October 2023 arXiv papers — page 28

Majid Kheirkhah, Igor F. Herbut

We consider the spin-3/2 Luttinger fermions with contact attraction near the SU(4)-symmetric limit of vanishing Luttinger spin-orbit-coupling parameter responsible for band inversion, and at finite chemical potential. In the case of exact SU(4) symmetry the previously considered $s$-wave and five $d$-wave superconducting order parameters together form a six-

Flavio Ascari, Roberto Bruni, Roberta Gori, Francesco Logozzo

Sound over-approximation methods have been proved effective for guaranteeing the absence of errors, but inevitably they produce false alarms that can hamper the programmers. Conversely, under-approximation methods are aimed at bug finding and are free from false alarms. We introduce Sufficient Incorrectness Logic~(SIL), a new under-approximating, triple-base

Mamta, Zishan Ahmad, Asif Ekbal

With the growing popularity of code-mixed data, there is an increasing need for better handling of this type of data, which poses a number of challenges, such as dealing with spelling variations, multiple languages, different scripts, and a lack of resources. Current language models face difficulty in effectively handling code-mixed data as they primarily fo

Nhan Tri Tran, Hoang Thanh Nguyen, Lan Nguyen Tran

Quantum chemical methods dealing with challenging systems while retaining low computational costs have attracted attention. In particular, many efforts have been devoted to developing new methods based on the second-order perturbation that may be the simplest correlated method beyond Hartree-Fock. We have recently developed a self-consistent perturbation the

Shalosh B. Ekhad, Doron Zeilberger

We revisit, implement, and experiment with a beautiful algorithm, due to Calabi and Wilf for the random generation of subspaces over a finie field.

Yijian Qin, Xin Wang, Ziwei Zhang, Wenwu Zhu

Text-attributed graphs (TAGs) are prevalent on the web and research over TAGs such as citation networks, e-commerce networks and social networks has attracted considerable attention in the web community. Recently, large language models (LLMs) have demonstrated exceptional capabilities across a wide range of tasks. However, the existing works focus on harness

Amaury Hayat, Arwa Alanqary, Rahul Bhadani, Christopher Denaro

The dissipation of stop-and-go waves attracted recent attention as a traffic management problem, which can be efficiently addressed by automated driving. As part of the 100 automated vehicles experiment named MegaVanderTest, feedback controls were used to induce strong dissipation via velocity smoothing. More precisely, a single vehicle driving differently i

Irene Perez-Salesa, Rodrigo Aldana-Lopez, Carlos Sagues

Distributed sensor networks have gained interest thanks to the developments in processing power and communications. Event-triggering mechanisms can be useful in reducing communication between the nodes of the network, while still ensuring an adequate behaviour of the system. However, very little attention has been given to continuous-time systems in this con

Agniv Bandyopadhyay, Sandeep Juneja

We consider a queuing network that opens at a specified time, where customers are non-atomic and belong to different classes. Each class has its own route, and as is typical in the literature, the costs are a linear function of waiting and service completion time. We restrict ourselves to a two class, two queue network: this simplification is well motivated

Tianrun Chen, Chaotao Ding, Lanyun Zhu, Ying Zang

The emerging trend of AR/VR places great demands on 3D content. However, most existing software requires expertise and is difficult for novice users to use. In this paper, we aim to create sketch-based modeling tools for user-friendly 3D modeling. We introduce Reality3DSketch with a novel application of an immersive 3D modeling experience, in which a user ca

Yuki Sato, Soma Nagahama, Ilya Belopolski, Ryutaro Yoshimi

Engineering heterostructures with various types of quantum materials can provide an intriguing playground for studying exotic physics induced by the proximity effect. Here, we report the successful synthesis of iron-based superconductor FeSe$_{x}$Te$_{1-x}$ (FST) thin films across the entire composition range of $0 \leq x \leq 1$ and its heterostructure with

Chandra Chekuri, Aleksander Bjørn Christiansen, Jacob Holm, Ivor van der Hoog

We give improved algorithms for maintaining edge-orientations of a fully-dynamic graph, such that the out-degree of each vertex is bounded. On one hand, we show how to orient the edges such that the out-degree of each vertex is proportional to the arboricity $\alpha$ of the graph, in, either, an amortised update time of $O(\log^2 n \log \alpha)$, or a worst-

Amar Bharti, Gopal Dixit

Generating and tailoring photocurrent in topological materials has immense importance in fundamental studies and the technological front. Present work introduces a universal method to generate ultrafast photocurrent in {\it both} inversion-symmetric and inversion-broken Weyl semimetals with degenerate Weyl nodes at the Fermi level. Our approach harnesses the

