March 2025 arXiv papers — page 127

Euclid Collaboration, V. Duret, S. Escoffier, W. Gillard

With about 1.5 billion galaxies expected to be observed, the very large number of objects in the Euclid photometric survey will allow for precise studies of galaxy clustering from a single survey, over a large range of redshifts $0.2 < z < 2.5$. In this work, we use photometric redshifts to extract the baryon acoustic oscillation signal (BAO) from the Flagsh

Jamison Sloan, Sachin Vaidya, Nicholas Rivera, Marin Soljačić

Multimode nonlinear optical systems are highly valued for their ability to withstand large amounts of optical power, transmit data with high bandwidth, perform physical computations, generate quantum correlations, and much more. For many of these applications, both classical and quantum noise place limitations on important performance metrics. Moreover, it i

Shuyang Hao, Yiwei Wang, Bryan Hooi, Ming-Hsuan Yang

Deploying large vision-language models (LVLMs) introduces a unique vulnerability: susceptibility to malicious attacks via visual inputs. However, existing defense methods suffer from two key limitations: (1) They solely focus on textual defenses, fail to directly address threats in the visual domain where attacks originate, and (2) the additional processing

Mingming Zhang, Haoze Du, Xuefeng Wang, Junda Chen

To support the boosting interconnect capacity of the AI-related data centers, novel techniques enabled high-speed and low-cost optics are continuously emerging. When the baud rate approaches 200 GBaud per lane, the bottle-neck of traditional intensity modulation direct detection (IM-DD) architectures becomes increasingly evident. The simplified coherent solu

Xinyi Wang, Jiashui Wang, Jinbo Su, Ke Wang

Assembly code analysis and comprehension play critical roles in applications like reverse engineering, yet they face substantial challenges due to low information density and a lack of explicit syntactic structures. While traditional masked language modeling (MLM) approaches do not explicitly focus on natural language interaction, emerging decoder-focused la

Maanav Srihari, Anil Shaji

The Eigenstate Thermalization Hypothesis (ETH) is a framework for discussing thermal behavior originating from chaotic dynamics in isolated many-body quantum systems. The PXP model, where certain states do not thermalize, has been compared with the Sachdev-Ye Kitaev (SYK) model, which is believed to be fully thermalizing. A gate-based quantum circuit approac

Liang Cheng, Tianyi Li, Zhaowei Wang, Tianyang Liu

LLMs are often claimed to be capable of Natural Language Inference (NLI), which is widely regarded as a cornerstone of more complex forms of reasoning. However, recent works show that LLMs still suffer from hallucinations in NLI due to attestation bias, where LLMs overly rely on propositional memory to build shortcuts. To solve the issue, we design an unsupe

Abhishek Kumar, Karunya Shirali, Nicholas J. Mayhall, Sophia E. Economou

Periodically driven quantum systems exhibit many fascinating phenomena absent in equilibrium systems, but their simulation is more challenging than that of static systems. Consequently, quantum simulation of these systems offers greater opportunity for achieving quantum advantage. To build the foundation for simulating time-periodic Hamiltonians, we utilize

Joseph Zuber, Aishwarya Sarkar, Joseph Jennings, Ali Jannesari

Graph Neural Networks (GNN) have demonstrated state-of-the-art performance in numerous scientific and high-performance computing (HPC) applications. Recent work suggests that "souping" (combining) individually trained GNNs into a single model can improve performance without increasing compute and memory costs during inference. However, existing souping algor

Fergus R. Donnan, Dimitra Rigopoulou, Ismael García-Bernete, Laura Bisigello

Characterizing the growth of supermassive Black Holes (SMBHs) is critical to the evolution of galaxies, however the majority of this activity is obscured, rendering traditional tracers of active SMBHs, such as in the restframe optical/UV, ineffective. The mid-infrared has been particularly successful in revealing obscured AGN activity however much of this wo

Alessio Corti, Tim Graefnitz, Helge Ruddat

We introduce a class of singular log schemes in three dimensions and conjecture that log schemes in this class admit log crepant log resolutions. We provide examples as evidence and relate this conjecture to the conjecture made in [4] and the Gross--Siebert program.

