November 2024 arXiv papers — page 147

Nguyen Hoang Vu

We generalize the concept of holography for the color superconductivity (CSC) phase by considering $d$-dimensional Anti de Sitter (AdS) space instead of the traditional 6 dimensions. The corresponding dual field theory is a gauge theory with $SU(N_c)$ symmetry defined in $(d-1)$-dimensions that, despite lacking a confinement phase, retains characteristics co

Ermanno Bartoli, Fethiye Irmak Dogan, Iolanda Leite

In real-world settings, robots are expected to assist humans across diverse tasks and still continuously adapt to dynamic changes over time. For example, in domestic environments, robots can proactively help users by fetching needed objects based on learned routines, which they infer by observing how objects move over time. However, data from these interacti

Giulio Delama, Alessandro Fornasier, Robert Mahony, Stephan Weiss

This letter proposes a new approach for Inertial Measurement Unit (IMU) preintegration, a fundamental building block that can be leveraged in different optimization-based Inertial Navigation System (INS) localization solutions. Inspired by recent advances in equivariant theory applied to biased INSs, we derive a discrete-time formulation of the IMU preintegr

Geonmin Kim, Jaeyeon Kim, Hancheol Park, Wooksu Shin

Thanks to unprecedented language understanding and generation capabilities of large language model (LLM), Retrieval-augmented Code Generation (RaCG) has recently been widely utilized among software developers. While this has increased productivity, there are still frequent instances of incorrect codes being provided. In particular, there are cases where plau

Fengyu Sun, Xinyu Xie, Wenpeng Wang, Stefan Weber

An isolated attosecond vortex $\gamma$-ray pulse is generated by using a relativistic spatiotemporal optical vortex (STOV) laser in particle-in-cell simulations. A $\sim$ 300-attosecond electron slice with transverse orbital angular momentum (TOAM) is initially selected and accelerated by the central spatiotemporal singularity of the STOV laser. This slice t

M. Siddikov, I. Zemlyakov, M. Roa, S. Valdebenito

In this paper we analyzed the exclusive photoproduction of $\eta_{c}\gamma$ pairs in the Color Glass Condensate framework. We found that the cross-section of this process is sensitive only to the forward dipole scattering amplitude, and thus could be used as a new tool for analysis of this fundamental nonperturbative object. Using the phenomenological parame

Nan Song, Xiaofeng Yang, Ze Yang, Guosheng Lin

Lifelong few-shot customization for text-to-image diffusion aims to continually generalize existing models for new tasks with minimal data while preserving old knowledge. Current customization diffusion models excel in few-shot tasks but struggle with catastrophic forgetting problems in lifelong generations. In this study, we identify and categorize the cata

Hirofumi Takesue

This study aimed to investigate the evolutionary dynamics of a three-strategy game that combines snowdrift and stag hunt games. This game is motivated by an experimental study, which found that individual solution lowers cooperation levels. Agents adopting this option aim to address a problem to the extent necessary to remove negative impact on themselves, a

Konstantin Herb, Laura A. Völker, John M. Abendroth, Nicholas Meinhardt

Quantum magnetometers based on spin defects in solids enable sensitive imaging of various magnetic phenomena, such as ferro- and antiferromagnetism, superconductivity, and current-induced fields. Existing protocols primarily focus on static fields or narrow-band dynamical signals, and are optimized for high sensitivity rather than fast time resolution. Here,

Emmanuel Kammerer

We prove that for $n = 2$ the gaskets of critical rigid $O(n)$ loop-decorated random planar maps are $3/2$-stable maps. The case $n = 2$ thus corresponds to the critical case in random planar maps. The proof relies on the Wiener-Hopf factorisation for random walks. Our techniques also provide a characterisation of weight sequences of critical $O(2)$ loop-dec

Penghui Liu, Yingzhou Bi, Jiangtao Huang, Xinxin Jiang

Software vulnerabilities are flaws in computer software systems that pose significant threats to the integrity, security, and reliability of modern software and its application data. These vulnerabilities can lead to substantial economic losses across various industries. Manual vulnerability repair is not only time-consuming but also prone to errors. To addr

A. Turan Gürkanlı

Let $G$ be a locally compact Abelian group with dual group $\widehat G $ and Haar measures $d\mu$ and $\hat d\mu$ respectively. In this work we have proved that if $X$ is an essential Banach ideal in Beurling algebra $ L^1_{\omega}(G),$ then a closed subset $E\subset \widehat G$ is a Ditkin set for $X$ if and only if $E$ is a Ditkin set for $ L^1_{\omega}(G)

