November 2025 arXiv papers — page 185

Berk Tan Perçin

In this study, a new and natural way of constructing a stochastic Susceptible-Infected-Susceptible (SIS) model is proposed. This approach is natural in the sense that the disease transmission rate, $\beta$, is substituted with a generic, almost surely non-negative one-dimensional diffusion. The condition $\beta \geq 0$ is essential in the deterministic model

Hans Peter Büchler, Tobias F. Maier, Simon Fell, Nicolai Lang

Exactly solvable models of topologically ordered phases with non-abelian anyons typically require complicated many-body interactions which do not naturally appear in nature. This motivates the "inverse problem" of quantum many-body physics: given microscopic systems with experimentally realistic two-body interactions, how to design a Hamiltonian that realize

Jianfeng Lu, Xuda Ye, Zhennan Zhou

This paper considers mean square error (MSE) analysis for stochastic gradient sampling algorithms applied to underdamped Langevin dynamics under a global convexity assumption. A novel discrete Poisson equation framework is developed to bound the time-averaged sampling error. For the Stochastic Gradient UBU (SG-UBU) sampler, we derive an explicit MSE bound an

Mark-Oliver Wolf

The Solvency Capital Requirement (SCR) calculation is computationally intensive, relying on the market-consistent estimation of own funds. While Solvency II prioritizes the direct valuation method, it theoretically yields the same value as the indirect method. This paper evaluates their practical performance within a risk-neutral pricing framework. First, we

Angsuman Das, Arnab Mandal, Labani Sarkar

The \emph{difference subgroup graph} $D(G)$ of a finite group $G$ is defined as the graph whose vertices are the non-trivial proper subgroups of $G$, with two distinct vertices $H$ and $K$ adjacent if and only if $\langle H, K \rangle = G$ but $HK \ne G$. This graph arises naturally as the difference between the join graph $\Delta(G)$ and the comaximal subgr

Gavin A. L. Coleman, Sierk E. van Terwisga

FUV radiation from massive stars launch photoevaporative winds from the outer regions of protoplanetary discs around other stars, removing gas and dust. Observations have identified a relation between the median dust disc mass and the external UV field strength. Here we use disc evolutionary models to explore how this relation evolves over time, and with res

Giacomo Zonneveld, Giulia Rafaiani, Massimo Battaglioni, Marco Baldi

The use of blockchains for data certification and traceability is now well established in both the literature and practical applications. However, while blockchain-based certification of individual data is clear and straightforward, the use of blockchain to certify large amounts of data produced on a nearly continuous basis still poses some challenges. In su

Aby Philip, Alexander Streltsov

Quantum data hiding stores classical information in bipartite quantum states that are, in principle, perfectly distinguishable, yet remain almost indistinguishable without access to a quantum communication channel. Here, we investigate whether this limitation can be overcome when the communicating parties are assisted by additional quantum resources. We deve

Tsz-Kiu Aaron Chow

We prove Llarull-type rigidity for $S^{n-m}\times\mathbb{T}^m$ ($3\le n\le 7$, $1\le m\le n-2$). If a closed spin $(M^n,g)$ admits a degree-nonzero map to $S^{n-m}\times\mathbb{T}^m$ whose spherical projection is area non-increasing, and there exists $\psi\in C^\infty(M)$ with $-\Delta_M\psi-\frac{1}{2}|D_M\psi|^2+\frac{1}{2}\big(R_M-(n-m)(n-m-1)\big)\ge0$,

Mohammad Amin Ghanizadeh, Mohammad Javad Dousti

Data quality and its effective selection are fundamental to improving the performance of machine translation models, serving as cornerstones for achieving robust and reliable translation systems. This paper presents a data selection methodology specifically designed for fine-tuning machine translation systems, which leverages the synergy between a learner mo

Benoit Cadorel, Ya Deng, Katsutoshi Yamanoi

This is the first part of a series of three papers. In this paper, we establish a Big Picard type theorem for holomorphic maps $f:Y \to X$, where $Y$ is a ramified covering of the punctured disc $\mathbb{D}^*$ with small ramification and $X$ is a complex quasi-projective variety of log-general type and of maximal quasi-Albanese dimension. As a byproduct, we

Charles Poussot-Vassal, Ion Victor Gosea, Athanasios C. Antoulas

We study algorithms for Zolotarev (3rd and 4th) problems rational approximation. First, we show that the Loewner framework (LF) is appropriate to rapidly and with no iterations, approximate the Zolotarev problems by compressing the (numerous) interpolation conditions. Second, we compare the approximation properties (e.g. coefficients and poles) of LF with th

