May 2024 arXiv papers — page 4

Fernando Albiac, Jose L. Ansorena, Vladimir Temlyakov

Although the basic idea behind the concept of a greedy basis had been around for some time, the formal development of a theory of greedy bases was initiated in 1999 with the publication of the article [S.~V.~Konyagin and V.~N.~Temlyakov, A remark on greedy approximation in Banach spaces, East J. Approx. 5 (1999), no. 3, 365--379]. The theoretical simplicity

Jia-Xiang Li, Song Wu, Li-Li Hao, Qun-Li Lei

Macromolecules can gain special properties by adopting knotted conformations, but engineering knotted macromolecules is a challenging task. Here we surprisingly observed that knotting can be very effectively produced in active polymers. When one end of an actively reptative polymer is anchored, it can undergo continual self-knotting as a result of intermitte

Abdur Rehman Anwar, Maruša Mur, Georgia Michailidou, Dimitrios N. Bikiaris

Traceability, security and freshness monitoring are crucial to the food and pharmaceutical industries. Currently, barcodes and sensors are almost exclusively located on product packaging. Making them edible and introducing them into edible products could significantly enhance their functions. Here, several types of microlasers made entirely out of edible sub

Yuren Zhou, Yuqi Gu, David B. Dunson

Our interest is in multiplex network data with multiple network samples observed across the same set of nodes. Examples originate from a variety of fields, including brain connectivity, international trade networks, and social networks, among others. Our goal is to infer a hierarchical structure of the nodes at a population level, while performing multi-reso

Simla Burcu Harma, Ayan Chakraborty, Elizaveta Kostenok, Danila Mishin

The increasing size of deep neural networks (DNNs) necessitates effective model compression to reduce their computational and memory footprints. Sparsity and quantization are two prominent compression methods that have been shown to reduce DNNs' computational and memory footprints significantly while preserving model accuracy. However, how these two methods

Colin Weller, Dongjun Li, Yanbei Chen

Recent detections of gravitational waves have made black hole quasinormal modes a powerful tool in testing predictions of general relativity. Understanding the spectrum of these quasinormal modes in a broad class of theories beyond general relativity and a variety of astrophysical environments around black holes remains vital. In this work, we study the quas

Ayon Ghosh, L. A. Prashanth, Krishna Jagannathan

We consider the problem of estimating the Optimized Certainty Equivalent (OCE) risk from independent and identically distributed (i.i.d.) samples. For the classic sample average approximation (SAA) of OCE, we derive mean-squared error as well as concentration bounds (assuming sub-Gaussianity). Further, we analyze an efficient stochastic approximation-based O

Marcelo E. Coniglio, Martín Figallo, Abilio Rodrigues

In this paper, we investigate proof-theoretic aspects of the logics of evidence and truth LETJ and LETF. These logics extend, respectively, Nelson's logic N and the logic of first-degree entailment FDE, also known as Belnap-Dunn four-valued logic, with a classicality operator that recovers classical logic for formulas in its scope. We will present natural de

Karolina Drabik, Tomáš Masařík

Finding a few solutions for a given problem that are diverse, as opposed to finding a single best solution to solve the problem, has recently become a notable topic in theoretical computer science. Recently, Baste, Fellows, Jaffke, Masa\v{r}\'ik, Oliveira, Philip, and Rosamond showed that under a standard structural parameterization by treewidth, one can fin

Bertrand Martinez, Robert Babjak, Marija Vranic

Positron creation and acceleration is one of the major challenges for constructing future lepton colliders. On the one hand, conventional technology can provide a solution, but at a prohibitive cost and scale. On the other hand, alternative, reduced-scale ideas for positron beam generation could bring this dream closer to reality. Here we propose a novel pla

S. De, S. Mandal, Sanket Sen, Arnab Sen

The three-body dissociation dynamics of the dicationic camphor molecule (C$_{10}$H$_{16}$O$^{2+}$) resulting from Auger decay are investigated using soft X-ray synchrotron radiation. A photoelectron-photoion-photoion coincidence (PEPIPICO) method, a combination of a velocity map imaging (VMI) spectrometer and a time-of-flight (ToF) spectrometer is employed t

Dylan Neff

The moments of proton and net-proton multiplicity distributions are observables expected to be sensitive to the QCD critical point and the nature of the QCD phase transition from QGP to hadron gas. Hyper-order cumulants are measured in wide centrality bins in STAR BES-I data and found to be qualitatively consistent with trends predicted by lattice QCD which

