March 2024 arXiv papers — page 172

Igor V. Kolokolov, Vladimir V. Lebedev

We present theory of two-dimensional turbulence excited by an external force in thin fluid films on scales larger than the film thickness. The principal feature of two-dimensional turbulence is the tendency of producing motions of larger and larger scales thanks to the nonlinear interaction. The tendency leads to formation of the so-called inverse cascade an

Yajie Liu, Pu Ge, Qingjie Liu, Di Huang

Recently, learning open-vocabulary semantic segmentation from text supervision has achieved promising downstream performance. Nevertheless, current approaches encounter an alignment granularity gap owing to the absence of dense annotations, wherein they learn coarse image/region-text alignment during training yet perform group/pixel-level predictions at infe

R. Manick, A. P. Sousa, J. Bouvier, J. M. Almenara

Detecting planets within protoplanetary disks around young stars is essential for understanding planet formation and evolution. However, planet detection using the radial velocity method faces challenges due to strong stellar activity in these early stages. We aim to detect long-term periodicities in photometric and spectroscopic time series of the classical

Tian-Cai Peng, Zi-Yue Bai, Jun-Zhang Wang, Xiang Liu

Recently, the BESIII collaboration performed a precise measurement of the $e^+e^-\to \eta J/\psi$ cross section. It is puzzling that the resonance parameters of the reported $Y(4230)$ show a substantial divergence from the previously measured results in both the open-charmed and hidden-charmed decay channels, and the line shape asymmetry of the data approach

Jingru Zhu, Ya Guo, Geng Sun, Liang Hong

Semantic segmentation of high-resolution remote sensing imagery (HRSI) suffers from the domain shift, resulting in poor performance of the model in another unseen domain. Unsupervised domain adaptive (UDA) semantic segmentation aims to adapt the semantic segmentation model trained on the labeled source domain to an unlabeled target domain. However, the exist

YongQing Liu

In this paper, we reveal an internal structure within Dedekind numbers, demonstrating that they can be expressed as polynomials of powers of 2. This discovery is based on innovative concepts and methods, offering a new perspective on the nature of these numbers.

Alban Farchi, Marcin Chrust, Marc Bocquet, Massimo Bonavita

In recent years, there has been significant progress in the development of fully data-driven global numerical weather prediction models. These machine learning weather prediction models have their strength, notably accuracy and low computational requirements, but also their weakness: they struggle to represent fundamental dynamical balances, and they are far

Sebastien Salva, Jarod Sue

The focus of this paper is on automating the security testing of RESTful APIs. The testing stage of this specific kind of components is often performed manually, and this is yet considered as a long and difficult activity. This paper proposes an automated approach to help developers generate test cases for experimenting with each service in isolation. This a

Felix Brakel, Uraz Odyurt, Ana-Lucia Varbanescu

Neural networks have become a cornerstone of machine learning. As the trend for these to get more and more complex continues, so does the underlying hardware and software infrastructure for training and deployment. In this survey we answer three research questions: "What types of model parallelism exist?", "What are the challenges of model parallelism?", and

Yifan Bao, Yihao Ang, Qiang Huang, Anthony K. H. Tung

Time Series Generation (TSG) has emerged as a pivotal technique in synthesizing data that accurately mirrors real-world time series, becoming indispensable in numerous applications. Despite significant advancements in TSG, its efficacy frequently hinges on having large training datasets. This dependency presents a substantial challenge in data-scarce scenari

Liyu Song, Helei Liu, Chunhua Zhu, Guoqing Zhen

Using the MESA code, we have carried out a detailed survey of the available parameter space for the double-peaked type I X-ray bursts. We find that the double-peaked structure appears at mass accretion rate $\dot{M}$ in the range of $\sim(4-8)\times10^{-10}\,M_{\odot}/{\rm yr}$ when metallicity $Z=0.01$, while in the range of $\sim(4-8)\times10^{-9}\,M_{\odo

Dieter Rautenbach, Florian Werner

A common subgraph of two graphs $G_1$ and $G_2$ is a graph that is isomorphic to subgraphs of $G_1$ and $G_2$. In the largest common subgraph problem the task is to determine a common subgraph for two given graphs $G_1$ and $G_2$ that is of maximum possible size ${\rm lcs}(G_1,G_2)$. This natural problem generalizes the well-studied graph isomorphism problem

Meem Arafat Manab

As we keep rapidly advancing toward an era where artificial intelligence is a constant and normative experience for most of us, we must also be aware of what this vision and this progress entail. By first approximating neural connections and activities in computer circuits and then creating more and more sophisticated versions of this crude approximation, we

