October 2022 arXiv papers — page 46

Serge Galam

Defining interdisciplinary physics today requires first a reformulation of what is physics today, which in turn calls for clarifying what makes a physicist. This assessment results from my forty year journey arguing and fighting to build sociophysics. My view on interdisciplinary physics has thus evolved jumping repeatedly to opposite directions before settl

Fulin Deng, Xing-Yan Chen, Xin-Yu Luo, Wenxian Zhang

For microwave-dressed polar molecules, we analytically derive an intermolecular potential composed of an anisotropic van der Waals shielding core and a long-range dipolar interaction. We validate this effective potential by comparing its scattering properties with those calculated using the full multi-channel interaction potential. It is shown that scatterin

J. S. Gonçalves, A. F. Santos

In this paper, $f(R,T,R_{\mu\nu} T^{\mu\nu}$) gravity is considered. It is a modified theory of gravity that exhibits a strong coupling of gravitational and matter fields. Therefore, if gravity is governed by this model a number of issues must be re-examined. In this context, the question of causality and its violation is studied. Such analysis is carried ou

Lingfei Wang, Wei Zhang, Zheyu Wang, Tsz Fung Poon

AV$_3$Sb$_5$ (A=Cs, K, Rb) are recently discovered superconducting systems ($T_{\rm c}\sim0.9-2.5$ K) in which the vanadium atoms adopt the kagome structure. Intriguingly, these systems enter a charge-density-wave (CDW) phase ($T_{\rm CDW}\sim80-100$ K), and further evidence shows that the time-reversal symmetry is broken in the CDW phase. Concurrently, the

Lilit V. Barkhudaryan

In this Letter, using classified 197 supernovae (SNe) Ia, we perform an analyses of their height distributions from the disc in edge-on spirals and investigate their light-curve (LC) decline rates $(\Delta m_{15})$. We demonstrate, for the first time, that 91T- and 91bg-like subclasses of SNe Ia are distributed differently toward the plane of their host disc

Marvin Lavechin, Marianne Métais, Hadrien Titeux, Alodie Boissonnet

Most automatic speech processing systems register degraded performance when applied to noisy or reverberant speech. But how can one tell whether speech is noisy or reverberant? We propose Brouhaha, a neural network jointly trained to extract speech/non-speech segments, speech-to-noise ratios, and C50room acoustics from single-channel recordings. Brouhaha is

Michela Meister, Jon Kleinberg

Contact tracing can be thought of as a race between two processes: an infection process and a tracing process. In this paper, we study a simple model of infection spreading on a tree, and a tracer who stabilizes one node at a time. We focus on the question, how should the tracer choose nodes to stabilize so as to prevent the infection from spreading further?

M. I. Belishev, A. V. Kaplun

The algebra of eikonals $\mathfrak E$ of a metric graph $\Omega$ is an operator $C^*$-algebra determined by dynamical system with boundary control that describes wave propagation on the graph. In this paper, two canonical block forms (algebraic and geometric) of the algebra $\mathfrak E$ are provided for an arbitrary connected locally compact graph. These fo

Yue Zhou

It is well-known that the Selberg integral is equivalent to the Morris constant term identity. More generally, Selberg type integrals can be turned into constant term identities for Laurent polynomials. In this paper, by extending the Gessel--Xin method of the Laurent series proof of constant term identities, we obtain an AFLT type $q$-Morris constant term i

Joao Marques-Silva

The last decade witnessed an ever-increasing stream of successes in Machine Learning (ML). These successes offer clear evidence that ML is bound to become pervasive in a wide range of practical uses, including many that directly affect humans. Unfortunately, the operation of the most successful ML models is incomprehensible for human decision makers. As a re

Miguel Díaz Montiel, Rachid Guerraoui, Pierre-Louis Roman

Blockchain intercommunication systems enable the exchanges of messages between blockchains. This interoperability promotes innovation, unlocks liquidity and access to assets. However, blockchains are isolated systems that originally were not designed for interoperability. This makes cross-chain communication, or bridges for short, insecure by nature. More pr

Alessandra Colla, Niklas Neubrand, Heinz-Peter Breuer

We investigate the dynamics of open quantum systems which are initially correlated with their environment. The strategy of our approach is to analyze how given, fixed initial correlations modify the evolution of the open system with respect to the corresponding uncorrelated dynamical behavior with the same fixed initial environmental state, described by a co

Giuseppe Clemente, Arianna Crippa, Karl Jansen, Selomit Ramírez-Uribe

We present a variational quantum eigensolver (VQE) algorithm for the efficient bootstrapping of the causal representation of multiloop Feynman diagrams in the Loop-Tree Duality (LTD) or, equivalently, the selection of acyclic configurations in directed graphs. A loop Hamiltonian based on the adjacency matrix describing a multiloop topology, and whose differe

Seok Ban, Florian Bertrand, Amir Jaber Chehayeb, Adam Salha

We study the higher order Kobayashi pseudometric introduced by Yu. We first obtain estimates of this pseudometric in a special pseudoconvex domain in $\C^3$. We then study the structure of the higher order extremal discs and their connection with the standard extremal discs for the Kobayashi metric.