Dylan Neff

The second phase of the RHIC Beam Energy Scan (BES-II) was conducted between 2019 and 2021. High statistics data was collected by the STAR experiment for Au+Au collisions at $\sqrt{s_{NN}}$ from 7.7 to 27 GeV in collider mode and from 3 to 13.7 GeV in fixed target mode. A selection of results from the various BES-II analyses are presented here to showcase th

Denys Malyshev, Maria Chernyakova, Felix Aharonian, Andrea Santangelo

HESS J1702-420 is a peculiar TeV complex with a morphology changing from a diffuse (HESS J1702-420B source) at $\lesssim 2$ TeV to point-like (HESS J1702-420A) at $\gtrsim 10$ TeV energies. The morphology and the spectral properties of HESS J1702-420 could be understood in terms of a (diffusive) hadronic or leptonic models in which the observed TeV emission

Valerio Antonini, Michael Scriney, Alessandra Mileo, Mark Roantree

The global sports analytics industry has a market value of USD 3.78 billion in 2023. The increase of wearables such as GPS sensors has provided analysts with large fine-grained datasets detailing player performance. Traditional analysis of this data focuses on individual athletes with measures of internal and external loading such as distance covered in spee

ATLAS Collaboration

A search for a hypothetical heavy scalar particle, $X$, decaying into a singlet scalar particle, $S$, and a Standard Model Higgs boson, $H$, using 140 fb$^{-1}$ of proton-proton collision data at the centre-of-mass energy of 13 TeV recorded with the ATLAS detector at the LHC is presented. The explored mass range is $300 \leq m_X \leq 1000$ GeV and $170 \leq

Ioannis D. Gialamas, Timo J. Kärkkäinen, Luca Marzola

Generalized uncertainty principles are effective changes to the Heisenberg uncertainty principle that emerge in several quantum gravity models. In the present letter, we study the consequences that two classes of these modifications yield on the physics of neutrinos. Besides analyzing the change in the oscillation probabilities that the generalized uncertain

Florin Ambro

We investigate the emptiness of adjoint linear systems associated to successive multiples of a given positive divisor with real coefficients

Shayan Majidy

Students often begin physics courses with misconceptions rooted in everyday experience and intuition, which can be resistant to change. While research has identified strategies for addressing misconceptions across physics, it remains unclear whether different domains, like classical and quantum physics, require different approaches. On one hand, quantum conc

Markus Weißenhofer, Alberto Marmodoro

Magnon band structures in altermagnets are characterized by an energy splitting of modes with opposite chirality, even in the absence of applied external fields and relativistic effects, due to an anisotropy in the Heisenberg exchange interactions. We perform quantitative atomistic spin dynamics simulations based on ab initio electronic structure calculation

Jose' M. Carcione, Jing Ba

The analogy between electromagnetism and gravitation was achieved by linearizing the tensorial gravitational equations of general relativity and converting them into a vector form corresponding to Maxwell's electromagnetic equations. On this basis, we use the equivalence with viscoelasticity (SH waves) and propose a theory of gravitational waves. We add a da

Holger Frahm, Sascha Gehrmann

The finite-size spectrum of the critical staggered six-vertex model with antidiagonal boundary conditions is studied. Similar to the case of periodic boundary conditions, we identify three different phases. In two of those, the underlying conformal field theory can be identified to be related to the twisted $U(1)$ Kac-Moody algebra. In contrast, the finite s

Martina Contisciani, Marius Hobbhahn, Eleanor A. Power, Philipp Hennig

Networked datasets can be enriched by different types of information about individual nodes or edges. However, most existing methods for analyzing such datasets struggle to handle the complexity of heterogeneous data, often requiring substantial model-specific analysis. In this paper, we develop a probabilistic generative model to perform inference in multil

İlker Işık, Ebru Aydin Gol, Ramazan Gokberk Cinbis

Temporal logic is a framework for representing and reasoning about propositions that evolve over time. It is commonly used for specifying requirements in various domains, including hardware and software systems, as well as robotics. Specification mining or formula generation involves extracting temporal logic formulae from system traces and has numerous appl

Lucy Temple, Gabriela Viale Pereira, Lukas Daniel Klausner

This short paper represents a systematic literature review that sets the basis for the future development of a framework for digital twin-based decision support in the public sector, specifically for the smart city domain. The final aim of the research is to model context-specific digital twins for aiding the decision-making processes in smart cities and dev

Metod Jazbec, Alexander Timans, Tin Hadži Veljković, Kaspar Sakmann

Scaling machine learning models significantly improves their performance. However, such gains come at the cost of inference being slow and resource-intensive. Early-exit neural networks (EENNs) offer a promising solution: they accelerate inference by allowing intermediate layers to exit and produce a prediction early. Yet a fundamental issue with EENNs is ho

