November 2024 arXiv papers — page 154

Luca Rosafalco, Paolo Conti, Andrea Manzoni, Stefano Mariani

We propose the use of the Extended Kalman Filter (EKF) for online data assimilation and update of a dynamic model, preliminary identified through the Sparse Identification of Nonlinear Dynamics (SINDy). This data-driven technique may avoid biases due to incorrect modelling assumptions and exploits SINDy to approximate the system dynamics leveraging a predefi

Théo Durandard, Alexis Ghersengorin

We study the robust regulation of contracts in moral hazard problems. A firm offers a contract to incentivise a worker protected by limited liability. A regulator restricts the set of permissible contracts to (i) improve efficiency and (ii) protect the worker. The regulator faces uncertainty about both the worker's actions and the firm's production cost, and

Federica Ferrarese, Claudia Totzeck

In this paper, we introduce a novel approach to multi-modal optimization by enhancing the recently developed kinetic-based optimization (KBO) method with genetic dynamics (GKBO). The proposed method targets objective functions with multiple global minima, addressing a critical need in fields like engineering design, machine learning, and bioinformatics. By i

John Mangeri, Varun R. Pavizhakumari, Thomas Olsen

We apply density functional theory to explore the magnetoelectric (ME) properties of two-dimensional $\mathrm{Nb}_3\mathrm{(Cl,Br,I)}_8$. These compounds have recently been proposed to exhibit coupled ferroelectric and ferromagnetic order leading to a switchable anomalous valley Hall effect (AVHE). Using both spin-spiral and self-consistent spin-orbit couple

Andrea E. V. Ferrari, Prateek Gupta, Nabil Iqbal

The notion of duality -- that a given physical system can have two different mathematical descriptions -- is a key idea in modern theoretical physics. Establishing a duality in lattice statistical mechanics models requires the construction of a dual Hamiltonian and a map from the original to the dual observables. By using simple neural networks to parameteri

Helmut Harbrecht, Remo von Rickenbach

The present article is concerned with the nonlinear approximation of functions in the Sobolev space H^q with respect to a tensor-product, or hyperbolic wavelet basis on the unit n-cube. Here, q is a real number, which is not necessarily positive. We derive Jackson and Bernstein inequalities to obtain that the approximation classes contain Besov spaces of hyb

Paulo J. Paulino, Albert Cabot, Gabriele De Chiara, Mauro Antezza

Open many-body quantum systems can exhibit intriguing nonequilibrium phases of matter, such as time crystals. In these phases, the state of the system spontaneously breaks the time-translation symmetry of the dynamical generator, which typically manifests through persistent oscillations of an order parameter. A paradigmatic model displaying such a symmetry b

Pete Janowczyk, Linda Laurier, Ave Giulietta, Arlo Octavia

Multi-Modal Language Models (MLLMs) have transformed artificial intelligence by combining visual and text data, making applications like image captioning, visual question answering, and multi-modal content creation possible. This ability to understand and work with complex information has made MLLMs useful in areas such as healthcare, autonomous systems, and

Rahman Mohammadpour

I show that it is consistent relative to the consistency of a Mahlo cardinal that Martin's axiom holds at $\omega_2$, but the weak Kurepa Hypothesis fails. This answers a question posed by Honzik, Lambie-Hanson and Stejskalov\'a. The consistency result is obtained by constructing a model where the weak Kurepa Hypothesis fails in any c.c.c. forcing extension.

Juan Luis Gonzales Santander, Francesco Mainardi

We compare the classical viscoelastic models due to Becker and Lomnitz with respect to a recent viscoelastic model based on the Lambert W function. We take advantage of this comparison to derive new analytical expressions for the relaxation spectrum in the Becker and Lomnitz models, as well as novel integral representations for the retardation and relaxation

Ala Aldin M. H. M. Darghouth, Denis Magero, Mark E. Casida

Ruthenium(II) polypyridine compounds often have a relatively long lived triplet metalligand charge transfer (3MLCT) state, making these complexes useful as chromophores for photoactivated electron transfer in photomolecular devices (PMDs). As different PMDs typically require different ligands and as the luminescence lifetime of the 3MLCT is sensitive to the

Matti Vahs, Shaohang Han, Jana Tumova

Control invariant sets play an important role in safety-critical control and find broad application in numerous fields such as obstacle avoidance for mobile robots. However, finding valid control invariant sets of dynamical systems under input limitations is notoriously difficult. We present an approach to safely expand an initial set while always guaranteei

John Chodacki, Mark Hanhel, Stefano Iacus, Ryan Scherle

The Generalist Repository Ecosystem Initiative (GREI), funded by the NIH, developed an AI taxonomy tailored to data repository roles to guide AI integration across repository management. It categorizes the roles into stages, including acquisition, validation, organization, enhancement, analysis, sharing, and user support, providing a structured framework for

