May 2024 arXiv papers — page 121

Tatsuya Horiguchi, Mikiya Masuda, Takashi Sato, John Shareshian

We determine that $\gamma$-vectors of partitioned permutohedra, thereby generalizing a result of Foata and Sch\"utzenberger. Our result is closely related to a result of Athanasiadis on the representation of the symmetric group on the cohomology of the permutohedral variety. We explain how to derive Athanasiadis' result from ours and vice versa.

Emmanouil Karystinaios, Francesco Foscarin, Gerhard Widmer

In this work, we present Score MUsic Graph (SMUG)-Explain, a framework for generating and visualizing explanations of graph neural networks applied to arbitrary prediction tasks on musical scores. Our system allows the user to visualize the contribution of input notes (and note features) to the network output, directly in the context of the musical score. We

Toru Nishimura, Masakiyo Kitazawa, Teiji Kunihiro

We explore how the electric conductivity and associated relaxation time are modified near the QCD critical point and the phase transition to a color superconducting phase using the two-flavor Nambu-Jona-Lasinio model with finite current quark masses. We give a comprehensive account of the nature of the soft modes associated with these phase transitions and h

Nicholas Orlofsky

Macroscopic dark matter like nontopological solitons can form either via the fusion and accumulation of free particles or during cosmological phase transitions. Both mechanisms can create dark matter with large masses ranging from TeV to solar mass. This can lead to interesting targets in direct detection, astrophysical, and cosmological searches.

Ting Lin

Understanding the origin of transverse single-spin asymmetries is a long-standing challenge in strong interaction physics. Recent precise measurements of the azimuthal distribution of charged pions in jets from STAR have shed new light on the spin momentum correlations within the Transverse Momentum Dependent (TMD) formalism. This measurement, particularly s

Katrin Ros, Anders Johansen

During their formation, nascent planetary systems are subject to FU Orionis outbursts that heat a substantial part of the disc. This causes water ice in the affected part of the disc to sublimate as the ice line moves outwards to several to tens of astronomical units. In this paper, we investigate how the subsequent cooling of the disc impacts the particle s

Wazib Ansar, Saptarsi Goswami, Amlan Chakrabarti

The emergence of Transformer-based Large Language Models (LLMs) has substantially augmented the capabilities of Natural Language Processing (NLP), thereby intensifying the demand for computational resources. Therefore, enhancing efficiency based on factors like computational requirements, energy consumption, carbon footprint and financial cost has become a v

François Doré, Kévin Perrot, Antonio E. Porreca, Sara Riva

Finite discrete-time dynamical systems (FDDS) model phenomena that evolve deterministically in discrete time. It is possible to define sum and product operations on these systems (disjoint union and direct product, respectively) giving a commutative semiring. This algebraic structure led to several works employing polynomial equations to model hypotheses on

Petter Hofverberg, Jean-Marc Bergerot, Jean-Michel Bruneau, Richard Trimaud

MEDICYC (MEDical CYClotron) is an isochronous cyclotron dedicated to radiotherapy which was built and commissioned in Nice, France, in 1990 by a local team aided by experts from CERN. The cyclotron accelerates negative H to a maximum energy of 65 MeV and uses stripping to extract a proton beam. Its primary purpose is treating ocular melanoma by protontherapy

Weixuan Chen, Shunpu Tang, Qianqian Yang

Semantic communication (SemCom) enhances transmission efficiency by sending only task-relevant information compared to traditional methods. However, transmitting semantic-rich data over insecure or public channels poses security and privacy risks. This paper addresses the privacy problem of transmitting images over wiretap channels and proposes a novel SemCo

Jiaee Cheong, Micol Spitale, Hatice Gunes

In recent years, the affective computing (AC) and human-robot interaction (HRI) research communities have put fairness at the centre of their research agenda. However, none of the existing work has addressed the problem of machine learning (ML) bias in HRI settings. In addition, many of the current datasets for AC and HRI are "small", making ML bias and debi

F. Bouyghf, M. El Guide, A. El Ichi

In the present paper, we introduce new tensor krylov subspace methods for solving large Sylvester tensor equations. The proposed method uses the well-known T-product for tensors and tensor subspaces. We introduce some new tensor products and the related algebraic properties. These new products will enable us to develop third-order the tensor FOM (tFOM), GMRE

Erdenebayar Bayarmagnai, Fatemeh Mohammadi, Rémi Prébet

Loop invariants are properties of a program loop that hold before and after each iteration of the loop. They are often employed to verify programs and ensure that algorithms consistently produce correct results during execution. Consequently, the generation of invariants becomes a crucial task for loops. We specifically focus on polynomial loops, where both

Qi Jia, Baoyu Fan, Cong Xu, Lu Liu

Existing video multi-modal sentiment analysis mainly focuses on the sentiment expression of people within the video, yet often neglects the induced sentiment of viewers while watching the videos. Induced sentiment of viewers is essential for inferring the public response to videos, has broad application in analyzing public societal sentiment, effectiveness o

Fayadh Kadhem

This study aims to shed light on new (sub)classes of matroids originating from cluster algebras and investigate their properties. We focus on what we call cluster matroids and build some results on them. Then, we point out a relationship between these kinds of matroids and uniform matroids and study their minors.