Sara Pérez-Vieites, Sahel Iqbal, Simo Särkkä, Dominik Baumann

Bayesian experimental design (BED) provides a principled framework for optimizing data collection by choosing experiments that are maximally informative about unknown parameters. However, existing methods cannot deal with the joint challenge of (a) partially observable dynamical systems, where only noisy and incomplete observations are available, and (b) ful

Subeen Park, Joowang Kim, Hakyung Lee, Sunjae Yoo

Deep learning models achieve strong performance across various domains but often rely on spurious correlations, making them vulnerable to distribution shifts. This issue is particularly severe in subpopulation shift scenarios, where models struggle in underrepresented groups. While existing methods have made progress in mitigating this issue, their performan

Hanyu Jiang, Baoyu Xu, Yun-Long Zhang

The approaches to searching for axion-like signals based on pulsars include observations with pulsar timing arrays (PTAs) and pulsar polarization arrays (PPAs). However, these methods are limited by observational uncertainties arising from multiple unknown and periodic physical effects, which substantially complicate subsequent data analysis. To mitigate the

Santanu Majhi, Debajyoti Bera

Quantum communication protocols can be designed to detect eavesdropping attacks, something that classical technologies are unable to do since classical information can be replicated in a non-destructive manner. Eavesdropping detection is, therefore, a standard feature in all the proposed quantum secret sharing (QSS) protocols. However, detection is often don

Reza Fareghbal, Abolfazl Hassani Majoulan

According to the flat/CCFT correspondence, Carrollian conformal field theories (CCFT) in d dimensions are dual to asymptotically flat spacetimes in d+1 dimensions. In this paper, starting from the holographic interpretation of pseudo-entropy in the (A)dS$_3$/CFT$_2$, we show that both extremal spacelike and timelike curves possess a well-defined flat-space l

Yoshinori Kurimoto, Dongjun Lee, Koichiro Ban, Shinichi Morisaka

We present the design and performance of QuEL-1 SE, which is a multichannel qubit controller developed for superconducting qubits. The system incorporates the active thermal stabilization of critical analog integrated circuits, such as phase-locked loops, amplifiers, and mixers, to suppress the long-term amplitude and phase drift. To evaluate the amplitude a

Mohammad F. Talafha, Mashhoor A. Al-Wardat, Ammar E. M. Abdulla, Hamid M. Al-Naimiy

In this study, we conduct a comparative analysis of observations carried out on the exoplanet HAT-P-25 b at the Sharjah Astronomical Observatory (SAO). We have employed two distinct filters, namely, the Luminoso (L) and Visual (V) filters. Our research aims to discern any variations in transit depth or exoplanet size resulting from the use of these different

Linus Taenzer, Paolo Tiso, Bart Van Damme

3D-printed materials are used in many different industries (automotive, aviation, medicine, etc.). Most of these 3D-printed materials are based on ceramics or polymers whose mechanical properties vary with frequency. For numerical modeling, it is crucial to characterize this frequency dependency accurately to enable realistic finite-element simulations. At t

Ke Du, Yimin Peng, Chao Gao, Fan Zhou

DORAEMON is an open-source PyTorch library that unifies visual object modeling and representation learning across diverse scales. A single YAML-driven workflow covers classification, retrieval and metric learning; more than 1000 pretrained backbones are exposed through a timm-compatible interface, together with modular losses, augmentations and distributed-t

Alireza Beygi, S. P. Klevansky, R. H. Lemmer

We calculate the binding energies of the hypothetical mesonic atom, $K^+ K^-$ (kaonium), using the $K^+ K^- \to K^+ K^-$ elastic scattering amplitude. Our findings are in line with previously reported results, which involve solving an eigenvalue equation of the Kudryavtsev-Popov type. Using chiral perturbation theory, we show that kaonium manifests itself as

Julian Gonzales, Jeremy B. Hume

We prove that ideals in amenable second-countable non-Hausdorff \'etale groupoid $C^*$-algebras are determined by their isotropy fibres. As an application, we characterise when the singular functions in Connes' algebra are dense in the singular ideal in terms of a property of explicit ideals in the isotropy group $C^*$-algebras. We then show this density pro

Pedro Antunes, Ana Rita Ortigoso, Gabriel Vieira, Daniel Fuentes

The rise of Large Language Models (LLM) has increased the need for scalable, high-performance inference systems, yet most existing frameworks assume homogeneous, resource-rich hardware, often unrealistic in academic, or resource-constrained settings. We introduce AIvailable, a low-cost, highly available LLM-as-a-Service (LLMaaS) platform, that uses a softwar

