October 2025 arXiv papers — page 141

Anne Weber, Job Feldbrugge, Emilio Pisanty

Light-matter interactions within the strong-field regime, where intense laser fields can ionise a target via tunnelling, give rise to fascinating phenomena such as the generation of high-order harmonic radiation (HHG). On the atomic scale, these strong-field processes are described in terms of highly-oscillatory time integrals which are often approximated us

Christos Tatakis

We give a necessary and sufficient graph-theoretic characterization of toric ideals of graphs that are unimodular. As a direct consequence, we provide the structure of unimodular graphs by proving that the incidence matrix of a graph $G$ is unimodular if and only if any two odd cycles of $G$ intersect.

Zylan Benjert, Kostas Lakis, Johannes Lengler, Raghu Raman Ravi

We prove that the diameter of threshold (zero temperature) Geometric Inhomogeneous Random Graphs (GIRG) is $\Theta(\log n)$. This has strong implications for the runtime of many distributed protocols on those graphs, which often have runtimes bounded as a function of the diameter. The GIRG model exhibits many properties empirically found in real-world networ

Jasmin Freudenberg, Kai Hahn, Christian Weber, Madjid Fathi

The increasing popularity of portable ECG systems and the growing demand for privacy-compliant, energy-efficient real-time analysis require new approaches to signal processing at the point of data acquisition. In this context, the edge domain is acquiring increasing importance, as it not only reduces latency times, but also enables an increased level of data

Malte Gerhold, Marcel Scherer, Orr Shalit

For a tuple $T$ of Hilbert space operators, the 'commuting dilation constant' is the smallest number $c$ such that the operators of $T$ are a simultaneous compression of commuting normal operators of norm at most $c$. We present numerical experiments giving a strong indication that the commuting dilation constant of a pair of independent random $N{\times}N$

Zhanle Zhao, Son Dinh-Van, Yuen Kwan Mo, Siddartha Khastgir

Connected braking can reduce fatal collisions in connected and autonomous vehicles (CAVs) by using reliable, low-latency 5G New Radio (NR) links, especially NR Sidelink Vehicle-to-Everything (V2X). In rural areas, road side units are sparse and power-constrained, so energy efficiency must be considered alongside safety. This paper studies how three communica

Changchi Huang, Jigen Peng, Yuchao Tang

This paper introduces a new definition of $\alpha$-monotone operators in real 2-uniformly convex and smooth Banach spaces. Based on this new definition, we establish several novel structural and analytical properties of such operators, which not only extend classical results from Hilbert spaces but also reveal new insights into the geometry of Banach spaces.

David Björkstrand, Tiesheng Wang, Lars Bretzner, Josephine Sullivan

Recent work has explored a range of model families for human motion generation, including Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), and diffusion-based models. Despite their differences, many methods rely on over-parameterized input features and auxiliary losses to improve empirical results. These strategies should not be stric

Adrián Lillo, Mercedes Rosas, Stefan Trandafir

A record of a rooted Cayley tree is a node whose label is the largest along the unique path to the root. In this work, we find elegant functional equations relating the generating functions for records of rooted Cayley trees and for records of forests of rooted trees with the Cayley tree function, and explore the consequences of our results.

Gavin A. L. Coleman, Thomas J. Haworth, Ilane Schroetter, Olivier Berné

We cannot understand planet formation without understanding disc evolutionary processes. However, there is currently ambiguity about how protoplanetary discs transport angular momentum (e.g. via viscosity or winds) and the relative contributions and interplay of different dispersal mechanisms. A key difficulty is that for any given system only a handful of d

Rustam Steingart

Let $K/E/\mathbb{Q}_p$ be a tower of finite extensions with $E$ Galois. We relate the category of $G_K$-equivariant vector bundles on the Fargues--Fontaine curve with coefficients in $E$ with $E$-$G_K$-$B$-pairs and describe crystalline and de Rham objects in explicit terms. When $E$ is a proper extension, we give a new description of the category in terms o

Domenico Lippolis

In the realm of spatiotemporal chaos, unstable periodic orbits play a major role in understanding the dynamics. Their stability changes and bifurcations in general are thus of central interest. Here, coupled map lattice discretizations of nonlinear partial differential equations, exhibiting a variety of behaviors depending on the coupling strength, are consi

Fabrizio Cinque, Enzo Orsingher

We study two different types of vector point processes with interacting components, introducing a migration-type effect. The first case concerns two groups which modify their states with rate functions depending on time only. This yields a representation of the vector process in terms of independent non-homogeneous Skellam processes. In the general case, the