Matteo Farina, Massimiliano Mancini, Giovanni Iacca, Elisa Ricci

An old-school recipe for training a classifier is to (i) learn a good feature extractor and (ii) optimize a linear layer atop. When only a handful of samples are available per category, as in Few-Shot Adaptation (FSA), data are insufficient to fit a large number of parameters, rendering the above impractical. This is especially true with large pre-trained Vi

Guo Chen, Xianlong Wang

LP-N and HLP-N are promising high-energy-density materials. However, these materials synthesized under high pressure cannot be maintained stable at ambient conditions. The mechanism behind their instability remains unclear. Our research, based on first-principles calculations and ab initio molecular dynamics simulations, reveals that while not edge exposed,

Zoé Perrin, Nathalie Carrasco, Thomas Gautier, Nathalie Ruscassier

Titan has a climate system with similarities to Earth, including the presence of a thick atmosphere made up of several atmospheric layers. As on Earth, Titan's climate is influenced by several factors: the gaseous species making up the atmosphere, the energy deposited on the satellite, and solid organic aerosols. Indeed, numerous observations have revealed t

Juan Sebastian Numpaque-Roa

In this work we introduce a notion of tensor product of (twisted) quiver representations with relations in the category of $\mathcal{O}_X$-modules. As a first application of our notion, we see that tensor products of polystable quiver bundles are polystable and later we use this to both deduce a quiver version of the Segre embedding and to identify distingui

Jeremy Beard, Marcos Mazari-Armida

We study the spectrum of limit models assuming the existence of a nicely behaved independence notion. Under reasonable assumptions, we show that all `long' limit models are isomorphic, and all `short' limit models are non-isomorphic. $\textbf{Theorem.}$ Let $\mathbf{K}$ be a $\aleph_0$-tame abstract elementary class stable in $\lambda \geq \operatorname{LS}(

Ivar S. Haugerud, Hidde D. Vuijk, Job Boekhoven, Christoph A. Weber

In living cells, cycles of formation and dissolution of liquid droplets can mediate biological functions such as DNA repair. However, the minimal physicochemical prerequisite for such droplet oscillations remains elusive. Here, we present a simple model composed of only two independent chemical components with their diffusive and chemical fluxes governed by

Hans Christiansen, Max Geier, Brian M. Andersen, Andreas Kreisel

The heavy-fermion compound UTe$_2$ is a candidate for hosting intrinsic spin-triplet superconductivity. At present, however, the type of triplet Cooper pairing realized in UTe$_2$ remains unknown, which calls for further experimental and theoretical investigations. In this paper, we develop a microscopic minimal model for the superconducting phases of UTe$_2

Anthony Hastir, Birgit Jacob, Hans Zwart

We derive an explicit solution to the operator Riccati equation solving the Linear-Quadratic (LQ) optimal control problem for a class of boundary controlled hyperbolic partial differential equations (PDEs). Different descriptions of the system are used to obtain different representations of the operator Riccati equation. By means of an example, we illustrate

Xuanqi Zhang, Jieun Lee, Chris Joslin, Wonsook Lee

We present a novel framework for enhancing the visual fidelity and consistency of text-guided 3D Gaussian Splatting (3DGS) editing. Existing editing approaches face two critical challenges: inconsistent geometric reconstructions across multiple viewpoints, particularly in challenging camera positions, and ineffective utilization of depth information during i

John Augustine, Christian Scheideler, Julian Werthmann

We introduce a new framework for distributed computing that extends and refines the standard master-worker approach of scheduling multi-threaded computations. In this framework, there are different roles: a supervisor, a source, a target, and a collection of workers. Initially, the source stores some instance $I$ of a computational problem, and at the end, t

Glenn Palmer, Narat Srivali, David B. Dunson

Obstructive Sleep Apnea (OSA) is a breathing disorder during sleep that affects millions of people worldwide. The diagnosis of OSA often occurs through an overnight polysomnogram (PSG) sleep study that generates a massive amount of physiological data. However, despite the evidence of substantial heterogeneity in the expression and symptoms of OSA, diagnosis

Jia-Lin Chen, Zhen Fan, Bo Zhan, Jiahang Hu

We investigate the thermodynamic properties of the Hubbard model on the Bethe lattice with a coordination number of 3 using the thermal canonical tree tensor network method. Our findings reveal two distinct thermodynamic phases: a low-temperature antiferromagnetic phase, where spin SU(2) symmetry is broken, and a high-temperature paramagnetic phase. A key fe

Michal Stano

The main goal of this thesis is to study the gravitational action for the Schwarzschild black hole and its subsequent regularisation from the perspective of general relativity and teleparallel gravity. The standard approach of general relativity requires the Einstein-Hilbert action to be supplemented with the Gibbons-Hawking-York (GHY) boundary term whenever

Karol A. Bacik, Jan Ondras, Aaron Rudkin, Jörn Dunkel

Lobbying networks constitute complex political systems that mobilize vast human and financial resources to influence governmental decision-making, often with profound national and global consequences. A comprehensive understanding of lobbying strategies and dynamics requires time-resolved, system-wide data, which are largely unavailable for most political sy

