April 2025 arXiv papers — page 3

Tanisha Jhaveri, Tanvi Karwal, Wayne Hu

Under $\Lambda$CDM, recent baryon acoustic oscillation (BAO) distance measures from DESI, which favor a low matter density $\Omega_m$, are in moderate $2-3\sigma$ tension with cosmic microwave background (CMB) observations. This tension appears alternately as a preference for the sum of neutrino masses dropping below the $\sum m_\nu = 0.06$eV value required

Martin Metodiev, Nicholas J. Irons, Marie Perrot-Dockès, Pierre Latouche

We present a new version of the truncated harmonic mean estimator (THAMES) for univariate or multivariate mixture models. The estimator computes the marginal likelihood from Markov chain Monte Carlo (MCMC) samples, is consistent, asymptotically normal and of finite variance. In addition, it is invariant to label switching, does not require posterior samples

Christos Kitsios, Thomas Schick, Federico Vigolo

We prove a conjecture of Roe by constructing unified warped cones that violate the coarse Baum-Connes conjecture. Interestingly, the reason for this is probably not what Roe expected, as the obstruction arises in odd rather than even degree.

Franko Hrzic, Mohammadreza Movahhedi, Ophelie Lavoie-Gagne, Ata Kiapour

It is well known that machine learning models require a high amount of annotated data to obtain optimal performance. Labelling Computed Tomography (CT) data can be a particularly challenging task due to its volumetric nature and often missing and$/$or incomplete associated meta-data. Even inspecting one CT scan requires additional computer software, or in th

Quanling Deng, Seung-Yeal Ha

We introduce a comprehensive modeling framework for the dynamics of sea ice floes using particle, kinetic, and hydrodynamic approaches. Building upon the foundational work of Ha and Tadmor on the Cucker-Smale model for flocking, we derive a Vlasov-type kinetic formulation and a corresponding hydrodynamic description. The particle model incorporates essential

Atieh Rahmani, Mansoor Davoodi, Justin M. Calabrese

Clustering algorithms fundamentally group data points by characteristics to identify patterns. Over the past two decades, researchers have extended these methods to analyze trajectories of humans, animals, and vehicles, studying their behavior and movement across applications. \noindent This paper presents whole-trajectory clustering and sub-trajectory clust

Fritz Colonius, Roberta Fabbri

For nonautonomous control systems with compact control range, associated control flows are introduced. This leads to several skew product flows with various base spaces. The controllability and chain controllability properties are studied and related to properties of the associated skew product flows.

Rachael Boyd, Corey Bregman

We study the unparametrised smooth embedding space of a Hopf link in $\mathbb{R}^3$, and prove that it is homotopy equivalent to the closed 3-manifold $S^3/\mathbb{Q}_8$. As an intermediate step in the proof, we show that the inclusion of the subspace of round embeddings is a homotopy equivalence. We provide analogous results for the unparametrised smooth em

Xiang-dong Hou, Shujun Zhao

A recent conjecture by C. Carlet on the sum-freedom of the binary multiplicative inverse function can be stated as follows: For each pair of positive integers $(n,k)$ with $3\le k\le n-3$, there is a $k$-dimensional $\Bbb F_2$-subspace $E$ of $\Bbb F_{2^n}$ such that $\sum_{0\ne\in E}1/u=0$. We confirm this conjecture when $n$ is not a prime.

Saikat Biswas

India is a founder-member country to participate in the construction of the international multipurpose accelerator facility called the Facility for Antiproton and Ion Research (FAIR) at Darmstadt, Germany. Bose Institute, Kolkata, has been designated as the Indian shareholder of the FAIR GmbH and the nodal Indian Institution for co-ordinating Indian particip

Xiuwei Shang, Zhenkan Fu, Shaoyin Cheng, Guoqiang Chen

Binary code analysis plays a pivotal role in the field of software security and is widely used in tasks such as software maintenance, malware detection, software vulnerability discovery, patch analysis, etc. However, unlike source code, reverse engineers face significant challenges in understanding binary code due to the lack of intuitive semantic informatio

Subhadip Dey, Konstantinos Tsouvalas

For uniform lattices $\Gamma$ in rank 1 Lie groups, we construct Anosov representations of virtual doubles of $\Gamma$ along certain quasiconvex subgroups. We also show that virtual HNN extensions of these lattices over some cyclic subgroups admit Anosov embeddings. In addition, we prove that for any Anosov subgroup $\Gamma$ of a real semisimple linear Lie g

