October 2023 arXiv papers — page 83

Michel Alexis, Gevorg Mnatsakanyan, Christoph Thiele

Elucidating a connection with nonlinear Fourier analysis, we extend a well known algorithm in quantum signal processing to represent measurable signals by square summable sequences. Each coefficient of the sequence is Lipschitz continuous as a function of the signal.

Kao-Yueh Kuo, Ching-Yi Lai

Quantum stabilizer codes often struggle with syndrome errors due to measurement imperfections. Typically, multiple rounds of syndrome extraction are employed to ensure reliable error information. In this paper, we consider phenomenological decoding problems, where data qubit errors may occur between extractions, and each measurement can be faulty. We introdu

Hanna Liis Tamm, João Luís Rosa

In this work we analyze the observational properties of relativistic fluid spheres when orbited by isotropically emitting sources, known as hot spots. We consider fluid star configurations in four different regimes of compacticity, from the Buchdahl limit to non-ultra compact solutions, thus obtaining fluid stars with qualitatively different geodesic structu

Puneesh Deora, Rouzbeh Ghaderi, Hossein Taheri, Christos Thrampoulidis

The training and generalization dynamics of the Transformer's core mechanism, namely the Attention mechanism, remain under-explored. Besides, existing analyses primarily focus on single-head attention. Inspired by the demonstrated benefits of overparameterization when training fully-connected networks, we investigate the potential optimization and generaliza

S. Semenov, A. N. Rubtsov

The Landau Free Energy determines the landscape of order parameter fluctuations that occur in a physical system at thermal equilibrium and, in particular, characterizes the critical phenomena. We propose a semi-analytical approach based on the Fluctuating Local Field method, which allows to estimate Landau Free Energy for small clusters with discrete (Ising

Jiaxu Zhang, Shaoli Huang, Zhigang Tu, Xin Chen

Previous motion generation methods are limited to the pre-rigged 3D human model, hindering their applications in the animation of various non-rigged characters. In this work, we present TapMo, a Text-driven Animation Pipeline for synthesizing Motion in a broad spectrum of skeleton-free 3D characters. The pivotal innovation in TapMo is its use of shape deform

Shreyasi Pathak, Jörg Schlötterer, Jeroen Geerdink, Jeroen Veltman

Breast cancer prediction models for mammography assume that annotations are available for individual images or regions of interest (ROIs), and that there is a fixed number of images per patient. These assumptions do not hold in real hospital settings, where clinicians provide only a final diagnosis for the entire mammography exam (case). Since data in real h

Herbie Bradley, Andrew Dai, Hannah Teufel, Jenny Zhang

In many text-generation problems, users may prefer not only a single response, but a diverse range of high-quality outputs from which to choose. Quality-diversity (QD) search algorithms aim at such outcomes, by continually improving and diversifying a population of candidates. However, the applicability of QD to qualitative domains, like creative writing, ha

Thibault Wildi, Alexander Ulanov, Nicolas Englebert, Thibault Voumard

Frequency combs from continuous-wave-driven Kerr-nonlinear microresonators have evolved into a key photonic technology with applications from optical communication to precision spectroscopy. Essential to many of these applications is the control of the comb's defining parameters, i.e., carrier-envelope offset frequency and repetition rate. An elegant and all

Simone Artini, Mauro Paternostro

We investigate the phenomenology leading to the non-conservation of energy of the continuous spontaneous localization (CSL) model from the viewpoint of non-equilibrium thermodynamics, and use such framework to assess the equilibration process entailed by the dissipative formulation of the model (dCSL). As a paradigmatic situation currently addressed in front

STAR Collaboration, M. I. Abdulhamid, B. E. Aboona, J. Adam

At the origin of the Universe, asymmetry between the amount of created matter and antimatter led to the matter-dominated Universe as we know today. The origins of this asymmetry remain not completely understood yet. High-energy nuclear collisions create conditions similar to the Universe microseconds after the Big Bang, with comparable amounts of matter and

Eloy Peña-Asensio, Jaakko Visuri, Josep M. Trigo-Rodríguez, Hector Socas-Navarro

The observation of interstellar objects 1I/'Oumuamua and 2I/Borisov suggests the existence of a larger population of smaller projectiles that impact our planet with unbound orbits. We analyze an asteroidal grazing meteor (FH1) recorded by the Finnish Fireball Network on October 23, 2022. FH1 displayed a likely hyperbolic orbit lying on the ecliptic plane wit

Andreas Gleis, Seung-Sup B. Lee, Gabriel Kotliar, Jan von Delft

We study paramagnetic quantum criticality in the periodic Anderson model (PAM) using cellular dynamical mean-field theory, with the numerical renormalization group (NRG) as an impurity solver. The PAM describes an itinerant $c$ band hybridizing with a localized $f$ band. At $T=0$, it exhibits a hybridization tuned Kondo breakdown quantum critical point (KB-Q

