November 2024 arXiv papers — page 87

Jonas Lampart, Arnaud Triay

We analyze the many-body Hamiltonian describing a mobile impurity immersed in a Bose-Einstein condensate (BEC). Using exact unitary transformations and rigorous error estimates, we show the validity of the Bogoliubov-Fr\"ohlich Hamiltonian for the Bose polaron in the regime of moderately strong, repulsive interactions with a dilute BEC. Moreover, we calculat

Ravishankar Chatta Subramaniam, Jason W. Morphew, Carina M. Rebello, N. Sanjay Rebello

Investigating students' thinking in classroom tasks, particularly in science and engineering, is essential for improving educational practices and advancing student learning. In this context, the notion of Ways of Thinking (WoT) has gained traction in STEM education, offering a framework to explore how students approach and solve interdisciplinary problems.

Mitsuo Higaki, Yulong Lu, Jinping Zhuge

This paper is concerned with effective approximations and wall laws of viscous laminar flows in 3D pipes with randomly rough boundaries. The random roughness is characterized by the boundary oscillation scale $\varepsilon \ll 1 $ and a probability space with ergodicity quantified by functional inequalities. The results in this paper generalize the previous w

Wangkun Xu, Zhongda Chu, Florin Capitanescu, Fei Teng

With the increasing penetration of Inverter-Based Resources (IBRs), power system stability constraints must be incorporated into the operational framework, transforming it into stability-constrained optimization. Currently, there exist parallel research efforts on developing the stability constraints within DC power flow-based unit commitment (UC) and AC Opt

Jeppe R. Andersen, Ana Cueto, Stephen P. Jones, Andreas Maier

We study the use of cell resampling to reduce the fraction of negatively weighted Monte Carlo events in a generated sample typical of that used in experimental analyses. To this end, we apply the Cell Resampler to a set of $pp \rightarrow \gamma \gamma + \mathrm{jets}$ shower-merged NLO matched events, describing the diphoton background to Higgs boson produc

A. M. Shikin, D. A. Estyunin, N. L. Zaitsev, T. P. Estyunina

The spin-resolved dispersion dependencies for the topological insulator Mn$_{1-x}$Ge$_x$Bi$_2$Te$_4$ in the $\bar{\rm K}\bar{\Gamma}\bar{\rm K}'$ path of the Brillouin zone were studied by spin- and angle-resolved photoemission spectroscopy using laser radiation (Laser Spin-ARPES) with variation of the concentration of substitutional Ge atoms (x from 0.1 to

Léo Vacher, Alessandro Carones, Jonathan Aumont, Jens Chluba

The variation of the physical conditions across the three dimensions of our Galaxy is a major source of complexity for the modelling of the foreground signal facing the cosmic microwave background (CMB). In the present work, we demonstrate that the spin-moment expansion formalism provides a powerful framework to model and understand this complexity, with a s

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

Using $e^+e^-$ collision data corresponding to an integrated luminosity of 19,fb$^{-1}$ collected by the BESIII detector at center-of-mass energies ranging from 4.13 to 4.70,GeV, we report the first evidence for a new excited $\Omega^{-}$ hyperon, the $\Omega(2109)^{-}$, through the process $e^+ e^- \to \Omega(2109)^{-} \bar{\Omega}^{+} +c.c.$ with a signifi

Shaojie Bai, Mohammad Sadegh Talebi, Chengcheng Zhao, Peng Cheng

Reinforcement learning (RL) is a powerful tool for sequential decision-making, but its application is often hindered by privacy concerns arising from its interaction data. This challenge is particularly acute in advanced networked systems, where learning from operational and user data can expose systems to privacy inference attacks. Existing differential pri

Xueqing Liu, Yuchen Xiong, Qiushi Liu, Jiangrui Zheng

In recent years, the rapid growth of security vulnerabilities poses great challenges to tracing and managing them. For example, it was reported that the NVD database experienced significant delays due to the shortage of maintainers. Such delay creates challenges for third-party security personnel (e.g., administrators) to trace the information related to the

Wenxiao Zhan, Siqi Yang, Minghui Liu, Liang Han

The Hessian method is widely applied in the global analysis of parton distribution functions (PDFs), which uses a set of orthogonal eigenvectors to give predictions of a physical observable. Its uncertainty is estimated based on the assumption that all physical observables can be approximately expressed as linear functions of the non-perturbative parameters

Aikya Banerjee, Priyajit Jana, P. K. Mohanty

Ashkin-Teller model is a two-layer lattice model where spins in each layer interact ferromagnetically with strength $J$, and the spin-dipoles (product of spins) interact with neighbors with strength $\lambda.$ The model exhibits simultaneous magnetic and electric transitions along a self-dual line on the $\lambda$-$J$ plane with continuously varying critical