Johanna Ansohn McDougall, Alessandro Brighente, Anne Kunstmann, Niklas Zapatka

Abstract. Since the introduction of active discovery in Wi-Fi networks, users can be tracked via their probe requests. Although manufacturers typically try to conceal Media Access Control (MAC) addresses using MAC address randomisation, probe requests still contain Information Elements (IEs) that facilitate device identification. This paper introduces generi

Yu. A. Lashko, V. S. Vasilevsky, V. I. Zhaba

We determine cross sections and astrophysical S-factors of the reactions generated in collisions between $^{6}$Li and $^{3}$H, and $^{6}$Li and $^{3}$He. A microscopic three-cluster model is employed to study the dynamics of reactions occurring in the mirror nuclei $^{9}$Be and $^{9}$B. In a previous study [Phys. Rev. C {\bf 109}, 045803 (2024)], this model

Pranab Sahoo, Prabhash Meharia, Akash Ghosh, Sriparna Saha

The rapid advancement of foundation models (FMs) across language, image, audio, and video domains has shown remarkable capabilities in diverse tasks. However, the proliferation of FMs brings forth a critical challenge: the potential to generate hallucinated outputs, particularly in high-stakes applications. The tendency of foundation models to produce halluc

N. N. Achasov, G. N. Shestakov

The rates of the $X(3872)\to\pi^0\pi^0\chi_{c1}$ and $X(3872)\to \pi^+\pi^-\chi_{c1}$ decays are estimated in the model of the triangle loop diagrams with charmed $D^*\bar DD$ and $\bar D^*D\bar D$ mesons in the loops. There are the triangle logarithmic singularities in the physical region of the $X(3872)\to\pi^0\pi^0 \chi_{c1}$ decay which manifest themselv

Xiang-Long Peng, Bai-Xiang Xu

The ionic conductivity at the grain boundaries (GBs) in oxide ceramics is typically several orders of magnitude lower than that within the grain interior. This detrimental GB effect is the main bottleneck for designing high-performance ceramic electrolytes intended for use in solid-state Lithium-ion batteries, fuel cells, and electrolyzer cells. The macrosco

Wen-Tao Lyu, Sheng-Chao Zhang, Guan-Ying Wang, Jia-Jun Wu

Motivated by the Belle measurements of the process $\Lambda_c^+\to \eta\pi^+\Lambda$, we investigate this process by considering the contributions from the $\Lambda(1670)$, $a_0(980)$, and $\Sigma(1385)$. In addition, we also consider the predicted low-lying baryon $\Sigma^*(1/2^-)$. Our results involving the $\Sigma^*(1/2^-)$ are favored by fitting to the B

Jialiang Tang, Ruoqian Xu, Yongcheng Ding, Xusheng Xu

Exploring the ground state properties of many-body quantum systems conventionally involves adiabatic processes, alongside exact diagonalization, in the context of quantum annealing or adiabatic quantum computation. Shortcuts to adiabaticity by counter-diabatic driving serve to accelerate these processes by suppressing energy excitations. Motivated by this, w

Emmanouil Karystinaios, Francesco Foscarin, Gerhard Widmer

We propose a new graph convolutional block, called MusGConv, specifically designed for the efficient processing of musical score data and motivated by general perceptual principles. It focuses on two fundamental dimensions of music, pitch and rhythm, and considers both relative and absolute representations of these components. We evaluate our approach on fou

Qiyu Wu, Masaaki Nagata, Zhongtao Miao, Yoshimasa Tsuruoka

The problem of hallucination and omission, a long-standing problem in machine translation (MT), is more pronounced when a large language model (LLM) is used in MT because an LLM itself is susceptible to these phenomena. In this work, we mitigate the problem in an LLM-based MT model by guiding it to better word alignment. We first study the correlation betwee

