November 2025 arXiv papers — page 32

Irene Schimperna, Lea Bold, Johannes Köhler, Karl Worthmann

This paper derives conditions under which Model Predictive Control (MPC) with terminal conditions, using a data-driven surrogate model as a prediction model, asymptotically stabilizes the plant despite approximation errors. In particular, we prove recursive feasibility and asymptotic stability if a proportional error bound holds, where proportional means tha

Kostiantyn Drach, Jonguk Yang

We establish rigidity for a class of higher-degree complex polynomials with irrationally indifferent dynamics. Specifically, we consider non-renormalizable (in the sense of Douady and Hubbard) polynomials of degree $d\geqslant 2$ with a Siegel disk whose rotation number is of bounded type. We call such maps atomic Siegel polynomials of bounded type. Our main

Ziheng Guo, Tianxiang Wei, Zeyu Li, Lianghao Zhang

Overdraw is inevitable in large-scale scatterplots. Current scatterplot abstraction methods lose features in medium-to-low density regions. We propose a visual abstraction method designed to provide better feature preservation across arbitrary abstraction levels for large-scale scatterplots, particularly in medium-to-low density regions. The method consists

Mengqiu Huang, Yongquan Xue, Shuo Li, Fukun Liu

Tidal disruption events (TDEs), which occur when stars enter the tidal radii of supermassive black holes (SMBHs) and are subsequently torn apart by their tidal forces, represent intriguing phenomena that stimulate growing research interest and pose an increasing number of puzzles in the era of time-domain astronomy. Here we report an unusual X-ray transient,

M. Kaniselvan, Y. R. Jeon, M. Mladenović, M. Luisier

The power and energy consumption of resistive switching devices can be lowered by reducing their active layer dimensions. Efforts to push this low-energy switching property to its limits have led to the investigation of active regions made with two-dimensional layered materials (2DLM). Despite their small dimensions, 2DLM exhibit a rich variety of switching

Pascal Autissier, Jean-Philippe Furter, Egor Yasinsky

For any infinite field k and any positive integer r, we show constructively that the map sending each polynomial P $\in$ k[x] to its r-th iterate is dominant in various inductive limit topologies on the space of all polynomials.

ATLAS Collaboration

A search for final states characterised by at least one isolated high transverse-momentum photon, jets and large missing transverse momentum is presented. Such a final state might occur in gauge-mediated supersymmetric models where a pair of binos and higgsinos mix to form neutralinos, one of which decays into a photon plus a gravitino while the other decays

Vendulka Humlova

A new phenomenon, gluon saturation, is expected to emerge in quantum chromodynamics (QCD) at high energies, when gluon splitting and recombination processes reach a dynamic equilibrium. In heavy nuclei, this balance is expected to be achieved at lower energies than in protons, making lead-lead collisions at the LHC an ideal environment to probe the onset of

Caihong Zheng, Fan Zheng

Fermi's golden rule which describes the transition rates between two electronic levels under external stimulations is used ubiquitously in different fields of physics. The original Fermi's golden rule was derived from perturbative time-dependent Schr\"{o}dinger's equation without the direct contribution by decoherence effect. However, as a result of recent d

Shuhan Xia, Xuannan Liu, Xing Cui, Peipei Li

Recently, partial audio forgery has emerged as a new form of audio manipulation. Attackers selectively modify partial but semantically critical frames while preserving the overall perceptual authenticity, making such forgeries particularly difficult to detect. Existing methods focus on independently detecting whether a single frame is forged, lacking the hie

Daniel Berend, Shlomi Dolev, Sweta Kumari, Dhruv Mishra

Efficient cache management is critical for optimizing the system performance, and numerous caching mechanisms have been proposed, each exploring various insertion and eviction strategies. In this paper, we present AdaptiveClimb and its extension, DynamicAdaptiveClimb, two novel cache replacement policies that leverage lightweight, cache adaptation to outperf

Cedric Baijot, Maria Groyne, Michaël De Becker

Shock types of low-velocity molecular outflows are not always well constrained. Astrochemical comparisons are often made between low-velocity and high-velocity outflows, but without considering the question of the shock type. We investigated molecular abundances of post-shock regions to determine whether strong differences between non-irradiated C-type and J

Luca O. Trinchão, Luiz Peres, Eduardo S. Gonçalves, Miguel Nienstedt

We present a method for resolving spatial mode overlaps in coupled microresonators based on Kerr and thermal cross-phase modulation. Through a pump-probe setup, we measure experimental overlap in a three-ring resonator with good agreement with analytical theory. Our technique can be generalized for describing nonlinear interactions in more complex multi- and