Chang Liu, Juan Li, Sheng Zhang, Chang Liu

Depth estimation is one of the key technologies for realizing 3D perception in unmanned systems. Monocular depth estimation has been widely researched because of its low-cost advantage, but the existing methods face the challenges of poor depth estimation performance and blurred object boundaries on embedded systems. In this paper, we propose a novel monocul

Cristina Pinneri, Christos Louizos

Guard models are a critical component of LLM safety, but their sensitivity to superficial linguistic variations remains a key vulnerability. We show that even meaning-preserving paraphrases can cause large fluctuations in safety scores, revealing a lack of semantic grounding. To address this, we introduce a practical, self-supervised framework for improving

Franziska Kühn, Matthias R. Schweizer, Tamara Azevedo, Vitaliy I. Vasyuchka

We present a combined theoretical and experimental study of angle-dependent parametric pumping of magnons in Yttrium Iron Garnet films, with a focus on the mechanisms that transfer parametrically injected magnons toward the spectral minimum where Bose-Einstein condensation occurs. Using a classical Hamiltonian formalism, we analyze the threshold conditions f

Johannes Lehmann, Artem Basalaev, Jonathan J. Carter, Matteo Carlassara

Homodyne Quadrature interferometers (HoQI) are an interferometric displacement sensing scheme proven to have excellent noise performance, making them a strong candidate for sensing and control schemes in gravitational wave detector seismic isolation. Like many interferometric schemes, HoQIs are prone to nonlinear effects when measuring displacements. These n

Itbaan Safwan, Muhammad Annas Shaikh, Muhammad Haaris, Ramail Khan

We present a multi-task framework for the MediaEval Medico 2025 challenge, leveraging a LoRA-tuned Florence-2 model for simultaneous visual question answering (VQA), explanation generation, and visual grounding. The proposed system integrates three curated datasets: (1) Kvasir-VQA-x1 for question-answer learning, (2) a synthetically enriched explanation data

Yujie Lu, Ao Liu, Changliang Li, Kun Wang

We present the physical design and systematic optimization of a high-performance storage ring tailored for the generation of high-power coherent radiation, with particular emphasis on the extreme ultraviolet (EUV) regime. The proposed ring adopts a Double Bend Achromat (DBA) lattice configuration and integrates 12 superconducting wigglers to significantly en

Naïn Jonckers, Toon Vinck, Peter Karsmakers, Jeffrey Prinzie

In recent years, the increased interest and the growth in application domains of Artificial Intelligence (AI), and more specifically Deep Neural Networks (DNNs), has led to an extensive usage of domain specific DNN accelerator processors to improve the computational efficiency of DNN inference. However, like any digital circuit, these processors are prone to

Thomas Chillery, David Rapagnani, Chemseddine Ananna, Edoardo D'Amore

We report a novel neutron-detection approach employing an EJ-309 liquid scintillator surrounded by six 3He proportional counters. Tests were performed at the FRANZ facility of the Goethe-University Frankfurt using the 7Li(p,n0)7Be reaction, producing neutrons across energies 50-720 keV. The scintillator's neutron energy quenching is determined, and its neutr

Dexin wang, Faliang Chang, Chunsheng Liu

Efficiently leveraging simulation to acquire advanced manipulation skills is both challenging and highly significant. We introduce \textit{ForeRobo}, a generative robotic agent that utilizes generative simulations to autonomously acquire manipulation skills driven by envisioned goal states. Instead of directly learning low-level policies, we advocate integra

Felipe Hernández

In joint work with Adam Black and Reuben Drogin, we develop a new approach to understanding the diffusive limit of the random Schrodinger equation based on ideas taken from random matrix theory. These lecture notes present the main ideas from this work in a self-contained and simplified presentation. The lectures were given at the summer school "PDE and Prob

Jessica Elisa Massetti, Michela Procesi, Laurent Stolovitch

In this paper, we study infinite dimensional holomorphic vector fields on sequence spaces, having a fixed point at $0$. Under suitable hypotheses we prove the existence of analytic invariant submanifolds passing through the fixed point. The restricted dynamics is analytically conjugate to the linear one under some Diophantine-like condition.

