March 2025 arXiv papers — page 8

Zizhuo Li, Yifan Lu, Linfeng Tang, Shihua Zhang

This prospective study proposes CoMatch, a novel semi-dense image matcher with dynamic covisibility awareness and bilateral subpixel accuracy. Firstly, observing that modeling context interaction over the entire coarse feature map elicits highly redundant computation due to the neighboring representation similarity of tokens, a covisibility-guided token cond

Ziyang Ma, Zuchao Li, Lefei Zhang, Gui-Song Xia

Large language models (LLMs) demonstrate strong performance across natural language processing tasks, yet undergo significant performance degradation when modified for deployment through quantization, pruning, or decoding strategy adjustments. We define this phenomenon as model hemorrhage - performance decline caused by parameter alterations and architectura

Michael Timothy Bennett

Artificial general intelligence (AGI) is an established field of research. Yet some have questioned if the term still has meaning. AGI has been subject to so much hype and speculation it has become something of a Rorschach test. Melanie Mitchell argues the debate will only be settled through long term, scientific investigation. To that end here is a short, a

Le Liu, Yu Kawano, Yangming Dou, Ming Cao

In this paper, we investigate distributionally robust model order reduction for linear, discrete-time, time-invariant systems. The external input is assumed to follow an uncertain distribution within a Wasserstein ambiguity set. We begin by considering the case where the distribution is certain and formulate an optimization problem to obtain the reduced mode

Shoto Aoki, Hidenori Fukaya, Mikio Furuta, Shinichiroh Matsuo

We show that the Wilson Dirac operator in lattice gauge theory can be identified as a mathematical object in $K$-theory and that its associated spectral flow is equal to the index. In comparison to the standard lattice Dirac operator index, our formulation does not require the Ginsparg-Wilson relation and has broader applicability to systems with boundaries

Lahiru Akmeemana, Chamodya Attanayake, Husni Faiz, Sandareka Wickramanayake

The transition to microservices has revolutionized software architectures, offering enhanced scalability and modularity. However, the distributed and dynamic nature of microservices introduces complexities in ensuring system reliability, making anomaly detection crucial for maintaining performance and functionality. Anomalies stemming from network and perfor

Zhou Rui, Zhi-Tian Zou, Ya Li, Ying Li

We perform a detailed analysis of the semileptonic $\Xi_b\rightarrow \Xi_c \ell^- \bar{\nu}_\ell$ decays within the perturbative QCD framework. In our study, the $\Xi_b\rightarrow \Xi_c$ transition form factors are calculated using several popular models for baryonic light-cone distribution amplitudes. These form factors are then employed to analyze a range

Xin-Nan Zhu, Xin-Li Sheng, Defu Hou

We develop a theoretical framework for the production of $K^+K^-$ pairs through the decay of $\phi$ mesons produced from a thermal background, based on the Nambu-Jona-Lasinio (NJL) model. The differential production rate of $K^+K^-$ is related to the self-energy of the $\phi$ meson, incorporating the contributions of the quark loop at leading order and the k

Hao Wang, Ze-Yu Peng, Yun-Song Piao

In the report by BICEP/Keck collaborations, the tensor-to-scalar ratio is $r_{0.05}<0.036$ (95\% C.L.). However, recent datasets have preferred the evolving dark energy, which thus have significantly shifted the bestfit values of standard $\Lambda$CDM cosmological parameters. In this paper, we perform the joint analysis of BICEP/Keck cosmic microwave backgro

Naoyuki Koike

In this paper, we give a construction of curvature-adapted hypersurfaces in the product $G_1/K_1\times G_2/K_2$ of (Riemannian) symmetric spaces $G_i/K_i$ ($i=1,2$). By this construction, we obtain many examples of curvature-adapted hypersurfaces in $G_1/K_1\times G_2/K_2$. Also, we calculate the eigenvalues of the shape operator and the normal Jacobi operat

Antonio Balena, Marianna D Amato, Muhammad Fayyaz Kashif, Chengjie Ding

This study introduces a novel method for the deterministic fabrication of metallic nanostructures with controlled geometry and composition on suspended, single mode tapered optical nanofibers (TNFs) using a tailored Blurred Electron Beam Induced Deposition (BEBID) technique. TNFs, owing to their subwavelength diameters and intense evanescent fields, offer a

Alexander Sakhnovich

A GBDT version of the B\"acklund-Darboux transformation for a non-isospectral canonical system is considered. Applications to multiplicative integrals and their limit values, to characteristic matrix functions and to linear similarity problems are obtained. Some interesting examples are constructed as well.