Muhammed Yildirim, Ozcan Ozturk

The increasing demand for on-device intelligence in Edge AI and TinyML applications requires the efficient execution of modern Convolutional Neural Networks (CNNs). While lightweight architectures like MobileNetV2 employ Depthwise Separable Convolutions (DSC) to reduce computational complexity, their multi-stage design introduces a critical performance bottl

Aaron Hofer, Ingo Runkel

We extend the TFT construction of CFT correlators of [arXiv:hep-th/0204148] to so-called finite logarithmic CFTs for which the algebraic input data is no longer semisimple but still finite. More specifically, starting from the data of a chiral CFT given in the form of a not necessarily semisimple modular tensor category C we use a three dimensional topologic

Patrik Knopf, Anastasija Pešić, Dennis Trautwein

In this work, we study a phase-field model for curvature-driven pattern formation in biomembranes. The model is derived as a gradient flow of an energy functional that approximates the two-phase Canham--Helfrich energy. This leads to a Cahn--Hilliard-type equation with cross diffusion for the relative chemical concentration of one lipid phase, coupled to a f

Adisai Na-Thalang, Chanakan Wittayasakpan, Kritsadha Phatcharoen, Supakit Buakaw

This paper introduces the development of the first open conversational speech dataset for the Isan language, the most widely spoken regional dialect in Thailand. Unlike existing speech corpora that are primarily based on read or scripted speech, this dataset consists of natural speech, thereby capturing authentic linguistic phenomena such as colloquials, spo

Anthony Couthures, Gustave Bainier, Vineeth Satheeskumar Varma, Samson Lasaulce

This paper establishes a theoretical framework to describe the transition from consensus to stable clustering in multi-agent systems with nonlinear, cooperative interactions. We first establish a sharp threshold for consensus. For a broad class of non-decreasing, Lipschitz-continuous interactions, an explicit inequality linking the interaction's Lipschitz co

Huiyu Li, Nicholas Ayache, Hervé Delingette

With the rapid expansion of data lakes storing health data and hosting AI algorithms, a prominent concern arises: how safe is it to export machine learning models from these data lakes? In particular, deep network models, widely used for health data processing, encode information from their training dataset, potentially leading to the leakage of sensitive in

Mathieu Hoyrup

Given a language, which in this article is a set of strings of some fixed length, we study the problem of producing its elements by a procedure in which each position has its own local rule. We introduce a way of measuring how much communication is needed between positions. The communication structure is captured by a simplicial complex whose vertices are th

Erenay Karacan

Many optimally scaling quantum simulation algorithms employ controlled time evolution of the Hamiltonian, which is typically the major bottleneck for their efficient implementation. This work establishes a compression protocol for encoding the controlled time evolution operator of translationally invariant, local Hamiltonians into a quantum circuit. It achie

Ruofeng Feng, Jack R. C. King, Steven J. Lind

This paper presents a novel p-adaptive, high-order mesh-free framework for the accurate and efficient simulation of fluid flows in complex geometries. High-order differential operators are constructed locally for arbitrary node distributions using linear combinations of anisotropic basis functions, formulated to ensure the exact reproduction of polynomial fi

Timm-Jonas Bäumer, Johannes W. de Vries, Stephan Töpken, Richard C. Hendriks

To improve speech intelligibility in complex everyday situations, the human auditory system partially relies on Interaural Time Differences (ITDs) and Interaural Level Differences (ILDs). However, hearing impaired (HI) listeners often exhibit limited sensitivity to ITDs, resulting in decreased speech intelligibility performance. This study aimed to investiga

Michel Crouzeix

We improve previous estimates for matrices belonging to the quantum annulus or to the numerical annulus.

Kexin Wang, Xiaomeng Zhang, Xinyu Zhang

Recognizing that asset markets generally exhibit shared informational characteristics, we develop a portfolio strategy based on transfer learning that leverages cross-market information to enhance the investment performance in the market of interest by forward validation. Our strategy asymptotically identifies and utilizes the informative datasets, selective

Jonas Berx, Nguyen Van Thu, Joseph O. Indekeu

Nucleation and wetting transitions are studied in a three-component Bose-Einstein condensate mixture within Gross-Pitaevskii theory. For special cases of intermediate segregation between components 1 and 2, the nucleation phase transition of a surfactant film of component 3 is obtained by exact solution. Additional exact results for the nucleation transition

Svyatoslav Covanov, Cedric Pradalier

This work extends a previous study that introduced an algorithm for state estimation on manifolds within the framework of the Kalman filter. Its objective is to address the limitations of the earlier approach. The reversible Kalman filter was designed to provide a methodology for evaluating the accuracy of existing Kalman filter variants with arbitrary preci