Daan Delabie, Thomas Wilding, Liesbet Van der Perre, Lieven De Strycker

Indoor positioning applications are craving for ever higher precision and accuracy across the entire coverage zone. Optimal anchor placement and the deployment of multiple distributed anchor nodes could have a major impact in this regard. This paper examines the influences of these two difficult to approach hypotheses by means of a straightforward ultrasonic

Josh McGiff, Nikola S. Nikolov

Our study addresses a significant gap in online hate speech detection research by focusing on homophobia, an area often neglected in sentiment analysis research. Utilising advanced sentiment analysis models, particularly BERT, and traditional machine learning methods, we developed a nuanced approach to identify homophobic content on X/Twitter. This research

Siwei Wang, Yifei Shen, Shi Feng, Haoran Sun

Planning is a crucial element of both human intelligence and contemporary large language models (LLMs). In this paper, we initiate a theoretical investigation into the emergence of planning capabilities in Transformer-based LLMs via their next-word prediction mechanisms. We model planning as a network path-finding task, where the objective is to generate a v

Sharon Mitrani, Ehud Behar, Jeremy J. Drake, Marina Orio

The origin of bright X-ray emission lines that appear late in a nova eruption remains largely a puzzle. We present two high-resolution X-ray grating spectra of the classical nova YZ Ret, observed 77 and 115 days post-eruption, using XMM-Newton and Chandra , respectively. Both spectra feature resolved emission lines blueshifted by $v = -1500$ km s$^{-1}$ and

Roberto D'Onofrio, Giovanni Ortenzi, Ian Roulstone

Chynoweth and Sewell proposed a mathematical model for an atmospheric front based on the singularities of the Legendre transformation between different pairs of dual variables. Drawing inspiration from their work, we formalize the idea of a Chynoweth-Sewell front and illuminate its geometrical meaning from the viewpoint of Monge-Ampere geometry. This extends

Xiangjian Qian, Jiale Huang, Mingpu Qin

Density Matrix Renormalization Group (DMRG) or Matrix Product States (MPS) are widely acknowledged as highly effective and accurate methods for solving one-dimensional quantum many-body systems. However, the direct application of DMRG to the study two-dimensional systems encounters challenges due to the limited entanglement encoded in the wave-function ansat

Wanting Xu, Yang Liu, Langping He, Xucheng Huang

We introduce Xmodel-VLM, a cutting-edge multimodal vision language model. It is designed for efficient deployment on consumer GPU servers. Our work directly confronts a pivotal industry issue by grappling with the prohibitive service costs that hinder the broad adoption of large-scale multimodal systems. Through rigorous training, we have developed a 1B-scal

Mirjam Trieb, Moritz Weber, Dean Zenner

We give a definition of hypergraph C*-algebras. These generalize the well-known graph C*-algebras as well as ultragraph C*-algebras. In contrast to those objects, hypergraph C*-algebras are not always nuclear. We provide a number of non-nuclear examples, we prove a Gauge-Invariant Uniqueness Theorem for a subclass of hypergraph C*-algebras and we study moves

Stefan Wallentowitz, Bastian Kersting, Dan Mihai Dumitriu

Application virtual machines provide strong isolation properties and are established in the context of software portability. Those opportunities make them interesting for scalable and secure IoT deployments. WebAssembly is an application virtual machine with origins in web browsers, that is getting rapidly adopted in other domains. The strong and steadily gr

Yifan Liu, You Wang, Guang Li

Model Predictive Control (MPC)-based trajectory planning has been widely used in robotics, and incorporating Control Barrier Function (CBF) constraints into MPC can greatly improve its obstacle avoidance efficiency. Unfortunately, traditional optimizers are resource-consuming and slow to solve such non-convex constrained optimization problems (COPs) while le

V. Y. Monarkha, S. Simbierowicz, M. Borrelli, R. van Gulik

We report a comparative study on microwave control lines for a transmon qubit using: (i) flexible stripline transmission lines, and (ii) semi-rigid coaxial cables. During each experiment we performed repeated measurements of the energy relaxation and coherence times of a transmon qubit using one of the wiring configurations. Each measurement run spanned 70 h

Helge Øystein Maakestad

Let $A$ be any commutative unital ring and let $\operatorname{GL}_{2,A}$ be the general linear group scheme on $A$ of rank $2$. We study the representation theory of $\operatorname{GL}_{2,A}$ and the symmetric powers $\operatorname{Sym}^d(V)$, where $(V, \Delta)$ is the standard right comodule on $\operatorname{GL}_{2,A}$. We prove a refined Weyl character f

Dimitrios S. Karachalios, Hossam S. Abbas

This study utilized the Gaussian Processes (GPs) regression framework to establish stochastic error bounds between the actual and predicted state evolution of nonlinear systems. These systems are embedded in the linear parameter-varying (LPV) formulation and controlled using model predictive control (MPC). Our main focus is quantifying the uncertainty of the

