April 2026 arXiv papers — page 110

Biswarup Paul

We present a comprehensive study of $Υ(nS)$ ($n=1,2,3$) production in proton-proton ($pp$) collisions at various LHC energies and rapidity ranges within the framework of leading-order non-relativistic quantum chromodynamics (NRQCD) factorization. The transverse momentum ($p_{\rm T}$)-dependent production cross sections are calculated, incorporating both dire

Christian Schmidt

We discuss the status and progress of recent efforts to modernize the International Lattice Data Grid(ILDG).This includes activities of the metadata and middleware workinggroups concerning deployment and operation of crucial services (user management, metadata catalogues, file catalogues) and extensions of the metadata format, which have been tailored accord

Stefan Škondrić, Alessandro Violini

In this article, we study Lions' density patch problem in two space dimensions at critical regularity. We prove global existence, uniqueness, and stability for a fluid occupying a bounded Lipschitz region surrounded by vacuum and evolving according to the incompressible Navier--Stokes equations, with initial velocity in $\dot{B}^0_{2,1}(\mathbb{R}^2)$. Moreo

Jean-Baptiste Vienney

A differential modality is a comonad on an additive symmetric monoidal category $(\mathsf{C},\otimes,I)$, whose underlying functor we denote $!\colon\mathsf{C} \rightarrow \mathsf{C}$, together with some additional structure including a differential operator $\partial\colon!A \otimes A \rightarrow !A$. A morphism $f\colon !A \rightarrow B$ is interpreted as

Paulin de Schoulepnikoff, Hendrik Poulsen Nautrup, Hans J. Briegel, Gorka Muñoz-Gil

Interpretable machine learning techniques are becoming essential tools for extracting physical insights from complex quantum data. We build on recent advances in variational autoencoders to demonstrate that such models can learn physically meaningful and interpretable representations from a broad class of unlabeled quantum datasets. From raw measurement data

Lang Qin, Zelin Liu, Rongjie Li, Zhiqiang Huang

High-precision indoor sensing using monostatic multiple-input multiple-output (MIMO) radar typically relies on increasing the physical aperture size of antennas, leading to high hardware complexity and cost. To overcome this bottleneck, this paper establishes a unified framework for multi-site radar sensing based on equivalent angular resolution, together wi

Yuqi Wang, Wei-Hai Fang, Zhendong Li

The GW approximation is a cornerstone of many-body perturbation theory for computing single-particle excitations, yet it can fail qualitatively in strongly correlated systems where the single-reference picture becomes inadequate. To overcome this limitation, we develop a diagrammatic route to multi-reference GW (MR-GW) from an interacting active-space refere

Yaping Mao

In 1981, Erd\H{o}s and Faudree asked whether there exists an infinite family of graphs $G_N$ on $N$ vertices with $\Delta(G_N)<N-1$ and $\sri(G_N)=1$, and whether every family with $|V(G_N)|=N$ and $\Delta(G_N)<c$ for some fixed constant $c$ must satisfy $\sri(G_N)\to 0$. We show first that the literal forms of the two questions are controlled entirely by is

Guangyu Wang, Xiaodong Ma, Xinming Wu

Borehole breakouts are stress-induced spalling on the borehole wall, which are identifiable in acoustic image logs as paired zones with near-symmetry azimuths, low acoustic amplitudes, and increased borehole radius. Accurate breakout characterization is crucial for in-situ stress analysis. In recent years, deep learning has been introduced to automate the ti

Rikuto Otsuka, Yuho Shoji, Yuka Ogino, Takahiro Toizumi

This paper proposes image-adaptive contrast limited adaptive histogram equalization (IA-CLAHE). Conventional CLAHE is widely used to boost the performance of various computer vision tasks and to improve visual quality for human perception in practical industrial applications. CLAHE applies contrast limited histogram equalization to each local region to enhan

Xingyan Chen, Tian Du, Changqiao Xu, Fuzhen Zhuang

Federated Learning (FL) faces challenges from client data heterogeneity and resource-constrained mobile devices, which can degrade model accuracy. Personalized Federated Learning (PFL) addresses this issue by adapting shared global knowledge to local data distributions. A promising approach in PFL is model decoupling, which separates the model into global an

Haoran Wu, Zeyu Cao, Yao Lai, Binglei Lou

Emerging agentic LLM workloads are driving rapidly growing demand on both memory capacity and bandwidth, with different phases of inference (e.g., prefill and decode) imposing distinct requirements. Industry is responding by composing heterogeneous accelerators into single interconnected systems, as exemplified by NVIDIA's Vera Rubin platform, where each dev

