December 2024 arXiv papers — page 67

Marie-Félicia Béclin, Pierre Lafaye de Micheaux, Nicolas Molinari, Frédéric Ouimet

This paper introduces a new objective measure for assessing treatment response in asthmatic patients using computed tomography (CT) imaging data. For each patient, CT scans were obtained before and after one year of monoclonal antibody treatment. Following image segmentation, the Hounsfield unit (HU) values of the voxels were encoded through quantile functio

Chirag Shah, Ryen W. White

In the midst of the growing integration of Artificial Intelligence (AI) into various aspects of our lives, agents are experiencing a resurgence. These autonomous programs that act on behalf of humans are neither new nor exclusive to the mainstream AI movement. By exploring past incarnations of agents, we can understand what has been done previously, what wor

Baptiste Filoche, Stefan Hohenegger, Taro Kimura

$A$-type Little String Theories (LSTs) are engineered from parallel M5-branes on a circle $\mathbb{S}_\perp^1$, probing a transverse $\mathbb{R}^4/\mathbb{Z}_M$ background. Below the scale of the radius of $\mathbb{S}_\perp^1$, these theories resemble a circular quiver gauge theory with $M$ nodes of gauge group $U(N)$ and matter in the bifundamental represen

Isadora Krsek, Anubha Kabra, Yao Dou, Tarek Naous

In pseudonymous online fora like Reddit, the benefits of self-disclosure are often apparent to users (e.g., I can vent about my in-laws to understanding strangers), but the privacy risks are more abstract (e.g., will my partner be able to tell that this is me?). Prior work has sought to develop natural language processing (NLP) tools that help users identify

Elena Cuoco, Marco Cavaglià, Ik Siong Heng, David Keitel

This article provides an overview of the current state of machine learning in gravitational-wave research with interferometric detectors. Such applications are often still in their early days, but have reached sufficient popularity to warrant an assessment of their impact across various domains, including detector studies, noise and signal simulations, and t

Boaz Klartag, Joseph Lehec

We provide the final step in the resolution of Bourgain's slicing problem in the affirmative. Thus we establish the following theorem: for any convex body $K \subseteq \mathbb{R}^n$ of volume one, there exists a hyperplane $H \subseteq \mathbb{R}^n$ such that $$ Vol_{n-1}(K \cap H) > c, $$ where $c > 0$ is a universal constant. Our proof combines Milman's th

Ion Grama, Michael Nussbaum

We develop a Hungarian construction for the partial sum process of independent non-identically distributed random variables. The process is indexed by functions $f$ from a class $\mathcal{H}$, but the supremum over $f\in $ $\mathcal{H}$ is taken outside the probability. This form is a prerequisite for the Koml\'{o}s-Major-Tusn\'{a}dy inequality in the space

Aymeric Fromherz, Jonathan Protzenko

The popularity of the Rust language continues to explode; yet, many critical codebases remain authored in C. Automatically translating C to Rust is thus an appealing course of action. Several works have gone down this path, handling an ever-increasing subset of C through a variety of Rust features, such as unsafe. While the prospect of automation is appealin

Guillermo Briseno-Sanchez, Nadja Klein, Andreas Groll, Andreas Mayr

We propose a highly flexible distributional copula regression model for bivariate time-to-event data in the presence of right-censoring. The joint survival function of the response is constructed using parametric copulas, allowing for a separate specification of the dependence structure between the time-to-event outcome variables and their respective margina

Yuke Cai, Davide Plozza, Steven Marty, Paul Joseph

Time of Flight ToF cameras renowned for their ability to capture realtime 3D information have become indispensable for agile mobile robotics These cameras utilize light signals to accurately measure distances enabling robots to navigate complex environments with precision Innovative depth cameras characterized by their compact size and lightweight design suc

Felix Joos, Marcus Kühn

Let $k\geq 2$ and fix a $k$-uniform hypergraph $\mathcal{F}$. Consider the random process that, starting from a $k$-uniform hypergraph $\mathcal{H}$ on $n$ vertices, repeatedly deletes the edges of a copy of $\mathcal{F}$ chosen uniformly at random and terminates when no copies of $\mathcal{F}$ remain. Let $R(\mathcal{H},\mathcal{F})$ denote the number of ed

Sylvain Nascimbene, Jean Dalibard

An optical flux lattice is a set of light beams that couple different internal states of an atom, thereby producing topological energy bands. Here we present a configuration in which the atoms exhibit a dark state, i.e. an internal state that is not coupled to the light. At large light intensity, the low-energy dynamics is restricted to the dark state, leadi

