April 2025 arXiv papers — page 4

Gustavo A. L. Forão, Jonas Berx, Carlos E. Fiore

Characterizing and optimizing nanoscopic heat engines require an appropriate understanding of the interplay between power, efficiency, entropy production and fluctuations. Despite significant recent advancements, including linear stochastic thermodynamics and thermodynamic uncertainty relations (TURs), a complete scenario remains elusive. In this work, we gi

Marc Glocker, Peter Hönig, Matthias Hirschmanner, Markus Vincze

We present an embodied robotic system with an LLM-driven agent-orchestration architecture for autonomous household object management. The system integrates memory-augmented task planning, enabling robots to execute high-level user commands while tracking past actions. It employs three specialized agents: a routing agent, a task planning agent, and a knowledg

Xu Zhou, Mengqi Wang, Xiangyu Ye, Haoyu Sun

Detecting individual spins--including stable and metastable states--represents a fundamental challenge in quantum sensing with broad applications across condensed matter physics, quantum chemistry, and single-molecule magnetic resonance imaging. While nitrogen-vacancy (NV) centers in diamond have emerged as powerful nanoscale sensors, their performance for s

Zhiyong Jin, Runhua Xu, Chao Li, Yizhong Liu

Gradient sparsification, while mitigating communication bottlenecks in Federated Learning (FL), fundamentally alters the geometric landscape of model updates. We reveal that the resultant high-dimensional orthogonality renders traditional Euclidean-based robust aggregation metrics mathematically ambiguous, creating a 'sparsity-robustness trade-off' that adve

Ellen Baake, Fernando Cordero, Sophia-Marie Mellis, Vitali Wachtel

We consider the long-term behaviour of critical multitype branching processes conditioned on non-extinction, both with respect to the forward and the ancestral processes. Forward in time, we prove a functional limit theorem in the space of trajectories of the linearly-scaled $h$-transformed process; the change of measure allows us to work on the same probabi

Manuel Fernandez-Guasti, Toshiaki Fujiwara, Ernesto Perez-Chavela, Shuqiang Zhu

We consider an $N$--body problem under a harmonic potential of the form $\frac{1}{2}\sum \kappa_{jl} |q_j-q_l|^2$. A $p$-lima\c{c}on curve is a planar curve parametrized by $t$ given by $a(\cos t,\sin t)+b(\cos pt, \sin pt)$, where $a,b\in \mathbb{R}$, $p \in \mathbb{Z}$, and $t \in [0,2\pi]$. We study $N$-body choreographic motions constrained to a $p$-lima

Gene Freudenburg

For an algebraically closed field $k$ of characteristic zero and a linear algebraic $k$-group $G$, it is well known that every affine $G$-variety admits a $G$-equivariant closed embedding into a finite-dimensional $G$-module. Such an embedding is a presentation of the $G$-variety, and a minimal presentation is one for which the dimension the $G$-module is mi

Jingbo Sun, Hengxiao Guo, Wenwen Zuo, Paulina Lira

The search for robust evidence of intermediate-mass black holes (IMBHs) is crucial for understanding black hole seeding process and the formation of supermassive black holes in the early Universe. NGC 4395 and POX 52 are two prototypical IMBH hosts, both exhibiting multi-line evidence of low-mass black hole activity. Here, we report the first detection of mi

Xi Fang, Hajime Uno, Fan Li

Composite endpoints, which combine two or more distinct outcomes, are frequently used in clinical trials to enhance the event rate and improve the statistical power. In the recent literature, the while-alive cumulative frequency measure offers a strong alternative to define composite survival outcomes, by relating the average event rate to the survival time.

Sahar Yarmohammadtoosky, Yiyun Zhou, Victoria Yaneva, Peter Baldwin

This study examines vulnerabilities in transformer-based automated short-answer grading systems used in medical education, with a focus on how these systems can be manipulated through adversarial gaming strategies. Our research identifies three main types of gaming strategies that exploit the system's weaknesses, potentially leading to false positives. To co

Ni Wang, Diego A. Tejada-Arango

This paper reviews discounting approaches for modeling multi-year energy investments, focusing on total versus annualised cost formulations. We discuss how time value of money is handled, and how salvage value and milestone-year weighting can address mismatches between asset lifetimes and model horizons. These methods are implemented in the open-source Tulip

Thi Xuan Vu

Let $\mathcal{R} = \mathbb{K}[x_1, \dots, x_n]$ be a multivariate polynomial ring over a field $\mathbb{K}$ of characteristic 0. Consider $n$ algebraically independent elements $g_1, \dots, g_n$ in $\mathcal{R}$. Let $\mathcal{S}$ denote the subring of $\mathcal{R}$ generated by $g_1, \dots, g_n$, and let $h$ be an element of $\mathcal{S}$. Then, there exist