Jiayun Li, Yilin Mo

This paper presents a data-driven model for Linear Time-Invariant (LTI) stochastic systems by sampling from the conditional probability distribution of future outputs given past input-outputs and future inputs. It operates in a fully behavioral manner, relying solely on the current trajectory and pre-collected input-output data, without requiring explicit id

Steven Wang, Kyle Hunt, Shaojie Tang, Kenneth Joseph

There is ongoing debate about whether large language models (LLMs) can serve as substitutes for human participants in survey and experimental research. While recent work in fields such as marketing and psychology has explored the potential of LLM-based simulation, a growing body of evidence cautions against this practice: LLMs often fail to align with real h

Kecheng Chen, Ziru Liu, Xijia Tao, Hui Liu

Diffusion Language Models (DLMs) have recently achieved significant success due to their any-order generation capabilities. However, existing inference methods typically rely on local, immediate-step metrics such as confidence or entropy which inherently lack a more reliable perspective. This limitation frequently leads to inconsistent sampling trajectories

Chetan Gupta, Raghunath Tewari, Vimal Raj Sharma

We show that given an embedding of an $O(\log n)$ genus bipartite graph, one can construct an edge weight function in logarithmic space, with respect to which the minimum weight perfect matching in the graph is unique, if one exists. As a consequence, we obtain that deciding whether such a graph has a perfect matching or not is in SPL. In 1999, Reinhardt, Al

Fangming Shi, Li Li, Kejiang Chen, Guorui Feng

Low-Rank Adaptation (LoRA) offers an efficient paradigm for customizing diffusion models, but its ease of redistribution raises concerns over unauthorized use and the generation of untraceable content. Existing watermarking techniques either target base models or verify LoRA modules themselves, yet they fail to propagate watermarks to generated images, leavi

Davide Nadalini, Manuele Rusci, Elia Cereda, Luca Benini

Monocular depth estimation (MDE) plays a crucial role in enabling spatially-aware applications in Ultra-low-power (ULP) Internet-of-Things (IoT) platforms. However, the limited number of parameters of Deep Neural Networks for the MDE task, designed for IoT nodes, results in severe accuracy drops when the sensor data observed in the field shifts significantly

Quan-Hoang Vuong, Thi Mai Anh Tran, Ni Putu Wulan Purnama Sari, Fatemeh Kianfar

The Anthropocene is characterized by escalating ecological crises rooted not only in technological and economic systems but also in deeply ingrained anthropocentric worldviews that shape human-nature relationships. As digital environments increasingly mediate these interactions, video games provide novel contexts for examining the psychological mechanisms un

Umang Agarwal, Rudraksh Sangore, Sumit Laddha

We present a comprehensive comparative study of three generative modeling paradigms: Denoising Diffusion Probabilistic Models (DDPM), Conditional Flow Matching (CFM), and MeanFlow. While DDPM and CFM require iterative sampling, MeanFlow enables direct one-step generation by modeling the average velocity over time intervals. We implement all three methods usi

Yifan Sun, Zhi Li, Tetsuya Imamura, Yuji Ohishi

Thermoelectrics (TEs) are promising candidates for energy harvesting with performance quantified by figure of merit, $ZT$. To accelerate the discovery of high-$ZT$ materials, efforts have focused on identifying compounds with low thermal conductivity $\kappa$. Using a curated dataset of 71,913 entries, we show that high-$ZT$ materials reside not only in the

Bowen Zhu, Tao Zhu, Yazhi Pi, Chunyang Ma

Photonics-assisted millimeter-wave bands and terahertz signal generation offer significant advantages over traditional electronic methods by leveraging the inherent benefits of optical components, including broad bandwidth, low power consumption, and minimal insertion loss. This work utilizes a silicon photonic chip in conjunction with a reconfigurable optic

Jithin VG, Ditto PS

The proliferation of GPU-accelerated workloads, particularly in artificial intelligence and large language model (LLM) inference, has created unprecedented demand for efficient GPU resource sharing in cloud and container environments. While NVIDIA's Multi-Instance GPU (MIG) technology provides hardware-level isolation, its availability is limited to high-end

Rubén Fernández-Farelo, Jorge Paz-Ruza, Bertha Guijarro-Berdiñas, Amparo Alonso-Betanzos

Gene prioritization (identifying genes potentially associated with a biological process) is increasingly tackled with Artificial Intelligence. However, existing methods struggle with the high dimensionality and incomplete labelling of biomedical data. This work proposes a more robust and efficient pipeline that leverages Fast-mRMR Feature Selection to retain