Timo Klein, Christoph Luther, Manus McAuliffe, Lukas Miklautz

Plasticity refers to a network's ability to adapt to changing data distributions, which is crucial for the successful training of deep reinforcement learning agents. Loss of plasticity causes performance plateaus and contributes to scaling failures, overestimation bias, and insufficient exploration. To deepen the understanding of plasticity loss, we propose

Parangama Sarkar

In this article, we extend the notion of multiplicity for weakly graded families of ideals which are bounded below linearly. In particular, we show that the limit $e_W(\mathfrak{I}):=\lim\limits_{n\to\infty}d!\frac{\ell_R(R/I_n)}{n^d}$ exists where $\mathfrak I=\{I_n\}$ is a bounded below linearly weakly graded families of ideals in a Noetherian local ring $

Corinna Burri, Nelson Hua, Dario Ferreira Sanchez, Wenxiang Hu

Van der Waals (vdW) materials exhibit a variety of states that can be switched with low power at low temperatures, offering a viable cryogenic "flash memory" required for the classical control electronics for solid-state quantum information processing. In 1T-TaS2, a non-volatile metallic 'hidden' state can be induced from an insulating equilibrium charge-den

Hans-Christian Herbig, William Osnayder Clavijo Esquivel

We develop the notions of connections and curvature for general Lie-Rinehart algebras without using smoothness assumptions on the base space. We present situations when a connection exists. E.g., this is the case when the underlying module is finitely generated. We show how the group of module automorphism acts as gauge transformations on the space of connec

L. Asquini, M. C. Baglio, S. Campana, P. D'Avanzo

We present spectroscopy of the accreting X-ray binary and millisecond pulsar SAX J1808.4-3658. These observations are the first to be obtained during a reflaring phase. We collected spectroscopic data during the beginning of reflaring of the 2019 outburst and we compare them to previous datasets, taken at different epochs both of the same outburst and across

Ieva Liepuoniute, Kirstin D. Doney, Javier Robledo-Moreno, Joshua A. Job

This study explores the electronic structure of the CH$_2$ molecule, modeled as a (6e, 23o) system using a 52-qubit quantum experiment, which is relevant for interstellar and combustion chemistry. We focused on calculating the dissociation energies for CH$_2$ in the ground state triplet and the first excited state singlet, applying the Sample-based Quantum D

Siyu Chen, Hong Liu, Wenhao Li, Ying Zhu

Depth estimation is a crucial technology in robotics. Recently, self-supervised depth estimation methods have demonstrated great potential as they can efficiently leverage large amounts of unlabelled real-world data. However, most existing methods are designed under the assumption of static scenes, which hinders their adaptability in dynamic environments. To

Ming Cheng, Jiaying Gong, Chenhan Yuan, William A. Ingram

Existing text simplification or paraphrase datasets mainly focus on sentence-level text generation in a general domain. These datasets are typically developed without using domain knowledge. In this paper, we release a novel dataset, VTechAGP, which is the first academic-to-general-audience text paraphrase dataset consisting of document-level these and disse

Panos Pantidis, Cornelius Otchere, Mostafa E. Mobasher

We present a novel image-based adaptive domain decomposition FEM framework to accelerate the solution of continuum damage mechanics problems. The key idea is to use image-processing techniques in order to identify the moving interface between the healthy subdomain and unhealthy subdomain as damage propagates, and then use an iterative Schur complement approa

Xinjing Guo, Menglin Huang, Shiyou Chen

As implemented in the commercialized device modeling software, the four-state nonradiative multi-phonon model has attracted intensive attention in the past decade for describing the physics in negative bias temperature instability (NBTI) and other reliability issues of Si/SiO$_\text{2}$ MOSFET devices. It was proposed initially based on the assumption that t

Tristan Coignion, Clément Quinton, Romain Rouvoy

In recent years,Large Language Models (LLMs) have significantly improved in generating high-quality code, enabling their integration into developers' Integrated Development Environments (IDEs) as code assistants. These assistants, such as GitHub Copilot, deliver real-time code suggestions and can greatly enhance developers' productivity. However, the environ

Seyoung Song, Haneul Yoo, Jiho Jin, Kyunghyun Cho

Historical documents in the Sinosphere are known to share common formats and practices, particularly in veritable records compiled by court historians. This shared linguistic heritage has led researchers to use Classical Chinese resources for cross-lingual transfer when processing historical documents from Korea and Japan, which remain relatively low-resourc