Benjamin Camus, Théo Voillemin, Corentin Le Barbu, Jean-Christophe Louvigné

In this work, we propose to tackle several challenges hindering the development of Automatic Target Detection (ATD) algorithms for ground targets in SAR images. To address the lack of representative training data, we propose a Deep Learning approach to train ATD models with synthetic target signatures produced with the MOCEM simulator. We define an incrustat

Marcin Radom, Piotr Formanowicz

In many complex systems that can be modeled using Petri nets time can be a very important factor which should be taken into account during creation and analysis of the model. Time data can describe starting moments of some actions or their duration before their immediate effects start to influence some other areas of the modeled system. Places in a Petri net

Kaiwei Liu, Bing Yuan, Jiang Zhang

After coarse-graining a complex system, the dynamics of its macro-state may exhibit more pronounced causal effects than those of its micro-state. This phenomenon, known as causal emergence, is quantified by the indicator of effective information. However, two challenges confront this theory: the absence of well-developed frameworks in continuous stochastic d

Aris Daniilidis, Robert Deville, Sebastian Tapia-Garcia

We construct a differentiable locally Lipschitz function $f$ in $\mathbb{R}^{N}$ with the property that for every convex body $K\subset \mathbb{R}^N$ there exists $\bar x \in \mathbb{R}^N$ such that $K$ coincides with the set $\partial_L f(\bar x)$ of limits of derivatives $\{Df(x_n)\}_{n\geq 1}$ of sequences $\{x_n\}_{n\geq 1}$ converging to~$\bar x$. The t

Ismael Castell-Uroz, Pere Barlet-Ros

Online privacy has become increasingly important in recent years. While third-party cookies have been widely used for years, they have also been criticized for their potential impact on user privacy. They can be used by advertisers to track users across multiple sites, allowing them to build detailed profiles of their behavior and interests. However, nowaday

Daniel M. Bot, Jan Aerts

Dimensionality reduction algorithms are often used to visualise high-dimensional data. Previously, studies have used prior information to enhance or suppress expected patterns in projections. In this paper, we adapt such techniques for domain knowledge guided interactive exploration. Inspired by Mapper and STAD, we present three types of lens functions for U

Weiyi Pan, Zhiming Xu

Antiferromagnetic (AFM) skyrmions, which are resistant to both the skyrmion Hall effect and external magnetic perturbations, are expected to be promising candidates for next-generation spintronics devices. Despite being observed in bulk materials and synthetic AFM layered systems, the existence of intrinsic AFM skyrmions within single magnetic layers, which

Shikun Feng, Yuyan Ni, Minghao Li, Yanwen Huang

Recently, a noticeable trend has emerged in developing pre-trained foundation models in the domains of CV and NLP. However, for molecular pre-training, there lacks a universal model capable of effectively applying to various categories of molecular tasks, since existing prevalent pre-training methods exhibit effectiveness for specific types of downstream tas

M. Fabbrichesi, L. Marzola

The Future Circular Collider (FCC) -- in its first incarnation as a lepton collider -- will produce, according to the proposed design, more than 100 billion pairs of $\tau$ leptons after working for four years at the energy of the $Z$-boson resonance. The $\tau$ lepton is special because its relatively long lifetime makes it possible to reconstruct the momen

Yu-Wen Huang, Christian Prehofer, William Lindskog, Ron Puts

This paper addresses the problem of predicting the energy consumption for the drivers of Battery electric vehicles (BEVs). Several external factors (e.g., weather) are shown to have huge impacts on the energy consumption of a vehicle besides the vehicle or powertrain dynamics. Thus, it is challenging to take all of those influencing variables into considerat

Taoyu Song, Enyu Shi, Yu Lu, Yiyang Zhu

In this paper, we investigate a reconfigurable intelligent surface (RIS)-aided multiple-input single-output (MISO) system in the presence of electromagnetic interference (EMI) and channel aging with a Rician fading channel model between the base station (BS) and user equipment (UE). Specifically, we derive the closed-form expression for downlink spectral eff

Mátyás Szücs, Carmelo Filippo Munafo, Róbert Kovács

Among the numerous heat conduction models, the Guyer--Krumhansl equation has a special role. Besides its various application possibilities in nanotechnology, cryotechnology, and even in case of modeling heterogeneous materials, it poses additional mathematical challenges compared to the Fourier or Cattaneo {(a.k.a. Maxwell--Cattaneo--Vernotte)} equations. Fu