Anthony D Martin

We propose a generalization of modern representation learning objectives by reframing them as recursive divergence alignment processes over localized conditional distributions While recent frameworks like Information Contrastive Learning I-Con unify multiple learning paradigms through KL divergence between fixed neighborhood conditionals we argue this view u

Saber Mehdipour, Seyed Abolghasem Mirroshandel, Seyed Amirhossein Tabatabaei

Detecting plant diseases is a crucial aspect of modern agriculture, as it plays a key role in maintaining crop health and increasing overall yield. Traditional approaches, though still valuable, often rely on manual inspection or conventional machine learning techniques, both of which face limitations in scalability and accuracy. Recently, Vision Transformer

János Kollár

Starting with an Abelian fiber space, the aim is to construct a Tate-Shafarevich twist that has a rational section.

Jordi Pérez-Guijarro, Alba Pagès-Zamora, Javier R. Fonollosa

Sequential methods for quantum hypothesis testing offer significant advantages over fixed-length approaches, which rely on a predefined number of state copies. Despite their potential, these methods remain underexplored for unambiguous discrimination. In this work, we derive performance bounds for such methods when applied to the discrimination of a set of p

Thiago Dias, Sebastián Gonçalves

We present an agent-based model of economic exchange in a society composed of two groups, representing two social groups and with different internal protection rules for the poor agents. The goal is to address the emerging wealth distribution when economic rules are not the same for all individuals. Individuals exchange wealth in pairwise interactions with n

Antonia Azzini, Ilaria Baroni, Irene Celino

The promotion of a healthy lifestyle is one of the main drivers of an individual's overall physical and psycho-emotional well-being. Digital technologies are more and more adopted as ''facilitators'' for this goal, to raise awareness and solicit healthy lifestyle habits. This study aims to experiment the effects of the adoption of a digital conversational to

Bhabana Kumar, Mrinal Kumar Das

In the absence of supersymmetry, modular forms need not be holomorphic functions of the modulus $\tau$. Using this idea, we construct a non-supersymmetric framework using polyharmonic $Maa\beta$ forms. In this approach, the Yukawa coupling is no longer strictly holomorphic in $\tau$ but instead incorporates both holomorphic and non-holomorphic components. We

Marco Arazzi, Vignesh Kumar Kembu, Antonino Nocera, Vinod P

Large Language Models are fundamental actors in the modern IT landscape dominated by AI solutions. However, security threats associated with them might prevent their reliable adoption in critical application scenarios such as government organizations and medical institutions. For this reason, commercial LLMs typically undergo a sophisticated censoring mechan

Abu Mohammed Raisuddin, Jesper Holmblad, Hamed Haghighi, Yuri Poledna

Sensor degradation poses a significant challenge in autonomous driving. During heavy rainfall, the interference from raindrops can adversely affect the quality of LiDAR point clouds, resulting in, for instance, inaccurate point measurements. This, in turn, can potentially lead to safety concerns if autonomous driving systems are not weather-aware, i.e., if t

Xiang-Yu Wu, Lipei Du, Charles Gale, Sangyong Jeon

We study thermal dilepton production and anisotropic flow in Pb+Pb collisions at $\sqrt{s_{NN}} = 5.02 \, \mathrm{TeV}$ using next-to-leading-order (NLO) thermal QCD dilepton emission rates. A hybrid model (IP-Glasma+\kompost+MUSIC+UrQMD) simulates the collision evolution. The role of the pre-equilibrium stage in dilepton observables is examined. We also exp

Jeho Choi

Large Language Models (LLMs) have shown promise in enabling natural language interfaces for structured data querying through text-to-SQL generation. However, their application in real-world Business Intelligence (BI) contexts remains limited due to semantic hallucinations, structural errors, and a lack of domain-specific evaluation frameworks. In this study,

Plastiras Demetriou, Jendrik Voss, Angela Madeo

We use the reduced relaxed micromorphic model (RRMM) to capture the effective "bulk" dynamical response of finite size metamaterial specimens made out of a Labyrinthine unit cell. We show that for small finite-size specimens, boundary effects can play a major role, so that the RRMM needs an enrichment to capture the metamaterial's bulk response, as well as t

Tian Chen, Shengping Liu, Li Liu, Heng Yong

Accurate modeling of closure terms is a critical challenge in engineering and scientific research, particularly when data is sparse (scarse or incomplete), making widely applicable models difficult to develop. This study proposes a novel approach for constructing closure models in such challenging scenarios. We introduce a Series-Parallel Multi-Network Archi

Cristina Rossi, Rini Varghese, Amy J Bastian

Virtual reality (VR) is increasingly used to enhance the ecological validity of motor control and learning studies by providing immersive, interactive environments with precise motion tracking. However, designing realistic VR-based motor tasks remains complex, requiring advanced programming skills and limiting accessibility in research and clinical settings.