Michael M. Schein, Re'em Waxman

The submodule structure of mod $p$ principal series representations of $\mathrm{GL}_2(k)$, for $k$ a finite field of characteristic $p$, was described by Bardoe and Sin and has played an important role in subsequent work on the mod $p$ local Langlands correspondence. The present paper studies the structure of mod $p$ principal series representations of $\mat

Saikat Panja

We introduce the notions of Fatou and Julia sets in the context of word maps on complex Lie groups and polynomial maps on finite-dimensional associative $\mathbb C$-algebras. For the group-theoretic question, we investigate the dynamics of the power map $x \mapsto x^{M}$ on the Lie group $\mathrm{GL}_n(\mathbb C)$, where $M \geq 2$ is an integer. For the alg

Ali Boudaghi, Hadi Zare

Music editing has emerged as an important and practical area of artificial intelligence, with applications ranging from video game and film music production to personalizing existing tracks according to user preferences. However, existing models face significant limitations, such as being restricted to editing synthesized music generated by their own models,

Anna Mészáros, Javier Alonso-Mora, Jens Kober

Effectively capturing the joint distribution of all agents in a scene is relevant for predicting the true evolution of the scene and in turn providing more accurate information to the decision processes of autonomous vehicles. While new models have been developed for this purpose in recent years, it remains unclear how to best represent the joint distributio

Hongliang Lu, Zixuan Yang, Feihong Yuan

Let $G$ be an edge-colored graph. We use $e(G)$ and $c(G)$ to denote the number of edges and colors in $G$, respectively. A subgraph $H$ is called rainbow if $c(H)=e(H)$. Li et al. (European J. Combin., 36 (2014), 453-459) proved that every edge-colored graph on $n$ vertices with $e(G)+c(G) \geq n(n+1)/2$ contains rainbow triangles. Later, Xu et al. (Europea

V. Vojáček, J. Borovička, P. Spurný

We present a study of the high-temperature spectral component in meteor fireballs, with a particular focus on neutral hydrogen at 656.28 nm and ionised silicon doublet at 634.71 nm and 637.14 nm. By analysing spectra from the European Fireball Network (EN) that exhibit H$\alpha$ and Si~II emissions, we investigated the relationship between H and Si abundance

Y. Duann, S. -H. Lai, H. J. Hoeijmakers, A. Johansen

Ultra-hot Jupiters (UHJs) in close orbits around early-type stars provide natural laboratories for studying atmospheric escape and star-planet interactions under extreme irradiation and wind conditions. The near-ultraviolet (NUV) regime is particularly sensitive to extended upper atmospheric and magnetospheric structures. We investigate whether star-planet i

G. M. Delgado, J. E. G. Silva

Twisted cylindrical tubes are important model systems for nanostructures, heterostructures, and curved quantum devices. In this work, we investigate the quantum behavior of an electron confined to a twisted cylindrical surface. By first calculating the strain tensor to obtain the induced surface metric, we employ da Costa's formalism to derive the geometry-i

Dennis Hendriks, Michel Reniers, Wan Fokkink, Wytse Oortwijn

Supervisory controllers control cyber-physical systems to ensure their correct and safe operation. Synthesis-based engineering (SBE) is an approach to largely automate their design and implementation. SBE combines model-based engineering with computer-aided design, allowing engineers to focus on 'what' the system should do (the requirements) rather than 'how

Renfeng Peng, Chengkai Zhu, Bin Gao, Xin Wang

Tensors with unit Frobenius norm are fundamental objects in many fields, including scientific computing and quantum physics, which are able to represent normalized eigenvectors and pure quantum states. While the tensor train decomposition provides a powerful low-rank format for tackling high-dimensional problems, it does not intrinsically enforce the unit-no

Josef Demmel, Emil Wiedemann

We analyze the two-dimensional incompressible Navier-Stokes equations on a smooth, bounded, simply connected domain with Navier boundary conditions with friction coefficient $α\in C^2$. For initial vorticity in $L^2$, we show that the unique weak solution for velocity is, in fact, strong and satisfies the Navier slip conditions for any positive time. The key

E. Dudas, J. Mourad, A. Sagnotti

The first part of this review tries to provide a self-contained view of supersymmetry breaking from the bottom-up perspective. We thus describe N=1 supersymmetry in four dimensions, the Standard Model and the MSSM, with emphasis on the ``soft terms'' that can link it to supergravity. The second part deals with the top-down perspective. It addresses, insofar

Weiyan Shi, Kenny Tsu Wei Choo

While multimodal large language models (MLLMs) are increasingly applied in human-centred AI systems, their ability to understand complex social interactions remains uncertain. We present an exploratory study on aligning MLLMs with speech-language pathologists (SLPs) in analysing joint attention in parent-child interactions, a key construct in early social-co

Matthew Shetrone, Rachael L. Beaton, Christian R. Hayes, Sten Hasselquist

In addition to comprehensive surveys of the Milky Way bulge, disk, and halo, the Apache Point Galactic Evolution Experiment (APOGEE) project observed seven dwarf spheroidal satellites (dSphs) of the Milky Way: Carina, Sextans, Sculptor, Draco, Ursa Minor, Bootes 1, and Fornax. APOGEE radial velocities, stellar parameters, and Gaia EDR3 proper motions are use