Yee-Jian Tan, Andreas Nuyts, Dominique Devriese

Some advantages of Cubical Type Theory, as implemented by Cubical Agda, over intensional Martin-L\"of Type Theory include Quotient Inductive Types (QITs), which exist as instances of Higher Inductive Types, and functional extensionality, which is provable in Cubical Type Theory. However, HoTT features an infinite hierarchy of equalities that may become unwie

Lucas Thil, Jesse Read, Rim Kaddah, Guillaume Doquet

Accurate remaining useful life (RUL) prediction hinges on the quality of health indicators (HIs), yet existing methods often fail to disentangle complex degradation mechanisms in multi-sensor systems or quantify uncertainty in HI reliability. This paper introduces a novel framework for HI construction, advancing three key contributions. First, we adapt Recon

Sergey Mirzoyan

Building on our previous work, we apply a U-Net Variational Autoencoder (VAE) framework to denoise galaxy images from the James Webb Space Telescope (JWST) and enhance morphological classification. This study focuses on galaxies observed up to redshift approximately at 8, capturing them at early evolutionary stages where their faintness and structural comple

Francisco J. G. de Oliveira, Martin Bourhis, Zahra Sharif Khodaei, Oliver R. H. Buxton

Wind turbines operating within wind farms experience complex aerodynamic loading arising from the interplay between wake-induced velocity deficits, enhanced turbulence, and varying operational conditions. Understanding the relationship between the blade's structural response to the different operating regimes and flow structures generated in the turbine's wa

A. Chilingarian, B. Sargsyan, L. Kozliner, T. Karapetyan

Ground Level Enhancement (GLE) events provide rare opportunities to study high-energy solar particle acceleration through direct detection of secondary radiation at ground level. On November 11, 2025, the Aragats Solar Neutron Telescope (ASNT) recorded a statistically significant increase in high-energy neutron and muon fluxes associated with an X5.1 flare a

Hao-Peng Yan, Zeng-Yi Zhang, Xiao-Jun Yue, Xiang-Qian Li

We present a unified investigation of black hole shadows, quasinormal modes (QNMs), and greybody factors (GBFs) for a static, spherically symmetric black hole within a composite environment of a modified Chaplygin-like dark fluid (MCDF) and a cloud of strings (CoS). We examine the structure of critical photon orbits and the corresponding optical appearance u

Fuyuki Tokuda, Akira Seino, Akinari Kobayashi, Kai Tang

In this paper, we propose a method to align and place a fabric piece on top of another using a dual-arm manipulator and a grayscale camera, so that their surface textures are accurately matched. We propose a novel control scheme that combines Transformer-driven visual servoing with dualarm impedance control. This approach enables the system to simultaneously

Baoli Sun, Yihan Wang, Xinzhu Ma, Zhihui Wang

Fine-grained action recognition (FGAR) aims to identify subtle and distinctive differences among fine-grained action categories. However, current recognition methods often capture coarse-grained motion patterns but struggle to identify subtle details in local regions evolving over time. In this work, we introduce the Action-Region Tracking (ART) framework, a

Yingnuo Qiu, Renhong Gao, Chuntao Li, Yixuan Yang

High-performance integrated broadband coherent light sources are essential for advanced applications in high-bandwidth data processing and chip-scale metrology, yet remain challenging. In this study, we demonstrate a monolithic Z-cut lithium niobate on insulator (LNOI) microring platform that enables simultaneous generation of tunable multi-chromatic microla

Abdelhaq El Khalfi, Hicham Laarabi, Suat Koç

Let $R$ be a commutative ring with $1\neq 0$ and $n$ be a fixed positive integer. A proper ideal $I$ of $R$ is said to be an \textit{$n$-OA ideal} if whenever $a_1a_2\cdots a_{n+1}\in I$ for some nonunits $a_1,a_2,\ldots,a_{n+1}\in R$, then $a_1a_2\cdots a_n\in I$ or $a_{n+1}\in I$. A commutative ring $R$ is said to be an \textit{$n$-OAF ring} if every prope

Alessia andò, Simone De Reggi, Francesca Scarabel, Rossana Vermiglio

We considered a model for an infectious disease outbreak, when the depletion of susceptible individuals is negligible, and assumed that individuals adapt their behavior according to the information they receive about new cases. In line with the information index approach, we supposed that individuals react to past information according to a memory kernel tha

Wei Qu, Siu-Long Lei, Sean Y. Hon, Yuan-Yuan Huang

A Crank-Nicolson finite volume approximation for three-dimensional conservative space-fractional diffusion equation results in large and dense three-level Toeplitz discrete linear systems. Preconditioned Krylov subspace methods with sine transform-based preconditioners are developed to solve these systems, including the preconditioned conjugate gradient (PCG

