October 2025 arXiv papers — page 59

Aziza Almanakly, Reouven Assouly, Harry Hanlim Kang, Michael Gingras

Non-Hermitian Hamiltonians with complex eigenenergies are useful tools for describing the dynamics of open quantum systems. In particular, parity and time (PT) symmetric Hamiltonians have generated interest due to the emergence of exceptional-point degeneracies, where both eigenenergies and eigenvectors coalesce as the energy spectrum transitions from real-

Jared Claypoole, Yunye Gong, Noson S. Yanofsky, Ajay Divakaran

We apply category theory to extract multimodal document structure which leads us to develop information theoretic measures, content summarization and extension, and self-supervised improvement of large pretrained models. We first develop a mathematical representation of a document as a category of question-answer pairs. Second, we develop an orthogonalizatio

Jacqueline Janssen, Frank Jülicher, Christoph A. Weber

In this work, we propose a theory for the kinetics of emulsions in which a continuous supply of matter feeds droplet growth. We consider cases where growth is either limited by bulk diffusion or the transport through the droplets' interfaces. Our theory extends the Lifshitz-Slyozov-Wagner (LSW) theory by two types of matter supply, where either the supersatu

Jialu Tang, Hung Manh Pham, Ignace De Lathauwer, Henk S. Schipper

Electrocardiogram (ECG) interpretation is essential for cardiovascular disease diagnosis, but current automated systems often struggle with transparency and generalization to unseen conditions. To address this, we introduce ZETA, a zero-shot multimodal framework designed for interpretable ECG diagnosis aligned with clinical workflows. ZETA uniquely compares

Christian Kremer

In this note, we record the proof of a theorem about the coincidence of genuine and homotopy fixed points for isometric group actions on complete Riemannian manifolds with nonpositive sectional curvature, and more generally, certain quotients of universal spaces for families. The result is put into context with the Nielsen realisation problem for aspherical

Marc Fuchs, Fabian Kuhn

The distributed coloring problem is arguably one of the key problems studied in the area of distributed graph algorithms. The most standard variant of the problem asks for a proper vertex coloring of a graph with $Δ+ 1$ colors, where $Δ$ is the maximum degree of the graph. Despite an immense amount of work on distributed coloring problems in the distributed

Valeriia Muraveva, Agniva Datta, Jeungeun Park, Veronika Pfeifer

Bacterial swimming is well characterized in uniform liquids at rest. The natural habitat of bacterial swimmers, however, is often dominated by moving fluids and interfaces, resulting in shear flows that may strongly alter bacterial navigation strategies. Here, we study how fluid shear flow affects the swimming motility of the soil bacterium Pseudomonas putid

Hangyu Zhang, Sachin S. Sapatnekar

Global placement is essential for high-quality and efficient circuit placement for complex modern VLSI designs. Recent advancements, such as electrostatics-based analytic placement, have improved scalability and solution quality. This work demonstrates that using an accelerated FFT technique, AccFFT, for electric field computation significantly reduces runti

Alexander Katsevich

We study the saddlepoint approximation (SPA) for sums of $n$ i.i.d. random vectors $X_i\in\mathbb R^d$ in growing dimensions. SPA provides highly accurate approximations to probability densities and distribution functions via the moment generating function. Recent work by Tang and Reid extended SPA to cases where the dimension $d$ increases with $n$, obtaini

Rushikesh Ubale, Yasar Mulani, Abhay Suresh, Gregory Byrd

Multi-period stock-keeping unit (SKU) allocation in supply chains is a combinatorial optimization problem that is both NP-hard and operationally critical, requiring simultaneous attention to profitability, feasibility, and diversity. Quadratic unconstrained binary optimization (QUBO) provides a principled framework for such tasks, yet prior studies often rel

Zhen-Tai Zhang, Wei Zhong, Wei Wang, Jianheng Guo

Vertical mixing disrupts the thermochemical equilibrium and introduces additional heat flux that alters exoplanetary atmospheric temperatures. We investigate how this mixing-induced heat flux affects atmospheric chemistry. Temperature increase in the lower atmosphere by the mixing-induced heat flux alters species abundances there and modifies those in the up

Johann Flemming Gloy, Simon Olsson

Flow and diffusion-based models have emerged as powerful tools for scientific applications, particularly for sampling non-normalized probability distributions, as exemplified by Boltzmann Generators (BGs). A critical challenge in deploying these models is their reliance on sample likelihood computations, which scale prohibitively with system size $n$, often