Louison Duboz, Ioan Cristinel Raileanu, Jette Krause, Ana Norman-López

The deployment of Automated Vehicles (AVs) is expected to address road transport externalities (e.g., safety, traffic, environmental impact, etc.). For this reason, a legal framework for their large-scale market introduction and deployment is currently being developed in the European Union. Despite the first steps towards road transport automation, the timel

Xiaoxuan Wang, Yihe Deng, Mingyu Derek Ma, Wei Wang

The mathematical problem-solving capabilities of large language models have become a focal point of research, with growing interests in leveraging self-generated reasoning paths as a promising way to refine and enhance these models. These paths capture step-by-step logical processes while requiring only the correct answer for supervision. The self-training m

Prashant Solanki, Nikolaus Vertovec, Yannik Schnitzer, Jasper Van Beers

Recent approaches to leveraging deep learning for computing reachable sets of continuous-time dynamical systems have gained popularity over traditional level-set methods, as they overcome the curse of dimensionality. However, as with level-set methods, considerable care needs to be taken in limiting approximation errors, particularly since no guarantees are

Ruisheng Han, Kanglei Zhou, Amir Atapour-Abarghouei, Xiaohui Liang

Action quality assessment (AQA) is critical for evaluating athletic performance, informing training strategies, and ensuring safety in competitive sports. However, existing deep learning approaches often operate as black boxes and are vulnerable to spurious correlations, limiting both their reliability and interpretability. In this paper, we introduce FineCa

Shubham Chakraborty, Someshwar Sanjay Ade, Lakshmana Dora Chandrala, Kirti Chandra Sahu

The present study investigates the morphology and breakup dynamics of a freely falling drop in a vertical airstream using shadowgraphy and in-line holography. The in-line holography provides the temporal evolution of the volumetric size distribution of child droplets formed during various fragmentation processes at different Weber numbers (We). The droplet u

Yusuke Nishida

We introduce a new member to the class of semisuper Efimov effects, where an infinite number of bound states emerge with their binding energies obeying the universal scaling law $E_n\sim e^{-2(\pi n/\gamma)^2}$ for sufficiently high excitation $n\in\mathbb{N}$. Our system consists of a pair of two-component fermions in three dimensions at infinite scattering

Shanze Wang, Mingao Tan, Zhibo Yang, Biao Huang

Deep Reinforcement Learning (DRL) based navigation methods have demonstrated promising results for mobile robots, but suffer from limited action flexibility in confined spaces. Conventional DRL approaches predominantly learn forward-motion policies, causing robots to become trapped in complex environments where backward maneuvers are necessary for recovery.

Zhichao Liao, Xiaokun Liu, Wenyu Qin, Qingyu Li

Image Aesthetic Assessment (IAA) is a long-standing and challenging research task. However, its subset, Human Image Aesthetic Assessment (HIAA), has been scarcely explored. To bridge this research gap, our work pioneers a holistic implementation framework tailored for HIAA. Specifically, we introduce HumanBeauty, the first dataset purpose-built for HIAA, whi

Angela A. Albanese, Héctor Ariza

We analyse the behaviour of the iterates of composition operators defined by polynomials acting on global classes of ultradifferentiable functions of Beurling type which are invariant under the Fourier transform. In particular, we determine the polynomials $\psi$ for which the sequence of iterates of the composition operator $C_\psi$ is topologizable (m-topo

Qihan Huang, Weilong Dai, Jinlong Liu, Wanggui He

MLLM reasoning has drawn widespread research for its excellent problem-solving capability. Current reasoning methods fall into two types: PRM, which supervises the intermediate reasoning steps, and ORM, which supervises the final results. Recently, DeepSeek-R1 has challenged the traditional view that PRM outperforms ORM, which demonstrates strong generalizat

Eugène Flesselle

We propose a calculus for modeling implicit programming that supports first-class, overlapping, locally scoped, and higher-order instances with higher-kinded types. We propose a straightforward generalization of the well-established System $F^\omega$ to implicit parameters, with a uniform treatment of type and term abstractions. Unlike previous works, we giv

Le Liu, Yu Kawano, Ming Cao

This paper addresses the challenge of privacy preservation for statistical inputs in dynamical systems. Motivated by an autonomous building application, we formulate a privacy preservation problem for statistical inputs in linear time-invariant systems. What makes this problem widely applicable is that the inputs, rather than being assumed to be deterministi

Pratyasha Tripathy, Hetvi Jadav, Himanshu Pandey

Sorbent materials, such as graphene-based systems coated with Cr, are being investigated as potential hydrogen storage materials. Graphene, a 2D material with a high surface-to-volume ratio, has been employed. A comparison is conducted between graphene systems with single vacancy defects and those without defects, using Cr adsorption. To verify the effective

Satyam Narayan Srivastava, Alexander Domoshnitsky, Seshadev Padhi, Rana D. Parshad