Jennifer C. Yee, Scott J. Kenyon

The mass function (MF) of isolated objects measured by microlensing consists of both a stellar and a planetary component. We compare the microlensing MFs of Gould et al (2022) and Sumi et al (2023) to other measurements of the MF. The abundance of brown dwarfs in the Sumi et al (2023) stellar MF is consistent with measurements from the local solar neighborho

Janik Potten, Yasir Iqbal, Ronny Thomale, Tobias Müller

The functional renormalization group (FRG) approach for spin models relying on a pseudo-fermionic description has proven to be a powerful technique in simulating ground state properties of strongly frustrated magnetic lattices. A drawback of the FRG framework is that it is formulated in the imaginary-time Matsubara formalism and thus only able to access stat

Eliseo Curcio

This study evaluates ethanol blending as a practical near-term strategy for significant transportation decarbonization in the United States. Despite rapid growth in electric vehicle adoption, gasoline is projected to remain dominant, with annual demand around 135 billion gallons by 2035, necessitating immediate complementary solutions. Analysis indicates eth

Scott Armstrong, Vlad Vicol

Anomalous diffusion is the fundamental ansatz of phenomenological theories of passive scalar turbulence, and has been confirmed numerically and experimentally to an extraordinary extent. The purpose of this survey is to discuss our recent result, in which we construct a class of incompressible vector fields that have many of the properties observed in a full

Tianliang Xu, Eva Maxfield Brown, Dustin Dwyer, Sabina Tomkins

Local governments around the world are making consequential decisions on behalf of their constituents, and these constituents are responding with requests, advice, and assessments of their officials at public meetings. So many small meetings cannot be covered by traditional newsrooms at scale. We propose PUBLICSPEAK, a probabilistic framework which can utili

Yin Chen, Shan Ren, Jiawen Shan, Runxuan Zhang

This article explores the structure theory of compatible generalized derivations of finite-dimensional $\omega$-Lie algebras over a field $\mathbb{K}$. We prove that any compatible quasiderivation of an $\omega$-Lie algebra can be embedded as a compatible derivation into a larger $\omega$-Lie algebra, refining the general result established by Leger and Luks

Davide Perego, Matteo Tarocchi

We give sufficient conditions for left- and bi-orderability of fundamental groups of Ore categories in terms of indirect factors, including Thompson groups and many of their generalizations. Besides recovering known results, we prove that braided groups of fractions of digit rewriting systems (which generalize braided Thompson groups to the wider setting of

Bastian Bunzeck, Daniel Duran, Sina Zarrieß

We analyze the influence of utterance-level construction distributions in German child-directed/child-available speech on the resulting word-level, syntactic and semantic competence (and their underlying learning trajectories) in small LMs, which we train on a novel collection of developmentally plausible language data for German. We find that trajectories a

Amol Sasane

Let $\mathscr{H}^\infty$ be the set of all Dirichlet series $f=\sum\limits_{n=1}^\infty \frac{a_n}{n^s}$ (where $a_n\in \mathbb{C}$ for each $n$) that converge at each $s\in {\mathbb{C}}_+$, such that $\|f\|_{\infty}:=\sup_{s\in {\mathbb{C}}_+}|f(s)|<\infty$. Let $\mathscr{B}\subset \mathscr{H}^\infty$ be a Banach algebra containing the Dirichlet polynomials

Srikar Yellapragada, Alexandros Graikos, Kostas Triaridis, Zilinghan Li

The growing volume of high-resolution Whole Slide Images in digital histopathology poses significant storage, transmission, and computational efficiency challenges. Standard compression methods, such as JPEG, reduce file sizes but often fail to preserve fine-grained phenotypic details critical for downstream tasks. In this work, we repurpose autoencoders (AE

Petr Jančar, Jérôme Leroux, Jiří Valůšek

We show that the EXPSPACE-hardness result for structural liveness of Petri nets [Jancar and Purser, 2019] holds even for a simple subclass of conservative nets. As our main result, we prove that for structurally live conservative nets, the values of the minimal live markings are at most doubly exponential in the size of the net. This implies the EXPSPACE-com

Raymond Wiedmann, Kirill Alpin, Moritz M. Hirschmann, Andreas P. Schnyder

Nodal planes, two-dimensional symmetry-enforced band crossings, can carry a topological charge, similar to Weyl points. While the transport properties of Weyl points are well understood, those of nodal planes remain largely unexplored. These properties are influenced not only by the Berry curvature, but also by other quantum geometric quantities. In this wor