Weihong Qin, Aimin Wang, Geng Sun, Zemin Sun

Space-air-ground integrated multi-access edge computing (SAGIN-MEC) provides a promising solution for the rapidly developing low-altitude economy (LAE) to deliver flexible and wide-area computing services. However, fully realizing the potential of SAGIN-MEC in the LAE presents significant challenges, including coordinating decisions across heterogeneous node

Christian Wallisch, Till Fluschnik, Leon Kellerhals

We study a network design problem motivated by the challenge of placing wildlife crossings to reconnect fragmented habitats of animal species, which is among the 17 goals towards sustainable development by the UN: Given a graph, whose vertices represent the fragmented habitat areas and whose edges represent possible green bridge locations (with costs), and t

Johannes Lohmann

It is tested whether past abrupt climate changes support the validity of statistical early-warning signals (EWS) as predictor of future climate tipping points. EWS are expected increases in amplitude and correlation of fluctuations driven by noise. This is a symptom of critical slowing down (CSD), where a system's recovery from an external perturbation becom

Paul-Niklas Ken Kandora, Adrian Asmund Fessler, Robert Fabian Lindermann, Phil Arnold

The Cable Routing Optimization Problem (CROP) is a Multi-Commodity Flow Problem (MCFP) central to industrial layouts and smart manufacturing. Historically, quantum optimization has modeled MCFPs as Quadratic Unconstrained Binary Optimization problems (QUBOs). Recent studies suggest that mapping routing problems to Polynomial Unconstrained Binary Optimization

Likun Tan, Kuan-Wei Huang, Joy Shi, Kevin Wu

Retrieval-Augmented Generation (RAG) integrates external knowledge to mitigate hallucinations, yet models often generate outputs inconsistent with retrieved content. Accurate hallucination detection requires disentangling the contributions of external context and parametric knowledge, which prior methods typically conflate. We investigate the mechanisms unde

Nikolai Gruzinov, Ksenia Sycheva, Earl T. Barr, Alex Bezzubov

Many tasks revolve around editing a document, whether code or text. We formulate the revision similarity problem to unify a wide range of machine learning evaluation problems whose goal is to assess a revision to an existing document. We observe that revisions usually change only a small portion of an existing document, so the existing document and its immed

Narendhiran Vijayakumar

Free-space segmentation is essential for autonomous robots to identify drivable regions and navigate safely across indoor, outdoor, and road-scene environments. However, conventional encoder-decoder models often recover coarse region masks while losing the fine spatial information needed to localize drivable-area boundaries accurately. We propose Attention-G

Retno Larasati

With the current progress of Artificial Intelligence (AI) technology and its increasingly broader applications, trust is seen as a required criterion for AI usage, acceptance, and deployment. A robust measurement instrument is essential to correctly evaluate trust from a human-centered perspective. This paper describes the development and validation process

Misaki Kida, Shimpei Sato

As IoT and edge inference proliferate,there is a growing need to simultaneously optimize area and delay in lookup-table (LUT)-based multipliers that implement large numbers of low-bitwidth operations in parallel. This paper proposes a hardwareefficientaccurate 4-bit multiplier design for AMD Xilinx 7-series FPGAs using only 11 LUTs and two CARRY4 blocks. By

Mojtaba Nafez, Mobina Poulaei, Nikan Vasei, Bardia Soltani Moakhar

Weakly Supervised Video Anomaly Detection (WSVAD) has achieved notable advancements, yet existing models remain vulnerable to adversarial attacks, limiting their reliability. Due to the inherent constraints of weak supervision, where only video-level labels are provided despite the need for frame-level predictions, traditional adversarial defense mechanisms,

Jan Wehner, Mario Fritz

Probes trained on model activations can detect undesirable behaviors like deception or biases that are difficult to identify from outputs alone. This makes them useful detectors to identify misbehavior. Furthermore, they are also valuable training signals, since they not only reward outputs, but also good internal processes for arriving at that output. Howev

Weiyong He, Junbang Liu

We prove that there is a unique $p_0\in [0,1)$, which can be characterized by the eigenvalue of Hilbert operator related to a convex body, that the even $L^p$ Minkowski problem has a unique solution for $p\geq p_0$, and the uniqueness fails for infinitely many convex bodies if $p<p_0$. The previous results by many experts in the field assert that the uniquen

Hideya Kuwata

A root system $\Phi$ of rank $n$ determines an $n$-dimensional smooth projective toric variety $X(\Phi)$ associated with the fan of its Weyl chambers. For the root system of type $A_n$, this variety is the well-known permutohedral variety $X_{A_n}$. Using purely combinatorial methods, we obtain an explicit closed formula expressing the product of Chern class