Charles-Edouard Bréhier, Marc Dambrine, Nassim En-Nebbazi

We consider a class of stochastic gradient optimization schemes. Assuming that the objective function is strongly convex, we prove weak error estimates which are uniform in time for the error between the solution of the numerical scheme, and the solutions of continuous-time modified (or high-resolution) differential equations at first and second orders, with

Chitranshi Saxena, Krishna Pal Thakur, Deb Mukherjee, Sadananda Behera

Vehicle-to-Everything (V2X) communication, which includes Vehicle-to-Infrastructure (V2I), Vehicle-to-Vehicle (V2V), and Vehicle-to-Pedestrian (V2P) networks, is gaining significant attention due to the rise of connected and autonomous vehicles. V2X systems require diverse Quality of Service (QoS) provisions, with V2V communication demanding stricter latency

Ricard Montalà, Bernat Font, Pol Suárez, Jean Rabault

This paper presents a deep reinforcement learning (DRL) framework for active flow control (AFC) to reduce drag in aerodynamic bodies. Tested on a 3D cylinder at Re = 100, the DRL approach achieved a 9.32% drag reduction and a 78.4% decrease in lift oscillations by learning advanced actuation strategies. The methodology integrates a CFD solver with a DRL mode

Mengyuan Huang, Chao Sun, Kerstin Eckert, Xianren Zhang

In gas evolving electrolysis, bubbles grow at electrodes due to a diffusive influx from oversaturation generated locally in the electrolyte by the electrode reaction. When considering electrodes of micrometer-size resembling catalytic islands, bubbles are found to approach dynamic equilibrium states at which they neither grow nor shrink. Such equilibrium sta

Qi Lü, Yu Wang

This book aims to provide a brief overview of recent advancements in the theory of inverse problems for stochastic partial differential equations. In order to keep the content concise, we will only discuss the inverse problems of two typical classes of stochastic partial differential equations: second-order stochastic parabolic equations and secondorder stoc

Dmytro Borysenkov, Adriano Vogel, Sören Henning, Esteban Perez-Wohlfeil

Logs are crucial for analyzing large-scale software systems, offering insights into system health, performance, security threats, potential bugs, etc. However, their chaotic nature$\unicode{x2013}$characterized by sheer volume, lack of standards, and variability$\unicode{x2013}$makes manual analysis complex. The use of clustering algorithms can assist by gro

Matheus Kriginsky, Ramon Oliver

Fibrillar structures are ubiquitous in the solar chromosphere and their potential for mediating the mass and energy transport in the solar atmosphere is undeniable. An accurate determination of their properties requires the use of advanced high-resolution observations which are now becoming broadly available from different observatories. We exploit the capab

Chenghong Bian, Kaitao Meng, Huihui Wu, Yumeng Zhang

We propose a novel coded integrated passive sensing and communication (CIPSAC) system with orthogonal frequency division multiplexing (OFDM), where a multi-antenna base station (BS) passively senses the parameters of the targets and decodes the information bit sequences transmitted by a user. The transmitted signal is comprised of pilot and data OFDM symbols

Y. V. Radeonychev, I. R. Khairulin

We propose a technique for transforming the intensity of quasi-monochromatic recoilless radiation with a photon energy of 93.3 keV, emitted by radioactive M\"ossbauer sources 67Ga or 67Cu, into a sequence of short pulses with individually and independently controlled, on demand, the moments of appearance of pulses, as well as the peak intensity, duration and

Tero Mäkinen, Anshul D. S. Parmar, Silvia Bonfanti, Mikko J. Alava

Designing metallic glasses in silico is a major challenge in materials science given their disordered atomic structure and the vast compositional space to explore. Here, we tackle this challenge by finding optimal compositions for target mechanical properties. We apply Bayesian exploration for the CuZrAl composition, a paradigmatic metallic glass known for i

Leon Kopitar, Leon Bedrac, Larissa J Strath, Jiang Bian

This study explores the effectiveness of Large Language Models in meal planning, focusing on their ability to identify and decompose compound ingredients. We evaluated three models-GPT-4o, Llama-3 (70b), and Mixtral (8x7b)-to assess their proficiency in recognizing and breaking down complex ingredient combinations. Preliminary results indicate that while Lla

Martin G. Gonzalez, Matias Vera, Leonardo Rey Vega

Optoacoustic tomography image reconstruction has been a problem of interest in recent years. By exploiting the exceptional generative power of the recently proposed diffusion models we consider a scheme which is based on a conditional diffusion process. Using a simple initial image reconstruction method such as Delay and Sum, we consider a specially designed