Z. Z. Ren, Zhihong Shao, Junxiao Song, Huajian Xin

We introduce DeepSeek-Prover-V2, an open-source large language model designed for formal theorem proving in Lean 4, with initialization data collected through a recursive theorem proving pipeline powered by DeepSeek-V3. The cold-start training procedure begins by prompting DeepSeek-V3 to decompose complex problems into a series of subgoals. The proofs of res

Suhas BN, Dominik Mattioli, Saeed Abdullah, Rosa I. Arriaga

Synthetic data adoption in healthcare is driven by privacy concerns, data access limitations, and high annotation costs. We explore synthetic Prolonged Exposure (PE) therapy conversations for PTSD as a scalable alternative for training clinical models. We systematically compare real and synthetic dialogues using linguistic, structural, and protocol-specific

John Yang, Kilian Lieret, Carlos E. Jimenez, Alexander Wettig

Despite recent progress in Language Models (LMs) for software engineering, collecting training data remains a significant pain point. Existing datasets are small, with at most 1,000s of training instances from 11 or fewer GitHub repositories. The procedures to curate such datasets are often complex, necessitating hundreds of hours of human labor; companion e

James Davies, Meike Hatzel, Kolja Knauer, Rose McCarty

We prove a conjecture of Geelen, Gerards, and Whittle that for any finite field $GF(q)$ and any integer $t$, every cosimple $GF(q)$-representable matroid with sufficiently large girth contains either $M(K_t)$ or $M(K_t)^*$ as a minor.

Yuankang Zhao, Matthew Engelhard

The Hawkes process (HP) is commonly used to model event sequences with self-reinforcing dynamics, including electronic health records (EHRs). Traditional HPs capture self-reinforcement via parametric impact functions that can be inspected to understand how each event modulates the intensity of others. Neural network-based HPs offer greater flexibility, resul

F. Castillo Menegotto, R. S. Severino, P. D. Mininni, E. Fradkin

We investigate the vortex flow anisotropy in the mixed state of nematic superconductors, focusing on the effects of nematic-superconducting coupling on vortex dynamics. Using numerical simulations within a time-dependent Ginzburg-Landau (TDGL) approach, we analyze vortex viscosity in a model featuring an s-wave superconducting order parameter coupled to an I

Rene Carmona, Mathieu Lauriere

Reinforcement learning (RL) is currently one of the most prominent methods for optimizing dynamical systems, with breakthrough results across various fields. The framework is based on the concept of a Markov decision process (MDP), leading to a discrete-time optimal control problem. In the RL literature, such problems are typically formulated and solved usin

Stephanie Chan, Peter Koymans, Nick Rome

We prove the refined Loughran--Smeets conjecture of Loughran--Rome--Sofos for a wide class of varieties arising as products of conic bundles. One interesting feature of our varieties is that the subordinate Brauer group may be arbitrarily large. As an application of our methods, we answer a question of Lenstra by giving an asymptotic for the triples of integ

Yu-Ting Chen

We study the martingale formulation of the two-dimensional stochastic heat equation (SHE) at criticality. The main theorem proves an exact recursive-type equation that expresses the covariation measures of the SHE in terms of the solutions via an integro-multiplication operator. As an application, the quadratic variations of the martingale parts in the mild

Kei Yuen Chan, Simeng Huang

This article confirms the prediction that the set of discrete series central character for the graded (affine) Hecke algebra of type $H_4$ coincides with the set of the Heckman-Opdam central characters. Combining with previous cases of Kazhdan-Lusztig, Kriloff, Kriloff-Ram, Opdam-Solleveld, Ciubotaru-Opdam, this completes the classification of discrete serie

Alessia Hu, Regina Beets-Tan, Lishan Cai, Eduardo Pooch

Magnetic Resonance Imaging (MRI) plays an important role in identifying clinically significant prostate cancer (csPCa), yet automated methods face challenges such as data imbalance, variable tumor sizes, and a lack of annotated data. This study introduces Anomaly-Driven U-Net (adU-Net), which incorporates anomaly maps derived from biparametric MRI sequences

Luis Welbanks, Matthew C. Nixon, Peter McGill, Lana J. Tilke

Claims of detections of gases in exoplanet atmospheres often rely on comparisons between models including and excluding specific chemical species. However, the space of molecular combinations available for model construction is vast and highly degenerate. Only a limited subset of these combinations is typically explored for any given detection. As a result,

Yu Wang, Zhangyu Yang, Xingyao Wu, Christian B. Mendl

We improve the convergence of the Lanczos algorithm using the matrix product state representation. As an alternative to the density matrix renormalization group (DMRG), the Lanczos algorithm avoids local minima and can directly find multiple low-lying eigenstates. However, its performance and accuracy are affected by the truncation required to maintain the e