Jae Sik Jin

Phonon transport near nanoscale hotspots (NHs) critically determines heat dissipation in advanced electronic devices. The prevailing understanding is that the enhanced thermal resistance (TR) observed in NHs originates from long mean free path (MFP) phonons, whose MFPs are much larger than the hotspot size, thereby limiting their ability to recognize hotspot

Giorgio Metafune, Luigi Negro, Chiara Spina

We prove uniqueness results and Harnack inequality for Bessel operators \begin{align*} %\label{def L transf alpha} D_t-\Delta_{x} -2a\cdot\nabla_xD_y- D_{yy}- \frac cy D_y % \nonumber \\[1ex]&=y^{\alpha}\sum_{i,j=1}^{N+1}a_{ij}D_{ij}+y^{\alpha-1}\left(v,\nabla\right)-by^{\alpha-2}. \end{align*} in the strip $[0,T]\times \mathbb{R}^{N+1}_+=\{0 \leq t \leq T,

Muxing Huang, Zibin Chen, Weiliang Xu, Zilan Li

Object compliance perception enables the identification of soft materials, supporting tasks such as fruit detection and assisted medical palpation. Compliance perception requires sensing an object's deformation and contact forces. Existing vision-based tactile sensing for compliance perception usually depends only on force or deformation. However, deform

Sihui Zhong, Valery M. Nakariakov, Dmitrii Y. Kolotkov

A coronal loop of 290~Mm length, observed at 171~\AA\ with SDO/AIA on February 6th 2024 near AR 13571, is found to oscillate with two significantly different oscillation periods, $48.8 \pm 6.1$~min and $4.8\pm 0.3$~min. The oscillations occur in the time intervals without detected flares or eruptions. Simultaneously, near the Northern footpoint of the oscill

Kolja Kypke, Peter Ashwin, Peter Ditlevsen

Regions of fast-flowing ice in ice sheets, known as ice streams, have been theorized to be able to exhibit build-up/surge oscillatory variability due to thermomechanical coupling at the base of the ice. A simple model of three coupled ice streams is constructed to replicate the spatial configuration of a single ice stream being bisected into two termini. The

Jiayi Kong, Chen Zong, Junkai Deng, Xuhui Chen

Unsigned Distance Fields (UDFs) provide a flexible representation for 3D shapes with arbitrary topology, including open and closed surfaces, orientable and non-orientable geometries, and non-manifold structures. While recent neural approaches have shown promise in learning UDFs, they often suffer from numerical instability, high computational cost, and limit

Ahmed Ben Yahmed, Hafedh El Ferchichi, Marc Abeille, Vianney Perchet

We examine a multi-armed bandit problem with contextual information, where the objective is to ensure that each arm receives a minimum aggregated reward across contexts while simultaneously maximizing the total cumulative reward. This framework captures a broad class of real-world applications where fair revenue allocation is critical and contextual variatio

Brian Lins

Topical maps are a nonlinear generalization of nonnegative matrices acting on the interior of the standard cone $\mathbb{R}^n_{\ge 0}$. Several analogues of irreducibility have been defined for topical maps, and all are sufficient to guarantee the existence of entrywise positive eigenvectors. In this note, we organize several of these notions, showing which

Sebastian Banert, Christoph Brauer, Dirk Lorenz, Lionel Tondji

This article addresses the challenge of learning effective regularizers for linear inverse problems. We analyze and compare several types of learned variational regularization against the theoretical benchmark of the optimal affine reconstruction, i.e. the best possible affine linear map for minimizing the mean squared error. It is known that this optimal re

Ramon van Handel

A family of random matrices is said to converge strongly to a limiting family of operators if the operator norm of every noncommutative polynomial of the matrices converges to that of the limiting operators. Recent developments surrounding the strong convergence phenomenon have led to new progress on important problems in random graphs, geometry, operator al

Remo Cristoforetti, Philipp Süss, Tobias Becher, Niklas Wahl

Treatment planning in radiotherapy is inherently a multi-criteria optimization (MCO) problem. Traditionally, the treatment's robustness is not formulated as a part of this decision making problem, but dealt with separately through margins or robust optimization. This work facilitates integration of robustness into multi-criteria optimization using a recently

Juan Li, Junzhi Wang, Zhiqiang Shen, Alba Vidal-Garcia

We observed NH3 metastable inversion lines from (3, 3) to (18, 18) toward G0.66-0.13 in the Galactic center with the Shanghai Tianma 65m radio telescope and Yebes 40 m telescope. Highly-excited lines of NH3 (17, 17), (18, 18) were detected in emission for the first time in the interstellar medium, with upper energy levels up to 3100 K. Mapping observations r

