May 2023 arXiv papers — page 110

Sergei P. Maydanyuk, Gyorgy Wolf, Kostiantyn A. Shaulskyi

(1) Purpose: Conditions of formation of compound nuclear system needed for synthesis of heavy nuclei in pycnonuclear reactions in compact stars are studied on a quantum mechanical basis. (2) Methods: Method of multiple internal reflections is generalized for pycnoreactions in compact stars with new calculations of quasibound spectra and spectra of zero-point

Thomas M. Tauris, Ed P. J. van den Heuvel

The majority of all stars are members of a binary system. The evolution of such binary stars and their subsequent production of pairs of compact objects in tight orbits, such as double neutron stars and double black holes, play a central role in modern astrophysics, Binary evolution leads to the formation of different types of violent cosmic events such as n

Shahin Mamedov, Narmin Akbarova, Minaya Allahverdiyeva

We study the deuteron charge radius in the framework of a hard-wall AdS/QCD model. We present basic elements of the hard-wall model and write metrics for the AdS space. We introduce a vector field with twist $\tau=6$ describing deuteron in the bulk of AdS space and other vector fields to describe photon respectively, write an effective action for the bulk fi

Han-Ze Li, Xue-Jia Yu, Jian-Xin Zhong

Utilizing exact diagonalization (ED) techniques, we investigate a one-dimensional, non-reciprocal, interacting hard-core boson model under a Stark potential with tail curvature. By employing the non-zero imaginary eigenenergies ratio, half-chain entanglement entropy, and eigenstate instability, we numerically confirm that the critical points of spectral real

Emanuela Rosazza Gianin, Marco Zullino

In the context of risk measures, the capital allocation problem is widely studied in the literature where different approaches have been developed, also in connection with cooperative game theory and systemic risk. Although static capital allocation rules have been extensively studied in the recent years, only few works deal with dynamic capital allocations

Hannes Köhler

Kernel-based regularized risk minimizers, also called support vector machines (SVMs), are known to possess many desirable properties but suffer from their super-linear computational requirements when dealing with large data sets. This problem can be tackled by using localized SVMs instead, which also offer the additional advantage of being able to apply diff

Sander Thuijsman, Kai Cai, Michel Reniers

Supervisor localization can be applied to distribute a monolithic supervisor into local supervisors. Performing supervisor localization can be computationally costly. In this work, we consider systems that evolve over time. We study how to reuse the results from a previous supervisor localization, to more efficiently compute local supervisors when the system

LHC Collaboration

We report the direct observation of muon neutrino interactions with the SND@LHC detector at the Large Hadron Collider. A data set of proton-proton collisions at $\sqrt{s} = 13.6\,$TeV collected by SND@LHC in 2022 is used, corresponding to an integrated luminosity of 36.8$\,\rm{fb}^{-1}$. The search is based on information from the active electronic component

Tobias Breiten, Jesper Schröder

The analytical background of nonlinear observers based on minimal energy estimation is discussed. It is shown that locally the derivation of the observer equation based on a trajectory with pointwise minimal energy can be done rigorously. The result is obtained by a local sensitivity analysis of the value function based on Pontryagin's maximum principle and

Bo Han, Hao Peng, Minjing Dong, Yi Ren

Human motion generation aims to produce plausible human motion sequences according to various conditional inputs, such as text or audio. Despite the feasibility of existing methods in generating motion based on short prompts and simple motion patterns, they encounter difficulties when dealing with long prompts or complex motions. The challenges are two-fold:

Raymond Isichei, João Magueijo

We study the Hamiltonian structure of unimodular-like theories, where the cosmological constant (or other supposed constants of nature) are demoted from fixed parameters to classical constants of motion. No new local degrees of freedom are present as a result of a $U(1)$ gauge invariance of the theory. Hamiltonian analysis of the action reveals that the only

Luca Di Persio, Peter Kuchling

In this article, we analyse the existence of an optimal feedback controller of stochastic optimal control problems governed by SDEs which have the control in the diffusion part. To this end, we consider the underlying Fokker-Planck equation to transform the stochastic optimal control problem into a deterministic problem with open-loop controller.