Christine E. Collins, Luke J. Shingles, Stuart A. Sim, Fionntan P. Callan

The double detonation is a widely discussed explosion mechanism for Type Ia supernovae, whereby a helium shell detonation ignites a secondary detonation in the carbon/oxygen core of a white dwarf. Even for modern models that invoke relatively small He shell masses, many previous studies have found that the products of the helium shell detonation lead to disc

Fugui Ma, Wenyi Tian, Weihua Deng

Myxobacteria aggregate and generate fruiting bodies in the soil to survive under starvation conditions. Considering soil as a porous medium, the biological mechanism and dynamic behavior of myxobacteria and slime (chemoattractants) affected by favorable environments in the soil can not be well characterized by the classical full parabolic Keller-Segel system

Mengxuan Li, Ke Liu, Hongyang Chen, Jiajun Bu

Time series anomaly detection aims to identify unusual patterns in data or deviations from systems' expected behavior. The reconstruction-based methods are the mainstream in this task, which learn point-wise representation via unsupervised learning. However, the unlabeled anomaly points in training data may cause these reconstruction-based methods to learn a

Michael Eichberg, Marc Wagner

We present selected preliminary lattice gauge theory results for $O(1/m_Q)$ and $O(1/m_Q^2)$ corrections to the static potential. These results are based on Wilson loops with two field strength insertions, which we renormalize using gradient flow. We explore tree level improvement to reduce systematic errors in the Wilson loops due to the finite lattice spac

Massimo Fornasier, Jona Klemenc, Alessandro Scagliotti

In this paper, we consider functionals of the form $H_\alpha(u)=F(u)+\alpha G(u)$ with $\alpha\in[0,+\infty)$, where $u$ varies in a set $U\neq\emptyset$ (without further structure). We first revisit a result stating that, excluding at most countably many values of $\alpha$, we have $\inf_{H_\alpha^\star}G= \sup_{H_\alpha^\star}G$, where $H_\alpha^\star := \

Yuming Zhu, Emil Prodan

We study the dynamics of synthetic molecules whose architectures are generated by space transformations from a point group acting on seed resonators. We show that the dynamical matrix of any such molecule can be reproduced as the left regular representation of a self-adjoint element from the stabilized group's algebra. Furthermore, we use elements of represe

Joschka Haltaufderheide, Stefanie Pfisterer-Heise, Dawid Pieper, Robert Ranisch

Background: Robot-assisted surgery has been widely adopted in recent years. However, compared to other health technologies operating in close proximity to patients in a vulnerable state, ethical issues of robot-assisted surgery have received less attention. Against the background of increasing automation that are expected to raise new ethical issues, this sy

Shiman Li, Jiayue Zhao, Shaolei Liu, Xiaokun Dai

Deep learning-based medical image segmentation helps assist diagnosis and accelerate the treatment process while the model training usually requires large-scale dense annotation datasets. Weakly semi-supervised medical image segmentation is an essential application because it only requires a small amount of scribbles and a large number of unlabeled data to t

Leon Kopitar, Primoz Kocbek, Lucija Gosak, Gregor Stiglic

This review examines the development of abstractive NLP-based text summarization approaches and compares them to existing techniques for extractive summarization. A brief history of text summarization from the 1950s to the introduction of pre-trained language models such as Bidirectional Encoder Representations from Transformer (BERT) and Generative Pre-trai

Hanieh Shojaei Miandashti, Qianqian Zou, Claus Brenner

Reliable deep learning models require not only accurate predictions but also well-calibrated confidence estimates to ensure dependable uncertainty estimation. This is crucial in safety-critical applications like autonomous driving, which depend on rapid and precise semantic segmentation of LiDAR point clouds for real-time 3D scene understanding. In this work

Zhen Lv, Yangqi Long, Congzhentao Huang, Cao Li

Stereo video synthesis from a monocular input is a demanding task in the fields of spatial computing and virtual reality. The main challenges of this task lie on the insufficiency of high-quality paired stereo videos for training and the difficulty of maintaining the spatio-temporal consistency between frames. Existing methods primarily address these issues

Jiawei Li, Xiaoang Xu, Yang Gao

Model evolution enables learning from feedback to refine experiences and update skills, transforming models from having no domain knowledge to becoming domain experts. However, there is currently no unified and effective method for guiding this evolutionary process. To address this gap, we propose the Meteor method, which includes three training phases: weak