Oleg Serikov, Vitaly Protasov, Ekaterina Voloshina, Viktoria Knyazkova

Linguistic analysis of language models is one of the ways to explain and describe their reasoning, weaknesses, and limitations. In the probing part of the model interpretability research, studies concern individual languages as well as individual linguistic structures. The question arises: are the detected regularities linguistically coherent, or on the cont

Ján Karabáš, Edita Máčajová, Roman Nedela, Martin Škoviera

A long-standing conjecture of Berge suggests that every bridgeless cubic graph can be expressed as a union of at most five perfect matchings. This conjecture trivially holds for $3$-edge-colourable cubic graphs, but remains widely open for graphs that are not $3$-edge-colourable. The aim of this paper is to verify the validity of Berge's conjecture for cubic

Wei Chao, Mingjie Jin, Hai-Jun Li, Ying-Quan Peng

Although axion-like particles (ALPs) are popular dark matter candidates, their mass generation mechanisms as well as cosmic thermal evolutions are still unclear. In this letter, we propose a new mass generation mechanism of ALP during the electroweak phase transition in the presence of the type-II seesaw mechanism. As ALP gets mass uniquely at the electrowea

David Berghaus, Robert Stephen Jones, Hartmut Monien, Danylo Radchenko

We numerically compute the lowest Laplacian eigenvalues of several two-dimensional shapes with dihedral symmetry at arbitrary precision arithmetic. Our approach is based on the method of particular solutions with domain decomposition. We are particularly interested in asymptotic expansions of the eigenvalues $\lambda(n)$ of shapes with $n$ edges that are of

Luis A. Razo-López, J. A. Méndez-Bermúdez, Victor A. Gopar

We study the time delay of reflected and transmitted waves in 1D disordered media with high transmission. Highly transparent and translucent random media are found in nature or can be synthetically produced. We perform numerical simulations of microwaves propagating in disordered waveguides to show that reflection amplitudes are described by complex Gaussian

Alireza Bordbar, Mohammad Hossein Kahaei

Despite the outstanding performance of deep neural networks in different applications, they are still computationally extensive and require a great number of memories. This motivates more research on reducing the resources required for implementing such networks. An efficient approach addressed for this purpose is matrix factorization, which has been shown t

Hanci Chi

We prove that there exists at least one positive Einstein metric on $\mathbb{HP}^{m+1}\sharp \overline{\mathbb{HP}}^{m+1}$ for $m\geq 2$. Based on the existence of the first Einstein metric, we give a criterion to check the existence of a second Einstein metric on $\mathbb{HP}^{m+1}\sharp \overline{\mathbb{HP}}^{m+1}$. We also investigate the existence of co

Ahsan Adeel, Adewale Adetomi, Khubaib Ahmed, Amir Hussain

Context-sensitive two-point layer 5 pyramidal cells (L5PCs) were discovered as long ago as 1999. However, the potential of this discovery to provide useful neural computation has yet to be demonstrated. Here we show for the first time how a transformative L5PCs-driven deep neural network (DNN), termed the multisensory cooperative computing (MCC) architecture

Liam van der Poel, Ryan Cotterell, Clara Meister

Despite significant progress in the quality of language generated from abstractive summarization models, these models still exhibit the tendency to hallucinate, i.e., output content not supported by the source document. A number of works have tried to fix--or at least uncover the source of--the problem with limited success. In this paper, we identify a simpl

Pascal Rink, Werner Brannath

In machine learning, the selection of a promising model from a potentially large number of competing models and the assessment of its generalization performance are critical tasks that need careful consideration. Typically, model selection and evaluation are strictly separated endeavors, splitting the sample at hand into a training, validation, and evaluatio

Mateusz Godzik, Jacek Dajda, Marek Kisiel-Dorohinicki, Aleksander Byrski

Evolutionary multi-agent systems (EMASs) are very good at dealing with difficult, multi-dimensional problems, their efficacy was proven theoretically based on analysis of the relevant Markov-Chain based model. Now the research continues on introducing autonomous hybridization into EMAS. This paper focuses on a proposed hybrid version of the EMAS, and covers