Yaoqi Ye, Chengkai Lin, Xiao Wang

We derive semiclassical analytical solutions for both the diagonal and off-diagonal functions in the eigenstate thermalization hypothesis (ETH) in a quarter-stadium quantum billiard. For a representative observable, we obtain an explicit expression and an asymptotic closed-form solution that naturally separate into a local contribution and a phase-space corr

Tomas Ruiz, Siyao Peng, Barbara Plank, Carsten Schwemmer

Test-time scaling is a family of techniques to improve LLM outputs at inference time by performing extra computation. To the best of our knowledge, test-time scaling has been limited to domains with verifiably correct answers, like mathematics and coding. We transfer test-time scaling to the LeWiDi-2025 tasks to evaluate annotation disagreements. We experime

Zhige Chen, Chengxuan Qin, Wenlong You, Rui Liu

Electroencephalography (EEG) is an essential technique for neuroscience research and brain-computer interface (BCI) applications. Recently, large-scale EEG foundation models have been developed, exhibiting robust generalization capabilities across diverse tasks and subjects. However, the heterogeneity of EEG devices not only hinders the widespread adoption o

Zhuo Long, Peng Gao

The chemical step is an elementary pattern in chemically heterogeneous substrates, featuring two regions of different wettability separated by a sharp border. Within the framework of lubrication theory, we investigate droplet motion and the contact-line dynamics driven by a chemical step, with the contact-line singularity addressed by the Navier slip conditi

Shivangi Pandey, Suvendu Rakshit, S. Muneer, Jincen Jose

Robust extragalactic distance measurements are crucial for resolving the persistent discrepancy in the value of the Hubble constant (H$_0$)). Active Galactic Nuclei (AGNs), through their compact and variable broad-line regions (BLRs), enable the determination of geometric distances when reverberation mapping (RM) is combined with spectroastrometry(SA). We re

Bryan Van Scoy, Gianluca Bianchin

This paper investigates the fundamental performance limits of gradient-based algorithms for time-varying optimization. Leveraging the internal model principle and root locus techniques, we show that temporal variabilities impose intrinsic limits on the achievable rate of convergence. For a problem with condition ratio $\kappa$ and time variation whose model

Robert Meiners Fuchs, Juanjuan Ren, Stephen Hughes, Marten Richter

The electromagnetic Green's function is a crucial ingredient for the theoretical study of modern photonic quantum devices, but is often difficult or even impossible to calculate directly. We present a numerically efficient framework for calculating the scattered electromagnetic Green's function of a multi-cavity system with spatially separated open cavities

A. Inventar, G. Peron, S. Recchia, S. Gabici

Gamma-ray observations of young star clusters have recently provided evidence for particle acceleration occurring at stellar wind termination shocks, fueled by the mechanical energy of stellar winds from massive stars. In this work, we explore the possibility that the wind from a single powerful star, whether isolated or part of a cluster, can alone provide

Gaoyuan Liu, Bas Boom, Naftali Slob, Yuri Durodié

Pruning is an essential agricultural practice for orchards. Proper pruning can promote healthier growth and optimize fruit production throughout the orchard's lifespan. Robot manipulators have been developed as an automated solution for this repetitive task, which typically requires seasonal labor with specialized skills. While previous research has primaril

Mohammed Hilal Al-Kharusi, Khizar Hayat, Khalil Bader Al Ruqeishi, Haroon Rashid Lone

The art and science of Quranic recitation (Tajweed), a discipline governed by meticulous phonetic, rhythmic, and theological principles, confronts substantial educational challenges in today's digital age. Although modern technology offers unparalleled opportunities for learning, existing automated systems for evaluating recitation have struggled to gain bro

Itai Arieli, Yakov Babichenko, Atulya Jain, Rann Smorodinsky

We study games with incomplete information and characterize when a feasible outcome is Pareto efficient. Outcomes with excessive randomization are inefficient: generically, the total number of action profiles across states must be strictly less than the sum of the number of players and the number of states. We consider three applications. A cheap talk outcom

Sheng-Ao Mao, Lin Zhang, Bo Li

Recently, machine learning has been widely applied in the field of quantum information, notably in tasks such as entanglement detection, steering characterization, and nonlocality verification. However, few studies have focused on utilizing machine learning to detect quantum information masking. In this work, we investigate supervised machine learning for de

Lingqi Meng, Paulo C. C. Freire, Kevin Stovall, Norbert Wex

We conducted high-precision timing of PSR J1946+2052 to determine the masses of the two neutron stars in the system, test general relativity (GR) and assessed the system's potential for future measurement of the moment of inertia of the pulsar. We analysed seven years of timing data from the Arecibo 305-m radio telescope, the Green Bank Telescope (GBT), and