Freek Holvoet, Katrien Antonio, Roel Henckaerts

Insurers usually turn to generalized linear models for modeling claim frequency and severity data. Due to their success in other fields, machine learning techniques are gaining popularity within the actuarial toolbox. Our paper contributes to the literature on frequency-severity insurance pricing with machine learning via deep learning structures. We present

Yuxin Wang, Xueze Kang, Shaohuai Shi, Xin He

To efficiently scale large model (LM) training, researchers transition from data parallelism (DP) to hybrid parallelism (HP) on GPU clusters, which frequently experience hardware and software failures. Existing works introduce in-memory checkpointing optimizations that snapshot parameters to device memory for rapid failure recovery. However, these methods in

Fatima Alarab, Karol Hricovini, Berengar Leikert, Christine Richter

Epitaxial thin films of SrTiO$_3$(100) doped with 6% and 12% Ni are studied with resonant angle-resolved photoelectron spectroscopy (ARPES) at the Ti and Ni L2,3-edges. We find that the Ni doping shifts the valence band (VB) of pristine SrTiO$_3$ towards the Fermi level (p-doping) and reduces its band gap. This is accompanied by an upward energy shift of the

Julio Arrechea, Carlos Barceló, Raúl Carballo-Rubio, Luis J. Garay

The backreaction of quantum fields in their vacuum state results in equilibrium structures that surpass the Buchdahl compactness limit. Such backreaction is encapsulated in the vacuum expectation value of the renormalized stress-energy tensor (RSET). In previous works we presented analytic approximations to the RSET, obtained by dimensional reduction, availa

Belhal Karimi, Jianwen Xie, Ping Li

We propose in this paper, STANLEY, a STochastic gradient ANisotropic LangEvin dYnamics, for sampling high dimensional data. With the growing efficacy and potential of Energy-Based modeling, also known as non-normalized probabilistic modeling, for modeling a generative process of different natures of high dimensional data observations, we present an end-to-en

Segev Wasserkrug, Takayuki Osogami

In enterprise cloud computing, there is a big and increasing investment to move to multi-cloud computing, which allows enterprises to seamlessly utilize IT resources from multiple cloud providers, so as to take advantage of different cloud providers' capabilities and costs. This investment raises several key questions: Will multi-cloud always be more benefic

Boyang Zhang, Zheng Li, Ziqing Yang, Xinlei He

While advanced machine learning (ML) models are deployed in numerous real-world applications, previous works demonstrate these models have security and privacy vulnerabilities. Various empirical research has been done in this field. However, most of the experiments are performed on target ML models trained by the security researchers themselves. Due to the h

Yue Guo, Zian Xu, Yi Yang

The emergence of Large Language Models (LLMs), such as ChatGPT, has revolutionized general natural language preprocessing (NLP) tasks. However, their expertise in the financial domain lacks a comprehensive evaluation. To assess the ability of LLMs to solve financial NLP tasks, we present FinLMEval, a framework for Financial Language Model Evaluation, compris

Cai Davies, Marc Roig Vilamala, Alun D. Preece, Federico Cerutti

This work reveals an evidential signal that emerges from the uncertainty value in Evidential Deep Learning (EDL). EDL is one example of a class of uncertainty-aware deep learning approaches designed to provide confidence (or epistemic uncertainty) about the current test sample. In particular for computer vision and bidirectional encoder large language models

Pedro Baptista, Ranyiliu Chen, Jędrzej Kaniewski, David Rasmussen Lolck

In this work we study the phenomenon of self-testing from the first principles, aiming to place this versatile concept on a rigorous mathematical footing. Self-testing allows a classical verifier to infer a quantum mechanical description of untrusted quantum devices that she interacts with in a black-box manner. Somewhat contrary to the black-box paradigm, e

J. M. Carmona, J. L. Cortés, M. A. Reyes

Modifications inspired by quantum gravity in the kinematics of special relativity can manifest in various ways, including anomalies in the time of flight of massless particles and the emergence of decay channels for otherwise stable particles. Typically, these effects are studied independently; however, it may be necessary to combine both to perform a consis

Abdullah Can Algan, Emre Yürekli, Aykut Çayır

One of the most important challenges for modern search engines is to retrieve relevant web content based on user queries. In order to achieve this challenge, search engines have a module to rewrite user queries. That is why modern web search engines utilize some statistical and neural models used in the natural language processing domain. Statistical machine

Rustem Takhanov, Maxat Tezekbayev, Artur Pak, Arman Bolatov

Classes of target functions containing a large number of approximately orthogonal elements are known to be hard to learn by the Statistical Query algorithms. Recently this classical fact re-emerged in a theory of gradient-based optimization of neural networks. In the novel framework, the hardness of a class is usually quantified by the variance of the gradie