Stavrow A. Bahnam, Christophe De Wagter, Guido C. H. E. de Croon

Ego-motion estimation is vital for drones when flying in GPS-denied environments. Vision-based methods struggle when flight speed increases and close-by objects lead to difficult visual conditions with considerable motion blur and large occlusions. To tackle this, vision is typically complemented by state estimation filters that combine a drone model with in

Tom Westermann, Malte Ramonat, Johannes Hujer, Felix Gehlhoff

AutomationML has seen widespread adoption as an open data exchange format in the automation domain. It is an open and vendor neutral standard based on the extensible markup language XML. However, AutomationML extends XML with additional semantics that limit the applicability of common XML-tools for applications like querying or data validation. This article

Longkang Zhu, Xinli Shi, Xiangping Xu, Jinde Cao

This paper addresses two fundamental challenges in distributed online convex optimization: communication efficiency and optimization under limited feedback. We propose Online Compressed Gradient Tracking with one-point Bandit Feedback (OCGT-BF), a novel algorithm that harness data compression and gradient-free optimization techniques in distributed networks.

Xing Kangwei

This study systematically tests a computational power reuse scheme proposed by the open source community disabling specific instruction sets (Fused Multiply Add instructions) through CUDA source code modifications on the NVIDIA CMP 170HX platform. Experimental results validate the effectiveness of this approach, partially restoring the GPU's computational ca

Zihan Zhou, Changrui Dai, Aibo Song, Xiaolin Fang

Successful video analysis relies on accurate recognition of pixels across frames, and frame reconstruction methods based on video correspondence learning are popular due to their efficiency. Existing frame reconstruction methods, while efficient, neglect the value of direct involvement of multiple reference frames for reconstruction and decision-making aspec

Valentín Reparaz, María José Sánchez, Maximiliano Gatto, Daniel Dominguez

In this work, we study the time-averaged populations obtained for a fluxonium circuit under a large amplitude nonresonant periodic drive. We present numerical simulations of the time evolution which consider the multi-level structure of the driven quantum circuit, looking for a realistic modeling closer to experimental implementations. The Landau-Zener-St\"u

Anastasia Doikou

We introduce the special set-theoretic Yang-Baxter algebra and show that it is a Hopf algebra subject to certain conditions. The associated universal R-matrix is also obtained via an admissible Drinfel'd twist. The structure of braces emerges naturally in this context by requiring the special set-theoretic Yang-Baxter algebra to be a Hopf algebra and a quasi

Qingming Zhao, Xueru Liu, Wei Wang

We explore the small mass limit of a stochastic wave equation (SWE) driven by cylindrical $\alpha$-stable noise, where $\alpha\in (1,2)$, and prove that it converges to a stochastic heat equation. We establish its well-posedness, and in particular, the c\`adl\`ag property, which is not trivial in the infinite dimensional case. Using a splitting technique, we

Ansh Singal, Kaitlin N. Smith

Quantum Random Access Memory (QRAM) holds the promise of enabling several large scale applications of quantum computers. However, designing fault tolerant QRAMs for large scale applications is still an open problem due to the poor error and resource scaling of current architectures. Existing protocols often overlook the need for error correcting QRAMs, which

F. Onori, M. Nicholl, P. Ramsden, S. McGee

We present the results from our multi-wavelength monitoring campaign of the transient AT2022wtn, discovered by the Zwicky Transient Facility in the nucleus of SDSSJ232323.79+104107.7, the less massive galaxy in an active merging pair with a mass ratio of ~10:1. AT2022wtn shows spectroscopic and photometric properties consistent with a X-ray faint N-strong TD

Reem Abdel-Salam, Mary Adewunmi

Health Mention Classification (HMC) plays a critical role in leveraging social media posts for real-time tracking and public health monitoring. Nevertheless, the process of HMC presents significant challenges due to its intricate nature, primarily stemming from the contextual aspects of health mentions, such as figurative language and descriptive terminology

Hugo Araujo, Xinyi Wang, Mohammad Mousavi, Shaukat Ali

Quantum computing has emerged as a powerful tool to efficiently solve computational challenges, particularly in simulation and optimisation. However, hardware limitations prevent quantum computers from achieving the full theoretical potential. Among the quantum algorithms, quantum annealing is a prime candidate to solve optimisation problems. This makes it a