Roger Creus Castanyer, Joshua Romoff, Glen Berseth

Exploration bonuses in reinforcement learning guide long-horizon exploration by defining custom intrinsic objectives. Several exploration objectives like count-based bonuses, pseudo-counts, and state-entropy maximization are non-stationary and hence are difficult to optimize for the agent. While this issue is generally known, it is usually omitted and soluti

Ferenc Fodor, Dániel I. Papvári

In this paper we prove a quantitative central limit theorem for the area of uniform random disc-polygons in smooth convex discs whose boundary is $C^2_+$. We use Stein's method and the asymptotic lower bound for the variance of the area proved by Fodor, Gr\"unfelder and V\'igh (2022).

Danni Yang, Jiayi Ji, Xiaoshuai Sun, Haowei Wang

Despite considerable progress, the advancement of Panoptic Narrative Grounding (PNG) remains hindered by costly annotations. In this paper, we introduce a novel Semi-Supervised Panoptic Narrative Grounding (SS-PNG) learning scheme, capitalizing on a smaller set of labeled image-text pairs and a larger set of unlabeled pairs to achieve competitive performance

Sara Hahner, Souhaib Attaiki, Jochen Garcke, Maks Ovsjanikov

We introduce a novel learning-based method for encoding and manipulating 3D surface meshes. Our method is specifically designed to create an interpretable embedding space for deformable shape collections. Unlike previous 3D mesh autoencoders that require meshes to be in a 1-to-1 correspondence, our approach is trained on diverse meshes in an unsupervised man

Qing Li, Yanyan Zhang

This study examines nonnegative solutions to the problem \begin{equation*}\left\{\arraycolsep=1.5pt \begin {array}{lll} \Delta u=\displaystyle\frac{\lambda|x|^{\alpha}}{u^p} \ \ &\hbox{ in} \,\ \R ^2\setminus \{0\},\\[2mm] u(0)=0 \ \text{and}\ u> 0 \ \ &\hbox{ in} \,\ \R ^2\setminus \{0\},\\ \end{array}\right. \label{eqn} \end{equation*} where $\lam >0,$ $\a

Yves Sibony, Cyril Georgy, Sylvia Ekström, Georges Meynet

We study the differences between models computed with Ledoux and Schwarzschild criteria on the internal structure, evolutionary track in the Hertzsprung-Russell diagram (HRD), lifetimes, evolution of the surface abundances and velocities, and masses of the He and CO cores. We investigate the consequences on the nature of the supernova (SN) progenitors and th

Aldo Cumitini, Stefano Tinelli, Balázs Matuz, Francisco Lázaro

We discuss single-shot decoding of quantum Calderbank-Shor-Steane codes with faulty syndrome measurements. We state the problem as a joint source-channel coding problem. By adding redundant rows to the code's parity-check matrix we obtain an additional syndrome error correcting code which addresses faulty syndrome measurements. Thereby, the redundant rows ar

Gabriel J. S. Bliard

In this thesis, we consider two approaches to the study of correlation functions in one-dimensional defect Conformal Field Theories (dCFT$_1$), in particular those defined by 1/2-BPS Wilson line defects in the three- and four-dimensional superconformal theories relevant in the AdS/CFT correspondence. In the first approach, we use the analytic conformal boots

Aslan S. Dizaji

There are several theories in economics regarding the roots or causes of prosperity in a society. One of these theories or hypotheses -- named geography hypothesis -- mentions that the reason why some countries are prosperous and some others are poor is the geographical location of the countries in the world as makes their climate and environment favorable o

Emilie Mai Elkiær, Sanaz Pooya

We define and study the notion of property $(\rm T)$ for Banach algebras, generalizing the one from $C^*$-algebras. For a second countable locally compact group $G$ and a given family of Banach spaces $\mathcal E$, we prove that our Banach algebraic property $(\rm{T}_{\mathcal E})$ of the symmetrized pseudofunction algebras $F^*_{\mathcal E}(G)$ characterize

Cihan Okay, Igor Sikora

We introduce an equivariant version of contextuality with respect to a symmetry group, which comes with natural applications to quantum theory. In the equivariant setting, we construct cohomology classes that can detect contextuality. This framework is motivated by the earlier topological approach to contextuality producing cohomology classes that serve as c

Rémy Pawlak, Jung-Ching Liu, Chao Li, Richard Hess

Topological superconductivity emerges in chains or arrays of magnetic atoms coupled to a superconductor. However, the external controllability of such systems with gate voltages is detrimental for their future implementation in a topological quantum computer. Here we showcase the supramolecular assembly of radical molecules on Pb(111), whose discharge is con