Bowen Zhu, Hao Wang, Jian Wu, Haijun Ren

We designed a new artificial neural network by modifying the neural ordinary differential equation (NODE) framework to successfully predict the time evolution of the 2D mode profile in both the linear growth and nonlinear saturated stages. Starting from the magnetohydrodynamic (MHD) equations, simplifying assumptions were applied based on physical properties

Kushal Tatariya, Artur Kulmizev, Wessel Poelman, Esther Ploeger

Wikipedia's perceived high quality and broad language coverage have established it as a fundamental resource in NLP. However, in recent years, such assumptions of high quality have become the subject of scrutiny in low-resource and multilingual contexts. In this study, we subject the entirety of non-English Wikipedia to a data filtering procedure typically r

Arif Rachmat

Footstep recognition is a relatively new biometric which aims to discriminate people using walking characteristics. There are several feature and technology have been adopted in various research. This study will attempt to show a comparative technology and feature which is offered each previous related works. We performed a broad manually search to find SLRs

E. Fanucchi, G. Forghieri, A. Secchi, P. Bordone

Holes in Si quantum dots are being investigated for the implementation of electrically addressable spin qubits. In this perspective, the attention has been focused on the electric-field induced transitions between the eigenstates belonging to the ground doublet. Here we theoretically extend the analysis to the first excited doublet. We show that - in a proto

Radek Holeňák, Michaela Malatinová, Eleni Ntemou, Tuan T. Tran

We investigate the dependence of the yield of positive secondary ions created upon impact of primary He, B and Ne ions on geometry and electronic and nuclear energy deposition by the projectiles. We employ pulsed beams in the medium energy regime and a large position-sensitive, time-of-flight detection system to ensure accurate quantification. As a target, w

Minh DUc Nguyen, Cong Thuong Le, Trong Lam Nguyen

The accurate alignment of 3D woodblock geometrical models with 2D orthographic projection images presents a significant challenge in the digital preservation of Vietnamese cultural heritage. This paper proposes a unified image processing algorithm to address this issue, enhancing the registration quality between 3D woodblock models and their 2D representatio

Philip Lah, Matthew Colless, Francesco D'Eugenio, Brent Groves

Optical emission lines across the Small Magellanic Cloud (SMC) have been measured from multiple fields using the Australian National University (ANU) 2.3m telescope with the Wide-Field Spectrograph (WiFeS). Interpolated maps of the gas-phase metallicity, extinction, H$\alpha$ radial velocity and H$\alpha$ velocity dispersion have been made from these measure

Gorin Benjamin, Ribe Neil, Bonn Daniel, Kellay Hamid

We study experimentally the impact on rigid surfaces of different soft porous solids saturated with liquid: hydrogel balls and liquid-saturated foam balls. The static con tact of such soft solids with the substrate is well described by Hertz contact theory. However, their rebound behavior can only be explained by invoking a variety of dissipa tion mechanisms

Remo Garattini

In this contribution we explore the consequences of including additional sources to the original Casimir energy Stress-Energy Tensor. In particular, we will discuss the effects of an additional electromagnetic field, the modification induced by non-zero temperature effects on the energy density obtained by a Casimir device and finally the effect obtained by

Sithursan Sivasubramaniam, Cedric Osei-Akoto, Yi Zhang, Kurt Stockinger

Electronic health records (EHRs) are stored in various database systems with different database models on heterogeneous storage architectures, such as relational databases, document stores, or graph databases. These different database models have a big impact on query complexity and performance. While this has been a known fact in database research, its impl

Martin Heczko, Petr Šesták, Hanuš Seiner, Martin Zelený

The impact of shear deformation in $(1\,0\,1)[1\,0\,\bar{1}]$ system of non-modulated (NM) martensite in Ni$_2$MnGa ferromagnetic shape memory alloy is investigated by means of ab initio atomistic simulations. The shear system is associated with twinning of NM lattice and intermatensitic transformation to modulated structures. The stability of the NM lattice

Shichao Jia, Soichiro Tsujino

Acoustic tweezers comprising a surface acoustic wave chip and a disposable silicon microfluidic chip are potentially advantageous to stable and cost-ffective acoustofluidic experiments while avoiding the cross-contamination by reusing the surface acoustic wave chip and disposing of the microfluidic chip. For such a device, it is important to optimize the chi

Weifeng Xie, Xiong Xu, Yunliang Yue, Huayan Xia

Clarifying the physical origin of valley polarization and exploring promising ferrovalley materials are conducive to the application of valley degrees of freedom in the field of information storage. Here, we explore two novel altermagnetic semiconductors (monolayers Nb2Se2O and Nb2SeTeO) with N\'eel temperature above room temperature based on first-principle