In this paper, we consider a non-autonomous allelopathic phytoplankton competition ODE model, incorporating the influence of fear effects observed in natural biological phenomena. Based on Mawhin's coincidence degree theory some sufficient conditions for existence of periodic solutions are obtained. We validate our findings through an illustrative example an

Ralf Hiptmair, Carolina Urzúa-Torres, Anouk Wisse

In this paper, we describe a framework to compute expected convergence rates for residuals based on the Calder\'on identities for general second order differential operators for which fundamental solutions are known. The idea is that these rates could be used to validate implementations of boundary integral operators and allow to test operators separately by

Diana Galvan-Sosa, Gabrielle Gaudeau, Pride Kavumba, Yunmeng Li

The performance and usability of Large-Language Models (LLMs) are driving their use in explanation generation tasks. However, despite their widespread adoption, LLM explanations have been found to be unreliable, making it difficult for users to distinguish good from bad explanations. To address this issue, we present Rubrik's CUBE, an education-inspired rubr

Rihui Zhang, Haiming Zhu, Jingtong Zhao, Lei Zhang

Accurate evaluation of regional lung ventilation is essential for the management and treatment of lung cancer patients, supporting assessments of pulmonary function, optimization of therapeutic strategies, and monitoring of treatment response. Currently, ventilation scintigraphy using nuclear medicine techniques is widely employed in clinical practice; howev

Yufei Wang, Lanqing Guo, Zhihao Li, Jiaxing Huang

Text-guided image editing is an essential task that enables users to modify images through natural language descriptions. Recent advances in diffusion models and rectified flows have significantly improved editing quality, primarily relying on inversion techniques to extract structured noise from input images. However, inaccuracies in inversion can propagate

Fabiola Ricci, Lorenzo Bardone, Sebastian Goldt

Deep neural networks learn structured features from complex, non-Gaussian inputs, but the mechanisms behind this process remain poorly understood. Our work is motivated by the observation that the first-layer filters learnt by deep convolutional neural networks from natural images resemble those learnt by independent component analysis (ICA), a simple unsupe

Yuqiao Tan, Shizhu He, Huanxuan Liao, Jun Zhao

Retrieval-augmented generation (RAG) enhances large language models (LLMs) by retrieving relevant documents from external sources and incorporating them into the context. While it improves reliability by providing factual texts, it significantly increases inference costs as context length grows and introduces challenging issue of RAG hallucination, primarily

Shubham Kala, Abhishek Negi, Hemwati Nandan

In this study, we investigate the quasinormal modes of a non-rotating dyonic black hole within the framework of Einstein-Euler-Heisenberg theory. We present a detailed analysis focuses on understanding the influence of dyonic charges on the oscillatory properties of these BHs. The quasinormal modes are calculated to explore the interplay between the dyonic c

Maximilian Springenberg, Noelia Otero, Yuxin Xue, Jackie Ma

Renewable resources are strongly dependent on local and large-scale weather situations. Skillful subseasonal to seasonal (S2S) forecasts -- beyond two weeks and up to two months -- can offer significant socioeconomic advantages to the energy sector. This study aims to enhance wind speed predictions using a diffusion model with classifier-free guidance to dow

Johannes Mäkelburg, Diego Perez-Palacin, Raffaela Mirandola, Maribel Acosta

Cyber-Physical Systems (CPS) operate in dynamic environments, leading to different types of uncertainty. This work provides a comprehensive review of uncertainty representations and categorizes them based on the dimensions used to represent uncertainty. Through this categorization, key gaps and limitations in existing approaches are identified. To address th

Joseph Cho, Katrin Leschke, Yuta Ogata

We show that every finite type polarised curve in the conformal $2$-sphere with a polynomial conserved quantity admits a resonance point, under a non-orthogonality assumption on the conserved quantity. Using this fact, we deduce that every finite type curve polarised by space form arc-length in the conformal $2$-sphere admits a resonance point, possibly on a

Julius Beerwerth, Bassam Alrifaee

Data-Driven Predictive Control (DPC) optimizes system behavior directly from measured trajectories without requiring an explicit model. However, its computational cost scales with dataset size, limiting real-time applicability to nonlinear robotic systems. For robotic tasks such as trajectory tracking and motion planning, real-time feasibility and numerical

Yawen Chang, Xudong Wang

With the developments of the Internet of Vehicles (IoV) from 4G to 5G, vehicle-to-infrastructure (V2I) communications are becoming attractive for vehicle users (VUEs) to obtain diverse cloud service through base stations (BSs). To tackle V2I link deterioration caused by blockage and out-of-coverage cases, multi-hop V2X routing with both vehicle-to-vehicle (V