Ibrahim Kajo, Mohamed Kas, Yassine Ruichek

The superior performance introduced by deep learning approaches in removing atmospheric particles such as snow and rain from a single image; favors their usage over classical ones. However, deep learning-based approaches still suffer from challenges related to the particle appearance characteristics such as size, type, and transparency. Furthermore, due to t

Alexander Y. Chuang, Huan Q. Bui, Arthur Christianen, Yiming Zhang

The quantum mechanics of three interacting particles gives rise to interesting universal phenomena, such as the staircase of Efimov trimers predicted in the context of nuclear physics and observed in ultracold gases. Here, we observe a novel type of halo trimer using radiofrequency spectroscopy in an ultracold mixture of $^{23}$Na and $^{40}$K atoms. The tri

Oles Shtanko, Kunal Sharma

It is widely accepted that noisy quantum devices are limited to logarithmic depth circuits unless mid-circuit measurements and error correction are employed. However, this conclusion holds only for unital error channels, such as depolarizing noise. Building on the idea of the "quantum refrigerator" [Ben-Or, Gottesman and Hassidim (2013)], we improve upon pre

Milan Žukovič

We study effects of $q$-order antinematic (AN$_q$) interactions on the critical behavior of the antiferromagnetic (AF) $XY$ model on a square lattice. It is found that the evolution of the phase diagram topology of such AF-AN$_q$ models with the parameter $q$ does not follow the same line as for the corresponding FM-N$_q$ models with the ferromagnetic (FM) a

Kishansingh Rajput, Malachi Schram, Auralee Edelen, Jonathan Colen

Particle accelerator operation requires simultaneous optimization of multiple objectives. Multi-Objective Optimization (MOO) is particularly challenging due to trade-offs between the objectives. Evolutionary algorithms, such as genetic algorithm (GA), have been leveraged for many optimization problems, however, they do not apply to complex control problems b

Martin Miguel Ocampo, Octavio Palermo, Gabriel León, Gabriel R. Bengochea

In this work we analyzed the physical origin of the primordial inhomogeneities during the inflation era. The proposed framework is based, on the one hand, on semiclassical gravity, in which only the matter fields are quantized and not the spacetime metric. Secondly, we incorporate an objective collapse mechanism based on the Continuous Spontaneous Localizati

Mattia Di Mauro, Nicolao Fornengo, Adil Jueid, Roberto Ruiz de Austri

The detection of cosmic antideuterons ($\overline{\rm D}$) at kinetic energies below a few GeV/n could provide a smoking gun signature for dark matter (DM). However, the theoretical uncertainties of coalescence models have represented so far one of the main limiting factors for precise predictions of the $\overline{\rm D}$ flux. In this Letter we present a n

W. Haensch

Neuromorphic computing with crossbar arrays has emerged as a promising alternative to improve computing efficiency for machine learning. Previous work has focused on implementing crossbar arrays to perform basic mathematical operations. However, in this paper, we explore the impact of mapping the layers of an artificial neural network onto physical cross-bar

Alistair Plum, Caroline Döhmer, Emilia Milano, Anne-Marie Lutgen

The Universal Dependencies (UD) project has significantly expanded linguistic coverage across 161 languages, yet Luxembourgish, a West Germanic language spoken by approximately 400,000 people, has remained absent until now. In this paper, we introduce LuxBank, the first UD Treebank for Luxembourgish, addressing the gap in syntactic annotation and analysis fo

Kirsten Köbschall, Lisa Hartung, Stefan Kramer

We propose soft Hoeffding trees (SoHoT) as a new differentiable and transparent model for possibly infinite and changing data streams. Stream mining algorithms such as Hoeffding trees grow based on the incoming data stream, but they currently lack the adaptability of end-to-end deep learning systems. End-to-end learning can be desirable if a feature represen

Lingyu Du, Yupei Liu, Jinyuan Jia, Guohao Lan

Deep regression models are used in a wide variety of safety-critical applications, but are vulnerable to backdoor attacks. Although many defenses have been proposed for classification models, they are ineffective as they do not consider the uniqueness of regression models. First, the outputs of regression models are continuous values instead of discretized l

Rakesh Raj Madavan, Akshat Kaimal, Badhrinarayanan K, Vinayak Gupta

Lensless imaging offers a significant opportunity to develop ultra-compact cameras by removing the conventional bulky lens system. However, without a focusing element, the sensor's output is no longer a direct image but a complex multiplexed scene representation. Traditional methods have attempted to address this challenge by employing learnable inversions a

Alba Gurpegui, Mark Jeeninga, Emma Tegling, Anders Rantzer

Explicit solutions to optimal control problems are rarely obtainable. Of particular interest are the explicit solutions derived for minimax problems, providing a framework to address adversarial conditions and uncertainty. This work considers a multi-disturbance minimax Linear Regulator (LR) framework for positive linear time-invariant systems in continuous