Paolo Buono, Mary Cerullo, Stefano Cirillo, Giuseppe Desolda

AI-assisted tools support developers in performing cognitively demanding tasks such as bug detection and code readability assessment. Despite the advancements in the technical characteristics of these tools, little is known about how developers mentally model them and how mismatches affect trust, control, and adoption. We conducted six co-design workshops wi

Zhang Xu, Wei Zhao

This paper provides a unified approach to characterize the set of all feasible signals subject to privacy constraints. The Blackwell frontier of feasible signals can be decomposed into minimum informative signals achieving the Blackwell frontier of privacy variables, and conditionally privacy-preserving signals. A complete characterization of the minimum inf

Selene Cerna, Sara Si-Moussi, Wilfried Thuiller, Hadrien Hendrikx

Foundation models have demonstrated a remarkable ability to learn rich, transferable representations across diverse modalities such as images, text, and audio. In modern machine learning pipelines, these representations often replace raw data as the primary input for downstream tasks. In this paper, we address the challenge of adapting a pre-trained foundati

Hanyang Li, Yuheng Jia, Hui Liu, Junhui Hou

Recent deep clustering models have produced impressive clustering performance. However, a common issue with existing methods is the disparity between global and local feature structures. While local structures typically show strong consistency and compactness within class samples, global features often present intertwined boundaries and poorly separated clus

Hui Lu, Yi Yu, Yiming Yang, Chenyu Yi

Vision-Language-Action (VLA) models are vulnerable to adversarial attacks, yet universal and transferable attacks remain underexplored, as most existing patches overfit to a single model and fail in black-box settings. To address this gap, we present a systematic study of universal, transferable adversarial patches against VLA-driven robots under unknown arc

Yutao Tang, Cheng Zhao, Gaurav Mittal, Rohith Kukkala

Recent advances in 3D vision-language models (VLMs) highlight a strong potential for 3D scene understanding and reasoning. However, effectively tokenizing 3D scenes into holistic scene tokens, and leveraging these tokens across diverse 3D understanding tasks, remain highly challenging. We present NDTokenizer3D, a generalist 3D VLM that performs a wide range

Tamara Mishenina, Teresa Kurtukian-Nieto, Tatiana Gorbaneva, Anish M. Amarsi

The stellar origin of the elements molybdenum (Mo, Z=42) and ruthenium (Ru, Z=44) is still a matter of debate. Studying their abundances provides valuable insights into nucleosynthesis processes and the broader evolution of neutron-capture elements. We presented new observations of Mo and Ru, together with nearby neutron-capture elements strontium (Sr) and z

Ruican Xia, Hailong Pei

Relative State Estimation perform mutually localization between two mobile agents undergoing six-degree-of-freedom motion. Based on the principle of circular motion, the estimation accuracy is sensitive to nonlinear rotations of the reference platform, particularly under large inter-platform distances. This phenomenon is even obvious for linearized kinematic

Pei Zhou, Wanting Yao, Qian Luo, Xunzhe Zhou

Goal-conditioned policy learning for robotic manipulation presents significant challenges in maintaining performance across diverse objectives and environments. We introduce Hyper-GoalNet, a framework that generates task-specific policy network parameters from goal specifications using hypernetworks. Unlike conventional methods that simply condition fixed ne

Zheng Li, Yibing Song, Xin Zhang, Lei Luo

Existing prompt learning methods, which are built upon CLIP models, leverage textual tokens as anchors to guide the learnable soft tokens. This guidance improves CLIP generalizations. However, these anchors-static in both value and position-lack cross-task and stage-adaptive flexibility. To address this limitation, we propose AnchorOPT, a dynamic anchor-base

Kijeong Yim, Soo-Chang Rey

We present a spatially resolved analysis of the molecular star formation law (SFL) and gravitational instability in a sample of nearby dwarf galaxies (NGC 1035, NGC 4310, NGC 4451, NGC 4701, NGC 5692, and NGC 6106), using high-resolution $^{12}$CO ($J=1\rightarrow0$) data from the Atacama Large Millimeter/submillimeter Array. We estimate the star formation r

Avraham Yair Negozio

We propose a novel protocol for aligning artificial superintelligence (ASI) based on mutual verification among multiple isolated systems that self-modify to achieve alignment. The protocol operates by containing multiple diverse artificial superintelligences in strict isolation ("boxes"), with humans remaining entirely outside the system. Each superintellige

Loris Di Cairano

Entanglement for pure bipartite states is most commonly quantified in a state-by-state manner to each pure state of a bipartite system a scalar quantity, such as the von Neumann entropy of a reduced density matrix. This provides a precise local characterization of how entangled a given state is. At the same time, this local description naturally invites a se