Rajendra Singh Bhati, Arvind

The emergence of the objective classical world from the quantum behavior of microscopic constituents is not fully understood. Models based on decoherence and the principle of quantum Darwinism, which attempt to provide such an explanation, require system-bath interactions in a preferred basis. Thus, the generic emergence of objectivity in the position basis,

Clodoaldo I. L. de Araujo, Pauli Virtanen, Maria Spies, Carmen González-Orellana

Heat engines are key devices that convert thermal energy into usable energy. Strong thermoelectricity, at the basis of electrical heat engines, is present in superconducting spin tunnel barriers at cryogenic temperatures where conventional semiconducting or metallic technologies cease to work. Here we realize a superconducting spintronic heat engine consisti

Yiran Guan, Zhuoguang Chen, Wenzheng Zeng, Zhiguo Cao

In this letter, we propose a new method, Multi-Clue Gaze (MCGaze), to facilitate video gaze estimation via capturing spatial-temporal interaction context among head, face, and eye in an end-to-end learning way, which has not been well concerned yet. The main advantage of MCGaze is that the tasks of clue localization of head, face, and eye can be solved joint

David Q. Sun, Artem Abzaliev, Hadas Kotek, Zidi Xiu

Controversy is a reflection of our zeitgeist, and an important aspect to any discourse. The rise of large language models (LLMs) as conversational systems has increased public reliance on these systems for answers to their various questions. Consequently, it is crucial to systematically examine how these models respond to questions that pertaining to ongoing

Jacob R. Goodman, Leonardo J. Colombo

In this work, we study the reduction by a Lie group of symmetries of variational collision avoidance probelms of multiple agents evolving on a Riemannian manifold and derive necessary conditions for the reduced extremals. The problem consists of finding non-intersecting trajectories of a given number of agents, among a set of admissible curves, to reach a sp

Michal K. Grzeszczyk, Szymon Płotka, Beata Rebizant, Katarzyna Kosińska-Kaczyńska

Medical data analysis often combines both imaging and tabular data processing using machine learning algorithms. While previous studies have investigated the impact of attention mechanisms on deep learning models, few have explored integrating attention modules and tabular data. In this paper, we introduce TabAttention, a novel module that enhances the perfo

Karl Bringmann, Nick Fischer, Ivor van der Hoog, Evangelos Kipouridis

The Dynamic Time Warping (DTW) distance is a popular similarity measure for polygonal curves (i.e., sequences of points). It finds many theoretical and practical applications, especially for temporal data, and is known to be a robust, outlier-insensitive alternative to the \frechet distance. For static curves of at most $n$ points, the DTW distance can be co

Xue Yan, Yan Song, Xinyu Cui, Filippos Christianos

Large language models (LLMs) demonstrate their promise in tackling complicated practical challenges by combining action-based policies with chain of thought (CoT) reasoning. Having high-quality prompts on hand, however, is vital to the framework's effectiveness. Currently, these prompts are handcrafted utilising extensive human labor, resulting in CoT polici

Dmytro Kolisnyk, Friedemann Queisser, Gernot Schaller, Ralf Schützhold

We investigate superradiant enhancements in the refrigeration performance of a set of $N$ three-level systems that are collectively coupled to a hot and a cold thermal reservoir and are additionally subject to collective periodic (circular) driving. Assuming the system-reservoir coupling to be weak, we explore the regime of stronger periodic driving strength

Sergio Girón Pacheco, Robert Neagu

We introduce a categorical approach to classifying actions of C$^*$-tensor categories $\mathcal{C}$ on C$^*$-algebras up to cocycle conjugacy. We show that, in this category, inductive limits exist and there is a natural notion of approximate unitary equivalence. Then, we generalise classical Elliott intertwining results to the $\mathcal{C}$-equivariant case

Rubén A. Hidalgo

We prove the existence of finite groups of orientation-preserving homeomorphisms of some closed orientable surface $S$ that act freely and which extends as a group of homeomorphisms of some compact orientable $3$-manifold with boundary $S$, but which cannot extend to a handlebody.