G. Esplugues, M. Rodríguez-Baras, D. Navarro-Almaida, A. Fuente

The observational detection of some metastable isomers in the interstellar medium with abundances comparable to those of the most stable isomer, or even when the stable isomer is not detected, highlights the importance of non-equilibrium chemistry. This challenges our understanding of the interstellar chemistry. We present a chemical study of isomers through

Sushil Shakya, Robert Abbas

This paper presents the detection of DDoS attacks in IoT networks using machine learning models. Their rapid growth has made them highly susceptible to various forms of cyberattacks, many of whose security procedures are implemented in an irregular manner. It evaluates the efficacy of different machine learning models, such as XGBoost, K-Nearest Neighbours,

Pruthviraj Mane, Allen Jacob George, Rajini Makam, Subhash Gurikar

Autonomous Underwater Vehicles (AUVs) have advanced significantly in obstacle detection and path planning through sonar, cameras, and learning-based methods. However, safe and efficient navigation in cluttered environments remains challenging due to partial observability, turbidity, the limited field-of-view of forward-looking sonar (FLS), and occlusions tha

Martin M. Roth

Recent progress with CMOS detector development has opened new parameter space for high cadence time resolved imaging of transients and fast proper motion solar system objects. Using computer simulations for a ground-based 1.23 m telescope, this research note illustrates the gain of a new generation of fast readout low noise qCMOS sensors over CCDs and makes

F. Ahlborn, E. P. Bellinger, S. Hekker, S. Basu

Rotation is an important, yet poorly-modelled phenomenon of stellar structure and evolution. Accurate estimates of internal rotation rates are therefore valuable for constraining stellar evolution models. We aim to assess the accuracy of asteroseismic estimates of internal rotation rates and how these depend on the fundamental stellar parameters. We apply th

Muhammad Zawad Mahmud, Shahran Rahman Alve, Samiha Islam, Mohammad Monirujjaman Khan

Software-defined network (SDN) is a new approach that allows network control to become directly programmable, and the underlying infrastructure can be abstracted from applications and network services. Control plane). When it comes to security, the centralization that this demands is ripe for a variety of cyber threats that are not typically seen in other ne

Fabian Gröger, Philippe Gottfrois, Ludovic Amruthalingam, Alvaro Gonzalez-Jimenez

The growing demand for accurate and equitable AI models in digital dermatology faces a significant challenge: the lack of diverse, high-quality labeled data. In this work, we investigate the potential of domain-specific foundation models for dermatology in addressing this challenge. We utilize self-supervised learning (SSL) techniques to pre-train models on

Simon Brezovnik, Matthias Dehmer, Niko Tratnik, Petra Žigert Pleteršek

In this paper, we examine roots of graph polynomials where those roots can be considered as structural graph measures. More precisely, we prove analytical results for the roots of certain modified graph polynomials and also discuss numerical results. As polynomials, we use, e.g., the Hosoya, the Schultz, and the Gutman polynomial which belong to an interesti

Ismihan Bayramoglu, Pelin Ersin

The local dependence function is important in many applications of probability and statistics. We extend the bivariate local dependence function introduced by Bairamov and Kotz (2000) and further developed by Bairamov et al. (2003) to three-variate and multivariate local dependence function characterizing the dependency between three and more random variable

Simon Forest

In this work, we investigate an effective method for showing that functors between categories are left adjoints. The method applies to a large class of categories, namely locally finitely presentable categories, which are ubiquitous in practice and include standard examples like Set, Grp, etc. Our method relies on a known description of these categories as o

Elisa Tomassini, Enrique García-Macías, Filippo Ubertini

The rising number of bridge collapses worldwide has compelled governments to introduce predictive maintenance strategies to extend structural lifespan. In this context, vibration-based Structural Health Monitoring (SHM) techniques utilizing Operational Modal Analysis (OMA) are favored for their non-destructive and global assessment capabilities. However, lon

Ajay Kumar, Anis Biswas, Yaroslav Mudryk

HoCo$_2$ exhibits a giant magnetocaloric (MC) effect at its first-order magnetostructural phase transition around 77~K, and understanding the thermodynamic nature of this transition in response to external magnetic fields is crucial for its MC applications. In this study, we present a comprehensive investigation of specific heat and magnetization measurement

Zijian Chen, Ronak Pradeep, Jimmy Lin

Recent advances have demonstrated that large language models (LLMs) excel as listwise rerankers, but their high computational demands remain a barrier to widespread adoption. Further, the traditional language modeling (LM) objective is not ideally suited for reranking tasks. FIRST is a novel approach that addresses these challenges by integrating a learning-