Vanessa Jacquier, Emilio Nicola Maria Cirillo, Cristian Spitoni

We pose the problem of metastability for a three--state spin system with conservative dynamics. We consider the Blume--Capel model with the Kawasaki dynamics, we prove that, in a particular region of the parameter plane, the metastable state is the unique homogeneous minus state, and we estimate the exit time. To achieve our goal we have to solve several var

Wilson Jallet, Ewen Dantec, Etienne Arlaud, Justin Carpentier

Recent strides in nonlinear model predictive control (NMPC) underscore a dependence on numerical advancements to efficiently and accurately solve large-scale problems. Given the substantial number of variables characterizing typical whole-body optimal control (OC) problems - often numbering in the thousands - exploiting the sparse structure of the numerical

Angel D Reyero Lobo, Alexis Ayme, Claire Boyer, Erwan Scornet

Supervised learning with missing data aims at building the best prediction of a target output based on partially-observed inputs. Major approaches to address this problem can be decomposed into $(i)$ impute-then-predict strategies, which first fill in the empty input components and then apply a unique predictor and $(ii)$ Pattern-by-Pattern (P-b-P) approache

Zimo Hao, Jean-Francois Jabir, Stéphane Menozzi, Michael Röckner

This work addresses the propagation of chaos properties in a class of moderately interacting particle systems for the approximation of singular kinetic McKean-Vlasov SDEs driven by alpha-stable processes.

Henri Bouma, Bart Joosten, Maarten C Kruithof, Maaike H T de Boer

Due to the increasing need for effective security measures and the integration of cameras in commercial products, a hugeamount of visual data is created today. Law enforcement agencies (LEAs) are inspecting images and videos to findradicalization, propaganda for terrorist organizations and illegal products on darknet markets. This is time consuming.Instead o

Yoo-Bin Bae, Yeong-Ung Kim, Jun-Oh Park, Hyo-Sung Ahn

As multiple and heterogenous unmanned vehicle systems continue to play an increasingly important role in addressing complex missions in the real world, the need for effective cooperation among unmanned vehicles becomes paramount. The concept of autonomous cooperation, wherein unmanned vehicles cooperate without human intervention or human control, offers pro

Yunsong Gan, Pablo Spiga, Binzhou Xia

This paper represents a significant leap forward in the problem of enumerating vertex-transitive graphs. Recent breakthroughs on symmetry of Cayley (di)graphs show that almost all finite Cayley (di)graphs have the smallest possible automorphism group. Extending the scope of these results, we enumerate (di)graphs admitting a fixed semiregular group of automor

Arun Amaithi Rajan, Vetriselvi V

In the age of digital technology, medical images play a crucial role in the healthcare industry which aids surgeons in making precise decisions and reducing the diagnosis time. However, the storage of large amounts of these images in third-party cloud services raises privacy and security concerns. There are a lot of classical security mechanisms to protect t

Marios Tyrovolas, Nikolaos D. Kallimanis, Chrysostomos Stylios

In the quest for accurate and interpretable AI models, eXplainable AI (XAI) has become crucial. Fuzzy Cognitive Maps (FCMs) stand out as an advanced XAI method because of their ability to synergistically combine and exploit both expert knowledge and data-driven insights, providing transparency and intrinsic interpretability. This letter introduces and invest

Saroj Prasad Chhatoi, Aneel Tanwani, Didier Henrion

This article develops mathematical formalisms and provides numerical methods for studying the evolution of measures in nonsmooth dynamical systems using the continuity equation. The nonsmooth dynamical system is described by an evolution variational inequality and we derive the continuity equation associated with this system class using three different forma

Shuji Fujino, Yuta Kozakai, Kohei Takamura

We explicitly construct two-sided tilting complexes corresponding to Membrillo-Hern\'{a}ndez's tree-to-star tilting complexes for generalized Brauer tree algebras.

Yu-Yang Wang, Jeng-Da Chai

For electronic systems with multi-reference (MR) character, Kohn-Sham density functional theory (KS-DFT) with the conventional exchange-correlation (xc) energy functionals can lead to incorrect spin densities and related properties. For example, for H2 dissociation, the spin-restricted and spin-unrestricted solutions obtained with the same xc energy function

Milan Gritta, Gerasimos Lampouras, Ignacio Iacobacci

Language models (LMs) as conversational assistants recently became popular tools that help people accomplish a variety of tasks. These typically result from adapting LMs pretrained on general domain text sequences through further instruction-tuning and possibly preference optimisation methods. The evaluation of such LMs would ideally be performed using human

