Vorobyov, Peter Woitke, Manuel Güdel

Context. Young Stellar Objects (YSOs) are observed to undergo powerful accretion events known as FU Orionis outbursts (FUors). Such events of episodic accretion are now considered to be common during low mass star formation, wherein the accretion onto the protostar occurs through a surrounding centrifugal disk. Increasing evidence suggests that the magnetic

Yongzheng Zhu, Weizheng Chen, Jian Deng, Xin Bian

Simultaneously detecting hidden solid boundaries and reconstructing flow fields from sparse observations poses a significant inverse challenge in fluid mechanics. This study presents a physics-informed neural network (PINN) framework designed to infer the presence, shape, and motion of static or moving solid boundaries within a flow field. By integrating a b

Qingmin Hu, Wen-Yi Zhang, Yunguang Han, Wen-Long You

Weak ergodicity breaking, particularly through quantum many-body scars (QMBS), has become a significant focus in many-body physics. Krylov state complexity quantifies the spread of quantum states within the Krylov basis and serves as a powerful diagnostic for analyzing nonergodic dynamics. In this work, we study spin-one XXZ magnets and reveal nonergodic beh

Zhanat Karashbayeva, Julien Berger, Helcio R. B. Orlande, Marie-Hélène Azam

Urbanization is the key contributor for climate change. Increasing urbanization rate causes an urban heat island (UHI) effect, which strongly depends on the short- and long-wave radiation balance heat flux between the surfaces. In order to calculate accurately this heat flux, it is required to assess the surface temperature which depends on the knowledge of

Teresa Dorszewski, Lenka Tětková, Robert Jenssen, Lars Kai Hansen

Vision Transformers (ViTs) are increasingly utilized in various computer vision tasks due to their powerful representation capabilities. However, it remains understudied how ViTs process information layer by layer. Numerous studies have shown that convolutional neural networks (CNNs) extract features of increasing complexity throughout their layers, which is

Zhiyuan Xu, Yinuo Zhao, Kun Wu, Ning Liu

Teleoperation is essential for autonomous robot learning, especially in manipulation tasks that require human demonstrations or corrections. However, most existing systems only offer unilateral robot control and lack the ability to synchronize the robot's status with the teleoperation hardware, preventing real-time, flexible intervention. In this work, we in

Harald Grosse, Albert Much

We present a quantum energy inequality (QEI) for quantum field theories formulated in non-commutative spacetimes, extending fundamental energy constraints to this generalized geometric framework. By leveraging operator-theoretic methods inspired by the positivity map of Waldmann et al. \cite{waldmannpos}, we construct linear combinations of deformed operator

Yixing Li, Ruobing Xie, Zhen Yang, Xingwu Sun

Transformers are the cornerstone of modern large language models, but their quadratic computational complexity limits efficiency in long-sequence processing. Recent advancements in Mamba, a state space model (SSM) with linear complexity, offer promising efficiency gains but suffer from unstable contextual learning and multitask generalization. Some works con

Max Berger, Hajo Holzmann

In this paper, in a multivariate setting we derive near optimal rates of convergence in the minimax sense for estimating partial derivatives of the mean function for functional data observed under a fixed synchronous design over H\"older smoothness classes. We focus on the supremum norm since it corresponds to the visualisation of the estimation error, and i

Siqi Zhang, Yanyuan Qiao, Qunbo Wang, Zike Yan

Vision-and-Language Navigation (VLN) tasks have gained prominence within artificial intelligence research due to their potential application in fields like home assistants. Many contemporary VLN approaches, while based on transformer architectures, have increasingly incorporated additional components such as external knowledge bases or map information to enh

Prajith Pillai, Ashton Hetherington, Laura Saavedra Sago, Soledad Le Clainche

This article applies low-cost singular value decomposition (lcSVD) for the first time, to the authors knowledge, on combustion reactive flow databases. The lcSVD algorithm is a novel approach to SVD, suitable for calculating high-resolution 2D or 3D proper orthogonal decomposition (POD) modes and temporal coefficients using data from sensors. Consequently, t

Sheila Masson, Alan Potts, Allan Williams, Steve Berggreen

During the 20th Century, aerial surveys captured hundreds of millions of high-resolution photographs of the earth's surface. These images, the precursors to modern satellite imagery, represent an extraordinary visual record of the environmental and social upheavals of the 20th Century. However, most of these images currently languish in physical archives whe