Kameyab Raza Abidi, Pekka Koskinen

Metallenes are atomically thin two-dimensional (2D) materials lacking a layered structure in the bulk form. They can be stabilized by nanoscale constrictions like pores in 2D covalent templates, but the isotropic metallic bonding makes stabilization difficult. A few metallenes have been stabilized but comparison with theory predictions has not always been cl

Limor Hatsor, Ronen Bar-El

An alternative to the dependence on traditional student loans may offer a viable relief from the tremendous burden that those loans usually incur. This article establishes that it is desirable for governmental intervention to grant students 'more choice' in their funding decisions by allowing them to have portfolios, mixtures of different types of loans. To

P. Segretain, H. Méheut, M. Moreira, G. Lesur

Planetesimal formation models often invoke the gravitational collapse of pebble clouds to overcome various barriers to grain growth and propose processes to concentrate particles sufficiently to trigger this collapse. On the other hand, the geochemical approach for planet formation constrains the conditions for planetesimal formation and evolution by providi

Haoran Lian, Yizhe Xiong, Zijia Lin, Jianwei Niu

The prevalent use of Byte Pair Encoding (BPE) in Large Language Models (LLMs) facilitates robust handling of subword units and avoids issues of out-of-vocabulary words. Despite its success, a critical challenge persists: long tokens, rich in semantic information, have fewer occurrences in tokenized datasets compared to short tokens, which can result in imbal

Anton Alekseev, Timur Turatali

Large language models (LLMs) have excelled in numerous benchmarks, advancing AI applications in both linguistic and non-linguistic tasks. However, this has primarily benefited well-resourced languages, leaving less-resourced ones (LRLs) at a disadvantage. In this paper, we highlight the current state of the NLP field in the specific LRL: kyrgyz tili. Human e

William Waites, Philip Gillibrand, Thomas Adams, Rek Bell

We address the question of how to connect predictions by hydrodynamic models of how sea lice move in water to observable measures that count the number of lice on each fish in a cage in the water. This question is important for management and regulation of aquacultural practice that tries to maximise food production and minimise risk to the environment. We d

Guang-Jie Chen, Dong Zhao, Zhu-Bo Wang, Ziqin Li

Precise control and manipulation of neutral atoms are essential for quantum technologies but largely dependent on conventional bulky optical setups. Here, we demonstrate a multifunctional metalens that integrates an achromatic lens with large numerical aperture, a quarter-wave plate, and a polarizer for trapping and characterizing single Rubidium atoms. The

Lingkai Zhu, Can Deniz Bezek, Orcun Goksel

In recent years, the increasing size of deep learning models and their growing demand for computational resources have drawn significant attention to the practice of pruning neural networks, while aiming to preserve their accuracy. In unstructured gradual pruning, which sparsifies a network by gradually removing individual network parameters until a targeted

Calum S. Skene, Florence Marcotte, Steven M. Tobias

Nearly fifty years ago, Roberts (1978) postulated that Earth's magnetic field, which is generated by turbulent motions of liquid metal in its outer core, likely results from a subcritical (finite-amplitude) dynamo instability characterised by a dominant balance between Coriolis, pressure and Lorentz forces. Here we numerically explore subcritical convective

Milan Sil, Ankan Das, Ramkrishna Das, Ruchi Pandey

HeH$^+$ was the first heteronuclear molecule to form in the metal-free Universe after the Big Bang. The molecule gained significant attention following its first circumstellar detection in the young and dense planetary nebula NGC 7027. We target some hydride ions associated with the noble gases (HeH$^+$, ArH$^+$, and NeH$^+$) to investigate their formation i

Chanuk Yang, Hayeon O, Kunsoo Huh

This paper proposes a novel algorithm for vehicle speed-aided monocular visual-inertial localization using a topological map. The proposed system aims to address the limitations of existing methods that rely heavily on expensive sensors like GPS and LiDAR by leveraging relatively inexpensive camera-based pose estimation. The topological map is generated offl

M. R. Mahani, Igor A. Nechepurenko, Thomas Flisgen, Andreas Wicht

The design and optimization of optical components, such as Bragg gratings, are critical for applications in telecommunications, sensing, and photonic circuits. To overcome the limitations of traditional design methods that rely heavily on computationally intensive simulations and large datasets, we propose an integrated methodology that significantly reduces

Ulrich Bauer, Jordan Matuszewski, Mikael Vejdemo-Johansson

Cofaces -- simplices that contain a given simplex -- have multiple important uses in generating and using a Vietoris-Rips filtration: both in creating the coboundary matrix for computing persistent cohomology, and for generating the ordered sequence of simplices in the first place. Traditionally, most methods have generated simplices first, and then sorted t