Sergei A. Klioner

This paper summarizes theoretical definitions of the relativistic coordinate time scales introduced by the IAU 2000 framework as well as practical aspects of their use. It is argued that the IAU framework already defines relativistic local GCRS-like reference systems and the corresponding TCG-like coordinates times for each body of the Solar system. The inte

Marek Gazdzicki, Francesco Giacosa, Katarzyna Grebieszkow, David Blaschke

This report summarizes the presentations and discussions during the ISO-BREAK 25 Workshop ``Isospin symmetry violation: kaons and beyond'', which was held at Jan Kochanowski University in Kielce on October 23-25, 2025. We address the current status of the isospin-symmetry breaking discovered by NA61/SHINE in nucleus-nucleus collisions at the CERN SPS, its co

Gunjan Yadav, Nilamoni Daloi, Pardeep Kumar, M. Bhattacharya

We theoretically investigate an annularly confined Bose-Einstein Condensate (BEC) coupled to a four-mirror ring cavity supporting traveling-wave optical modes. Under symmetric driving by counter-propagating Laguerre-Gaussian beams carrying equal and opposite orbital angular momenta, the system realizes supersolid phases coexisting with persistent superfluid

Jiazheng Zhang, Ziche Fu, Zhiheng Xi, Wenqing Jing

Verifiers have been demonstrated to enhance LLM reasoning via test-time scaling (TTS). Yet, they face significant challenges in complex domains. Error propagation from incorrect intermediate reasoning can lead to false positives for seemingly plausible solutions, while lacking external grounding makes verifiers unreliable on computation or knowledge-intensiv

Jiashuo Cao, Chen Li, Wujie Gao, Simon Hoermann

Virtual agents have shown promising potential in mental health applications, but current research has predominantly focused on contexts outside of traditional therapy sessions. This paper examines the impact of a virtual supporter in remote psychotherapy sessions conducted via Zoom. We used a two-phase research approach. First we conducted a formative study

Yukun Chen, Xiangdi Fu, Zhaofeng Lin, Yanqi Qiu

A Berry--Ess\'{e}en theorem for linear combinations of iterates of an inner function is obtained. Our proof, which is based an elementary transfer argument and classical results in martingale theory, also leads to a simple proof of Nicolau and Soler i Gibert's central limit theorem for inner functions.

Yuqing Nie, Chong Wang, Guosheng Xu, Guoai Xu

Code Large Language Models (Code LLMs) have revolutionized software development but raised critical concerns regarding code provenance, copyright protection, and security. Existing code watermarking approaches suffer from two fundamental limitations: black-box methods either exhibit detectable syntactic patterns vulnerable to statistical analysis or rely on

Rahul Barthwal, Philipp Öffner, Christian Rohde

We prove the existence of global weak entropy solutions for a class of non-symmetric Keyfitz-Kranzer type systems that includes lubrication models for thin-film flow. We identify a family of entropy/entropy-flux pairs for these first-order systems, which is, in particular, admissible for a tailored second-order approximate system. The latter is motivated by

Ke Xiong, Qian Wu, Wangjie Gan, Yuke Li

Few-shot Hierarchical Text Classification (few-shot HTC) is a challenging task that involves mapping texts to a predefined tree-structured label hierarchy under data-scarce conditions. While current approaches utilize structural constraints from the label hierarchy to maintain parent-child prediction consistency, they face a critical bottleneck, the difficul

Lúcio Folly Sanches Zebendo, Eleonora Cicciarella, Michele Rossi

Spiking neural networks (SNNs) are rapidly gaining momentum as an alternative to conventional artificial neural networks in resource constrained edge systems. In this work, we continue a recent research line on recurrent SNNs where axonal delays are learned at runtime along with the other network parameters. The first proposed approach, dubbed DelRec, demons

Jinghan Zhang, Xitao Gong, Qi Wang, Richard A. Stirling-Gallacher

Wireless radiance field (WRF) reconstruction aims to learn a continuous, queryable representation of radio frequency characteristics over 3D space and direction, from which specific quantities, such as the spatial power spectrum (SPS) at a receiver given a transmitter position, can be predicted. While Gaussian splatting (GS)-based method has surpassed Neural

Ali Eslami, Jiangbo Yu, Mohammad Pirani

This paper studies the vehicle bicycle model under three classes of stealthy cyber-attacks: replay attacks, zero dynamics attacks, and covert attacks. Using a system-theoretic framework, we analyze the feasibility and impact of these attacks on vehicle lateral dynamics. The investigation considers different measurement configurations, including yaw rate, lat