Sanyam Jain, Aarati Shrestha, Stefano Nichele

This research project investigates Lenia, an artificial life platform that simulates ecosystems of digital creatures. Lenia's ecosystem consists of simple, artificial organisms that can move, consume, grow, and reproduce. The platform is important as a tool for studying artificial life and evolution, as it provides a scalable and flexible environment for cre

Eli Bagno, Yisca Kares

We find the range of the major index on the various conjugacy classes of involutions in the symmetric group $S_n$. In addition to indicating the minimum and the maximum values, we show that except for the case of involutions without fixed points, all the values in the range are attained. For the conjugacy classes of involutions without fixed points, we show

N. Gavrielov

Nuclei in the $Z\!\approx\!40,N\!\approx\!60$ region have one of the most complicated structural evolution across the nuclear chart, with coexisting shapes arising from different mixed configurations. In such a region, it is difficult to investigate odd-mass nuclei. In this paper a new algebraic framework is introduced, the interacting boson-fermion model wi

Loriano Bonora

Weyl 0- and 1-cocycles of canonical dimension 6 in six dimensions, which were computed earlier in ref.\cite{bonorabregolapasti1986}, are recalculated from scratch. The analysis yields five Weyl invariants (0-cocycles), instead of four, and the same four non-trivial 1-cocycles (possible trace anomalies), like in that reference (up to the correction of one typ

Naixu Guo, Feng Pan, Patrick Rebentrost

Measuring properties of quantum systems is a fundamental problem in quantum mechanics. We provide a simple method for estimating the expectation value of observables with an unknown quantum state. The idea is to use a data structure to sample the terms of observables based on the Pauli decomposition proportionally to their importance. We call this technique

Derya Soydaner, Johan Wagemans

As people's aesthetic preferences for images are far from understood, image aesthetic assessment is a challenging artificial intelligence task. The range of factors underlying this task is almost unlimited, but we know that some aesthetic attributes affect those preferences. In this study, we present a multi-task convolutional neural network that takes into

Yonadav Barry Ginat, Robert Reischke, Ivan Rapoport, Vincent Desjacques

The superposition of many astrophysical gravitational wave (GW) signals below typical detection thresholds baths detectors in a stochastic gravitational wave background (SGWB). In this work, we present a Fourier space approach to compute the frequency-domain distribution of stochastic gravitational wave backgrounds produced by discrete sources. Expressions f

Chensheng Wu, Fuyang Zhou, Yong Wu, Jun Yan

For warm and hot dense plasma (WHDP), the ionization potential depression (IPD) is a key physical parameter in determining its ionization balance, therefore a reliable and universal IPD model is highly required to understand its microscopic material properties and resolve those existing discrepancies between the theoretical and experimental results. However,

Mathieu Molitor

We compute the Weyl group (in the sense of Segal) of the group of holomorphic isometries of a K\"ahler toric manifold with real analytic K\"ahler metric.

Eleni Nisioti, Clément Moulin-Frier

In both natural and artificial studies, evolution is often seen as synonymous to natural selection. Individuals evolve under pressures set by environments that are either reset or do not carry over significant changes from previous generations. Thus, niche construction (NC), the reciprocal process to natural selection where individuals incur inheritable chan

Chang Min Hyun, Tae-Geun Kim, Kyounghun Lee

This study proposes an unsupervised sequence-to-sequence learning approach that automatically assesses the motion-induced reliability degradation of the cardiac volume signal (CVS) in multi-channel electrical impedance-based hemodynamic monitoring. The proposed method attempts to tackle shortcomings in existing learning-based assessment approaches, such as t