Rohit Kumar, Sourabh Bikas Paul, Nikita Singh

We analyze the impact of the Reserve Bank of India's (RBI) monetary policy communications on Indian financial market from April 2014 to June 2024 using advanced natural language processing techniques. Employing BERTopic for topic modeling and a fine-tuned RoBERTa model for sentiment analysis, we assess how variations in sentiment across different economic to

Sohang Kundu, Hong-Zhou Ye, Timothy C. Berkelbach

Charge transfer (CT) processes that are electronically non-adiabatic are ubiquitous in chemistry, biology, and materials science, but their theoretical description requires diabatic states or adiabatic excited states. For complex systems, these latter states are more difficult to calculate than the adiabatic ground state. Here, we propose a simple method to

Lewis Croney, Ruth Gregory, Sam Patrick

We investigate ultra slow-roll inflation with a seed black hole in a de Sitter background. By numerically tracking transitions from slow-roll to ultra slow-roll inflation, we find that quasi-normal mode solutions of the scalar field are excited following the decay of the slow-roll attractor, depending on the mass of the black hole. For small black holes, the

P. Telang, T. Treu, M. Klinger, A. A. Tsirlin

We present a comprehensive study of the structural, magnetic, and thermodynamic properties, as well as the adiabatic demagnetization refrigeration (ADR) performance of NaGdP$_2$O$_7$. Although NaGdP$_2$O$_7$ exhibits antiferromagnetic ordering at a N\'eel temperature of $T_{\rm N} = 570$ mK in zero field, ADR experiments achieved a minimum temperature of 220

Yu-Chen Guo, Chun-Jing Pan, Man-Qi Ruan, Ji-Chong Yang

This study investigates Neutral Triple Gauge Couplings (nTGCs) through $ZZ$ production at future electron-positron colliders. The impact of beam polarization on cross section is analyzed. We compare the signals and backgrounds for five different $ZZ$ decay channels and present our event selection strategies for future $e^+e^-$ colliders. The expected coeffic

Klim Efremenko, Or Zamir

Traditional error-correcting codes (ECCs) assume a fixed message length, but many scenarios involve ongoing or indefinite transmissions where the message length is not known in advance. For example, when streaming a video, the user should be able to fix a fraction of errors that occurred before any point in time. We introduce unbounded error-correcting codes

Erik Ekström, Yuqiong Wang

We study a stopping game of preemption type between two players who both act under uncertain competition. In this framework we introduce, and study the effect of, (i) asymmetry of payoffs, allowing e.g. for different investment costs, and (ii) consolation, i.e. partial compensation to the forestalled stopper. In general, this setting does not offer an explic

Omar Leon Sanchez

We prove that the theory of differentially closed fields of characteristic zero in $m\geq 1$ commuting derivations DCF$_{0,m}$ satisfies the expected form of the dichotomy. Namely, any minimal type is either locally modular or nonorthogonal to the (algebraically closed) field of constants. This dichotomy is well known for finite-dimensional types; however, a

Justin Curry, Ryan C. Gelnett, Matthew C. B. Zaremsky

We consider the space of all configurations of finitely many (potentially nested) circles in the plane. We prove that this space is aspherical, and compute the fundamental group of each of its connected components. It turns out these fundamental groups are obtained as iterated semidirect products of subgroups of braid groups, with the structure for each comp

Xingyu Lu, Yuhang Hu, Changyi Liu, Tianke Zhang

Mathematical reasoning presents a significant challenge to the cognitive capabilities of LLMs. Various methods have been proposed to enhance the mathematical ability of LLMs. However, few recognize the value of state transition for LLM reasoning. In this work, we define mathematical problem-solving as a process of transiting from an initial unsolved state to

Chenyang Yang, Tesi Xiao, Michael Shavlovsky, Christian Kästner

Machine learning in production needs to balance multiple objectives: This is particularly evident in ranking or recommendation models, where conflicting objectives such as user engagement, satisfaction, diversity, and novelty must be considered at the same time. However, designing multi-objective rankers is inherently a dynamic wicked problem -- there is no

Sayat Ibrayev, Arman Ibrayeva, Bekzat Amanov, Serik Tolenov

This paper presents the development and evaluation of a medical service robot equipped with 3D LiDAR and advanced localization capabilities for use in hospital environments. The robot employs LiDAR-based Simultaneous Localization and Mapping SLAM to navigate autonomously and interact effectively within complex and dynamic healthcare settings. A comparative a