Daniel Brosch, Bernard Lidický, Sydney Miyasaki, Diane Puges

In this paper, we investigate three extensions of Ramsey numbers to other combinatorial settings. We first consider ordered Ramsey numbers. Here, we ask for a monochromatic copy of a linearly ordered graph $G$ in every $2$-edge-coloring of a linearly ordered complete graph $K_n$. The smallest such $n$ is denoted by $\vec{R}(G)$. Next, we study canonical Rams

Bernhard Kepka, Klaus Widmayer

We study the long-time behavior of radially symmetric solutions to the Vlasov-Poisson equation consisting of an attractive point mass and a small, suitably localized and absolutely continuous distribution of particles: if the latter is initially localized on hyperbolic trajectories for the associated Kepler problem, we obtain global in time, unique Lagrangia

Chiara Telli, Oleg Antropov, Anne Lönnqvist, Marco Lavalle

In this study, we examine the potential of high-resolution forest mapping using L-band interferometric time series datasets and deep learning modeling. Our SAR data are represented by a time series of nine ALOS-2 PALSAR-2 dual-pol SAR images acquired at near-zero spatial baseline over a study site in Asturias, Northern Spain. Reference data are collected usi

Dennis Thumm

Energy markets exhibit complex causal relationships between weather patterns, generation technologies, and price formation, with regime changes occurring continuously rather than at discrete break points. Current approaches model electricity prices without explicit causal interpretation or counterfactual reasoning capabilities. We introduce Augmented Time Se

Minsu Ji, Jihoon Kang, Seongkwon Yu, Jaemyoung Kim

Photon scattering has traditionally limited the ability of near-infrared spectroscopy (NIRS) to extract accurate, layer-specific information from the brain. This limitation restricts its clinical utility for precise neurological monitoring. To address this, we introduce an AI-driven, high-density NIRS system optimized to provide real-time, layer-specific oxy

Yucheng Wang

Localization transitions represent a fundamental class of continuous phase transitions, yet they occur without any accompanying symmetry breaking. We resolve this by introducing the concept of dynamical translational symmetry (DTS), which is defined not by the Hamiltonian but by the long-time dynamics of local observables. Its order parameter, the time-avera

Sinchan Snigdha Rej, Bimalendu Deb

Adiabatic geometric phase gates offer enhanced robustness against fluctuations compared to con- ventional Rydberg blockade-based phase gates that rely on dynamical phase accumulation. We theoretically demonstrate two- and multi-qubit phase gates in a neutral atom architecture, relying on a double stimulated Raman adiabatic passage (double-STIRAP) pulse seque

Maëlic Neau, Zoe Falomir, Paulo E. Santos, Anne-Gwenn Bosser

Deploying autonomous robots that can learn new skills from demonstrations is an important challenge of modern robotics. Existing solutions often apply end-to-end imitation learning with Vision-Language Action (VLA) models or symbolic approaches with Action Model Learning (AML). On the one hand, current VLA models are limited by the lack of high-level symboli

Yaru Liu, Yucheng Wang

The Mpemba effect, where a state farther from equilibrium relaxes faster than one closer to it, is a striking phenomenon in both classical and quantum systems. In open quantum systems, however, the quantum Mpemba effect (QME) typically occurs only for specifically chosen initial states, which limits its universality. Here we present a general and experimenta

Jia-Ying Xiong, Yao Ma, Bing-Kai Sheng, Yong-Liang Ma

We established a new power counting scheme, chiral-scale density counting (CSDC) rules, for the application of the chiral-scale effective field theory to nuclear matter at finite densities and temperatures. Within this framework, the free fermion gas is at the leading order, while one-boson-exchange interactions appear at the next-to-leading order, and the m

Adam Dor-On, Travis B. Russell

We study unital operator spaces endowed with a partially defined product. We give a matrix-norm characterization of such products that allows for a representation theorem where the partial product is realized as composition of operators on Hilbert space. We study product-respecting C*-covers, including a universal product C*-cover, and product quotients. We

Hasan Akgul, Mari Eplik, Javier Rojas, Akira Yamamoto

Human action recognition (HAR) with multi-modal inputs (RGB-D, skeleton, point cloud) can achieve high accuracy but typically relies on large labeled datasets and degrades sharply when sensors fail or are noisy. We present Robust Cross-Modal Contrastive Learning (RCMCL), a self-supervised framework that learns modality-invariant representations and remains r

Gabriel Ponte, Marcia Fampa, Jon Lee

We establish strong connections between two fundamental nonlinear 0/1 optimization problems coming from the area of experimental design, namely maximum-entropy sampling and 0/1 D-optimality. The connections are based on maps between instances, and we analyze the behavior of these maps. Using these maps, we transport basic upper-bounding methods between these