Jose Soto, Natalia Chepiga

Experiments on chains of Rydberg atoms appear as a new playground to study quantum phase transitions in 1D. As a natural extension, we report a quantitative ground-state phase diagram of Rydberg atoms arranged in a two-leg ladder that interact via van der Waals potential. We address this problem numerically, using the Density Matrix Renormalization Group (DM

Martín Blufstein, Motiejus Valiunas

We show that the twisted conjugacy problem is solvable for large-type Artin groups whose outer automorphism group is finite, generated by graph automorphisms and the global inversion. This includes XXXL Artin groups whose defining graph is connected, twistless, and not an even edge; and large-type Artin groups whose defining graph admits a twistless hierarch

Ziyue Wang, Yang Li, Ya-Feng Liu, Junjie Ma

This paper studies the device activity detection problem in a massive multiple-input multiple-output (MIMO) system for near-field communications (NFC). In this system, active devices transmit their signature sequences to the base station (BS), which detects the active devices based on the received signal. In this paper, we model the near-field channels as co

David Georg Reichelt, Reiner Jung, André van Hoorn

In order to detect performance changes, measurements are performed with the same execution environment. In cloud environments, the noise from different processes running on the same cluster nodes might change measurement results and thereby make performance changes hard to measure. The benchmark MooBench determines the overhead of different observability too

Jonah Kömen, Hannah Marienwald, Jonas Dippel, Julius Hense

Deep learning has led to remarkable advancements in computational histopathology, e.g., in diagnostics, biomarker prediction, and outcome prognosis. Yet, the lack of annotated data and the impact of batch effects, e.g., systematic technical data differences across hospitals, hamper model robustness and generalization. Recent histopathological foundation mode

Andrea Iannucci, Dan Crisan, Thomas Cass

In this work, we investigate the degeneracy problem in pathwise control, extending the framework developed in \cite{allan2020pathwise} to a more general class of driving signals and a broader set of admissible controls. Our approach consists in choosing admissible controls from a suitable class of Hölder-continuous paths. This leads naturally to the use of f

Lakshmi Kanta Patra, Constantinos Petropoulos, Shrajal Bajpai, Naresh Garg

In the usual statistical inference problem, we estimate an unknown parameter of a statistical model using the information in the random sample. A priori information about the parameter is also known in several real-life situations. One such information is order restriction between the parameters. This prior formation improves the estimation quality. In this

Simone Brivio, Stefania Fresca, Andrea Manzoni

Deep Learning-based Reduced Order Models (DL-ROMs) provide nowadays a well-established class of accurate surrogate models for complex physical systems described by parametrized PDEs, by nonlinearly compressing the solution manifold into a handful of latent coordinates. Until now, design and application of DL-ROMs mainly focused on physically parameterized pr

Efstratios Stratoglou, Alexandre Anahory Simoes, Anthony Bloch, Leonardo J. Colombo

Nonholonomic systems are, so to speak, mechanical systems with a prescribed restriction on the velocities. A virtual nonholonomic constraint is a controlled invariant distribution associated with an affine connection mechanical control system. A Riemannian homogeneous space is, a Riemannian manifold that looks the same everywhere, as you move through it by t

Luiz Hartmann, Matthias Lesch

We review the multivariate holomorphic functional calculus for tuples in a commutative Banach algebra and establish a simple "na\"ive" extension to commuting tuples in a general Banach algebra. The approach is na\"ive in the sense that the na\"ively defined joint spectrum maybe too big. The advantage of the approach is that the functional calculus then is gi

Daniel Menges, Florian Stadtmann, Henrik Jordheim, Adil Rasheed

This paper explores the development and practical application of a predictive digital twin specifically designed for condition monitoring, using advanced mathematical models and thermal imaging techniques. Our work presents a comprehensive approach to integrating Proper Orthogonal Decomposition (POD), Robust Principal Component Analysis (RPCA), and Dynamic M

Bo Li, Wei Wang, Peng Ye

Differential privacy (DP) is a formal notion that restricts the privacy leakage of an algorithm when running on sensitive data, in which privacy-utility trade-off is one of the central problems in private data analysis. In this work, we investigate the fundamental limits of differential privacy in online learning algorithms and present evidence that separate

Arthur Candalot, Malik-Manel Hashim, Brigid Hickey, Mickael Laine

Although wheeled robots have been predominant for planetary exploration, their geometry limits their capabilities when traveling over steep slopes, through rocky terrains, and in microgravity. Legged robots equipped with grippers are a viable alternative to overcome these obstacles. This paper proposes a gripping system that can provide legged space-explorer