Avelino Vicente

Neutrino masses provide one of the clearest indications of physics beyond the Standard Model. In this brief review, I discuss the main theoretical frameworks developed to account for them, with particular emphasis on scenarios in which neutrinos are Majorana particles. After a short overview of the current landscape of neutrino mass models, I focus on constr

Qiang Xu, Shengyuan Bai, Yu Wang, He Cao

Multimodal Large Language Models (MLLMs) excel at recognizing individual visual elements and reasoning over simple linear diagrams. However, when faced with complex topological structures involving branching paths, converging flows, and cyclic dependencies, their reasoning capabilities degrade sharply, even on tasks as basic as counting endpoints. Existing b

Shujing Pan, Julian Scheuer

This paper is about hypersurfaces with boundary lying in the Euclidean unit ball, which meet the unit sphere at a fixed angle $\theta\in(0,\frac{\pi}{2}]$. Such hypersurfaces are called $\theta$-capillary hypersurfaces and for those we introduce a new notion of convexity, which we call $\theta$-horocap-convexity. For such hypersurfaces, we prove the converge

Pablo F. Castro

This paper introduces SATFuL, a SAT solver for fuzzy logics. In contrast to the Boolean case, for which numerous SAT solvers exist, the SAT problem for fuzzy logics has attracted less attention, even though these tools have interesting applications. Unlike existing SAT solvers for fuzzy logics, SATFuL uses MINLP (Mixed Integer Non-Linear Programming) solvers

Kemal Bayik, Olayinka Ajayi, Daniel Roggen, Philip Birch

Wi-Fi Channel State Information (CSI) enables device-free human activity recognition, but existing multi-user approaches assume a fixed set of known users during both training and inference. This closed-set assumption limits deployment, as models trained on a specific user set degrade when applied to new individuals or environments. We reformulate multi-user

S. E. Chorfi, F. Et-tahri, L. Maniar

In this work, we initiate the study of the biharmonic heat equation in a spatial bounded domain subject to dynamic boundary conditions involving the bi-Laplace-Beltrami operator on the boundary. The boundary heat equation is coupled to the interior one via a normal derivative term. By combining the sesquilinear form method and semigroup theory, we establish

Delfina S. Martinez Pandiani, Ella Streefkerk, Laurens Naudts, Paula Helm

This paper traces a conceptual shift from understanding vulnerability as a static, essentialized property of data subjects to examining how it is actively enacted through data practices. Unlike reflexive ethical frameworks focused on missing or counter-data, we address the condition of abundance inherent to platformized life-a context where a near inexhausti

M. V. Ivanov, A. N. Antonov

The quasielastic cross-sections of charged-current neutrino and antineutrino scattering on $^{12}$C are calculated using the coherent density fluctuation model with a relativistic effective mass $m_N^* =0.8 m_N$ (CDFM$_{M^*}$). The model explicitly considers the modification of the relativistic effective mass of the nucleon within the relativistic mean field

Markus Uehlein, Tobias Held, Christopher Seibel, Lukas G. Jonda

Computational physics increasingly depends on large simulation datasets generated by software that remains under active development for many years. In such settings, reproducibility requires not only well documented data but also explicit links between code versions, simulation inputs, generated outputs, analysis steps, and published figures. Here, we presen

Jiaying Zhu, Baoqi Zhang, Mengxia Tao, Kezhi Li

Ensuring functional consistency between high-level algorithmic models and low-level hardware implementations is a critical challenge, particularly as modern design flows increasingly span heterogeneous abstractions--from deep learning frameworks to hardware netlists. In this paper, we present EquivFusion, an end-to-end equivalence checking tool tailored for

Paul Romatschke, Ulrike Romatschke

Recently, self-dualities based on saddle-point expansions have been proposed as a means to obtain qualitative non-perturbative information in scalar field theories. In this work, we test this proposition quantitatively by studying the phase transition for critical scalar $\phi^4$ field theory in 1+1 dimensions using a variational method. We find that saddle-

Marcin Hoffmann, Paweł Kryszkiewicz

This paper proposes a Radio Environment Map (REM) for energy-efficient (EE) serving cluster formulation in a user-centric cell-free network. By incorporating the location of the user and the characteristics of the power amplifier, REM enables EE to be improved by up to 19%.