Puneet Mishra, Martijntje Vollebregt, Yizhou Ma, Maria Font-i-Furnols

Background In analytical chemistry, spatial information about materials is commonly captured through imaging techniques, such as traditional color cameras or with advanced hyperspectral cameras and microscopes. However, efficiently extracting and analyzing this spatial information for exploratory and predictive purposes remains a challenge, especially when u

Domenico delli Gatti, Filippo Gusella, Giorgio Ricchiuti

This paper investigates Minsky's cycles by extending the paper of stockhammer et al. (2019) with a nonlinear model to capture possible local real-financial endogenous cycles. We trace nonlinear regime changes and check the presence of Minsky cycles from the 1970s to 2020 for the USA, France, Germany, Canada, Australia, and the UK, linking the GDP with corpor

Zhen Yi Lau

This short technical note presents a formal generalization of the Time Warp Edit Distance (TWED) proposed by Marteau (2009) to arbitrary metric spaces. By viewing both the observation and temporal domains as metric spaces $(X, d)$ and $(T, \Delta)$, we define a Generalized TWED (GTWED) that remains a true metric under mild assumptions. We provide self-contai

Sanjay Kumar, Tim Brophy, Eoin Martino Grua, Ganesh Sistu

Accurate 3D object detection is essential for automated vehicles to navigate safely in complex real-world environments. Bird's Eye View (BEV) representations, which project multi-sensor data into a top-down spatial format, have emerged as a powerful approach for robust perception. Although BEV-based fusion architectures have demonstrated strong performance t

Vitaliy Rusov, Tatiana Zelentsova

We propose a phenomenological model in which empty flux tubes in strong magnetic fields are associated with both the conversion of axions to photons of axion origin to generate coronal heating, and the simultaneous preservation of the Parker-Biermann cooling effect by converting high-energy photons from the radiative zone to axions from the convective zone t

Muhammad Annas Shaikh, Hamza Zaman, Arbaz Asif

This paper presents a comprehensive evaluation of nine convolutional neural network architectures for binary classification of horses and motorcycles in the VOC 2008 dataset. We address the significant class imbalance problem by implementing minority-class augmentation techniques. Our experiments compare modern architectures including ResNet-50, ConvNeXt-Tin

Themistoklis Haris, Fabian Spaeh, Spyros Dragazis, Charalampos Tsourakakis

Hitting times provide a fundamental measure of distance in random processes, quantifying the expected number of steps for a random walk starting at node $u$ to reach node $v$. They have broad applications across domains such as network centrality analysis, ranking and recommendation systems, and epidemiology. In this work, we develop local algorithms for est

Kaiwen Guo, Yanjun Liu

In this paper, we investigate the extremal functions for anisotropic Trudinger-Moser inequalities. Our method uses convex symmetrization, the continuity of the supremum function, together with the relation between the supremums of the subcritical and the critical anisotropic Trudinger-Moser inequality, we give some results of existence and symmetry about the

Nick Oh, Fernand Gobet

Test-time reasoning architectures such as those following the Generate-Verify paradigm, where a model iteratively refines or verifies its own generated outputs, prioritise generation and verification but exclude the monitoring processes that determine when and how reasoning should begin. This omission may contribute to the prefix dominance trap, in which mod

Jacopo Bellazzini, Luigi Forcella, Vladimir Georgiev

We prove small data scattering in the mass-subcritical regime for the NLS equation with double nonlinearities, where a focusing leading term is perturbed by a lower order defocusing nonlinear term. Our proof relies on the pseudo-conformal transformation in conjunction with a general variational argument used to obtain the positivity of certain modified energ

Federico Settimo, Bassano Vacchini

We study phase-synchronization in a driven two-level system coupled to a non-Markovian bosonic reservoir. The dynamics is described by treating the system-bath coupling and the coherent drive without invoking the rotating-wave approximation, and simulated using the numerically exact hierarchical equations of motion. We observe that a robust phase-locking dev

Hesham El Faham, Giuseppe Ventura, Eleni Vryonidou

We present a comprehensive analysis of dimension-8 and dimension-6 effects in fully leptonic $WZ$ and $WW$ production at the Large Hadron Collider (LHC) within the Standard Model (SM) Effective Field Theory (SMEFT). We focus on dimension-8 operators with maximal energy growth in the quark-(anti)quark-initiated production channel and assess their impact diffe