Zuyan Wang, Jun Tao, Dika Zou

The growing popular awareness of personal privacy raises the following quandary: what is the new paradigm for collecting and protecting the data produced by ever-increasing sensor devices. Most previous studies on co-design of data aggregation and privacy preservation assume that a trusted fusion center adheres to privacy regimes. Very recent work has taken

Christopher T. S. Cheung, Zachary A. H. Goodwin, Yixuan Han, Jiong Lu

Twisted bilayers of two-dimensional materials have emerged as a highly tunable platform for studying broken symmetry phases. While most interest has been focused on emergent states in systems whose constituent monolayers do not feature broken symmetry states, assembling monolayers that exhibit ordered states into twisted bilayers can also give rise to intere

Roberta Citro, Claudio Guarcello, Sergio Pagano

In the realm of physics, a pivotal moment occurred six decades ago when Brian Josephson made a groundbreaking prediction, setting in motion a series of events that would eventually earn him the prestigious Nobel Prize eleven years later. This prediction centered around what is now known as the Josephson effect, a phenomenon with far-reaching implications. At

Ming Du, Tao Zhou, Junjing Deng, Daniel J. Ching

Ptychography is a powerful imaging technique that is used in a variety of fields, including materials science, biology, and nanotechnology. However, the accuracy of the reconstructed ptychography image is highly dependent on the accuracy of the recorded probe positions which often contain errors. These errors are typically corrected jointly with phase retrie

Paul Rosa, Judith Rousseau

We consider the nonparametric regression problem when the covariates are located on an unknown smooth compact submanifold of a Euclidean space. Under defining a random geometric graph structure over the covariates we analyze the asymptotic frequentist behaviour of the posterior distribution arising from Bayesian priors designed through random basis expansion

Federico Bernini, Bartosz Bieganowski, Daniel Strzelecki

In the paper, we utilize the recent variational, abstract theorem to show the existence of homoclinic solutions to the Hamiltonian system $$ \dot{z} = J D_z H(z, t), \quad t \in \mathbb{R}, $$ where the Hamiltonian $H : \mathbb{R}^{2N} \times \mathbb{R} \rightarrow \mathbb{R}$ is of the form $$ H(z, t) = \frac12 Az \cdot z + \Gamma(t) \left( F(z) - \lambda G

Zoe Nieraeth

The goal of this paper is to unify the theory of weights beyond the setting of weighted Lebesgue spaces in the general setting of quasi-Banach function spaces. We prove new characterizations for the boundedness of singular integrals, pose several conjectures, and prove partial results related to the duality of the Hardy-Littlewood maximal operator. Furthermo

Adithya TG, Adithya SK, Abhinav R Bharadwaj, Abhiram HA

Interacting and understanding with text heavy visual content with multiple images is a major challenge for traditional vision models. This paper is on enhancing vision models' capability to comprehend or understand and learn from images containing a huge amount of textual information from the likes of textbooks and research papers which contain multiple imag

Alex Lence, Federica Granese, Ahmad Fall, Blaise Hanczar

In this work, we address the challenge of reconstructing the complete 12-lead ECG signal from its incomplete parts. We focus on two main scenarios: (i) reconstructing missing signal segments within an ECG lead and (ii) recovering entire leads from signal in another unique lead. Two emerging clinical applications emphasize the relevance of our work. The first

Paolo Conti, Jonas Kneifl, Andrea Manzoni, Attilio Frangi

The simulation of many complex phenomena in engineering and science requires solving expensive, high-dimensional systems of partial differential equations (PDEs). To circumvent this, reduced-order models (ROMs) have been developed to speed up computations. However, when governing equations are unknown or partially known, typically ROMs lack interpretability

Patrick De Causmaecker, Lennart Van Hirtum

We study systems of equations on antichains, together with a way to count the number of solutions. We start with a simple example, generalise and show more applications. One of the results was used in the recent computation of D(9), the others have potential to speed up existing techniques in the future. In fact, the result of two independent computations of

Valeria Mascolo, Alessandro Lovo, Corentin Herbert, Freddy Bouchet

Extreme events are the major weather-related hazard for humanity. It is then of crucial importance to have a good understanding of their statistics and to be able to forecast them. However, lack of sufficient data makes their study particularly challenging. In this work, we provide a simple framework for studying extreme events that tackles the lack of data