Kenneth Skiba, Tjitze Rienstra, Matthias Thimm, Jesse Heyninck

In this paper, we present a general framework for ranking sets of arguments in abstract argumentation based on their plausibility of acceptance. We present a generalisation of Dung's extension semantics as extension-ranking semantics, which induce a preorder over the power set of all arguments, allowing us to state that one set is "closer" to being acceptabl

Yan Shu, Weichao Zeng, Fangmin Zhao, Zeyu Chen

Visual text is a crucial component in both document and scene images, conveying rich semantic information and attracting significant attention in the computer vision community. Beyond traditional tasks such as text detection and recognition, visual text processing has witnessed rapid advancements driven by the emergence of foundation models, including text i

Andrei-Alexandru Manea, Jindřich Libovický

Most pre-trained Vision-Language (VL) models and training data for the downstream tasks are only available in English. Therefore, multilingual VL tasks are solved using cross-lingual transfer: fine-tune a multilingual pre-trained model or transfer the text encoder using parallel data. We study the alternative approach: transferring an already trained encoder

Pan Suo, Yu-Ming Shang, San-Chuan Guo, Xi Zhang

Retrieval-Augmented Generation (RAG) integrates Large Language Models (LLMs) with external knowledge bases, improving output quality while introducing new security risks. Existing studies on RAG vulnerabilities typically focus on exploiting the retrieval mechanism to inject erroneous knowledge or malicious texts, inducing incorrect outputs. However, these ap

Aman Sharma, Benoit Baudry, Martin Monperrus

The increasing complexity of software supply chains and the rise of supply chain attacks have elevated concerns around software integrity. Users and stakeholders face significant challenges in validating that a given software artifact corresponds to its declared source. Reproducible Builds address this challenge by ensuring that independently performed build

Davide Ferri

The Yang-Baxter equation (YBE) and the reflection equation (RE) both come from mathematical physics, and they can be defined in any monoidal category. For cartesian monoidal categories, we prove that every solution to the RE provides a Drinfeld twist for a solution of the YBE. As we observe, Drinfeld twists of solutions are relevant for the following reason:

Michelle Wastl, Jannis Vamvas, Selena Calleri, Rico Sennrich

We present 20min-XD (20 Minuten cross-lingual document-level), a French-German, document-level comparable corpus of news articles, sourced from the Swiss online news outlet 20 Minuten/20 minutes. Our dataset comprises around 15,000 article pairs spanning 2015 to 2024, automatically aligned based on semantic similarity. We detail the data collection process a

Qu Cao, Jin Dong, Song He, Fan Zhu

We reformulate tree-level amplitudes in open superstring theory (type-I) in terms of stringy Tr$(\phi^3)$ amplitudes with various kinematical shifts in the "curve-integral" formulation: while the bosonic-string amplitude with $n$ pairs of "scaffolding" scalars comes from a particularly simple shift of the Tr$(\phi^3)$ one (corresponding to $n$ length-$2$ cyc

Nicole Schirrmacher, Sebastian Siebertz, Alexandre Vigny

In the Dominated Cluster Deletion problem, we are given an undirected graph $G$ and integers $k$ and $d$ and the question is to decide whether there exists a set of at most $k$ vertices whose removal results in a graph in which each connected component has a dominating set of size at most $d$. In the Elimination Distance to Dominated Clusters problem, we are

Nikolaos Galatos, Vitor Greati, Revantha Ramanayake, Gavin St. John

Substructural logics are formal logical systems that omit familiar structural rules of classical and intuitionistic logic such as contraction, weakening, exchange (commutativity), and associativity. This leads to a resource-sensitive logical framework that has proven influential beyond mathematical logic and its algebraic semantics, across theoretical comput

Adam Erickson, Qihan Zhang, Hamed Vakili, Edward Schwartz

Topological spin textures (e.g. skyrmions) can be stabilized by interfacial Dzyaloshinskii-Moriya interaction (DMI) in the magnetic multilayer, which has been intensively studied. Recently, Bloch-type magnetic skyrmions stabilized by composition gradient-induced DMI (g-DMI) have been observed in 10-nm thick CoPt single layer. However, magnetic anisotropy in

Giacomo Perri

The Futaki invariant is a fundamental tool in K\"ahler geometry representing an obstruction to the existence of K\"ahler-Einstein metrics. Recently, it was generalized to compact complex manifolds. In this paper, we prove that it vanishes on Hopf manifolds.