Georgios Antoniou, Leonardo Gualtieri, Paolo Pani

We study the gravitational perturbations of black holes in quadratic gravity, in which the Einstein-Hilbert term is supplemented by quadratic terms in the curvature tensor. In this class of theories, the Schwarzschild solution can coexist with modified black hole solutions, and both families are radially stable in a wide region of the parameter space. Here w

Felix Friedrich, Simone Tedeschi, Patrick Schramowski, Manuel Brack

Building safe Large Language Models (LLMs) across multiple languages is essential in ensuring both safe access and linguistic diversity. To this end, we conduct a large-scale, comprehensive safety evaluation of the current LLM landscape. For this purpose, we introduce M-ALERT, a multilingual benchmark that evaluates the safety of LLMs in five languages: Engl

Nolwenn Le Quellec

We study the orthospectrum and the simple orthospectrum of compact hyperbolic surfaces with geodesic boundary. We show that there are finitely many hyperbolic surfaces sharing the same simple orthospectrum and finitely many hyperbolic surfaces sharing the same orthospectrum. Then, we show that generic surfaces are determined by their orthospectrum and by the

Kerwann Tep, Christophe Pichon, Michael S Petersen

This paper investigates the linear response of a series of spheroidal stellar clusters, the Kuzmin-Kutuzov St\"ackel family, which exhibit a continuous range of flattening and rotation, extending from an isochrone sphere to a Toomre disk. The method successfully replicates the growing modes previously identified in published $N$-body simulations. It relies o

Mang Ning, Mingxiao Li, Jianlin Su, Haozhe Jia

This paper explores image modeling from the frequency space and introduces DCTdiff, an end-to-end diffusion generative paradigm that efficiently models images in the discrete cosine transform (DCT) space. We investigate the design space of DCTdiff and reveal the key design factors. Experiments on different frameworks (UViT, DiT), generation tasks, and variou

Advait Sarkar, Xiaotong, Xu, Neil Toronto

Generative AI, with its tendency to "hallucinate" incorrect results, may pose a risk to knowledge work by introducing errors. On the other hand, it may also provide unprecedented opportunities for users, particularly non-experts, to learn and apply advanced software features and greatly increase the scope and complexity of tasks they can successfully achieve

Mahmoud Filali, Jorge Galindo

A long standing problem in abstract harmonic analysis concerns the strong Arens irregularity (sAir, for short) of the Fourier algebra $A(G)$ of a locally compact group $G.$ The groups for which $A(G)$ is known to be sAir are all amenable. So far this class includes the abelian groups, the discrete amenable groups, the second countable amenable groups $G$ suc

Gareth C. Jones, Rebecca A. A. Bowler, Andrew J. Bunker, Mirko Curti

We present JWST/NIRSpec IFU observations of the z=7.152 galaxy system B14-65666, as part of the GA-NIFS survey. Line and continuum emission in this massive system (log10(M*/Msol)=9.8+/-0.2) is resolved into two strong cores surrounded by diffuse emission, as seen in recent JWST/NIRCam imaging. Our dataset contains detections of [OII]3726,3729, [NeIII]3869,39

Spyridon Kakaroumpas, Zoe Nieraeth

In this work we fully characterize the classes of matrix weights for which multilinear Calder\'on-Zygmund operators extend to bounded operators on matrix weighted Lebesgue spaces. To this end, we develop the theory of multilinear singular integrals taking values in tensor products of finite dimensional Hilbert spaces. On the one hand, we establish quantitati

Alexandre C. Ricardo, Gubio G. de Lima, Amanda G. Valério, Tiago de S. Farias

Continuous-variable quantum computing utilizes continuous parameters of a quantum system to encode information, promising efficient solutions to complex problems. Trapped-ion systems provide a robust platform with long coherence times and precise qubit control, enabling the manipulation of quantum information through its motional and electronic degrees of fr

Alison Warman, Fan Yang, Apoorv Tiwari, Hannes Pichler

Categorical symmetries have recently been shown to generalize the classification of phases of matter, significantly broadening the traditional Landau paradigm. To test these predictions, we propose a simple spin chain model that encompasses all gapped phases and second-order phase transitions governed by the categorical symmetry $\mathsf{Rep}(D_8)$. This mod

Riccardo Fosco Gramaccioni, Christian Marinoni, Emilian Postolache, Marco Comunità

Traditional sound design workflows rely on manual alignment of audio events to visual cues, as in Foley sound design, where everyday actions like footsteps or object interactions are recreated to match the on-screen motion. This process is time-consuming, difficult to scale, and lacks automation tools that preserve creative intent. Despite recent advances in

Christian Križan, Janka Biznárová, Liangyu Chen, Emil Hogedal

It is advantageous for any quantum processor to support different classes of two-qubit quantum logic gates when compiling quantum circuits, a property that is typically not seen with existing platforms. In particular, access to a gate set that includes support for the CZ-type, the iSWAP-type, and the SWAP-type families of gates, renders conversions between t

