March 2026 arXiv papers — page 19

Kazuma Ikeda, Ryosei Hara, Rokuto Nagata, Ozora Sako. Zihao Ding

LiDAR has become an essential sensing modality in autonomous driving, robotics, and smart-city applications. However, ghost points (or ghosts), which are false reflections caused by multi-path laser returns from glass and reflective surfaces, severely degrade 3D mapping and localization accuracy. Prior ghost removal relies on geometric consistency in dense p

Jiani Cao, Kun Wang, Yang Liu, Zhenjiang Li

Motor Imagery (MI) is an emerging Brain-Computer Interface (BCI) paradigm where a person imagines body movements without physical action. By decoding scalp-recorded electroencephalography (EEG) signals, BCIs establish direct communication to control external devices, offering significant potential in prosthetics, rehabilitation, and human-computer interactio

Mahdi Hormozi, Jie-Xiang Zhu

For any $1 < p < q < \infty$, we investigate fixed-time hypercontractive bounds from $L^p$ to $L^q$ of Poisson semigroups associated with the Ornstein--Uhlenbeck, Laguerre and Jacobi operators. We prove that, in the Ornstein--Uhlenbeck and Laguerre cases, the Poisson semigroups fail to be $L^p \to L^q$ bounded for any fixed $t > 0$. In contrast, for Jacobi o

Bryan Quaife, Kevin Speer

Wildfire spread is strongly influenced by the transport and ignition of embers. While long-range spotting driven by plume lofting has received significant attention, embers transported near the surface by turbulent winds can also influence fire propagation. We develop a stochastic model for near-surface ember transport, referred to as ember wash. The model r

David Bold, Brendan Shanahan

Modeling the Scape-off layer (SOL) of stellarator fusion devices is challenging due to the complicated magnetic topology, requiring numerical tools to solve transport equations for realistic geometries. Previously the flux coordinate independent (FCI) method has been successfully applied to model the SOL in simplified geometries. The current work presents so

Haijuan Liu, Zhuoqing Zheng, Cong Li, Wenying Xu

Decentralized primal-dual methods are widely used for solving decentralized optimization problems, but their updates often rely on the potentially crude first-order Taylor approximations of the objective functions, which can limit convergence speed. To overcome this, we replace the first-order Taylor approximation in the primal update of EXTRA, which can be

Yves Ruffenach

Transformers for language modeling usually rely on deterministic internal computation, with uncertainty expressed mainly at the output layer. We introduce variational neurons into Transformer feed-forward computation so that uncertainty becomes part of the internal computation itself. Concretely, we replace deterministic feed-forward units with local variati

Joffrey Dumont Le Brazidec, Simon Lang, Martin Leutbecher, Baudouin Raoult

We introduce a probabilistic diffusion-based method for global atmospheric downscaling implemented within the Anemoi framework. The approach transforms low-resolution ensemble forecasts into high-resolution ensembles by learning the conditional distribution of finer-scale residuals, defined as the difference between the high-resolution fields and the interpo

Alain Billionnet

In this article, we focus on determining a minimum-cost treatment program aimed at maintaining the size of a cancerous tumor at a level that allows the patient to live comfortably. At each predetermined point in a treatment horizon, the patient either receives drug treatment or does not. In the first case, the tumor shrinks and its size is multiplied by a co

Michela Boffi, Jessica Leoni, Fabrizio Leonforte, Mara Tanelli

Decarbonization in buildings calls for advanced control strategies that coordinate on-site renewables, grid electricity, and thermal demand. Literature approaches typically rely on demand side management strategies or on active energy storage, like batteries. However, the first solution often neglects carbon-aware objectives, and could lead to grid overload

Rajat Adak, Yash Bakshi, L. Sunil Chandran, Saraswati Girish Nanoti

The study of Ramsey-type problems for linear equations originated with Schur&#39;s theorem and was later placed in a systematic framework by Richard Rado. In the off-diagonal setting, one fixes a pair of linear equations $(\mathcal{E}_1, \mathcal{E}_2)$ and seeks the least integer $N$ such that every red--blue coloring of $\{1,2,\dots,N\}$ contains either a

Kenichi Shimizu, Harshit Yadav

We give criteria for when finitely generated local modules over a commutative algebra $A$ in the ind-completion $\widehat{\mathcal{C}}$ of a braided tensor category $\mathcal{C}$ inherit the structure of a (rigid, braided, ribbon) tensor category. We then apply this to simple current algebras $A = \bigoplus_{g \in \Gamma} E_g$, where $\Gamma$ is a subgroup o