Alexander Heinlein, Bjoern Kiefer, Stefan Prüger, Oliver Rheinbach

Sparse direct linear solvers are at the computational core of domain decomposition preconditioners and therefore have a strong impact on their performance. In this paper, we consider the Fast and Robust Overlapping Schwarz (FROSch) solver framework of the Trilinos software library, which contains a parallel implementations of the GDSW domain decomposition pr

Bruno Lourenço, Cátia Vaz, Miguel E. Coimbra, Alexandre P. Francisco

phyloDB is a modular and extensible framework for large-scale phylogenetic analyses, which are essential for understanding epidemics evolution. It relies on the Neo4j graph database for data storage and processing, providing a schema and an API for representing and querying phylogenetic data. Custom algorithms are also supported, allowing to perform heavy co

Zeinab Roostaie, Mohammad Gholami, Farzad Parvaresh

Spatially coupled low-density parity-check (SC-LDPC) codes are a class of capacity approaching LDPC codes with low message recovery latency when a sliding window decoding is used. In this paper, we first present a new method for the construction of a class of SC-LDPC codes by the incidence matrices of a given non-negative integer matrix $E$, and then the rel

S. Monir, E. N. Osika, S. K. Gorman, I. Thorvaldson

Phosphorus donor nuclear spins in silicon couple weakly to the environment making them promising candidates for high-fidelity qubits. The state of a donor nuclear spin qubit can be manipulated and read out using its hyperfine interaction with the electron confined by the donor potential. Here we use a master equation-based approach to investigate how the bac

Paul Krühner, Shijie Xu

We find explicit and optimal upper bounds for the expected occupation density for an It\^o-process when its drift and diffusion coefficients are unknown under boundedness and ellipticity conditions on the coefficients. This is related to the optimal bound for the expected interval occupation found in Ankirchner and Wendt(2021). In contrast, our bound is for

O. Fawwaz, H. Shams, F. Arneodo, A. Di Giovanni

In this work we present the characterization of a Broad Energy Germanium (BEGe) type High Purity Germanium (HPGe) detector, with a carbon fiber entrance window thickness of 0.6 mm and an active area of 6305 mm2, operated at shallow depth (~ 8m) in Abu Dhabi, UAE. A 1.6 keV Full Width Half Maximum (FWHM) was obtained for the 662 keV peak of 137Cs. A muon veto

Jinrong Liu, Liujun Xu, Gaole Dai, Gang Wang

Geometric phases in particle diffusion systems, an intriguing aspect enlightened from thermal systems, offer a different understanding beyond traditional Brownian motion and Fick's laws. This concept introduces a phase factor with significant implications for particle behavior, central to which is the non-Hermitian nature of the Hamiltonian in the diffusion

Martin Zach, Erich Kobler, Antonin Chambolle, Thomas Pock

In this work we tackle the problem of estimating the density $ f_X $ of a random variable $ X $ by successive smoothing, such that the smoothed random variable $ Y $ fulfills the diffusion partial differential equation $ (\partial_t - \Delta_1)f_Y(\,\cdot\,, t) = 0 $ with initial condition $ f_Y(\,\cdot\,, 0) = f_X $. We propose a product-of-experts-type mod

Pradeep Kumar, Bhaskar De, Rishabh Tripathi, Rohan Singh

Many-body interactions (MBIs) such as exciton-exciton interactions significantly affect the optical response of semiconductor nanostructures. These interactions can be rigorously modeled through microscopic calculations. However, these calculations can be computationally intensive and often lack physical insights. An alternative is to use phenomenological ma

Hang Su, Eric E Keaveny

The efficient simulation of fluid-structure interactions at zero Reynolds number requires the use of fast summation techniques in order to rapidly compute the long-ranged hydrodynamic interactions between the structures. One approach for periodic domains involves utilising a compact or exponentially decaying kernel function to spread the force on the structu

Tomoya Shiba, Akinobu Mizutani, Yuga Yano, Tomohiro Ono

This paper describes an overview of the techniques of Hibikino-Musashi@Home, which intends to participate in the domestic standard platform league. The team has developed a dataset generator for the training of a robot vision system and an open-source development environment running on a human support robot simulator. The robot system comprises self-develope

LHCb collaboration, R. Aaij, A. S. W. Abdelmotteleb, C. Abellan Beteta

Using a dataset corresponding to $9~\mathrm{fb}^{-1}$ of integrated luminosity collected with the LHCb detector between 2011 and 2018 in proton-proton collisions, the decay-time distributions of the decay modes $B_s^0 \rightarrow J/\psi \eta'$ and $B_s^0 \rightarrow J/\psi \pi^{+} \pi^{-}$ are studied. The decay-width difference between the light and heavy m