Wenhui Wan, Xinyue Liu, Yanfeng Ge, Ziqang Li

Two-dimensional (2D) phase-change materials (PCMs) with moderate transition barriers and distinctly contrasting properties are highly desirable for multifunctional devices, yet such systems remain scarce. Using first-principles calculations, we propose a hexagonal InOI monolayer as a promising 2D PCM. This material exhibits two distinct polymorphs: an energe

Isaac Johnson, Yu-Ming Liou, Jacob Rogers, Aaron Shaw

Writing Wikipedia with a neutral point of view is one of the five pillars of Wikipedia. Although the topic is core to Wikipedia, it is relatively understudied considering hundreds of research studies are published annually about the project. We hypothesize that part of the reason for the low research activity on the topic is that Wikipedia's definition of ne

Huatian Gong, Jiuh-Biing Sheu, Zheng Wang, Xiaoguang Yang

Post-disaster road assessment (PDRA) is essential for emergency response, enabling rapid evaluation of infrastructure conditions and efficient allocation of resources. Although drones provide a flexible and effective tool for PDRA, routing them in large-scale networks remains challenging. Exact and heuristic optimization methods scale poorly and demand domai

Ilija Lichkovski, Alexander Müller, Mariam Ibrahim, Tiwai Mhundwa

Large language models (LLMs) are increasingly deployed as agents in various contexts by providing tools at their disposal. However, LLM agents can exhibit unpredictable behaviors, including taking undesirable and/or unsafe actions. In order to measure the latent propensity of LLM agents for taking illegal actions under an EU legislative context, we introduce

Francesco Innocenti

Backpropagation (BP) is the standard algorithm for training the deep neural networks that power modern artificial intelligence including large language models. However, BP is energy inefficient and unlikely to be implemented by the brain. This thesis studies an alternative, potentially more efficient brain-inspired algorithm called predictive coding (PC). Un

Tobias M. R. Wolf, Tian Xie, Chenhao Jin, Allan H. MacDonald

Many monolayer transition metal dichalcogenides, including MoS$_2$, MoSe$_2$, WS$_2$, and WSe$_2$, are direct bandgap two-dimensional (2D) semiconductors with sharp optical resonances at excitonic bound state frequencies. Recent experiments have demonstrated that excitonic resonance frequencies in multilayer van der Waals stacks are altered by long-range Cou

Ya-Nan Du, Ji-Yu Song, Yichao Li, Shang-Jie Jin

Gravitational-wave (GW) events are generally believed to originate in galaxies and can thus serve, like galaxies, as tracers of the universe's large-scale structure. In GW observations, waveform analysis provides direct measurements of luminosity distances; however, without relying on a specific cosmological model, the redshifts of GW sources cannot be deter

Syon Bhattacharjee, Deepika Behmani, Sudeep Bhattacharjee

Cold atmospheric pressure plasma jets (APPJs) are non-equilibrium plasmas, that are capable of producing reactive oxygen and nitrogen species (RONS) at near-room temperature. Their interaction with water leads to the formation of plasma-activated water (PAW), whose chemical activity depends on discharge conditions. In this work, a helium-air (14:1) micro-pla

Omer Moussa, Mariya Toneva

Pretrained language models are remarkably effective in aligning with human brain responses elicited by natural language stimuli, positioning them as promising model organisms for studying language processing in the brain. However, existing approaches for both estimating and improving this brain alignment are participant-dependent and highly affected by the a

Simone Manti, Leonardo Abbene, Francesco Artibani, Massimiliano Bazzi

Kaonic atoms, formed when a negatively charged kaon replaces an electron, provide a unique laboratory to test fundamental interactions at low energies. EXKALIBUR (EXtensive Kaonic Atoms research: from LIthium and Beryllium to URanium) is a program to perform systematic, high-precision X-ray spectroscopy of selected kaonic atoms across the periodic table at t

Lorenzo Basile, Valentino Maiorca, Diego Doimo, Francesco Locatello

Language and vision-language models have shown impressive performance across a wide range of tasks, but their internal mechanisms remain only partly understood. In this work, we study how individual attention heads in text-generative models specialize in specific semantic or visual attributes. Building on an established interpretability method, we reinterpre

Hongbo Zhang, Han Cui, Yidong Wang, Yijian Tian

Automatic literature survey generation has attracted increasing attention, yet most existing systems follow a one-shot paradigm, where a large set of papers is retrieved at once and a static outline is generated before drafting. This design often leads to noisy retrieval, fragmented structures, and context overload, ultimately limiting survey quality. Inspir