Maria Sabitova

We study the endomorphism ring $End(G_A)$ of a subgroup $G_A$ of $\mathbb{Q}^n$ defined by a non-singular $n\times n$-matrix $A$ with integer entries. In the case when the characteristic polynomial of $A$ is irreducible and an extra assumption holds if $n$ is not prime, we show that $End(G_A)$ is commutative and can be identified with a subring of the number

Jan E. Grabowski, Matthew Pressland

We develop a general theory of cluster categories, applying to a 2-Calabi-Yau extriangulated category $\mathcal{C}$ and cluster-tilting subcategory $\mathcal{T}$ satisfying only mild finiteness conditions. We show that the structure theory of $\mathcal{C}$ and the representation theory of $\mathcal{T}$ give rise to the rich combinatorial structures of seed d

Jitendra Bajpai, Daniele Dona

We prove a version of Jordan's classification theorem for finite subgroups of $\mathrm{GL}_{n}(K)$ that is at the same time quantitatively explicit, CFSG-free, and valid for arbitrary $K$. This is the first proof to satisfy all three properties at once. Our overall strategy follows Larsen and Pink [24], with explicit computations based on techniques develope

Charis Anastopoulos, Konstantina Savvidou

This paper continues on the program of developing a relativistic quantum information theory in terms of unequal-time correlation functions in quantum field theory (QFT)[arXiv:2208.03696]. Here, we focus on the definition of quantum resources from the irreducibly quantum behavior contained in the correlation functions of a QFT. We explain how set-ups with $N$

Sofia Morelli, Nina Effenberger, Luca Schmidt, Nicole Ludwig

Reliable wind speed data is crucial for applications such as estimating local (future) wind power. Global Climate Models (GCMs) and Regional Climate Models (RCMs) provide forecasts over multi-decadal periods. However, their outputs vary substantially, and higher-resolution models come with increased computational demands. In this study, we analyze how the sp

Xuechun Li, Susu Xu

Rapid and accurate estimation of post-earthquake ground failures and building damage is critical for effective post-disaster responses. Progression in remote sensing technologies has paved the way for rapid acquisition of detailed, localized data, enabling swift hazard estimation through analysis of correlation deviations between pre- and post-quake satellit

Sagar J C, Karthik R, Katheek Hegde, K. M. Ajith

Our research aims to probe the anisotropic matter field around black holes using black hole perturbation theory. Black holes in the universe are usually surrounded by matter or fields, and it is important to study the perturbation and the characteristic modes of a black hole that coexists with such a matter field. In this study, we focus on a family of black

Qingyuan Kong, Rujun Jiang, Yihan He

We study the linear convergence rates of the proximal gradient method for composite functions satisfying two classes of Polyak-{\L}ojasiewicz (PL) inequality: the PL inequality, the variant of PL inequality defined by the proximal map-based residual. Using the performance estimation problem, we either provide new explicit linear convergence rates or improve

Jun-Ting Hsieh, Ting-Chun Lin, Sidhanth Mohanty, Ryan O'Donnell

We construct the first explicit two-sided vertex expanders that bypass the spectral barrier. Previously, the strongest known explicit vertex expanders were given by $d$-regular Ramanujan graphs, whose spectral properties imply that every small subset of vertices $S$ has at least $0.5d|S|$ distinct neighbors. However, it is possible to construct Ramanujan gra

Matteo Beccaria, Lorenzo Casarin, Arkady A. Tseytlin

We consider two supersymmetric M5 brane probe solutions in $\textrm{AdS}_7 \times S^4$ and one in $\textrm{AdS}_4 \times S^7$ that all have the $\textrm{AdS}_3 \times S^3$ world-volume geometry. The values of the classical action of the first two M5 probes (with $S^3$ in $\textrm{AdS}_7$ or in $S^4$) are related to the leading $N^2$ parts in the anomaly b-co

Fernando Payró, Evan Piermont

We consider an analyst whose goal is to identify a subject's utility function through revealed preference analysis. We argue the analyst's preference about which experiments to run should adhere to three normative principles: The first, Structural Invariance, requires that the value of a choice experiment only depends on what the experiment may potentially r

Fangzheng Lin, Zhongfa Wang, Hiroshi Sasaki

Speculative execution is crucial in enhancing modern processor performance but can introduce Spectre-type vulnerabilities that may leak sensitive information. Detecting Spectre gadgets from programs has been a research focus to enhance the analysis and understanding of Spectre attacks. However, one of the problems of existing approaches is that they rely on