Belen Alastruey, Matthias Sperber, Christian Gollan, Dominic Telaar

Code-switching (CS), i.e. mixing different languages in a single sentence, is a common phenomenon in communication and can be challenging in many Natural Language Processing (NLP) settings. Previous studies on CS speech have shown promising results for end-to-end speech translation (ST), but have been limited to offline scenarios and to translation to one of

Yu. Skorov, J. Markkanen, V. Reshetnyk, S. Mottola

The standard approach to obtaining knowledge about the properties of the surface layer of a comet from observations of gas production consists of two stages. First, various thermophysical models are used to calculate gas production for a few sets of parameters. Second, a comparison of observations and theoretical predictions is performed. This approach is co

William Ndzimbong, Cyril Fourniol, Loic Themyr, Nicolas Thome

Inter-modal image registration (IMIR) and image segmentation with abdominal Ultrasound (US) data has many important clinical applications, including image-guided surgery, automatic organ measurement and robotic navigation. However, research is severely limited by the lack of public datasets. We propose TRUSTED (the Tridimensional Renal Ultra Sound TomodEnsit

Gayanath W. Fernando, Donal Sheets, Jason Hancock, Arthur Ernst

We investigate the halide perovskite TiF$_3$, renowned for its intricate interplay between structure, electronic correlations, magnetism, and thermal expansion. Despite its simple structure, understanding its low-temperature magnetic behavior has been a challenge. Previous theories proposed antiferromagnetic ordering. In contrast, experimental signatures for

Thomas Perrin

For the focusing cubic wave equation on a compact Riemannian manifold of dimension $3$, the dichotomy between global existence and blow-up for solutions starting below the energy of the ground state is known since the work of Payne and Sattinger. In the case of a damped equation, we prove that the dichotomy between global existence and blow-up still holds. I

David Kalaj

Let $K\ge 1$ and $p\in(1,2]$. We obtain asymptotically sharp constant $c(K,p)$, when $K\to 1$ in the inequality $$\|\Im f\|_{p}\le c(K,p)\|\Re(f)\|_p$$ where $f\in \mathbf{h}^p$ is a $K-$quasiregular harmonic mapping in the unit disk belonging to the Hardy space $\mathbf{h}^p$, under the conditions $\arg(f(0))\in (-\pi/(2p),\pi/(2p))$ and $f(\mathbb{D})\cap(

V. L. Martinez-Consentino, A. M. Cantizani, J. E. Amaro

This paper delves into the distribution of semi-inclusive events involving the emission of two nucleons in (anti) neutrino charged-current scattering. The analysis is conducted within the framework of relativistic mean field theory applied to nuclear matter. To quantify the likelihood of such semi-inclusive events occurring, we employ a relativistic model of

Gauthier Krizman, Tetiana Zakusylo, Lakshmi Sajeev, Mahdi Hajlaoui

Fast, reversible, and low-power manipulation of the spin texture is crucial for next generation spintronic devices like non-volatile bipolar memories, switchable spin current injectors or spin field effect transistors. Ferroelectric Rashba semiconductors (FERSC) are the ideal class of materials for the realization of such devices. Their ferroelectric charact

Yi Bin, Wenhao Shi, Bin Ji, Jipeng Zhang

Existing sentence ordering approaches generally employ encoder-decoder frameworks with the pointer net to recover the coherence by recurrently predicting each sentence step-by-step. Such an autoregressive manner only leverages unilateral dependencies during decoding and cannot fully explore the semantic dependency between sentences for ordering. To overcome

Dominic J. P. Koyroytsaltis-McQuire, Rahul Kumar, Tamas Javorfi, Giuliano Siligardi

Chiral materials display a property called optical activity, which is the capability to interact differentially with left and right circularly polarised light. This leads to the ability to manipulate the polarisation state of light, which has a broad range of applications spanning from energy efficient displays to quantum technologies. Both synthesised and e

Hanna Abi Akl

The Scholarly Question Answering over Linked Data (Scholarly QALD) at The International Semantic Web Conference (ISWC) 2023 challenge presents two sub-tasks to tackle question answering (QA) over knowledge graphs (KGs). We answer the KGQA over DBLP (DBLP-QUAD) task by proposing a neuro-symbolic (NS) framework based on PSYCHIC, an extractive QA model capable

Bartłomiej Pawelski, Andrzej Szepietowski

Let $D_n$ denote the set of monotone Boolean functions with $n$ variables. Elements of $D_n$ can be represented as strings of bits of length $2^n$. Two elements of $D_0$ are represented as 0 and 1 and any element $g\in D_n$, with $n>0$, is represented as a concatenation $g_0\cdot g_1$, where $g_0, g_1\in D_{n-1}$ and $g_0\le g_1$. For each $x\in D_n$, we hav