Kunrui Ze, Wei Wang, Shuoyu Yue, Guibin Sun

This article studies the problem of distributed formation control for multiple robots by using onboard ultra wide band (UWB) distance and inertial odometer (IO) measurements. Although this problem has been widely studied, a fundamental limitation of most works is that they require each robot's pose and sensor measurements are expressed in a common reference

Suhas Srinath, Aditya Chandrasekar, Hemang Jamadagni, Rajiv Soundararajan

With the rise of marine exploration, underwater imaging has gained significant attention as a research topic. Underwater video enhancement has become crucial for real-time computer vision tasks in marine exploration. However, most existing methods focus on enhancing individual frames and neglect video temporal dynamics, leading to visually poor enhancements.

O. M. Ogreid, P. Osland, M. N. Rebelo

We explore the phenomenology of Weinberg's $Z_2\times Z_2$ symmetric three-Higgs-doublet potential, allowing for spontaneous violation of CP due to complex vacuum expectation values. An overview of all possible ways of satisfying the stationary-point conditions is given, with one, two or three non-vanishing vacuum expectation values, together with conditions

Abdoul Nasser Hassane Amadou, Anas Motii, Saida Elouardi, EL Houcine Bergou

Underground forums serve as hubs for cybercriminal activities, offering a space for anonymity and evasion of conventional online oversight. In these hidden communities, malicious actors collaborate to exchange illicit knowledge, tools, and tactics, driving a range of cyber threats from hacking techniques to the sale of stolen data, malware, and zero-day expl

Anupama R Itagi, Rakhee Kallimani, Krishna Pai, Sridhar Iyer

The operation efficiency of the electric transportation, energy storage, and grids mainly depends on the fundamental characteristics of the employed batteries. Fundamental variables like voltage, current, temperature, and estimated parameters, like the State of Charge (SoC) of the battery pack, influence the functionality of the system. This motivates the im

Giulia Cencetti, Alain Barrat

Surrogate networks can constitute suitable replacements for real networks, in particular to study dynamical processes on networks, when only incomplete or limited datasets are available. As empirical datasets most often present complex features and interplays between structure and temporal evolution, creating surrogate data is however a challenging task, in

Andrew Fonseca, Sarah Dodson-Robinson

Based on radial velocities, EXORAP photometry, and activity indicators, the HADES team reported a 16.3-day rotation period for the M dwarf GJ 3942. However, an RV--H$\alpha$ magnitude-squared coherence estimate has significant peaks at frequencies 1/16 cycles/day and 1/32 cycles/day. We re-analyze HADES data plus Hipparcos, SuperWASP, and TESS photometry to

Mehmet Ahad Yurtoglu, Ramez Askar

The paper introduces a novel dual-port dual-polarized magneto-electric dipole (MED) antenna with orthogonal Gamma and inverted-Gamma shape probes, which was fabricated by means of an additive 3D metal printing process. Electromagnetic wave simulation and RF measurement report a resonance bandwidth from 3 GHz to 4 GHz at both MED's ports with respect to a sta

Émiland Garrabé, Pierre Teixeira, Mahdi Khoramshahi, Stéphane Doncieux

Recent advances in large language models (LLMs) have led to significant progress in robotics, enabling embodied agents to better understand and execute open-ended tasks. However, existing approaches using LLMs face limitations in grounding their outputs within the physical environment and aligning with the capabilities of the robot. This challenge becomes ev

Ahmed Karam Eldaly, Matteo Figini, Daniel C. Alexander

Image Quality Transfer (IQT) aims to enhance the contrast and resolution of low-quality medical images, e.g. obtained from low-power devices, with rich information learned from higher quality images. In contrast to existing IQT methods which adopt supervised learning frameworks, in this work, we propose two novel formulations of the IQT problem. The first ap

Alakh Desai, Nuno Vasconcelos

For image generation with diffusion models (DMs), a negative prompt n can be used to complement the text prompt p, helping define properties not desired in the synthesized image. While this improves prompt adherence and image quality, finding good negative prompts is challenging. We argue that this is due to a semantic gap between humans and DMs, which makes

Peidong Liu, Wenbo Zhang, Wei Ju, Jiancheng Lv

The paradigm shift toward structure-driven molecule generation has been propelled by advances in deep generative models, such as variational auto-encoders and diffusion models. However, these generative models for molecular design remain constrained by exposure bias, error accumulation, and suboptimal handling of activity cliffs. Here, we introduce DiffGap,