Hengyuan Xiao, Fei Li, Shuang Liu, Yuchen Jiang

Free-electron lasers (FELs) provide a revolutionary tool for capturing the structure and dynamics of matter in real time at the atomic scale. The size and cost of FELs can be substantially reduced by using laser wakefield acceleration (LWFA), which offers acceleration gradients orders of magnitude beyond radiofrequency technology, producing multi-GeV electro

Qunqiang Feng, Zixin Tang, Zhishui Hu

This paper investigates the Fr\'echet mean of the Erd\H{o}s-R\'enyi random graph $G_{n,p}$ with respect to the Frobenius distance on graph Laplacians, a metric that captures global structural information beyond local edge flips. We first characterize the Fr\'echet mean set as consisting of quasi-regular graphs (i.e., graphs where all vertex degrees differ by

Onat Ozdemir, Anders Christensen, Stephan Alaniz, Zeynep Akata

Large-scale vision-language models such as CLIP have achieved remarkable success in zero-shot image recognition, yet their predictions remain largely opaque to human understanding. In contrast, Concept Bottleneck Models provide interpretable intermediate representations by reasoning through human-defined concepts, but they rely on concept supervision and lac

Charul Gupta, Rishabh Sharma, Tejasvi Hegde, Venkata Sai Anvesh Sangadi

This study investigates the role of inertia in moving contact lines using experiments, theoretical analysis, and numerical simulations. Experiments are conducted using a plate immersion configuration over a wide range of Reynolds numbers from $O(10^{-3})$ to $O(10)$. Flow configurations and quantitative measurements are obtained using high-speed imaging and

Sagi Della Torre, Mirco Pezzoli, Fabio Antonacci, Sharon Gannot

Room Impulse Responses estimation is a fundamental problem in spatial audio processing and speech enhancement. In this paper, we build upon our previously introduced diffusion-based inpainting framework for Room Impulse Response interpolation and demonstrate its applicability to enhancing the performance of practical multi-microphone array processing tasks.

Izzy L. Garland, Henry Best, Lucy F. Fortson, Tobias Géron

Context. Via scaling relations, it is well-known that active galactic nuclei (AGN) and bulges are linked. This link was thought to be driven by mergers, but recent studies show that secular processes are the dominant mechanism of supermassive black hole growth. One such secular mechanism is gas inflow driven by large-scale bars. Since bulges can also grow vi

Xiuhui Zuo, Zhenghua Huang, Maria S. Madjarska, Hui Fu

Transition-region loops are a type of critical magnetic structure in the solar atmosphere, yet their physical properties and evolutionary characteristics remain statistically poorly constrained. We aim to statistically characterize the physical properties of propagating brightening events in transition-region loops and to explore the underlying heating mecha

Jonathan Holland, George Sparling

This article studies wave equations and their solutions on plane wave spacetimes of arbitrary dimension, developing the interplay among three structural layers: the Ward progressing-wave representation of solutions to the scalar wave equation, the Fourier analysis of the Heisenberg group naturally associated to the plane wave, and the Schr\"odinger propagato

Esraa Fahmy Othman, Lina Bariah, Merouane Debbah

Beam alignment is a key challenge in directional mmWave and THz systems, where narrow beams require accurate yet low-overhead training. Existing learning-based approaches typically predict a single beam and do not quantify uncertainty, limiting adaptive beam sweeping. We recast beam alignment as a generative task and propose a conditional diffusion model tha

Song Yu, Li Li, Wenwen Zhao, Zhisheng Yang

Reinforcement learning from verifiable rewards has significantly advanced the reasoning capabilities of large language models. However, Group Relative Policy Optimization (GRPO) typically assigns a uniform, sequence-level advantage to all tokens, thereby overlooking the intrinsic information heterogeneity along reasoning chains. We show that this coarse-grai

Muhammed Öz, Jasmin Hörter, Kaleb Phipps, Charlotte Debus

With the rise of renewable energy sources and their high variability in generation, the management of power grids becomes increasingly complex and computationally demanding. Conventional AC-power-flow simulations, which use the Newton-Raphson (NR) method, suffer from poor scalability, making them impractical for emerging use cases such as joint transmission-

Debmalya Bandyopadhyay, Allan Lo, Richard Mycroft

We prove that every $3$-graph $H$ on $n$ vertices with minimum codegree $\delta_2(H) \geq 7n/9 + o(n)$ contains the square of a tight Hamilton cycle. This strengthens a theorem of Bedenknecht and Reiher that $\delta_2(H) \geq 4n/5 + o(n)$ is sufficient. The central novelty of our arguments is an improved understanding of the connectivity structure of $3$-gra