Moreno D'Incà, Elia Peruzzo, Xingqian Xu, Humphrey Shi

Vision-language models (VLMs) often inherit the biases and unsafe associations present within their large-scale training dataset. While recent approaches mitigate unsafe behaviors, their evaluation focuses on how safe the model is on unsafe inputs, ignoring potential shortcomings on safe ones. In this paper, we first revise safety evaluation by introducing S

Thi Thuy Nga Nguyen, Clément Dorffer, Frédéric Jourdin, Ronan Fablet

Neural mapping schemes have become appealing approaches to deliver gap-free satellite-derived products for sea surface tracers. The generalization performance of these learning-based approaches naturally arises as a key challenge. This is particularly true for satellite-derived ocean colour products given the variety of bio-optical variables of interest, as

Aritra Biswas

We propose a set of optimized observables using penguin mediated $\bar{B}_d$ and $\bar{B}_s$ decays to $K^{(*)}\bar{K}^{(*)}$ and $K^*\phi$ final states that exhibhit a reduced sensitivity to power corrections than the corresponding branching ratios. Using these observables, branching ratios for the related vector-vector and pseudoscalar-pseudoscalar modes a

Zhiliang Chen, Xinyuan Niu, Chuan-Sheng Foo, Bryan Kian Hsiang Low

Large language models (LLMs) are used in chatbots or AI assistants to hold conversations with a human user. In such applications, the quality (e.g., user engagement, safety) of a conversation is important and can only be exactly known at the end of the conversation. To maximize its expected quality, conversation planning reasons about the stochastic transiti

Enea Di Dio, Sveva Castello, Camille Bonvin

The light that we receive from clusters of galaxies is redshifted by the presence of the clusters' gravitational potential. This effect, known as gravitational redshift, was first detected from a sample of stacked clusters in 2011, by taking redshift differences between the centre of each cluster and the respective member galaxies. However, the interpretatio

Adrian Lopez, L. Mahadevan

We consider the problem of inverting the artifacts associated with scanning a page from an open book, i.e. "xeroxing." The process typically leads to a non-uniform combination of distortion, blurring and darkening owing to the fact that the page is bound to a stiff spine that causes the sheet of paper to be bent inhomogeneously. Complementing purely data-dri

Gianni Manno, Filippo Salis

In this paper, we provide necessary and sufficient conditions for the existence of para-Kaehler immersions in para-Kaehler space forms. As a consequence, we prove that, in general, a local para-Kaehler immersion cannot be globally extended, even if it is defined on a simply connected para-Kaehler manifold. Finally, we classify para-Kaehler immersions between

Ji Tong Wang, Nicolae C. Panoiu

Optical bound-states in the continuum (BICs) have greatly enriched the field of nonlinear optics with novel ways to control and manipulate light-matter interaction at the nanoscale. This has been made possible by their unique physical properties, including effective confinement of light, non-trivial topological features, and robustness upon the propagation o

Ke-Xin Gao, Yuan Zhang, Shi-Lei Su, Gang Chen

A recent experiment demonstrated delayed superradiance from strontium-88 atoms, which are coupled to a longitudinal mode of a cavity while being excited by laser pulses propagating along a transversal direction [Nat. Commun. 15, 1084 (2024)]. A coherent picture of the atomic ensemble dynamics in this experiment requires complementary representations of the e

Weiming Ren, Wentao Ma, Huan Yang, Cong Wei

State-of-the-art transformer-based large multimodal models (LMMs) struggle to handle hour-long video inputs due to the quadratic complexity of the causal self-attention operations, leading to high computational costs during training and inference. Existing token compression-based methods reduce the number of video tokens but often incur information loss and

Moritz Engl, Wassim Hamouda, Ines Häusler, Suzanne Lancaster

The pristine state of hafnium based ferroelectric devices exhibits various unwanted properties, such as imprint and peak splitting, which diminish with bipolar cycling. The incorporation of a niobium oxide layer at different positions in metal-ferroelectric-metal and metal-ferroelectric-insulator-metal stacks is used to modify the pristine state of the devic

Oscar Bouverot-Dupuis, Alberto Rosso, Manon Michel

We design an enhanced Event-Chain Monte Carlo algorithm to study 1D quantum dissipative systems, using their bosonized representation. Expressing the bosonized Hamiltonian as a path integral over a scalar field enables the application of Monte Carlo algorithms developed for classical systems. Specifically, we focus on a dissipative XXZ spin chain, exhibiting