Seokcheon Lee

The Generalized Cosmological Time (GCT) framework interprets the observed time dilation in Type Ia supernovae (SNe Ia) as a manifestation of a generalized lapse function in the background metric, favoring a parameter value b \approx 0.04. However, precision spectroscopic measurements of the fine-structure constant \alpha via the alkali doublet (AD) and many-

Indrani Pal, C. S. Stalin, Rwitika Chatterjee, Vivek K. Agrawal

X-ray polarimetry is a powerful tool to probe the geometry of the hot X-ray corona in active galactic nuclei (AGN). Here, we present our results on the characterisation of the X-ray polarization of the radio-quiet Seyfert-type AGN IC 4329A at a redshift of $z$ = 0.016. This is based on observations carried out by the {\it Imaging X-ray Polarimeter (IXPE)}. {

S. Nojoumi, S. Shamsigamchi

In this paper we are concerned with weighted conditional type(WCT) operators on Orlicz spaces. We prove that all WCT operators have finite ascent. Also, we provide some sufficient conditions for WCT operators to have finite descent. As a consequence we find some decompositions for Orlicz space L. In the sequel we discuss power bounded WCT operators and some

Isaac Skog, Gustaf Hendeby, Manon Kok

A framework for tightly integrated motion mode classification and state estimation in motion-constrained inertial navigation systems is presented. The framework uses a jump Markov model to describe the navigation system's motion mode and navigation state dynamics with a single model. A bank of Kalman filters is then used for joint inference of the navigation

Guojun Liang, Prayag Tiwari, Sławomir Nowaczyk, Stefan Byttner

Graph neural networks (GNNs), especially dynamic GNNs, have become a research hotspot in spatio-temporal forecasting problems. While many dynamic graph construction methods have been developed, relatively few of them explore the causal relationship between neighbour nodes. Thus, the resulting models lack strong explainability for the causal relationship betw

Srija Chakraborty, Simona Gallerani, Tommaso Zana, Alberto Sesana

We investigate the coalescence of massive black hole ($M_{\rm BH}\gtrsim 10^{6}~\rm M_{\odot}$) binaries (MBHBs) at $6<z<10$ by adopting a suite of cosmological hydrodynamical simulations of galaxy formation, zoomed-in on biased ($ >3 \sigma$) overdense regions ($M_h\sim 10^{12}~\rm M_{\odot}$ dark matter halos at $z = 6$) of the Universe. We first analyse t

M. A. Hamadi, K. Jbilou, A. Ratnani

In this work, we explore the application of multilinear algebra in reducing the order of multidimentional linear time-invariant (MLTI) systems. We use tensor Krylov subspace methods as key tools, which involve approximating the system solution within a low-dimensional subspace. We introduce the tensor extended block and global Krylov subspaces and the corres

Jia-Chen Gu, Zhen-Hua Ling, Quan Liu, Cong Liu

Addressing the issues of who saying what to whom in multi-party conversations (MPCs) has recently attracted a lot of research attention. However, existing methods on MPC understanding typically embed interlocutors and utterances into sequential information flows, or utilize only the superficial of inherent graph structures in MPCs. To this end, we present a

Fiona Anting Tan, Debdeep Paul, Sahim Yamaura, Miura Koji

Many financial jobs rely on news to learn about causal events in the past and present, to make informed decisions and predictions about the future. With the ever-increasing amount of news available online, there is a need to automate the extraction of causal events from unstructured texts. In this work, we propose a methodology to construct causal knowledge

Côme Fontaine, Francesco Vercesi, Marc Brachet, Léonie Canet

The celebrated Kardar-Parisi-Zhang (KPZ) equation describes the kinetic roughening of stochastically growing interfaces. In one dimension, the KPZ equation is exactly solvable and its statistical properties are known to an exquisite degree. Yet recent numerical simulations in the tensionless (or inviscid) limit of the KPZ equation [Phil. Trans. Roy. Soc. A 3