Christopher N. Everett, Marc Klinger-Plaisier, Garret Cotter

DIPLODOCUS (Distribution-In-PLateaux methODOlogy for the CompUtation of transport equationS) is a framework being developed for the mesoscopic modelling of astrophysical systems via the transport of particle distribution functions through the seven dimensions of phase space, including continuous forces and discrete interactions between particles. Following P

Rubén Martos, Christophe Ambroise, Guillem Rigaill

We propose a novel framework for reconstructing the chronology of genetic regulation using causal inference based on Pearl's theory. The approach proceeds in three main stages: causal discovery, causal inference, and chronology construction. We apply it to the ndhB and ndhD genes of the chloroplast in Arabidopsis thaliana, generating four alternative maturat

Huiyang Yi, Yanyan He, Duxin Chen, Mingyu Kang

Causal discovery aims to learn causal relationships between variables from targeted data, making it a fundamental task in machine learning. However, causal discovery algorithms often rely on unverifiable causal assumptions, which are usually difficult to satisfy in real-world data, thereby limiting the broad application of causal discovery in practical scena

Eric Buffenoir

The quantum logic program originated in a 1936 article by G. Birkhoff and J. von Neumann. This program is generally disregarded due to no-go theorems restricting the existence of the tensor product of elementary quantum logics and, above all, the impossibility of considering entangled states and Bell non-local states within the framework of these composite q

Francisco J. Cruz-Zamorano, Konstantinos Zarvalis

This paper investigates the dynamical behaviour of holomorphic self-maps of the upper half-plane. More precisely, we focus on the hyperbolic and parabolic self-maps whose orbits approach the Denjoy--Wolff point with the slowest possible rate. We characterize self-maps of such extremal rate using various tools, like the Herglotz representation, the conformali

J. Patrick Harrington, Richard Ignace, Kenneth G. Gayley

Stellar rotation has long been recognized as important to the evolution of stars, by virtue of the chemical mixing it can induce and how it interacts with binary mass transfer. Binary interaction and rapid rotation are both common in massive stars and involve processes of angular momentum distribution and transport. An important question is how this angular

Wenshuai Hu, Guanghua Ji

The blue phases are fascinating and complex states of chiral liquid crystals which can be modeled by a comprehensive framework of the Landau-de theory, satisfying energy dissipation and maximum bound principle. In this paper, we develop and analyze first and second order exponential time differencing numerical schemes for the gradient flow of the chiral liqu

Chengpeng Hu, Calvin Yu-Chian Chen

Artificial Intelligence Virtual Cells (AIVCs) aim to learn executable, decision-relevant models of cell state from multimodal, multiscale measurements. Recent studies have introduced single-cell and spatial foundation models, improved cross-modality alignment, scaled perturbation atlases, and explored pathway-level readouts. Nevertheless, although held-out v

Jincheng Zhong, Boyuan Jiang, Xin Tao, Pengfei Wan

Existing denoising generative models rely on solving discretized reverse-time SDEs or ODEs. In this paper, we identify a long-overlooked yet pervasive issue in this family of models: a misalignment between the pre-defined noise level and the actual noise level encoded in intermediate states during sampling. We refer to this misalignment as noise shift. Throu

Boyi Dai

We study irreducibility of Galois representations $\rho_{\pi,\lambda}$ associated to a $n=7$ or 8-dimensional regular algebraic essentially self-dual cuspidal automorphic representation $\pi$ of $\text{GL}_n(\mathbb{A}_\mathbb{Q})$. We show $\rho_{\pi,\lambda}$ is irreducible for all but finitely many $\lambda$ under the following extra conditions. (i) If $n

Nizar Riane

This paper revisits the Arrow-Debreu general equilibrium framework through the lens of effective trade, emphasizing the distinction between theoretical and realizable market interactions. We develop the Effective Trade Model (ETM), where transactions arise from bilateral feasibility rather than aggregate supply and demand desires. Within this framework, we e

Zsolt Regaly, Viktoria Frohlich, Csaba Kiss

Weywot, Quaoar's small satellite, follows a nearly circular orbit at a distance of 12.9 times Quaoar's diameter and coexists with a compact ring system. Nevertheless, Quaoar's flattening of 0.16, slow 17.7hr rotation and Weywot's low mass are difficult to reconcile with conventional tidal-evolution theory. We assess whether standard tides can reproduce the p

Yi Liu, Yang Liu, Leqian Zheng, Jue Hong

With the rapid advancement of the digital economy, data collaboration between organizations has become a well-established business model, driving the growth of various industries. However, privacy concerns make direct data sharing impractical. To address this, Two-Party Split Learning (a.k.a. Vertical Federated Learning (VFL)) has emerged as a promising solu