Samuel Olivier, James S. Warsa, HyeongKae Park

Thermal radiative transfer (TRT) presents significant computational challenges due to the stiff, nonlinear coupling between radiation and material energy, particularly in multigroup, high-fidelity transport models. In this work, we develop an efficient nonlinear acceleration framework for TRT based on the Second Moment (SM) method. Our approach couples high-

Santiago Ibáñez, Alexandre A. P. Rodrigues

Motivated by a certain type of unfolding of a Hopf-Hopf singularity, we consider a one-parameter family $(f_\gamma)_{\gamma\geq0}$ of $C^3$--vector fields in $\mathbb{R}^4$ whose flows exhibit a heteroclinic cycle associated to two periodic solutions and a bifocus, all of them hyperbolic. It is formally proved that combining rotation with a generic condition

Howard S. Cohl, Michael J. Schlosser

We review and derive transformation and summation formulas for bilateral basic hypergeometric series. Our study focuses on consequences of certain bilateral extensions of two important results by Bailey, namely a transformation for very-well-poised $_8W_7$ series in terms of two balanced $_4\phi_3$ series, and a transformation connecting three $_8W_7$ series

Markus J. Aschwanden, Felix Scholkmann

We investigate the relevance of {\sl self-organized criticality (SOC)} models in previously published empirical datasets, which includes statistical observations in astrophysics, geophysics, biophysics, sociophysics, and informatics. We study 25 interdisciplinary phenomena with five different event detection and power law fitting methods. The total number of

Fabien Dufoulon, Shreyas Pai, Gopal Pandurangan, Sriram Pemmaraju

Round complexity is an extensively studied metric of distributed algorithms. In contrast, our knowledge of the \emph{message complexity} of distributed computing problems and its relationship (if any) with round complexity is still quite limited. To illustrate, for many fundamental distributed graph optimization problems such as (exact) diameter computation,

Paola F. Antonietti, Matteo Caldana, Ilario Mazzieri, Andrea Re Fraschini

We introduce MAGNET, an open-source Python library designed for mesh agglomeration in both two- and three-dimensions, based on employing Graph Neural Networks (GNN). MAGNET serves as a comprehensive solution for training a variety of GNN models, integrating deep learning and other advanced algorithms such as METIS and k-means to facilitate mesh agglomeration

Valérie Gillot, Philippe Langevin, Alexandr Polujan

Bent functions are Boolean functions in an even number of variables that are indicators of Hadamard difference sets in elementary abelian 2-groups. A bent function in m variables is said to be normal if it is constant on an affine space of dimension m/2. In this paper, we demonstrate that all bent functions in m = 8 variables -- whose exact count, determined

Ayman A. Ameen, Thomas Richter, André Kaup

Current learned image compression models typically exhibit high complexity, which demands significant computational resources. To overcome these challenges, we propose an innovative approach that employs hierarchical feature extraction transforms to significantly reduce complexity while preserving bit rate reduction efficiency. Our novel architecture achieve

Malte Baumecker, Yannic Maus, Jara Uitto

Given a graph $G=(V,E)$, a $\beta$-ruling set is a subset $S\subseteq V$ that is i) independent, and ii) every node $v\in V$ has a node of $S$ within distance $\beta$. In this paper we present almost optimal distributed algorithms for finding ruling sets in trees and high girth graphs in the classic LOCAL model. As our first contribution we present an $O(\lo

Eleftherios Tzanis, Michail E. Klontzas

Agentic systems built on large language models (LLMs) offer promising capabilities for automating complex workflows in healthcare AI. We introduce mAIstro, an open-source, autonomous multi-agentic framework for end-to-end development and deployment of medical AI models. The system orchestrates exploratory data analysis, radiomic feature extraction, image seg

Xiaoxi Li, Jiajie Jin, Guanting Dong, Hongjin Qian

Large reasoning models (LRMs), such as OpenAI-o1 and DeepSeek-R1, demonstrate impressive long-horizon reasoning capabilities. However, their reliance on static internal knowledge limits their performance on complex, knowledge-intensive tasks and hinders their ability to produce comprehensive research reports requiring synthesis of diverse web information. To

Rongguang Ye, Ming Tang

Recent methods leverage a hypernet to handle the performance-fairness trade-offs in federated learning. This hypernet maps the clients' preferences between model performance and fairness to preference-specifc models on the trade-off curve, known as local Pareto front. However, existing methods typically adopt a uniform preference sampling distribution to tra