Yi-Xian Chen, Avery Bailey, James M. Stone, Zhaohuan Zhu

We apply 3D hydrodynamical simulations to study the rotational aspect of gas flow patterns around eccentric companions embedded in an accretion disk around its primary host. We sample a wide range of companion mass ratio q and disk aspect ratio h, and confirm a generic transition from prograde (steady tidal interaction dominated) to retrograde (background Ke

Julien Melleray

We investigate some properties of the clopen type semigroup of an action of a countable group on a compact, $0$-dimensional, Hausdorff space X. We discuss some characterizations of dynamical comparison (most of which were already known in the metrizable case) in this setting; and prove that for a Cantor minimal action $\alpha$ of an amenable group the topolo

Aymen Rachdi, Fedi Zrelli, Amine Kammmoun

For a robot to be perfect and enter the everyday life of humans,like computers did, it needs to move from special-purpose robots to general-purpose. So, the idea of modularity is considered in this project.Thus, any type of task that falls in the 4 D's of Robotization: Dull, Dirty, Dangerous and Dear can be achieved by adding a module to the robot.

Timo Breuer, Narges Tavakolpoursaleh, Johann Schaible, Daniel Hienert

Involving users in early phases of software development has become a common strategy as it enables developers to consider user needs from the beginning. Once a system is in production, new opportunities to observe, evaluate and learn from users emerge as more information becomes available. Gathering information from users to continuously evaluate their behav

Laetitia Mbetkwe Youwa, Jean Pierre Nguenang, Paul André Paglan, Thierry Dauxois

We study the effective dynamics of ferromagnetic spin chains in presence of long-range interactions. We consider the Heisenberg Hamiltonian in one dimension for which the spins are coupled through power-law long-range exchange interactions with exponent $\alpha$. We add to the Hamiltonian an anisotropy in the $z$-direction. In the framework of a semiclassica

Jonas Landman, Slimane Thabet, Constantin Dalyac, Hela Mhiri

Many applications of quantum computing in the near term rely on variational quantum circuits (VQCs). They have been showcased as a promising model for reaching a quantum advantage in machine learning with current noisy intermediate scale quantum computers (NISQ). It is often believed that the power of VQCs relies on their exponentially large feature space, a

Thomas T. Enevoldsen, Roberto Galeazzi

This paper addresses local path re-planning for $n$-dimensional systems by introducing an informed sampling scheme and cost function to achieve collision avoidance with minimum deviation from an (optimal) nominal path. The proposed informed subset consists of the union of ellipsoids along the specified nominal path, such that the subset efficiently encapsula

Christoph Lamm

We present a table of symmetric diagrams for strongly invertible knots up to 10 crossings, point out the similarity of transvergent diagrams for strongly invertible knots with symmetric union diagrams and discuss open questions.

Francisco J. Casas, Patricio Vielva, R. Belen Barreiro, Enrique Martínez-González

This paper presents a polarization calibration method applied to a microwave polarimeter demonstrator based on a near-infrared (NIR) frequency up-conversion stage that allows both optical correlation and signal detection at a wavelength of 1550 nm. The instrument was designed to measure the polarization of cosmic microwave background (CMB) radiation from the

H. Babaei-Aghbolagh, Komeil Babaei Velni, Davood Mahdavian Yekta, H. Mohammadzadeh

In this paper, we will investigate a manifestly $SL(2,R)$-invariant structure for the energy-momentum tensor of ModMax theory as a nonlinear modification of Maxwell electrodynamics which includes conformal invariance as well. In the context of this theory, we show that the energy-momentum tensor of the generalized Born-Infeld theory can also be written in th

N. Brughmans, J. M. Jenkins, R. Keppens

Aims. We begin by exploring the influence of two classes of commonly adopted heating models on the formation behaviour of solar prominences. These models consider either an exponential variation dependent on height alone, or local density and magnetic field conditions. We highlight and address some of the limitations inherent to these early approximations by

Nima Haghpanah, Ron Siegel

We consider a monopolistic seller in a market that may be segmented. The surplus of each consumer in a segment depends on the price that the seller optimally charges, which depends on the set of consumers in the segment. We study which segmentations may result from the interaction among consumers and the seller. Instead of studying the interaction as a non-c