A. Anitra, D. Mata Sanchez, T. Munoz-Darias, T. Di Salvo

Swift J1357.2-0933 is a transient low-mass X-ray binary hosting a stellar-mass black hole. The source exhibits optical dips and very broad emission lines during both outburst and quiescence, which are thought to be the result of a high orbital inclination. We present phase-resolved spectroscopy obtained with the 10.4m Gran Telescopio Canarias (GTC). The spec

Justin Plogmann, Oliver Brenner, Patrick Jenny

Data assimilation (DA) plays a crucial role in extracting valuable information from flow measurements in fluid dynamics problems. Often only time-averaged data is available, which poses challenges for DA in the context of unsteady flow problems. Recent works have shown promising results in optimizing Reynolds-averaged Navier-Stokes (RANS) simulations of stat

S. Schneidewind, J. Schürmann, A. Lokhov, C. Weinheimer

The KArlsruhe TRItium Neutrino experiment (KATRIN) aims to determine the effective mass of the electron antineutrino via a high-precision measurement of the tritium beta-decay spectrum in its end-point region. The target neutrino-mass sensitivity of 0.2 eV / c^2 at 90% C.L. can only be achieved in the case of high statistics and a good control of the systema

Ziyi Yang, Yanzhen Chen, Xinyu Gao, Yazhen Yuan

Implicit neural representation has opened up new possibilities for inverse rendering. However, existing implicit neural inverse rendering methods struggle to handle strongly illuminated scenes with significant shadows and indirect illumination. The existence of shadows and reflections can lead to an inaccurate understanding of scene geometry, making precise

Ritu Nehra, Dibyendu Roy

Composite topological phases with intriguing topology like M${\"o}$bius strips emerge in sublattice symmetric non-Hermitian systems due to spontaneous breaking of time-reversal symmetry at some parameter regime. While these phases have been characterized by nonadiabatic complex geometric phases of multiple participating complex bands, the physical properties

Illia Horenko

Simply-verifiable mathematical conditions for existence, uniqueness and explicit analytical computation of minimal adversarial paths (MAP) and minimal adversarial distances (MAD) for (locally) uniquely-invertible classifiers, for generalized linear models (GLM), and for entropic AI (EAI) are formulated and proven. Practical computation of MAP and MAD, their

Yannik Hahn, Robert Maack, Guido Buchholz, Marion Purrio

The digitization of manufacturing processes enables promising applications for machine learning-assisted quality assurance. A widely used manufacturing process that can strongly benefit from data-driven solutions is gas metal arc welding (GMAW). The welding process is characterized by complex cause-effect relationships between material properties, process co

Dimitrios Bachtis

We propose inverse renormalization group transformations to construct approximate configurations for lattice volumes that have not yet been accessed by supercomputers or large-scale simulations in the study of spin glasses. Specifically, starting from lattices of volume $V=8^{3}$ in the case of the three-dimensional Edwards-Anderson model we employ machine l

Zeynep Hilal Kilimci, Mustafa Yalcin, Ayhan Kucukmanisa, Amit Kumar Mishra

Heart disease, also known as cardiovascular disease, is a prevalent and critical medical condition characterized by the impairment of the heart and blood vessels, leading to various complications such as coronary artery disease, heart failure, and myocardial infarction. The timely and accurate detection of heart disease is of paramount importance in clinical

Ryotaro Mitsuboshi, Kohei Hatano, Eiji Takimoto

Metarounding is an approach to convert an approximation algorithm for linear optimization over some combinatorial classes to an online linear optimization algorithm for the same class. We propose a new metarounding algorithm under a natural assumption that a relax-based approximation algorithm exists for the combinatorial class. Our algorithm is much more ef

Ming-Yue Liu, Shu-Min Zhao, Song Gao, Xing-Yu Han

In the present study, we investigate the decays of the top quark $t\rightarrow c\gamma$, $t\rightarrow cg$, $t\rightarrow cZ$ and $t\rightarrow ch$. They are extremely rare processes in the Standard Model (SM). As the $U(1)$ extension of the minimal supersymmetric standard model (MSSM), the $U(1)_X$SSM features new superfields such as the right-handed neutri

Kai-Fan Ye, Qiang Wang, Jia-Hao Shi, Zhi-Ying Qin

In this work we investigate the $J/\psi$ production in proton-proton collisions at the center-of-mass energy ($\sqrt{s}$) equal to 2.76, 5.02, 7, 8 and 13 TeV with a parton and hadron cascade model PACIAE 2.2a. It is based on PYTHIA but extended considering the partonic and hadronic rescatterings before and after hadronization, respectively. In the PYTHIA se