Ivan Vankov, Matyo Ivanov, Adriana Correia, Victor Botev

Large Language Models (LLMs) have demonstrated considerable success in open-book question answering (QA), where the task requires generating answers grounded in a provided external context. A critical challenge in open-book QA is to ensure that model responses are based on the provided context rather than its parametric knowledge, which can be outdated, inco

Jiuwu Hao, Liguo Sun, Yuting Wan, Yueyang Wu

Collaborative perception enhances environmental awareness through inter-agent communication and is regarded as a promising solution to intelligent transportation systems. However, existing collaborative methods for Unmanned Aerial Vehicles (UAVs) overlook the unique characteristics of the UAV perspective, resulting in substantial communication overhead. To a

Jen-tse Huang, Kaiser Sun, Wenxuan Wang, Mark Dredze

While Large Language Models (LLMs) excel in reasoning, whether they can sustain persistent latent states remains under-explored. The capacity to maintain and manipulate unexpressed, internal representations-analogous to human working memory-is a cornerstone of complex reasoning. In this paper, we formalize and quantify the "Latent State Persistence" (LSP) ga

Junsheng Huang, Zhitao He, Yucheng Huang, Sandeep Polisetty

The hallucination of non-existent facts by LLMs is an important problem given its widespread adoption across various applications. Previous research addresses this problem by analyzing the internal parameterized knowledge boundaries to estimate confidence. However, these studies focus on the single-problem setting and have not explored the more challenging m

Minwoo Oh, Minsu Park, Eunil Park

Short video platforms like YouTube Shorts and TikTok face significant copyright compliance challenges, as infringers frequently embed arbitrary background music (BGM) to obscure original soundtracks (OST) and evade content originality detection. To tackle this issue, we propose a novel pipeline that integrates Music Source Separation (MSS) and cross-modal vi

Bahram Jafrasteh, Wei Peng, Cheng Wan, Yimin Luo

Generative models enhance neuroimaging through data augmentation, quality improvement, and rare condition studies. Despite advances in realistic synthetic MRIs, evaluations focus on texture and perception, lacking sensitivity to crucial anatomical fidelity. This study proposes a new metric, called WASABI (Wasserstein-Based Anatomical Brain Index), to assess

Baleegh Ahmad, Hammond Pearce, Ramesh Karri, Benjamin Tan

While static analysis is useful in detecting early-stage hardware security bugs, its efficacy is limited because it requires information to form checks and is often unable to explain the security impact of a detected vulnerability. Large Language Models can be useful in filling these gaps by identifying relevant assets, removing false violations flagged by s

Jonas Werner, Kun Chu, Cornelius Weber, Stefan Wermter

Recent advancements in machine learning provide methods to train autonomous agents capable of handling the increasing complexity of sequential decision-making in robotics. Imitation Learning (IL) is a prominent approach, where agents learn to control robots based on human demonstrations. However, IL commonly suffers from violating the independent and identic

Lucas Alland, Robert Viator

We consider Steklov eigenvalues of nearly circular domains in $\R^{2}$ of fixed unitary area. In \cite{viator2018}, the authors treated such domains as perturbations of the disk, and they computed the first-order term of the asymptotic expansions of the Steklov eigenvalues for reflection-symmetric perturbations; here, we expand these first-order results beyo

Tomasz Linowski, Konrad Schlichtholz, Giacomo Sorelli

Ideal spatial demultiplexing (SPADE) is proven to be a quantum-optimal tool for exoplanet detection, i.e., asymmetric source discrimination. However, recent investigations into the related problems of separation estimation and symmetric source discrimination showed its efficiency to be limited in the presence of noise. In this work, we use analytical tools t

Yinglei Zhu, Sixiao He, Yan Ning, Zhenghao Qi

Wheel-legged robots combine the advantages of both wheeled robots and legged robots, offering versatile locomotion capabilities with excellent stability on challenging terrains and high efficiency on flat surfaces. However, existing wheel-legged robots typically have limited hip joint mobility compared to humans, while hip joint plays a crucial role in locom

Herondy Mota, K. E. L. de Farias

We investigate thermal effects on density fluctuations in confined classical liquids using phonon quantization. The system is modeled via a massless scalar field between perfectly reflecting parallel planes with Dirichlet, Neumann, and mixed boundary conditions. Exact closed-form expressions are derived for the mean square mass density, total energy density,

Soumaya Ouhsousou, Lucy Q. Shen, Chhavi Saini, Amin Pourasghar

To establish the tissue regions necessary to accurately represent the mechanics of the optic nerve head (ONH), imaging data of the ONH from 2 healthy subjects were used to create in vivo subject-specific eye mechanical models considering distinct properties for all major ocular tissues. Tests were performed to evaluate the effect of the material properties a

Vladimir Drinfeld

If X is a groupoid equipped with an action of a 2-group G then one has a 2-groupoid X/G. We describe the fibers of the functor from X/G to the 1-groupoid $\pi_0(X)/\pi_0(G)$. We also give an explicit model for X/G in a certain situation.