Sayan Paul, Ruddra dev Roychoudhury, Brojeshwar Bhowmick

Visual odometry (VO) is essential for enabling accurate point-goal navigation of embodied agents in indoor environments where GPS and compass sensors are unreliable and inaccurate. However, traditional VO methods face challenges in wide-baseline scenarios, where fast robot motions and low frames per second (FPS) during inference hinder their performance, lea

Leonid Koralov, Ishfaaq Mohammed Imtiyas

In this paper, we consider semi-Markov processes whose transition times and transition probabilities depend on a small parameter $\varepsilon$. Understanding the asymptotic behavior of such processes is needed in order to study the asymptotics of various randomly perturbed dynamical and stochastic systems. The long-time behavior of a semi-Markov process $X^\

Yuxin Zuo, Wenxuan Jiang, Wenxuan Liu, Zixuan Li

Empirical evidence indicates that LLMs exhibit spontaneous cross-lingual alignment. However, although LLMs show promising cross-lingual alignment in Information Extraction (IE), a significant imbalance across languages persists, highlighting an underlying deficiency. To address this, we propose KnowCoder-X, a powerful code LLM with advanced cross-lingual and

Igor Andreoni, Raffaella Margutti, John Banovetz, Sarah Greenstreet

The Legacy Survey of Space and Time (LSST) at Vera C. Rubin Observatory is planned to begin in the Fall of 2025. The LSST survey cadence has been designed via a community-driven process regulated by the Survey Cadence Optimization Committee (SCOC), which recommended up to 3% of the observing time to carry out Target of Opportunity (ToO) observations. Experts

Shuochen Bi, Tingting Deng, Jue Xiao

The outlook for the future of artificial intelligence (AI) in the financial sector, especially in financial forecasting, the challenges and implications. The dynamics of AI technology, including deep learning, reinforcement learning, and integration with blockchAIn and the Internet of Things, also highlight the continued improvement in data processing capabi

Matthew D. Blair, Chamsol Park

We consider restriction analogues on hypersurfaces of the uniform Sobolev inequalities in Kenig, Ruiz, and Sogge and the resolvent estimates in Dos Santos Ferreira, Kenig, and Salo.

Beniamino Di Lorenzo, Gian Carlo Maffettone, Mario di Bernardo

In this paper, we address the large-scale shepherding control problem using a continuification-based strategy. We consider a scenario in which a large group of follower agents (targets) must be confined within a designated goal region through indirect interactions with a controllable set of leader agents (herders). Our approach transforms the microscopic age

Lorenzo Lyons, Manuel Boldrer, Laura Ferranti

This paper presents a novel distributed vehicle platooning control and coordination strategy. We propose a distributed predecessor-follower CACC scheme that allows to choose an arbitrarily small inter-vehicle distance while guaranteeing no rear-end collisions occur, even in the presence of undetected cyber-attacks on the communication channels such as false

Xuewen Han, Neng Wang, Shangkun Che, Hongyang Yang

In recent years, the application of generative artificial intelligence (GenAI) in financial analysis and investment decision-making has gained significant attention. However, most existing approaches rely on single-agent systems, which fail to fully utilize the collaborative potential of multiple AI agents. In this paper, we propose a novel multi-agent colla

Guillaume Bellegarda, Milad Shafiee, Auke Ijspeert

We present a framework for learning a single policy capable of producing all quadruped gaits and transitions. The framework consists of a policy trained with deep reinforcement learning (DRL) to modulate the parameters of a system of abstract oscillators (i.e. Central Pattern Generator), whose output is mapped to joint commands through a pattern formation la

Juan Pablo Aguilera, Thibaut Kouptchinsky

We prove level-by-level upper and lower bounds on the strength of determinacy for finite differences of sets in the hyperarithmetical hierarchy in terms of subsystems of finite-and transfinite-order arithmetic, extending the Montalb\'an-Shore theorem to each of the levels of the Borel hierarchy beyond the one they treated. We also prove equivalences between

Bernardo Gameiro, Jorge Lerendegui-Marco, Victor Babiano-Suarez, Javier Balibrea-Correa

Compton cameras are radiation detectors that provide spatial information on the origin of the {\gamma}-ray sources based on the Compton scattering effect. Many applications require these detectors to be used at high counting rate. As such, the preprocessing of the detections as well as the imaging algorithms are required to be time-efficient in order for the

Zuzanna Osika, Jazmin Zatarain-Salazar, Frans A. Oliehoek, Pradeep K. Murukannaiah

Multi-objective reinforcement learning (MORL) is used to solve problems involving multiple objectives. An MORL agent must make decisions based on the diverse signals provided by distinct reward functions. Training an MORL agent yields a set of solutions (policies), each presenting distinct trade-offs among the objectives (expected returns). MORL enhances exp