Zhenyu Zhu, Francesco Locatello, Volkan Cevher

This paper provides statistical sample complexity bounds for score-matching and its applications in causal discovery. We demonstrate that accurate estimation of the score function is achievable by training a standard deep ReLU neural network using stochastic gradient descent. We establish bounds on the error rate of recovering causal relationships using the

Yuchen Shen, Xiaojun Wan

Opinion summarization sets itself apart from other types of summarization tasks due to its distinctive focus on aspects and sentiments. Although certain automated evaluation methods like ROUGE have gained popularity, we have found them to be unreliable measures for assessing the quality of opinion summaries. In this paper, we present OpinSummEval, a dataset

Baptiste Lefaucher, Jean-Baptiste Jager, Vincent Calvo, Félix Cache

Generating single photons on demand in silicon is a challenge to the scalability of silicon-on-insulator integrated quantum photonic chips. While several defects acting as artificial atoms have recently demonstrated an ability to generate antibunched single photons, practical applications require tailoring of their emission through quantum cavity effects. In

Sajjad Zahir

We consider a two-time (characterized by distinct speeds of causality) and three-space-dimensional Minkowski space and derive relativistic coordinate and velocity transformation formulas and expressions for a new effective speed limit. Extending the ideas of Einstein's Theory of Special Relativity, concepts of five-velocity and five-momenta are introduced le

Yeongseo Jung, Eunseo Jung, Lei Chen

In Conversational Recommendation System (CRS), an agent is asked to recommend a set of items to users within natural language conversations. To address the need for both conversational capability and personalized recommendations, prior works have utilized separate recommendation and dialogue modules. However, such approach inevitably results in a discrepancy

Saverio De Vito, Gerardo D Elia, Sergio Ferlito, Girolamo Di Francia

Scalable and effective calibration is a fundamental requirement for Low Cost Air Quality Monitoring Systems and will enable accurate and pervasive monitoring in cities. Suffering from environmental interferences and fabrication variance, these devices need to encompass sensors specific and complex calibration processes for reaching a sufficient accuracy to b

Vladimír Kubelka, Emil Fritz, Martin Magnusson

There is a current increase in the development of "4D" Doppler-capable radar and lidar range sensors that produce 3D point clouds where all points also have information about the radial velocity relative to the sensor. 4D radars in particular are interesting for object perception and navigation in low-visibility conditions (dust, smoke) where lidars and came

Benjamin Salmon, Alexander Krull

Traditional supervised denoisers are trained using pairs of noisy input and clean target images. They learn to predict a central tendency of the posterior distribution over possible clean images. When, e.g., trained with the popular quadratic loss function, the network's output will correspond to the minimum mean square error (MMSE) estimate. Unsupervised de

Achyut Tiwari, Bruno Gompf, Martin Dressel

Determining the optical and electronic properties of strongly anisotropic materials with symmetries below orthorhombic remains challenging; generalized ellipsometry is a powerful technique in this regard. Here, we employ Mueller matrix spectroscopic and temperature-dependent ellipsometry to determine the frequency dependence of six components of the dielectr

Deepthi Ayyagari, Soumen Datta, Saurabh Das, Abhirup Datta

Here, we explore the different characteristics of a possible coupling between tropospheric and ionospheric activities during the impact of tropical cyclones (TC) like Amphan and Nisarga in the Indian subcontinent. We have analyzed the effect of TCs Amphan and Nisarga on the low latitude ionosphere using the measurements from several IGS stations around India

Gabriele Bressanini, Benoit Seron, Leonardo Novo, Nicolas J. Cerf

Gaussian boson sampling (GBS), a computational problem conjectured to be hard to simulate on a classical machine, has been at the forefront of recent years' experimental and theoretical efforts to demonstrate quantum advantage. The classical intractability of the sampling task makes validating these experiments a challenging and essential undertaking. In thi

Ayoub Raji, Danilo Caporale, Francesco Gatti, Andrea Giove

The Indy Autonomous Challenge (IAC) brought together for the first time in history nine autonomous racing teams competing at unprecedented speed and in head-to-head scenario, using independently developed software on open-wheel racecars. This paper presents the complete software architecture used by team TII EuroRacing (TII-ER), covering all the modules need

Susanne Kunzmann, Thomas Hammerschmidt, Gabi Schierning, Anna Grünebohm

Although Niobium is a well characterized material it still shows some anomalies that are not yet understood. Therefore we revisit its metastable phases using density functional theory. First, we systematically compare energies and ground state volumes of chosen crystal structures and discuss possible transition paths to the bcc ground state structure and the

Hampus Malmberg, Fredrik Feyling, Jose M. de la Rosa

In this paper, the design flexibility of the control-bounded analog-to-digital converter principle is demonstrated. A band-pass analog-to-digital converter is considered as an application and case study. We show how a low-pass control-bounded analog-to-digital converter can be translated into a band-pass version where the guaranteed stability, converter band

Hauke Fischer, Christian Käding, Hartmut Lemmel, Stephan Sponar

We use previously obtained experimental results by neutron interferometry to effectively constrain the parameter space of several prominent dark energy models. This investigation encompasses the environment-dependent dilaton field, a compelling contender for dark energy that emerges naturally within the strong coupling limit of string theory, alongside symme