Ilian Pihlajamaa, Corentin C. L. Laudicina, Chengjie Luo, Liesbeth M. C. Janssen

The complete quantitative description of the structure of dense and supercooled liquids remains a notoriously difficult problem in statistical physics. Most studies to date focus solely on two-body structural correlations, and only a handful of papers have sought to consider additional three-body correlations. Here, we go beyond the state of the art by extra

Audrey Blizard, Stephanie Stockar

Strict user demands and large variability in external disturbances, along with limited richness in the data collected on the daily operating conditions of district heating networks makes the design and testing of novel energy-reducing control algorithms for district heating networks challenging. This paper presents the development of a dynamically similar la

Diego García-Lucas, Ángel del Río

We prove that the isomorphism problem for group algebras reduces to group algebras over finite extensions of the prime field. In particular, the modular isomorphism problem reduces to finite modular group algebras.

Nicole Gehring, Abdurrahman Irscheid, Joachim Deutscher, Frank Woittennek

This paper gives an overview of the control of distributed-parameter systems using normal forms. Considering linear controllable PDE-ODE systems of hyperbolic type, two methods derive tracking controllers by mapping the system into a form that is advantageous for the control design, analogous to the finite-dimensional case. A flatness-based controller makes

Jinsong Shi, Pan Gao, Aljosa Smolic

Image quality assessment is a fundamental problem in the field of image processing, and due to the lack of reference images in most practical scenarios, no-reference image quality assessment (NR-IQA), has gained increasing attention recently. With the development of deep learning technology, many deep neural network-based NR-IQA methods have been developed,

Tatsuki Inoue

This study is the first to investigate whether pawnshops, financial institutions for low-income populations, have contributed to the decline in mortality in the early twentieth century. Using ward-level panel data from Tokyo City, this study revealed that the popularity of public pawnshops was associated with a 4% and 5% decrease in infant mortality and feta

Pedro Antonino, Ante Derek, Wojciech Aleksander Wołoszyn

We propose a protocol that explores a synergy between two TEE implementations: it brings SGX-like remote attestation to SEV VMs. We use the notion of a \emph{trusted guest owner}, implemented as an SGX enclave, to deploy, attest, and provision a SEV VM. This machine can, in turn, rely on the trusted owner to generate SGX-like attestation proofs on its behalf

Michal Hnatič, Matej Kecer, Tomáš Lučivjanský

We study random velocity effects on a two-species reaction-diffusion system consisting of three reaction processes $A + A \rightarrow (\varnothing, A),A+B \rightarrow A$. Using the field-theoretic perturbative renormalization group we analyze this system in the vicinity of its upper critical dimension $d_c = 2$. Velocity ensemble is generated by means of sto

Nikolaos Kondylidis, Ilaria Tiddi, Annette ten Teije

We propose a method that allows to develop shared understanding between two agents for the purpose of performing a task that requires cooperation. Our method focuses on efficiently establishing successful task-oriented communication in an open multi-agent system, where the agents do not know anything about each other and can only communicate via grounded int

Soyed Tuhin Ahmed, Mehdi B. Tahoori

Neural networks (NNs) are capable of learning complex patterns and relationships in data to make predictions with high accuracy, making them useful for various tasks. However, NNs are both computation-intensive and memory-intensive methods, making them challenging for edge applications. To accelerate the most common operations (matrix-vector multiplication)

Qiang Chen, Jialin Li, Huanfeng Zhu, Tian Zhang

Photo-Thermoelectric (PTE) response is usually one of the main working mechanisms for photodetectors. However, as another fast and easier way to measure thermoelectric characteristics of materials, it can also reveal important physics such as electric-phonon coupling, electron-electron correlation, etc. Recently, the spin entropy related to magnetic order tr

M. K. Volkov, A. A. Pivovarov, K. Nurlan

The widths of the decays $\tau \to K^- K^+ K^- \nu_\tau$ and $\tau \to K^- K^0 \bar{K}^0 \nu_\tau$ are calculated in the $U(3)\times U(3)$ chiral quark NJL model. Four channels are considered: contact, axial vector, vector and pseudoscalar channels. It is shown that the dominant contribution is given by the axial vector channel with an intermediate $\phi$ me