Tobias König, Meng Yu

Let $s \in (0, 1]$ and $N > 2s$. It is known that positive solutions to the (fractional) fast diffusion equation $\partial_t u + (-\Delta)^s (u^\frac{N-2s}{N+2s}) = 0$ on $(0, \infty) \times \mathbb R^N$ with regular enough initial datum extinguish after some finite time $T_* > 0$. More precisely, one has $\frac{u(t,\cdot)}{U_{T_*, z, \lambda}(t,\cdot)} - 1

Quan Huu Cap

Whole-slide images (WSI) glomerulus segmentation is essential for accurately diagnosing kidney diseases. In this work, we propose a general and practical pipeline for glomerulus segmentation that effectively enhances both patch-level and WSI-level segmentation tasks. Our approach leverages stitching on overlapping patches, increasing the detection coverage,

Wiebe de Gruijter, Shang-Min Tsai, Michiel Min, Rens Waters

Context. Photochemistry is a key process driving planetary atmospheres away from local thermodynamic equilibrium. Recent observations of the H$_2$ dominated atmospheres of hot gas giants have detected SO$_2$ as one of the major products of this process. Aims. We investigate which chemical pathways lead to the formation of SO$_2$ in an atmosphere, and we inve

Brian Batell, Keith R. Dienes, Brooks Thomas, Scott Watson

This document summarizes the discussions which took place during the PITT-PACC Workshop entitled "Non-Standard Cosmological Epochs and Expansion Histories," held in Pittsburgh, Pennsylvania, Sept. 5-7, 2024. Much like the non-standard cosmological epochs that were the subject of these discussions, the format of this workshop was also non-standard. Rather tha

Tatjana Zähringer, Raimund Girwidz, Andreas Müller

Pictures in physics education go beyond instructional functions and serve affective roles, such as attracting attention, creating fascination, and fostering engagement with the depicted content. Recognizing the importance of these affective functions highlights the need to understand and utilize aesthetic pictures in a research-based educational environment.

Chenlin Gu, Zhonggen Su, Ruizhe Xu

For the supercritical Bernoulli bond percolation on $\mathbb{Z}^d$ ($d \geq 2$), we give a coupling between the random walk on the infinite cluster and its limit Brownian motion, such that the maximum distance between the paths during $[0,T]$ has a mean of order $T^{\frac{1}{3}+o(1)}$. The construction of the coupling utilizes the optimal transport tool. The

Elija Deineko, Carina Kehrt

Finding a feasible and prompt solution to the Vehicle Routing Problem (VRP) is a prerequisite for efficient freight transportation, seamless logistics, and sustainable mobility. Traditional optimization methods reach their limits when confronted with the real-world complexity of VRPs, which involve numerous constraints and objectives. Recently, the ability o

Duc Huy Nguyen, Tim Schneider, Guillaume Duret, Alap Kshirsagar

Training robot policies in simulation is becoming increasingly popular; nevertheless, a precise, reliable, and easy-to-use tactile simulator for contact-rich manipulation tasks is still missing. To close this gap, we develop TacEx -- a modular tactile simulation framework. We embed a state-of-the-art soft-body simulator for contacts named GIPC and vision-bas

Mohammad Tabish, Neil K. Chada, Stefan Klus

The Koopman operator plays a crucial role in analyzing the global behavior of dynamical systems. Existing data-driven methods for approximating the Koopman operator or discovering the governing equations of the underlying system typically require a fixed set of basis functions, also called dictionary. The optimal choice of basis functions is highly problem-d

Weicheng Zhao, Pu-Jian Mao, Jun-Bao Wu

In this paper, we present a second realization of the Weyl double copy (WDC) in four-dimensional algebraic type D spacetime. We show that any type D vacuum solution admits an algebraically general Maxwell scalar on the curved background that squares to give the Weyl scalar. The WDC relation defines a scalar field that satisfies the Klein-Gordon equation sour

Elie Aïdékon, Chengshi Wang, Yaolin Yu

We study the meeting level between squared Bessel (BESQ) flow lines of different dimensions, and show that it gives rise to a jump Markov process. We apply these results to the skew Brownian flow introduced by Burdzy and Chen \cite{burdzy2001local} and Burdzy and Kaspi \cite{burdzy2004lenses}. It allows us to extend the results of \cite{burdzy2001local} and

Yunfan Shi

Despite recent research advancements in adversarial attack methods, current approaches against XAI monitors are still discoverable and slower. In this paper, we present an adaptive framework for attention mask generation to enable stealthy, explainable and efficient PGD image classification adversarial attack under XAI monitors. Specifically, we utilize muta

Anustup Mukherjee, Alaska Subedi

We present a comprehensive first-principles analysis of the thermoelectric transport properties of hole-doped pyrite FeS$_2$ that includes electron-phonon interactions. This work was motivated by the observed variations in the magnitude of thermopower reported in previous experimental and theoretical studies of hole-doped FeS$_2$ systems. Our calculations re