Ulysse Gazin, Gilles Blanchard, Etienne Roquain

Conformal inference is a fundamental and versatile tool that provides distribution-free guarantees for many machine learning tasks. We consider the transductive setting, where decisions are made on a test sample of $m$ new points, giving rise to $m$ conformal $p$-values. While classical results only concern their marginal distribution, we show that their joi

Nathan Keller, Noam Lifshitz, Ohad Sheinfeld

We study covering numbers of subsets of the symmetric group $S_n$ that exhibit closure under conjugation, known as \emph{normal} sets. We show that for any $\epsilon>0$, there exists $n_0$ such that if $n>n_0$ and $A$ is a normal subset of the symmetric group $S_n$ of density $\ge e^{-n^{2/5 - \epsilon}}$, then $A^2 \supseteq A_n$. This improves upon a semin

Hannah Götsch, Reinhard Bürger

We study the response of a quantitative trait to exponential directional selection in a finite haploid population at the genetic and the phenotypic level. We assume an infinite sites model, in which the number of new mutations per generation in the population follows a Poisson distribution (with mean $\Theta$) and each mutation occurs at a new, previously mo

Ken Pounds, Kim Page

The luminous narrow line Seyfert galaxy PG1211+143 was the first non-BAL AGN to reveal a powerful ionized wind, based on early observations with ESA's XMM-Newton X-ray Observatory. Subsequent observations, mainly with XMM-Newton and the Japanese Suzaku Observatory, found such winds to be a common feature of luminous AGN. Typical outflow velocities of v ~ 0.1

Zhuohao Sun, Yiqiao Qiu, Zhijun Tan, Weishi Zheng

Out-of-distribution (OOD) detection is essential when deploying neural networks in the real world. One main challenge is that neural networks often make overconfident predictions on OOD data. In this study, we propose an effective post-hoc OOD detection method based on a new feature masking strategy and a novel logit smoothing strategy. Feature masking deter

Snehal Bhayani, Praneeth Susarla, S. S. Krishna Chaitanya Bulusu, Olli Silven

Beamforming is a signal processing technique where an array of antenna elements can be steered to transmit and receive radio signals in a specific direction. The usage of millimeter wave (mmWave) frequencies and multiple input multiple output (MIMO) beamforming are considered as the key innovations of 5th Generation (5G) and beyond communication systems. The

Cornelis van Damme, Gandhika K. Wardhana, Andrada Iulia Velea, Vasiliki Giagka

In the emerging research field of bioelectronic medicine, it has been indicated that neuromodulation of the Vagus Nerve (VN) has the potential to treat various conditions such as epilepsy, depression, and autoimmune diseases. In order to reduce side effects, as well as to increase the effectiveness of the delivered therapy, subfascicle stimulation specificit

Onurcan Kaya, Luigi Colombo, Aleandro Antidormi, Marco A. Villena

Interconnect materials with ultralow dielectric constant, and good thermal and mechanical properties are crucial for the further miniaturization of electronic devices. Recently, it has been demonstrated that ultrathin amorphous boron nitride (aBN) films have a very low dielectric constant, high density (above 2.1 g/cm3), high thermal stability, and mechanica

Sill Verberne, Sergey E. Koposov, Elena M. Rossi, Tommaso Marchetti

The Gaia mission has provided us full astrometric solutions for over 1.5B sources. However, only the brightest 34M of those have radial velocity measurements. As a proof of concept, this paper aims to close that gap, by obtaining radial velocity estimates from the low-resolution BP/RP spectra that Gaia now provides. These spectra are currently published for

Jichang Xiao, Fengjiang Fu, Xiaoqun Wang

Deep learning algorithms have been widely used to solve linear Kolmogorov partial differential equations~(PDEs) in high dimensions, where the loss function is defined as a mathematical expectation. We propose to use the randomized quasi-Monte Carlo (RQMC) method instead of the Monte Carlo (MC) method for computing the loss function. In theory, we decompose t

Tamay Aykut, Markus Hofbauer, Christopher Kuhn, Eckehard Steinbach

The COVID-19 pandemic shifted many events in our daily lives into the virtual domain. While virtual conference systems provide an alternative to physical meetings, larger events require a muted audience to avoid an accumulation of background noise and distorted audio. However, performing artists strongly rely on the feedback of their audience. We propose a c

Maja Stahl, Nick Düsterhus, Mei-Hua Chen, Henning Wachsmuth

Writing strong arguments can be challenging for learners. It requires to select and arrange multiple argumentative discourse units (ADUs) in a logical and coherent way as well as to decide which ADUs to leave implicit, so called enthymemes. However, when important ADUs are missing, readers might not be able to follow the reasoning or understand the argument'