Pierre Mergny, Justin Ko, Florent Krzakala

We discuss the inhomogeneous spiked Wigner model, a theoretical framework recently introduced to study structured noise in various learning scenarios, through the prism of random matrix theory, with a specific focus on its spectral properties. Our primary objective is to find an optimal spectral method and to extend the celebrated \cite{BBP} (BBP) phase tran

Marcin Raczkowski, Fakher F. Assaad

We map out the ground state phase diagram of a one-dimensional SU($N$) Kondo-Heisenberg lattice model at half filling and in the fully antisymmetric self-adjoint representation as a function of $\tfrac {1}{N}$ and Kondo coupling $J_k/t$. On the basis of auxiliary field quantum Monte Carlo (QMC) simulations with even $N$ up to 8, we show that the enlarged SU(

C. Paz-Soldan, S. Gu, N. Leuthold, P. Lunia

The operational space and global performance of plasmas with edge-localized modes (ELMs) suppressed by resonant magnetic perturbations (RMPs) are surveyed by comparing AUG, DIII-D, EAST, and KSTAR stationary operating points. RMP-ELM suppression is achieved over a range of plasma currents, toroidal fields, and RMP toroidal mode numbers. Consistent operationa

Yandong Bai, Wenpei Jia

Bermond and Thomassen conjectured in 1981 that every digraph with minimum outdegree at least $2k-1$ contains $k$ vertex-disjoint cycles,here $k$ is a positive integer. Lichiardopol conjectured in 2014 that for every positive integer $k$ there exists an integer $g(k)$ such that every digraph with minimum outdegree at least $g(k)$ contains $k$ vertex-disjoint

Yufan Chen, Ching Ting Leung, Yong Huang, Jianwei Sun

In the field of chemical structure recognition, the task of converting molecular images into machine-readable data formats such as SMILES string stands as a significant challenge, primarily due to the varied drawing styles and conventions prevalent in chemical literature. To bridge this gap, we proposed MolNexTR, a novel image-to-graph deep learning model th

Yikun Sun, Zhen Wan, Nobuhiro Ueda, Sakiko Yahata

The creation of instruction data and evaluation benchmarks for serving Large language models often involves enormous human annotation. This issue becomes particularly pronounced when rapidly developing such resources for a non-English language like Japanese. Instead of following the popular practice of directly translating existing English resources into Jap

Kaidi Chen, Ben Chen, Dehong Gao, Huangyu Dai

Existing Neural Machine Translation (NMT) models mainly handle translation in the general domain, while overlooking domains with special writing formulas, such as e-commerce and legal documents. Taking e-commerce as an example, the texts usually include amounts of domain-related words and have more grammar problems, which leads to inferior performances of cu

Liya Popova, Valerie J. Carabetta

The revolutionary progress in development of next-generation sequencing (NGS) technologies has made it possible to deliver accurate genomic information in a timely manner. Over the past several years, NGS has transformed biomedical and clinical research and found its application in the field of personalized medicine. Here we discuss the rise of personalized

Lianghui Luo

We consider the precise upper large deviations estimates for the maximal displacement of a branching random walk. In addition, we obtain a description of the extremal process of the branching random walk conditioned on this large deviations event. This introduces a family of point measure playing a role similar to the decoration measures introduced in [9] fo

Laureano F. Escudero, M. Araceli Garín, Aitziber Unzueta

The cross dock door design problem consists of deciding on the number and capacity of inbound and outbound doors for receiving product pallets from origin nodes and exiting them to destination nodes. The uncertainty, realized in scenarios, lies in the occurrence of these nodes, the number and cost of the pallets, and the disruption of the capacity of the doo

Igor V. Kolokolov, Vladimir V. Lebedev

We examine fluctuations of vorticity excited by an external random force in two-dimensional fluid in the presence of a strong external shear flow. The problem is motivated by the analysis of big coherent vortices appearing as a consequence of the inverse energy cascade in a finite box at large Reynolds numbers. We develop the perturbation theory for calculat

Nicholas Rabb, Nitya Nadgir, Jan P. de Ruiter, Lenore Cowen

How political beliefs change in accordance with media exposure is a complicated matter. Some studies have been able to demonstrate that groups with different media diets in the aggregate (e.g., U.S. media consumers ingesting partisan news) arrive at different beliefs about policy issues, but proving this from data at a granular level -- at the level of attit