Dong-Young Lim, Ariel Neufeld, Sotirios Sabanis, Ying Zhang

We introduce a new Langevin dynamics based algorithm, called e-TH$\varepsilon$O POULA, to solve optimization problems with discontinuous stochastic gradients which naturally appear in real-world applications such as quantile estimation, vector quantization, CVaR minimization, and regularized optimization problems involving ReLU neural networks. We demonstrat

Bhushan Chaudhari, Akash Agarwal, Tanmoy Bhowmik

Machine learning models built on datasets containing discriminative instances attributed to various underlying factors result in biased and unfair outcomes. It's a well founded and intuitive fact that existing bias mitigation strategies often sacrifice accuracy in order to ensure fairness. But when AI engine's prediction is used for decision making which ref

Yiming Hu, Yangchuan Huang, Shuying Liu, Yuanyang Qi

Urban rail transit provides significant comprehensive benefits such as large traffic volume and high speed, serving as one of the most important components of urban traffic construction management and congestion solution. Using real passenger flow data of an Asian subway system from April to June of 2018, this work analyzes the space-time distribution of the

Leonie Weissweiler, Valentin Hofmann, Abdullatif Köksal, Hinrich Schütze

Construction Grammar (CxG) is a paradigm from cognitive linguistics emphasising the connection between syntax and semantics. Rather than rules that operate on lexical items, it posits constructions as the central building blocks of language, i.e., linguistic units of different granularity that combine syntax and semantics. As a first step towards assessing t

Thomas Christopoulos, Emmanouil E. Kriezis, Odysseas Tsilipakos

Resonant structures in modern nanophotonics are non-Hermitian (leaky and lossy), and support quasinormal modes. Moreover, contemporary cavities frequently include 2D materials to exploit and resonantly enhance their nonlinear properties or provide tunability. Such materials add further modeling complexity due to their infinitesimally thin nature and strong d

Rongrong Xie, Matteo Marsili

We discuss probabilistic neural networks with a fixed internal representation as models for machine understanding. Here understanding is intended as mapping data to an already existing representation which encodes an {\em a priori} organisation of the feature space. We derive the internal representation by requiring that it satisfies the principles of maxima

Hanxuan Yang, Ruike Zhang, Qingchao Kong, Wenji Mao

Graph representation learning is a fundamental research issue and benefits a wide range of applications on graph-structured data. Conventional artificial neural network-based methods such as graph neural networks (GNNs) and variational graph auto-encoders (VGAEs) have achieved promising results in learning on graphs, but they suffer from extremely high energ

Davide Cusseddu, Anotida Madzvamuse

The bulk-surface wave pinning model is a reaction-diffusion system for studying cell polarisation. It is constituted by a surface reaction-diffusion equation, coupled to a bulk diffusion equation with a non-linear boundary condition. Cell polarisation arises as the surface component develops specific patterns. Since proteins diffuse much faster in the cell i

Yuanzhe Xu, Sumit Mukherjee

In this paper, we derive the limit of experiments for one parameter Ising models on dense regular graphs. In particular, we show that the limiting experiment is Gaussian in the low temperature regime, non Gaussian in the critical regime, and an infinite collection of Gaussians in the high temperature regime. We also derive the limiting distributions of the m

Hans-Peter Schröcker, Zbyněk Šír

All rational parametric curves with prescribed polynomial tangent direction form a vector space. Via tangent directions with rational norm, this includes the important case of rational Pythagorean hodograph curves. We study vector subspaces defined by fixing the denominator polynomial and describe the construction of canonical bases for them. We also show (a

Diana Caponetti, Alessandro Trombetta, Giulio Trombetta

In this paper we estimate the Kuratowski and the Hausdorff measures of noncompactness of bounded subsets of spaces of vector-valued bounded functions and of vector-valued bounded differentiable functions. To this end, we use a quantitative characteristic modeled on a new equiconti\-nuity-type concept and classical quantitative characteristics related to poin

J. Tounli, A. S. Sanz

In the last decades, the experimental research on Bose-Einstein interferometry has received much attention due to promising technological implications. This has thus motivated the development of numerical simulations aimed at solving the time-dependent Gross-Pitaevskii equation and its reduced one-dimensional version to better understand the development of i

Ben Brubaker, Will Grodzicki, Andrew Schultz

Recent works have sought to realize certain families of orthogonal, symmetric polynomials as partition functions of well-chosen classes of solvable lattice models. Many of these use Boltzmann weights arising from the trigonometric six-vertex model $R$-matrix (or generalizations or specializations of these weights). In this paper, we seek new variants of boso