Tatiana Petrova, Stanislav Sokol, Radu State

Which persuasion strategies, if any, are associated with donation compliance? Answering this requires fine-grained strategy labels across a full corpus and statistical tests corrected for multiple comparisons. We annotate all 10,600 persuader turns in the 1,017-dialogue PersuasionForGood corpus (Wang et al., 2019), where donation outcomes are directly observ

Takato Shibayama, Hiroaki Kawashima

Guiding collective motion in biological groups is a fundamental challenge in understanding social interaction rules. In this study, we propose a deep reinforcement learning (RL) framework for closed-loop guidance of fish schools using virtual agents. These agents are controlled by policies trained via Proximal Policy Optimization (PPO) in simulation and depl

Jean-Marie Malherbe

The second solar spectrum is the solar spectrum of Stokes parameter Q observed in linear polarization close to the solar limb. It differs significantly of the usual intensity spectrum (Stokes parameter I). The second solar spectrum contains in the visible range a few polarized lines with Q/I > 1% (such as CaI, SrI, SrII, BaII), but most lines exhibit weak or

Hongkai Hu

Static regret to a single expert is often the wrong target for strictly online prediction under non-stationarity, where the best expert may switch repeatedly over time. We study Policy-Controlled Generalized Share (PCGS), a general strictly online framework in which the generalized-share recursion is fixed while the post-loss update controls are allowed to v

Yujie Zhang, Weikang Yuan, Zhuoren Jiang, Pengwei Yan

Pluralistic alignment is essential for adapting large language models (LLMs) to the diverse preferences of individuals and minority groups. However, existing approaches often mix stable personal traits with episode-specific factors, limiting their ability to generalize across episodes. To address this challenge, we introduce EpiPersona, a framework for expli

Neha Puri, Tim Dixon

As AI becomes embedded in customer-facing systems, ethical scrutiny has largely focused on models, data, and governance. Far less attention has been paid to how AI is experienced through user-facing design. This commentary argues that many AI front-ends implicitly assume an 'ideal user body and mind', and that this becomes visible and ethically consequential

Yiming Zhu, Yafei Wang, Carla Amatetti, Alessandro Vanelli-Coralli

The stringent link budget, caused by long propagation distances and payload constraints, poses a fundamental bottleneck for single-satellite transmission. Although LEO mega-constellations make multi-satellite cooperative transmission (MSCT), such as distributed precoding (DP), increasingly feasible, its cooperative gains critically rely on stringent time-fre

Eugenia Franco, Bernhard Kepka

In this paper we study a two-component coagulation equation that models the aggregation of rouleaux in blood. We consider product kernels that have homogeneity $2$ and we characterize the initial data that lead to gelation. We prove that, when gelation occurs, the solution to the two-component coagulation equation localizes along a direction of the space of

Fernando Albiac, José L. Ansorena

We show that inclusions of $p$-metric spaces always produce genuine linear embeddings at the level of Lipschitz-free $p$-spaces. More precisely, for every $0<p<1$ and every inclusion $ \mathit{N}\subset \mathit{M}$ of $p$-metric spaces, the canonical map from $ \mathit{F}_p(\mathit{N})$ into $ \mathit{F}_p( \mathit{M})$ is always an isomorphic embedding, as

T. de Groot, W. P. M. H. Heemels, S. J. A. M. van den Eijnden

In this letter, we prove that under mild conditions, the scaled graph of a reset control system is bounded by the scaled graph of its underlying base linear system, i.e., the system without resets. Building on this new insight, we establish that the negative feedback interconnection of a linear time-invariant plant and a reset controller is stable, if the sc

Hua Li, Yingying Li, Xiaobin Feng, Xinyi Fu

The clinical burden of spleen-stomach disorders is substantial. While large language models (LLMs) offer new potential for medical applications, they face three major challenges in the context of integrative Chinese and Western medicine (ICWM): a lack of high-quality data, the absence of models capable of effectively integrating the reasoning logic of tradit

Deepal Basak, Joyee Deb, Aditya Kuvalekar

Algorithmic content targeting homogenizes information, with implications for strategic interactions. For example, this increased homogenization was arguably responsible for the run on the Silicon Valley Bank. We argue that existing measures of similarity are inappropriate for studying games -- especially coordination games -- because they do not discipline a

Manoj Mandal, Sachindra Naik, Birendra Chhotaray

We performed a comprehensive study of thermonuclear bursts from the millisecond X-ray pulsar SAX J1808.4$-$3658 with XMM-Newton and NICER. We report the results from the analysis of an intense burst with NICER using a self-consistent and physically motivated disc reflection modeling approach and investigate the burst-disc interaction. The dynamic evolution o