Joonhyung Park, Hyeongwon Jang, Joowon Kim, Eunho Yang

Recent visual autoregressive (AR) models have shown promising capabilities in text-to-image generation, operating in a manner similar to large language models. While test-time computation scaling has brought remarkable success in enabling reasoning-enhanced outputs for challenging natural language tasks, its adaptation to visual AR models remains unexplored

Thomas Hajnik, Nicholas A. Walton, Giuseppe D'Ago, Piercarlo Bonifacio

Current-day multi-object spectroscopic surveys are often limited in their ability to observe bright stars due to their low surface densities, resulting in increased observational overheads and reduced efficiency. Addressing this, we have developed a novel observing mode for WEAVE (William Herschel Telescope Enhanced Area Velocity Explorer) that enables effic

David Díaz-Guerra, Angel Rincon, Diego Rubiera-Garcia

We consider the optical appearance of a non-singular, spherically symmetric black hole from Eddington-inspired Born-Infeld gravity coupled to anisotropic fluids. Such a black hole has a single (external) horizon located very near the Schwarzschild radius, $r_h=2M$, while its surface of unstable bound geodesics (photon sphere) is located at a moderately short

Avik Kumar Das, Pankaj Kushwaha, Veeresh Singh, Sandeep Kumar Mondal

We present a long-term broad-band temporal and spectral study of a TeV BL Lac source TXS 0518+211 by analyzing nearly 16 years (MJD 54682 -- 60670) of simultaneous optical, UV and X-ray light curves from \textit{Swift}-XRT/UVOT and gamma-ray light curves from \textit{Fermi}-LAT. Based on the availability of simultaneous multi-wavelength data and considering

Dogukan Aksu, Jesus Martinez del Rincon, Ihsen Alouani

Spiking neural networks (SNNs) have emerged as prominent candidates for embedded and edge AI. Their inherent low power consumption makes them far more efficient than conventional ANNs in scenarios where energy budgets are tightly constrained. In parallel, federated learning (FL) has become the prevailing training paradigm in such settings, enabling on-device

Shuhan Xia, Jing Dai, Hui Ouyang, Yadong Shang

Diffusion models exhibit notable fragility when faced with adversarial prompts, and strengthening attack capabilities is crucial for uncovering such vulnerabilities and building more robust generative systems. Existing works often rely on white-box access to model gradients or hand-crafted prompt engineering, which is infeasible in real-world deployments due

O. R. Skorikov, S. V. Pilipenko, M. V. Tkachev

We consider cosmological models with a power spectrum of perturbations featuring an enhanced amplitude on dwarf galaxy scales (with a "bump" or a "tilt"). Early formation of a large number of galaxies in such models, compared to the standard spectrum, can shift the epoch of reionization to higher redshifts compared to observations. We show that for moderate

Pratik Chattopadhyay, Divyesh N. Solanki

We study the tree-level scattering of massless scalars followed by an emission of a soft graviton in the small compact region inside the static patch in de Sitter space. We derive in the small cosmological constant limit the perturbative corrections to the Weinberg soft graviton theorem. Exploiting the remarkable relationship between asymptotic symmetries an

Qi Yan

In this paper, we study the motion by mean curvature of curves in the plane perturbed by scale-dependent noise. We first introduce a so-called scale-dependent noise from the physics background to the curve shortening flow. To be more precise, the scale-dependent noise defined on a curve is a noise whose intensity is proportional to the length of the curve. T

Paulo Vitor Ribeiro Plácido, Danilo da Silva Borges, Willian Righi Assis, Erick de Moraes Franklin

We investigate the possible outcomes of a subaqueous barchan moving over a crater-like depression in the bed. For that, we carried out experiments where we varied the dune size, crater and grain diameters, and flow velocities. We found that subaqueous barchans can be blocked, destroyed, or pass over craters, with transitional situations, and that strong inst

Mattia Brescia, Bernardo Giuseppe Di Siena, Ernesto Ingross, Marco Trombetti

In 1973, Jim Wiegold introduced the concept of pseudocentre P(G) of a group G as the intersection of the normal closures of the centralizers of its elements. He proved that the pseudocentre of a non-trivial finite group is always non-trivial, giving a new variable on which one can use induction in finite group theory. In the same paper, Wiegold states that n

Y. M. Cho

The standard model has the electroweak monopole which has the magnetic charge $4\pi/e$, as a hybrid between the Dirac and 'tHooft-Polyakov monopoles. We argue that it may have new type of monopoles, in particular the neutral monopole (``the Z monopole") which is electromagnetically neutral but has the neutral magnetic charge $4\pi/\be$, where $\be$ is the ne