Birendra Chhotaray, Gaurava K. Jaisawal, Sachindra Naik, Arghajit Jana

We present the results of the broadband timing and spectral analysis of the poorly understood SMC pulsar RX J0032.9-7348 (= SXP 7.02) using NuSTAR and NICER observations during its X-ray brightening in 2024. Our timing analysis revealed a pulsation period of approximately 7.02 s in the X-ray light curve. The pulse profile obtained in the broad energy range i

Quentin Bonassies, Thanh Huy Nguyen, Ludovic Cassan, Andrea Piacentini

Floods are one of the most common and devastating natural disasters worldwide. The contribution of remote sensing is important for reducing the impact of flooding both during the event itself and for improving hydrodynamic models by reducing their associated uncertainties. This article presents the innovative capabilities of the Surface Water and Ocean Topog

Demian Pouzo, Martin Sola, Zacharias Psaradakis

This paper studies the robustness of quasi-maximum-likelihood (QML) estimation in hidden Markov models (HMMs) when the regime-switching structure is misspecified. Specifically, we examine the case where the true data-generating process features a hidden Markov regime sequence with covariate-dependent transition probabilities, but estimation proceeds under a

Baolei Zhang, Haoran Xin, Minghong Fang, Zhuqing Liu

Large language models (LLMs) integrated with retrieval-augmented generation (RAG) systems improve accuracy by leveraging external knowledge sources. However, recent research has revealed RAG's susceptibility to poisoning attacks, where the attacker injects poisoned texts into the knowledge database, leading to attacker-desired responses. Existing defenses, w

Jingwen Cai, Sara Leckner, Johanna Björklund

Keyword extraction is a foundational task in natural language processing, underpinning countless real-world applications. One of these is contextual advertising, where keywords help predict the topical congruence between ads and their surrounding media contexts to enhance advertising effectiveness. Recent advances in artificial intelligence have improved key

Haowei Li, Zhiyuan Yao, Xingze Qiu

Estimating partition functions of Ising spin glasses is a cornerstone of statistical physics and computational science, yet it remains classically challenging due to its $\#$P-hard complexity. While Jarzynski's equality offers a theoretical pathway, its practical application is crippled at low temperatures by rare, divergent statistical fluctuations. Here, w

Paige Tuttösí, Mantaj Dhillon, Luna Sang, Shane Eastwood

Some speech recognition tasks, such as automatic speech recognition (ASR), are approaching or have reached human performance in many reported metrics. Yet, they continue to struggle in complex, real-world, situations, such as with distanced speech. Previous challenges have released datasets to address the issue of distanced ASR, however, the focus remains pr

Stephen McKean, Giosuè Muratore, Wern Juin Gabriel Ong

We give two geometric interpretations for the local type of a line that is highly tangent to a hypersurface in a single point. One interpretation is phrased in terms of the Wronski map, while the other interpretation relates to the fundamental forms of the hypersurface. These local types are the local contributions of an quadratic form-valued Euler number th

Won Hee Ryu, John D. Russo, Mats S. Johnson, Jeremy T. Copperman

Weighted ensemble (WE) is an enhanced path-sampling method that is conceptually simple, widely applicable, and statistically exact. In a WE simulation, an ensemble of trajectories is periodically pruned or replicated to enhance sampling of rare transitions and improve estimation of mean first passage times (MFPTs). However, poor choices of the parameters gov

Mauricio Ortiz Torres, Markus Lange, Arne P. Raulf

The Forward-Forward algorithm has evolved in machine learning research, tackling more complex tasks that mimic real-life applications. In the last years, it has been improved by several techniques to perform better than its original version, handling a challenging dataset like CIFAR10 without losing its flexibility and low memory usage. We have shown in our

Marco Jeschke, Timm Faulwasser, Roland Fried

Predicting the time series of future evolutions of renewable injections and demands is of utmost importance for the operation of power systems. However, the current state of the art is mostly focused on mean-value time series predictions and only very few methods provide probabilistic forecasts. In this paper, we rely on kernel density estimation and vine co

Ling-Yan Hung, Yikun Jiang, Bing-Xin Lao

In this paper, we study the ensemble average of boundary CFT (BCFT) data consistent with the bootstrap equations. We apply the results to computing ensemble average of copies of multi-point correlation functions of boundary changing operators (BCO), and find the results in agreement with one copy of the Virasoro TQFT. Further, we consider ensemble average of

Haotian Luo, Haiying He, Yibo Wang, Jinluan Yang

Recently, long-thought reasoning models achieve strong performance on complex reasoning tasks, but often incur substantial inference overhead, making efficiency a critical concern. Our empirical analysis reveals that the benefit of using Long-CoT varies across problems: while some problems require elaborate reasoning, others show no improvement, or even degr

Edoardo Lombardo

This Ph.D. thesis explores approximations and regularity for the Heston stochastic volatility model through three interconnected works. The first work focuses on developing high-order weak approximations for the Cox-Ingersoll-Ross (CIR) process, essential for financial modelling but challenging due to the square root diffusion term preventing standard method

Runbo Li

The author prove that there exists a function $\rho(n)$ which is a minorant for the prime indicator function $\mathbb{1}_{p}(n)$ and has distribution level $\frac{10}{19}$ in arithmetic progressions to smooth moduli. This refines the previous results of Baker--Irving and Stadlmann.