Fatemeh Mohammadi, Tommaso Romano, Samira Maghool, Paolo Ceravolo

Collecting high-quality training data is essential for fine-tuning Large Language Models (LLMs). However, acquiring such data is often costly and time-consuming, especially for non-English languages such as Italian. Recently, researchers have begun to explore the use of LLMs to generate synthetic datasets as a viable alternative. This study proposes a pipeli

Albert Atserias, Moritz Müller

We introduce a technically and conceptually simple approach to magnification of circuit and formula lower bounds. Central to the method are so-called distinguishers, sparse matrices that retain some of the key properties of error-correcting codes. As applications, we generalize and strengthen known general (not problem specific) magnification results and in

Jumpei Gohara, Akifumi Sako

A quantization of Lie-Poisson algebras is studied. Classical solutions of the mass-deformed Ishibashi-Kawai-Kitazawa-Tsuchiya (IKKT) matrix model can be constructed from semisimple Lie algebras whose dimension matches the number of matrices in the model. We consider the geometry described by the classical solutions of the Lie algebras in the limit where the

Marvin Kopp, Charu Garg, Sarah Krebber, Kristin Kliemt

Antiferromagnetic EuCd$_2$P$_2$ has attracted considerable attention due to its unconventional (magneto)transport properties. At a temperature $T_{\rm peak}$ significantly above the magnetic ordering temperature $T_\textrm{N} = 11\,$K a large peak in resistivity is observed which gets strongly suppressed in magnetic field, resulting in a colossal magnetoresi

Bogomila S. Nikolova, Motitz Göb, Kilian Singer, Peter A. Ivanov

We propose the realization of a mechanically squeezed Kerr oscillator with a single ion in a tapered trap. We show that the motion coupling between the axial and radial modes caused by the trap geometry leads to Kerr nonlinearity of the radial mode with magnitude controlled by the trap frequencies. This allows the realization of non-Gaussian quantum gates, w

Xuxiong Liu, Tengteng Dong, Fei Wang, Weijie Feng

Micro-expressions are typically regarded as unconscious manifestations of a person's genuine emotions. However, their short duration and subtle signals pose significant challenges for downstream recognition. We propose a multi-task learning framework named the Adaptive Motion Magnification and Sparse Mamba (AMMSM) to address this. This framework aims to enha

Mathieu Molitor

We show that the moment polytope of a K\"ahler toric manifold, constructed as the torification (in the sense of M. Molitor, K\"ahler toric manifolds from dually flat spaces, arXiv:2109.04839, 2021) of an exponential family defined on a finite sample space, is the projection of a higher-dimensional simplex.

Dimitri Cobb, Daniel Sánchez-Simón del Pino, Juan J. L. Velázquez

In this article we study a one dimensional model for Magnetic Relaxation. This model was introduced by Moffatt and describes a low resistivity viscous plasma, in which the pressure and the inercia are much smaller than the magnetic pressure. In the limit of resistivity $\varepsilon\rightarrow 0$, we prove the existence of two time scales for the evolution of

Mamy Laingo Nomenjanahary Rakotoarison, Dimbiniaina Ratovilebamboavison, Fanja Rakotondrajao

In this paper, we study the Euler-Seidel matrices with coefficients and determine the associated Riordan matrix to a given matrix, if it does exist. Computation of the generating fonction of the final sequence is established by the associated Riordan matrix. Applications are given.

Tong Xie, Jiawang Zhao, Zishen Wan, Zuodong Zhang

The demand for efficient large language model (LLM) inference has propelled the development of dedicated accelerators. As accelerators are vulnerable to hardware faults due to aging, variation, etc, existing accelerator designs often reserve a large voltage margin or leverage algorithm-based fault tolerance (ABFT) techniques to ensure LLM inference correctne

Anantram Patel, Nikhil Mogre, Mandar Mane, Jayavardhan Reddy Enumula

In this paper, prediction of airfoil shape from targeted pressure distribution (suction and pressure sides) and vice versa is demonstrated using both Convolutional Neural Networks (CNNs) and Deep Neural Networks (DNNs) techniques. The dataset is generated for 1600 airfoil shapes, with simulations carried out at Reynolds numbers (Re) ranging from 10,000 and 9

Zhenhuan Liu

Realizing practical quantum advantage with meaningful economic impact is the holy grail of the quantum information field. Recent quantum technology advances have driven exponential growth in quantum information research, with resultant publications achieving significantly elevated impact. Within academia, citation counts serve as a key metric for evaluating