Hannah Bossi, Austin Baty, Yi Chen, Yu-Chen Chen

Recently, energy-energy correlators (EECs) have garnered renewed interest for studying hadronic collisions at the Large Hadron Collider (LHC) and the Relativistic Heavy Ion Collider (RHIC). EEC measurements within jets provide a clear scale separation, facilitating the study of both perturbative and non-perturbative Quantum Chromodynamics (QCD) in the collin

Gabriel Béna, Timo Wunderlich, Mahmoud Akl, Bernhard Vogginger

Neuromorphic computing aims to replicate the brain's capabilities for energy efficient and parallel information processing, promising a solution to the increasing demand for faster and more efficient computational systems. Efficient training of neural networks on neuromorphic hardware requires the development of training algorithms that retain the sparsity o

Matteo Quinzi, Tommaso Chiarotti, Marco Gibertini, Andrea Ferretti

In this work we study self-consistent solutions in one-dimensional lattice models obtained via many-body perturbation theory. The Dyson equation is solved in a fully self-consistent manner via the algorithmic-inversion method based on the sum-over-poles representation (AIM-SOP) of dynamical operators. In particular, we focus on the GW approximation, analyzin

Thibault D. Décoppet, Sean Sanford

In arXiv:2211.04917, it was shown that, over an algebraically closed field of characteristic zero, every fusion 2-category is Morita equivalent to a connected fusion 2-category, that is, one arising from a braided fusion 1-category. This result has recently allowed for a complete classification of fusion 2-categories. Here we establish that compact semisimpl

Masoud Elhamiasl, Frederic Jolivet, Ahmadreza Rezaei, Michael Fieseler

Whole-body PET imaging is often hindered by respiratory motion during acquisition, causing significant degradation in the quality of reconstructed activity images. An additional challenge in PET/CT imaging arises from the respiratory phase mismatch between CT-based attenuation correction and PET acquisition, leading to attenuation artifacts. To address these

Jeffrey C. Everts, Robert Hołyst, Karol Makuch

Brownian motion is essential for describing diffusion in systems ranging from simple to complex liquids. Unlike simple liquids, which consist of only a solvent, complex liquids, such as colloidal suspensions or the cytoplasm of a cell, are mixtures of various constituents with different shapes and sizes. Describing Brownian motion in such multiscale systems

Matthew Romney

We construct functions $f \colon [0,1] \to [0,1]$ whose graph as a subset of $\mathbb{R}^2$ has Hausdorff dimension greater than any given value $\alpha \in (1,2)$ but conformal dimension $1$. These functions have the property that a positive proportion of level sets have positive codimension-$1$ measure. This result gives a negative answer to a question of

Emma Schwartzman, Tracy Clarke, Simona Giacintucci, Wendy Peters

We present new radio observations of the galaxy cluster merger CIZA J0107.7+5408 (CIZA0107), a large, roughly equal mass, post-core passage, dissociative binary system at z = 0.1066. CIZA0107 is an elongated, disturbed system, hosting two subclusters with optical galaxy number density peaks offset from their associated X-ray density peaks and double-peaked d

George Trenins, Mariana Rossi

We address the challenge of incorporating non-Markovian electronic friction effects in quantum-mechanical approximations of dynamical observables. A generalized Langevin equation (GLE) is formulated for ring-polymer molecular dynamics (RPMD) rate calculations, which combines electronic friction with a description of nuclear quantum effects (NQEs) for adsorba

Riccardo Munafò, Simone Saitta, Luca Vicentini, Davide Tondi

The MitraClip is the most widely percutaneous treatment for mitral regurgitation, typically performed under the real-time guidance of 3D transesophagel echocardiography (TEE). However, artifacts and low image contrast in echocardiography hinder accurate clip visualization. This study presents an automated pipeline for clip detection from 3D TEE images. An At

Brian D. Williamson, Chloe Krakauer, Eric Johnson, Susan Gruber

In pharmacoepidemiology, safety and effectiveness are frequently evaluated using readily available administrative and electronic health records data. In these settings, detailed confounder data are often not available in all data sources and therefore missing on a subset of individuals. Multiple imputation (MI) and inverse-probability weighting (IPW) are go-

Jingyan Feng, Mohan Zhang, Matteo Fadel, Tim Byrnes

We propose a teleportation protocol involving beam splitting operations and binary-outcome measurements, such as parity measurements. These operations have a straightforward implementation using the dispersive regime of the Jaynes-Cummings Hamiltonian, making our protocol suitable for a broad class of platforms, including trapped ions, circuit quantum electr