Dimple Saini

The notion of Cauchy dual for left-invertible covariant representations was studied by Trivedi and Veerabathiran. Using the Moore-Penrose inverse, we extend this notion for the covariant representations having closed range and explore several useful properties. We obtain a Wold-type decomposition for {regular} completely bounded covariant representation whos

Sabine Thater, Prashin Jethwa, Edward J. Lilley, Alice Zocchi

Triaxial dynamical models of massive galaxies observed in the ATLAS3D project can provide new insights into the complex evolutionary processes that shape galaxies. The ATLAS3D survey is ideal as the sample comprises a good mix of fast and slow rotators with vastly different mass assembly histories. We present a detailed dynamical study with our triaxial mode

Walter Dehnen, Marcin Semczuk, Ralph Schönrich

We examine the Galactic warp in a sample of all classical Cepheids with Gaia DR3 radial velocity. In each radial bin, we determine (1) the inclined plane normal to the mean orbital angular momentum of the stars and (2) that best fitting their positions. We find no warping inside $R\approx 11$ kpc; for larger $R$ the disc is increasingly inclined, reaching $i

Angela Carollo, Paul H. C. Eilers, Hein Putter, Jutta Gampe

Hazard models are the most commonly used tool to analyse time-to-event data. If more than one time scale is relevant for the event under study, models are required that can incorporate the dependence of a hazard along two (or more) time scales. Such models should be flexible to capture the joint influence of several times scales and nonparametric smoothing t

Michael Gr. Voskoglou

Maji et al. introduced in 2002 a method of parametric decision making using soft sets as tools and representing their tabular form as a binary matrix. In cases, however, where some or all of the parameters used for the characterization of the elements of the universal set are of fuzzy texture, their method does not give always the best decision making soluti

Jialin Li, Yuzhong Chen, Yujie Li, Haiming Zhu

2D ferroelectric \{beta}-InSe/graphene heterostructure was fabricated by mechanical exfoliation, and the carrier dynamics crossing the heterostructure interface has been systematically investigated by Raman, photoluminescence and transient absorption measurements. Due to the efficient interfacial photo excited electron transfer and photogating effect from tr

François Ollivier

Computing analytic B\'ezout identities remains a difficult task, which has many applications in control theory. Flat PDE systems have cast a new light on this problem. We consider here a simple case of special interest: a rod of length $a+b$, insulated at both ends and heated at point $x=a$. The case $a=0$ is classical, the temperature of the other end $\the

Jean-Baptiste Bayle, Olaf Hartwig, Marc Lilley, Aurélien Hees

The data produced by the future space-based millihertz gravitational-wave detector LISA will require nontrivial pre-processing, which might affect the science results. It is crucial to demonstrate the feasibility of such processing algorithms and assess their performance and impact on the science. We are building an end-to-end pipeline that includes state-of

Matteo Caggio, Donatella Donatelli

We derive a relative entropy inequality for capillary compressible fluids with density dependent viscosity. Applications in the context of weak-strong uniqueness analysis, pressureless fluids and high-Mach number flows are presented.

Muhammad Al-Zafar Khan, Mervlyn Moodley, Francesco Petruccione

We calculate soliton solutions to the scalar field equation of motion that arises for the 4th-order extended Lagrangian (\(\phi^{4}\) theory) in quantum field theory using the extended hyperbolic tangent and the sine-cosine methods. Using the former technique, ten complex soliton waves are obtained; we graphically represent three of these profiles using dens

Nicholas Choustikov, Zvonimir Vlah, Anthony Challinor

Perturbation theory is a powerful tool for studying large-scale structure formation in the universe and calculating observables such as the power spectrum or bispectrum. However, beyond linear order, typically this is done by assuming a simplification in the time-dependence of gravitational-coupling kernels between the matter and velocity fluctuations. Thoug