Xinyuan Liang, Renxi Liu, Mohan Chen

Accurately modeling the electronic structure of water across scales, from individual molecules to bulk liquid, remains a grand challenge. Traditional computational methods face a critical trade-off between computational cost and efficiency. We present an enhanced machine-learning Deep Kohn-Sham (DeePKS) method for improved electronic structure, DeePKS-ES, th

H. Abramowicz, E. Adli, F. Alharthi, M. Almanza-Soto

In this paper we outline a proposal for a Linear Collider Facility as the next flagship project for CERN. It offers the opportunity for a timely, cost-effective and staged construction of a new collider that will be able to comprehensively map the Higgs boson's properties, including the Higgs field potential, thanks to a large span in centre-of-mass energies

Pouria Mohamadzadehoqaz, Elena Dieckmann, Anthony Quinn, Robert Shorten

We propose a surge sourcing approach to address occasional synchronous high demand (surge demand) in sharing economy systems, providing a socio-economically progressive alternative to surge pricing. Instead of suppressing demand among disadvantaged consumers, our scheme increases supply by involving privileged consumer-providers (prosumers) who under-utilize

Shuo Ren, Can Xie, Pu Jian, Zhenjiang Ren

As scientific research becomes increasingly complex, innovative tools are needed to manage vast data, facilitate interdisciplinary collaboration, and accelerate discovery. Large language models (LLMs) are now evolving into LLM-based scientific agents that automate critical tasks ranging from hypothesis generation and experiment design to data analysis and si

Jose Reina-Galvez, Matyas Nachtigall, Nicolas Lorente, Jan Martinek

Understanding the coherent properties of electron spins driven by electric fields is crucial for their potential application in quantum-coherent nanoscience. In this work, we address two distinct driving mechanisms in electric-field driven electron-spin resonance as implemented in scanning tunneling spectroscopy. We study the origin of the driving field usin

A. Barış Özgüler

We investigate the potential of near-term quantum algorithms for solving partial differential equations (PDEs), focusing on a linear one-dimensional advection-diffusion equation as a test case. This study benchmarks a ground-state algorithm, Variational Quantum Eigensolver (VQE), against three leading quantum dynamics algorithms, Trotterization, Variational

Jiahui Lu, Shuang Wu, Zhenkai Qin, Guifang Yang

To enhance the accuracy and robustness of PM$_{2.5}$ concentration forecasting, this paper introduces FALNet, a Frequency-Aware LSTM Network that integrates frequency-domain decomposition, temporal modeling, and attention-based refinement. The model first applies STL and FFT to extract trend, seasonal, and denoised residual components, effectively filtering

Ioannis Varveris, Gianni D. Aliberti, Tianyin Chen, Filip A. Sfetcu

The direct bonding process of a diamond-on-insulator (DOI) substrate enables monolithic integration of diamond photonic structures for quantum computing by improving photon collection efficiency and entanglement generation rate between emitters. It also addresses key fabrication challenges, such as robustness, bonding strength, and scalability. This study in

Morten Roed Frederiksen, Kasper Støy, Maja Matarić

A common denominator for most therapy treatments for children who suffer from an anxiety disorder is daily practice routines to learn techniques needed to overcome anxiety. However, applying those techniques while experiencing anxiety can be highly challenging. This paper presents the design, implementation, and pilot study of a tactile hand-held pocket robo

Marie Farrell, Matt Luckcuck, Rosemary Monahan, Conor Reynolds

This paper gives an overview of previous work in which the authors used NASA's Formal Requirement Elicitation Tool (FRET) to formalise requirements. We discuss four case studies where we used FRET to capture the system's requirements. These formalised requirements subsequently guided the case study specifications in a combination of formal paradigms. For eac

E. Tempel, J. Laur, Z. R. Jones, R. Kipper

Context. Accurate photometric redshift estimation is crucial for cosmological and galaxy evolution studies, especially with the advent of large-scale photometric surveys. Aims. We developed a photo-z estimation code called TOPz (Tartu Observatory Photo-z) and applied it to the GAMA photometric catalogue. Using nine-band photometric data from the GAMA project

Jakob Nicolai Bruhnke, Edvin Olofsson, Axel Stenquist, Jan Marcus Dahlström

We predict an unexplored type of ultrastrong coupling between atoms and intense ultraviolet light that leads to giant population oscillations on the attosecond timescale. These counter-rotating oscillations can be of similar amplitude as the elementary femtosecond Rabi oscillations between the two strongly coupled states. The effect, which is beyond the two-