Songnian Xu, Wenhao Zhen, Dein Wong

Let $G$ be a simple connected graph. If every pendant path in $G$ is at least $P_s$, we denote that $G\in \mathbb{G}_s$. For $G \in \mathbb{G}_s$, let $Q_s(G)$ be the set of vertices in $G$ that are distance $s$ from the pendant vertex, and let $|Q_s(G)| = q_s(G)$. For $G \in \mathbb{G}_s$, Li et al. (2024) proved that when $\lambda$ is not an eigenvalue of

Wenjiang Zhou, Nianjie Liang, Xiguang Wu, Shiyun Xiong

Machine-learned potentials (MLPs) have been extensively used to obtain the lattice thermal conductivity via atomistic simulations. However, the impact of force errors in various MLPs on thermal transport has not been widely recognized and remains to be fully understood. Here, we employ MLP-driven molecular dynamics (MD) and anharmonic lattice dynamics (LD) t

Carlos Cárdenas-Bravo, Sylvain Lespinats, Denys Dutykh

The state of health of solar photovoltaic (PV) systems is assessed by measuring the current-voltage (I-V) curves, which present a collection of three cardinal points: the short-circuit point, the open-circuit point, and the maximum power point. To understand the response of PV systems, the I-V curve is typically modeled using the well-known single-diode mode

Andrew Shannon, Conor Houghton, David Barton, Martin Homer

Surrogate modeling of non-linear oscillator networks remains challenging due to discrepancies between simplified analytical models and real-world complexity. To bridge this gap, we investigate hybrid reservoir computing, combining reservoir computing with "expert" analytical models. Simulating the absence of an exact model, we first test the surrogate models

Fabian Wiesner, Ziad Chaoui, Diana Kessler, Anna Pappa

The advantage of quantum protocols lies in the inherent properties of the shared quantum states. These states are sometimes provided by sources that are not trusted, and therefore need to be verified. Finding secure and efficient quantum state verification protocols remains a big challenge, and recent works illustrate trade-offs between efficiency and securi

Yu-Xuan Chen, Takumi Yuri, Kenji Toyoda

We systematically investigate local phonon hopping in the radial direction of a linear trapped-ion string. We measure the decay of hopping as a function of key trap parameters and analyze the results in terms of the decay time and the number of oscillations. We attribute the loss of coherence to nonlinear coupling between different modes. Despite quantitativ

Yihuai Zhang, Ruiguo Zhong, Huan Yu

This paper presents a novel neural operator learning framework for designing boundary control to mitigate stop-and-go congestion on freeways. The freeway traffic dynamics are described by second-order coupled hyperbolic partial differential equations (PDEs). The proposed framework learns feedback boundary control strategies from the closed-loop PDE solution

István Pink, Csaba Sándor

Let $n$ be a positive integer. The Diophantine equation $n(x_1+x_2+\dots +x_n)=x_1x_2\dots x_n$, $1 \le x_1\le x_2\le \dots \le x_n$ is called Erd\H{o}s's last equation. We prove that $x_n\to \infty $ as $n\to \infty$ and determine all tuples $(n,x_1,\dots ,x_n)$ with $x_n\le 10$.

Bernardo Luiz Ribeiro, Cayan Dantas, William Wolf

The flow over a NACA0012 airfoil at a moderate Reynolds number Re = 50,000 and angle of attack of alpha = 3 degrees is investigated using the lattice-Boltzmann method (LBM). The LBM solutions are computed in direct numerical simulation (DNS) mode, i.e., without a wall model. A validation is performed against a Navier-Stokes wall-resolved large eddy simulatio

Geng Sun, Jiaxu Wu, Zemin Sun, Long He

In the era of the sixth generation (6G) and industrial Internet of Things (IIoT), an industrial cyber-physical system (ICPS) drives the proliferation of sensor devices and computing-intensive tasks. To address the limited resources of IIoT sensor devices, unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) has emerged as a promising solution,

Mohsen Dehghankar, Abolfazl Asudeh

Due to a variety of reasons, such as privacy, data in the wild often misses the grouping information required for identifying minorities. On the other hand, it is known that machine learning models are only as good as the data they are trained on and, hence, may underperform for the under-represented minority groups. The missing grouping information presents

Sanja Karilanova, Maxime Fabre, Emre Neftci, Ayça Özçelikkale

Spiking Neural Networks (SNNs) are biologically-inspired deep neural networks that efficiently extract temporal information while offering promising gains in terms of energy efficiency and latency when deployed on neuromorphic devices. SNN parameters are sensitive to temporal resolution, leading to significant performance drops when the temporal resolution o