Clément Guillet

This work introduces and analyzes B-spline approximation spaces defined on general geometric domains obtained through a mapping from a parameter domain. These spaces are constructed as sparse-grid tensor products of univariate spaces in the parameter domain and are mapped to the physical domain via a geometric parametrization. Both the univariate approximati

Marvin Böcker, Ralph Biggins, Michael Schmeing

We present our approach for a periodically unstaffed, fully automated ground segment. The concept is in use for the first time on the German satellite communications mission Heinrich Hertz on behalf of the German Space Agency at DLR. Heinrich Hertz was launched in July 2023 and offers access to scientific and technical experiments to its users. The mission u

Wei He, Jungwon Lee

Inspired by the work of Deninger, we present a formula that relates the Mahler measure of a two-variable variant of cyclotomic polynomial to regulator of class in motivic cohomology associated to cyclotomic fields and linear combination of special values of the derivative of Dirichlet $L$-functions. The formula is derived by studying the Beilinson regulator

Wojciech Czerwiński, Łukasz Orlikowski

In this work, we extend undecidability of language equivalence for two-dimensional Vector Addition System with States (VASS) accepting by coverability condition. We show that the problem is undecidable even when one of the two-dimensional VASSs is deterministic and the other is history-deterministic. Moreover, we observe, that the languages of two history-de

Fernando Vallecillos-Ruiz, Max Hort, Leon Moonen

Today's pursuit of a single Large Language Model (LMM) for all software engineering tasks is resource-intensive and overlooks the potential benefits of complementarity, where different models contribute unique strengths. However, the degree to which coding LLMs complement each other and the best strategy for maximizing an ensemble's potential are unclear, le

Kaibo Wang, Jianda Mao, Tong Wu, Yang Xiang

Classifier-Free Guidance (CFG) is an essential component of text-to-image diffusion models, and understanding and advancing its operational mechanisms remains a central focus of research. Existing approaches stem from divergent theoretical interpretations, thereby limiting the design space and obscuring key design choices. To address this, we propose a unifi

Qihua Zhang, Christopher J. Jensen, Alexander J. Grutter, Sandra Santhosh

Altermagnets are a recently-discovered class of materials with magnetic ordering that have a zero net magnetization and a momentum-dependent spin splitting in their band structure, arising from a collinear spin arrangement with alternating polarizations in the crystal lattice. The nickeline-structured manganese telluride ({\alpha}-MnTe) is an attractive alte

Huai-Jin Tang, Xiao-Lei Meng, Hu Zhan, Guo-Liang Li

Low Earth Orbit satellite (LEOsat) mega-constellations are considered to be an unavoidable source of contamination for survey observations to be carried out by the China Space Station Telescope (CSST) over the next decade. This study reconstructs satellite trail profiles based on simulated parameters, including brightness levels and orbital altitudes, in com

Carmen Álvarez Roa, Yunus Can Gültekin, Vincent van Vliet, Menno van den Hout

Weak turbulence is commonly modeled using the log-normal distribution. Our experimental results show that this distribution fails to capture irradiance fluctuations in this regime. The Gamma-Gamma model is shown to be more accurate.

Victor Jüttner, Charlotte S. Löffler, Erik Buchmann

The proliferation of smart home devices has increased convenience but also introduced cybersecurity risks for everyday users, as many devices lack robust security features. Intrusion Detection Systems are a prominent approach to detecting cybersecurity threats. However, their alerts often use technical terms and require users to interpret them correctly, whi

Lingke Jiang, G. Brooke Anderson, Yanran Li, Xiao Wu

Full impact assessment of tropical cyclones each year requires a comprehensive sociodemographic analysis. We evaluated sociodemographic characteristics of tropical cyclone-impacted regions during the 2024 calendar year in recent historical context of 1980-2024. In 2024, tropical cyclone-force wind affected an estimated 429,902,820 people (5.5% of global popu

Eyad H. Al-Samra

An introductory, self-contained overview, with pedagogical figures, is provided to acquaint readers unfamiliar with the subjects with key aspects of de Sitter space and inflation. The connection between de Sitter space and cosmology is reviewed. The embedding of a hyperboloid surface in higher-dimensional Minkowski space is analysed, and the Killing vectors

Tanmay Devale, Pramith Devulapalli, Steve Hanneke

We characterize conditions under which collections of distributions on $\{0,1\}^\mathbb{N}$ admit uniform estimation of their mean. Prior work from Vapnik and Chervonenkis (1971) has focused on uniform convergence using the empirical mean estimator, leading to the principle known as $P-$ Glivenko-Cantelli. We extend this framework by moving beyond the empiri