Xiao Wang, Dieter Jaksch, Frank Schlawin

We study cavity-mediated interactions that are generated in a two-dimensional two-band Hubbard model coupled to an optical cavity, when it is driven in-gap by a strong laser. Starting from a Floquet description of the driven system, we derive effective low-energy Hamiltonians by projecting out the high-energy degrees of freedom and treating intrinsic interac

Paolo Bonicatto, Gennaro Ciampa, Gianluca Crippa

The goal of this paper is to study weak solutions of the Fokker-Planck equation. We first discuss existence and uniqueness of weak solutions in an irregular context, providing a unified treatment of the available literature along with some extensions. Then, we prove a regularity result for distributional solutions under suitable integrability assumptions, re

Arunava Das, Pinaki Dutta, Vishwanath Shukla

We construct a formally time-reversible, one-dimensional forced Burgers equation by imposing a global constraint of energy conservation, wherein the constant viscosity is modified to a fluctuating state-dependent dissipation coefficient. The system exhibits dynamical properties which bear strong similarities with those observed for the Burgers equation and c

Antonino de Martino, Stefano Pinton, Peter Schlosser

The aim of this paper is to introduce the $H^\infty$-functional calculus for harmonic functions over the quaternions. More precisely, we give meaning to Df(T) for unbounded sectorial operators T and polynomially growing functions of the form Df, where f is a slice hyperholomorphic function and $D=\partial_{q_0}+e_1\partial_{q_1}+e_2\partial_{q_2}+e_3\partial

Xianzhi Zhang, Linchang Xiao, Yipeng Zhou, Miao Hu

As users conveniently stream their favorite online videos, video request records are automatically stored by video content providers, which have a high chance of privacy leakage. Unfortunately, most existing privacy-enhancing approaches are not applicable for protecting user privacy in video requests, because they cannot be easily altered or distorted by use

Abolfazl Tarizadeh

In the literature, there is no known general method (formula) to compute the Zariski closure of an ``infinite'' subset of the prime spectrum. This problem indeed deals with the prime ideals of an infinite direct product of nonzero commutative rings that are very complicated to understand (the structure of most of them is unknown). In this article, by appeali

Yue Guo, Chenxi Hu, Yi Yang

Temporal data distribution shift is prevalent in the financial text. How can a financial sentiment analysis system be trained in a volatile market environment that can accurately infer sentiment and be robust to temporal data distribution shifts? In this paper, we conduct an empirical study on the financial sentiment analysis system under temporal data distr

Thomas Reichenbach, Severin Sylla, Leonhard Mayrhofer, Pedro Antonio Romero

We present a non-reactive force field for molecular dynamics simulations of interfaces between passivated amorphous surfaces and their interaction with water. The force field enables large-scale dynamic simulations of dry and lubricated tribological contacts and is tailored to surfaces with hydrogen, hydroxyl and aromatic surface passivation. To favour its c

Éloi Descamps, Arne Keller, Pérola Milman

GKP states, introduced by Gottesman, Kitaev, and Preskill, are continuous variable logical qubits that can be corrected for errors caused by phase space displacements. Their experimental realization is challenging, in particular using propagating fields, where quantum information is encoded in the quadratures of the electromagnetic field. However, travelling

Jonah Heiler, Jonathan Körber, Erik Hesselmeier, Pierre Kuna

Colour centres in silicon carbide emerge as a promising semiconductor quantum technology platform with excellent spin-optical coherences.However, recent efforts towards maximising the photonic efficiency via integration into nanophotonic structures proved to be challenging due to reduced spectral stabilities. Here, we provide a large-scale systematic investi

Sidi Wu, Yizi Chen, Konrad Schindler, Lorenz Hurni

Historical maps provide useful spatio-temporal information on the Earth's surface before modern earth observation techniques came into being. To extract information from maps, neural networks, which gain wide popularity in recent years, have replaced hand-crafted map processing methods and tedious manual labor. However, aleatoric uncertainty, known as data-d

Hugo Rincon Galeana, Ulrich Schmid

Whereas distributed computing research has been very successful in exploring the solvability/impossibility border of distributed computing problems like consensus in representative classes of computing models with respect to model parameters like failure bounds, this is not the case for characterizing necessary and sufficient communication requirements. In t

MEG II collaboration, K. Afanaciev, A. M. Baldini, S. Ban

The MEG II experiment, based at the Paul Scherrer Institut in Switzerland, reports the result of a search for the decay $\mu^+\to e^+\gamma$ from data taken in the first physics run in 2021. No excess of events over the expected background is observed, yielding an upper limit on the branching ratio of B($\mu^+\to e^+\gamma$) < $7.5 \times 10^{-13}$ (90% C.L.