Haruka Nakajima Suzuki, Midori Inaba

Online disinformation often provokes strong anger, driving social media users to spread it; however, few measures specifically target sharing behaviors driven by this emotion to curb the spread of disinformation. This study aimed to evaluate whether digital nudges that encourage deliberation by drawing attention to emotional information can reduce sharing dr

Yutong Xin, Jimmy Xin, Gabriel Poesia, Noah Goodman

Enabling more concise and modular proofs is essential for advancing formal reasoning using interactive theorem provers (ITPs). Since many ITPs, such as Rocq and Lean, use tactic-style proofs, learning higher-level custom tactics is crucial for proof modularity and automation. This paper presents a novel approach to tactic discovery, which leverages Tactic De

Paul Madley-Dowd, Rachael A. Hughes, Maya B. Mathur, Jon Heron

Missing data is a pervasive problem in epidemiology, with multiple imputation (MI) a commonly used analysis method. MI is valid when data are missing at random (MAR). However, definitions of MAR with multiple incomplete variables are not easily interpretable and graphical model-based conditions are not accessible to applied researchers. Previous literature s

Marion Cromb, Maria Chiara Braidotti, Andrea Vinante, Daniele Faccio

The amplification and generation of electromagnetic radiation by a rotating metallic or lossy cylinder, first theorized by Zeldovich in the 1970s, is tightly connected to the concepts of quantum friction, energy extraction from rotating black holes and runaway mechanisms such as black hole bombs. Despite recent advances including acoustic analogues of the Ze

Denis-Charles Cisinski

We study the process of $\ell$-adic completion of motivic sheaves. We observe that, in equal characteristic, when restricted to constructible objets, it is compatible with the six operations. This implies that one can reconstruct $\ell$-adic sheaves of geometric origin over a scheme of finite type over a field from $\ell$-adic cohomology of smooth schemes. I

Yasashwini Sai Gowri P, Karthik Seemakurthy, Andrews Agyemang Opoku, Sita Devi Bharatula

Wheat plays a critical role in global food security, making it one of the most extensively studied crops. Accurate identification and measurement of key characteristics of wheat heads are essential for breeders to select varieties for cross-breeding, with the goal of developing nutrient-dense, resilient, and sustainable cultivars. Traditionally, these measur

Huu-Thinh Do, Ionela Prodan, Florin Stoican

Neural networks have proven practical for a synergistic combination of advanced control techniques. This work analyzes the implementation of rectified linear unit neural networks to achieve constrained control in differentially flat systems. Specifically, the class of flat systems enjoys the benefit of feedback linearizability, i.e., the systems can be linea

Emmanuel Jacquet

I report the discovery of jacquetium ($_0$Jq), the first naturally occurring element found since more than 80 years. It is volumically the most important element of the local Universe.

Rishabh Mishra

This paper extends our previous results on logarithmically improved regularity criteria for the three-dimensional Navier-Stokes equations by establishing a comprehensive framework of multi-level logarithmic improvements. We prove that if the initial data $u_0 \in L^2(\mathbb{R}^3)$ satisfies a nested logarithmically weakened condition $\|(-\Delta)^{s/2}u_0\|

Qiang Wang, Dawei Feng, Xu Zhang, Ao Shen

Instruction tuning has emerged as a paramount method for tailoring the behaviors of LLMs. Recent work has unveiled the potential for LLMs to achieve high performance through fine-tuning with a limited quantity of high-quality instruction data. Building upon this approach, we further explore the impact of prompt's robustness on the selection of high-quality i

Florian Carichon, Romain Rampa, Golnoosh Farnadi

Novelty modeling and detection is a core topic in Natural Language Processing (NLP), central to numerous tasks such as recommender systems and automatic summarization. It involves identifying pieces of text that deviate in some way from previously known information. However, novelty is also a crucial determinant of the unique perception of relevance and qual

Boyuan Wang, Xiaofeng Wang, Chaojun Ni, Guosheng Zhao

Human-motion video generation has been a challenging task, primarily due to the difficulty inherent in learning human body movements. While some approaches have attempted to drive human-centric video generation explicitly through pose control, these methods typically rely on poses derived from existing videos, thereby lacking flexibility. To address this, we

Renato Vizuete, Julien M. Hendrickx

We show how graphons can be used to model and analyze open multi-agent systems, which are multi-agent systems subject to arrivals and departures, in the specific case of linear consensus. First, we analyze the case of replacements, where under the assumption of a deterministic interval between two replacements, we derive an upper bound for the disagreement i