Xilong Qu, Wenbin Pei, Yingchao Yang, Xirong Xu

Influence maximization (IM) is a crucial optimization task related to analyzing complex networks in the real world, such as social networks, disease propagation networks, and marketing networks. Publications to date about the IM problem focus mainly on graphs, which fail to capture high-order interaction relationships from the real world. Therefore, the use

S. Sazonov, R. Burenin, E. Filippova, R. Krivonos

We present an updated catalog of sources detected by the Mikhail Pavlinsky ART-XC telescope aboard the Spektrum-Roentgen-Gamma (SRG) observatory during its all-sky survey. It is based on the data of the first four and the partially completed fifth scans of the sky (ARTSS1-5). The catalog comprises 1545 sources detected in the 4-12 keV energy band. The achiev

Paolo Ballarini, Mahmoud Bentriou, Paul-Henry Cournède

Periodic recurrence is a prominent behavioural of many biological phenomena, including cell cycle and circadian rhythms. Although deterministic models are commonly used to represent the dynamics of periodic phenomena, it is known that they are little appropriate in the case of systems in which stochastic noise induced by small population numbers is actually

Nils Faltermann

The top quark is the heaviest elementary particle known to date and therefore an important topic to study in the context of the standard model at the LHC. In this contribution the latest measurements of top quark production cross sections and the top quark mass at the LHC by the ATLAS and CMS Collaborations are presented.

Zongwei Li, Wenkai Li, Xiaoqi Li, Yuqing Zhang

Decentralized Exchanges (DEXs), leveraging blockchain technology and smart contracts, have emerged in decentralized finance. However, the DEX project with multi-contract interaction is accompanied by complex state logic, which makes it challenging to solve state defects. In this paper, we conduct the first systematic study on state derailment defects of DEXs

Chen-Guang Wang, Wuyue Xu, Chong Li, Lili Shi

Frequency combs, specialized laser sources emitting multiple equidistant frequency lines, have revolutionized science and technology with unprecedented precision and versatility. Recently, integrated frequency combs are emerging as scalable solutions for on-chip photonics. Here, we demonstrate a fully integrated superconducting microcomb that is easy to manu

Zhiqing Wei, Haotian Liu, Hujun Li, Wangjun Jiang

Integrated sensing and communication (ISAC) is a potential technology of the sixth-generation (6G) mobile communication system, which enables communication base station (BS) with sensing capability. However, the performance of single-BS sensing is limited, which can be overcome by multi-BS cooperative sensing. There are three types of multi-BS cooperative se

Neilson Carlos Leite Ramalho, Higor Amario de Souza, Marcos Lordello Chaim

Quantum computing has existed in the theoretical realm for several decades. Recently, quantum computing has re-emerged as a promising technology to solve problems that a classical computer could take hundreds of years to solve. However, there are challenges and opportunities for academics and practitioners regarding software engineering practices for testing

Péter Király

The Shapes Constraint Language (SHACL) is a formal language for validating RDF graphs against a set of conditions. Following this idea and implementing a subset of the language, the Metadata Quality Assessment Framework provides Shacl4Bib: a mechanism to define SHACL-like rules for data sources in non-RDF based formats, such as XML, CSV and JSON. QA catalogu

Changming Xu, Gagandeep Singh

Existing work in trustworthy machine learning primarily focuses on single-input adversarial perturbations. In many real-world attack scenarios, input-agnostic adversarial attacks, e.g. universal adversarial perturbations (UAPs), are much more feasible. Current certified training methods train models robust to single-input perturbations but achieve suboptimal

Andrew Mummery, Adam Ingram, Shane Davis, Andrew Fabian

The thermal continuum emission observed from accreting black holes across X-ray bands has the potential to be leveraged as a powerful probe of the mass and spin of the central black hole. The vast majority of existing ``continuum fitting'' models neglect emission sourced at and within the innermost stable circular orbit (ISCO) of the black hole. Numerical si

Radek Machulka, Jan Peřina, Václav Michálek, Roberto de J. León-Montiel

The identification of nonclassical features of multiphoton quantum states represents a task of the utmost importance in the development of many quantum photonic technologies. Under realistic experimental conditions, a photonic quantum state gets affected by its interaction with several nonideal opto-electronic devices, including those used to guide, detect o

Eric Budish, Andrew Lewis-Pye, Tim Roughgarden

The purpose of a consensus protocol is to keep a distributed network of nodes "in sync," even in the presence of an unpredictable communication network and adversarial behavior by some of the participating nodes. In the permissionless setting, these nodes may be operated by unknown players, with each player free to use multiple identifiers and to start or st