Balduin Katzer, Daniel Betsche, Klemens Böhm, Daniel Weygand

Three-dimensional dislocation networks control the mechanical properties such as strain hardening of crystals. Due to the complexity of dislocation networks and their temporal evolution, analysis tools are needed that fully resolve the dynamic processes of the intrinsic dislocation graph structure. We propose the use of a graph database for the analysis of t

Lucia Amidani, Jonas J. Joos, Pieter Glatzel, Jindrich Kolorenc

We report the valence-to-core resonant inelastic x-ray scattering (RIXS) of EuS measured at the L3 edge of Eu. The obtained data reveal two sets of excitations: one set is composed of a hole in the S 3p bands and an electron excited to extended Eu 5d band states, the other is made up from a hole in the Eu 4f states and an electron in localized Eu 5d states b

Arafa A. Yagob

In this study the crystal structure of hornblende gneiss has been analyzed by X-ray powder diffraction technique. From X-ray data shows the hornblende is a mixture of four molecules; quartz (SiO_2 ), albite(Al_1 Na_1 O_8 Si_3 ), microcline(Al_1 K_1 O_8 Si_3 ), and biotite (H_1.47 Al_1.92 F_1.98 Fe_2.59 K_2 Mg_3.15 Mn_0.09 O_21.47 Si_5.98 Ti_0.27 ),Then deter

A. C. Ulibarri, C. T. K. Lew, S. Q. Lim, J. C. McCallum

A Gallium interstitial defect (Ga$_{\textrm{i}}$) is thought to be responsible for the spectacular spin-dependent recombination (SDR) in GaAs$_{1-x}$N$_x$ dilute nitride semiconductors. Current understanding associates this defect with two in-gap levels corresponding to the (+/0) and (++/+) charge-state transitions. Using a spin-sensitive photo-induced curre

Xiaolong Hans Han

For closed hyperbolic $3$-manifolds $M$ with volume less than a constant $V$, we prove an inequality regarding the geometric $L^2$-norm and the topological Thurston norm, which is qualitatively sharp and verifies a conjecture of Brock and Dunfield in this case. Generically, we show that the $L^2$-norm is less than a constant $c(V)$ times the Thurston norm by

Katsumasa Nakayama, Kei Suzuki

The Casimir effect is induced by the interplay between photon fields and boundary conditions, and in particular, photon fields modified in axion electrodynamics may lead to the sign-flipping of the Casimir energy. We propose a theoretical approach to derive the Casimir effect in axion electrodynamics. This approach is based on a lattice regularization and en

Fiete Lüer, Tobias Weber, Maxim Dolgich, Christian Böhm

Anomaly detection in imbalanced datasets is a frequent and crucial problem, especially in the medical domain where retrieving and labeling irregularities is often expensive. By combining the generative stability of a $\beta$-variational autoencoder (VAE) with the discriminative strengths of generative adversarial networks (GANs), we propose a novel model, $\

Zhen Du, Fan Liu, Yifeng Xiong, Tony Xiao Han

Integrated Sensing and Communications (ISAC) has garnered significant attention as a promising technology for the upcoming sixth-generation wireless communication systems (6G). In pursuit of this goal, a common strategy is that a unified waveform, such as Orthogonal Frequency Division Multiplexing (OFDM), should serve dual-functional roles by enabling simult

Dorian Quelle, Calvin Cheng, Alexandre Bovet, Scott A. Hale

Misinformation and disinformation are growing threats in the digital age, affecting people across languages and borders. However, no research has investigated the prevalence of multilingual misinformation and quantified the extent to which misinformation diffuses across languages. This paper investigates the prevalence and dynamics of multilingual misinforma

Leandro C. de Almeida, Rafael Pasquini, Chrysa Papagianni, Fábio L. Verdi

Routers employ queues to temporarily hold packets when the scheduler cannot immediately process them. Congestion occurs when the arrival rate of packets exceeds the processing capacity, leading to increased queueing delay. Over time, Active Queue Management (AQM) strategies have focused on directly draining packets from queues to alleviate congestion and red

Jiesi Hu, Yanwu Yang, Xutao Guo, Jinghua Wang

Source-free domain adaptation (SFDA) aims to adapt models trained on a labeled source domain to an unlabeled target domain without the access to source data. In medical imaging scenarios, the practical significance of SFDA methods has been emphasized due to privacy concerns. Recent State-of-the-art SFDA methods primarily rely on self-training based on pseudo