Ahmed Nassar, Andres Marafioti, Matteo Omenetti, Maksym Lysak

We introduce SmolDocling, an ultra-compact vision-language model targeting end-to-end document conversion. Our model comprehensively processes entire pages by generating DocTags, a new universal markup format that captures all page elements in their full context with location. Unlike existing approaches that rely on large foundational models, or ensemble sol

Jian Qian, Teck Lun Goh, Bingyu Xie, Chengyao Zhu

Biological signals, such as electroencephalograms (EEGs) and electrocardiograms (ECGs), play a pivotal role in numerous clinical practices, such as diagnosing brain and cardiac arrhythmic diseases. Existing methods for biosignal classification rely on Attention-based frameworks with dense Feed Forward layers, which lead to inefficient learning, high computat

Guangya Cai

Selecting a subset of the $k$ "best" items from a dataset of $n$ items, based on a scoring function, is a key task in decision-making. Given the rise of automated decision-making software, it is important that the outcome of this process, called top-$k$ selection, is fair. Here we consider the problem of identifying a fair linear scoring function for top-$k$

Chuanwei Gao, Diankun Liu, Yakun Xi

In this paper, we study curved Kakeya sets associated with phase functions satisfying Bourgain's condition. In particular, we show that the analysis of curved Kakeya sets arising from translation-invariant phase functions under Bourgain's condition, as well as Nikodym sets on manifolds with constant sectional curvature, can be reduced to the study of standar

Adarsh Vatsa, Pratyush Patel, William Eiers

Cloud compute systems allow administrators to write access control policies that govern access to private data. While policies are written in convenient languages, such as AWS Identity and Access Management Policy Language, manually written policies often become complex and error prone. In this paper, we investigate whether and how well Large Language Models

Messi H. J. Lee, Calvin K. Lai

Implicit biases refer to automatic mental processes that shape perceptions, judgments, and behaviors. Previous research on "implicit bias" in LLMs focused primarily on outputs rather than the processes underlying the outputs. We present the Reasoning Model Implicit Association Test (RM-IAT) to study implicit bias-like processing in reasoning models, LLMs tha

Cécile Aprili, Gwennou Coupier, Élise Lorenceau, Benjamin Dollet

Aqueous foams are solid materials composed of gases and liquids, exhibiting a large gas/liquid surface area and enabling dynamic exchanges between their fluid components. The structure of binary-gas foams, whose bubbles consist of a mixture of two gases having different affinities with the liquid, thus offers real potential for the dynamic separation of thes

Tianrui Pan, Lin Liu, Jie Liu, Xiaopeng Zhang

Portrait video editing focuses on modifying specific attributes of portrait videos, guided by audio or video streams. Previous methods typically either concentrate on lip-region reenactment or require training specialized models to extract keypoints for motion transfer to a new identity. In this paper, we introduce a training-free universal portrait video ed

F. Wang, N. Cooper, D. Johnson, B. Hopton

The development of quantum technology has opened up exciting opportunities to revolutionize computing and communication, timing and navigation systems, enable non-invasive imaging of the human body, and probe fundamental physics with unprecedented precision. Alongside these advancements has come an increase in experimental complexity and a correspondingly gr

Tomoaki Okayama

Sinc-collocation methods for Volterra-Fredholm integral equations of the second kind were proposed independently by multiple authors: by Shamloo et al. in 2012 and by Mesgarani and Mollapourasl in 2013. Their theoretical analyses and numerical experiments suggest that the presented methods can attain root-exponential convergence. However, their convergence h

Jielan Li, Zekun Chen, Qian Wang, Han Yang

Heat transfer is a fundamental property of matter. Research spanning decades has attempted to discover materials with exceptional thermal conductivity, yet the upper limit remains unknown. Using deep learning accelerated crystal structure prediction and first-principles calculation, we systematically explore the thermal conductivity landscape of inorganic cr

A. Morozov

A modification of the optical model for rough surfaces, implemented in Geant4 as a part of the unified model, is suggested. The modified model takes into account the variation of the interaction probability of the photon with the microfacet based on the relative orientation of the photon and the sampled microfacet's normal. The implementation is using a reje

Abida Sultana, Cezary Adamczyk, Mayukh Roy Chowdhury, Adrian Kliks

Conflict Mitigation (CM) in Open Radio Access Network (O-RAN) is a topic that is gaining importance as commercial O-RAN deployments become more complex. Although research on CM is already covered in terms of simulated network scenarios, it lacks validation using real-world deployment and Over The Air (OTA) Radio Frequency (RF) transmission. Our objective is