Caterina Beatrice Leimer Saglio, Stefano Pagani, Paola F. Antonietti

Multiscale mathematical models have shown great promise in computational brain electrophysiology but are still hindered by high computational costs due to fast dynamics and complex brain geometries, requiring very fine spatio-temporal resolution. This paper introduces a novel p-adaptive discontinuous Galerkin method on polytopal grids (PolyDG) coupled with C

Hossein Davoudi, Behrouz Shahgholi Ghahfarokhi, Neda Moghim, Sachin Shetty

In the future wireless networks, terrestrial, aerial, space, and maritime wireless networks are integrated into a unified network to meet the needs of a fully connected global network. Nowadays, vehicular communication has become one of the challenging applications of wireless networks. In this article, we aim to address the radio resource management in Cell

Hongshu Lin, Wenston J. T. Zang

Let $b_{n,k}$ denote the number of hooks of length $k$ in all the $t$-regular partitions of $n$. Singh and Barman raised the question of finding the relation between $b_{t,2}(n)$ and $b_{t,1}(n)$. Kim showed that there exists $N$ such that $b_{t,2}(n)\ge b_{t,1}(n)$ and $b_{t,2}(n) \geq b_{t,3}(n)$ for $n>N$. In this paper, we find an explicit bound of $N=O(

Antonio Amariti, Fabio Mantegazza, Simone Rota

In this paper we study the IR dynamics of $SU(N)$ gauge theories with four supercharges in 3d in presence of symmetric or antisymmetric tensor. Using the tensor deconfinement technique we provide some proofs of results previously claimed in the literature about confining dualities for $SU(N)$ with two antisymmetric tensors. Furthermore we study 3d confining

Zan-Bo Zhang, Weihua He, Hajo Broersma, Xiaoyan Zhang

A digraph $D$ is called \emph{path extendable} if for every nonhamiltonian (directed) path $P$ in $D$, there exists another path $P^\prime$ with the same initial and terminal vertices as $P$, and $V(P^\prime) = V (P)\cup \{w\}$ for a vertex $w \in V(D)\setminus V(P)$. Hence, path extendability implies paths of continuous lengths between every vertex pair. In

Colby Kelln, Jason Manning

Let M be a compact hyperbolic manifold with totally geodesic boundary. If the injectivity radius of the boundary is larger than an explicit function of the normal injectivity radius of the boundary, we show that there is a negatively curved metric on the space obtained by coning each boundary component of M to a point. Moreover, we give explicit geometric co

Jean-Baptiste de Vaulx, Quintin N. Meier, Pierre Toulemonde, Andrés Cano

The recent discovery of superconductivity in La$_3$Ni$_2$O$_7$ at a critical temperature above 80~K points to a non-conventional pairing mechanism in nickelates as in cuprates, possibly due to electronic correlations. We have calculated from first principles the electronic structure of La$_3$Ni$_2$O$_7$ under the effect of pressure and epitaxial strain inclu

Haiyang Zhou, Wangbo Yu, Jiawen Guan, Xinhua Cheng

The rapid advancement of diffusion models holds the promise of revolutionizing the application of VR and AR technologies, which typically require scene-level 4D assets for user experience. Nonetheless, existing diffusion models predominantly concentrate on modeling static 3D scenes or object-level dynamics, constraining their capacity to provide truly immers

Pravin Kumar Dahal, Kieran Hymas

We demonstrate that the future and left Rindler wedges of Minkowski spacetime are entangled, leading to the Unruh effect. Similarly, the past and right Rindler wedges are also entangled. We propose a protocol to extract this entanglement using two two-state detectors located in the past and right Rindler wedges. By scaling the detector transition frequencies

Raluca M. Balan, Juan J. Jiménez

In this article, we continue the investigations initiated by the first author in Balan (2015) related to the study of stochastic partial differential equations (SPDEs) with L\'evy colored noise on $\mathbb{R}_{+} \times \mathbb{R}^d$. This noise is constructed from a L\'evy white noise (which is in turn built from a Poisson random measure with intensity $dtd