Fabienne Comte, Nicolas Marie

In the present paper, we consider that $N$ diffusion processes $X^1,\dots,X^N$ are observed on $[0,T]$, where $T$ is fixed and $N$ grows to infinity. Contrary to most of the recent works, we no longer assume that the processes are independent. The dependency is modeled through correlations between the Brownian motions driving the diffusion processes. A nonpa

Benjamin Hivert, Denis Agniel, Rodolphe Thiébaut, Boris P Hejblum

Clustering is part of unsupervised analysis methods that consist in grouping samples into homogeneous and separate subgroups of observations also called clusters. To interpret the clusters, statistical hypothesis testing is often used to infer the variables that significantly separate the estimated clusters from each other. However, data-driven hypotheses ar

Viet Anh Khoa Tran, David Thulke, Yingbo Gao, Christian Herold

Currently, in speech translation, the straightforward approach - cascading a recognition system with a translation system - delivers state-of-the-art results. However, fundamental challenges such as error propagation from the automatic speech recognition system still remain. To mitigate these problems, recently, people turn their attention to direct data and

Jiawei Wang, Yingzhao Lian, Yuning Jiang, Qing Xu

Cooperative control of connected and automated vehicles (CAVs) promises smoother traffic flow. In mixed traffic, where human-driven vehicles with unknown dynamics coexist, data-driven predictive control techniques allow for CAV safe and optimal control with measurable traffic data. However, the centralized control setting in most existing strategies limits t

Surya Giri, S. Sivaprasad Kumar

For the classes of analytic functions $f$ defined on the unit disk satisfying $$\frac{z {f}'(z)}{f(z) - f(-z)} \prec \varphi(z) \quad \text{and} \quad \frac{(2 z {f}'(z))'}{(f(z) - f(-z))'} \prec \varphi(z),$$ denoted by $\mathcal{S}^*_s(\varphi)$ and $\mathcal{C}_s(\varphi)$ respectively, the sharp bound of the $n^{th}$ Taylor coefficients are known for $n=

Daisuke Miki, Nobuyuki Matsumoto, Akira Matsumura, Tomoya Shichijo

This study is aimed at investigating the feasibility of generating quantum entanglement between macroscopic mechanical mirrors in optomechanical systems while under continuous measurement and feedback control. We carefully derive a covariance matrix for mechanical mirrors in a steady state, employing the Kalman filtering problem with an assumed dominant cavi

Stefano Bannò, Marco Matassoni

The increasing demand for learning English as a second language has led to a growing interest in methods for automatically assessing spoken language proficiency. Most approaches use hand-crafted features, but their efficacy relies on their particular underlying assumptions and they risk discarding potentially salient information about proficiency. Other appr

Ivica Obadic, Ribana Roscher, Dario Augusto Borges Oliveira, Xiao Xiang Zhu

Transformer models have become a promising approach for crop-type classification. Although their attention weights can be used to understand the relevant time points for crop disambiguation, the validity of these insights depends on how closely the attention weights approximate the actual workings of these black-box models, which is not always clear. In this

Surya Giri, S. Sivaprasad Kumar

This paper examines the coefficient problems for the class of semigroup generators, a topic in complex dynamics that has recently been studied in context of geometric function theory. Further, sharp bounds of coefficient functional such as second order Hankel determinant, third order Toeplitz and Hermitian-Toeplitz determinants are derived. Additionally, the

Bocoum Maïmouna, Cheng Zhao, Kaur Jaismeen, Lopez-Martens Rodrigo

Discriminating between ballistic and diffuse components of light propagating through highly scattering media is not only important for imaging purposes but also for investigating the fundamental diffusion properties of the medium itself. Massively developed to this end over the past 20 years, nonlinear temporal gating remains limited to about 10e-10 transmis

Hélène Halconruy, Nicolas Marie

This paper deals with a projection least squares estimator of the drift function of a jump diffusion process $X$ computed from multiple independent copies of $X$ observed on $[0,T]$. Risk bounds are established on this estimator and on an associated adaptive estimator. Finally, some numerical experiments are provided.