Shogo Nakakita

We study sparsity-regularized maximum likelihood estimation for the drift parameter of high-dimensional non-stationary Ornstein--Uhlenbeck processes given repeated measurements of i.i.d. paths. In particular, we show that Lasso and Slope estimators can achieve the minimax optimal rate of convergence. We exhibit numerical experiments for sparse estimation met

F. Daem, T. Durt, A. Matzkin

From "surreal" trajectories to which-way measurements, Basil Hiley had a lesson: claims of falsifying the Bohmian model do not withstand scrutiny provided the model is applied correctly. In this work we compute de Broglie-Bohm trajectories for particles tunneling in coupled waveguides relevant to a recent experiment having claimed to challenge the Bohmian mo

Alexandru Chirvasitu, Piotr M. Sołtan, Mateusz Wasilewski

A quantum graph $\mathcal{G}$ housed by a matrix algebra $M_n$ can be encoded as an operator system $\mathcal S=\mathcal{S}_{\mathcal{G}}\le M_n$. There are two sensible notions of quantum automorphism group for any such: $\mathrm{Qut}(\mathcal G)$, capturing the quantum symmetries of the adjacency matrix $A:M_n\to M_n$ attached to $\mathcal{G}$, and $\mathr

Fadi Dornaika, Ahmad Khoder, Abdelmalik Moujahid, Wassim Khoder

The performance of machine learning and pattern recognition algorithms generally depends on data representation. That is why, much of the current effort in performing machine learning algorithms goes into the design of preprocessing frameworks and data transformations able to support effective machine learning. The method proposed in this work consists of a

Leonardo Ricca, Matthias Vereecken, Christoph Raab, Mathieu Lamoureux

Binary black holes (BBHs) in the vicinity of Active Galactic Nuclei (AGNs) are particularly interesting systems from both a cosmological and astrophysical point of view. Matter and radiation fields within the dense AGN environment could produce electromagnetic and neutrino emission in addition to gravitational waves (GWs). Moreover, interactions between BBHs

K. É. Gabányi, S. Komossa, A. Kraus, A. Mezősi

We have identified a high-amplitude radio outburst in the course of a large-sample study of the radio properties of narrow-line Seyfert 1 (NLS1) galaxies. We have analysed previous radio data and obtained new radio observations with the Effelsberg 100 m telescope, in order to measure the properties and understand the nature of the high-amplitude radio variab

G. Lusztig

Let W be a Weyl group. We can define the notion of positivity of a W-module in terms of the corresponding module over the asymptotic Iwahori-Hecke algebra. We state a conjecture which says that certain explicit W-modules are positive and we prove it in the case where W is of classical type.

Silvia Barbina, Riccardo Camerlo, Domenico Zambella

Recently, a classical approach to continuous structures has been proposed in [ABBMZ] and [Z] that extends the class of structures falling under the scope of [HI] or [BBHU]. These articles introduce the notion of structures with a standard sort. We discuss local stability in this context. We examine three variants of the order property which are prima facie n

Victor Alfieri

In this paper, we construct in characteristic zero a derived foliation on derived mapping stacks $\underline{\mathbf{Map}}_S(X,Y)$, for $S$ a base derived stack, $X$ a proper schematic, flat, and local complete intersection derived stack over $S$, and $Y$ a relative derived Deligne-Mumford stack over $S$, when $Y$ is equipped with a derived foliation relativ

Job Petrovčič, David Eliecer Narvaez Denis, Ljupčo Todorovski

Premise selection is a key bottleneck for scaling theorem proving in large formal libraries. Yet existing language-based methods often treat premises in isolation, ignoring the web of dependencies that connects them. We present a graph-augmented approach that combines dense text embeddings of Lean formalizations with graph neural networks over a heterogeneou

Yinhe Peng

We show that Martin's axiom for $\omega_1$ dense sets is equivalent to its fragment asserting that every ccc poset has the Knaster property K$_3$. On the other hand, we show that the dimension 3 in K$_3$ is in some sense minimal.

Xiaoqing Liu, Jitai Han, Hua Yan, Peng Li

Placental abruption is a severe complication during pregnancy, and its early accurate diagnosis is crucial for ensuring maternal and fetal safety. Traditional ultrasound diagnostic methods heavily rely on physician experience, leading to issues such as subjective bias and diagnostic inconsistencies. This paper proposes an improved model, EH-YOLOv11n (Enhance

Anshika Bansal, Guido Bell, Aritra Biswas, Diptaparna Biswas

Sharing the amazing achievements of the (particle) physics world with the general public is at the heart of the mission of the Subatomic Heroes, based at the University of Siegen, Germany. Originally this started out as an endeavor of theoretical particle physics, now we are steadily spreading out to cover and include more branches of physics and science. Ou