Xin Zhang, Siting Huang, Xiangyang Luo, Yifan Xie

Face editing modifies the appearance of face, which plays a key role in customization and enhancement of personal images. Although much work have achieved remarkable success in text-driven face editing, they still face significant challenges as none of them simultaneously fulfill the characteristics of diversity, controllability and flexibility. To address t

Bowei Qiao, Hongwei Wang

To satisfy the requirements of the end-to-end fault diagnosis of gears, an integrated intelligent method of fault diagnosis for gears using acceleration signals was proposed, which was based on Gabor-based Adaptive Short-Time Fourier Transform (Gabor-ASTFT) and Dual-Tree Complex Wavelet Transform(DTCWT) algorithms, Dilated Residual structure and feature fusi

Qin Wang, Youhuan Li, Yansong Feng, Si Chen

People without a database background usually rely on file systems or tools such as Excel for data management, which often lead to redundancy and data inconsistency. Relational databases possess strong data management capabilities, but require a high level of professional expertise from users. Although there are already many works on Text2SQL to automate the

Maciej Niedźwiecki, Artur Gańcza, Wojciech Żuławiński, Agnieszka Wyłomańska

While local basis function (LBF) estimation algorithms, commonly used for identifying/tracking systems with time-varying parameters, demonstrate good performance under the assumption of normally distributed measurement noise, the estimation results may significantly deviate from satisfactory when the noise distribution is impulsive in nature, for example, co

Rami Katz, Andrii Mironchenko

We show that if a linear infinite-dimensional system is exponentially stabilizable by compact feedback, it is also stabilizable by means of a sampled-data feedback that is fed through a globally Lipschitz nonlinearity, provided that the sector bound for the nonlinearity and the sampling time is small enough. Next we develop a switching-based event-triggered

Cheng Luo, Luping Xiang, Jie Hu, Kun Yang

Sensing-assisted communication schemes have recently garnered significant research attention. In this work, we design a dual-function reconfigurable intelligent surface (RIS), integrating both active and passive elements, referred to as the reconfigurable intelligent sensing surface (RISS), to enhance communication. By leveraging sensing results from the act

Halil İbrahim Öztürk, Muhammet Esat Kalfaoğlu, Ozsel Kilinc

Accurate and efficient lane detection in 3D space is essential for autonomous driving systems, where robust generalization is the foremost requirement for 3D lane detection algorithms. Considering the extensive variation in lane structures worldwide, achieving high generalization capacity is particularly challenging, as algorithms must accurately identify a

Tianyi Gong, Boyan Li, Yifei Zhong, Fangxin Wang

The increasing demand for augmented and virtual reality applications has highlighted the importance of crafting immersive 3D scenes from a simple single-view image. However, due to the partial priors provided by single-view input, existing methods are often limited to reconstruct low-consistency 3D scenes with narrow fields of view from single-view input. Th

Soumya Sarkar, Xiwen Liu, Deep Jariwala

Recent advances in silicon foundry-process compatible ferroelectric (FE) thin films have reinvigorated interest in FE-based non-volatile memory (NVM) devices. Ferroelectric diodes (FeDs) are two-terminal NVM devices exhibiting rectifying current-voltage hysteretic characteristics that enable self-selecting designs critical for high-density memory. We examine

Giovanni Palermo, Emanuele Brugnoli, Ruggiero D. Lo Sardo, Vittorio Loreto

Election polls play a critical role in political discussions by probing public opinion and enabling political parties to assess their performance before elections. However, traditional polling methods sometimes fail to predict election outcomes accurately, leading researchers to explore new methodologies. One such approach is the "social circle" question, wh

C. Schürmann, X. -T. Xu, N. Langer, D. Lennon

Massive star evolution plays a crucial role in astrophysics but bares large uncertainties. This problem becomes more severe by the majority of massive stars being born in close binary systems, whose evolution is affected by the interaction of their components. We want to constrain major uncertainties in massive binary star evolution, in particular the effici

Junyao Shi, Zhuolun Zhao, Tianyou Wang, Ian Pedroza

Many recent advances in robotic manipulation have come through imitation learning, yet these rely largely on mimicking a particularly hard-to-acquire form of demonstrations: those collected on the same robot in the same room with the same objects as the trained policy must handle at test time. In contrast, large pre-recorded human video datasets demonstratin

X. -T. Xu, C. Schürmann, N. Langer, C. Wang

Context. The majority of massive stars are born with a close binary companion. How this affects their evolution and fate is still largely uncertain, especially at low metallicity. Aims. We derive synthetic populations of massive post-interaction binary products and compare them with corresponding observed populations in the Small Magellanic Cloud (SMC). Meth