Surya Giri, S. Sivaprasad Kumar

In this paper, we establish the sharp bounds of certain Toeplitz determinants formed over the coefficients of mappings from a class defined on the unit ball of complex Banach space and on the unit polydisc in $\mathbb{C}^n$. Derived bounds provide certain new results for the subclasses of normalized univalent functions and extend some known results in higher

Jitao Xu, Josep Crego, François Yvon

Machine Translation (MT) is usually viewed as a one-shot process that generates the target language equivalent of some source text from scratch. We consider here a more general setting which assumes an initial target sequence, that must be transformed into a valid translation of the source, thereby restoring parallelism between source and target. For this bi

Tobias Lojewski, Mohamed F. Elhanoty, Loïc Le Guyader, Oscar Grånäs

The complex electronic structure of metallic ferromagnets is determined by a balance between exchange interaction, electron hopping leading to band formation, and local Coulomb repulsion. The interplay between the respective terms of the Hamiltonian is of fundamental interest, since it produces most, if not all, of the exotic phenomena observed in the solid

Adolfo Arroyo-Rabasa

We introduce a general difference quotient representation for non-local operators associated with a first-order linear operator. We establish new local to non-local estimates and strong localization principles in various spaces of functions, measures and distributions, which fully generalize those known for gradients. Under suitable assumptions, we also esta

Gernot Beer

The aim of the paper is to show algorithms for geometrical manipulations on NURBS surfaces. These include generating NURBS surfaces that pass through given points, calculating the minimum distance to a point and include line to surface and surface to surface intersections.

Jan-Hendrik Lorenz, Florian Wörz

The satisfiability problem is one of the most famous problems in computer science. Its NP-completeness has been used to argue that SAT is intractable. However, there have been tremendous advances that allow SAT solvers to solve instances with millions of variables. A particularly successful paradigm is stochastic local search. In most cases, there are differ

Surya Giri, S. Sivaprasad Kumar

In this study, we derive the sharp bounds of certain Toeplitz determinants whose entries are the coefficients of holomorphic functions belonging to a class defined on the unit disk $\mathbb{U}$. Further, these results are extended to a class of holomorphic functions on the unit ball in a complex Banach space and on the unit polydisc in $\mathbb{C}^n$. The ob

Feimin Huang, Xiaochun Wu

In 1992, Hsiao and Liu \cite{Hsiao-Liu-1} firstly showed that the solution to the compressible Euler equations with damping time-asymptotically converges to the diffusion wave $(\bar v, \bar u)$ of the porous media equation. In \cite{Geng-Huang-Jin-Wu}, we proposed a time-asymptotic expansion around the diffusion wave $(\bar v, \bar u)$, which is a better as

Manon Flageat, Felix Chalumeau, Antoine Cully

Quality-Diversity algorithms, among which MAP-Elites, have emerged as powerful alternatives to performance-only optimisation approaches as they enable generating collections of diverse and high-performing solutions to an optimisation problem. However, they are often limited to low-dimensional search spaces and deterministic environments. The recently introdu

Leyu Han

Let \mathfrak{g}=\mathfrak{g}_{\bar{0}}\oplus\mathfrak{g}_{\bar{1}} be a basic classical Lie superalgebra over an algebraically closed field \mathbb{K} whose characteristic p>0 is a good prime for \mathfrak{g}. Let G_{\bar{0}} be the reductive algebraic group over \mathbb{K} such that \mathrm{Lie}(G_{\bar{0}})=\mathfrak{g}_{\bar{0}}. Suppose e\in\mathfrak{g}

James R. Wootton

The recently introduced Floquet codes have already inspired several follow up works in terms of theory and simulation. Here we report the first preliminary results on their experimental implementation, using IBM Quantum hardware. Specifically, we implement the stabilizer measurements of the original Floquet code based on the honeycomb lattice model, as well

Kaixin Wang, Kuangqi Zhou, Jiashi Feng, Bryan Hooi

In Reinforcement Learning (RL), Laplacian Representation (LapRep) is a task-agnostic state representation that encodes the geometry of the environment. A desirable property of LapRep stated in prior works is that the Euclidean distance in the LapRep space roughly reflects the reachability between states, which motivates the usage of this distance for reward

Jun Gao, Chunhua Zhu, Jinlong Yu, Helei Liu

Context. About 0.2-2% of giant stars are Li-rich, whose lithium abundance (A(Li)) is higher than 1.5 dex. Among them, near 6% are super Li-rich with A(Li) exceeding 3.2 dex. Meanwhile, the formation mechanism of these Li-rich and super Li-rich giants is still under debate. Aims. Considering the compact He core of red giants, attention is paid to the effect o

Mahmood Khosrowjerdi

Information transparency is a major building block of responsible governments. We explored factors influencing the information transparency of 117 world nations. After controlling for the effects of confounding variables of wealth (GDP per capita), corruption rate, population density, human capital, and telecommunication infrastructure, we found that the goo