Tim Kräuter, Patrick Stünkel, Adrian Rutle, Yngve Lamo

The Visual Debugger is an IntelliJ IDEA plugin that presents debug information as an object diagram to enhance program understanding. Reflecting on our past development, we detail the lessons learned and roadblocks we have experienced while implementing and integrating the Visual Debugger into the IntelliJ IDEA. Furthermore, we describe recent improvements t

D. N. Starostin

This article advances the hypothesis that the heightened eschatological sensitivity evident among the historians writing in the 5th century and its weaker echos in the time of Charlemagne were caused by the irregularities of the the lunisolar calendar and its particular realization, the Easter calendar. The lunisolar calendar that Christians used for the cal

Chuanyu Luo, Nuo Cheng, Ren Zhong, Haipeng Jiang

With the rapid advancement of hardware and software technologies, research in autonomous driving has seen significant growth. The prevailing framework for multi-sensor autonomous driving encompasses sensor installation, perception, path planning, decision-making, and motion control. At the perception phase, a common approach involves utilizing neural network

Emilio Gómez-Déniz, Pablo Dorta-González

Measuring the impact of a publication in a fair way is a significant challenge in bibliometrics, as it must not introduce biases between fields and should enable comparison of the impact of publications from different years. In this paper, we propose a Bayesian approach to tackle this problem, motivated by empirical data demonstrating heterogeneity in citati

Orazio Scarlatella, Nigel R. Cooper

Subwavelength arrays of quantum two-level emitters have emerged as an interesting platform displaying prominent collective effects that can be harnessed for applications. Here we study such arrays under strong coherent driving, realizing an open quantum many-body problem in a strongly non-linear regime. For this we introduce a novel approach to this problem

Enrico Ballini, Luca Formaggia, Alessio Fumagalli, Anna Scotti

We apply reduced-order modeling (ROM) techniques to single-phase flow in faulted porous media, accounting for changing rock properties and fault geometry variations using a radial basis function mesh deformation method. This approach benefits from a mixed-dimensional framework that effectively manages the resulting non-conforming mesh. To streamline complex

Shaoyu Yang, Xiang Chen, Ke Liu, Guang Yang

When drafting question posts for Stack Overflow, developers may not accurately summarize the core problems in the question titles, which can cause these questions to not get timely help. Therefore, improving the quality of question titles has attracted the wide attention of researchers. An initial study aimed to automatically generate the titles by only anal

Bingheng Li, Xuanting Xie, Haoxiang Lei, Ruiyi Fang

Graph Neural Networks (GNNs) have garnered significant attention for their success in learning the representation of homophilic or heterophilic graphs. However, they cannot generalize well to real-world graphs with different levels of homophily. In response, the Possion-Charlier Network (PCNet) \cite{li2024pc}, the previous work, allows graph representation

Libin Zheng, Zihao Wang, Minru Bai, Zhenjie Tan

In the rapidly evolving landscape of 5G and beyond 5G (B5G) mobile cellular communications, efficient data compression and reconstruction strategies become paramount, especially in massive multiple-input multiple-output (MIMO) systems. A critical challenge in these systems is the capacity-limited fronthaul, particularly in the context of the Ethernet-based c

Kalibinuer Tiliwalidi

Currently, infrared imaging technology enjoys widespread usage, with infrared object detection technology experiencing a surge in prominence. While previous studies have delved into physical attacks on infrared object detectors, the implementation of these techniques remains complex. For instance, some approaches entail the use of bulb boards or infrared QR

Jianshi Sun, Xiangjun Liu, Yucheng Xiong, Yuhang Yao

Two-dimensional gallium nitride (2D-GaN) has great potential in power electronics and optoelectronics. Heat dissipation is a critical issue for these applications of 2D-GaN. Previous studies showed that higher-order phonon-phonon scattering has extremely strong effects on the lattice thermal conductivity of 2D-GaN, which exhibits noticeable discrepancies wit

Francesco Emanuele Stradi, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti

We study online learning in constrained Markov decision processes (CMDPs) with adversarial losses and stochastic hard constraints, under bandit feedback. We consider three scenarios. In the first one, we address general CMDPs, where we design an algorithm attaining sublinear regret and cumulative positive constraints violation. In the second scenario, under

Xavier Bou, Thibaud Ehret, Rafael Grompone von Gioi, Jeremy Anger

Identifying flood affected areas in remote sensing data is a critical problem in earth observation to analyze flood impact and drive responses. While a number of methods have been proposed in the literature, there are two main limitations in available flood detection datasets: (1) a lack of region variability is commonly observed and/or (2) they require to d