Wenkang Ji, Huaben Chen, Mingyang Chen, Guobin Zhu

The development of control policies for multi-robot systems traditionally follows a complex and labor-intensive process, often lacking the flexibility to adapt to dynamic tasks. This has motivated research on methods to automatically create control policies. However, these methods require iterative processes of manually crafting and refining objective functi

Y. S. Huang, H. X. Song, Q. D. Hao, X. L. Pan

The polymorphism and mechanism of helium compounds is crucial for understanding the physical and chemical nature of He-bearing materials under pressures. Here, we predict two new types of He-bearing compounds, MgHe and MgnHe (n = 6, 8, 10, 15, 18), being formed above 750 GPa by unbiased ab initio structure search. An unexpected bandgap is opened up in MgHe a

Mahdi Amiri, Hatef Otroshi Shahreza, Ina Kodrasi

Automatic pathological speech detection approaches have shown promising results, gaining attention as potential diagnostic tools alongside costly traditional methods. While these approaches can achieve high accuracy, their lack of interpretability limits their applicability in clinical practice. In this paper, we investigate the use of multimodal Large Langu

DiCE Collaboration

The exploration of the phase diagram of Quantum ChromoDynamics (QCD) is carried out by studying ultrarelativistic heavy-ion collisions. The energy range covered by the CERN SPS ($\sqrt{s_{\rm {NN}}} \sim 6-17$ GeV) is ideal for the investigation of the region corresponding to finite baryochemical potential ($\mu_{\rm B}$), and was little explored up to now.

Camille Laurent-Gengoux, Ruben Louis

We construct a finite-dimensional higher Lie groupoid integrating a singular foliation $\mathcal{F}$, under the mild assumption that the latter admits a geometric resolution. More precisely, a recursive use of bi-submersions, a tool coming from non-commutative geometry and invented by Androulidakis and Skandalis, allows us to integrate any universal Lie $ \i

Hojer Key

This paper introduces a novel formal SAT-based explanation model for deep learning in video understanding. The proposed method integrates SAT solving techniques with the principles of formal explainable AI to address the limitations of existing XAI techniques in this domain. By encoding deep learning models and video data into a logical framework and formula

Yongle Li, Bo Liu, Sheng Huang, ZHeng ZHang

In federated learning, fine-tuning pre-trained foundation models poses significant challenges, particularly regarding high communication cost and suboptimal model performance due to data heterogeneity between the clients. To address these issues, this paper introduces communication-efficient federated LoRA adaption (CE-LoRA), a method that employs a tri-fact

George Pappas, Ippocratis D. Saltas, Laurent Eyer

We use the framework of microlensing to show that observations of binary systems, such as those made by {\it Gaia}, combined with follow-up weak lensing measurements, can provide a means to probe halos of exotic matter, possibly clumped around compact objects such as black holes. This could potentially cover a broad range of physical scenarios - from dark ma

Xulong Wang, Guancong Ma

The duality of left and right eigenvectors underpins the comprehensive understanding of many physical phenomena. In Hermitian systems, left and right eigenvectors are simply Hermitian-conjugate pairs. Non-Hermitian eigenstates in contrast, have left and right eigenvectors that are distinct from each other. However, despite the tremendous interest in non-Herm

Ji Woo Han

The study examines how Gacha games affect gambling practices by analyzing when players start playing and how often they play and how much money they spend on games. The modified Problem Gambling Severity Index (PGSI) serves as the research tool to examine the impact of these variables on mobile Gacha game gambling-like severity. A survey distributed to onlin

Jialin Wan, Jinglong Shen, Nan Cheng, Zhisheng Yin

This paper investigates backdoor attacks in image-oriented semantic communications. The threat of backdoor attacks on symbol reconstruction in semantic communication (SemCom) systems has received limited attention. Previous research on backdoor attacks targeting SemCom symbol reconstruction primarily focuses on input-level triggers, which are impractical in

Ignasi Guillén-Mola

We establish the solvability of the $L^p$-Dirichlet and $L^{p^\prime}$-Neumann problems for the Laplacian for $p\in (\frac{n}{n-1}-\varepsilon,\frac{2n}{n-1}]$ for some $\varepsilon>0$ in $2$-sided chord-arc domains with unbounded boundary that is sufficiently flat at large scales and outward unit normal vector whose oscillation fails to be small only at fin

Pierre Bertrand, Michel Broniatowski, Wolfgang Stummer

We propose a new random method to minimize deterministic continuous functions over subsets $\mathcal{S}$ of high-dimensional space $\mathbb{R}^K$ without assuming convexity. Our procedure alternates between a Global Search (GS) regime to identify candidates and a Concentrated Search (CS) regime to improve an eligible candidate in the constraint set $\mathcal