Xingchen Shen, Jiongzhi Zheng, Michael Marek Koza, Petr Levinsky

Ultralow glass-like lattice thermal conductivity in crystalline materials is crucial for enhancing energy conversion efficiency in thermoelectrics and thermal insulators. We introduce a universal descriptor for thermal conductivity that relies only on the atomic number in the primitive cell and the sound velocity, enabling fast and scalable materials screeni

Lennart Gehrmann, Xavier Guitart, Marc Masdeu

We develop the tools required to effectively evaluate the Bianchi rigid meromorphic cocycles introduced by Darmon-Gehrmann-Lipnowski at big ATR points, and use them to obtain the first numerical verification of the conjectured algebraicity of these special values. Moreover, our computations suggest that these special values exhibit behaviour analogous to tha

Da Zhang, Bingyu Li, Zhiyuan Zhao, Yanhan Zhang

Time series classification (TSC) is crucial in numerous real-world applications, such as environmental monitoring, medical diagnosis, and posture recognition. TSC tasks require models to effectively capture discriminative information for accurate class identification. Although deep learning architectures excel at capturing temporal dependencies, they often s

Kaiyan Xiao, Zihan Xu, Cheng Zhe, Chengju Liu

Humanoid robots, with their human-like morphology, hold great potential for industrial applications. However, existing loco-manipulation methods primarily focus on dexterous manipulation, falling short of the combined requirements for dexterity and proactive force interaction in high-load industrial scenarios. To bridge this gap, we propose a reinforcement l

Xianxian Cao, Zhen Guan, Junjun Wang

In this paper, a fully implicit Crank-Nicolson discontinuous Galerkin method is proposed for solving the Ginzburg-Landau equation. By leveraging a novel analytical technique, we rigorously establish the unique solvability of the constructed numerical scheme, as well as its unconditionally optimal error estimates under both the \(L^2\)-norm and the energy nor

Tchougoune Moustapha Mai, Mohamed Hajajji, Catherine Azzaro-Pantel, Maude Chin Choi

A multi-objective framework for hydrogen supply chain (HSC) planning is developed for island contexts, incorporating Mixed-Integer Linear Programming (MILP) over multiple time periods. The model minimizes total system cost, greenhouse gas (GHG) emissions, and a risk index criteria. The case study of Corsica is considered, using Geographic Information Systems

B. Allés, O. Borisenko, V. Chelnokov, A. Papa

We explore the possibility to use the Fredenhagen-Marcu operator as a candidate order parameter of the deconfinement phase transition in gauge matter systems at finite temperature. Concretely, we compute by numerical simulations this operator in the (2+1)-dimensional Z(2) lattice gauge theory (LGT) with Z(2) gauge fields coupled to Z(2)-valued Higgs fields.

John E. Beetar, Jen-Hao Ou, Yuki Kobayashi, Stephen R. Leone

The reported ''dissociation times'' for the Br$_{2}$ C ($^{1}\Pi_{u}$ $1_{u}$) state by various measurement methods differ widely across the literature (30 to 340 fs). We consider this issue by investigating attosecond extreme ultraviolet (XUV) transient absorption spectroscopy at the Br M4,5 3d$_{3/2,5/2}$ edges (66 to 80 eV), tracking core-to-valence (3d t

Junhua Shi, Qingyun Sun, Haonan Yuan, Xingcheng Fu

We present Graph Foundation Models (GFMs) which have made significant progress in various tasks, but their robustness against domain noise, structural perturbations, and adversarial attacks remains underexplored. A key limitation is the insufficient modeling of hierarchical structural semantics, which are crucial for generalization. In this paper, we propose

Haokun Zhao, Yingzhe Bai, Qingyang Xu, Lixin Zhou

Accurate disease detection is of paramount importance for effective medical treatment and patient care. However, the process of disease detection is often associated with extensive medical testing and considerable costs, making it impractical to perform all possible medical tests on a patient to diagnose or predict hundreds or thousands of diseases. In this

Sayaka Ishibashi, Kou Tamura, Ayana Goma, Kenta Yamamoto

Older adults often experience increased difficulty in decision making due to age-related declines particularly in contexts that require information search or the generation of alternatives from memory. This study examined whether using generative AI for information search enhances choice satisfaction and reduces choice difficulty among older adults. A total

Hua Sun, Hui-Xiang Chen, Libin Li, Yinhuo Zhang

Let $\Bbbk$ be an algebraically closed field of characteristic $0$. In this paper, we study the Grothendieck ring $G_0(D(H_\mathcal{D}))$ and the projective class ring $r_p(D(H_\mathcal{D}))$ of the Drinfeld double $D(H_{\mathcal{D}})$ of the rank one pointed Hopf algebra $H_{\mathcal{D}}$. We analyze the tensor products of simple modules with simple modules