Michael Wieck-Sosa, Michel F. C. Haddad, Aaditya Ramdas

Identifying relationships among stochastic processes is a core objective in many fields, such as economics. While the standard toolkit for multivariate time series analysis has many advantages, it can be difficult to capture nonlinear dynamics using linear vector autoregressive models. This difficulty has motivated the development of methods for causal disco

Liqin Wang, Qianyue Hu, Wei Lu, Xiangyang Luo

The success of face recognition (FR) systems has led to serious privacy concerns due to potential unauthorized surveillance and user tracking on social networks. Existing methods for enhancing privacy fail to generate natural face images that can protect facial privacy. In this paper, we propose diffusion-based adversarial identity manipulation (DiffAIM) to

Dieter Boeyaert, Stefano Carli, Wouter Dekeyser, Sven Wiesen

The effect of neon seeding on different transport mechanisms in EAST is investigated by analyzing SOLPSITER simulations. By evaluating the agreement between experimental observations and the performed simulations, four simulations are selected for a detailed analysis. In this analysis, it is shown that the presence of neon reduces the influence of drifts on

Qiu Shi Wang

We construct a 2-parameter family of new triaxial $SU(2)$-invariant complete negative Einstein metrics on the complex line bundle $\mathcal{O}(-4)$ over $\mathbb{C}P^1$. The metrics are conformally compact and neither K\"ahler nor self-dual. The proof involves using rigorous numerics to produce an approximate Einstein metric to high precision in a bounded re

Luca Marzari, Francesco Trotti, Enrico Marchesini, Alessandro Farinelli

Achieving safe autonomous navigation systems is critical for deploying robots in dynamic and uncertain real-world environments. In this paper, we propose a hierarchical control framework leveraging neural network verification techniques to design control barrier functions (CBFs) and policy correction mechanisms that ensure safe reinforcement learning navigat

Raffaele Di Santo, Dikran Dikranjan, Anna Giordano Bruno, Hans Weber

According to Cartan, given an ideal $\mathcal I$ of $\mathbb N$, a sequence $(x_n)_{n\in\mathbb N}$ in the circle group $\mathbb T$ is said to {\em $\mathcal I$-converge} to a point $x\in \mathbb T$ if $\{n\in \mathbb N: x_n \not \in U\}\in \mathcal I$ for every neighborhood $U$ of $x$ in $\mathbb T$. For a sequence $\mathbf u=(u_n)_{n\in\mathbb N}$ in $\mat

Ian G. Moss

Given the right set of circumstances, ultracold quantum gases are able to change character and condense into a liquid state of quantum droplets. The size distribution of the droplets is determined dynamically in the condensation process. A semi-quantitative argument is presented which suggests that, at zero temperature, a multiple droplet system has is a pre

Leyi Ouyang

Modern news is often comprehensive, weaving together information from diverse domains, including technology, finance, and agriculture. This very comprehensiveness creates a challenge for interpretation, as audiences typically possess specialized knowledge related to their expertise, age, or standpoint. Consequently, a reader might fully understand the financ

Matúš Labaj, Sean M. Ressler, Michal Zajaček, Tomáš Plšek

Intermediate-mass black holes (IMBHs) are a missing link in black hole demographics, with only tentative observational evidence to date. Dense stellar clusters such as IRS 13E near the Galactic Center are promising IMBH hosts, where accretion is likely driven by winds from nearby Wolf-Rayet (WR) stars. Yet, the dynamics of such wind-fed systems remain largel

Carlo Marcati, Christoph Schwab, Jakob Zech

We investigate the sparsity of Wiener polynomial chaos expansions of holomorphic maps $\mathcal{G}$ on Gaussian Hilbert spaces, as arise in the coefficient-to-solution maps of linear, second order, divergence-form elliptic PDEs with log-Gaussian diffusion coefficient. Representing the Gaussian random field input as an affine-parametric expansion, the nonline

Owen Ekblad

In this note, we prove that the index of primitivity of any primitive unital Schwarz map is at most $2(D-1)^2$, where $D$ is the dimension of the underlying matrix algebra. This inequality was first proved by Rahaman for Schwarz maps which were both unital and trace preserving. As we show, the assumption of unitality is basically innocuous, but in general no

Paolo Piersanti

The purpose of this paper is twofold. First, we rigorously justify Koiter's model for linearly elastic elliptic membrane shells in the case where the shell is subject to a geometrical constraint modelled via a normal compliance contact condition defined in the interior of the shell. To achieve this, we establish a novel density result for non-empty, closed,