Rongwu Xu, Zehan Qi, Wei Xu

Large language models (LLMs) showcase impressive reasoning capabilities when coupled with Chain-of-Thought (CoT) prompting. However, the robustness of this approach warrants further investigation. In this paper, we introduce a novel scenario termed preemptive answers, where the LLM obtains an answer before engaging in reasoning. This situation can arise inad

Pierre-Henri Chavanis

A model of magnetic universe based on nonlinear electrodynamics has been introduced by Kruglov. This model describes an early inflation era followed by a radiation era. We show that this model is related to our model of universe based on a quadratic equation of state. We discuss two quantitatively different models of early universe. In Model I, the primordia

Alexa Morales, Steven Finkelstein, Micaela Bagley, Anahita Alavi

We present an analysis of rest-frame UV colors of 17,243 galaxies at $z\sim2-4$ in the HST UVCANDELS fields: GOODS-N, GOODS-S, COSMOS, and EGS. Here, we study the rest-frame UV spectral slope, $\beta$, measured via model spectra obtained via spectral energy distribution (SED) fitting, $\beta_{SED}$, and explore its correlation with various galaxy parameters

David Rodriguez, Ian Yang, Jose M. Del Alamo, Norman Sadeh

The number and dynamic nature of web and mobile applications presents significant challenges for assessing their compliance with data protection laws. In this context, symbolic and statistical Natural Language Processing (NLP) techniques have been employed for the automated analysis of these systems' privacy policies. However, these techniques typically requ

Fulin Xu

In this paper, by running MMP and considering the anti-canonical fibration, we prove the Morrison-Kawamata cone conjecture for klt Calabi-Yau pairs $(X,\Delta)$ such that $\dim X$ is at most $4$, and the Iitaka dimension $\kappa(X,-K_X)$ is at least $\dim X - 2$.

Elena Campedel, Ginevra Giordani, Antonio Ioppolo

Let $F$ be a fixed field of characteristic zero containing an element $i$ such that $i^2 = -1$. In this paper we consider finite dimensional superalgebras over $F$ endowed with a pseudoautomorphism $p$ and we investigate the asymptotic behaviour of the corresponding sequence of $p$-codimensions $c_n^p(A),$ $n=1,2, \ldots$. First we give a positive answer to

Zhen Zhao, Emil Östberg, Ferdi Aryasetiawan, Claudio Verdozzi

A quantum description is given of nanoskyrmions in 2D textures with localised spins and itinerant electrons, isolated or coupled to leads, in or out-of-equilibrium. The spin-electron exchange is treated at the mean-field level, while Tensor Networks and exact diagonalization or nonequilibrium Green's functions are used for localised spins and itinerant elect

Dhanushka Balasingham, Sadeesha Samarathunga, Gayantha Godakanda Arachchige, Anuththara Bandara

The advancements in precision agriculture are vital to support the increasing demand for global food supply. Precision spot spraying is a major step towards reducing chemical usage for pest and weed control in agriculture. A novel spot spraying algorithm that autonomously detects weeds and performs trajectory planning for the sprayer nozzle has been proposed

Qianqian Qi, Ayoub Bagheri, David J. Hessen, Peter G. M. van der Heijden

Popular word embedding methods such as GloVe and Word2Vec are related to the factorization of the pointwise mutual information (PMI) matrix. In this paper, we establish a formal connection between correspondence analysis (CA) and PMI-based word embedding methods. CA is a dimensionality reduction method that uses singular value decomposition (SVD), and we sho

Ben Cox, Barbara Kaltenbacher, Vanja Nikolić, Felix Lucka

We investigate models for nonlinear ultrasound propagation in soft biological tissue based on the one that serves as the core for the software package k-Wave. The systems are solved for the acoustic particle velocity, mass density, and acoustic pressure and involve a fractional absorption operator. We first consider a system that incorporates additional visc

Nikolaos Panagiotis Souris

We explore general intrinsic and extrinsic conditions that allow the transitivity of the relation of being a Lie ideal, in the sense that if a Lie algebra $\mathfrak{h}$ is a subideal of a Lie algebra $\mathfrak{g}$ (i.e. there exist Lie subalgebras $\mathfrak{l}_0,\mathfrak{l}_1,\dots,\mathfrak{l}_n$ of $\mathfrak{g}$ with $\mathfrak{h}=\mathfrak{l}_0\unlhd

Zhipeng Yang, Ruoyu Wang, Yang Tan, Liping Xie

Online action detection (OAD) aims to identify ongoing actions from streaming video in real-time, without access to future frames. Since these actions manifest at varying scales of granularity, ranging from coarse to fine, projecting an entire set of action frames to a single latent encoding may result in a lack of local information, necessitating the acquis