Aloïs Demory

In this paper, we present four families of maximal real algebraic hypersurfaces of even degree in $\mathbb{RP}^4$ constructed using O. Viro's combinatorial patchworking method. We compare the Euler characteristic of the real part and the signature of the complex part of double coverings of $\mathbb{CP}^4$ ramified over the complex part of the constructed rea

Han Xu, Yangbin Zeng, Jialin Zheng, Kainan Chen

Railway Wireless Power Transfer (WPT) is a promising non-contact power supply solution, but constructing prototypes for controller testing can be both costly and unsafe. Real-time hardware-in-the-loop simulation is an effective and secure testing tool, but simulating the dynamic charging process of railway WPT systems is challenging due to the continuous cha

C. L. Pereira, F. Braga-Ribas, B. Sicardy, A. R. Gomes-Júnior

The Centaur (60558) Echeclus was discovered on March 03, 2000, orbiting between the orbits of Jupiter and Uranus. After exhibiting frequent outbursts, it also received a comet designation, 174P. If the ejected material can be a source of debris to form additional structures, studying the surroundings of an active body like Echeclus can provide clues about th

Motohiko Ezawa

Recently, the two-site Kitaev model hosting Majorana edge states was experimentally realized based on double quantum dots. In this context, we construct two-band effective models describing Majorana edge states of a finite-length Kitaev chain by using the isospectral matrix reduction method. We analytically estimate the robustness of Majorana edge states as

Íñigo Zubeldia

As demonstrated by Planck, SPT, and ACT, the abundance of Sunyaev-Zeldovich-detected galaxy clusters across mass and redshift is a powerful cosmological probe. Upcoming experiments such as the Simons Observatory (SO) will detect over an order of magnitude more objects than what previous experiments have found, thereby providing an unprecedented constraining

Chris Evans, Wagner Marcolino, Jean-Claude Bouret, Miriam Garcia

We use synthetic model spectra to investigate the potential of near-ultraviolet (3000-4050 \r{A}) observations of massive O-type stars. We highlight the He I $\lambda$3188 and He II $\lambda$3203 pair as a potential temperature diagnostic in this range, supported by estimates of gravity using the high Balmer series lines. The near-ultraviolet also contains i

Denis Janiak, Jakub Binkowski, Piotr Bielak, Tomasz Kajdanowicz

In recent years, self-supervised learning has played a pivotal role in advancing machine learning by allowing models to acquire meaningful representations from unlabeled data. An intriguing research avenue involves developing self-supervised models within an information-theoretic framework, but many studies often deviate from the stochasticity assumptions ma

Adriane Chapman, Luca Lauro, Paolo Missier, Riccardo Torlone

Successful data-driven science requires complex data engineering pipelines to clean, transform, and alter data in preparation for machine learning, and robust results can only be achieved when each step in the pipeline can be justified, and its effect on the data explained. In this framework, our aim is to provide data scientists with facilities to gain an i

Christian Fiedler

Reproducing kernel Hilbert spaces (RKHSs) are very important function spaces, playing an important role in machine learning, statistics, numerical analysis and pure mathematics. Since Lipschitz and H\"older continuity are important regularity properties, with many applications in interpolation, approximation and optimization problems, in this work we investi

Philhoon Oh, James Thorne

For knowledge intensive NLP tasks, it has been widely accepted that accessing more information is a contributing factor to improvements in the model's end-to-end performance. However, counter-intuitively, too much context can have a negative impact on the model when evaluated on common question answering (QA) datasets. In this paper, we analyze how passages

Yejoon Lee, Philhoon Oh, James Thorne

Recent works in open-domain question answering (QA) have explored generating context passages from large language models (LLMs), replacing the traditional retrieval step in the QA pipeline. However, it is not well understood why generated passages can be more effective than retrieved ones. This study revisits the conventional formulation of QA and introduces

Xiaoyu Tian, Liangyu Chen, Na Liu, Yaxuan Liu

Inspired by the dual-process theory of human cognition, we introduce DUMA, a novel conversational agent framework that embodies a dual-mind mechanism through the utilization of two generative Large Language Models (LLMs) dedicated to fast and slow thinking respectively. The fast thinking model serves as the primary interface for external interactions and ini

Christian Fiedler, Michael Herty, Sebastian Trimpe

In many applications of machine learning, a large number of variables are considered. Motivated by machine learning of interacting particle systems, we consider the situation when the number of input variables goes to infinity. First, we continue the recent investigation of the mean field limit of kernels and their reproducing kernel Hilbert spaces, completi

Xinyu Wang, Lin Gui, Yulan He

Table of contents (ToC) extraction centres on structuring documents in a hierarchical manner. In this paper, we propose a new dataset, ESGDoc, comprising 1,093 ESG annual reports from 563 companies spanning from 2001 to 2022. These reports pose significant challenges due to their diverse structures and extensive length. To address these challenges, we propos