C. Alexander Thomas, Lauren M. Weiss, Matthias Y. He

In an era when we are charting multiple planets per system, one might wonder the extent to which "missing" (or failing to detect) a planet can skew our interpretation of the system architecture. We address this question with a simple experiment: starting from a large, homogeneous catalog, we remove planets and monitor how several well-defined metrics of the

Benjamin Delarue, Colin Guillarmou, Daniel Monclair

A three-dimensional quasi-Fuchsian Lorentzian manifold $M$ is a globally hyperbolic spacetime diffeomorphic to $\Sigma\times (-1,1)$ for a closed orientable surface $\Sigma$ of genus $\geq 2$. It is the quotient $M=\Gamma\backslash \Omega_\Gamma$ of an open set $\Omega_\Gamma\subset {\rm AdS}_3$ by a discrete group $\Gamma$ of isometries of ${\rm AdS}_3$ whi

Takayuki Hibi, Seyed Amin Seyed Fakhari

Let $S=K[x_1, \ldots,x_n]$ denote the polynomial ring in $n$ variables over a field $K$ and $I \subset S$ a monomial ideal. Given a vector $\mathfrak{c}\in\mathbb{N}^n$, the ideal $I_{\mathfrak{c}}$ is the ideal generated by those monomials belonging to $I$ whose exponent vectors are componentwise bounded above by $\mathfrak{c}$. Let $\delta_{\mathfrak{c}}(I

Mohamed Moursi, Norbert Wehn, Bilal Hammoud

Oil spill incidents pose severe threats to marine ecosystems and coastal environments, necessitating rapid detection and monitoring capabilities to mitigate environmental damage. In this paper, we demonstrate how artificial intelligence, despite the inherent high computational and memory requirements, can be efficiently integrated into marine pollution monit

Stefano Longhi

The Mpemba effect -- where hot systems cool faster than colder ones -- has intrigued both classical and quantum thermodynamics. As compared to classical systems, quantum systems add complexity due to quantum correlations. Recent works have explored anomalous relaxation and Mpemba-like effects in several quantum systems, considering isolated systems at zero t

Ghulam Murtaza, Saikat Chakraborty, Avik De

In this article, we present a generic dynamical system formulation for Bianchi-I cosmology in the presence of an isotropic fluid within the coincident gauge connection branch and one of the non-coincident gauge connection branches of $f(Q)$ gravity theory. For both the connection branches under consideration, we start from the generic Bianchi-I cosmological

Benjamin Dozier, Samuel Grushevsky, Myeongjae Lee

We enumerate the ends of each stratum of meromorphic 1-forms on Riemann surfaces with prescribed multiplicities of zeroes and poles. Our proof uses degeneration techniques based on the construction by Bainbridge-Chen-Gendron-Grushevsky-Moeller of the moduli space of multi-scale differentials, together with recent classification of connected components of gen

Ariadna Uxue Palomino Ylla, Yasutaka Koga, Chul-Moon Yoo

We investigate the motion of a massive particle around a spherically symmetric black hole surrounded by a stationary and radial inflow of perfect fluid. The background spacetime is modelled as a spherically symmetric solution to the Einstein field equations, where the effect of the fluid on the geometry is treated as a perturbation on the Schwarzschild backg

Stefano Longhi

In waveguide quantum electrodynamics systems, atomic radiation emission is shaped by the photonic environment and collective atom interactions, offering promising applications in quantum technologies. In particular, atom-photon bound states, inhibiting complete spontaneous decay of the atom, can be realized through waveguide dispersion engineering or by util

Rosario Martínez-Herrero, Ángel S. Sanz, Javier Hernandez-Rueda

Surface plasmons have attracted growing interest from the photonics community due to their inherent ability to controllably confine light below the diffraction limit and their direct application in trapping and transporting matter at the nanoscale. This method, known as plasmonic tweezers, employs confined fields generated by either localized plasmons or sur

Haochen Sun, Xi He

Although differential privacy (DP) is widely regarded as the de facto standard for data privacy, its implementation remains vulnerable to unfaithful execution by servers, particularly in distributed settings. In such cases, servers may sample noise from incorrect distributions or generate correlated noise while appearing to follow established protocols. This