Philipp Heering

Let $\Gamma_4$ be the graph whose vertices are the chambers of the finite projective $4$-space PG(4,q), with two vertices being adjacent if the corresponding chambers are in general position. For $q\geq 749 $ we show that $\alpha:=(q^2+q+1)(q^3+2q^2+q+1)(q+1)^2$ is the independence number of $\Gamma_4$ and the geometric structure of independent sets with $\a

Kai Ma, Lin-Yun He

Weakly interacting fermions with the Standard Model particles are promising candidates for the dark matter. In this paper, we study signatures of the gluonic interactions of a dark fermion and a neutrino at hadron colliders and direct detection experiments. The lowest order interactions are described by contact operators in dimension 7. At hadron colliders,

Alice Pagano, Matthias M Müller, Tommaso Calarco, Simone Montangero

Quantum Optimal Control (QOC) supports the advance of quantum technologies by tackling its problems at the pulse level: Numerical approaches iteratively work towards a given target by parametrising the applied time-dependent fields with a finite set of variables. The effectiveness of the resulting optimisation depends on the complexity of the problem and the

Louis-Pierre Arguin, Nathan Creighton

We prove a result on the large deviations of the central values of even primitive Dirichlet $L$-functions with a given modulus. For $V\sim \alpha\log\log q$ with $0<\alpha<1$, we show that \begin{equation}\nonumber\frac{1}{\varphi(q)} \# \left\{\chi \text{ even, primitive mod }q: \log \left|L\left(\chi,\frac{1}{2}\right)\right| >V\right\}\ll \frac{e^{-\frac{

Michele Pizzochero, Nikita V. Tepliakov, Johannes Lischner, Arash A. Mostofi

We examine the electronic structure of recently fabricated in-plane heterojunctions of zigzag graphene nanoribbons embedded in hexagonal boron nitride. We focus on hitherto unexplored interface configurations in which both edges of the nanoribbon are bonded to the same chemical species, either boron or nitrogen atoms. Using ab initio and mean-field Hubbard m

Claude Godrèche, Marco Picco

This paper investigates various geometrical properties of interfaces of the two-dimensional voter model. Despite its simplicity, the model exhibits dual characteristics, resembling both a critical system with long-range correlations, while also showing a tendency towards order similar to the Ising-Glauber model at zero temperature. This duality is reflected

Tianyue Wu, Gongye Zaitian, Qianhao Wang, Fei Gao

This paper explores the distance-based relative state estimation problem in large-scale systems, which is hard to solve effectively due to its high-dimensionality and non-convexity. In this paper, we alleviate this inherent hardness to simultaneously achieve scalability and robustness of inference on this problem. Our idea is launched from a universal geomet

Bao Nguyen, Lorenzo Sani, Xinchi Qiu, Pietro Liò

Graph hypernetworks (GHNs), constructed by combining graph neural networks (GNNs) with hypernetworks (HNs), leverage relational data across various domains such as neural architecture search, molecular property prediction and federated learning. Despite GNNs and HNs being individually successful, we show that GHNs present problems compromising their performa

Haolong Ma, Hui Li, Chunyang Cheng, Gaoang Wang

As one of the tasks in Image Fusion, Infrared and Visible Image Fusion aims to integrate complementary information captured by sensors of different modalities into a single image. The Selective State Space Model (SSSM), known for its ability to capture long-range dependencies, has demonstrated its potential in the field of computer vision. However, in image

Yoav Kolumbus, Joe Halpern, Éva Tardos

In repeated games, such as auctions, players rely on autonomous learning agents to choose their actions. We study settings in which players have their agents make monetary transfers to other agents during play at their own expense, in order to influence learning dynamics in their favor. Our goal is to understand when players have incentives to use such payme

Kenji Fukumizu, Taiji Suzuki, Noboru Isobe, Kazusato Oko

Flow matching (FM) has gained significant attention as a simulation-free generative model. Unlike diffusion models, which are based on stochastic differential equations, FM employs a simpler approach by solving an ordinary differential equation with an initial condition from a normal distribution, thus streamlining the sample generation process. This paper d

Yuxi Liu, Lianghao Xia, Chao Huang

Sequential recommendation effectively addresses information overload by modeling users' temporal and sequential interaction patterns. To overcome the limitations of supervision signals, recent approaches have adopted self-supervised learning techniques in recommender systems. However, there are still two critical challenges that remain unsolved. Firstly, exi