Zhao Kang, Xuanting Xie, Bingheng Li, Erlin Pan

In today's data-driven digital era, the amount as well as complexity, such as multi-view, non-Euclidean, and multi-relational, of the collected data are growing exponentially or even faster. Clustering, which unsupervisely extracts valid knowledge from data, is extremely useful in practice. However, existing methods are independently developed to handle one

Weichun Xia, Lei Shi

The existing research on spectral algorithms, applied within a Reproducing Kernel Hilbert Space (RKHS), has primarily focused on general kernel functions, often neglecting the inherent structure of the input feature space. Our paper introduces a new perspective, asserting that input data are situated within a low-dimensional manifold embedded in a higher-dim

Nikola Jedličková, Jan Kratochvíl

A Hamiltonian path (cycle) in a graph is a path (cycle, respectively) which passes through all of its vertices. The problems of deciding the existence of a Hamiltonian cycle (path) in an input graph are well known to be NP-complete, and restricted classes of graphs which allow for their polynomial-time solutions are intensively investigated. Until very recen

Ion Nechita, Sang-Jun Park

The group symmetries inherent in quantum channels often make them tractable and applicable to various problems in quantum information theory. In this paper, we introduce natural probability distributions for covariant quantum channels. Specifically, this is achieved through the application of ``twirling operations'' on random quantum channels derived from th

Paolo Burelli, Laurits Dixen

Videogames have been a catalyst for advances in many research fields, such as artificial intelligence, human-computer interaction or virtual reality. Over the years, research in fields such as artificial intelligence has enabled the design of new types of games, while games have often served as a powerful tool for testing and simulation. Can this also happen

Michele Bucelli, Francesco Regazzoni, Luca Dede', Alfio Quarteroni

Multiphysics simulations frequently require transferring solution fields between subproblems with non-matching spatial discretizations, typically using interpolation techniques. Standard methods are usually based on measuring the closeness between points by means of the Euclidean distance, which does not account for curvature, cuts, cavities or other non-tri

Liam J Berrisford, Ronaldo Menezes

Ambient air pollution is a pervasive issue with wide-ranging effects on human health, ecosystem vitality, and economic structures. Utilizing data on ambient air pollution concentrations, researchers can perform comprehensive analyses to uncover the multifaceted impacts of air pollution across society. To this end, we introduce Environmental Insights, an open

Joseph Breeden, Luca Zaccarian, Dimitra Panagou

This paper presents extensions of control barrier function (CBF) theory to systems with disturbances wherein a controller only receives measurements infrequently and operates open-loop between measurements, while still satisfying state constraints. The paper considers both impulsive and continuous actuators, and models the actuators, measurements, disturbanc

Muhammad Kashif Ali, Eun Woo Im, Dongjin Kim, Tae Hyun Kim

Video stabilization is a longstanding computer vision problem, particularly pixel-level synthesis solutions for video stabilization which synthesize full frames add to the complexity of this task. These techniques aim to stabilize videos by synthesizing full frames while enhancing the stability of the considered video. This intensifies the complexity of the

Laura Martín, Luis Sánchez, Jorge Lanza, Pablo Sotres

Nowadays, data is becoming the new fuel for economic wealth and creation of novel and profitable business models. Multitude of technologies are contributing to an abundance of information sources which are already the baseline for multi-millionaire services and applications. Internet of Things (IoT), is probably the most representative one. However, for an e

Shrinit Singh

In this paper, we study the $C$-width of HNN extension of a group via its proper isomorphic subgroups and amalgamated free product of two groups via their proper isomorphic subgroups with respect to conjugation invariant generating set. We will also establish that infinite one relator group has infinite $C$-width.

Xuanting Xie, Zhao Kang, Wenyu Chen

Graph is a fundamental mathematical structure in characterizing relations between different objects and has been widely used on various learning tasks. Most methods implicitly assume a given graph to be accurate and complete. However, real data is inevitably noisy and sparse, which will lead to inferior results. Despite the remarkable success of recent graph

Tobias Duswald, Brendan Keith, Boyan Lazarov, Socratis Petrides

This work highlights an approach for incorporating realistic uncertainties into scientific computing workflows based on finite elements, focusing on applications in computational mechanics and design optimization. We leverage Mat\'ern-type Gaussian random fields (GRFs) generated using the SPDE method to model aleatoric uncertainties, including environmental