Ozgu Goksu, Nicolas Pugeault

Federated Learning offers a solution for decentralised model training, addressing the difficulties associated with distributed data and privacy in machine learning. However, the fact of data heterogeneity in federated learning frequently hinders the global model's generalisation, leading to low performance and adaptability to unseen data. This problem is par

Altti Jääskeläinen, Jussi Toivanen, Asko Hänninen, Ville Kolehmainen

This work introduces a method for preprocessing measurements of electrical impedance tomography to considerably reduce the effect uncertainties in the electrode contacts have on the reconstruction quality, without a need to explicitly estimate the contacts. The idea is to compute the Jacobian matrix of the forward map with respect to the contact strengths an

Yue Wu, Benjamin Grimmer

This work considers the nonconvex, nonsmooth problem of minimizing a composite objective of the form $f(g(x))+h(x)$ where the inner mapping $g$ is a smooth finite summation or expectation amenable to variance reduction. In such settings, prox-linear methods can enjoy variance-reduced speed-ups despite the existence of nonsmoothness. We provide a unified conv

Hao Jiang, Zhaolin Wang, Yuanwei Liu, Arumugam Nallanathan

A Cram\'er-Rao bound (CRB) optimization framework for near-field sensing (NISE) with continuous-aperture arrays (CAPAs) is proposed. In contrast to conventional spatially discrete arrays (SPDAs), CAPAs emit electromagnetic (EM) probing signals through continuous source currents for target sensing, thereby exploiting the full spatial degrees of freedom (DoFs)

Álvaro Gutiérrez

To find crystals of $\mathfrak{sl}_2$ representations of the form $\Lambda^n\text{Sym}^r\mathbb{C}^2$ it suffices to solve the combinatorial problem of decomposing Young's lattice into symmetric, saturated chains. We review the literature on this latter problem, and present a strategy to solve it. For $n \le 4$, the strategy recovers recently discovered solu

Hourun Li, Yifan Wang, Zhiping Xiao, Jia Yang

Recommender systems are widely used in various real-world applications, but they often encounter the persistent challenge of the user cold-start problem. Cross-domain recommendation (CDR), which leverages user interactions from one domain to improve prediction performance in another, has emerged as a promising solution. However, users with similar preference

Enna Basic, Alberto Giaretta

Large Language Models (LLMs) have emerged as powerful tools for automating programming tasks, including security-related ones. However, they can also introduce vulnerabilities during code generation, fail to detect existing vulnerabilities, or report nonexistent ones. This systematic literature review investigates the security benefits and drawbacks of using

Kuanysh Zhussupbekov, Killian Walshe, Brian Walls, Andrei Ionov

Defects introduced to the surface of Bi(111) break the translational symmetry and modify the surface states locally. We present a theoretical and experimental study of the 2D defects on the surface of Bi(111) and the states that they induce. Bi crystals cleaved in ultrahigh vacuum (UHV) at low temperature (110 K) and the resulting ion-etched surface are inve

Shisheng Lin, Shaoqi Huang, Minhui Yang, Xin Chen

Exciton mediated superconductor is a fascinating quantum phase of matter that occurs when excitons become the dominant excitation in materials, which is also very promising for high temperature superconductor. However, there is no experimental report of exciton mediated superconductivity. Herein, we realize exciton mediated superconductivity from exciton ins

Aakash Khandelwal, Ranjan Mukherjee

We introduce a two-dimensional discrete-time dynamical system which represents the evolution of an angle and angular velocity. While the angle evolves by a fixed amount in every step, the evolution of the angular velocity is governed by a nonlinear map. We study the periodicity and stability of solutions to the system for a range of parameter values and init

Wentian Zheng, Shichen Zhang, Jian Jiang, Yipeng He

Nanoconfined water plays an indispensable role in various phenomena in biology, chemistry, and engineering. It exhibits many abnormal properties compared to bulk water, especially under strong confinement. However, the origin of those anomalies is still elusive due to the lack of structural information on hydrogen-bonding networks. Considering the inhomogene

Davide Plozza, Steven Marty, Cyril Scherrer, Simon Schwartz

In the rapidly evolving landscape of autonomous mobile robots, the emphasis on seamless human-robot interactions has shifted towards autonomous decision-making. This paper delves into the intricate challenges associated with robotic autonomy, focusing on navigation in dynamic environments shared with humans. It introduces an embedded real-time tracking pipel

Joseanne Viana, Hamed Farkhari, Pedro Sebastiao, Victor P Gil Jimenez

Unmanned Aerial Vehicles (UAVs) face significant security risks from jamming attacks, which can compromise network functionality. Traditional detection methods often fall short when confronting AI-powered jamming that dynamically modifies its behavior, while contemporary machine learning approaches frequently demand substantial feature engineering and strugg