An Zhao, Piaopiao Yu, Zhe Zhu, Mingqiang Wei

3D Gaussian Splatting has exhibited remarkable capabilities in 3D scene reconstruction. However, reconstructing high-quality 3D scenes from motion-blurred images caused by camera motion poses a significant challenge.The performance of existing 3DGS-based deblurring methods are limited due to their inherent mechanisms, such as extreme dependence on the accura

Aakash Anand, A. Bhattacharyay

Understanding surface-driven transport is of paramount importance from the perspective of biological applications and the synthesis of microfluidic devices. In this work, we develop an analysis of a local inversion symmetry broken fluid flow model through an undulating microchannel. Surface undulations of a few tens of Hertz in a soft microchannel keep the f

Richard G. Arendt, F. Yusef-Zadeh, I. Heywood

We present a catalog of 1.28 GHz radio filaments observed by MeerKAT over the innermost 200 pc of the Galaxy (roughly $\pm 1.5\deg$), which includes the central molecular zone (CMZ). The catalog is generated by repurposing software developed for the automated detection of filaments in solar coronal loops. There are two parts to the catalog. The first part, t

Rui Reis, Pedro Rangel Henriques, João Ferreira-Coimbra, Eva Oliveira

We developed a task-oriented dialogue framework structured as a Directed Acyclic Graph (DAG) of medical questions. The system integrates: (1) a systematic pipeline for transforming medical algorithms and guidelines into a clinical question corpus; (2) a cold-start mechanism based on hierarchical clustering to generate efficient initial questioning without pr

Beibu Li, Qichao Shentu, Yang Shu, Hui Zhang

Time series anomaly detection plays a crucial role in a wide range of real-world applications. Given that time series data can exhibit different patterns at different sampling granularities, multi-scale modeling has proven beneficial for uncovering latent anomaly patterns that may not be apparent at a single scale. However, existing methods often model multi

J. L. Nilo-Castellón, M. V. Alonso, L. Baravalle, C. Villalon

The Zone of Avoidance (ZoA) remains one of the last frontiers in constructing a comprehensive three-dimensional map of the Universe. Galactic extinction, stellar crowding, and confusion noise have historically limited the detection of background galaxies in these regions, with implications for large-scale structure and cosmological measurements. We assess th

Evgeniy Glukhov, Michele Conti, Egor Bogomolov, Yaroslav Golubev

Reliable handling of code diffs is central to agents that edit and refactor repositories at scale. We introduce Diff-XYZ, a compact benchmark for code-diff understanding with three supervised tasks: apply (old code $+$ diff $\rightarrow$ new code), anti-apply (new code $-$ diff $\rightarrow$ old code), and diff generation (new code $-$ old code $\rightarrow$

Mousomi Bhakta, Anup Biswas, Roberta Filippucci

In this paper, we present a series of Liouville-type theorems for a class of nonhomogeneous quasilinear elliptic equations featuring reactions that depend on the solution and its gradient. Specifically, we investigate equations of the form $-\Delta_p u - \Delta_q u = f(u,\nabla u)$ with $p > q > 1$, where the nonlinearity $f$ takes forms such as $u^s|\nabla

Jiatong Li, Simon Doclo

Recently, a complex variational autoencoder (VAE)-based single-channel speech enhancement system based on the DCCRN architecture has been proposed. In this system, a noise suppression VAE (NSVAE) learns to extract clean speech representations from noisy speech using pretrained clean speech and noise VAEs with skip connections. In this paper, we improve DCCRN

Takafumi Akahori, Slim Ibrahim, Hiroaki Kikuchi, Masataka Shibata

In this paper, we investigate positive radial solutions to double-power nonlinear stationary Schrodinger equations in three space dimensions. It is now known that the non-uniqueness of H^{1}-positive solutions can occur in three dimensions when the frequency is sufficiently small. Under suitable conditions, in addition to the ground state solution (whose L^{

Jingkai Jia, Tong Yang, Xueyao Chen, Chenhuan Liu

We present a fast and effective policy framework for robotic manipulation, named Energy Policy, designed for high-frequency robotic tasks and resource-constrained systems. Unlike existing robotic policies, Energy Policy natively predicts multimodal actions in a single forward pass, enabling high-precision manipulation at high speed. The framework is built up

Shurong Chai, Rahul Kumar JAIN, Rui Xu, Shaocong Mo

Deep learning relies heavily on data augmentation to mitigate limited data, especially in medical imaging. Recent multimodal learning integrates text and images for segmentation, known as referring or text-guided image segmentation. However, common augmentations like rotation and flipping disrupt spatial alignment between image and text, weakening performanc