Mohammad Ayman-Mursaleen, Bishnu P. Lamichhane, Adem Kiliçman, Norazak Senu

The aim of this research is to examine various statistical approximation properties with respect to Kantorovich \textit{\text{\texthtq}}-Baskakov operators using wavelets. We discuss and investigate a weighted statistical approximation employing a Bohman-Korovkin type theorem as well as a statistical rate of convergence applying a weighted modulus of smoothn

Muhammad Al-Zafar Khan

We study soliton solutions to the Klein-Gordon equation via Lie symmetries and the travelling-wave ansatz. It is shown, by taking a linear combination of the spatial and temporal Lie point symmetries, that soliton solutions naturally exist, and the resulting field lies in the complex plane. We normalize the field over a finite spatial interval, and thereafte

Vladimir Spokoiny

Laplace approximation is a very useful tool in Bayesian inference and it claims a nearly Gaussian behavior of the posterior. \cite{SpLaplace2022} established some rather accurate finite sample results about the quality of Laplace approximation in terms of the so called effective dimension $p$ under the critical dimension constraint $p^{3} \ll n$. However, th

Siyuan Wang, Jianming Zheng, Xuejun Hu, Fei Cai

Event detection (ED) is aimed to identify the key trigger words in unstructured text and predict the event types accordingly. Traditional ED models are too data-hungry to accommodate real applications with scarce labeled data. Besides, typical ED models are facing the context-bypassing and disabled generalization issues caused by the trigger bias stemming fr

Farid Labib, Hiroyuki Takakura, Asuka Ishikawa, Ryuji Tamura

The atomic structure of the recently discovered antiferromagnetic Ga50Pd35.5Tb14.5 2/1 approximant to quasicrystal with the space group of Pa-3(No. 205), a = 23.1449(0) angstrom was determined by means of a single crystal X-ray diffraction. The refined structure model revealed two main building units, namely, a Tsai-type rhombic triacontahedron (RTH) cluster

Yuzhou Peng

Multi-modal visual understanding of images with prompts involves using various visual and textual cues to enhance the semantic understanding of images. This approach combines both vision and language processing to generate more accurate predictions and recognition of images. By utilizing prompt-based techniques, models can learn to focus on certain features

Pedro Contreras, Dianela Osorio, Anjna Devi

This work is aimed at numerically investigating the behavior of the Fermi energy in Strontium-doped Lanthanum Cuprate, using a numerical zero temperature elastic scattering cross-section procedure in the unitary collision regime. The main task is to vary the zero temperature superconducting energy gap from its zero value in the normal state, to the highest v

Yimeng Huang, Lijie Liu, Jihong Yu, Yuguang Fang

The boom of the Internet of Things has revolutionized people's lives, but it has also resulted in massive resource consumption and environmental pollution. Recently, Green IoT (GIoT) has become a worldwide consensus to address this issue. In this paper, we propose EEWScatter, an energy-efficient WiFi backscatter communication system to pursue the goal of GIo

Bjørnar Vassøy, Helge Langseth

In the current landscape of ever-increasing levels of digitalization, we are facing major challenges pertaining to scalability. Recommender systems have become irreplaceable both for helping users navigate the increasing amounts of data and, conversely, aiding providers in marketing products to interested users. The growing awareness of discrimination in mac

Zheng Fang, Yulan He, Rob Procter

Most existing topic models rely on bag-of-words (BOW) representation, which limits their ability to capture word order information and leads to challenges with out-of-vocabulary (OOV) words in new documents. Contextualized word embeddings, however, show superiority in word sense disambiguation and effectively address the OOV issue. In this work, we introduce

Tianwei Hou, Anna Li

Satellite communication constitutes a promising solution for the sixth generation (6G) wireless networks in terms of providing global communication services. In order to provide a cost-effective satellite network, we propose a novel medium-earth-orbit (MEO) satellite aided integrated-navigation-and-communication (INAC) network. To overcome the severe path lo