Leonhard Hahn, Tim Pfahler, Tobias Bader, Gerald Gold

This paper reports on 3D-printed dielectric image lines for low-loss subTHz applications between 140 and 220 GHz. In contrast to conventional dielectric waveguides, a conductive copper substrate is used to achieve robust routing and increased mechanical stability. For easy integration and characterization of the dielectric image line within a waveguide measu

Karen S Auestad, The Tien Mai, Mina Spremic, Jo Eidsvik

Stochastic reservoir characterization, a critical aspect of subsurface exploration for oil and gas reservoirs, relies on stochastic methods to model and understand subsurface properties using seismic data. This paper addresses the computational challenges associated with Bayesian reservoir inversion methods, focusing on two key obstacles: the demanding forwa

Yizhong Liu, Andi Liu, Yuan Lu, Zhuocheng Pan

Sharding enhances blockchain scalability by dividing the network into shards, each managing specific unspent transaction outputs or accounts. As an introduced new transaction type, cross-shard transactions pose a critical challenge to the security and efficiency of sharding blockchains. Currently, there is a lack of a generic sharding consensus pattern that

Chris J Mitchell

This paper re-examines the security of three related block cipher modes of operation designed to provide authenticated encryption. These modes, known as PES-PCBC, IOBC and EPBC, were all proposed in the mid-1990s. However, analyses of security of the latter two modes were published more recently. In each case one or more papers describing security issues wit

Luigi Marra, Guy Y. Cornejo Maceda, Andrea Meilán-Vila, Vanesa Guerrero

We propose a data-driven methodology to learn a low-dimensional manifold of controlled flows. The starting point is resolving snapshot flow data for a representative ensemble of actuations. Key enablers for the actuation manifold are isometric mapping as encoder and a combination of a neural network and a k-nearest-neighbour interpolation as decoder. This me

Dechuan Sun, Gregory Tanyi, Alan Lee, Chris French

Mass production of augmented reality (AR) waveguides has been challenging due to the intricate nature of the fabrication technique and the high precision required for its optical characteristics. In this paper, we have presented a novel and low-cost approach for fabricating geometric optical waveguides designed for AR applications utilizing 3D printing techn

Pavel Panteleev, Gleb Kalachev

We study sheaf codes, a type of linear codes with a fixed hierarchical collection of local codes, viewed as a sheaf of vector spaces on a finite topological space we call coded space. Many existing codes, such as tensor product codes, Sipser-Spielman codes, and their more recent high-dimensional analogs, can be naturally represented as sheaf codes on simplic

Qian Zhao, Kaitong Sun, Si Wu, Hai-Feng Li

We synthesized the ferromagnetic EuAgP semiconductor and conducted a comprehensive study of its crystalline, magnetic, heat capacity, band gap, and magnetoresistance properties. Our investigation utilized a combination of X-ray diffraction, optical, and PPMS DynaCool measurements. EuAgP adopts a hexagonal structure with the $P6_3/mmc$ space group. As the tem

Enzo Brox, Riccardo Di Francesco

Many individuals hesitate to disclose their sexual orientation, anticipating that disclosure may alter how others respond to them. At the same time, concealing one's identity can entail substantial personal and social costs. Understanding how others react to sexual orientation disclosure is therefore central to evaluating the broader consequences of coming o

Laura Martín, Jorge Lanza, Víctor González, Juan Ramón Santana

Nowadays, there are plenty of data sources generating massive amounts of information that, combined with novel data analytics frameworks, are meant to support optimisation in many application domains. Nonetheless, there are still shortcomings in terms of data discoverability, accessibility and interoperability. Open Data portals have emerged as a shift towar

Calum Hughes, Adrian Miranda

We give an elementary description of $2$-categories $\mathbf{Cat}\left(\mathcal{E}\right)$ of internal categories, functors and natural transformations, where $\mathcal{E}$ is a category modelling Lawvere's elementary theory of the category of sets (ETCS). This extends Bourke's characterisation of $2$-categories $\mathbf{Cat}\left(\mathcal{E}\right)$ where $

Daniel Dempsey, Jason Wyse

Distributed Lag Models (DLMs) and similar regression approaches such as MIDAS have been used for many decades in econometrics and more recently to investigate how poor air quality adversely affects human health. In this paper we describe how to expand the utility of these models for Bayesian inference by leveraging latent variables. In particular we explain

Yucheng Wang, Min Wu, Ruibing Jin, Xiaoli Li

Sourced from multiple sensors and organized chronologically, Multivariate Time-Series (MTS) data involves crucial spatial-temporal dependencies. To capture these dependencies, Graph Neural Networks (GNNs) have emerged as powerful tools. As explicit graphs are not inherent to MTS data, graph generation becomes a critical first step in adapting GNNs to this do

Minoru Wakimoto

In this paper we compute the characters of certain non-irreducible N=4 superconformal modules which are different from the ones treated in our previous paper, and study their relation with characters of N=2 superconformal modules. Also, for these non-irreducible N=4 modules, we deduce the expression of characters in terms of string functions.