Johannes Grünberger, Arne Winterhof

We improve bounds on the degree and sparsity of Boolean functions representing the Legendre symbol as well as on the $N$th linear complexity of the Legendre sequence. We also prove similar results for both the Liouville function for integers and its analog for polynomials over $\mathbb{F}_2$, or more general for any (binary) arithmetic function which satisfi

Piotr A. Kołaczek-Szymański, Piotr Łojko, Andrzej Pigulski, Tomasz Różański

The evolution of massive stars is heavily influenced by their binarity, and the massive eccentric binary system MACHO 80.7443.1718 (ExtEV) serves as a prime example. This study explores whether the light variability of ExtEV, observed near the periastron during its 32.8-day orbit, can be explained by a wind-wind collision (WWC) model and reviews other potent

Gábor Hofer-Szabó, Szilárd Szalay

In this paper, we revisit the concept of noncommuting common causes; refute two objections raised against them, the triviality objection and the lack of causal explanatory force; and explore how their existence modifies the EPR argument. More specifically, we show that 1) product states screening off all quantum correlations do not compromise noncommuting co

Niko Naumann, Luca Pol, Maxime Ramzi

Given a symmetric monoidal stable $\infty$-category $\mathcal{C}$ which is rigidly-compactly generated and a set of compact objects $\mathcal{K}$ of $\mathcal{C}$, one can form the subcategories of $\mathcal{K}$-complete and $\mathcal{K}$-local objects. The goal of this paper is to explain how to recover $\mathcal{C}$ from its $\mathcal{K}$-local and $\mathc

Lei Zhang, Lars Banko, Wolfgang Schuhmann, Alfred Ludwig

Mastering the challenge of predicting properties of unknown materials with multiple principal elements (high entropy alloys/compositionally complex solid solutions) is crucial for the speedup in materials discovery. We show and discuss three models, using property data from two ternary systems (Ag-Pd-Ru; Ag-Pd-Pt), to predict material performance in the shar

Yu Duan, Jaime Agudo-Canalejo, Ramin Golestanian, Benoît Mahault

Motility and nonreciprocity are two primary mechanisms for self-organization in active matter. In a recent study [Phys. Rev. Lett. 131, 148301 (2023)], we explored their joint influence in a minimal model of two-species quorum-sensing active particles interacting via mutual motility regulation. Our results notably revealed a highly dynamic phase of chaotic c

Levi Rauchwerger, Stefanie Jegelka, Ron Levie

We analyze the universality and generalization of graph neural networks (GNNs) on attributed graphs, i.e., with node attributes. To this end, we propose pseudometrics over the space of all attributed graphs that describe the fine-grained expressivity of GNNs. Namely, GNNs are both Lipschitz continuous with respect to our pseudometrics and can separate attrib

Diego Nehab, Gabriel Coutinho de Paula, Augusto Teixeira

In this paper, we introduce a new fraud-proof algorithm that offers an unprecedented combination of decentralization, security, and liveness. The resources that must be mobilized by an honest participant to defeat an adversary grow only logarithmically with what the adversary ultimately loses. As a consequence, there is no need to introduce high bonds that p

Jean-Guy Caputo, Adel Hamdi

We study the nonlinear inverse source problem of detecting, localizing and identifying unknown accidental disturbances on forced and damped transmission networks. A first result is that strategic observation sets are enough to guarantee detection of disturbances. To localize and identify them, we additionally need the observation set to be absorbent. If this

Sophia Tangui, Simon Hurand, Rashed Aljasmi, Ayoub Benmoumen

MXenes stand out from other 2D materials because they combine very good electrical conductivity with hydrophilicity, allowing cost-effective processing as thin films. Therefore, there is a high fundamental interest in unraveling the electronic transport mechanisms at stake in multilayers of the most conducting MXene, Ti$_3$C$_2$T$_x$. Although weak localizat

Amani S. Abumansour, Arkaitz Zubiaga

Selecting check-worthy claims for fact-checking is considered a crucial part of expediting the fact-checking process by filtering out and ranking the check-worthy claims for being validated among the impressive amount of claims could be found online. The check-worthy claim detection task, however, becomes more challenging when the model needs to deal with ne

Simon Elias Schrader, Thomas Bondo Pedersen, Simen Kvaal

In a previous publication [J. Chem. Phys., 161, 044105 (2024)], it has been shown that Rothe's method can be used to solve the time-dependent Schr\"odinger equation (TDSE) for the hydrogen atom in a strong laser field using time-dependent Gaussian wave packets. Here, we generalize these results, showing that Rothe's method can propagate arbitrary numbers of