Arash Behboodi, Gabriele Cesa, Taco Cohen

Equivariant networks capture the inductive bias about the symmetry of the learning task by building those symmetries into the model. In this paper, we study how equivariance relates to generalization error utilizing PAC Bayesian analysis for equivariant networks, where the transformation laws of feature spaces are determined by group representations. By usin

Junfu Wang, Yuanfang Guo, Liang Yang, Yunhong Wang

The current success of Graph Neural Networks (GNNs) usually relies on loading the entire attributed graph for processing, which may not be satisfied with limited memory resources, especially when the attributed graph is large. This paper pioneers to propose a Binary Graph Convolutional Network (Bi-GCN), which binarizes both the network parameters and input n

Yuankai Luo, Veronika Thost, Lei Shi

Transformer models have recently gained popularity in graph representation learning as they have the potential to learn complex relationships beyond the ones captured by regular graph neural networks. The main research question is how to inject the structural bias of graphs into the transformer architecture, and several proposals have been made for undirecte

Fabiola Antonietta Gerosa, Héloïse Meheut, Jérémie Bec

Protoplanetary disks are gaseous systems in Keplerian rotation around young stars, known to be turbulent. They include a small fraction of dust from which planets form. In the incremental scenario for planet growth, the formation of kilometer-size objects (planetesimals) from pebbles is a major open question. Clustering of particles is necessary for solids t

Toshiyuki Kobayashi

We prove that any simply connected non-compact semisimple Lie group $G$ admits an infinite-dimensional irreducible representation $\Pi$ with bounded multiplicity property of the restriction $\Pi|_{G'}$ for all symmetric pairs $(G, G')$. We also discuss which irreducible representations $\Pi$ satisfy the bounded multiplicity property.

Richard Andrášik, Václav Mácha, Rostislav Vodák

Our paper deals with three-dimensional nonsteady Navier-Stokes equations for non-Newtonian compressible fluids. It contains a~derivation of the relative energy inequality for the weak solutions to these equations. We show that the standard energy inequality implies the relative energy inequality. Consequently, the relative energy inequality allows us to achi

Jinzi Qi, Hugo Van hamme

The scarcity of training data and the large speaker variation in dysarthric speech lead to poor accuracy and poor speaker generalization of spoken language understanding systems for dysarthric speech. Through work on the speech features, we focus on improving the model generalization ability with limited dysarthric data. Factorized Hierarchical Variational A

Belle II collaboration, F. Abudinén, I. Adachi, K. Adamczyk

We present a determination of the magnitude of the Cabibbo-Kobayashi-Maskawa (CKM) matrix element $V_{cb}$ using $B\to D\ell\nu$ decays. The result is based on $e^+e^-\to\Upsilon(4S)$ data recorded by the Belle II detector corresponding to 189.2/fb of integrated luminosity. The semileptonic decays $B^0\to D^-(\to K^+\pi^-\pi^-)\ell^+\nu_\ell$ and $B^+\to\bar

Shui Feng

The Hierarchical Dirichlet process is a discrete random measure serving as an important prior in Bayesian non-parametrics. It is motivated with the study of groups of clustered data. Each group is modelled through a level two Dirichlet process and all groups share the same base distribution which itself is a drawn from a level one Dirichlet process. It has t

Maksym Ovchynnikov, Thomas Schwetz, Jing-Yu Zhu

We estimate the sensitivity of the DUNE experiment to new physics particles interacting with neutrinos, considering the dipole portal to heavy neutral leptons and a neutrinophilic scalar with lepton-number $2$ as examples. We demonstrate that neutrinos from the high-energy tail of the DUNE flux, with energies $E_{\nu}\gtrsim 5-10\text{ GeV}$, may significant

Vittorio Capocasale, Guido Perboli

Blockchain and distributed ledger technologies are gaining the interest of the academy, companies, and institutions. Nonetheless, the path toward blockchain adoption is not straightforward, as blockchain is a complex technology that requires revisiting the standard way of addressing problems and tackling them from a decentralized perspective. Thus, decision-

Sjoerd Hermes, Joost van Heerwaarden, Pariya Behrouzi

This article proposes a graphical model that handles mixed-type, multi-group data. The motivation for such a model originates from real-world observational data, which often contain groups of samples obtained under heterogeneous conditions in space and time, potentially resulting in differences in network structure among groups. Therefore, the i.i.d. assumpt

Eric Buschmann

Caribou is a flexible open-source DAQ system developed and used within several collaborative frameworks (CERN EP R&D, RD50, AIDAinnova) for laboratory and high-rate beam tests and easy integration of new silicon-pixel detector prototypes. It uses common hardware, firmware and software components that are shared across different projects, thereby reducing the