Di Zhang, Moyang Wang, Joseph Mango, Xiang Li

The challenge of spatial resource allocation is pervasive across various domains such as transportation, industry, and daily life. As the scale of real-world issues continues to expand and demands for real-time solutions increase, traditional algorithms face significant computational pressures, struggling to achieve optimal efficiency and real-time capabilit

Himanshu Prabhat, Raktim Bhattacharya

This paper presents a novel distribution-agnostic Wasserstein distance-based estimation framework. The goal is to determine an optimal map combining prior estimate with measurement likelihood such that posterior estimation error optimally reaches the Dirac delta distribution with minimal effort. The Wasserstein metric is used to quantify the effort of transp

Eslam Eldeeb, Mohammad Shehab, Hirley Alves

Task-oriented semantic communication is an emerging technology that transmits only the relevant semantics of a message instead of the whole message to achieve a specific task. It reduces latency, compresses the data, and is more robust in low SNR scenarios. This work presents a multi-task-oriented semantic communication framework for connected and autonomous

In-Gyu Lee, Jun-Young Oh, Hee-Jung Yu, Jae-Hwan Kim

Recently, with increasing interest in pet healthcare, the demand for computer-aided diagnosis (CAD) systems in veterinary medicine has increased. The development of veterinary CAD has stagnated due to a lack of sufficient radiology data. To overcome the challenge, we propose a generative active learning framework based on a variational autoencoder. This appr

Jiawei Huang, Hajime Tanaka, Taku Komura, Yoshifumi Kitamura

In production rendering systems, caustics are typically rendered via photon mapping and gathering, a process often hindered by insufficient photon density. In this paper, we propose a novel photon guiding method to improve the photon density and overall quality for caustic rendering. The key insight of our approach is the application of a global 3D Gaussian

Xidong Wang, Nuo Chen, Junyin Chen, Yidong Wang

Despite the vast repository of global medical knowledge predominantly being in English, local languages are crucial for delivering tailored healthcare services, particularly in areas with limited medical resources. To extend the reach of medical AI advancements to a broader population, we aim to develop medical LLMs across the six most widely spoken language

Victor Dhédin, Adithya Kumar Chinnakkonda Ravi, Armand Jordana, Huaijiang Zhu

Legged robots have become capable of performing highly dynamic maneuvers in the past few years. However, agile locomotion in highly constrained environments such as stepping stones is still a challenge. In this paper, we propose a combination of model-based control, search, and learning to design efficient control policies for agile locomotion on stepping st

Jieliang Hong, Jie Xiong

Let $X=(X_t, t\geq 0)$ be a superprocess in a random environment described by a Gaussian noise $W^g=\{W^g(t,x), t\geq 0, x\in \mathbb{R}^d\}$ white in time and colored in space with correlation kernel $g(x,y)$. We show that when $d=1$, $X_t$ admits a jointly continuous density function $X_t(x)$ that is a unique in law solution to a stochastic partial differe

Mihailo Stojnic

We consider \emph{random linear programs} (rlps) as a subclass of \emph{random optimization problems} (rops) and study their typical behavior. Our particular focus is on appropriate linear objectives which connect the rlps to the mean widths of random polyhedrons/polytopes. Utilizing the powerful machinery of \emph{random duality theory} (RDT) \cite{StojnicR

Yibin Chen, Yifu Yuan, Zeyu Zhang, Yan Zheng

Spreadsheets are ubiquitous across the World Wide Web, playing a critical role in enhancing work efficiency across various domains. Large language model (LLM) has been recently attempted for automatic spreadsheet manipulation but has not yet been investigated in complicated and realistic tasks where reasoning challenges exist (e.g., long horizon manipulation

Sirui Miao, Neng Ye, Peisen Wang, Qiaolin Ouyang

The rapid advance of mega-constellation facilitates the booming of direct-to-satellite massive access, where multi-user detection is critical to alleviate the induced inter-user interference. While centralized implementation of on-board detection induces unaffordable complexity for a single satellite, this paper proposes to allocate the processing load among