Yimin Huang, Tiancheng Qi, Quanshui Wu, Ruipeng Zhu

In this paper, we study the Chevalley property of Cayley-Hamilton Hopf algebras in the sense of De Concini-Procesi-Reshetikhin-Rosso using discriminant ideals. For any affine Cayley-Hamilton Hopf algebra $(H,C,\text{tr})$ whose identity fiber algebra has the Chevalley property, we prove that an irreducible $H$-module $V$ has the property that $V\otimes W$ is

Mahyar Hassani-Vasmejani, Hosein Alavi-Rad, Meysam Bagheri Tagani

The landscape of condensed matter physics is facing an unprecedented data surge driven by high-throughput ab initio workflows and rapidly expanding experimental datasets. Traditional first-principles methods such as Density Functional Theory (DFT), despite their foundational role, suffer from cubic scaling, creating a major bottleneck when exploring the vast

Caroline Tornow, Julia Rupprecht, Pascal Engeler, Ute Drechsler

Topological insulators are typically characterized by particularly stable properties, such as global invariants, and can be identified by probing their robust surface states. A recently discovered novel form of band topology, delicate topology, challenges this paradigm: its defining property, multicellularity, can be removed by introducing a coupling to loca

J. Frechilla, A. Frechilla, G. F. de la Fuente, A. Larrea

Laser nitriding represents a versatile approach for tailoring the surface properties of metals. Up to now, its effect on the superconducting response of niobium nitrides remains largely unexplored. In this work, the nitriding process of niobium by laser irradiation under a controlled nitrogen atmosphere up to 2.50 bar, using a nanosecond pulsed laser with wa

Erik Kennerland

This paper examines a stochastic deconvolution problem on compact symmetric spaces which is referred to as decompounding. This involves estimating the step distributions of a random walk, where in addition the number of steps between observations is unknown. The harmonic analysis of symmetric spaces is used to construct an estimator to the problem which conv

Zhijiang Tang, Jiaxin Qi, Yan Cui, Jinli Ou

DNA sequence encoding is fundamental to gene function prediction, protein synthesis, and diverse downstream biological tasks. Despite the substantial progress achieved by large-scale DNA sequence pretraining, existing studies have overwhelmingly emphasized pretraining scale and custom downstream evaluation datasets, while neglecting some essential components

Chenye Wang, Qingyuan Cai, Saihui Hou, Aoqi Li

Gait recognition has emerged as a powerful biometric technique for identifying individuals at a distance without requiring user cooperation. Most existing methods focus primarily on RGB-derived modalities, which fall short in real-world scenarios requiring multi-modal collaboration and cross-modal retrieval. To overcome these challenges, we present MMGait, a

Lukas Panneke, Heike Wehrheim

Folklore is often saying "The Java memory model is broken." Therefore, several approaches have proposed repairs, only to find new programs exhibiting unexpected, unintuitive behavior or the model forbidding standard compiler optimizations. The complexity of defining a memory model for concurrent Java lies in the fact that it requires a multi-execution model.

Marcin Hoffmann, Paweł Kryszkiewicz

M-MIMO is one of the crucial technologies for increasing spectral and energy efficiency of wireless networks. Most of the current works assume that M-MIMO arrays are equipped with a linear front end. However, ongoing efforts to make wireless networks more energy-efficient push the hardware to the limits, where its nonlinear behavior appears. This is especial

Zhenhua Zhu, Ziqiang Wang, Dong E. Liu

The interplay between charge density waves (CDWs) and superconductivity is a central theme in quantum materials, yet how CDW phase textures govern vortex topology remains poorly understood. We develop a theoretical framework showing that the phase of a stripe CDW can switch a magnetic vortex between topological and trivial regimes. Motivated by recent experi

Christian Klein, El Mehdi Zejly

The double Schwarzschild solution in the equal mass case is studied in bispherical coordinates. An explicit conformal transformation from cylindrical Weyl coordinates to bispherical coordinates is given in terms of elliptic functions. A multi-domain spectral method for spacetimes in bispherical coordinates is presented to numerically reconstruct this solutio

Lokenath Thakur

In this artcle, we introduce and investigate a subclass of Bazilevi{\v{c}} functions, denoted by $\mathcal{B}_{\varphi_{A,B}}(\alpha^{(m)})$. We determine the Hardy space to which this subclass of Bazilevi{\v{c}} functions belong to. Additionally, we provide a necessary condition for a particular case of this subclass. Finally, we obtain a sharp coefficient

Bence Ladóczk, Miklós Rásonyi, János Tapolcai

A central question of the Ethereum ecosystem is where Maximal Extractable Value (MEV)revenue originates and to what extent it stems from harming unsuspecting users. It is acceptable if MEV arises from arbitrages between centralised and decentralised exchanges (CEX-DEX). Yet theoretical models have significantly underestimated the scale of these arbitrages, w

Haoyu Bian, Chaoning Zhang, Jiaquan Zhang, Xingyao Li

LLM-driven multi-agent frameworks address complex reasoning tasks through multi-role collaboration. However, existing approaches often suffer from reasoning instability, where individual agent errors are amplified through collaboration, undermining overall performance. Current research mainly focuses on enhancing high-capability agents or suppressing unrelia