Attila Egri-Nagy

Programming languages tend to evolve over time to use more and more concepts from theoretical computer science. Still, there is a gap between programming and pure mathematics. Not all theoretical results have realized their promising applications. The algebraic decomposition of finite state automata (Krohn-Rhodes Theory) constructs an emulating hierarchical

Svante Janson

We define cyclic $U$-statistics as a variant of $U$-statistics based on variables $X_1,\dots,X_n$ that are assumed to be cyclically ordered. We also define alternating $U$-statistics where in the definition terms are summed with alternating sings (in three different ways). Only $U$-statistics of order 2 are considered. The definitions are inspired by special

Huu-Tai Phung, Zong-Lin Gao, Yi-Chen Yao, Kuan-Wei Ho

This work, termed MH-LVC, presents a multi-hypothesis temporal prediction scheme that employs long- and short-term reference frames in a conditional residual video coding framework. Recent temporal context mining approaches to conditional video coding offer superior coding performance. However, the need to store and access a large amount of implicit contextu

Øystein Haugen, Stefan Klikovits, Martin Arthur Andersen, Jonathan Beaulieu

The new SysMLv2 adds mechanisms for the built-in specification of domain-specific concepts and language extensions. This feature promises to facilitate the creation of Domain-Specific Languages (DSLs) and interfacing with existing system descriptions and technical designs. In this paper, we review these features and evaluate SysMLv2's capabilities using conc

Gaoyuan Liu, Joris de Winter, Kelly Merckaert, Denis Steckelmacher

In a Human-Robot Cooperation (HRC) environment, safety and efficiency are the two core properties to evaluate robot performance. However, safety mechanisms usually hinder task efficiency since human intervention will cause backup motions and goal failures of the robot. Frequent motion replanning will increase the computational load and the chance of failure.

Lang Gao, Xuhui Li, Chenxi Wang, Mingzhe Li

Large language models (LLMs) have grown more powerful in language generation, producing fluent text and even imitating personal style. Yet, this ability also heightens the risk of identity impersonation. To the best of our knowledge, no prior work has examined personalized machine-generated text (MGT) detection. In this paper, we introduce \dataset, the firs

Somnath Dutta

Jets and outflows are key components of low-mass star formation, regulating accretion and shaping the surrounding molecular clouds. These flows, traced by molecular species at (sub)millimeter wavelengths (e.g., CO, SiO, SO, H$_2$CO, and CH$_3$OH) and by atomic, ionized, and molecular lines in the infrared (e.g., H$_2$, [Fe II], [S I]), originate from protost

Biao Zhang, Lixin Chen, Tong Liu, Bo Zheng

Large language models (LLMs) generate high-dimensional embeddings that capture rich semantic and syntactic information. However, high-dimensional embeddings exacerbate computational complexity and storage requirements, thereby hindering practical deployment. To address these challenges, we propose a novel training framework named Sequential Matryoshka Embedd

Run-Jie Peng, Xing-Yu Wang, Jun-Hui Yuan, Nian-Nian Yu

High-performance, low-power transistors are core components of advanced integrated circuits, and the ultimate limitation of Moore's law has made the search for new alternative pathways an urgent priority. Two-dimensional (2D) materials have become the most promising exploration target due to their exceptional electronic properties and scalability. In this wo

Nakul Aggarwal, Ali Pourmand, Fatimah Shojai, Harish Parthasarathy

In the framework of $f(Q)$ gravity, where gravity emerges from non-metricity $Q$, we explore the cosmological implications of its non-minimal coupling to matter. Inspired by the recent success of Chaplygin gas models in explaining dark energy, we consider a background fluid composed of baryonic matter, radiation, and a family of Chaplygin gas variants namely

Alfio Bonanno, Enrico Corsaro, Travis S. Metcalfe, Sylvain Breton

The stellar Rossby number, a dimensionless parameter quantifying the influence of Coriolis forces on convective motions, plays a pivotal role in understanding magnetic stellar evolution. In this work, we explore the connection between the Rossby number and potential dynamo mechanisms in Sun-like stars, as well as its dependence on fundamental stellar propert

Zhiwei Chen, Qingjuan Yu, Youjun Lu, Xiao Guo

Lensed gravitational wave (GW) events are expected to be powerful new probes of cosmology, contingent on redshift measurement by electromagnetic observations. Host galaxy identification is thus crucial but challenging due to poor localization by GW signal alone. In this paper, we show that the third-generation ground-based GW detectors will detect a populati