David Emukpere, Romain Deffayet, Bingbing Wu, Romain Brégier

Learning robotic manipulation skills from vision is a promising approach for developing robotics applications that can generalize broadly to real-world scenarios. As such, many approaches to enable this vision have been explored with fruitful results. Particularly, object-centric representation methods have been shown to provide better inductive biases for s

Yang Wang, Alexander N. Craddock, Jaeda M. Mendoza, Rourke Sekelsky

Entanglement distribution through existing telecommunication infrastructure is crucial for realizing large-scale quantum networks. However, distance limitations imposed by photon losses and the no-cloning theorem present significant challenges. Quantum repeaters based on entangled telecom wavelength photons and quantum memories offer a promising solution to

Fang Zhang, Jiawei Ruan, Gurjyot Sethi, Chen Hu

An excitonic insulator$^{1,2}$ (EI) is a correlated many-body state of electron-hole pairs, potentially leading to high-temperature condensate and superfluidity$^{3-7}$. Despite ever-growing experiments suggesting possible EI states in various materials, direct proofs remain elusive and debated. Here we address the problem by introducing an ab initio methodo

Franco Caspe, Jordie Shier, Mark Sandler, Charalampos Saitis

Neural Audio Synthesis (NAS) models offer interactive musical control over high-quality, expressive audio generators. While these models can operate in real-time, they often suffer from high latency, making them unsuitable for intimate musical interaction. The impact of architectural choices in deep learning models on audio latency remains largely unexplored

Shan Huang, Yi Ji, Leyu Lin

The pervasive rise of digital platforms has reshaped how individuals engage with information, with algorithms and peer influence playing pivotal roles in these processes. This study investigates the effects of algorithmic curation and peer influence through social cues (e.g., peer endorsements) on engagement with novel content. Through a randomized field exp

Anderson da Silva-Andrade, Diogo Souto

We present metallicities derived from a sample of eleven M dwarfs belonging to wide binary systems with warmer FG primary companions observed by the high-resolution (R=22,500) near-infrared SDSS-IV APOGEE spectra. Using a plane-parallel one-dimensional local thermodynamic equilibrium (LTE) abundance analysis, we determine effective temperatures ($T_{\rm eff}

Alexis A. A. Delgado, Devin A. Matthews

Orbital relaxation of the core region is a primary source of error in the computation of core ionization and core excitation energies. Recently, Transition-Potential Coupled Cluster (TP-CC) methods have been used to explicitly treat orbital relaxation using non-variational molecular orbitals determined by reoccupation of orbitals optimized for a fractional c

Jing Bi, Junjia Guo, Susan Liang, Guangyu Sun

Visual reasoning is central to human cognition, enabling individuals to interpret and abstractly understand their environment. Although recent Multimodal Large Language Models (MLLMs) have demonstrated impressive performance across language and vision-language tasks, existing benchmarks primarily measure recognition-based skills and inadequately assess true

Daniele Masti, Davide Grande, Andrea Peruffo, Filippo Fabiani

Actuator faults heavily affect the performance and stability of control systems, an issue that is even more critical for systems required to operate autonomously under adverse environmental conditions, such as unmanned vehicles. To this end, passive fault-tolerant control (PFTC) systems can be employed, namely fixed-gain control laws that guarantee stability

Gaetan de Rassenfosse

Firms' decisions to patent innovations involve a complex evaluation of costs, benefits, and strategic considerations. This article explores the economic and practical factors that influence whether companies seek patent protection. It discusses explicit monetary costs--such as legal fees, filing, and international expenses--and non-monetary costs related to

Nadia Loy, Andrea Tosin

In this paper, we present a critical collection of essential mathematical tools and techniques for the analysis of Boltzmann-type kinetic equations, which in recent years have established themselves as a flexible and powerful paradigm to model interacting multi-agent systems. We consider, in particular, scalar equations implementing linear symmetric interact

German Neubaum, Irene-Angelica Chounta, Eva Gredel, David Wiesche

This research explores whether the rapid digital transformation due to COVID-19 managed to close or exacerbate the digital divide concerning users' digital skills. We conducted a pre-registered survey with N = 1143 German Internet users. Our findings suggest the latter: younger, male, and higher educated users were more likely to improve their digital skills

A. Bonaldi, P. Hartley, R. Braun, S. Purser

We present and analyse the results of the Science data challenge 3a (SDC3a, https://sdc3.skao.int/challenges/foregrounds), an EoR foreground-removal community-wide exercise organised by the Square Kilometre Array Observatory (SKAO). The challenge ran for 8 months, from March to October 2023. Participants were provided with realistic simulations of SKA-Low da