Bocheng Guo, Jin Wang, Yijie Li, Junyi Wang

Tractography fiber clustering using diffusion MRI (dMRI) is a crucial method for white matter (WM) parcellation to enable analysis of brains structural connectivity in health and disease. Current fiber clustering strategies primarily use the fiber geometric characteristics (i.e., the spatial trajectories) to group similar fibers into clusters, while neglecti

Rüdiger Valk, Daniel Moldt

Cycloids are particular Petri nets for modelling processes of actions and events, belonging to the fundaments of Petri's general systems theory. Defined by four parameters they provide an algebraic formalism to describe strongly synchronized sequential processes. To further investigate their structure, reduction systems of cycloids are defined in the style o

Mathieu Dutour

In a previous paper, we studied the connection between points in $\mathbb{H}^n$ and $2$-dimensional rigid adelic spaces on a totally real number field $K$ with class number $h_K = 1$. This last assumption was needed to link heights and distances to cusps. In this paper, we remove this hypothesis to obtain, without restriction on $K$ totally real, an analogue

Khaled Hallak, Oudom Kem

Catastrophic forgetting (CF) poses a persistent challenge in continual learning (CL), especially within federated learning (FL) environments characterized by non-i.i.d. time series data. While existing research has largely focused on classification tasks in vision domains, the regression-based forecasting setting prevalent in IoT and edge applications remain

Jared Miller, Fabian Jakob, Carsten Scherer, Andrea Iannelli

Deployment of optimization algorithms over communication networks face challenges associated with time delays and corruptions. Fixed time delays can destabilize popular gradient-based algorithms, and this degradation is exacerbated by time-varying delays that may arise from packet drops. This work concentrates on the analysis and synthesis of discrete-time o

Nouredine Medjoudj, Abdelkrim Moussaoui

We consider singular quasilinear elliptic systems with homogeneous Dirichlet boundary condition. Using Leray-Schauder topological degree, combined with the sub-supersolutions method and suitable truncation arguments, we establish the existence of at least three nontrivial solutions, two of which are of opposite constant sign. The third solution is nodal and

Yuan Qilong, Michal Pavelka

This paper works on heuristic solver for joint assignment and routing optimization problem. Study on previous works shows that MIP based exact solvers can only provide efficient solutions for small to moderate size problems, due to exponentially growing computational complexity. This paper proposes to start with high quality initial guess through Hungarian a

Jun Dai, Ayumi Asai, Dechao Song, Ye Qiu

Prominence seismology, applied to the large-amplitude longitudinal oscillation, is used to indirectly diagnose the geometry and strength of the magnetic fields inside the prominence. In this paper, combining imaging and spectroscopic data, the magnetic field configuration of a quiescent prominence is revealed by large-amplitude longitudinal oscillations obse

Marco Belli

We show that the canonical isomorphism $\mathrm{H}_{sin}^*(X,\underline{\mathbb{Z}})\xrightarrow{\sim} \check{\mathrm{H}}_{\mathcal{U}}^*(X,\underline{\mathbb{Z}})$ is the evaluation of singular cohomology classes at the simplices of the Čech nerve $ N\mathcal{U}$ through a homotopy equivalence $N\mathcal{U}\to X$. We apply this to real tori $V/Λ$ to show th

Yoshiki Masuyama, Kohei Saijo, Francesco Paissan, Jiangyu Han

Speech separation and enhancement (SSE) has advanced remarkably and achieved promising results in controlled settings, such as a fixed number of speakers and a fixed array configuration. Towards a universal SSE system, single-channel systems have been extended to deal with a variable number of speakers (i.e., outputs). Meanwhile, multi-channel systems accomm

Pierre Guillot, Auguste Hoang Duc, Michel Koskas, Florian Méhats

We present GRAFHEN, a new cryptographic scheme which offers Fully Homomorphic Encryption without the need for bootstrapping (or in other words, without noise). Building on the work of Nuida and others, we achieve this using encodings in groups. The groups are represented on a machine using rewriting systems. In this way the subgroup membership problem, which

Marek Socha, Michał Marczyk, Aleksander Kempski, Michał Cogiel

GRAP-MOT is a new approach for solving the person MOT problem dedicated to videos of closed areas with overlapping multi-camera views, where person occlusion frequently occurs. Our novel graph-weighted solution updates a person's identification label online based on tracks and the person's characteristic features. To find the best solution, we deeply investi