Bach Nguyen, Tianlong Chen, Shu Yang, Bojian Hou

Recent years have witnessed an emerging trend in neuromorphic computing that centers around the use of brain connectomics as a blueprint for artificial neural networks. Connectomics-based neuromorphic computing has primarily focused on embedding human brain large-scale structural connectomes (SCs), as estimated from diffusion Magnetic Resonance Imaging (dMRI

D. M. Vasileva, K. N. Lyashchenko, O. Yu. Andreev

We investigate the polarization of the electron beam acquired during the inelastic resonant scattering on hydrogen-like ions initially being in the ground state. The formation and subsequent Auger decay of the intermediate (3l3l') doubly excited states in the resonant channel modify the mechanism of polarization change by enhancing both spin-orbit and exchan

Lukas Fußangel, Buddhika Priyasad, Paul Stephan

We investigate regularity properties of minimizers for non-autonomous convex variational integrands $F(x, \mathrm{D} u)$ with linear growth, defined on bounded Lipschitz domains $\Omega \subset \mathbb{R}^n$. Assuming appropriate ellipticity conditions and H\"older continuity of $\mathrm{D}_zF(x,z)$ with respect to the first variable, we establish higher int

Jerome Garnier-Brun, Ruben Zakine, Michael Benzaquen

We study the hydrodynamics of a system of agents who optimize either their individual utility (self-interest) or the collective welfare (cooperation). When agents act selfishly, their interactions are non-reciprocal, driving the system out of equilibrium; by contrast, purely altruistic dynamics restore reciprocity and yield an equilibrium-like description. W

Joel Coacalle, Tiago Picon, Claudio Vasconcelos

In this work, we present sufficient cancellation conditions for the boundedness of inhomogeneous Calder\'on-Zygmund type operators on local Hardy spaces defined over spaces of homogeneous type in the sense of Coifman & Weiss for $ 0<p\leq 1 $. A new approach to atoms and molecules for local Hardy spaces in this setting are introduced with special moment cond

Daniel A. Vajner, Koray Kaymazlar, Fenja Drauschke, Lucas Rickert

Quantum key distribution (QKD) can be used to establish a secret key between trusted parties. Many practical use-cases in communication networks, however, involve parties who do not trust each other. A fundamental cryptographic building block for such distrustful scenarios is quantum coin flipping, which has been investigated only in few experimental studies

Luca Ciambelli, Marc Geiller

When studying gauge theories in the presence of boundaries, local symmetry transformations are typically classified as gauge or physical depending on whether the associated charges vanish or not. Here, we propose that physical charges should further be refined into "dynamical" or "kinematical" depending on whether they are associated with flux-balance laws o

Valentina De Romeri, Dimitrios K. Papoulias, Gonzalo Sanchez Garcia, Christoph A. Ternes

Despite being neutral particles, neutrinos can acquire non-zero electromagnetic properties from radiative corrections that can be induced by the presence of new physics. Electromagnetic neutrino processes induce spectral distortions in neutrino scattering data, which are especially visible at experiments characterized by low recoil thresholds. We investigate

Maria Tsanai, Teresa Head-Gordon

We employ a multiscale computational approach to investigate the condensation process of the C-terminal low-complexity region of the Caprin1 protein as a function of increasing ATP concentration for three states: the initial mixed state, nanocondensate formation, and the dissolution of the droplet as it reenters the mixed state. We show that upon condensatio

Seonguk Seo, Bohyung Han

Group distributionally robust optimization, which aims to improve robust accuracies -- worst-group and unbiased accuracies -- is a prominent algorithm used to mitigate spurious correlations and address dataset bias. Although existing approaches have reported improvements in robust accuracies, these gains often come at the cost of average accuracy due to inhe

Raphael Memmesheimer, Jan Nogga, Bastian Pätzold, Evgenii Kruzhkov

We present the approaches and contributions of the winning team NimbRo@Home at the RoboCup@Home 2024 competition in the Open Platform League held in Eindhoven, NL. Further, we describe our hardware setup and give an overview of the results for the task stages and the final demonstration. For this year's competition, we put a special emphasis on open-vocabula

Haitao Tian, Pierre Payeur

Existing skeleton-based human action classification models rely on well-trimmed action-specific skeleton videos for both training and testing, precluding their scalability to real-world applications where untrimmed videos exhibiting concatenated actions are predominant. To overcome this limitation, recently introduced skeleton action segmentation models invo

Benedikt Jahnel, Lukas Lüchtrath, Anh Duc Vu

We study a version of first passage percolation on $\mathbb{Z}^d$ where the random passage times on the edges are replaced by contact times represented by random closed sets on $\mathbb{R}$. Similarly to the contact process without recovery, an infection can spread into the system along increasing sequences of contact times. In case of stationary contact tim