Duzhen Zhang, Yahan Yu, Chenxing Li, Jiahua Dong

Federated Named Entity Recognition (FNER) boosts model training within each local client by aggregating the model updates of decentralized local clients, without sharing their private data. However, existing FNER methods assume fixed entity types and local clients in advance, leading to their ineffectiveness in practical applications. In a more realistic sce

Hajar Belmahi

Motivated by recent Event Horizon Telescope findings, we investigate constrained optics of rotating black holes in Einstein-Maxwell-scalar gravity theory. Precisely, we mainly study the parameter effects on two relevant optical concepts being the shadow and deflection angle. Using the Hamilton-Jacobi algorithm, we find certain shadow geometries being corrobo

Lars Reichwein, Zheng Gong, Chuan Zheng, Liangliang Ji

Spin-polarized particle beams are of interest for applications like deep-inelastic scattering, e.g. to gain further understanding of the proton's nuclear structure. With the advent of high-intensity laser facilities, laser-plasma-based accelerators offer a promising alternative to standard radiofrequency-based accelerators, as they can shorten the required a

Mingsen Du, Yanxuan Wei, Yingxia Tang, Xiangwei Zheng

Multivariate time series classification is of great importance in practical applications and is a challenging task. However, deep neural network models such as Transformers exhibit high accuracy in multivariate time series classification but lack interpretability and fail to provide insights into the decision-making process. On the other hand, traditional ap

Sabri Mustafa Kahya, Muhammet Sami Yavuz, Eckehard Steinbach

This study proposes a novel approach for real-time facial expression recognition utilizing short-range Frequency-Modulated Continuous-Wave (FMCW) radar equipped with one transmit (Tx), and three receive (Rx) antennas. The system leverages four distinct modalities simultaneously: Range-Doppler images (RDIs), micro range-Doppler Images (micro-RDIs), range azim

Alireza Ghasemifard, Agnieszka Kuc, Thomas Heine

Molybdenum disulfide (MoS$_2$) is a high-potential material for nanoelectronic applications, especially when thinned to a few layers. Liquid phase exfoliation enables large-scale fabrication of thin films comprising single- and few-layer flakes of MoS$_2$ or other transition-metal dichalcogenides (TMDCs), exhibiting variations in flake size, geometry, edge t

Yingte Xu, Gilles Barthe, Li Zhou

Dirac notation is widely used in quantum physics and quantum programming languages to define, compute and reason about quantum states. This paper considers Dirac notation from the perspective of automated reasoning. We prove two main results: first, the first-order theory of Dirac notation is decidable, by a reduction to the theory of real closed fields and

Leo Cazenille, Maxime Toquebiau, Nicolas Lobato-Dauzier, Alessia Loi

This paper investigates the role of communication in improving coordination within robot swarms, focusing on a paradigm where learning and execution occur simultaneously in a decentralized manner. We highlight the role communication can play in addressing the credit assignment problem (individual contribution to the overall performance), and how it can be in

Colby C. Merrill, Jackson Kulik, Dmitry Savransky

In this work, we investigate trajectories that require thrust to maintain periodic structure in the circular restricted three-body problem (CR3BP). We produce bounds in position and velocity space for the energy-constrained reachable set of initial conditions. Our trajectories are energy-optimal and analyzed via linear analysis. We provide validation for our

Xingjian Zhang, Yuhao Wang, Elie Wolfe

Determining potential probability distributions with a given causal graph is vital for causality studies. To bypass the difficulty in characterizing latent variables in a Bayesian network, the nested Markov model provides an elegant algebraic approach by listing exactly all the equality constraints on the observed variables. However, this algebraically motiv

Danny Barash, Emilie Manning, Aidan Van Vleck, Omri Hirsch

Noninvasive optical imaging modalities can probe patient's tissue in 3D and over time generate gigabytes of clinically relevant data per sample. There is a need for AI models to analyze this data and assist clinical workflow. The lack of expert labelers and the large dataset required (>100,000 images) for model training and tuning are the main hurdles in cre

J. Braun, H. J. Bentz

Linear harmonic number sums had been studied by a variety of authors during the last centuries, but only few results are known about nonlinear Euler sums of quadratic or even higher degree. The first systematic study on nonlinear Euler sums consisting of products of hyperharmonic sums had been published by Flajolet and Salvy in 1997 followed by similar studi

Hanno Bertle, Elli Pomoni, Xinyu Zhang, Konstantinos Zoubos

We study the global symmetries of the $\mathbb{Z}_2$-orbifold of N=4 Super-Yang-Mills theory and its marginal deformations. The process of orbifolding to obtain an N=2 theory would appear to break the $\mathrm{SU}(4)$ R-symmetry down to $\mathrm{SU}(2)\times \mathrm{SU}(2)\times \mathrm{U}(1)$. We show that the broken generators can be recovered by moving be