Filip Rezabek, Moe Mahhouk, Andrew Miller, Quintus Kilbourn

Confidential Virtual Machines (CVMs) protect data in use by running workloads within hardware-enforced Trusted Execution Environments (TEEs). However, existing CVM attestation mechanisms only certify what code is running, not where it is running. Commercial TEEs mitigate passive physical attacks through memory encryption but explicitly exclude active hardwar

Dion J. X. Ho, Gabriel Lee Jun Rong, Niharika Shrivastava, Harshavardhan Abichandani

We present MS-GAGA (Metric-Selective Guided Adversarial Generation Attack), a two-stage framework for crafting transferable and visually imperceptible adversarial examples against deepfake detectors in black-box settings. In Stage 1, a dual-stream attack module generates adversarial candidates: MNTD-PGD applies enhanced gradient calculations optimized for sm

Kevyn Gallegos-Moncayo, Josephine Rezkallah, Justine Jean, Arash Jamali

A deeper understanding of the cathode electrolyte interphase (CEI) formation mechanism is essential to elucidate battery degradation. Here, we combine Liquid Electrochemical Transmission Electron Microscopy (ec-TEM) with Gas Chromatography/Mass Spectrometry (GC/MS) to monitor CEI evolution in a realistic electrochemical environment, focusing on electrolyte b

Stephanie Riedmüller, Niels Lindner

Periodic timetabling for public transportation networks is typically modelled as a Periodic Event Scheduling Problem (PESP). Solving instances of the benchmark library PESPlib to optimality continues to pose a challenge. As a further approach towards this goal, we remodel the problem by a time discretization of the underlying graph and consider arc-based as

Stefano Torniamenti, Michela Mapelli, Lumen Boco, Filippo Simonato

Intermediate-mass black holes (IMBHs) are the link between stellar-mass and supermassive black holes. Gravitational waves have started unveiling a population of IMBHs in the $\sim 100-300 \, \mathrm{M_{\odot}}$ range. Here, we investigate the formation of IMBHs from non-rotating very massive stars (VMSs, $>100\,{} \mathrm{M_{\odot}}$). We calculate new VMS m

Kazuo Aoki, Niclas Bernhoff

A polyatomic ideal gas with weak interaction between the translational and internal modes is considered. For the purpose of describing the behavior of such a gas, a Boltzmann equation is proposed in the form that the collision integral is a linear combination of inelastic and elastic (or resonant) collisions, and its basic properties are discussed. Then, in

Nikoleta Pantelidou, Evelina Leivada, Raquel Montero, Paolo Morosi

The linguistic abilities of Large Language Models are a matter of ongoing debate. This study contributes to this discussion by investigating model performance in a morphological generalization task that involves novel words. Using a multilingual adaptation of the Wug Test, six models were tested across four partially unrelated languages (Catalan, English, Gr

Jiaxin Gao, Chen Chen, Yanwen Jia, Xueluan Gong

Large Language Models (LLMs) are increasingly being used to autonomously evaluate the quality of content in communication systems, e.g., to assess responses in telecom customer support chatbots. However, the impartiality of these AI "judges" is not guaranteed, and any biases in their evaluation criteria could skew outcomes and undermine user trust. In this p

Andrei Chernov, Haroon Wahab, Oleg Novitskij

In recent years, various approaches have been proposed to leverage large language models (LLMs) for incorporating textual information about items into recommender systems. Existing methods primarily focus on either fine-tuning LLMs to generate recommendations or integrating LLM-based embeddings into downstream models. In this work, we follow the latter direc

Linfeng Gao, Qinggang Zhang, Baolong Bi, Bo Zeng

Retrieval-Augmented Generation (RAG) systems often fail to maintain contextual faithfulness, generating responses that conflict with the provided context or fail to fully leverage the provided evidence. Existing methods attempt to improve faithfulness through external interventions, such as specialized prompting, decoding-based calibration, or preference opt

Thomas Kalmes, Dalimil Peša

We study ergodicity of composition operators on rearrangement-invariant Banach function spaces. More precisely, we give a natural and easy-to-check condition on the symbol of the operator which entails mean ergodicity on a very large class of rearrangement-invariant Banach function spaces. Further, we present some natural additional assumptions that allow us

Cristina Emilia Costa, Tatenda Horiro Zhou, Fabrizio Granelli

Network Digital Twins represent a key technology in future networks, expected to provide the capability to perform accurate analysis and predictions about the behaviour of 6G mobile networks. However, despite the availability of several theoretical works on the subject, still very few examples of actual implementations of Network Digital Twin are available.