Mitchell Chiew, Cameron Ibrahim, Ilya Safro, Sergii Strelchuk

Simulation of fermionic systems is one of the most promising applications of quantum computers. It spans problems in quantum chemistry, high-energy physics and condensed matter. Underpinning the core steps of any quantum simulation algorithm, fermion-qubit mappings translate the fermionic interactions to the operators and states of quantum computers. This tr

Zeina Aldallal, Sara Chrouf, Khalil Hennara, Mohamed Motaism Hamed

Arabic text diacritization remains a persistent challenge in natural language processing due to the language's morphological richness. In this paper, we introduce Sadeed, a novel approach based on a fine-tuned decoder-only language model adapted from Kuwain 1.5B Hennara et al. [2025], a compact model originally trained on diverse Arabic corpora. Sadeed is fi

Chih-Cheng Rex Yuan, Bow-Yaw Wang

Fairness auditing of AI systems can identify and quantify biases. However, traditional auditing using real-world data raises security and privacy concerns. It exposes auditors to security risks as they become custodians of sensitive information and targets for cyberattacks. Privacy risks arise even without direct breaches, as data analyses can inadvertently

Simon Viel, Lionel Truquet, Ikko Yamane

Estimating some mathematical expectations from partially observed data and in particular missing outcomes is a central problem encountered in numerous fields such as transfer learning, counterfactual analysis or causal inference. Matching estimators, estimators based on k-nearest neighbours, are widely used in this context. It is known that the variance of s

Fuma Ito, Chihiro Tsutake, Keita Takahashi, Toshiaki Fujii

To efficiently compress the sign information of images, we address a sign retrieval problem for the block-wise discrete cosine transformation (DCT): reconstruction of the signs of DCT coefficients from their amplitudes. To this end, we propose a fast sign retrieval method on the basis of binary classification machine learning. We first introduce 3D represent

Sibo Guo, Shuai Yin, Shi-Xin Zhang, Zi-Xiang Li

Non-equilibrium dynamics in non-Hermitian systems has attracted significant interest, particularly due to the skin effect and its associated anomalous phenomena. Previous studies have primarily focused on initial states with a definite particle number. Here, we present a systematic study of non-reciprocal quench dynamics in the pairing states with indefinite

Ian Pilé, Evgeni Burovski

We investigate the interplay between superconducting correlations and trimer formation in polarized two-component Fermi gases confined to multileg attractive-$U$ Hubbard ladders. Employing density matrix renormalization group (DMRG) simulations, we explore the effects of spin-dependent tunneling amplitudes on these systems. Specifically, we analyze how bound

Marco Cicalese, Leonard Kreutz, Gian Paolo Leonardi, Gabriele Morselli

While the classical Faber-Krahn inequality shows that the ball uniquely minimizes the first Dirichlet eigenvalue of the Laplacian in the continuum, this rigidity may fail in the discrete setting. We establish quantitative fluctuation estimates for the first Dirichlet eigenvalue of the combinatorial Laplacian on subsets of $\mathbb{Z}^{d}$ when their cardinal

Zan-Bo Zhang, Wenhao Wu, Weihua He

Bang-Jensen-Gutin-Li type conditions are the conditions for hamiltonicity of digraphs which impose degree restrictions on nonadjacent vertices which have a common in-neighbor or a common out-neighbor. They can be viewed as an extension of Fan type conditions in undirected graphs, as well as generalization of locally (in-, out-)semicomplete digraphs. Since th

Shin Fujieda, Chih-Chen Kao, Takahiro Harada

Neural representations have shown the potential to accelerate ray casting in a conventional ray-tracing-based rendering pipeline. We introduce a novel approach called Locally-Subdivided Neural Intersection Function (LSNIF) that replaces bottom-level BVHs used as traditional geometric representations with a neural network. Our method introduces a sparse hash

Or Dobkowski, Barak Trok, Peter Skakunenko, Yonathan Japha

We show that in contrast to a recent claim, the Quantum Galileo Interferometer is sensitive to a uniform gravitational field in the presence and even in the absence of the levitation condition.

Jiaming wang, Yunke Zhao, Peng Ding, Jun Kuang

The capability to precisely adhere to instructions is a cornerstone for Large Language Models (LLMs) to function as dependable agents in real-world scenarios. However, confronted with complex prompts, LLMs frequently encounter difficulties in fulfilling all specified requirements within a single response. Drawing inspiration from recent advancements in Chain

Florian Hörsch, Dániel Marx

Given a graph $G$, a set $T$ of terminal vertices, and a demand graph $H$ on $T$, the \textsc{Multicut} problem asks for a set of edges of minimum weight that separates the pairs of terminals specified by the edges of $H$. The \textsc{Multicut} problem can be solved in polynomial time if the number of terminals and the genus of the graph is bounded (Colin de