Fatemeh Ghasemi, Swastik Kopparty, Madhu Sudan

In this paper, we construct new t-server Private Information Retrieval (PIR) schemes with communication complexity subpolynomial in the previously best known, for all but finitely many t. Our results are based on combining derivatives (in the spirit of Woodruff-Yekhanin) with the Matching Vector based PIRs of Yekhanin and Efremenko. Previously such a combina

Alexandre Didier, Melanie N. Zeilinger

We propose integrating an approximation of a predictive control barrier function (PCBF) in a safety filter framework, resulting in a prediction horizon independent formulation. The PCBF is defined through the value function of an optimal control problem and ensures invariance as well as stability of a safe set within a larger domain of attraction. We provide

Bangguo Yu, Yuzhen Liu, Lei Han, Hamidreza Kasaei

Following human instructions to explore and search for a specified target in an unfamiliar environment is a crucial skill for mobile service robots. Most of the previous works on object goal navigation have typically focused on a single input modality as the target, which may lead to limited consideration of language descriptions containing detailed attribut

Bertrand Eynard, Soufiane Oukassi

We prove the existence of an algebraic plane curve of equation $P(x,y)=0$, with prescribed asymptotic behaviors at punctures, and with the Boutroux property, namely, periods have vanishing real part, i.e, $\Re(\int_\gamma y dx)=0$ for every closed loop $\gamma$. This has applications in the Riemann-Hilbert problem, in random matrix theory, in spectral networ

Jorin Kouril, Bernd Schäufele, Ilja Radusch, Bettina Schnor

Automated driving is currently a prominent area of scientific work. In the future, highly automated driving and new Advanced Driver Assistance Systems will become reality. While Advanced Driver Assistance Systems and automated driving functions for certain domains are already commercially available, ubiquitous automated driving in complex scenarios remains a

Dmitriy Taubman, Boris Gleyzer, Ke Yang, Farhad Rassekh

This paper designs a market algorithm for fractional ownership of an indivisible asset. It provides an efficient market mechanism, named Direct Fractional Auction (DFA) that offers valuable assets to both small and large investors who can become partial owners of such assets. Additionally, it introduces procedures and algorithms with DFA to determine the opt

Huashan Sun, Yizhe Yang, Yinghao Li, Jiawei Li

Although substantial efforts have been made to mitigate catastrophic forgetting in continual learning, the intrinsic mechanisms are not well understood. In this work, we demonstrate the existence of "pseudo forgetting": the performance degradation on previous tasks is not attributed to a loss of capabilities, but rather to the failure of the instructions to

J. Rozalén Sarmiento, A. Rios

We present an overview of the method of Neural Quantum States applied to the many-body problem of atomic nuclei. Through the lens of group representation theory, we focus on the problem of constructing neural-network ans\"atze that respect physical symmetries. We explicitly prove that determinants, which are among the most common methods to build antisymmetr

Pere Munar-Vallespir, Janis Nötzel

We study the problem of joint communication and sensing for data transmission systems using optimal quantum instruments in order to transmit data and, at the same time, estimate environmental parameters. In particular we consider the specific but at the same time generic case of a noiseless bosonic classical-quantum channel where part of the transmitted ligh

Charles Westphal, Stephen Hailes, Mirco Musolesi

Network Intrusion Detection (NID) remains a key area of research within the information security community, while also being relevant to Machine Learning (ML) practitioners. The latter generally aim to detect attacks using network features, which have been extracted from raw network data typically using dimensionality reduction methods, such as principal com

Shuyun Jiao, David Waxman

Many biological systems are governed by difference equations and exhibit discrete-time dynamics. Examples include the size of a population when generations are non-overlapping, and the incidence of a disease when infections are recorded at fixed intervals. For discrete-time systems lacking exact solutions, continuous-time approximations are frequently employ

Pascal Grange, Linglong Yuan

We consider a run-and-tumble particle on a half-line with an absorbing target at the origin. The particle has an internal velocity state that switches between two opposite values at Poisson-distributed times. The position of the particle evolves according to an overdamped Langevin dynamics with a spatially-periodic force field such that every point in a give

Max Hausmann, Berend van Wachem

In the present paper, we apply the framework of volume-filtering for particle-laden flows, to large eddy simulations (LES) of wall-bounded flows leading to a new perspective on wall-modeled LES (WMLES) that we refer to as volume-filtered WMLES (VF-WMLES). In contrast to existing wall-models, the VF-WMLES framework does not rely on temporal averaging, does no