Thomas Schultz

Correlated rotational alignment spectroscopy correlates observables of ultrafast gas-phase spectroscopy with high-resolution, broad-band rotational Raman spectra. This article reviews the measurement principle of CRASY, existing implementations for mass-correlated measurements, and the potential for future developments. New spectroscopic capabilities are dis

Alexandre Seuret, Rafael Vazquez, Luca Zaccarian

This paper introduces a hybrid dynamical system methodology for managing impulsive control in spacecraft rendezvous and proximity operations under the Hill-Clohessy-Wiltshire model. We address the control design problem by isolating the out-of-plane from the in-plane dynamics and present a feedback control law for each of them. This law is based on a Lyapuno

Honglin Wen, Pierre Pinson, Jie Gu, Zhijian Jin

Machine learning methods are widely and successfully used for probabilistic wind power forecasting, yet the pervasive issue of missing values (e.g., due to sensor faults or communication outages) has received limited attention. The prevailing practice is impute-then-predict, but conditioning on point imputations biases parameter estimates and fails to propag

Emile Bouaziz

We study a differential graded VOA associated to the derived critical locus of a function $f$ on a smooth oriented $D$-dimensional variety $(X,\mathbf{vol})$. Informally, this VOA, $\mathbf{crit}^{ch}_{f}$, is just the algebra of chiral differential operators on the derived critical locus $\mathbf{crit}_{f}$. We prove, using a generalization of a physical co

Fredrik Rusek, Jose Flordelis, Kun Zhao, Erik Bengtsson

A standard reconfigurable intelligent surface (RIS) can be configured to reflect signals from an arbitrary impinging direction to an arbitrary outgoing direction. However, if a signal impinges from any other direction, said signal is reflected, with full beamforming gain, to a specific direction, which is easily determined. The goal of this paper is to propo

Arik Reuter, Bishnu Khadka, Anton Thielmann, Christoph Weisser

Topic modeling seems to be almost synonymous with generating lists of top words to represent topics within large text corpora. However, deducing a topic from such list of individual terms can require substantial expertise and experience, making topic modelling less accessible to people unfamiliar with the particularities and pitfalls of top-word interpretati

Jiahui Geng, Yova Kementchedjhieva, Preslav Nakov, Iryna Gurevych

Multimodal large language models (MLLMs) carry the potential to support humans in processing vast amounts of information. While MLLMs are already being used as a fact-checking tool, their abilities and limitations in this regard are understudied. Here is aim to bridge this gap. In particular, we propose a framework for systematically assessing the capacity o

Venus Rai, Subhadip Jana, Jörg Perßon, Shibabrata Nandi

The discovery of a significantly large anomalous Hall effect in the chiral antiferromagnetic system - Mn$_3$Ge - indicates that the Weyl points are widely separated in phase space and positioned near the Fermi surface. In order to examine the effects of Fe substitution in Mn$_3$Ge on the presence and location of the Weyl points, we synthesized (Mn$_{1-\alpha

Mohan, Raj Kumar Mistri, Ram Krishna Pandey

Given a positive integer $h$ and a nonempty finite set of integers $A=\{a_{1},a_{2},\ldots,a_{k}\}$, the restricted $h$-fold signed sumset of $A$, denoted by $h^{\wedge}_{\pm}A$, is defined as $$h^{\wedge}_{\pm}A=\left\lbrace \sum_{i=1}^{k} \lambda_{i} a_{i}: \lambda_{i} \in \left\lbrace -1, 0, 1\right\rbrace \ \text{for} \ i= 1, 2, \ldots, k \ \text{and} \

Jared Miller, Tianyu Dai, Mario Sznaier

The Error-in-Variables model of system identification/control involves nontrivial input and measurement corruption of observed data, resulting in generically nonconvex optimization problems. This paper performs full-state-feedback stabilizing control of all discrete-time linear systems that are consistent with observed data for which the input and measuremen

Gaurav Bhatnagar, Archna Kumari

We provide an alternate approach to obtaining expansion formulas on the lines of the well-poised Bailey lemma. We recover results due to Spiridonov and Warnaar and one new formula of this type. These formulas contain an arbitrary sequence as an argument, and are thus flexible in the number of parameters they contain. As a result, we are able to derive $19$ n