Johannes Wehrstein, Tiemo Bang, Roman Heinrich, Carsten Binnig

User-Defined-Functions (UDFs) are a pivotal feature in modern DBMS, enabling the extension of native DBMS functionality with custom logic. However, the integration of UDFs into query optimization processes poses significant challenges, primarily due to the difficulty of estimating UDF execution costs. Consequently, existing cost models in DBMS optimizers lar

SeonYeong Lee, EonSeung Seong, DongEon Lee, SiYeoul Lee

Digital pathology images play a crucial role in medical diagnostics, but their ultra-high resolution and large file sizes pose significant challenges for storage, transmission, and real-time visualization. To address these issues, we propose CLERIC, a novel deep learning-based image compression framework designed specifically for whole slide images (WSIs). C

Junkang Huang, Tao Zhou

Recent angle-resolved photoemission spectroscopy (ARPES) experiments on La$_{2.85}$Pr$_{0.15}$Ni$_2$O$_7$ thin films have revealed a superconducting gap near the diagonal direction for the $d_{x^2-y^2}$ orbital, confined to a narrow momentum region. Our numerical calculations indicate that interlayer pairing is dominant, resulting in an $s_\pm$-wave symmetry

Julián Agredo, Franco Fagnola, Damiano Poletti

We investigate the relationship between strict positivity of the Kossakowski matrix, irreducibility and positivity improvement properties of Markovian Quantum Dynamics. We show that for a Gaussian quantum dynamical semigroup strict positivity of the Kossakowski matrix implies irreducibility and, with an additional technical assumption, that the support of an

S. Riggi, T. Cecconello, A. Pilzer, S. Palazzo

The advent of next-generation radio telescopes is set to transform radio astronomy by producing massive data volumes that challenge traditional processing methods. Deep learning techniques have shown strong potential in automating radio analysis tasks, yet are often constrained by the limited availability of large annotated datasets. Recent progress in self-

Chenyu Jia, Guangshu Xia, Yuanhao Shi, Jianfang Jia

Lithium-ion batteries have become an indispensable part of human industrial production and daily life. For the safe use, management and maintenance of lithium-ion batteries, the state of health (SOH) of lithium-ion batteries is an important indicator so that the SOH estimation is of significant practical value. In order to accurately predict SOH, this paper

Guodong Wang

In this paper, we establish two stability theorems for steady or traveling solutions of the two-dimensional incompressible Euler equation in a finite periodic channel, extending Arnold's classical work from the 1960s. Compared to Arnold's approach, we employ a compactness argument rather than relying on the negative definiteness of the energy-Casimir functio

K. Maltsev, F. R. N. Schneider, I. Mandel, B. Mueller

Massive stars undergoing iron core-collapse at the end of their evolution terminate their lives either in successful or failed supernovae (SNe). The physics of core-collapse supernovae (CCSNe) is complex, and their understanding requires computationally expensive simulations. Using these to predict CCSN outcomes over large, densely sampled parameter spaces o

David d'Enterria, Pier Francesco Monni, Peter Skands, Andrii Verbytskyi

Measurements of hadronic final states in $e^{+}e^{-}$ collisions at centre-of-mass (CM) energies below the Z peak can notably extend the FCC-ee physics reach in terms of precision quantum chromodynamics (QCD) studies. Hadronic final states can be studied over a range of hadronic energies $\sqrt{s_\mathrm{had}} \approx 20\mbox{--}80\,\mathrm{GeV}$ by exploiti

Ozan Balci, Stien Poncelet, Alex Binh Vinh Duc Nguyen, Andrew Vande Moere

Although intended to foster spontaneous interactions among workers, a typical open-plan office layout cannot mitigate visual, acoustic, or privacy-related distractions that originate from unplanned meetings. As office workers often refrain from tackling these issues by manually demarcating or physically relocating to a more suitable subspace that is enclosed

Hao Cheng, Katrin Löer, Max A. N. Hendriks, Yuguang Yang

This paper presents a new method for determining the diffusive properties of diffuse body waves, specifically diffusivity and dissipation, in concrete with multiple planar boundaries. Instead of relying on the analytical solution to the diffusion equation, which accounts for all possible reflections and has a significantly complex form, we propose a simpler

C. Cramail, R. Lhermerout, E. Charlaix

We present a theory of the hydrodynamic forces in the drainage flow of an electrolyte between a sphere and a plane with charged surfaces. Our theory considers a thin electrolyte film which is at all times in local equilibrium across its thickness. In addition to the usual lubrication force, we explicit the electro-kinetic force due to the transport of the di