Robert Stárek, Tim Gollerthan, Olga Leskovjanová, Michael Meth

A central concept in quantum information processing is genuine multipartite entanglement (GME), a type of correlation beyond biseparability, that is, correlations that cannot be explained by statistical mixtures of partially separable states. GME is relevant for characterizing and benchmarking complex quantum systems, and it is an important resource for appl

Nisith Dissanayake, Uthayasanker Thayasivam

The growing scale and sophistication of cyberattacks pose critical challenges to network security, particularly in detecting diverse intrusion types within imbalanced datasets. Traditional intrusion detection systems (IDS) often struggle to maintain high accuracy across both frequent and rare attacks, leading to increased false negatives for minority classes

Yi Yuan, Jian Cao, Jinbo Yuan, Dehao Wang

Precise time scale is the universal base for all measurements. Here we report the deployment of a compact and transportable optical clock to a timekeeping institution and steering an active hydrogen maser to generate an optical time scale, realizing the upgrade of the local time scale in the Global Navigation Satellite System. The optical clock was transport

Viacheslav Vasilev, Arseny Ivanov, Nikita Gushchin, Maria Kovaleva

Diffusion models excel in noise-to-data generation tasks, providing a mapping from a Gaussian distribution to a more complex data distribution. However, they struggle to model translations between complex distributions, limiting their effectiveness in data-to-data tasks. While Bridge Matching models address this by finding the translation between data distri

Ji-Hai Yuan, Ya-Dong Gu, Yun-Qing Shi, Hao-Yu He

The Ge-doped GaNb4Se8 polycrystalline samples were synthesized by solid-state reaction method. Zero resistance transitions were observed in one batch of samples with the highest onset superconducting Tc at 45 K. This discovery may demonstrate a new class of Nb-based high-Tc superconductors arising from doped Mott insulators.

Francesco Giarrusso, Olga E. Sorokoletova, Vincenzo Suriani, Daniele Nardi

Jailbreaking techniques pose a significant threat to the safety of Large Language Models (LLMs). Existing defenses typically focus on single-turn attacks, lack coverage across languages, and rely on limited taxonomies that either fail to capture the full diversity of attack strategies or emphasize risk categories rather than jailbreaking techniques. To advan

Israel Mason-Williams, Gabryel Mason-Williams, Helen Yannakoudakis

Flat minima are strongly associated with improved generalisation in deep neural networks. However, this connection has proven nuanced in recent studies, with both theoretical counterexamples and empirical exceptions emerging in the literature. In this paper, we revisit the role of sharpness in model performance and argue that sharpness is better understood a

Gerald Kuba

Let S denote the family of all subspaces of the plane that are graphs of functions from the real line R to itself. We prove that S has two subfamilies G,H of spaces such that the cardinality of G is c (the cardinality of the continuum) and the cardinality of H is 2^c, every space in the family G is completely metrizable, each element of H is a dense subset o

M. Demirci, H. I. Sezer, M. F. Mustamin, A. B. Balantekin

Neutrinos that are elastically scattered off atomic electrons provide a unique opportunity to investigate the Standard Model (SM) and beyond SM physics. In this work, we explore the new physics effects of neutrino electromagnetic properties through elastic neutrino-electron scattering using solar neutrinos at the low energy range of PandaX-4T and XENONnT exp

Paul Merrikin

In this thesis, the AdS/CFT correspondence is used as a tool to explore novel AdS$_5$ Supergravity backgrounds (containing five-dimensional Anti-de Sitter spacetime) and their dual (four dimensional) Conformal Field Theory descriptions. In order to obtain precise results, both conformal symmetry and supersymmetry play an important role. However, in order to

Anush Anand, Pranav Agrawal, Tejas Bodas

Dynamic pricing is the practice of adjusting the selling price of a product to maximize a firm's revenue by responding to market demand. The literature typically distinguishes between two settings: infinite inventory, where the firm has unlimited stock and time to sell, and finite inventory, where both inventory and selling horizon are limited. In both cases

Weixiao Lu, Guodong Xi

We study the automorphic period associated to a $G$-Hamiltonian variety $M$ whose dual is $\check{M} = T^*(\check{G}/\check{L})$, where $\check{G}$ is a general linear group and $\check{L}$ is a Levi subgroup. For certain cuspidal Eisenstein series, we prove that their period is equal to a finite sum of special values of $L$-functions. This sum is indexed by

Xiangyu Li, Ran Su, Liangliang Liu

Accurate prediction of drug-target interactions (DTI) is pivotal in drug discovery. However, existing approaches often fail to capture deep intra-modal feature interactions or achieve effective cross-modal alignment, limiting predictive performance and generalization. To address these challenges, we propose M3ST-DTI, a multi-task learning model that enables