F. Ghoreishi, R. Ghaffari

This paper investigates, a new class of fractional order Runge-Kutta (FORK) methods for numerical approximation to the solution of fractional differential equations (FDEs). By using the Caputo generalizedTaylor formula and the total differential for Caputo fractional derivative, we construct explicit and implicit FORK methods, as the well-known Runge-Kutta s

Takuya Murata, Lara Bossinger

Given a toric degeneration (a degeneration to a toric variety), over the complex numbers, we construct a surjective continuous map from a general fiber to the special fiber of the degeneration in the classical topology. The construction is a variant of one due to Goresky and MacPherson based on the Thom--Mather theory of stratified spaces. As an application,

Yuya Sasaki

Graph association rule mining is a data mining technique used for discovering regularities in graph data. In this study, we propose a novel concept, {\it path association rule mining}, to discover the correlations of path patterns that frequently appear in a given graph. Reachability path patterns (i.e., existence of paths from a vertex to another vertex) ar

Evgeny I. Buchbinder, Benjamin J. Stone

We analyse the general structure of the three-point functions involving conserved bosonic and fermionic higher-spin currents in three-dimensional conformal field theory. Using the constraints of conformal symmetry and conservation equations, we use a computational formalism to analyse the general structure of $\langle J^{}_{s_{1}} J'_{s_{2}} J''_{s_{3}} \ran

Chen Qiu, Dan Oneata, Emanuele Bugliarello, Stella Frank

Most vision-and-language pretraining research focuses on English tasks. However, the creation of multilingual multimodal evaluation datasets (e.g. Multi30K, xGQA, XVNLI, and MaRVL) poses a new challenge in finding high-quality training data that is both multilingual and multimodal. In this paper, we investigate whether machine translating English multimodal

Sina Mews, Bastian Surmann, Lena Hasemann, Svenja Elkenkamp

We explore Markov-modulated marked Poisson processes (MMMPPs) as a natural framework for modelling patients' disease dynamics over time based on medical claims data. In claims data, observations do not only occur at random points in time but are also informative, i.e. driven by unobserved disease levels, as poor health conditions usually lead to more frequen

Otmane Sakhi, Pierre Alquier, Nicolas Chopin

This paper introduces a new principled approach for off-policy learning in contextual bandits. Unlike previous work, our approach does not derive learning principles from intractable or loose bounds. We analyse the problem through the PAC-Bayesian lens, interpreting policies as mixtures of decision rules. This allows us to propose novel generalization bounds

J. Ignacio Deza, Hisham Ihshaish, Lamine Mahdjoubi

We introduce the first automated models for classifying natural language descriptions provided in cost documents called "Bills of Quantities" (BoQs) popular in the infrastructure construction industry, into the International Construction Measurement Standard (ICMS). The models we deployed and systematically evaluated for multi-class text classification are l

Gustav Eriksson, Jonatan Werpers, David Niemelä, Niklas Wik

We consider energy stable summation by parts finite difference methods (SBP-FD) for the homogeneous and piecewise homogeneous dynamic beam equation (DBE). Previously the constant coefficient problem has been solved with SBP-FD together with penalty terms (SBP-SAT) to impose boundary conditions. In this work we revisit this problem and compare SBP-SAT to the

Marcelo de Almeida, Tiago Picon, Claudio Vasconcelos

In this note we address the continuity of strongly singular Calder\'on-Zygmund operators on Hardy-Morrey spaces $\mathcal{HM}_{q}^{\lambda}(\mathbb{R}^n)$, assuming weaker integral conditions on the associated kernel. Important examples that falls into this scope are pseudodifferential operators on the H\"ormander classes $OpS^{m}_{\sigma,\mu}(\mathbb{R}^n)$

Ester Gonzalez-Sosa, Julian Fierrez, Ruben Vera-Rodriguez, Fernando Alonso-Fernandez

The role of soft biometrics to enhance person recognition systems in unconstrained scenarios has not been extensively studied. Here, we explore the utility of the following modalities: gender, ethnicity, age, glasses, beard, and moustache. We consider two assumptions: 1) manual estimation of soft biometrics and 2) automatic estimation from two commercial off

Viktor Valadi, Madeleine Englund, Mark Spanier, Austin O'brien

This paper proposes and investigates a new approach for detecting and preventing several different types of poisoning attacks from affecting a centralized Federated Learning model via average accuracy deviation detection (AADD). By comparing each client's accuracy to all clients' average accuracy, AADD detect clients with an accuracy deviation. The implement