Adrian Benedit-Cardenas, Tobias Fox, Stéphanie Bruyère, Christoph Pauly

The rapid advancement of digital technologies necessitates significant progress in functional materials, which are often derived from scarce elements and involve complex manufacturing processes. Additionally, the trend towards miniaturization in high-tech devices has heightened the demand for extremely small components with tailored functionalities. In the d

Jing Li, Guo-Wei Yang, Bai-Zhuo Li, Yi Liu

In one-dimensional (1D) electron systems, the Fermi liquid state breaks down due either to electron interactions, which results in a Tomonaga-Luttinger liquid (TLL) state, or to Peierls instability, which leads to an insulating charge-density-wave (CDW) phase. In general, these two phenomena are mutually exclusive, and their coexistence remains elusive in re

Maximiliano Escayola, Victor Kleptsyn

Given a finitely generated, torsion-free nilpotent group, we find the maximum possible (critical) regularity for its faithful actions by diffeomorphisms of the closed or half-open interval and of the circle. Our result gives an expression for its value in purely algebraic terms (using the relative growth of appropriate subgroups), generalizing many preceding

Tiantian Yang, Xuanle Ren, Qingdian Wan, Qi Meng

Adders are fundamental building blocks in modern digital systems, and their performance, power, and area (PPA) directly impact system efficiency. Contemporary adders typically use parallel-prefix architectures with established PPA trade-offs, but these often fail to deliver globally optimal PPA for specific design goals. Prior work lacks netlist-/cell-level

Zehua Han, Jing Xiao, Yiqi Duan, Mengyu Xiang

Multimodal Large Language Models have demonstrated powerful cross-modal understanding and reasoning capabilities in general domains. However, in the electromagnetic (EM) domain, they still face challenges such as data scarcity and insufficient integration of domain knowledge. This paper proposes PReD, the first foundation model for the EM domain that covers

Xuanlong Yu, Youyang Sha, Longfei Liu, Xi Shen

Few-shot object detection (FSOD) is challenging due to unstable optimization and limited generalization arising from the scarcity of training samples. To address these issues, we propose a hybrid ensemble decoder that enhances generalization during fine-tuning. Inspired by ensemble learning, the decoder comprises a shared hierarchical layer followed by multi

Gulzoda Rakhimova, Beyhan Puliçe, Elham Ghorani, Farruh Atamurotov

We investigate the dynamics of spinning test particles in the vicinity of Einstein--geometric Proca (EGP) Anti-de Sitter (AdS) compact objects, which arise from metric-Palatini gravity extended by the antisymmetric part of the affine curvature. Using the Mathisson-Papapetrou-Dixon (MPD) equations with the Tulczyjew spin supplementary condition, we derive the

Duc-Duy Tran, Cedric Mannequin, Fabrice Donatini, Masahiro Sasaki

We report a direct, maskless electron beam-induced etching (EBIE) process for diamond in air, enabling high-precision patterning without lithography or plasma processing. Through a comprehensive analysis of electron-gas, electron-diamond, and gas-surface interactions in the SEM environment, we demonstrate that etching is predominantly governed by low-energy

Michael T. M. Emmerich

We study the optimal placement of $k$ ordered points on the unit interval for the bounded pair potential \[ K_q(d)=e^{-d^q}, \qquad q>0. \] The family interpolates between strongly cusp-like kernels for $0<q<1$, the threshold kernel $e^{-d}$, and the flatter Gaussian-type regime $q>1$. Our emphasis is on the transition from collision-free minimizers to endpo

Yucheng Huang, Luping Ji, Xiangwei Jiang, Wen Li

3D Scene Graph (3DSG) generation plays a pivotal role in spatial understanding and affordance perception. To mitigate generalization issues from data scarcity, joint-embedding and generative proxy tasks are proposed to pre-train 3DSG representations on predicate label-free datasets. Currently, generative pre-training usually bypasses the semantic corruption

Fanny Seizilles, Maximilian Siebel

In many practical and numerical inverse problems, the exact data log-likelihood is not fully accessible, motivating the use of surrogate models. We study heteroscedastic nonparametric nonlinear regression problems with Gaussian errors and establish contraction results for posterior distributions arising from a surrogate log-likelihood constructed from proxy

Jian He, Cong Zhou, Shuo Shi

In this paper, a rate-splitting multiple access (RSMA) based joint optimization framework for the space-air-ground integrated network (SAGIN) is proposed, where the satellite and base stations employ uniform planar array (UPA) antennas for signal transmission, and unmanned aerial vehicles (UAVs) relay the satellite signals. Earth stations (ESs) and user equi