Siqi Li, Yufan Shen, Xiangnan Chen, Jiayi Chen

The rapid advancement of multimodal large language models (MLLMs) has profoundly impacted the document domain, creating a wide array of application scenarios. This progress highlights the need for a comprehensive benchmark to evaluate these models' capabilities across various document-specific tasks. However, existing benchmarks often fail to locate specific

Sizhe Wang, Zhengren Wang, Dongsheng Ma, Yongan Yu

Modern software development demands code that is maintainable, testable, and scalable by organizing the implementation into modular components with iterative reuse of existing codes. We formalize this iterative, multi-turn paradigm as codeflow and introduce CodeFlowBench, the first benchmark designed to comprehensively evaluate LLMs' ability to perform codef

Jakub Balabán, Matthias Gehnen, Henri Lotze, Finn Seesemann

Imagine you are a computer scientist who enjoys attending conferences or workshops within the year. Sadly, your travel budget is limited, so you must select a subset of events you can travel to. When you are aware of all possible events and their costs at the beginning of the year, you can select the subset of the possible events that maximizes your happines

Leonhard Sommer, Olaf Dünkel, Christian Theobalt, Adam Kortylewski

3D morphable models (3DMMs) are a powerful tool to represent the possible shapes and appearances of an object category. Given a single test image, 3DMMs can be used to solve various tasks, such as predicting the 3D shape, pose, semantic correspondence, and instance segmentation of an object. Unfortunately, 3DMMs are only available for very few object categor

Sudipta Mondal, Pritam Halder, Saptarshi Roy, Aditi Sen De

Current advancements in communication equipment demand the investigation of classical information transfer over quantum channels, by encompassing realistic scenarios in finite dimensions. To address this issue, we develop a framework for analyzing classical capacities of quantum channels where the set of states used for encoding information is restricted bas

Maxime Bouthors, Josep Crego, François Yvon

Conventional retrieval-augmented neural machine translation (RANMT) systems leverage bilingual corpora, e.g., translation memories (TMs). Yet, in many settings, monolingual corpora in the target language are often available. This work explores ways to take advantage of such resources by directly retrieving relevant target language segments, based on a source

Roy Zektzer, Ashish Chanana, Xiyuan Lu, David A. Long

High-resolution electro-optic frequency combs (EO combs) consisting of thousands to millions of comb teeth across a bandwidth between 1 GHz to 500 GHz are powerful tools for atomic, molecular, and cavity-based spectroscopy, including in the context of deployable quantum sensors. However, achieving sufficiently high signal-to-noise ratio (SNR) EO combs for us

Matthew Civiletti

In this paper we consider the extent to which a lack of observations from SETI may be used to quantify the Fermi paradox. Building on previous research, we construct a geometrical model to compute the probability of at least one detection of an extraterrestrial electromagnetic (EM) signal of galactic origin, as a function of the number $N$ of communicative c

Sridhar Prabhu, Vladimir Kremenetski, Saeed A. Khan, Ryotatsu Yanagimoto

Conventionally in quantum sensing, the goal is to estimate one or more unknown parameters that are assumed to be deterministic - that is, they do not change between shots of the quantum-sensing protocol. We instead consider the setting where the parameters are stochastic: each shot of the quantum-sensing protocol senses parameter values that come from indepe

Daniel Pablos

This text contains a summary and personal perspective on the current status and challenges of jet quenching physics as portrayed by the presentations delivered at the 12th International Conference on Hard and Electromagnetic Probes of High-Energy Nuclear Collisions (Hard Probes 2024) which took place in September 2024 in Nagasaki, Japan.

Mantas Rinkevičius, Jesús Lázaro, Eduardo Gil, Pablo Laguna

Obstructive sleep apnea (OSA) is believed to contribute significantly to atrial fibrillation (AF) development in certain patients. Recent studies indicate a rising risk of AF with increasing OSA severity. However, the commonly used apnea-hypopnea index in clinical practice may not adequately account for the potential cardiovascular risks associated with OSA.