Y. -Z. Cai, A. Pastorello, K. Maeda, J. -W. Zhao

We present a photometric and spectroscopic analysis of the Type Ibn supernova (SN) 2024acyl. It rises to an absolute magnitude peak of about -17.58 mag in 10.6 days, and displays a rapid linear post-peak light-curve decline in all bands, similar to most SNe Ibn. The optical pseudobolometric light curve peaks at $(3.5\pm0.8) \times 10^{42}$ erg s$^{-1}$, with

Hadar Aharon, Zahava Barkay, Sophie Meuret, Ofer Kfir

Cathodoluminescence (CL) enables optical-frequency analysis of samples with nanometer resolutions, originating from the interaction of a focused electron beam with radiative electronic states, or directly with the optical modes of the sample. Here we decompose the various mechanisms underlying CL generation and emission from an archetype spherical resonator

Srimoy Bhattacharya, Mukesh Kumar, Rachid Mazini, Bruce Mellado

The discovery of the Higgs boson at the LHC completed the Standard Model (SM), yet the possibility of additional scalars remains open, provided their contributions to electroweak symmetry breaking are sufficiently small. Recent analyses of LHC data have revealed statistically significant anomalies in multi-lepton final states - events characterized by multip

Saúl Alonso-Monsalve, Leigh H. Whitehead, Adam Aurisano, Lorena Escudero Sanchez

Accurate delineation of kidney tumours in Computed Tomography (CT) is essential for downstream quantitative analysis and precision oncology, but manual segmentation is a specialised task, time-consuming and difficult to scale. Automated 3D segmentation remains challenging because CT scans are large volumetric images, making high-resolution dense convolutiona

Federico Pirola, Fabio Stella, Marco Grzegorczyk

Dynamic Bayesian networks (DBNs) are increasingly used in healthcare due to their ability to model complex temporal relationships in patient data while maintaining interpretability, an essential feature for clinical decision-making. However, existing approaches to handling missing data in longitudinal clinical datasets are largely derived from static Bayesia

Antti Koskela, Tejas Kulkarni, Laith Zumot

Differentially private in-context learning (DP-ICL) has recently become an active research topic due to the inherent privacy risks of in-context learning. However, existing approaches overlook a critical component of modern large language model (LLM) pipelines: the similarity search used to retrieve relevant context data. In this work, we introduce a DP fram

Carlos A. Ribeiro Diniz, Victor E. Lachos Olivares, Victor H. Lachos Davila

This paper introduces a matrix-variate regression model for analyzing multivariate data observed across spatial locations and over time. The model's design incorporates a mean structure that links covariates to the response matrix and a separable covariance structure, based on a Kronecker product, to capture spatial and temporal dependencies efficiently. We

Christian Portilla, Arviandy G Aribowo, Ramachandran Anantharaman, César A Gómez-Pérez

This paper explores the application of data-driven system identification techniques in the frequency domain to obtain simplified, control-oriented models of photosynthesis regulation under oscillating light conditions. In-silico datasets are generated using simulations of the physics-based Basic DREAM Model (BDM) Funete et al.[2024], with light intensity sig

Jonas Berx

I investigate the generic problem of lossy compression of a fluctuating stochastic signal $X$ into a discrete representation $Z$ through optimal thresholding. The signal modulates transition rates of a two-state system described by a binary variable $Y$. Optimising the retained mutual information between $Z$ and $Y$ under a constraint on fixed encoding cost

Jiahao Zhao, Luxin Xu, Minghuan Tan, Lichao Zhang

Numerous medical systems powered by Large Language Models (LLMs) have achieved remarkable progress in diverse healthcare tasks. However, research on their medication safety remains limited due to the lack of real world datasets, constrained by privacy and accessibility issues. Moreover, evaluation of LLMs in realistic clinical consultation settings, particul

Kazuki Ikeda

We recast quantum entanglement as a cohomological obstruction to reconstructing a global quantum state from locally compatible information. We address this by considering presheaf cohomologies of states and entanglement witnesses. Sheafification erases the global-from-local signature while leaving within-patch multipartite structure, captured by local entang

Egor S. Vyatkin, Sergey A. Tarasenko

We present an analytical theory of second harmonic generation (SHG) in hybrid structures combining a nonlinear 2D crystal with a dielectric metasurface waveguide. The theory describes the excitation spectrum and enhancement of SHG at both leaky mode and quasi-bound state in the continuum (quasi-BIC) resonances in terms of the material parameters. For low-los

Eugenia Pyurbeeva, Ronnie Kosloff

Continuous particle exchange thermal machines require no time-dependent driving, can be realised in solid-state electronic devices, and miniaturised to nanometre scale. Quantum dots, providing a narrow energy filter and allowing to manipulate particle flow between the hot and cold reservoirs are at the heart of such devices. It has been theoretically shown t

Jiayu Li, Xiangrong Zhu

We study interior estimates for solutions of the linear Poisson equation: $$ \triangle u = g u + f $$ where $g$ and $f$ belong to the Zygmund space $L\ln L$ on a Riemann surface $M$ satisfying the isoperimetric inequality. As applications, we derive corresponding interior estimates, Harnack inequalities, and a global estimate.