A. Sahade, A. Vourlidas, C. Mac Cormack

Coronal mass ejections (CMEs) can exhibit non-radial evolution. The background magnetic field is considered the main driver for the trajectory deviation relative to the source region. The influence of the magnetic environment has been largely attributed to the gradient of the magnetic pressure. In this work, we propose a new approach to investigate the role

Panpan Chen, Nader Motee, Qiyu Sun

This paper presents a Carleman-Fourier linearization method for nonlinear dynamical systems with periodic vector fields involving multiple fundamental frequencies. By employing Fourier basis functions, the nonlinear dynamical system is transformed into a linear model on an infinite-dimensional space. The proposed approach yields accurate approximations over

Friedrich Tuttas, Constantin Traub, Marcel Pfeiffer, Walter Fichter

In the context of satellite aerodynamics in the Very-Low-Earth-Orbit (VLEO) regime, accurate modeling of gas-surface interactions (GSI) is crucial for determining aerodynamic forces and torques. Common models such as Sentman's assume that gas particles are reflected diffusely from a surface, which leads to the incorporation of energy accommodation into the m

Pablo Cortes, Alejandra Tabares, Fredy Franco, Astrid Xiomara Rodríguez

The reconfiguration of electrical power distribution systems is a crucial optimization problem aimed at minimizing power losses by altering the system topology through the operation of interconnection switches. This problem, typically modelled as a mixed integer nonlinear program demands high computational resources for large scale networks and requires spec

Zhen Xu, Hua Xing Zhu

Large double-logarithmic corrections are induced by soft gluon emissions near threshold in the semi-inclusive $e^+e^-$ annihilation (SIA) distributions, and must be resummed to all-orders in perturbation theory for reliable theoretical predictions. Building on strategy developed for threshold resummation for DIS structure function in momentum space using sof

Stephan Durr, Philip Rouenhoff

In two dimensions, $U(N_c)$ gauge theories exhibit a non-trivial topological structure, while $SU(N_c)$ theories are topologically trivial. Hence, for $G = U(N_c)$ the phase space is divided into topological sectors, characterized by a topological index (a.k.a. ``topological charge''). These sectors are separated by action barriers, which diverge if the latt

Sankha Shuvra Das, Pablo Garcia-Sanchez, Antonio Ramos, Gilad Yossifon

While previous studies indicated the mobility reversal of an electrically-powered metallo-dielectric Janus particle (JP) with increasing frequency, here we report an intriguing second mobility reversal observed in optoelectronically-driven JPs. In contrast to the commonly used setup with parallel ITO-coated glass substrates to induce a uniform electric field

Gabriele Immordino, Andrea Vaiuso, Andrea Da Ronch, Marcello Righi

This study presents a framework for predicting unsteady transonic wing pressure distributions, integrating an autoencoder architecture with graph convolutional networks and graph-based temporal layers to model time dependencies. The framework compresses high-dimensional pressure distribution data into a lower-dimensional latent space using an autoencoder, en

Adam Gindl, Martin Čmel, František Trojánek, Petr Malý

Some semiconductors have more than one degenerate minimum of the conduction band in their band structure. These minima-known as valleys-can be used for storing and processing information, if it is possible to generate a difference in their electron populations. However, to compete with conventional electronics, it is necessary to develop universal and fast m

Boris Lorbeer, Axel Küpper

We live in a world full of complex systems which we need to improve our understanding of. To accomplish this, purely probabilistic investigations are often not enough. They are only the first step and must be followed by learning the system's underlying mechanisms. This is what the discipline of causality is concerned with. Many of those complex systems cont

Klaus M. Miller, Bernd Skiera, Julia Schmitt

Privacy regulations aim to safeguard consumers, but can have unintended consequences on how users interact with websites. This article estimates the causal effect of the EU's General Data Protection Regulation (GDPR) on online usage behavior and decomposes it into usage frequency (unique visitors) and usage intensity (visits per unique visitor). Using a

Jie Zou, Jimmy Xiangji Huang, Zhaochun Ren, Evangelos Kanoulas

Online shopping platforms, such as Amazon and AliExpress, are increasingly prevalent in society, helping customers purchase products conveniently. With recent progress in natural language processing, researchers and practitioners shift their focus from traditional product search to conversational product search. Conversational product search enables user-mac

J. S. Gonçalves, A. F. Santos

In this paper, $f(R,\lm, T)$ gravity is considered. It is a generalization of the theories $f(R,T)$ and $f(R, \lm)$. This modified theory of gravity exhibits strong geometry-matter coupling. The problem of causality and its violation is verified in this model. Such analysis is carried out using G\"{o}del-type solutions considering different types of matter.