Iku Nakamura

Let $R$ be a complete discrete valuation ring, $k(\eta)$ its fraction field, $S={\rm Spec} R$, $(G_{\eta},\mathcal{L}_{\eta})$ a polarized abelian variety over $k(\eta)$ with $\mathcal{L}_{\eta}$ symmetric ample cubical and $\mathcal{G}$ the N\'eron model of $G_{\eta}$ over $S$. Suppose that $\mathcal{G}$ is semiabelian over $S$. Then there exists a {\it uni

Sho Inoue, Kun Zhou, Shuai Wang, Haizhou Li

It remains a challenge to effectively control the emotion rendering in text-to-speech (TTS) synthesis. Prior studies have primarily focused on learning a global prosodic representation at the utterance level, which strongly correlates with linguistic prosody. Our goal is to construct a hierarchical emotion distribution (ED) that effectively encapsulates inte

Chen-Guang Wang, Wen-Cheng Yue, Xuecou Tu, Tianyuan Chi

Superconducting microwave resonators play a pivotal role in superconducting quantum circuits. The ability to fine-tune their resonant frequencies provides enhanced control and flexibility. Here, we introduce a frequency-tunable superconducting coplanar waveguide resonator. By applying electrical currents through specifically designed ground wires, we achieve

Lina Döring, Felix Grumbach, Pascal Reusch

Recognizing that traditional forecasting models often rely solely on historical demand, this work investigates the potential of data-driven techniques to automatically select and integrate market indicators for improving customer demand predictions. By adopting an exploratory methodology, we integrate macroeconomic time series, such as national GDP growth, f

J. A. Montanez-Barrera, Kristel Michielsen

The Quantum Approximate Optimization Algorithm (QAOA) is a promising algorithm for solving combinatorial optimization problems (COPs), with performance governed by variational parameters $\{\gamma_i, \beta_i\}_{i=0}^{p-1}$. While most prior work has focused on classically optimizing these parameters, we demonstrate that fixed linear ramp schedules, linear ra

K. -H. Rehren

There exist several good reasons why one may wish to add a total derivative to an interaction in quantum field theory, e.g., in order to improve the perturbative construction. Unlike in classical field theory, adding derivatives in general changes the theory. The analysis whether and how this can be prevented, is presently limited to perturbative orders $g^n

G. Kitagawa

Particle filters are applicable to a wide range of nonlinear, non-Gaussian state-space models and have already been applied to a variety of problems. However, there is a problem in the calculation of smoothed distributions, where particles gradually degenerate and accuracy is reduced. The purpose of this paper is to consider the possibility of generating mul

Omar Abdul-Aziz, Daniel Wolverson, Charles Sayers, Ettore Carpene

We report a comprehensive Raman study of the phonon behaviour in PdSe$_2$ in the temperature range of 5 K to 300 K. A remarkable change in the Raman spectrum is observed at 120 K: a significant enhancement of the out-of-plane phonon A$^{1}_{g}$ mode, accompanied by a suppression of the in-plane A$^{2}_{g}$ and B$^{2}_{1g}$ modes. This intriguing behavior is

Masanari Kondo, Daniel M. German, Yasutaka Kamei, Naoyasu Ubayashi

In software development, developers frequently apply maintenance activities to the source code that change a few lines by a single commit. A good understanding of the characteristics of such small changes can support quality assurance approaches (e.g., automated program repair), as it is likely that small changes are addressing deficiencies in other changes;

Honghui Shang, Xiongzhi Zeng, Ming Gong, Yangju Wu

Finding accurate ground state energy of a many-body system has been a major challenge in quantum chemistry. The integration of classic and quantum computers has shed new light on resolving this outstanding problem. Here we propose QiankunNet-VQE, a transformer based language models enforced with quantum computing to learn and generate quantum states. It has

Jingwen Yang, Ping Wang, Fatemeh Golpayegani, Shen Wang

Variable speed limit (VSL) control is an established yet challenging problem to improve freeway traffic mobility and alleviate bottlenecks by customizing speed limits at proper locations based on traffic conditions. Recent advances in deep reinforcement learning (DRL) have shown promising results in solving VSL control problems by interacting with sophistica

Konstantin Y. Guslienko

Magnetic hopfions are localized magnetic solitons with non-zero 3D topological charge (Hopf index). Here I present an analytical calculation of the toroidal magnetic hopfion vector potential, emergent magnetic field, the Hopf index, and the magnetization configuration. The calculation method is based on the concept of the spinor representation of the Hopf ma

Yuki Nishimura, Tsubasa Takagi

Hybrid logic is a modal logic with additional operators specifying nominals and is highly expressive. For example, there is no formula corresponding to the irreflexivity of Kripke frames in basic modal logic, but there is in hybrid logic. Irreflexivity is significant in that irreflexive and symmetric Kripke frames can be regarded as undirected graphs reviewe