Ioana Buhnila, Georgeta Cislaru, Amalia Todirascu

Large Language Models (LLMs) have been used to generate texts in response to different writing tasks: reports, essays, story telling. However, language models do not have a meta-representation of the text writing process, nor inherent communication learning needs, comparable to those of young human students. This paper introduces a fine-grained linguistic an

Mario Beluri, Bhupendra Acharya, Soheil Khodayari, Giada Stivala

There has been a rise in online platforms facilitating the buying and selling of social media accounts. While the trade of social media profiles is not inherently illegal, social media platforms view such transactions as violations of their policies. They often take action against accounts involved in the misuse of platforms for financial gain. This research

Zongtan Li, Yunli Shao

Connected and automated vehicles (CAVs) represent the future of transportation, utilizing detailed traffic information to enhance control and decision-making. Eco-driving of CAVs has the potential to significantly improve energy efficiency, and the benefits are maximized when both vehicle speed and powertrain operation are optimized. In this paper, we studie

Chiara Le Roux, José Guilherme Milhano, Korinna Zapp

It is a continued open question how there can be an azimuthal anisotropy of high $p_\perp$ particles quantified by a sizable $v_2$ in p+Pb collisions when, at the same time, the nuclear modification factor $R_\text{AA}$ is consistent with unity. We address this puzzle within the framework of the jet quenching model \textsc{Jewel}. In the absence of reliable

Huseyin Harmankaya, Adrian Brietzke, Rebecca Pham-Xuan, Barys Shyrokau

The ability to engage in other activities during the ride is considered by consumers as one of the key reasons for the adoption of automated vehicles. However, engagement in non-driving activities will provoke occupants' motion sickness, deteriorating their overall comfort and thereby risking acceptance of automated driving. Therefore, it is critical to exte

Shinsuke Takasao, Masanobu Kunitomo, Takeru K. Suzuki, Kazunari Iwasaki

Stellar spin is one of the fundamental quantities that characterize a star itself and its planetary system. Nevertheless, stellar spin-down mechanisms in protostellar and pre-main-sequence stellar phases have been a long-standing problem in the star formation theory. To realize the spin-down, previous axisymmetric models based on the conventional magnetosphe

Golo Wolff

We consider cubic forms $\phi_{a,b}(x,y,z) = ax^3 + by^3 - z^3$ with coefficients $a,b \in \mathbb{Z}$. We give an asymptotic formula for how many of these forms are locally soluble everywhere, i.e. we give an asymptotic formula for the number of pairs of integers $(a, b)$ that satisfy $1 \leq a \leq A$, $1 \leq b \leq B$ and some mild conditions, such that

Lorenzo Facciaroni, Costantino Ricciuti, Enrico Scalas, Bruno Toaldo

There is a well established theory that links semi-Markov chains having Mittag-Leffler waiting times to time-fractional equations. We here go beyond the semi-Markov setting, by defining some non-Markovian chains whose waiting times, although marginally Mittag-Leffler, are assumed to be stochastically dependent. This creates a long memory tail in the evolutio

Rongqing Kenneth Ong, Andy W. H. Khong

Incorporating multi-modal features as side information has recently become a trend in recommender systems. To elucidate user-item preferences, recent studies focus on fusing modalities via concatenation, element-wise sum, or attention mechanisms. Despite having notable success, existing approaches do not account for the modality-specific noise encapsulated w

Adriana Fernández-Fernández, Angel Martin, Guillermo Gomez

The 6GENABLERS-DLT project addresses critical challenges in fostering multi-party collaboration within dynamic 6G environments. As operators and service providers increasingly depend on third-party resources to meet their contractual and operational needs, the project introduces an innovative, Distributed Ledger Technology (DLT)-anchored Marketplace designed

Martin J. A. Schuetz, Ruben S. Andrist, Grant Salton, Romina Yalovetzky

We propose and implement a comprehensive quantum compilation toolkit for solving the maximum independent set (MIS) problem on quantum hardware based on Rydberg atom arrays. Our end-to-end pipeline involves three core components to efficiently map generic MIS instances onto Rydberg arrays with unit-disk connectivity, with modules for graph reduction, hardware

Angelo Borsotti, Luca Breveglieri, Stefano Crespi Reghizzi, Angelo Morzenti

Speculative data-parallel algorithms for language recognition have been widely experimented for various types of finite-state automata (FA), deterministic (DFA) and nondeterministic (NFA), often derived from regular expressions (RE). Such an algorithm cuts the input string into chunks, independently recognizes each chunk in parallel by means of identical FAs