Javier Esparza, Rubén Rubio, Salomon Sickert

In the mid 80s, Lichtenstein, Pnueli, and Zuck proved a classical theorem stating that every formula of Past LTL (the extension of LTL with past operators) is equivalent to a formula of the form $\bigwedge_{i=1}^n \mathbf{G}\mathbf{F}\, \varphi_i \vee \mathbf{F}\mathbf{G}\, \psi_i $, where $\varphi_i$ and $\psi_i$ contain only past operators. Some years late

Ioannis Nasios, Konstantinos Vogklis

In this paper we tackle the problem of point and probabilistic forecasting by describing a blending methodology of machine learning models that belong to gradient boosted trees and neural networks families. These principles were successfully applied in the recent M5 Competition on both Accuracy and Uncertainty tracks. The keypoints of our methodology are: a)

Lorenzo Giambagli, Lorenzo Buffoni, Lorenzo Chicchi, Duccio Fanelli

In theoretical ML, the teacher-student paradigm is often employed as an effective metaphor for real-life tuition. The above scheme proves particularly relevant when the student network is overparameterized as compared to the teacher network. Under these operating conditions, it is tempting to speculate that the student ability to handle the given task could

Abhijith Chintam, Rahel Beloch, Willem Zuidema, Michael Hanna

Language models (LMs) exhibit and amplify many types of undesirable biases learned from the training data, including gender bias. However, we lack tools for effectively and efficiently changing this behavior without hurting general language modeling performance. In this paper, we study three methods for identifying causal relations between LM components and

Francisco Peña-Benítez, Patricio Salgado-Rebolledo

We show that the fractonic dipole-conserving algebra can be obtained as an Aristotelian (and pseudo-Carrollian) contraction of the Poincar\'e algebra in one dimension higher. Such contraction allows to obtain fracton electrodynamics from a relativistic higher-dimensional theory upon dimensional reduction. The contraction procedure produces several scenarios

Junwoo Chang, Hyunwoo Ryu, Jiwoo Kim, Soochul Yoo

Diffusion models have risen as a powerful tool in robotics due to their flexibility and multi-modality. While some of these methods effectively address complex problems, they often depend heavily on inference-time obstacle detection and require additional equipment. Addressing these challenges, we present a method that, during inference time, simultaneously

Daiver Cardona-Salgado, Yves Dumont, Olga Vasilieva

We study the impact of pheromone control against the Asian citrus psyllid, Diaphorina citri, a principal vector of diseases in citrus cultures. The model is expressed as a piecewise smooth ODE system, and its long-term behavior is analyzed. In particular, through qualitative analysis and applying an open-loop control approach, we identify the threshold in te

Ludwig Frank

In this paper we introduce and investigate moment generating Stirling numbers of the first kind, "`MSN1"'. They are inverses of MSN2's, which make the representation of the moments for a lot of statistical distributions in closed formulas possible. Both MSN1's and MSN2's are related to the r-Stirling numbers, and extend their properties to any real third par

Christoph Tries, Fabian Hofmann, Tom Brown

In wind- and solar-dominated energy systems it has been assumed that there are synergies between producing electricity and electrolytic hydrogen since electrolysis can use excess electricity that would otherwise be curtailed. However, it remains unclear whether these synergies hold true at higher levels of hydrogen demand and how they compare with benefits o

Guillaume Gbikpi-Benissan, Frédéric Magoulès

Recently, asynchronous coarse-space correction has been achieved within both the overlapping Schwarz and the primal Schur frameworks. Both additive and multiplicative corrections have been discussed. In this paper, we address some implementation drawbacks of the proposed additive correction scheme. In the existing approach, each coarse solution is applied on

Eunhee Jeong, Sanghyuk Lee, Jaehyeon Ryu

We study the Bochner-Riesz problem for the twisted Laplacian $\mathcal L$ on $\mathbb R^2$. For $p\in [1, \infty]\setminus\{2\}$, it has been conjectured that the Bochner-Riesz means $S_\lambda^\delta(\mathcal L) f$ of order $\delta$ converges in $L^p$ for every $f\in L^p$ if and only if $\delta> \max(0,|(p-2)/p|-1/2)$. We prove the conjecture by obtaining u

Younguk Song, Jonginn Yun, Jehyun Kim, Wonjin Jang

Engineered spin-electric coupling enables spin qubits in semiconductor nanostructures to be manipulated efficiently and addressed individually. While synthetic spin-orbit coupling using a micromagnet is widely used for driving qubits based on single spins in silicon, corresponding demonstration for encoded spin qubits is so far limited to natural silicon. He