Suman Raj, Bhavani A Madhabhavi, Madhav Kumar, Prabhav Gupta

Autonomous navigation by drones using onboard sensors, combined with deep learning and computer vision algorithms, is impacting a number of domains. We examine the use of drones to autonomously follow and assist Visually Impaired People (VIPs) in navigating urban environments. Estimating the absolute distance between the drone and the VIP, and to nearby obje

Nat Gopalswamy, Pertti Mäkelä, Sachiko Akiyama, Hong Xie

We report on the 2024 September 9 sustained gamma ray emission (SGRE) event observed by the Large Area Telescope (LAT) onboard the Fermi satellite. The event was associated with a backside solar eruption observed by multiple spacecraft such as the Solar and Heliospheric Observatory (SOHO), Solar Terrestrial Relations Observatory (STEREO), Parker Solar Probe

Wayne Zheng, Jia-Xin Zhang, Zheng-Yuan Yue, Zheng-Cheng Gu

We apply the fermionic tensor network (TN) state method to understand the strongly correlated nature in a doped Mott insulator. We conduct a comparative study of the $\sigma t$-$J$ model, in which the no-double-occupancy constraint remains unchanged but the quantum phase string effect associated with doped holes is precisely switched off. Thus, the ground st

Robert Vertesi

Heavy-flavor production at the LHC offers valuable tests of quantum-chromodynamics calculations, owing to the large masses of heavy quarks. Measurements of charm production as a function of event activity reveal new features of charm production and fragmentation, providing insights to the interplay between soft and hard processes. In addition, charm producti

Jiachen Jiang, Dominic J. Walton, Luigi C. Gallo, Andrew C. Fabian

Narrow-line Seyfert 1 AGNs (NLS1s) represent a unique stage in the black hole growth history, characterised by low black hole masses of approximately $10^{6}$-$10^{8}$ solar masses and around-Eddington accretion rates. X-ray studies of NLS1s have largely been confined to the local Universe ($z < 0.2$), while their broad-line counterparts and radio-loud quasa

Anders Blilie, Nita Mulliqi, Xiaoyi Ji, Kelvin Szolnoky

Prostate cancer diagnosis heavily relies on histopathological evaluation, which is subject to variability. While immunohistochemical staining (IHC) assists in distinguishing benign from malignant tissue, it involves increased work, higher costs, and diagnostic delays. Artificial intelligence (AI) presents a promising solution to reduce reliance on IHC by acc

Minghan Wang, Ye Bai, Yuxia Wang, Thuy-Trang Vu

High-quality speech dialogue datasets are crucial for Speech-LLM development, yet existing acquisition methods face significant limitations. Human recordings incur high costs and privacy concerns, while synthetic approaches often lack conversational authenticity. To address these challenges, we introduce \textsc{SpeechDialogueFactory}, a production-ready fra

Z. K. Silagadze

Central supermassive black holes are found in most massive galaxies. However, their origin is still poorly understood. Observations of quasars show that many supermassive black holes existed less than 700 million years after the Big Bang. To explain the existence of such black holes with masses comparable to the stellar mass of the host galaxy, just ~500 mil

Daniel Jirovec, Pablo Cova Fariña, Stefano Reale, Stefan D. Oosterhout

Coupled spins in semiconductor quantum dots are a versatile platform for quantum computing and simulations of complex many-body phenomena. However, on the path of scale-up, cross-talk from densely packed electrodes poses a severe challenge. While cross-talk onto the dot potentials is nowadays routinely compensated for, cross-talk on the exchange interaction

Timothy C. Burness

The depth of a subgroup $H$ of a finite group $G$ is a positive integer defined with respect to the inclusion of the corresponding complex group algebras $\mathbb{C}H \subseteq \mathbb{C}G$. This notion was originally introduced by Boltje, Danz and K\"{u}lshammer in 2011, and it has been the subject of numerous papers in recent years. In this paper, we study

Xuyang Li, Chenyu Li, Pedram Ghamisi, Danfeng Hong

The rapid expansion of multi-source satellite imagery drives innovation in Earth observation, opening unprecedented opportunities for Remote Sensing Foundation Models to harness diverse data. However, many existing models remain constrained by fixed spatial resolutions and patch sizes, limiting their ability to fully exploit the heterogeneous spatial charact

Alberto Vecchiato, Alexey Butkevich, Mario Gai, Valentina Cesare

In this contribution we give a brief account of the problem of the Global Astrometric Sphere Reconstruction in Astrometry, with particular reference to the Gaia and Gaia-like astrometric missions, namely those adopting a scanning strategy with observations in TDI mode. We sketch the design of the Gaia mission, the mathematical modelling that comes naturally