Josua D. Schär, Simon Storz, Paul Magnard, Philipp Kurpiers

Quantum technologies promise a radically new way to solve classically intractable computing problems. Superconducting circuits as a platform are at the forefront of this field. The cryogenic operation temperatures of superconducting circuits however impose challenges for the further scaling to many connected quantum information processing units into a local

Florin Felix Nichita

I was interested in the work of Solomon Marcus in Mathematical Linguistics as a high-school student. Later, I had the opportunity to discuss with him about many topics. He was a polymath. We wrote a paper together, and I refereed an editorial paper about his work in 2021. Samples of (possible) discussions are presented: some topology conjectures, a self-dual

B. N. J. Persson

The temperature increase in the contact regions between solids in sliding contact has a huge influence on friction and wear. Here we test an analytical theory for the flash temperature, valid for randomly rough surface with multiscale roughness, by comparing the theory predictions with the experimental results of Sutter et al \cite{Sutter} for steel sliding

Isak Sundelius

We define the category of $G_2$-structures over a Riemannian 7-manifold $M$ and present an isomorphism between this category and a full subcategory of the category of octonion algebras over the ring of smooth real-valued functions $C^\infty(M)$ of the same manifold $M$. A classification of $G_2$-structures in the same metric class is shown to agree with a pa

Prabin Bohara, Pralhad Kumar Shrestha, Arpan Rai, Usha Poudel Lamgade

Accurate automatic brain tumor segmentation in Low and Middle-Income (LMIC) countries is challenging due to the lack of defined national imaging protocols, diverse imaging data, extensive use of low-field Magnetic Resonance Imaging (MRI) scanners and limited health-care resources. As part of the Brain Tumor Segmentation (BraTS) Africa 2025 Challenge, we appl

Florian Sihler, Oliver Gerstl, Lars Pfrenger, Julian Schubert

A lot of research relies on data analysis scripts to process, clean, and visualize data. However, recent studies show that these scripts are often hard to comprehend and maintain, hindering reproducibility and reuse, accompanied by a lack of tool support for handling such scripts. In this work, we focus on the R programming language, addressing this problem

Ana-Andreea Stoica, Celestine Mendler-Duenner, Moritz Hardt

Digital labor platforms are increasingly used to procure human input, ranging from annotating data and red-teaming AI models, to ride-sharing and food delivery. A central concern in such markets is the ability of platforms to suppress wages by exploiting the abundance of low-cost labor. To study this exploitation pattern, we introduce a novel posted-price pr

Jean-Baptiste Escudié, Benjamin Barnes, Stefan Meisegeier, Klaus Kraywinkel

There is no consensus in the field of synthetic data on concise metrics for quality evaluations or benchmarks on large health datasets, such as historical epidemiological data. This study presents an evaluation of seven recent models from major machine learning families. The models were evaluated using four different datasets, each with a distinct scale. To

Haitao Yang, Ruiqi Hu, Heng Wu, Xiaolong He

Two-dimensional materials are expected to play an important role in next-generation electronics and optoelectronic devices. Recently, twisted bilayer graphene and transition metal dichalcogenides have attracted significant attention due to their unique physical properties and potential applications. In this study we describe the use of optical microscopy to

Andreea-Elena Bodea, Stephen Meisenbacher, Florian Matthes

Despite the considerable promise of Retrieval-Augmented Generation (RAG), many real-world use cases may create privacy concerns, where the purported utility of RAG-enabled insights comes at the risk of exposing private information to either the LLM or the end user requesting the response. As a potential mitigation, using anonymization techniques to remove pe

Xhevahire Tërnava, Georges Aaron Randrianaina, Luc Lesoil, Mathieu Acher

Many small-scale software systems, that is, with limited codebase or binary size, are widely used in everyday tasks, yet their configurability remains largely unexplored. At the same time, studies on modern software systems show a trend toward increasing configurability, alongside growing interest in building immutable, specialized, and reproducible software

Kangchun Zhao, Haitian Yang, Yijie Mao

Ultra-massive multiple-input multiple-output (UM-MIMO) is a key technology for enabling terahertz (THz) communications in 6G networks, offering high beamforming gain to combat severe path loss. However, the large antenna array expands the near-field region, resulting in a hybrid near- and far-field communication environment. This makes channel estimation sig

Leo Bürk, Artjom Hermann, Markus Weyrauch, Markus Uhlmann

Particle-resolved direct numerical simulation (PR-DNS) is performed for turbulent open channel flow over a smooth horizontal wall with a vertical cylinder and a dilute set of mobile, heavy, spherical particles. At the chosen parameter point (which matches a previous study without a cylinder) the particles are mostly translating in the horizontal plane while