Maximilian Mihm, Stephan Glamsch, Christian Holzmann, Matthias Küß

Altermagnets are a newly identified class of materials that combine advantageous characteristics of both ferro- and antiferromagnets, making them highly promising for spintronic applications. Hematite has recently been identified as an altermagnetic material and exhibits several noteworthy properties, including a high N\'eel temperature, a temperature depend

Zixu Feng, Patrick Henning, Qinglin Tang

The structure and degeneracy of ground states of the Gross-Pitaevskii energy functional play a central role in both analysis and computation, yet a precise characterization of the ground-state manifold in the presence of symmetries remains a fundamental challenge. In this paper, we establish sharp theoretical results describing the geometric structure of loc

Weiqi Chen, Wenwei Wang, Qilong Yuan, Lefei Shen

Data-driven weather models have advanced global medium-range forecasting, yet high-resolution regional prediction remains challenging due to unresolved multiscale interactions between large-scale dynamics and small-scale processes such as terrain-induced circulations and coastal effects. This paper presents a global-regional coupling framework for kilometer-

Stefano Almi, Anna Kubin, Emanuele Tasso

The paper investigates the approximation of the symmetric Total Variation functional on graphs. Such an approximation is given in terms of a discrete and symmetric finite difference model defined on point clouds obtained by randomly sampling a reference probability measure. We identify suitable scalings of the point distribution that guarantee an almost sure

Fedor B. Lyudogovskiy

For each positive integer $n$, let $G_n$ be the graph whose vertices are the partitions of $n$, with edges given by elementary transfers of one unit between parts, followed by reordering. We study the local simplex dimension in the clique complex $K_n=\Cl(G_n)$ as a geometric thickness invariant of $G_n$. For a partition $\lambda\vdash n$, let $\tau_n(\lambd

Bori Anna Mészáros, Bálint Vető

We consider finite configurations of particles and holes sampled according to Bernoulli product measure and with a second class particle added to a random position. The stabilization time is the number of steps needed to reach an ordered state under discrete time TASEP dynamics with parallel update. We describe the additional time of stabilization caused by

Yuxing Jiao, Qing Yang, Mingcheng Yang

Under a thermodynamic gradient, for example, the concentration or temperature gradients, the colloidal particles immersed in the solvent can exhibit a directional migration along or against the gradient -- phoresis, a cross transport effect. When the solvent is an odd fluid, where the time-reversal and parity symmetries are broken microscopically, the odd tr

Xinchi Han, Weihao Jiang, Yingming Mao, Yike Liu

Recent years have witnessed the growing deployment of optical circuit switches (OCS) in commercial GPU clusters (e.g., Google A3 GPU cluster) optimized for machine learning (ML) workloads. Such clusters adopt a three-tier leaf-spine-OCS topology, servers attach to leaf-layer electronic packet switches (EPSes); these leaf switches aggregate into spine-layer E

Ane G Domingo-Aldama, Marcos Merino Prado, Alain García Olea, Josu Goikoetxea

This study presents a fully automated methodology for early prediction studies in clinical settings, leveraging information extracted from unstructured discharge reports. The proposed pipeline uses discharge reports to support the three main steps of early prediction: cohort selection, dataset generation, and outcome labeling. By processing discharge reports

Quan Zhang, Lianhang Fu, Lvsi Lian, Gwihwan Go

Equipping LLM agents with real-world tools can substantially improve productivity. However, granting agents autonomy over tool use also transfers the associated privileges to both the agent and the underlying LLM. Improper privilege usage may lead to serious consequences, including information leakage and infrastructure damage. While several benchmarks have

Guram Bezhanishvili, Marcus Tressl

We study rings of real-valued continuous functions in terms of pseudocomplementation conditions on various lattices attached to their prime spectrum. We fully characterize pseudocomplementation in all cases and have an almost complete characterization of relative pseudocomplementation.

Deguang Wu, Yiran Xue, Baigeng Wang, Rui Wang

Exciton condensation, characterized by uniform phase coherence across macroscopic length scales, has enabled the discovery of a variety of excitonic states, greatly enriching our understanding of correlated many-body physics. More exotic quantum phenomena are anticipated when the phase factor develops spatial dependence. However, whether excitonic condensate

Shadman Sakib, Oishy Fatema Akhand, Tasnia Tasneem, Shohel Ahmed

App store reviews provide a constant flow of real user feedback that can help improve software requirements. However, these reviews are often messy, informal, and difficult to analyze manually at scale. Although automated techniques exist, many do not perform well when replicated and often fail to produce clean, backlog-ready user stories for agile projects.