R. M. Khakimov, M. T. Makhammadaliev

In this paper, we study the Hard Core (HC) model with a countable set $\mathbb Z$ of spin values on a Cayley tree of order $k=2$. This model is defined by a countable set of parameters (that is, the activity function $\lambda_i>0$, $i\in \mathbb Z$). A functional equation is obtained that provides the consistency condition for finite-dimensional Gibbs distri

Kouichi Okunishi, Tadashi Takayanagi

The Bethe lattice Ising model -- a classical model of statistical mechanics for the phase transition -- provides a novel and intuitive understanding of the prototypical relationship between tensor networks and Anti-de Sitter (AdS)/conformal field theory (CFT) correspondence. After analytically formulating a holographic renormalization group for the Bethe lat

Hussain Alasmawi, Leanne Bricker, Mohammad Yaqub

Ultrasound is the primary imaging modality in clinical practice during pregnancy. More than 140M fetuses are born yearly, resulting in numerous scans. The availability of a large volume of fetal ultrasound scans presents the opportunity to train robust machine learning models. However, the abundance of scans also has its challenges, as manual labeling of eac

Frederik Rautenberg, Michael Kuhlmann, Jana Wiechmann, Fritz Seebauer

Unsupervised speech disentanglement aims at separating fast varying from slowly varying components of a speech signal. In this contribution, we take a closer look at the embedding vector representing the slowly varying signal components, commonly named the speaker embedding vector. We ask, which properties of a speaker's voice are captured and investigate to

Yun Peng, Ruida Hu, Ruoke Wang, Cuiyun Gao

Python is widely used in the open-source community, largely owing to the extensive support from diverse third-party libraries within the PyPI ecosystem. Nevertheless, the utilization of third-party libraries can potentially lead to conflicts in dependencies, prompting researchers to develop dependency conflict detectors. Moreover, endeavors have been made to

Jiaogen Zhang

The quaternionic Calabi conjecture, posed by Alesker and Verbitsky \cite{Alesker-Verbitsky (2010)}, predicts that the quaternionic Monge-Amp\`ere equation can always be solved on any compact HKT manifold. Motivated by this conjecture, we will introduce a quaternionic version of the Gauduchon conjecture on any compact $SL(n,\mathbb{H})$-manifold, specifically

Nicholas Rungi, Andrea Tamburelli

We study the moduli space of flat maximal space-like embeddings in $\mathbb{H}^{2,2}$ from various aspects. We first describe the associated Codazzi tensors to the embedding in the general setting, and then, we introduce a family of pseudo-K\"ahler metrics on the moduli space. We show the existence of two Hamiltonian actions with associated moment maps and u

Sophie Wharrie, Lisa Eick, Lotta Mäkinen, Andrea Ganna

Machine learning strategies like multi-task learning, meta-learning, and transfer learning enable efficient adaptation of machine learning models to specific applications in healthcare, such as prediction of various diseases, by leveraging generalizable knowledge across large datasets and multiple domains. In particular, Bayesian meta-learning methods pool d

Mohammadreza Doostmohammadian, Houman Zarrabi, Azam Doustmohammadian, Hamid R. Rabiee

Understanding the impact of network clustering and small-world properties on epidemic spread can be crucial in developing effective strategies for managing and controlling infectious diseases. Particularly in this work, we study the impact of these network features on targeted intervention (e.g., self-isolation and quarantine). The targeted individuals for s

Raquel Molina, Chu-Wen Xiao, Wei-Hong Liang, Eulogio Oset

The $N^*(1535)$ can be dynamically generated in the chiral unitary approach with the coupled channels, $K^0 \Sigma^+, K^+ \Sigma^0, K^+ \Lambda$ and $\eta p$. In this work we evaluate the correlation functions for every channel and face the inverse problem. Assuming the correlation functions to correspond to real measurements, we conduct a fit to the data wi

R. N. Soguel, S. Fritzsche

Relying on the redefined vacuum state approach, and based on one-particle three-loop Feynman diagrams, partial third-order interelectronic corrections to the valence electron energy shift are investigated in Li-like ions. The idea is to begin with simple one-particle gauge-invariant subsets composed of Feynman diagrams and to keep track of them in the many-e

Shilpa Jangid, Hiroshi Okada

We consider the Type-II seesaw model extended with another Higgs doublet, which is odd under the $Z_2$ symmetry. We look for the possibility of triggering the electroweak symmetry breaking via radiative effects. The Higgs mass parameter changes sign from being positive at higher energy scales to negative at lower energy scales in the presence of the TeV scal

Mariia Zameshina, Marlene Careil, Olivier Teytaud, Laurent Najman

Classical techniques for protecting facial image privacy typically fall into two categories: data-poisoning methods, exemplified by Fawkes, which introduce subtle perturbations to images, or anonymization methods that generate images resembling the original only in several characteristics, such as gender, ethnicity, or facial expression.In this study, we int