Akash Harapanahalli, Samuel Coogan

Infinitesimal contraction analysis provides exponential convergence rates between arbitrary pairs of trajectories of a system by studying the system's linearization. An essentially equivalent viewpoint arises through stability analysis of a linear differential inclusion (LDI) encompassing the incremental behavior of the system. In this note, we use contracti

Xiaodong Guo, Xiaokang Li, Lingxiao Zhao, Zengwei Zhu

The electrical conductivity of metallic crystals exhibits size effects when the electron mean free path exceeds the sample thickness. One such phenomenon, known as Sondheimer oscillations, was discovered decades ago. These oscillations, periodic in magnetic field, have been hitherto treated with no reference to Landau quantization. Here, we present a study o

Alaska Subedi, Kamran Behnia

Semi-Dirac fermions are massless in one direction and massive in the perpendicular directions. Such quasiparticles have been proposed in various contexts in condensed matter. Using first principles calculations, we identify a pair of semi-Dirac bands anti-crossing at $-3$ eV below the Fermi level in the electronic structure of hexagonal close-packed cadmium.

S. Veronese, W. J. G. de Blok, J. Healy, D. Kleiner

The observed star formation rates of galaxies in the Local Universe suggests that they are replenishing their gas reservoir across cosmic time. Cosmological simulations predict that this accretion of fresh gas can occur in a hot or a cold mode, yet the existence of low column density ($\sim10^{17}$ cm$^{-2}$) neutral atomic hydrogen (HI) tracing the cold mod

Clément Cancès, Maxime Herda, Annamaria Massimini

We present a finite volume scheme for modeling the diffusion of charged particles, specifically ions, in constrained geometries using a degenerate Poisson-Nernst-Planck system with size exclusion yielding cross-diffusion. Our method utilizes a two-point flux approximation and is part of the exponentially fitted scheme framework. The scheme is shown to be the

Lasse M. Reinpold, Marvin Schieseck, Lukas P. Wagner, Felix Gehlhoff

Requirements engineering is a knowledge intensive process and crucial for the success of engineering projects. The field of knowledge-based requirements engineering (KBRE) aims to support engineers by providing knowledge to assist in the elicitation, validation, and management of system requirements. The advent of large language models (LLMs) opens new oppor

Ziyi Yang, Zaibin Zhang, Zirui Zheng, Yuxian Jiang

There has been a growing interest in enhancing rule-based agent-based models (ABMs) for social media platforms (i.e., X, Reddit) with more realistic large language model (LLM) agents, thereby allowing for a more nuanced study of complex systems. As a result, several LLM-based ABMs have been proposed in the past year. While they hold promise, each simulator i

Vida Zamanifarizhandi, Joni Virta

The Oja depth (simplicial volume depth) is one of the classical statistical techniques for measuring the central tendency of data in multivariate space. Despite the widespread emergence of object data like images, texts, matrices or graphs, a well-developed and suitable version of Oja depth for object data is lacking. To address this shortcoming, a novel mea

Andrej Kancko, Cinthia Antunes Corrêa, Ross Harvey Colman

We report the crystal structures, magnetic and thermodynamic properties of two magnetically frustrated $A$'$A$"$M_2$F$_7$-type antiferromagnets, NaCdNi$_2$F$_7$ and NaCdMn$_2$F$_7$. While NaCdNi$_2$F$_7$ forms a stable pyrochlore structure (SG: $Fd \overline{3} m$, #227) with magnetic $S$ = 1 Ni$^{2+}$ ions on the frustrated pyrochlore 16$c$ site and fully d

Richard J Anslow, Amy Bonsor, Paul B Rimmer, Auriol S P Rae

Hydrogen cyanide delivered by cometary impactors can be concentrated as ferrocyanide salts, which may support the initial stages of prebiotic chemistry on the early Earth. One way to achieve the conditions required for a variety of prebiotic scenarios, requiring for example the formation of cyanamide and cyanoacetylene, is through the arrival of a secondary

Jakob Kellner, Saharon Shelah

If $\lambda$ is (strongly) inaccessible and $2^\lambda = \lambda^+$, then there is a nowhere trivial automorphism of the Boolean algebra $\mathcal P(\lambda)/[\lambda]^{<\lambda}$.