Jianhua Sun, Yuxuan Li, Jiude Wei, Longfei Xu

The acquisition of substantial volumes of 3D articulated object data is expensive and time-consuming, and consequently the scarcity of 3D articulated object data becomes an obstacle for deep learning methods to achieve remarkable performance in various articulated object understanding tasks. Meanwhile, pairing these object data with detailed annotations to e

Fuqiang Chen, Matteo Ravasi, David Keyes

Low-rank regularization is an effective technique for addressing ill-posed inverse problems when the unknown variable exhibits low-rank characteristics. However, global low-rank assumptions do not always hold for seismic wavefields; in many practical situations, local low-rank features are instead more commonly observed. To leverage this insight, we propose

Flavio Lorez, Mohit Pundir

Recent advancements have demonstrated that fully Eulerian methods can effectively model frictionless contact between deformable solids. Unlike traditional Lagrangian approaches, which require contact detection and resolution algorithms, the Eulerian framework utilizes a single, fixed spatial mesh combined with a diffuse interface phase-field approach, simpli

Zia Qi, Brian E. Perron, Miao Wang, Cao Fang

Objective: This study examines how well leading Chinese and Western large language models understand and apply Chinese social work principles, focusing on their foundational knowledge within a non-Western professional setting. We test whether the cultural context in the developing country influences model reasoning and accuracy. Method: Using a published sel

Lewi Westcott, Christopher J. Conselice, Thomas Harvey, Duncan Austin

We present a structural analysis of 521 galaxy candidates at 6.5 < z < 12.5, with $SNR > 10\sigma$ in the F444W filter, taken from the EPOCHS v1 sample, consisting of uniformly reduced deep JWST NIRCam data, covering the CEERS, JADES GOOD-S, NGDEEP, SMACS0723, GLASS and PEARLS surveys. We use standard software to fit single S\'ersic models to each galaxy in

Julián O'Flaherty, Rodrigo Paganini, Juan Pablo Sotelo, Julieta Umpiérrez

In this paper, we introduce PhotoHolmes, an open-source Python library designed to easily run and benchmark forgery detection methods on digital images. The library includes implementations of popular and state-of-the-art methods, dataset integration tools, and evaluation metrics. Utilizing the Benchmark tool in PhotoHolmes, users can effortlessly compare va

Davide Dardari, Giulia Torcolacci, Gianni Pasolini, Nicolo Decarli

This article provides a tutorial on over-the-air electromagnetic signal processing (ESP) for next-generation wireless networks, addressing the limitations of digital processing to enhance the efficiency and sustainability of future 6th Generation (6G) systems. It explores the integration of electromagnetism and signal processing (SP) under a unified framewor

Giulio D'Erasmo, Giovanni Trappolini, Nicola Tonellotto, Fabrizio Silvestri

Recent advances in Information Retrieval have leveraged high-dimensional embedding spaces to improve the retrieval of relevant documents. Moreover, the Manifold Clustering Hypothesis suggests that despite these high-dimensional representations, documents relevant to a query reside on a lower-dimensional, query-dependent manifold. While this hypothesis has in

Agnieszka Dziurda, Maciej Giza, Vladimir V. Gligorov, Wouter Hulsbergen

The physics programme of the LHCb experiment at the Large Hadron Collider requires an efficient and precise reconstruction of the particle collision vertices. The LHCb Upgrade detector relies on a fully software-based trigger with an online reconstruction rate of 30 MHz, necessitating fast vertex finding algorithms. This paper describes a new approach to ver

Kangning Li, Zheyang Jia, Anyu Ying

In recent years, large-scale models have achieved significant advancements, accompanied by the emergence of numerous high-quality benchmarks for evaluating various aspects of their comprehension abilities. However, most existing benchmarks primarily focus on spatial understanding in static image tasks. While some benchmarks extend evaluations to temporal tas

Kalle Kujanpää, Pekka Marttinen, Harri Valpola, Alexander Ilin

In many practical applications, large language models (LLMs) need to acquire new knowledge not present in their pre-training data. Efficiently leveraging this knowledge usually relies on supervised fine-tuning or retrieval-augmented generation (RAG). Although RAG has emerged as the industry standard for knowledge injection, fine-tuning has not yet achieved c

Yiyu Zhuang, Jiaxi Lv, Hao Wen, Qing Shuai

Creating a high-fidelity, animatable 3D full-body avatar from a single image is a challenging task due to the diverse appearance and poses of humans and the limited availability of high-quality training data. To achieve fast and high-quality human reconstruction, this work rethinks the task from the perspectives of dataset, model, and representation. First,