Célestin Zimmerlin, Thomas Louail, Manuel Moussallam, Marc Barthelemy

When following a sequence - such as reading a text or tracking a user's activity - one can measure how the "dictionary" of distinct elements (types) grows with the number of observations (tokens). When this growth follows a power law, it is referred to as Heaps' law, a regularity often associated with Zipf's law and frequently used to characterize human disc

Rowan Batzofin, Pierre Cristofari, Kathrin Egberts

Young massive star clusters (YMSCs) can produce gamma rays in the very-high-energy (VHE, E>100 GeV) range and have been proposed as sources that can accelerate cosmic rays up to PeV energies. Observations with current instruments have lead to the detection of only a few YMSCs but future instruments should significantly increase this number. However, the deta

Yating Huang, Qijun Yang, Lintao Xiang, Hujun Yin

Accurate interpretation of histopathological images demands integration of information across spatial and semantic scales, from nuclear morphology and cellular textures to global tissue organization and disease-specific patterns. Although recent foundation models in pathology have shown strong capabilities in capturing global tissue context, their omission o

Paolo Bonicatto

A classical result in Differential Geometry states that the flows of two smooth vector fields commute if and only if their Lie Bracket vanishes. In this work, we extend this result to a more general setting where one of the vector fields is bounded and Lipschitz, while the other may be a singular vector-valued measure, i.e. a normal 1-current. This result is

Junseo Ko

In this paper, we investigate the conditions under which an odd nilpotent element in $\mathfrak{gl}(m|n)$ lies inside an $\mathfrak{osp}(1|2)$-subalgebra. In the case of the classical Lie algebra $\mathfrak{gl}_m$, every nilpotent element can be embedded into an $\mathfrak{sl}_2$-subalgebra, which is the result of the Jacobson-Morozov Theorem. In the case of

Liubov A. Markovich, Vladimir A. Orlov, Alexey N. Rubtsov, Vladimir I. Man'ko

Hybrid quantum systems that combine discrete-variable (DV) and continuous-variable (CV) architectures represent a promising direction in quantum information science. However, transferring concepts, information and states between such fundamentally different platforms entails both practical and theoretical challenges. The formalisms of these two universes dif

Malihe Heydari-Fard, Mohaddese Heydari-Fard

Exploring the influence of plasma on the light rays trajectories in the vicinity of black holes is significat since that astrophysical black holes are generally surrounded by a plasma medium. In this work, we analyze the null geodesics in the space-time of rotating hairy Horndeski black holes immersed in a plasma medium using the Hamilton-Jacobi method. By c

Cécile Marie Vincent, Sapna Ravindran, Alexis Michel Prevost, Léa-Laetitia Pontani

In tissues, cells in direct physical contact with each other can exchange ions or molecules via protein clusters called gap junctions that form channels across the membranes of adjacent cells. Here, we use a simplified biomimetic approach, coupled with theoretical modeling, to unravel the physical mechanisms controlling such transport. Tissues are mimicked w

Chenglong Wang, Yang Gan, Hang Zhou, Chi Hu

Recent advances in diffusion language models (DLMs) have presented a promising alternative to traditional autoregressive large language models (LLMs). However, DLMs still lag behind LLMs in reasoning performance, especially as the number of denoising steps decreases. Our analysis reveals that this shortcoming arises primarily from the independent generation

Pu Gao, Mikhail Isaev, Xavier Perez-Gimenez

We establish new couplings among several random graph and multigraph models related to the random regular graph $G(n,d)$, including the configuration model and unions of random perfect matchings. As a main result, we verify the Kim-Vusandwich conjecture for all large degrees $d=n-O(\log^4 n)$ and prove a weakened version for $d=O(\log^4 n)$, which are the on

Marvin Knöller, Jörg Nick

This work describes and analyzes the domain derivative for a time-dependent acoustic scattering problem. We study the nonlinear operator that maps a sound-soft scattering object to the solution of the time-dependent wave equation evaluated at a finite number of points away from the obstacle. The Fr\'echet derivative of this operator with respect to variation

Gabriele Bianchi, Federico Re, Oliver Fabio Piattella

We argue that the standard post-Newtonian expansion scheme used in General Relativity leaves room for time-space components $g_{ti}$ of the metric to be of the same order of the usual gravitational potential. We explore this possibility and find that such leading order contributions to $g_{ti}$ are related to the Coriolis field of Newton-Cartan gravity. We i

Domenico Palmisano, Giuseppe Palestra, Berardina Nadja De Carolis

As artificial intelligence continues to advance and becomes more integrated into sensitive areas like healthcare, education, and everyday life, it's crucial for these systems to be both resilient and robust. This paper shows how resilience is a fundamental characteristic of social robots, which, through it, ensure trust in the robot itself-an essential eleme