Mattia Merluzzi, Miltiadis C. Filippou

We study the problem of spectrum sharing between goal-oriented (GO) and legacy data-oriented (DO) systems. For the former, data quality and representation is no longer optimized based on classical communication key performance indicators, but rather configured on the fly to achieve the goal of communication with the least resource overhead. This paradigm can

Moju Zhao

In this paper, I present vectorable thrust control for different locomotion modes by a novel quadruped robot, SPIDAR, equipped with vectoring rotor in each link. First, the robot's unique mechanical design, the dynamics model, and the basic control framework for terrestrial/aerial locomotion are briefly introduced. Second, a vectorable thrust control method

Yurij Salmaniw, Di Liu, Junping Shi, Hao Wang

Nonlocal aggregation-diffusion models, when coupled with a spatial map, can capture cognitive and memory-based influences on animal movement and population-level patterns. In this work, we study a one-dimensional reaction-diffusion-aggregation system in which a population's spatiotemporal dynamics are tightly linked to a separate, dynamically updating map. D

Ahmadreza Jeddi, Negin Baghbanzadeh, Elham Dolatabadi, Babak Taati

The computational demands of Vision Transformers (ViTs) and Vision-Language Models (VLMs) remain a significant challenge due to the quadratic complexity of self-attention. While token pruning offers a promising solution, existing methods often introduce training overhead or fail to adapt dynamically across layers. We present SAINT, a training-free token prun

J. W. Moffat

This paper examines the Higgs particle self-coupling and its implications for electroweak symmetry breaking in the Standard Model. We review the current experimental constraints on the Higgs trilinear coupling and discuss the challenges in measuring it precisely. The potential consequences of deviations from the Standard Model prediction are explored, includ

Vyacheslav Ivanovskiy, Dmitry Ponomarev

We use the light-cone gauge formalism to study interactions of point particles with massless higher-spin fields. By analysing the light-cone consistency conditions at the subleading order in higher-spin fields, we find that no local interactions of point particles with chiral higher-spin fields are possible. Considering that chiral higher-spin theories form

Brad T. Aagaard, Scott Marshall, Sarah Minson, Dan Boyd

The California Community Earth Models for Seismic Hazard Assessments Workshop (https://www.scec.org/workshops/2024/california-community-models, accessed December 16, 2024) was held online on March 4-5, 2024, with more than 200 participants over two days. In this report, we provide a summary of the key points from the presentations and discussions. We highlig

Parsa Rahimi, Damien Teney, Sebastien Marcel

The increasing reliance on large-scale datasets in machine learning poses significant privacy and ethical challenges, particularly in sensitive domains such as face recognition. Synthetic data generation offers a promising alternative; however, most existing methods depend heavily on external datasets or pre-trained models, increasing complexity and resource

Wystan Benbow, Jodi Christiansen, Julia Francescutti, Garrett Kunkler

VERITAS began full-scale operations in 2007 and it remains one of the world's most sensitive very-high-energy (VHE; E >100 GeV) gamma-ray observatories. More than 8,300 hours (~50%) of its good-weather data were targeted on active galactic nuclei (AGN). Many of these observations were taken as part of an ongoing comprehensive program to discover new VHE AGN.

Pham Huu Tiep, Alexandre Zalesski

Extending earlier results of the authors on minimal polynomials of $p$-elements of finite groups of Lie type in cross-characteristic representations, this paper focuses on the case where Sylow $p$-subgroups are cyclic and $p$ is distinct from the representation field characteristic.

Simone Baldassarri, Nikolai Kriukov

In this paper we consider two-opinion voter models on dynamic random graphs, in which the joint dynamics of opinions and graphs acts as one-way feedback, i.e., edges appear and disappear over time depending on the opinions of the two connected vertices, while the opinion dynamics is not affected by the graph structure. Our goal is to investigate the joint ev

Yu Yamane, Takahiro Onimaru, Yasuyuki Shimura, Suguru Tsuda

A diluted non-Kramers doublet system Y$_{1-x}$Pr$_x$Ir$_2$Zn$_{20}$ is a promising candidate for exhibiting single-site quadrupolar (two-channel) Kondo effect. We have measured temperature-dependent magnetization of a sample for $x$ = 0.028 down to 0.1 K at various constant magnetic fields to extract the characteristic behaviors due to the quadrupolar Kondo

Sebastian Ohrem, Wolfgang Reichel

For Maxwell's equations with nonlinear polarization we prove the existence of time-periodic breather solutions travelling along slab or cylindrical waveguides. The solutions are TE-modes which are localized in space directions orthogonal to the direction of propagation. We assume a magnetically inactive and electrically nonlinear material law with a linear $