Christopher Hansen, Alexander Battey, Anson Braun, Sander Miller

In this paper we present a new thin-wall eddy current modeling code, ThinCurr, for studying inductively-coupled currents in 3D conducting structures -- with primary application focused on the interaction between currents flowing in coils, plasma, and conducting structures of magnetically-confined plasma devices. The code utilizes a boundary finite element me

Xianghui Fan, Chao Ye, Anping Deng, Xiaotian Wu

The sensing and manipulation of transparent objects present a critical challenge in industrial and laboratory robotics. Conventional sensors face challenges in obtaining the full depth of transparent objects due to the refraction and reflection of light on their surfaces and their lack of visible texture. Previous research has attempted to obtain complete de

Adam Abdalla, Mahiro Abe, Sven Abend, Mouine Abidi

This summary of the second Terrestrial Very-Long-Baseline Atom Interferometry (TVLBAI) Workshop provides a comprehensive overview of our meeting held in London in April 2024, building on the initial discussions during the inaugural workshop held at CERN in March 2023. Like the summary of the first workshop, this document records a critical milestone for the

Qingjie Zhang, Di Wang, Haoting Qian, Yiming Li

Intrinsic self-correction was proposed to improve LLMs' responses via feedback prompts solely based on their inherent capability. However, recent works show that LLMs' intrinsic self-correction fails without oracle labels as feedback prompts. In this paper, we aim to interpret LLMs' intrinsic self-correction for different tasks, especially for those failure

Kristof Schmieden, Tim Schneemann, Matthias Schott, Malavika Unni

A new axion-haloscope is setup at the Johannes Gutenberg university of Mainz, named the Supax (a SUPerconducting AXion search) experiment. This setup is used to characterize the behaviour of a NbN coated superconducting cavity in a 2.5T strong magnetic field, at a resonance frequency of 8.4GHz. We observe an increasing surface resistance with increasing magn

Leonardo Barcellona, Andrii Zadaianchuk, Davide Allegro, Samuele Papa

A world model provides an agent with a representation of its environment, enabling it to predict the causal consequences of its actions. Current world models typically cannot directly and explicitly imitate the actual environment in front of a robot, often resulting in unrealistic behaviors and hallucinations that make them unsuitable for real-world robotics

Jeremy L. Smallwood, Stephen H. Lubow, Rebecca G. Martin, Rebecca Nealon

We revisit the origin of the observed misaligned rings in the circumtriple disk around GW Ori. Previous studies appeared to disagree on whether disk breaking is caused by the differential precession driven in the disk by the triple star system. In this letter, we show that the previous studies are in agreement with each other when using the same set of param

Nathan Sprague, John Evans, Michael Mardikes

Monitoring growth behavior of maize plants such as the development of ears can give key insights into the plant's health and development. Traditionally, the measurement of the angle of ears is performed manually, which can be time-consuming and prone to human error. To address these challenges, this paper presents a computer vision-based system for detecting

Mathieu Istas, Scott Jensen, Yubo Yang, Markus Holzmann

We simulate high-pressure hydrogen in its liquid phase close to molecular dissociation using a machine-learned interatomic potential. The model is trained with density functional theory (DFT) forces and energies, with the Perdew-Burke-Ernzerhof (PBE) exchange-correlation functional. We show that an accurate NequIP model, an E(3)-equivariant neural network po

Leïla Bessila, Adrien Deckx van Ruys, Valentin Buriasco, Stéphane Mathis

Recent observational results from asteroseismic studies show that an important fraction of solar-like stars do not present detectable stochastically excited acoustic oscillations. This non-detectability seems to correlate with a high rotation rate in the convective envelope and a high surface magnetic activity. At the same time, the properties of stellar con

M. O. Malcolms, Henri Menke, Yi-Ting Tseng, Eric Jacob

The pseudogap in high-temperature superconducting cuprates is an exotic state of matter, displaying emerging Fermi arcs and a momentum-selective suppression of states upon cooling. We show how these phenomena are originating in the three-band Emery model by performing cutting-edge dynamical vertex approximation calculations for its normal state. For the hole

Dimos Tsouros, Senne Berden, Steven Prestwich, Tias Guns

Constraint Acquisition (CA) aims to widen the use of constraint programming by assisting users in the modeling process. However, most CA methods suffer from a significant drawback: they learn a single set of individual constraints for a specific problem instance, but cannot generalize these constraints to the parameterized constraint specifications of the pr

Rui Yang, Jiaming Guo, Linghai Li, Xun Xue

We investigate the global structure of the Gauged Two-Higgs-Doublet Model (G2HDM), a framework that extends the Standard Model by introducing a dark sector governed by the gauge symmetry $U(1)_X \times SU(2)_H$. The full gauge symmetry of the theory, including the visible sector, is given by the universal covering group $\tilde{G} = U(1)_Y \times SU(2)_L \ti