Nikos G. Evgenidis, Nikos A. Mitsiou, Sotiris A. Tegos, Panagiotis D. Diamantoulakis

In response to the increasing number of devices expected in next-generation networks, a shift to over-the-air (OTA) computing has been proposed. By leveraging the superposition of multiple access channels, OTA computing enables efficient resource management by supporting simultaneous uncoded transmission in the time and frequency domains. To advance the inte

Pallavi Mitra, Gesina Schwalbe, Nadja Klein

Convolutional Neural Networks (CNNs) have achieved state-of-the-art performance in many computer vision tasks. However, high computational and storage demands hinder their deployment into resource-constrained environments, such as embedded devices. Model pruning helps to meet these restrictions by reducing the model size, while maintaining superior performan

Lorenzo Barca, Gunnar Bali, Sara Collins

Nucleon weak matrix elements can be extracted from nucleon correlation functions with lattice QCD simulations. The signal-to-noise ratio prohibits the analysis at large source-sink separations and as a consequence, excited state contamination affects the extraction of the nucleon matrix elements. Chiral perturbation theory (ChPT) suggests that the dominant c

Alexander R. Klotz

We develop a minimal system to study the stochastic formation of Borromean links within topologically entangled networks without requiring the use of knot invariants. Borromean linkages may form in entangled solutions of open polymer chains or in Olympic gel systems such as kinetoplast DNA, but it is challenging to investigate this due to the difficulty of c

Mikhail G. Katz

We give a synthetic construction of a complete system of mutually unbiased bases in $\mathbb{C}^3$.

Sajida Mhammedi, Hakim El Massari, Noreddine Gherabi, Amnai Mohamed

Recommender systems are a kind of data filtering that guides the user to interesting and valuable resources within an extensive dataset. by providing suggestions of products that are expected to match their preferences. However, due to data overloading, recommender systems struggle to handle large volumes of data reliably and accurately before offering sugge

Wayne Cheng-Wei Huang, Sai Mu, Gevin von Witte, Yanshuo Sophie Li

Tailored optical excitations can steer a system along non-equilibrium pathways to metastable states with specific structural or electronic properties. The light-induced hidden state of 1T-TaS$_{2}$, with its strongly enhanced conductivity and exceptionally long lifetime, represents a unique model system for studying the ultrafast switching of correlated elec

Jihong Huang

We point out that the observed pattern of lepton flavor mixing can be well described by a proper nearest-neighbor expansion of a constant $3\times 3$ unitary matrix in powers of a small parameter characterizing the fine effect of $\mu$-$\tau$ permutation symmetry breaking. We take an example of this kind for illustration, and provide complete discussions on

Tao Chen, Shangzhi Song, Yang Shen, Kexin Zhang

State-of-the-art techniques like dual-frequency Time-Domain Thermoreflectance (TDTR) and Frequency-Domain Thermoreflectance (FDTR) offer superb capability for simultaneous measurements of thermal conductivity and heat capacity with a spatial resolution on the order of 10 {\mu}m. However, their applicability is limited to highly conductive materials with an i

Vamsi Addanki, Chen Avin, Stefan Schmid

The increasing gap between the growth of datacenter traffic volume and the capacity of electrical switches led to the emergence of reconfigurable datacenter network designs based on optical circuit switching. A multitude of research works, ranging from demand-oblivious (e.g., RotorNet, Sirius) to demand-aware (e.g., Helios, ProjecToR) reconfigurable networks

Pedram Ghamisi, Weikang Yu, Andrea Marinoni, Caroline M. Gevaert

The convergence of artificial intelligence (AI) and Earth observation (EO) technologies has brought geoscience and remote sensing into an era of unparalleled capabilities. AI's transformative impact on data analysis, particularly derived from EO platforms, holds great promise in addressing global challenges such as environmental monitoring, disaster response

Eunho Lee, Youngbae Hwang

Despite the strong performance of Transformers, their quadratic computation complexity presents challenges in applying them to vision tasks. Automatic pruning is one of effective methods for reducing computation complexity without heuristic approaches. However, directly applying it to multi-head attention is not straightforward due to channel misalignment. I

Jan Benáček, Andrey Timokhin, Patricio A. Muñoz, Axel Jessner

Pair cascades in polar cap regions of neutron stars are considered to be an essential process in various models of coherent radio emissions of pulsars. The cascades produce pair plasma bunch discharges in quasi-periodic spark events. The cascade properties, and therefore also the coherent radiation, depend strongly on the magnetospheric plasma properties and