Emelie Hallenberg

The Greek fictional narratives often termed love novels or romances, ranging from the first century CE to the middle of the 15th century, have long been considered as similar in many ways, not least in the use of particular literary motifs. By applying the use of fine-tuned large language models, this study aims to investigate which motifs exactly that the t

Hang Du, Shuyang Gong, Zhangsong Li, Haodong Zhu

We study the asymptotic diameter of the preferential attachment model $\operatorname{PA}\!_n^{(m,\delta)}$ with parameters $m \ge 2$ and $\delta > 0$. Building on the recent work \cite{VZ25}, we prove that the diameter of $G_n \sim \operatorname{PA}\!_n^{(m,\delta)}$ is $(1+o(1))\log_\nu n$ with high probability, where $\nu$ is the exponential growth rate of

Edward Varvak

We study the monodromy representations underlying compact Lagrangian fibrations. In the case where the associated period map is generically immersive, we prove that the mondromy representation is irreducible over $\mathbb{C}$. In the alternative case where the fibration is isotrivial, we recover a result of Kim--Laza--Martin, proving that its fibers are isog

Bokang Zhang, Zhikun Zhang, Haodong Jiang, Yang Liu

Federated learning is a distributed machine learning paradigm that enables collaborative training across multiple parties while ensuring data privacy. Gradient Boosting Decision Trees (GBDT), such as XGBoost, have gained popularity due to their high performance and strong interpretability. Therefore, there has been a growing interest in adapting XGBoost for

Yiyang Shao, Xiaoyu Huang, Bike Zhang, Qiayuan Liao

General-purpose humanoid robots are expected to interact intuitively with humans, enabling seamless integration into daily life. Natural language provides the most accessible medium for this purpose. However, translating language into humanoid whole-body motion remains a significant challenge, primarily due to the gap between linguistic understanding and phy

Zheng Hao, Gaolei Zhao, Haoran Li, Jizhang Zhang

Two-dimensional (2D) layered ferroelectrics, as an emerging area of research, have attracted extensive attention, while memristors based on new 2D ferroelectric materials have yet to be fully explored, thereby limiting their applications in modern nanoelectronics. In this work, we report the observation of intrinsic memristive behavior in a newly discovered

Han Wang, Ana B. Villas Bôas, Jacques Vanneste, William R. Young

Currents modulate the energy of surface gravity waves, leading to spatial inhomogeneities in significant wave height (SWH). Previous work indicates that the overall scale of the inhomogeneities is set by the scale of the currents, that the inhomogeneities are strongly anisotropic even for isotropic currents, and that the rotational and divergent components o

Shengqian Wang

Massage therapy training emphasizes hands-on techniques and effective therapist--patient communication. However, many educational programs struggle to provide realistic practice scenarios. To address this problem, we propose TheraQuest, a gamified, web-based simulation platform that employs large language models (LLMs) to generate diverse virtual patients wi

Kamaljeet Singh, Raghunath Sahoo

Heavy-ion collision experiments such as the Large Hadron Collider and the Relativistic Heavy Ion Collider offer a unique platform to study several key properties of the quark-gluon plasma (QGP), a deconfined state of strongly interacting matter. Quarks, being the electrically charged particles, can induce an electric current in the medium in response to the

Michał Czerwiński, Mateusz Mrukiewicz, Mateusz Filipow, Damian Pociecha

The emergence of ferroelectric mesophases in non-chiral liquid crystal (LCs) has sparked fundamental interest in the molecular mechanisms governing polarity. In this study, we investigate how terminal molecular groups influence the formation and stability of polar phases by analyzing six compounds from three homologous series. Specifically, we compare newly

Antonio Rodríguez-Sánchez

We give a pedagogical introduction to the rich phenomenology of hadronic tau decays. These decays provide a unique window into the interplay of electroweak and strong interactions at low energies, as they occur primarily via $W$ exchange after the electroweak quark current hadronizes. In this manuscript, we summarize the basic ingredients required to perform

Kiran Kate, Tejaswini Pedapati, Kinjal Basu, Yara Rizk

Multiple recent studies have documented large language models' (LLMs) performance on calling external tools/functions. Others focused on LLMs' abilities to handle longer context lengths. At the intersection of these areas lies another interesting problem: LLMs' abilities to accurately perform function calls in long context settings. Particularly, when callin

Feiyu Lu, Mengyu Chen, Hsiang Hsu, Pranav Deshpande

Mixed Reality (MR) could assist users' tasks by continuously integrating virtual content with their view of the physical environment. However, where and how to place these content to best support the users has been a challenging problem due to the dynamic nature of MR experiences. In contrast to prior work that investigates optimization-based methods, we are

Ting Qiao, Yingjia Wang, Xing Liu, Sixing Wu

Deep neural networks (DNNs) are vulnerable to backdoor attacks, where an attacker manipulates a small portion of the training data to implant hidden backdoors into the model. The compromised model behaves normally on clean samples but misclassifies backdoored samples into the attacker-specified target class, posing a significant threat to real-world DNN appl

Ke Chen, Anita Yang, Mingying Zhong

In the present paper, we study the diffusion limit of the strong solution to the one-species Vlasov-Maxwell-Boltzmann (VMB) system with initial data near a global Maxwellian. Based on spectral analysis techniques, we prove the convergence and establish the convergence rate of the classical solution to the VMB system towards the solution to the incompressible