Federico Herrero-Hervás, Mihaela Negreanu

In this paper, we investigate the long-time dynamics of a repulsive Keller-Segel chemotaxis system. The model features negative chemotaxis, logistic growth and a cell death term, accounting for a lethal chemorepellent that is self-produced by the cells and externally supplied. We prove that, for constant chemorepellent supplies, depending on their magnitude

Wanyan Chen, Miao Chen, Yu-Han Ma

While externally driven information engines are well understood, the thermodynamic constraints of their autonomous counterparts remain an open question. Here, we investigate the finite-time operation of an autonomous machine functioning as both an information eraser and a refrigerator, revealing that its irreversibility is bounded by the transient informatio

Vicenç Méndez, Carlos Hervás, Rosa Flaquer-Galmés

We derive the first two moments of generic positive stochastic functionals in terms of the one- and two-time probability density functions of the underlying random walk, and we prove ergodicity of observables in stationary random walks. These general results are applied to the half-occupation time and the occupation time in an interval of a Gaussian random w

Hamed Jelodar, Samita Bai, Mohammad Meymani, Parisa Hamedi

Generative AI, particularly Large Language Models, increasingly integrates graph-based representations to enhance reasoning, retrieval, and structured decision-making. Despite rapid advances, there remains limited clarity regarding when, why, where, and what types of graph-LLM integrations are most appropriate across applications. This survey provides a conc

Thomas Le Deun, Joël Rovera, Kevin Heggarty

The serial nature of two-photon polymerization (2PP) limits fabrication throughput. While diffractive optical elements (DOEs) can be used to generate multiple write spots in a single plane, three-dimensional structures still require sequential layer-by-layer fabrication. We demonstrate a dual-plane multi-spot 2PP approach using a single static DOE capable of

Patrizio Cintioli

Dëgtev proved that if a noncomputable computably enumerable set \(U\) satisfies his property \((R)\) and the many-one degree of \(U\) contains no simple set, then the \(1\)-degree of \(U\) is minimal. We show that his proof yields the stronger conclusion that, for every noncomputable \(A\lem U\), \[ U\le_1 A. \] In particular, the injectivity of the reductio

Jinhao Shen, Haoqian Du, Xulu Zhang, Xiao-Yong Wei

Text-guided image editing, a pivotal task in modern multimedia content creation, has seen remarkable progress with training-free methods that eliminate the need for additional optimization. Despite recent progress, existing methods are typically constrained by a competitive paradigm in which the editing and reconstruction branches are independently driven by

David Lafontaine, Camille Laurent

We prove scattering for the defocusing energy-critical non-linear wave equation with Dirichlet boundary conditions outside two strictly convex obstacles in dimension three. This is the first large data scattering result for such an equation in the presence of trapped trajectories. Our result is in fact more general and can be used as a black box in other geo

Thomas Campagnolo, Ezio Malis, Philippe Martinet, Gaétan Bahl

Open-vocabulary semantic segmentation enables models to segment objects or image regions beyond fixed class sets, offering flexibility in dynamic environments. However, existing methods often rely on single-view images and struggle with spatial precision, especially under occlusions and near object boundaries. We propose SENSE, the first work on Stereo OpEN

Fabian Ridder, Laurin Lessel, Malte Schilling

Retrieval-Augmented Generation (RAG) is widely used to augment the input to Large Language Models (LLMs) with external information, such as recent or domain-specific knowledge. Nonetheless, current models still produce closed-domain hallucinations and generate content that is unsupported by the retrieved context. Current detection approaches typically treat

Bas Ahn, Xingjian Tao, Manil Dev Gomony, Marc Geilen

Large Language Models (LLMs) such as LLaMA and DeepSeek, are built on transformer architectures, which have become a standard model for achieving state-of-the-art performance in natural language processing tasks. Recently, there has been growing interest in deploying LLMs on edge devices. Although smaller LLM models are being proposed, they often still conta

Khang Le, Joaquín Torres-Sospedra, Philipp Müller

Fixed Radius Near Neighbor (FRNN) search is an alternative to the widely used k Nearest Neighbors (kNN) search. Unlike kNN, FRNN determines a label or an estimate for a test sample based on all training samples within a predefined distance. While this approach is beneficial in certain scenarios, assuming a fixed maximum distance for all training samples can