Gabriel H. S. Aguiar, George E. A. Matsas

Explaining the behavior of macroscopic objects from the point of view of the quantum paradigm has challenged the scientific community for a century today. A mechanism of gravitational self-interaction, governed by the so-called Schroedinger-Newton equation, is among the proposals that aim to shed some light on it. Despite all efforts, this mechanism has been

Naonori Kakimura, Tomohiro Nakayoshi

In this paper, we study the Min-cost Perfect $k$-way Matching with Delays ($k$-MPMD), recently introduced by Melnyk et al. In the problem, $m$ requests arrive one-by-one over time in a metric space. At any time, we can irrevocably make a group of $k$ requests who arrived so far, that incurs the distance cost among the $k$ requests in addition to the sum of t

Yilin Zhao, Hai Zhao, Sufeng Duan

Multi-choice Machine Reading Comprehension (MRC) is a major and challenging task for machines to answer questions according to provided options. Answers in multi-choice MRC cannot be directly extracted in the given passages, and essentially require machines capable of reasoning from accurate extracted evidence. However, the critical evidence may be as simple

Dennis Peuter, Philipp Marohn, Viorica Sofronie-Stokkermans

We present an approach to the verification of systems for whose description some elements - constants or functions - are underspecified and can be regarded as parameters, and, in particular, describe a method for automatically generating constraints on such parameters under which certain safety conditions are guaranteed to hold. We present an implementation

Emil Toftegaard Gæde, Inge Li Gørtz, Ivor van der Hoog, Christoffer Krogh

The convex hull of a data set $P$ is the smallest convex set that contains $P$. In this work, we present a new data structure for convex hull, that allows for efficient dynamic updates. In a dynamic convex hull implementation, the following traits are desirable: (1) algorithms for efficiently answering queries as to whether a specified point is inside or out

Ivan Eryganov, Jaroslav Hrdina, Aleš Návrat

In this paper, a novel quantization scheme for cooperative games is proposed. The considered circuit is inspired by the Eisert-Wilkens-Lewenstein protocol modified to represent cooperation between players and extended to $3$-qubit states. The framework of Clifford algebra is used to perform necessary computations. In particular, we use a direct analogy betwe

Hannah Elfner, Niklas Götz, Oscar Garcia-Montero, Jean-Francois Paquet

The photon emission from the late stages of the dynamical evolution of heavy-ion reactions at the highest RHIC and LHC energies is investigated. A comparison between a calculation from hadronic rates from a fluid dynamic evolution down to temperatures of 120 MeV and a full non-equilibrium hadronic transport approach is performed. The photon yields are very s

Franck Ramaharo, Fitiavana Randriamifidy

The aim of this note is to identify the factors influencing renewable energy consumption in Madagascar. We tested 12 features covering macroeconomic, financial, social, and environmental aspects, including economic growth, domestic investment, foreign direct investment, financial development, industrial development, inflation, income distribution, trade open

A. Jaries, M. Stryjczyk, A. Kankainen, T. Eronen

We report on the precise mass measurements of the $^{91}$Sr and $^{95}$Y isotopes performed using the JYFLTRAP double Penning trap mass spectrometer. The mass-excess values from this work, ${\mathrm{ME}(^{91}\mathrm{Sr}) = -83645.5(13)}$ keV and ${\mathrm{ME}(^{95}\mathrm{Y}) = -81226.4(10)}$ keV, deviate by 6.5(52) keV and $-18(7)$ keV from the Atomic Mass

Said Boussakta, Mounir T. Hamood, Mohammed Sh. Ahmed

In this paper, a new fast and low complexity transform is introduced for orthogonal frequency division multiplexing (OFDM) wireless systems. The new transform combines the effects of fast complex-Walsh-Hadamard transform (CHT) and the fast Fourier transform (FFT) into a single unitary transform named in this paper as the complex transition transform (CTT). T

Antoine Chaffin, Julien Delaunay

The ubiquity of complex machine learning has raised the importance of model-agnostic explanation algorithms. These methods create artificial instances by slightly perturbing real instances, capturing shifts in model decisions. However, such methods rely on initial data and only provide explanations of the decision for these. To tackle these problems, we prop

Caroline Namanya

This paper constructs derived autoequivalences associated to an algebraic flopping contraction \(X\to X_{\con}, \) where \(X\) is quasi-projective with only mild singularities. These functors are constructed naturally using bimodule cones, and we prove these cones are locally two-sided tilting complexes by using the local-global properties and a key commutat