Ayush Paliwal, Oliver Schlenczek, Birte Thiede, Manuel Santos Pereira

Reconstructing the 3D location and size of microparticles from diffraction images - holograms - is a computationally expensive inverse problem that has traditionally been solved using physics-based reconstruction methods. More recently, researchers have used machine learning methods to speed up the process. However, for small particles in large sample volume

Kavindri Ranasinghe, Adam L. Baskerville, Geoffrey P. F. Wood, Gerhard Koenig

Neural network potentials trained on quantum-mechanical data can calculate molecular interactions with relatively high speed and accuracy. However, neural network potentials might exhibit instabilities, nonphysical behavior, or lack accuracy. To assess the reliability of neural network potentials, a series of tests is conducted during model training, in the

Freddie Jensen, Edward James Brambley

We develop a weakly nonlinear model of duct acoustics in two and three dimensions (without flow). The work extends the previous work of McTavish & Brambley (2019, J. Fluid Mech. 875, pp. 411-447) to three dimensions and significantly improves the numerical efficiency. The model allows for general curvature and width variation in two-dimensional ducts, and ge

Mario Scrocca, Lina Molinas Comet, Benjamin Witsch, Daham Mohammed Mustafa

Integrated and efficient mobility requires data sharing among the involved stakeholders. In this direction, regulators and transport authorities have been defining policies to foster the digitalisation and online publication of mobility data. However, the creation of several heterogeneous data portals for mobility data resulted in a fragmented ecosystem that

Di Zheng, Riccardo Scarfiello, Muhammad Fayyaz Kashif, Liam Collard

We present an innovative fabrication method to achieve bottom-up in situ surface-overstructured Au nanoislands (NIs) with tunable grades of surface coverage, elongation, and branching, directly on micro-optical fibers for sensing applications. These all-in-gold hierarchical nanostructures consist of NIs coated with surface protrusions of various morphologies

Xichen Liang, Kseniia M. Karnaukh, Qixuan Cao, Marielle Cooper

Control of bubble motion is essential for improving efficiency and creating new functionalities in electrochemistry, heat transfer, and biomedical systems. Photoresponsive surfactants enable bubble manipulation by creating surface tension gradients, inducing a photo-Marangoni flow under illumination, without needing any engineered substrates, by leveraging a

Clément Dorffer, Frédéric Jourdin, Thi Thuy Nga Nguyen, Rodolphe Devillers

Monitoring optical properties of coastal and open ocean waters is crucial to assessing the health of marine ecosystems. Deep learning offers a promising approach to address these ecosystem dynamics, especially in scenarios where gap-free ground-truth data is lacking, which poses a challenge for designing effective training frameworks. Using an advanced neura

Zonghan Li, Song Tong, Yi Liu, Kaiping Peng

The increasing amount of pressure related to water and energy shortages has increased the urgency of cultivating individual conservation behaviors. While the concept of nudging, i.e., providing usage-based feedback, has shown promise in encouraging conservation behaviors, its efficacy is often constrained by the lack of targeted and actionable content. This

F. Castillo, N. A. Moraga, M. E. Gusakov, J. A. Valdivia

This paper addresses the evolution of an axially symmetric magnetic field in the core of a neutron star. The matter in the core is modeled as a system of two fluids, namely neutrons and charged particles, with slightly different velocity fields, controlled by their mutual collisional friction. This problem was addressed in our previous work through the so-ca

Junwoo Park, Nataliya Sokolovska, Clément Cabriel, Ignacio Izeddin

In recent years, the segmentation of short molecular trajectories with varying diffusive properties has drawn particular attention of researchers, since it allows studying the dynamics of a particle. In the past decade, machine learning methods have shown highly promising results, also in changepoint detection and segmentation tasks. Here, we introduce a nov

Christine Johnson, Ben Shipway, Thomas Melvin, Thomas Bendall

This paper explores how to adapt a new dynamical core to enable its use in one-way nested regional weather and climate models, where lateral boundary conditions (LBCs) are provided by a lower-resolution driving model. The dynamical core has recently been developed by the Met Office and uses an iterated-semi-implicit time discretisation and mixed finite-eleme

Luke Murray Kearney, Emma L. Davis, Matt J. Keeling

Capturing the structure of a population and characterising contacts within the population are key to reliable projections of infectious disease. Two main elements of population structure -- contact heterogeneity and age -- have been repeatedly demonstrated to be key in infection dynamics, yet are rarely combined. Regarding individuals as nodes and contacts a