Xinglei Yu, Zhenyang Liu, Shufeng Nan, Simo Wu

Diffusion policies are becoming mainstream in robotic manipulation but suffer from hard negative class imbalance due to uniform sampling and lack of sample difficulty awareness, leading to slow training convergence and frequent inference timeout failures. We propose VADF (Vision-Adaptive Diffusion Policy Framework), a vision-driven dual-adaptive framework th

Nicolò Pagan, Christopher Barrie, Chris Andrew Bail, Petter Törnberg

Large Language Models (LLMs) are increasingly deployed to curate and rank human-created content, yet the nature and structure of their biases in these tasks remains poorly understood: which biases are robust across providers and platforms, and which can be mitigated through prompt design. We present a controlled simulation study mapping content selection bia

Jesse Huhtala, Iiro Vilja

We investigate momentum reconstruction for particle processes observed by Unruh-deWitt detector setups. In particular, we derive the probability distributions for particle momenta conditioned on detector clicks in three spatial dimensions. We investigate the statistical properties of such detector setups and discuss their use as models of measurement devices

Evar Jones, Daniel J. Jakubisin, Sanmay Das

Dense wireless deployments face co-channel interference from heterogeneous sources that vary across base stations (gNBs in 5G). While centralized DNN-based approaches to interference mitigation have shown strong performance, deploying and adapting these models across distributed gNBs via federated learning (FL) requires transmitting full model updates each r

Yifan Wang, Chenchao Xu, Yi Liu, Jinke Bao

Kagome metals are prone to charge-density wave (CDW), magnetic, and superconducting phases, with their flat electronic band conducive for correlated physics. In contrast to the weakly correlated $A$V$_3$Sb$_5$ ($A$ = K, Rb, Cs) kagome metals with a $2\times2$ CDW, CsCr$_3$Sb$_5$ is a correlated metal with a flat band close to the Fermi level, and exhibits a

Pontus Svensson, Thomas Chuna, Jan Vorberger, Zhandos A. Moldabekov

We present density response estimators for Monte Carlo simulations that are based on a reweighting procedure, where the samples of an unperturbed system are used to estimate the properties of a system perturbed by an external harmonic potential. This allows the linear and nonlinear static density response to be estimated purely from simulations of the unpert

Xujin Chen, Xiaodong Hu, Changjun Wang, Yuchun Xiong

This paper studies an online trading variant of the classical secretary problem, called secretary problem variant trading (SPVT), from the perspective of an intermediary who facilitates trade between a seller and $n$ buyers (collectively referred to as agents). The seller has an item, and each buyer demands the item. These agents arrive sequentially in a uni

Hirobumi Tominaga, Asuka Nakamura, Tomoaki Ishiyama, Mohamed H. Abdullah

We investigate the ability of machine learning to infer the virial mass ($M_{\rm vir}$) and the scale radius ($r_{\rm s}$) of galaxy clusters from their observables. Using the Uchuu--UniverseMachine galaxy catalog at $z=0.093$, we generate mock cluster observations that include interlopers, and we encode each cluster as an image representing the two-dimensio

Kevin M. Hickson, Jean-Christophe Loison, Audrey Coutens

Reactions occurring on the ice-covered surfaces of interstellar dust grains are considered to be among the most important sources of complex species in the interstellar medium. Despite this, molecules such as cyanamide, NH2CN, are largely underpredicted by current astrochemical models suggesting that the network of reactions currently used to describe this s

Demba Barry, Adam Chapman, Ahmed Laghribi

In this paper, study sums $A=\{a,b\}_2+\{c,d\}_2$ of two symbols in $K_2(F)/2K_2(F)$ when $\operatorname{char}(F)=2$. We first prove a chain lemma that connects $A$ to $B=\{\alpha,\beta\}_2+\{\gamma,\delta\}_2$ by a finite sequence of small steps when $A \equiv B$. We use this lemma to prove that $\{a,b,c,d\}_2 \in K_4(F)/2K_4(F)$ is a well-defined invariant

Leif Eriksson, Victor Lagerkvist, Sebastian Ordyniak, George Osipov

The quantified Boolean formula problem (QBF) is a well-known PSpace-complete problem with rich expressive power, and is generally viewed as the SAT analogue for PSpace. Given that many problems today are solved in practice by reducing to SAT, and then using highly optimized SAT solvers, it is natural to ask whether problems in PSpace are amenable to this app

Andrea Palermo, Daniele Roselli

We study a boost-invariant, out-of-equilibrium fluid of non-interacting Dirac fermions with a finite canonical spin potential. After solving the Dirac equation in Milne coordinates, we exactly diagonalize the non-equilibrium density operator and compute the partition function and expectation values of relevant observables, including spin polarization, energy