Binnan Tu

In this paper, we show that Oda's question holds for $n$-dimensional simplicial reflexive polytope $P$ and lattice polytope $Q$ containing the origin, when the vertex of $Q$ is either a vertex of $P$ or the origin, provided that $P$ has no more than $n+1$ lattice points on each facet and possesses unimodular triangulation. Then we prove Oda's question is tru

Yuanpeng Zhang, Xing Hu, Xi Chen, Zhihang Yuan

SRAM Processing-in-Memory (PIM) has emerged as the most promising implementation for high-performance PIM, delivering superior computing density, energy efficiency, and computational precision. However, the pursuit of higher performance necessitates more complex circuit designs and increased operating frequencies, which exacerbate IR-drop issues. Severe IR-d

Kuankuan Sima, Longbin Tang, Zhenyu Yang, Haozhe Ma

Autonomous navigation in unknown environments requires multi-scale spatial understanding that captures geometric details, topological connectivity, and global structure to support high-level decision making under partial observability. Existing approaches struggle to efficiently capture such multi-scale spatial understanding while maintaining low computation

Majid Layachi, Remi Merindol, Laura Casanellas

The way living tissues respond to external mechanical forces is crucial in physiological processes like embryogenesis, homeostasis or tumor growth. Providing a complete description across length scales which relates the properties of individual cells to the rheological behavior of complex 3D-tissues remains an open challenge. The development of simplified bi

Deyu Chen, Guixiang Hong, Liang Wang, Wenhua Wang

We investigate in the present paper the Navier-Stokes equations on quantum Euclidean spaces $\mathbb{R}^d_{\theta}$ with $\theta$ being a $d\times d$ antisymmetric matrix, which is a standard example of non-compact noncommutative manifolds. The quantum analogues of Ladyzhenskaya and Kato's results are established, that is, we obtain the global well-posedness

Xiangjun Zhang, Litong Gong, Yinglin Zheng, Yansong Liu

Most text-to-video(T2V) diffusion models depend on pre-trained text encoders for semantic alignment, yet they often fail to maintain video quality when provided with concise prompts rather than well-designed ones. The primary issue lies in their limited textual semantics understanding. Moreover, these text encoders cannot rephrase prompts online to better al

Husam Ismaeel

We prove that Rado's graph admits no quantum symmetries.

Tim Beyer, Jonas Dornbusch, Jakob Steimle, Moritz Ladenburger

The rapid expansion of research on Large Language Model (LLM) safety and robustness has produced a fragmented and oftentimes buggy ecosystem of implementations, datasets, and evaluation methods. This fragmentation makes reproducibility and comparability across studies challenging, hindering meaningful progress. To address these issues, we introduce Adversari

Saad Nabeebaccus, David Perez, Lech Szymanowski, Samuel Wallon

We consider the exclusive photoproduction of a di-meson pair with large invariant mass, $\gamma N \rightarrow N' M_1M_2$, in the framework of collinear factorisation. The mesons considered $M_1$ and $M_2$ are either pions or rho mesons, charged or neutral. We consider the kinematic regime characterised by a large invariant mass of the two-meson system, and a

Tomasz Kania

We prove that no separable Banach algebra is universal for homomorphic embeddings of all separable Banach algebras, whether embeddings are merely bounded or required to be contractive. The same holds in the commutative category. The proof is short and direct. For each closed subspace $X$ of $c_0$ we build a separable commutative Banach algebra $A_X$ whose mu

Kangjian Wu, Qingxiang Xu

We investigate the generalized quadratic operator defined by $$T =\left( \begin{array}{cc} a I_H & A \\ c A^* & bI_K \end{array} \right) ,$$ where $H$ and $K$ are Hilbert spaces, $A:K\to H$ is a bounded linear operator, $I_H$ and $I_K$ denote the identity operators on $H$ and $K$, respectively, and $a,b,c$ are complex numbers. It is shown that $T$ attains it

Jacob Lysnæs-Larsen, Marte Eggen, Inga Strümke

In explainable AI, Concept Activation Vectors (CAVs) are typically obtained by training linear classifier probes to detect human-understandable concepts as directions in the activation space of deep neural networks. It is widely assumed that a high probe accuracy indicates a CAV faithfully representing its target concept. However, we show that the probe's cl