Bhaskar Ray Chaudhury, Christian Kroer, Ruta Mehta, Tianlong Nan

In this paper, we initiate the study of t\^atonnement dynamics in markets with chores. T\^atonnement is a fundamental market dynamics, capturing how prices evolve when they are adjusted in proportion of their excess demand. While its convergence to a competitive equilibrium (CE) is well understood in goods markets for broad classes of utilities, no analogous

Xu Hu, Yiyang Feng, Junran Peng, Jiawei He

The development of embodied agents for complex commercial environments is hindered by a critical gap in existing robotics datasets and benchmarks, which primarily focus on household or tabletop settings with short-horizon tasks. To address this limitation, we introduce MarketGen, a scalable simulation platform with automatic scene generation for complex supe

Wu Sai, Xia Ruichen, Yang Dingyu, Wang Rui

The increasing demand for deep neural inference within database environments has driven the emergence of AI-native DBMSs. However, existing solutions either rely on model-centric designs requiring developers to manually select, configure, and maintain models, resulting in high development overhead, or adopt task-centric AutoML approaches with high computatio

Emily R. Korfanty, Jan Mazáč

We review the diffraction theory for plane waves and establish its connection to the diffraction of Besicovitch almost periodic functions, extending the theory to an unbounded setting and providing explicit formulas. Then, we give an alternative proof that the diffraction of a spherical wave in $\mathbb{R}^d$ is a single sphere, which was recently shown in \

Taejun Kim, Youngbo Aram Shim, Youngin Kim, Sunbum Kim

The paradigm of bare-hand interaction has become increasingly prevalent in Augmented Reality (AR) and Virtual Reality (VR) environments, propelled by advancements in hand tracking technology. However, a significant challenge arises in delivering haptic feedback to users' hands, due to the necessity for the hands to remain bare. In response to this challenge,

Hui Liang, Zhihui Wu, Runqi Yuan, Guobin Zhang

In space-air-ground integrated networks (SAGIN)-enabled IoT networks, secure access has become a significant challenge due to the increasing risks of eavesdropping attacks. To address these threats to data confidentiality, this paper proposes a Digital Twin (DT)-driven secure access strategy. The strategy leverages a virtual replica of the physical SAGIN env

Gonzalo Mateo-Garcia, Anna Allen, Itziar Irakulis-Loitxate, Manuel Montesino-San Martin

Methane is a potent greenhouse gas, responsible for roughly 30% of warming since pre-industrial times. A small number of large point sources account for a disproportionate share of emissions, creating an opportunity for substantial reductions by targeting relatively few sites. Detection and attribution of large emissions at scale for notification to asset ow

Takashi Goda, Roswitha Hofer, Kosuke Suzuki

In this short article, we prove that the Halton sequence, one of the most well-known low-discrepancy sequences, is not quasi-uniform in any dimension $d \ge 2$ with any pairwise relatively prime bases. We further disprove the quasi-uniformity of some Halton-type sequences, including the $p$-dimensional Faure sequence in base $p$, $p \in \mathbb{P}$, which pr

Radu A. Talmazan, Christophe Chipot

As computational chemistry methods evolve, dynamic effects have been increasingly recognized to govern chemical reaction pathways in both organic and inorganic systems. Here, we introduce a committor-based workflow that integrates a path-committor-consistent artificial neural network (PCCANN) with an iteratively trained hybrid-DFT-level message passing atomi

M. Alecci, P. Jiménez, J. Samhi, T. Bissyandé

While mobile app evolution has been widely studied, geographical variation in app behavior remains largely unexplored. This paper presents a large-scale study of location-based Android app differentiation, uncovering two important and underexamined phenomena with security and fairness implications. First, we introduce GeoTwins: apps that are functionally sim

Shichu Sun, Yichen Zhang, Haolin Song, Zonghao Guo

Visual encoding followed by token condensing has become the standard architectural paradigm in multi-modal large language models (MLLMs). Many recent MLLMs increasingly favor global native- resolution visual encoding over slice-based methods. To investigate this trend, we systematically compare their behavior on vision-language understanding and attention pa

Guoming Huang, Qingyi Zhou, Dianjing Liu, Shuai Zhang

Non-contact manipulation has emerged as a transformative approach across various industrial fields. However, current flexible 2D and 3D non-contact manipulation techniques are often limited to microscopic scales, typically controlling objects in the milligram range. In this paper, we present a magnetic levitation system, termed Maglev-Pentabot, designed to a