Emre Sahinoglu, Youbang Sun, Shahin Shahrampour

This work addresses the finite-time analysis of nonsmooth nonconvex stochastic optimization under Riemannian manifold constraints. We adapt the notion of Goldstein stationarity to the Riemannian setting as a performance metric for nonsmooth optimization on manifolds. We then propose a Riemannian Online to NonConvex (RO2NC) algorithm, for which we establish t

Ravinithesh Annapureddy, Alessandro Fornaroli, Massimo Fattori, Valeria Lacovara

This paper presents the co-design and design evaluation of Sbocciamo Torino civic tool, which helps understand and act upon the issues of youth deviance in the Italian city of Turin through multi-stakeholder collaboration and collaborative data analysis. Rooted in research through design and participatory design methodologies, the civic tool integrates a dat

Adriel O. Aquino, J. E. G. Silva

We study the late-time cosmological expansion of a modified teleparallel gravity model. This modified gravitational lagrangian yields a cosmological constant term along with power-law corrections to the Teleparallel Equivalent of General Relativity (TEGR) for small $λ$. By combining observational data from cosmic chronometers, Type Ia supernovae from the Pan

Stephen Overall, John Southworth

Detached eclipsing binary stars (dEBs) are a key source of data on fundamental stellar parameters. Within the light curve databases of survey missions such as Kepler and TESS are a wealth of new systems awaiting characterisation. We aim to improve the scalability of efforts to process these data by developing a Convolutional Neural Network (CNN) machine lear

Alexandre Tlili, Basile Gallet

We revisit the interaction of an initially uniform near-inertial wave (NIW) field with a steady background flow, with the goal of predicting the subsequent organization of the wave field. To wit, we introduce an exact analogy between the Young Ben Jelloul (YBJ) equation and the quantum dynamics of a charged particle in a steady electromagnetic field, whose p

Chaewoon Bae, Doyun Choi, Jaehyun Lee, Jaemin Yoo

Few-shot node classification on hypergraphs requires models that generalize from scarce labels while capturing high-order structures. Existing hypergraph neural networks (HNNs) effectively encode such structures but often suffer from overfitting and scalability issues due to complex, black-box architectures. In this work, we propose ZEN (Zero-Parameter Hyper

Ming Xie, Junqiu Yu, Qiaole Dong, Xiangyang Xue

Recent image-to-video (I2V) based video inpainting methods have made significant strides by leveraging single-image priors and modeling temporal consistency across masked frames. Nevertheless, these methods suffer from severe content degradation within video chunks. Furthermore, the absence of a robust frame alignment scheme compromises intra-chunk and inter

Sean McGregor, Victor Lu, Vassil Tashev, Armstrong Foundjem

Large language model (LLM) benchmarks inform LLM use decisions (e.g., "is this LLM safe to deploy for my use case and context?"). However, benchmarks may be rendered unreliable by various failure modes that impact benchmark bias, variance, coverage, or people's capacity to understand benchmark evidence. Using the National Institute of Standards and Technolog

Y. F. Wang, L. T. Yang, Q. Yue, K. J. Kang

We report a search for ultraheavy dark matter (UHDM) with the CDEX-10 experiment at the China Jinping Underground Laboratory. Using a Monte Carlo framework that incorporates Earth shielding effects, we simulated UHDM propagation and energy deposition in p-type point-contact germanium detectors. Analysis of 205.4 kg$\cdot$day exposure in the 0.16--4.16 keVee

K. G. Strassmeier, I. Ilyin, M. Steffen, S. A. Barnes

Aims. The Hyades cluster is key for the study of rotational, activity, and chemical evolution of solar-like low-mass stars. Here we present quantitative surface-activity information for a sequence of 21 Hyades dwarf stars. Conclusions. We conclude that the Rossby-number dependencies of the surface activity tracers A(Li), R(IRT), and B on our Hyades dwarf seq

Jules Gerard, Leandro Di Bella, Filip Huyghe, Marc Kochzius

Coral reef monitoring in the Western Indian Ocean is limited by the labor demands of underwater visual censuses. This work evaluates a YOLOv8-based deep learning pipeline for automating family-level fish identification from video transects collected in Kenya and Tanzania. A curated dataset of 24 families was tested under different configurations, providing t

Jorge Díez, Pablo Pérez-Núñez, Oscar Luaces, Beatriz Remeseiro

Explaining the output of a complex system, such as a Recommender System (RS), is becoming of utmost importance for both users and companies. In this paper we explore the idea that personalized explanations can be learned as recommendation themselves. There are plenty of online services where users can upload some photos, in addition to rating items. We assum