Bingchen Li, Zhixin Wang, Fan Li, Jiaqi Xu

Old photos preserve invaluable historical memories, making their restoration and colorization highly desirable. While existing restoration models can address some degradation issues like denoising and scratch removal, they often struggle with accurate colorization. This limitation arises from the unique degradation inherent in old photos, such as faded brigh

Michael Cooper, Samuel Cooper

Although language models demonstrate remarkable proficiency on mathematical benchmarks, it remains unclear whether this reflects true mathematical reasoning or statistical pattern matching over learning formal syntax. Most existing evaluations rely on symbolic problems grounded in established mathematical conventions, limiting insight into the models' abilit

Gefei Cai

We derive the boundary four-point Green's functions for conformal loop ensembles (CLE) with $\kappa\in(4,8)$. Specializing to $\kappa=6$ and $\kappa=16/3$, we establish the exact formulas for the boundary four-point connectivities in critical Bernoulli percolation and the FK-Ising model conjectured by Gori-Viti (2017, 2018). In particular, we identify a loga

Hadi Bakhshan, Sima Farshbaf, Adrián Travieso-Disotuar, Luciano Mijaíl Villarreal

With the emergence of data-driven approaches in science, there is growing interest in their application to manufacturing, particularly in surface precision engineering. However, generating large datasets required for model training is often impractical experimentally due to high costs and the time-intensive nature of measurements. High-fidelity synthetic dat

Banglei Guan, Yifei Bian, Zibin Liu, Haoyang Li

Background: Large engineering structures, such as space launch towers and suspension bridges, are subjected to extreme forces that cause high-speed 3D deformation and compromise safety. These structures typically operate under extreme illumination conditions. Traditional cameras often struggle to handle strong light intensity, leading to overexposure due to

Eduard Feireisl, Maria Lukacova-Medvidova, Bangwei She, Yuhuan Yuan

We study the long-time behaviour of the temperature-driven compressible flows. We show that numerical solutions of a structure-preserving finite volume method generate a discrete attractor that consists of entire discrete trajectories. Further, we prove the convergence of discrete attractors to their continuous counterparts. Theoretical results are illustrat

Constantina Chatzieleftheriou, Eirini Liotou

As wireless communication evolves, each generation of networks brings new technologies that change how we connect and interact. Artificial Intelligence (AI) is becoming crucial in shaping the future of sixth-generation (6G) networks. By combining AI and Machine Learning (ML), 6G aims to offer high data rates, low latency, and extensive connectivity for appli

J. Golonka, G. Maciejewski

Tidal interactions shape the evolution of close-in giant planets and internal gravity-wave breaking offers an efficient pathway for dynamical-tide dissipation, although its population-wide impact remains poorly constrained. We aim to quantify wave-breaking tidal dissipation for 550 hot Jupiters, accounting for stellar-parameter uncertainties. We also aim to

Shoichi Hasegawa, Akira Taniguchi, Lotfi El Hafi, Gustavo Alfonso Garcia Ricardez

Multi-robot coordination based on large language models (LLMs) has attracted growing attention, since LLMs enable the direct translation of natural language instructions into robot action plans by decomposing tasks and generating high-level plans. However, recovering from physical execution failures remains difficult, and tasks often stagnate due to the repe

Chien-Hong Cho, Hisashi Okamoto

We consider a nonlinear parabolic equation of fractional order in space and propose its numerical discretization. The fractional derivative is defined through a functional analytic setting, rather than the traditional definition of fractional derivatives such as the Riemann-Liouville derivative. Numerical experiments are reported and some conjectures are pre

Qi Chen

In this paper, by the technique of inverse relations and comparing coefficients, we establish some generalized forms of Andrews' q-series identity and two new Bailey pairs and q-identities closely related to Andrews-Warnaar's sum identity for partial theta functions.

Yuhuan Xie, Aoxuan Pan, Yi-Hua Huang, Chirui Chang

Achieving precise, object-level control in image editing remains challenging: 2D methods lack 3D awareness and often yield ambiguous or implausible results, while existing 3D-aware approaches rely on heavy optimization or incomplete monocular reconstructions. We present ObjectMorpher, a unified, interactive framework that converts ambiguous 2D edits into geo

Hendrik Richter, Frank Neumann

Graphs with diverse structural characteristics play a central role in modelling and optimization tasks. The ability to generate different types of graphs that exhibit shared properties is likewise essential for algorithm selection and configuration. However, constructing graphs that preserve high-level properties across a broad range of graph classes remains

Ege Küçükkomürcü, Simon Labouesse, Marc Allain, Thomas Chaigne

Iterative model-based image reconstruction in photoacoustic tomography (PAT) enables principled incorporation of detector physics, object-related priors, and complex acquisition strategies. However, for three-dimensional (3D) imaging scenario, the computational cost is often dominated by repeatedly solving wave equations. We propose a fast forward model for