Pasin Manurangsi, Warut Suksompong, Tomohiko Yokoyama

Several resource allocation settings involve agents with unequal entitlements represented by weights. We analyze weighted fair division from an asymptotic perspective: if $m$ items are divided among $n$ agents whose utilities are independently sampled from a probability distribution, when is it likely that a fair allocation exist? We show that if the ratio b

Dominik Dorer, Shinsuke Haze, Jing-Lun Li, José P. D'Incao

We demonstrate a method for controlling the outcome of an ultracold chemical few-body reaction by redirecting a tunable fraction of reaction flux from one selected product channel to another one. In the reaction, three ultracold atoms collide to form a diatomic molecule. This product molecule can be produced in various internal states, characterizing the dif

P. Ochner, F. Manzini, V. Oldani, A. Farina

The ASIACO project is an atlas of cometary imaging and spectroscopy obtained from the Asiago Astrophysical Observatory between 2012 and 2024, still ongoing. Up to now, we monitored 41 comets, acquiring broad-band images using the INAF-OAPd 1.82m Copernico and the 0.67/0.92m Schmidt telescopes, as well as low-to-medium resolution spectra with the DFA-UniPd 1.

Jean-Louis Colliot-Thélène

For a smooth projective variety X over an arbitrary field k, we discuss the surjectivity of the Albanese map from the Chow group of zero-cycles of degree zero on X to the group of rational points of the Albanese variety of X. Over arithmetic fields, we use Severi-Brauer fibrations to produce examples where the map is not surjective. For varieties X over the

Adriana R. Raduta, Mikhail V. Beznogov

In numerical simulations of core-collapse supernova and binary neutron stars mergers, information about the energetics and composition of matter is implemented via external tables covering the huge ranges of thermodynamic conditions explored during the astrophysical evolution. More than 120 general-purpose equation of state (EOS) tables have been contributed

Wei Guo, Xiyao Guo, Xin Lan, Hongbao Zhang

Instead of the much more involved covariant counterterm method, we apply the well justified background subtraction method to calculate the first order corrections to Kerr-AdS black hole thermodynamics induced by the higher derivative terms up to the cubic of Riemann tensor, where the computation is further simplified by the decomposition trick for the bulk a

Hao Wei, Wen Wang, Wanli Ni, Wenjun Xu

As a paradigm shift towards pervasive intelligence, semantic communication (SemCom) has shown great potentials to improve communication efficiency and provide user-centric services by delivering task-oriented semantic meanings. However, the exponential growth in connected devices, data volumes, and communication demands presents significant challenges for pr

Vitaly Alekseev, Tom Cuchta, Alexander Lyapin

We define discrete generating series for arbitrary functions \( f \colon \mathbb{Z}^n \rightarrow \mathbb{C} \) and derive functional relations that these series satisfy. For linear difference equations with constant coefficients, we establish explicit functional equations linking the generating series to the initial data, and for equations with polynomial c

Zhongyuan Zhao, Yujun Ming, Ananthram Swami, Kevin Chan

Backpressure (BP) routing and scheduling is a well-established resource allocation method for wireless multi-hop networks, known for its fully distributed operations and proven maximum queue stability. Recent advances in shortest path-biased BP routing (SP-BP) mitigate shortcomings such as slow startup and random walk, but exclusive link-level commodity sele

Michael Rowan-Robinson

In Paper I (Rowan-Robinson 2024), models derived in 2009 to fit mid-infrared (8-24 micron) source counts from the IRAS, ISO and Spitzer missions, were found to provide an excellent fit to deep counts at 7.7-21 mu with JWST, demonstrating that the evolution of dusty star-forming galaxies is well understood. Here the treatment of optical spectral energy distri

Fayçal Aït Aoudia, Jakob Hoydis, Merlin Nimier-David, Baptiste Nicolet

Sionna is an open-source, GPU-accelerated library that, as of version 0.14, incorporates a ray tracer, Sionna RT, for simulating radio wave propagation. A unique feature of Sionna RT is differentiability, enabling the calculation of gradients for the channel impulse responses (CIRs), radio maps, and other related metrics with respect to system and environmen

Shiying Li, Xingqun Qi, Bingkun Yang, Chen Weile

Generating responsive listener head dynamics with nuanced emotions and expressive reactions is crucial for practical dialogue modeling in various virtual avatar animations. Previous studies mainly focus on the direct short-term production of listener behavior. They overlook the fine-grained control over motion variations and emotional intensity, especially i