Yiyong Sun, Jiajun He, Zhidi Lin, Wenqiang Pu

Accurate prediction of mmWave time-varying channels is essential for mitigating the issue of channel aging in complex scenarios owing to high user mobility. Existing channel prediction methods have limitations: classical model-based methods often struggle to track highly nonlinear channel dynamics due to limited expert knowledge, while emerging data-driven m

Shivani Sharma, Darshika G. Perera

Neuromorphic computing, inspired by biological neural networks, has emerged as a promising approach for solving complex machine learning tasks with greater efficiency and lower power consumption. The integration of biologically plausible learning algorithms, such as the Generalized Hebbian Algorithm (GHA), is key to enhancing the performance of neuromorphic

Kunpeng Zhang, Xinlei Yi, Jinliang Ding, Ming Cao

This paper studies the distributed bandit convex optimization problem with time-varying inequality constraints, where the goal is to minimize network regret and cumulative constraint violation. To calculate network cumulative constraint violation, existing distributed bandit online algorithms solving this problem directly use the clipped constraint function

Shanlin Huang, Gengsheng Wang, Ming Wang

This paper studies observability inequalities for heat equations on both bounded domains and the whole space $\mathbb{R}^d$. The observation sets are measured by log-type Hausdorff contents, which are induced by certain log-type gauge functions closely related to the heat kernel. On a bounded domain, we derive the observability inequality for observation set

Shuvrodeb Adikary, Matthew W. Urban, Murthy N. Guddati

Tissue viscoelasticity is becoming an increasingly useful biomarker beyond elasticity and can theoretically be estimated using shear wave elastography (SWE), by inverting the propagation and attenuation characteristics of shear waves. Estimating viscosity is often more difficult than elasticity because attenuation, the main effect of viscosity, leads to poor

Christopher Duffey, Michael Lea, Julie Brisset

This paper presents the design and development of a Shear and Compression Cell (SCC) for measuring the mechanical properties of granular materials in low-gravity environments. This research is motivated by the increasing interest in planetary exploration missions that involve surface interactions, such as those to asteroids and moons. The SCC is designed to

Andreas Costa, Osamu Kanehira, Hiroaki Matsueda, Jaroslav Fabian

Chiral materials lacking mirror symmetry can exhibit unconventional spin-orbit fields, including fully momentum-aligned radial Rashba fields as seen in twisted van der Waals homobilayers. We theoretically study Cooper-pair transfer in superconductor/ferromagnet/superconductor Josephson junctions with crossed (tangential and radial) interfacial Rashba fields.

Boudewijn Bosch

The colored Jones polynomial associated to a knot admits an expansion of knot invariants known as the large-color expansion or Melvin-Morton-Rozansky expansion. We will show how this expansion can be derived from the universal invariant arising from a Hopf algebra $\mathbb{D}$, as introduced by Bar-Natan and Van der Veen. We utilize a Mathematica implementat

Elizaveta Reganova, Peter Steinbach

Large Language Models (LLMs) have gained significant popularity in recent years for their ability to answer questions in various fields. However, these models have a tendency to "hallucinate" their responses, making it challenging to evaluate their performance. A major challenge is determining how to assess the certainty of a model's predictions and how it c

Juan P. Aguilera, Joan Bagaria, Philipp Lücke

We introduce exacting cardinals and a strengthening of these, ultraexacting cardinals. These are natural large cardinals defined equivalently as weak forms of rank-Berkeley cardinals, strong forms of J\'onsson cardinals, or in terms of principles of structural reflection. However, they challenge commonly held intuition on strong axioms of infinity. We prove

Varun Gadey, Raphael Goetz, Christoph Sendner, Sampo Sovio

Securing sensitive operations in today's interconnected software landscape is crucial yet challenging. Modern platforms rely on Trusted Execution Environments (TEEs), such as Intel SGX and ARM TrustZone, to isolate security sensitive code from the main system, reducing the Trusted Computing Base (TCB) and providing stronger assurances. However, identifying w

M. Mereb, L. Vendramin

We prove that the Rubik's cube group can be realized as a Galois group over the rationals.

I. A. Aleksandrov, N. N. Rosanov

We examine the phenomenon of electron-positron pair production from vacuum in a combination of two counterpropagating electromagnetic pulses having a duration of the order of the Compton time. We show that in this extreme short-time domain, the momentum distributions of the particles produced possess a peculiar structure which strongly depends on whether the

Alvaro Donís Vela, Carlo W. J. Beenakker

The stationary Dirac equation $(p\cdot\sigma)\psi=E\psi$, confined to a two-dimensional (2D) region, supports states propagating along the boundary and decaying exponentially away from the boundary. These edge states appear on the 2D surface of a 3D topological insulator, where massless fermionic quasiparticles are governed by the Dirac equation and confined