Carlo Marra, Beatrice Alessandra Motetti, Alessio Burrello, Enrico Macii

Deploying tiny computer vision Deep Neural Networks (DNNs) on-board nano-sized drones is key for achieving autonomy, but is complicated by the extremely tight constraints of their computational platforms (approximately 10 MiB memory, 1 W power budget). Early-exit adaptive DNNs that dial down the computational effort for "easy-to-process" input frames represe

Jaume Giné, Dmitry Sinelshchikov

We consider a family of nonlinear oscillators, which is the autonomous case of the two-dimensional projective connection. We construct several classes of these oscillators that are simultaneously integrable and metrisable. This leads to families of (super)integrable two-dimensional metrics that are parametrized by arbitrary functions. In the superintegrable

Gaetana Gambino, Francesco Gargano, Alessandra Rizzo, Vincenzo Sciacca

We introduce a spatially extended mathematical model for Duchenne muscular dystrophy based on a damage-driven paradigm, in which immune recruitment is triggered by tissue injury. The model is formulated as a reaction--diffusion--chemotaxis system describing the interaction between healthy tissue, damaged fibers, immune cells and inflammatory signals. We esta

Xiao Wang, Fengfeng Zhu, Markus Braden, Karin Schmalzl

The layered honeycomb magnet $\alpha$-RuCl$_3$ has attracted intense scrutiny as a prime candidate for realizing the Kitaev quantum spin liquid, yet a consensus on its microscopic Hamiltonian remains elusive due to the material's extreme sensitivity to structural details. Here, we report a comprehensive reexamination of the low-temperature crystallographic a

Ji Han, Marta Staff, Saeema Ahmed-Kristensen

Conventional service design methods are valuable for improving healthcare experience, but are limited in scale and information capture. Based on a constructed database of 2,320 stories from patients and carers with multiple long-term conditions (MLTC), this paper shows how real-life experiences can be used to inform healthcare service redesign. By combining

Ivan Calic, Filippo Coletti, Betty Sovilla

Powder snow avalanches are highly dynamic, multiphase gravity-driven flows typically composed of a dense basal layer overlain by airborne layers in which snow particles are suspended within a turbulent air phase. Despite extensive work on related systems such as pyroclastic density currents and turbidity currents, all gravity current communities face a funda

Viktor Tarasov, Sergey Chernezhenko, Volodymyr Vashchenko, Mykhailo Shcherbina

This paper presents the principle scheme of the prototype of the fast single channel reactor operating in the traveling wave fission mode on the soft fast neutron spectrum. The reactor design has cylindrical symmetry. The problem of the radiation resistance construction materials in this experimental reactor is solved by the base proposals published by the a

Jinyuan Li, Liang Feng Zhang

As machine learning as a service (MLaaS) gains increasing popularity, it raises two critical challenges: privacy and verifiability. For privacy, clients are reluctant to disclose sensitive private information to access MLaaS, while model providers must safeguard their proprietary models. For verifiability, clients lack reliable mechanisms to ensure that clou

Chanseul Cho, Seokju Yun, Jeaseong Jeon, Seungjae Moon

Domain Generalized Semantic Segmentation (DGSS) aims to maintain robust performance across unseen target domains. Vision Foundation Models (VFMs) offer rich multi-domain knowledge that can enhance generalization. However, strategies for actively exploiting the rich subspace structures within VFMs remain under-explored, with many existing methods focusing pri

Amber Cassimon, Robin Kerstens, Walter Daems, Jan Steckel

In this paper, we investigate the capabilities of in-air 3D SONAR sensors for the monitoring of road surface conditions. Concretely, we consider two applications: Road material classification and Road damage detection and classification. While such tasks can be performed with other sensor modalities, such as camera sensors and LiDAR sensors, these sensor mod

Fran Nekvapil, Cosmin Farcău

The dependence of surface-enhanced Raman scattering (SERS) spectra on the precise axial position of the laser focus relative to a solid nanostructured substrate has received little to no attention in the literature. Here we show this dependence is both real and physically meaningful. Through vertical (Z-axis) scans varying the distance between the laser focu

Tsukasa Iwabuchi

We study the Cauchy problem for the surface quasi-geostrophic (SQG) equations in a two-dimensional bounded domain with the homogeneous Dirichlet boundary condition. We establish the unique existence of strong solutions in the critical Besov space $\dot B^2_{2,1}$, which is embedded in $C^1$. The proof is based on spectral localization using dyadic decomposit