Luca Gallerani, Marcello Miranda, Andrea Giusti, Andrea Mentrelli

We explore alternative formulations of the analogy between viable Horndeski gravity and Eckart's first-order thermodynamics. We single out a class of identifications for the effective stress-energy tensor of the scalar field fluid that, upon performing the imperfect fluid decomposition, yields constitutive relations that can be mapped onto Eckart's theory. W

Tobias Diez, Akito Futaki, Tudor Ratiu

We pioneer the development of a rigorous infinite-dimensional framework for the Kempf-Ness theorem, addressing the significant challenge posed by the absence of a complexification for the symmetry group in infinite dimensions, e.g, the diffeomorphism group. We propose a novel approach, based on Cartan bundles, to generalize Kempf-Ness theory to infinite dime

Henry Kenlay, Frédéric A. Dreyer, Daniel Cutting, Daniel Nissley

Accurate prediction of antibody structure is a central task in the design and development of monoclonal antibodies, notably to understand both their developability and their binding properties. In this article, we introduce ABodyBuilder3, an improved and scalable antibody structure prediction model based on ImmuneBuilder. We achieve a new state-of-the-art ac

Songze Li, Yanbo Dai

In a federated learning (FL) system, decentralized data owners (clients) could upload their locally trained models to a central server, to jointly train a global model. Malicious clients may plant backdoors into the global model through uploading poisoned local models, causing misclassification to a target class when encountering attacker-defined triggers. E

Julia Chuzhoy, Sanjeev Khanna

Maximum bipartite matching (MBM) is a fundamental problem in combinatorial optimization with a long and rich history. A classic result of Hopcroft and Karp (1973) provides an $O(m \sqrt{n})$-time algorithm for the problem, where $n$ and $m$ are the number of vertices and edges in the input graph, respectively. For dense graphs, an approach based on fast matr

Shangding Gu, Laixi Shi, Yuhao Ding, Alois Knoll

Safe reinforcement learning (RL) is crucial for deploying RL agents in real-world applications, as it aims to maximize long-term rewards while satisfying safety constraints. However, safe RL often suffers from sample inefficiency, requiring extensive interactions with the environment to learn a safe policy. We propose Efficient Safe Policy Optimization (ESPO

Anne Beyer, Kranti Chalamalasetti, Sherzod Hakimov, Brielen Madureira

It has been established in recent work that Large Language Models (LLMs) can be prompted to "self-play" conversational games that probe certain capabilities (general instruction following, strategic goal orientation, language understanding abilities), where the resulting interactive game play can be automatically scored. In this paper, we take one of the pro

Yibin Yang, Shaobing Xu, Xintao Yan, Junkai Jiang

This paper presents an efficient algorithm, naming Centralized Searching and Decentralized Optimization (CSDO), to find feasible solution for large-scale Multi-Vehicle Trajectory Planning (MVTP) problem. Due to the intractable growth of non-convex constraints with the number of agents, exploring various homotopy classes that imply different convex domains, i

Meskerem Abebaw Mebratie, Rüdiger Nather, Guido Falk von Rudorff, Werner M. Seiler

Conservation laws are of great theoretical and practical interest. We describe a novel approach to machine learning conservation laws of finite-dimensional dynamical systems using trajectory data. It is the first such approach based on kernel methods instead of neural networks which leads to lower computational costs and requires a lower amount of training d

Daniele Tramontano, Mathias Drton, Jalal Etesami

Linear non-Gaussian causal models postulate that each random variable is a linear function of parent variables and non-Gaussian exogenous error terms. We study identification of the linear coefficients when such models contain latent variables. Our focus is on the commonly studied acyclic setting, where each model corresponds to a directed acyclic graph (DAG

L. C. T. Brito, J. C. C. Felipe, A. C. Lehum, J. R. Nascimento

Quantum photon effects in vacuum provide an interesting setting to test quantum electrodynamics, serving as a source for predictions about physics beyond the Standard Model. In this paper, we investigate these effects by calculating the one-loop Euler-Heisenberg-like effective action within a Lorentz-violating scalar quantum electrodynamics framework. In bot

Marion Boucrot

In this article we study the homotopy theory of pre-Calabi-Yau morphisms, viewing them as Maurer-Cartan elements of an $L_{\infty}$-algebra. We give two different notions of homotopy: a notion of weak homotopy for morphisms between $d$-pre-Calabi-Yau categories whose underlying graded quivers on the domain (resp. codomain) are the same, and a notion of homot