Emilie Dufresne, Gabriela Jeronimo, Jenny Kenkel, Haydee Lindo

The graph reconstruction conjecture asserts that every simple graph on at least three vertices is uniquely determined by its deck of vertex-deleted subgraphs. In this expository article we survey the conjecture and present an invariant-theoretic approach to studying it. The aim is to be able to show that polynomials that distinguish between decks also distin

Youngjae Kim, Sejoong Kim, Jun-Won Rhim

Technological progress towards next-generation electronics critically relies on achieving faster switching with reduced energy consumption. Because device operation speeds are fundamentally constrained by the intrinsic properties of constituent materials, identifying systems with inherently superior switching capabilities is essential. Here, we propose that

Jiaxin Ye, Gaoxiang Cong, Chenhui Wang, Xin-Cheng Wen

Video-to-Speech (VTS) generation aims to synthesize speech from a silent video without auditory signals. However, existing VTS methods disregard the hierarchical nature of speech, which spans coarse speaker-aware semantics to fine-grained prosodic details. This oversight hinders direct alignment between visual and speech features at specific hierarchical lev

Arya Mary K J, Deepthy K Bhaskar, Sinu T S, Binu V P

Agentic Artificial Intelligence (AI) represents a paradigm shift from reactive systems to proactive, autonomous decision making frameworks. Existing AI-based educational systems remain fragmented and lack multi-level integration across stakeholders. This paper proposes the Agentic Unified Student Support System (AUSS), a novel multi-agent architecture integr

Leontine Aarnoudse, Mark Haring, Nathan van de Wouw, Alexey Pavlov

Data-based adaptive optimization methods hold great promise for the performance optimization of uncertain, time-varying processes. However, current methods are often based on continuous perturbation which is in general undesired for real-life (e.g., industrial) applications. In this paper, a new uncertainty-based perturb-and-observe method is developed that

Jan Niklas Schmäke, Oliver Wege, Martin Ruess

An extension of the multi-level hp Finite Cell Method is proposed for the simulation of thermoviscoplastic problems with temperature-dependent material behavior. The approach combines hierarchical adaptive refinement with a non-negative moment fitting (NNMF) quadrature scheme for efficient and robust integration of non-linear, history-dependent constitutive

Szilárd Szalay, Frédéric Holweck

We present two general methods to implement quantum circuits for the direct measuring of local unitary invariants on quantum computers. We work these out for important three-qubit invariants, and also demonstrate these on the IBM Quantum Platform for important entanglement measures of three qubits.

Trever Schirmer, Aris Wiegand, Lucca di Benedetto, Linus Gustafsson

With the ever-increasing usage of serverless computing in both industry and academia, it is essential to understand the mechanisms that power the underlying platforms. As serverless is more than ten years old, there are different platforms with vastly different approaches. We show that, next to the traditional and popular platforms, a second generation of se

Narasimha Kumar, Dwipanjana Shit

Let $\mathbb{F}_{q}$ be a finite field, and $A:=\mathbb{F}_{q}[T]$. In this article, we give explicit criteria, involving concrete valuations, on the coefficients of the Drinfeld $A$-modules of rank $r$ for $r=2,3$, which ensure the surjectivity of the associated $(T)$-adic Galois representation. As a result, we shall calculate the densities of such Drinfeld

Koralia Tzanni, John Miritzis

We study flat Friedmann-Lema\^{\i}tre-Robertson-Walker (FLRW) models with a perfect fluid matter source and a scalar field minimally coupled to matter with power-law-exponential \textquotedblleft hybrid\textquotedblright potential. Using expansion-normalised variables, we formulate the field equations as a constrained three-dimensional dynamical system and d

F. Minotti, G. Modanese

We consider the application of the Fluctuation Dissipation Theorem (FDT) to the electrodynamics of Aharonov-Bohm (ABE), which differs from Maxwell's in that it allows for local non-conservation of charge. For the case of a system of non-conserved charges at thermal equilibrium we obtain the same spectral distribution of energy of the electromagnetic field as

Tianyu Zhou, Haipeng Xie, Xin Wang

Rydberg atoms, which possess exceptionally large electric dipole moments, offer a promising route for electric field sensing as well as metrology traceable to the International System of Units (SI); however, current research predominantly focuses on the microwave (MW) regime, leaving the quasi-direct current (quasi-DC) and low-frequency bands, ubiquitous in

Shitong Shao, Lichen Bai, Pengfei Wan, James Kwok

Video diffusion models have rapidly become the dominant paradigm for high-fidelity generative video synthesis, but their practical deployment remains constrained by severe inference costs. Compared with image generation, video synthesis compounds computation across spatial-temporal token growth and iterative denoising, making attention and memory traffic maj