Dan Zhang, Gray Rybka, Edward J. Daw, Robyn Evren

We estimate the synchrotron radiation of cosmic muons in a uniform magnetic field in the $\mu$eV-to-meV energy scale. Such events can potentially bring backgrounds to the axion dark matter searches. The GEANT4 software package is utilized to simulate the muon tracks in a cylindrical region of interest with an 8~T solenoid magnetic field applied. We further d

Wang Bo, Wang Cong, Wang Zhizhang

In this paper, we provide examples to show that for $1 \leq k \leq n/2$, solutions to $k$-Hessian equations $S_k(D^2u)=1$ in the exterior of a strictly convex domain need not be quasiconvex, when prescribing quadratic growth at infinity. Additionally, we give a new proof for the quasiconvexity of harmonic functions in such exterior domains that decay to zero

Shunsuke Hirotani, Kunitaka Shintani, Yoshikatsu Furusawa, Kentaro Yaji

Efficient thermal management in high-power electronic devices requires cooling channel designs that provide high heat removal while satisfying strict spatial and manufacturing constraints. This study presents a two-stage hierarchical topology optimization framework for cooling channels based on the Moving Morphable Components (MMC) method. The optimization i

Joachim Dahl Thomsen, Qianqian Lan, Nikolai S. Kiselev, Eva Duft

Magnetic van der Waals (vdW) materials are promising for memory and logic applications because of their highly tunable magnetic properties and compatibility with vdW heterostructure devices. However, coupling between magnetic textures in stacked layers is difficult to resolve in conventional plan-view measurements because the magnetic signal is integrated ov

Siyuan Ma, Bo Gao, Zikai Xiao, Hailong Wang

Recent test-time reasoning methods improve performance by generating more candidate chains or searching over larger reasoning trees, but they typically lack explicit control over when to expand, what to prune, how to repair, and when to abstain. We introduce CoT2-Meta, a training-free metacognitive reasoning framework that combines object-level chain-of-thou

Qiya Song, Yiqiang Xie, Yuan Sun, Renwei Dian

As a pivotal task that bridges remote visual and linguistic understanding, Remote Sensing Image-Text Retrieval (RSITR) has attracted considerable research interest in recent years. However, almost all RSITR methods implicitly assume that image-text pairs are matched perfectly. In practice, acquiring a large set of well-aligned data pairs is often prohibitive

Yuji Tachikawa

Recently, Altavista, Anastasi, Angius and Uranga discussed a method to construct junctions and bouquets of different perturbative string theories. Following this analysis, we here argue that three non-tachyonic ten-dimensional heterotic string theories can be joined together at a nine-dimensional junction. This is done by creating a two-dimensional non-confo

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

Measurements of the combined CP asymmetries in $\kern 0.18em\overline{\kern -0.18em B}^0 \to D_s^- D^+$ and $\kern 0.18em\overline{\kern -0.18em B}_s^0 \to D_s^+ D^-$ decays are made using proton-proton collision data collected by the LHCb experiment, corresponding to an integrated luminosity of 9fb$^{-1}$. The measurements are found to be \begin{aligned} A_

Phacharatouch Chaimongkon, Krittaporn Anukulkitch, Pornrad Srisawad, Natthaphat Thongyoo

We investigate the production of the scalar meson $f_0(980)$ in proton--proton collisions at $\sqrt{s}=5.02$~TeV using the Ultra-relativistic Quantum Molecular Dynamics (UrQMD) transport model supplemented with a $K\bar{K}$ coalescence afterburner. After conservatively tuning the UrQMD string-fragmentation parameters, the model reproduces the bulk charged-ka

Zhang Li, Zhibo Lin, Qiang Liu, Ziyang Zhang

We introduce Multilingual Document Parsing Benchmark, the first benchmark for multilingual digital and photographed document parsing. Document parsing has made remarkable strides, yet almost exclusively on clean, digital, well-formatted pages in a handful of dominant languages. No systematic benchmark exists to evaluate how models perform on digital and phot

Harry Robertshaw, Anna Barnes, Phil Blakelock, Raphael Blanc

While we are making progress in overcoming infectious diseases and cancer; one of the major medical challenges of the mid-21st century will be the rising prevalence of stroke. Large vessels occlusions are especially debilitating, yet effective treatment (needed within hours to achieve best outcomes) remains limited due to geography. One solution for improvin

Pengcheng Xue, Yan Tian, Qiutao Song, Ziyi Wang

Text-driven 3D scene editing has attracted considerable interest due to its convenience and user-friendliness. However, methods that rely on implicit 3D representations, such as Neural Radiance Fields (NeRF), while effective in rendering complex scenes, are hindered by slow processing speeds and limited control over specific regions of the scene. Moreover, e