Sijin Chen, Xin Chen, Anqi Pang, Xianfang Zeng

The polygon mesh representation of 3D data exhibits great flexibility, fast rendering speed, and storage efficiency, which is widely preferred in various applications. However, given its unstructured graph representation, the direct generation of high-fidelity 3D meshes is challenging. Fortunately, with a pre-defined ordering strategy, 3D meshes can be repre

Xuxin Cheng, Wanshi Xu, Zhihong Zhu, Hongxiang Li

Spoken language understanding (SLU) is a core task in task-oriented dialogue systems, which aims at understanding the user's current goal through constructing semantic frames. SLU usually consists of two subtasks, including intent detection and slot filling. Although there are some SLU frameworks joint modeling the two subtasks and achieving high performance

Shurong Yang, Huadong Li, Juhao Wu, Minhao Jing

Despite raw driving videos contain richer information on facial expressions than intermediate representations such as landmarks in the field of portrait animation, they are seldom the subject of research. This is due to two challenges inherent in portrait animation driven with raw videos: 1) significant identity leakage; 2) Irrelevant background and facial d

Zihuiwen Ye, Fraser Greenlee-Scott, Max Bartolo, Phil Blunsom

Reward models (RMs) play a critical role in aligning language models through the process of reinforcement learning from human feedback. RMs are trained to predict a score reflecting human preference, which requires significant time and cost for human annotation. Additionally, RMs tend to quickly overfit on superficial features in the training set, hindering

Kuikui Liu, Sidhanth Mohanty, Prasad Raghavendra, Amit Rajaraman

Many natural Markov chains fail to mix to their stationary distribution in polynomially many steps. Often, this slow mixing is inevitable since it is computationally intractable to sample from their stationary measure. Nevertheless, Markov chains can be shown to always converge quickly to measures that are locally stationary, i.e., measures that don't change

Rui Ren, Jingbang Yang, Linxiao Yang, Xinyue Gu

The newly deployed service -- one kind of change service, could lead to a new type of minority fault. Existing state-of-the-art methods for fault localization rarely consider the imbalanced fault classification in change service. This paper proposes a novel method that utilizes decision rule sets to deal with highly imbalanced data by optimizing the F1 score

Narmina Baghirova, Antoine Castillon

A proportionally dense subgraph (PDS) of a graph is an induced subgraph of size at least two such that every vertex in the subgraph has proportionally as many neighbors inside as outside of the subgraph. Then, maxPDS is the problem of determining a PDS of maximum size in a given graph. If we further require that a PDS induces a connected subgraph, we refer t

A. Bavaresco, A. Testoni, R. Fernández

Image-based advertisements are complex multimodal stimuli that often contain unusual visual elements and figurative language. Previous research on automatic ad understanding has reported impressive zero-shot accuracy of contrastive vision-and-language models (VLMs) on an ad-explanation retrieval task. Here, we examine the original task setup and show that co

Ángel Arroyo, Rafael López-Soriano, Alejandro Ortega

In this paper we study a class of Hardy--Sobolev type systems defined in $\mathbb{R}^N$ and coupled by a singular critical Hardy--Sobolev term. The main novelty of this work is that the orders of the singularities are independent and contained in a wide range. By means of variational techniques, we will prove the existence of positive bound and ground states

Daniel J. Bosworth, Matthew T. Eiles, Peter Schmelcher

H$_3^{2+}$ is a one-electron system with three positive nuclei and is known to be unstable in its electronic ground-state. We examine an analogous one-electron system composed of a $^{87}$Rb Rydberg atom interacting with a pair of cations and predict the existence of metastable vibrationally-bound states of $^{87}$Rb$_3^{2+}$. These molecules are long-range

Andreas Windischhofer, Nikola Opačak, Benedikt Schwarz

Interband cascade lasers (ICLs) stand out due to their low threshold current and minimal power consumption, rendering them viable sources for compact and mobile devices in the mid-infrared. Since their first demonstration, they experienced major performance improvements. Many of them originate, on one hand, from technological enhancements and, on the other h

Jacques Carette, Chris Heunen, Robin Kaarsgaard, Amr Sabry

Reversible computing is motivated by both pragmatic and foundational considerations arising from a variety of disciplines. We take a particular path through the development of reversible computation, emphasizing compositional reversible computation. We start from a historical perspective, by reviewing those approaches that developed reversible extensions of

Francesco Maria Saettone

We prove an equidistribution statement for the reduction of Galois orbits of CM points on the special fiber of a Shimura curve over a totally real field attached to some ramified primes. To do so we study the reduction of CM points in the special fiber and we use Ratner's theorem to obtain the desired equidistribution.