Hayato Taya, Yuto Takatsu, Hiroyasu Koizumi

A theory for cuprate superconductivity predicts the existence of nano-sized loop currents called, ``spin-vortex-induced loop currents (SVILCs)''. In this wok, we first calculate magnetic fields produced by them in a single bilayer Bi$_2$Sr$_2$CaCu$_2$O$_{8+\delta}$ (Bi-2212) thin film for the purpose of detecting the SVILCs. The estimated magnitude of the ma

Ji Woo Han

This comprehensive study investigates the intricate relationship between water scarcity and agricultural production, emphasizing its critical global significance. The research, through multidimensional analysis, investigates the various effects of water scarcity on crop productivity, especially the economic water scarcity (AEWS) which is the main factor of i

M. Agundez, C. Cabezas, N. Marcelino, B. Tercero

The molecule 1,3-butadiene (CH2CHCHCH2) could play a key role in the synthesis of the cyclic molecules cyclopentadiene and benzene in cold dense clouds. Since 1,3-butadiene is non-polar, we searched for its cyano derivative, which exists in the form of three different polar isomers, in the cold dense cloud TMC-1. We used the most recent data obtained with th

Teng Wang, Xu Feng, Bing-Nan Lu

We present an \textit{ab initio} calculation of nuclear $\beta$ decay within the framework of nuclear lattice effective field theory (NLEFT), employing auxiliary-field quantum Monte Carlo methods to solve the nuclear many-body problem. Our approach combines next-to-next-to-leading order two- and three-body chiral interactions with one- and two-body axial cur

Flip de Jong, Pablo Diez-Silva, Jui-Kai Chen, Raúl Pérez-Peláez

Sorting, filtering, moving and controlling colloidal particles is crucial in many fields, ranging from chemistry to biology and physics. Dielectrophoresis is an outstanding tool for the manipulation of small particles by AC electric fields, due to its high selectivity and the absence of the need for labels. We use a new theoretical-experimental approach to s

Yuriy Golovaty, Rostyslav Hryniv, Stanislav Lavrynenko

We introduce a new exactly solvable model in quantum mechanics that describes the propagation of particles through a potential field created by regularly spaced $\delta'$-type point interactions, which model the localized dipoles often observed in crystal structures. We refer to the corresponding potentials as $\delta'_\theta$-combs, where the parameter $\th

Antoine Demiquel, Vassos Achilleos, Georgios Theocharis, Vincent Tournat

We explore the generation of extreme wave events in mechanical metamaterials using the regularization of the gradient catastrophe theory developed by A. Tovbis and M. Bertola for the nonlinear Schr\"odinger equation. According to this theory, Peregrine solitons can locally emerge in the semiclassical limit of the nonlinear Schr\"odinger equation. Our objecti

Yifei Yang, Lu Chen, Zherui Song, Yenan Chen

Grasp-based manipulation tasks are fundamental to robots interacting with their environments, yet gripper state ambiguity significantly reduces the robustness of imitation learning policies for these tasks. Data-driven solutions face the challenge of high real-world data costs, while simulation data, despite its low costs, is limited by the sim-to-real gap.

Sophie Morier-Genoud, Valentin Ovsienko

The concept of $q$-deformation, or ``$q$-analogue'' arises in many areas of mathematics. In algebra and representation theory, it is the origin of quantum groups; $q$-deformations are important for knot invariants, combinatorial enumeration, discrete geometry, analysis, and many other parts of mathematics. In mathematical physics, $q$-deformations are often

Yuki Kanakubo, Gleb Koshevoy, Toshiki Nakashima

We show that a $q$-character of a Kirillov-Reshetikhin module (KR modules) for untwisted quantum affine algebras of simply laced types $A_n^{(1)}$, $D_n^{(1)}$, $E_6^{(1)}$, $E_7^{(1)}$, $E_8^{(1)}$ might be obtained from a specific cluster variable of a seed obtained by applying a maximal green sequence to the initial (infinite) quiver of the Hernandez-Lecl

Nicolas Gillis, Margherita Porcelli, Giovanni Seraghiti

ReLU matrix decomposition (RMD) is the following problem: given a sparse, nonnegative matrix $X$ and a factorization rank $r$, identify a rank-$r$ matrix $\Theta$ such that $X\approx \max(0,\Theta)$. RMD is a particular instance of nonlinear matrix decomposition (NMD) that finds application in data compression, matrix completion with entries missing not at r

Tomas Fullana, Alejandro Quirós Rodríguez, Vincent Le Chenadec, Taraneh Sayadi

In this work, we propose an adjoint-based optimization procedure to control the onset of the Rayleigh-B\'enard instability with a melting front. A novel cut cell method is used to solve the Navier-Stokes equations in the Boussinesq approximation and the convection-diffusion equation in the fluid layer, as well as the heat equation in the solid phase. To trac