Vinayak Krishnamurthy, Ergun Akleman

We present medial parametrization, a new approach to parameterizing any compact planar domain bounded by simple closed curves. The basic premise behind our proposed approach is to use two close Voronoi sites, which we call dipoles, to construct and reconstruct an approximate piecewise-linear version of the original boundary and medial axis through Voronoi te

M. Nashaat, E. Kovalenko, Yu. M. Shukrinov

The dynamics of magnetization and current-voltage characteristics of the superconductor-ferromagnet-superconductor $\varphi_0$ Josephson junction in the presence of external electromagnetic radiation have been studied. Effects of radiation magnetic component are investigated in the frameworks of one- and two-signal models. The implementation of two types of

Hannah C. Strauch, Fengling Zhang, Stefan Mathias, Thorsten Hohage

Extreme ultraviolet pulses as generated by high harmonic generation (HHG) are a powerful tool for both time-resolved spectroscopy and coherent diffractive imaging. However, the integration of spectroscopy and microscopy to harness the unique broadband spectra provided by HHG is hardly explored due to the challenge to decouple spectroscopic and microscopic in

V. Rivasseau

Assuming some familiarity with quantum field theory and with the tensor track approach that we presented in the previous series Tensor Track I-VII, we provide, as usual, the developments in tensors models of the last two years. Then we expose the fundamental breakthrough of Martin Hairer on regularity structures and the work of L\'eonard Ferdinand on stochas

Hanqing Zhou, Anastasia Nikolova, Pengcheng An

This Late-Breaking Work explores the significance of socio-emotional learning (SEL) and the challenges inherent in designing child-appropriate technologies, namely storytelling agents, to support SEL. We aim to probe their needs and preferences regarding agents for SEL by conducting co-design which involves children co-creating characters and social-emotiona

Łukasz Kułacz

Dynamic spectrum access is essential for radiocommunication and its limited spectrum resources. The key element of dynamic spectrum access systems is effective spectrum occupancy detection. In many cases, machine learning algorithms improve detection effectiveness. Because of the recent trend of using federated learning, a federated learning algorithm is pre

Barbara Olmi, Elena Amato, Rino Bandiera, Pasquale Blasi

Context. We propose that the X-ray filaments emerging from selected bow shock pulsar wind nebulae are due to a charge-separated outflow of electrons and/or positrons escaping the nebula and propagating along the local Galactic magnetic field. Aims. The X-ray brightness, length, and thickness of filaments are all accounted for if a nonresonant streaming insta

Alessio Borzì

We characterize the realizability of a quotient of matroids, over an infinite field $K$, in terms of the realizability over $K$ of a single matroid associated to it, called the Higgs major. This result extends to realizability of flag matroids. Further, we provide some applications to the relative realizability problem for Bergman fans in tropical geometry.

Oothan Nweit, Daqing Yang

For a graph $G$ and an integer $k\geq 2$, a $\chi'_{k}$-coloring of $G$ is an edge coloring of $G$ such that the subgraph induced by the edges of each color has all degrees congruent to $1 ~ (\mod k)$, and $\chi'_{k}(G)$ is the minimum number of colors in a $\chi'_{k}$-coloring of $G$. In ["The mod $k$ chromatic index of graphs is $O(k)$", J. Graph Theory. 2

Paul Wilsens, Katrien Antonio, Gerda Claeskens

Hierarchical categorical variables often exhibit many levels (high granularity) and many classes within each level (high dimensionality). This may cause overfitting and estimation issues when including such covariates in a predictive model. In current literature, a hierarchical covariate is often incorporated via nested random effects. However, this does not

Kinshuk Jerath, Klaus M. Miller, D. Daniel Sokol

Privacy-enhancing technologies (PETs) represent a critical operational challenge for the online advertising industry, requiring substantial infrastructure investment while promising improved consumer privacy protection. Even when PETs may improve privacy protection from an operational or technical viewpoint, understanding whether PETs actually reduce consume

Dang Thoai Phan

Acoustic recognition has emerged as a prominent task in deep learning research, frequently utilizing spectral feature extraction techniques such as the spectrogram from the Short-Time Fourier Transform and the scalogram from the Wavelet Transform. However, there is a notable deficiency in studies that comprehensively discuss the advantages, drawbacks, and pe

Timo Mueller-Tribbensee, Klaus M. Miller, Bernd Skiera

Prestigious news publishers, and more recently, Meta, have begun to request that users pay for privacy. Specifically, users receive a notification banner, referred to as a pay-or-tracking wall, that requires them to (i) pay money to avoid being tracked or (ii) consent to being tracked. These walls have invited concerns that privacy might become a luxury. How