Jochen Wulf, Juerg Meierhofer

Purpose: The purpose of this study is to investigate the potential of Large Language Models (LLMs) in transforming technical customer service (TCS) through the automation of cognitive tasks. Design/Methodology/Approach: Using a prototyping approach, the research assesses the feasibility of automating cognitive tasks in TCS with LLMs, employing real-world tec

Marina Zajnulina, Michael Böhm

The temporal Talbot effect refers to the periodic self-imaging of pulse trains in optical fibers. The connection between the linear and nonlinear temporal Talbot effect is still not fully understood. To address this challenge, we use Soliton Radiation Beat Analysis and numerically investigate the evolution of a phase-modulated continuous-wave laser input in

Ran Tang, Christop Herb, Jörg Voigt, Robert Georgii

We present a concept for an indirect geometry crystal time-of-flight spectrometer, which we propose for a source similar to the FRM-II reactor in Garching. Recently, crystal analyzer spectrometers at modern spallation sources have been proposed and are under construction. The secondary spectrometers of these instruments are evolutions of the flat cone multi-

Fumio Hiroshima, Tomoyuki Shirai

The spectral zeta function of the quantum Rabi Hamiltonian is considered. It is shown that the spectral zeta function converges to the Riemann zeta function as the coupling constant goes to infinity. Moreover the path measure associated with the ground state of the quantum Rabi Hamiltonian is constructed on a discontinuous path space, and several application

Jiaqi Zheng, Antonios Varvitsiotis, Tiow-Seng Tan, Wayne Lin

In this paper, we introduce a primal-dual algorithmic framework for solving Symmetric Cone Programs (SCPs), a versatile optimization model that unifies and extends Linear, Second-Order Cone (SOCP), and Semidefinite Programming (SDP). Our work generalizes the primal-dual framework for SDPs introduced by Arora and Kale, leveraging a recent extension of the Mul

Yamato Kindaichi, Yuki Ueda

The concept of free extreme value distributions as universal limit laws for the spectral maximum of free noncommutative real random variables was discovered by Ben Arous and Voiculescu in 2006. This paper contributes to study the convergence of densities towards free extreme value distributions under the von Mises condition for sample distributions.

Lim Chang Quan Thaddeus, C. Rajashekar Reddy, Yuvraj Singh Bhadauria, Dhairya Shah

Sensing the motion of physical objects in an environment enables numerous applications, from tracking occupancy in buildings and monitoring vital signs to diagnosing faults in machines. Typically, these application scenarios involve attaching a sensor, such as an accelerometer, to the object of interest, like a wearable device that tracks our steps. However,

Anton Dmytriiev, Andrzej A. Zdziarski, Denys Malyshev, Valenti Bosch-Ramon

We model the currently available $\gamma$-ray data from the Fermi Large Area Telescope on Cyg X-3. Thanks to its very strong $\gamma$-ray activity during 2018--2021, the data quality has significantly improved. We study the strong orbital modulation of the $\gamma$-rays observed during at high $\gamma$-ray fluxes. The modulation, as found earlier, is well mo

Mahsa Khoshnoodi, Vinija Jain, Mingye Gao, Malavika Srikanth

Despite the crucial importance of accelerating text generation in large language models (LLMs) for efficiently producing content, the sequential nature of this process often leads to high inference latency, posing challenges for real-time applications. Various techniques have been proposed and developed to address these challenges and improve efficiency. Thi

Jon Z. Cai, Kristin Wright-Bettner, Martha Palmer, Guergana K. Savova

This paper is dedicated to the design and evaluation of the first AMR parser tailored for clinical notes. Our objective was to facilitate the precise transformation of the clinical notes into structured AMR expressions, thereby enhancing the interpretability and usability of clinical text data at scale. Leveraging the colon cancer dataset from the Temporal H

Takahiro Shindo, Taiju Watanabe, Yui Tatsumi, Hiroshi Watanabe

As image recognition models become more prevalent, scalable coding methods for machines and humans gain more importance. Applications of image recognition models include traffic monitoring and farm management. In these use cases, the scalable coding method proves effective because the tasks require occasional image checking by humans. Existing image compress

Ran Li, Jin Wang

We propose that the thermodynamics and the kinetics of state switching for the asymptotically flat black hole enclosed by a cavity can be studied in terms of the free energy landscape formalism. The generalized free energy for the black hole enclosed by a cavity in the canonical ensemble is derived by using the York's approach, where the temperature on the c