Kunhao Zhong, Gary Bernstein, Supranta S. Boruah, Bhuvnesh Jain

Nonlinear cosmological fields like galaxy density and lensing convergence can be approximately related to Gaussian fields via analytic point transforms. The lognormal transform (LN) has been widely used and is a simple example of a function that relates nonlinear fields to Gaussian fields. We consider more accurate General Point-Transformed Gaussian (GPTG) f

Taichi Hara, Akira Kusaba, Yoshihiro Kangawa, Tetsuji Kuboyama

h-BCN is an intriguing material system where the bandgap varies considerably depending on the atomic configuration, even at a fixed composition. Exploring stable atomic configurations in this system is crucial for discussing the energetic formability and controllability of desirable configurations. In this study, this challenge is tackled by combining first-

Shambel Sahlu, Bhupendra Kumar Shukla, Rishi Kumar Tiwari, Değer Sofuoğlu

In this paper, we have studied the late-time accelerating expansion of the Universe using the matter-geometry coupled $ f(Q, T) $ gravity model, where $ Q $ is the non-metricity scalar and $ T $ represents the trace of the energy-momentum tensor. We constrain the best-fit values of cosmological parameters $\Omega_{m0}, H_0, \alpha_0~\mbox{and}~ \beta_0$ thro

Hung Tuan Le, Long Truong To, Manh Trong Nguyen, Quyen Nguyen

Determining the difficulty of a text involves assessing various textual features that may impact the reader's text comprehension, yet current research in Vietnamese has only focused on statistical features. This paper introduces a new approach that integrates statistical and semantic approaches to assessing text readability. Our research utilized three disti

Dechen Zhang, Yuan Zhu, Guoxin Zheng, Kuan-Wen Chen

Quantum magnetism is one of the most active fields for exploring exotic phases and phase transitions. The recently synthesized Na2BaCo(PO4)2 (NBCP) is an ideal material incarnation of the spin-1/2 easy axis triangular lattice antiferromagnet (TLAF). Experimental evidence shows that NBCP hosts the spin supersolid state with a giant magnetocaloric effect. It w

Osamu Fukushima, Tomohiro Shigemura, Kentaroh Yoshida

Membrane configurations in the Banks-Fischler-Shenker-Susskind matrix model are unstable due to the existence of flat directions in the potential and the decay process can be seen as a realization of chaotic scattering. In this note, we compute the lifetime of a membrane in a reduced model. The resulting lifetime exhibits scaling laws with respect to energy,

Özlem Tuğfe Demir, Emil Björnson, Luca Sanguinetti

Accurate estimation of the cascaded channel from a user equipment (UE) to a base station (BS) via each reconfigurable intelligent surface (RIS) element is critical to realizing the full potential of the RIS's ability to control the overall channel. The number of parameters to be estimated is equal to the number of RIS elements, requiring an equal number of p

Aniket Deroy, Subhankar Maity

Code-mixing, the integration of lexical and grammatical elements from multiple languages within a single sentence, is a widespread linguistic phenomenon, particularly prevalent in multilingual societies. In India, social media users frequently engage in code-mixed conversations using the Roman script, especially among migrant communities who form online grou

Marco Caliendo, Katrin Huber, Ingo E. Isphording, Jakob Wegmann

Surveys are an indispensable source of data for applied economic research; however, their reliance on self-reported information can introduce bias, especially if core variables such as personal income are misreported. To assess the extent and impact of this misreporting bias, we compare self-reported wages from the German Socio-Economic Panel (SOEP) with adm

Nolan Koblischke, Jo Bovy

Machine learning models in astrophysics are often limited in scope and cannot adapt to data from new instruments or tasks. We introduce SpectraFM, a Transformer-based foundation model architecture that can be pre-trained on stellar spectra from any wavelength range and instrument. SpectraFM excels in generalization by combining flexibility with knowledge tra

Qing-Hong Cao, Shuailiang Ge, Yandong Liu, Jun-Chen Wang

We investigate the Berry phase arising from axion-photon and axion-fermion interactions. The effective Hamiltonians in both systems share the same form, enabling a unified description of the Berry phase and providing a novel perspective on axion experiments. We conceptually propose a new photon-ring experiment for axion detection. Furthermore, we demonstrate

Mingzhong Lu, Yu-Feng Song, Ming Li, Youjin Deng

Spatial self-similarity is a hallmark of critical phenomena. We investigate the dynamic process of percolation, in which bonds are incrementally inserted to an empty lattice until fully occupied, and track the gaps describing the changes in cluster sizes. Surprisingly, we find that the gap sizes follow a universal power-law distribution throughout the whole