Jeremiah Scully, Ronan Flynn, Peter Gallagher, Eoin Carley

Solar flares are energetic events in the solar atmosphere that are often linked with solar radio bursts (SRBs). SRBs are observed at metric to decametric wavelengths and are classified into five spectral classes (Type I--V) based on their signature in dynamic spectra. The automatic detection and classification of SRBs is a challenge due to their heterogeneou

Muhammad Al-Zafar Khan, Mervlyn Moodley, Francesco Petruccione

We construct Lie point symmetries, a closed-form solution and conservation laws using a non-Noetherian approach for a specific case of the Gorini-Kossakowski-Sudarshan-Lindblad equation that has been recast for the study of non-relativistic free particles in a thermal reservoir environment. Conservation laws are constructed subsequently using the Ibragimov m

Leon Lettermann, Alejandro Jurado, Timo Betz, Florentin Wörgötter

Building a representative model of a complex system remains a highly challenging problem. While by now there is basic understanding of most physical domains, model design is often hindered by lack of detail, for example concerning model dimensions or its relevant constraints. Here we present a novel model-building approach -- adoptODE -- augmenting basic sys

Guo-Quan Wong, Khai-Ming Wong, Dan Zhu

We report on generalized half-dyon solutions in SU(2) Yang-Mills-Higgs theory, namely Type I and Type II solutions. These solutions are constructed by considering $\phi$-winding number $1\leq n \leq 4$, electric charge parameter $0 \leq\eta <\eta_{max}$ and Higgs self-coupling constant $0 \leq \beta \leq 1$. They represent system of magnetic charge $+2n\pi/g

Mehdi Abdi, Moslem Zarei

We study nonclassical effects in the dynamics of an open quantum system. The model involves a harmonic oscillator coupled to a reservoir of non-interacting harmonic oscillators. Different system-bath interaction schemes as well as reservoir states are considered. Particularly, the squeezed reservoirs coupled to the system through single and two quanta exchan

ATLAS Collaboration

A search for supersymmetry targeting the direct production of winos and higgsinos is conducted in final states with either two leptons ($e$ or $\mu$) with the same electric charge, or three leptons. The analysis uses 139 fb$^{-1}$ of $pp$ collision data at $\sqrt{s}=13$ TeV collected with the ATLAS detector during Run 2 of the Large Hadron Collider. No signi

Yair Litman, Jinggang Lan, Yuki Nagata, David M. Wilkins

Our current understanding of the structure and dynamics of aqueous interfaces at the molecular level has grown substantially in the last few decades due to the continuous development of surface-specific spectroscopies, such as vibrational sum-frequency generation (VSFG). Similarly to what happens in other spectroscopies, to extract all of the information enc

H. J. H. Brouwers

In this paper the random packing fraction of hard disks in a plane is analyzed, following a geometric probabilistic approach. First, the random close packing (RCP) of equally sized disks is modelled. Subsequently, following the same methodology, a simple, statistical geometric model is proposed for the random loose packing (RLP) of monodisperse disks. This v

Lorenzo Porcaro, Carlos Castillo, Emilia Gómez, João Vinagre

Among the seven key requirements to achieve trustworthy AI proposed by the High-Level Expert Group on Artificial Intelligence (AI-HLEG) established by the European Commission (EC), the fifth requirement ("Diversity, non-discrimination and fairness") declares: "In order to achieve Trustworthy AI, we must enable inclusion and diversity throughout the entire AI

Xueyan Niu, Deniz Gündüz, Bo Bai, Wei Han

Recent advances in machine learning-aided lossy compression are incorporating perceptual fidelity into the rate-distortion theory. In this paper, we study the rate-distortion-perception trade-off when the perceptual quality is measured by the total variation distance between the empirical and product distributions of the discrete memoryless source and its re

Parvin Zarei Eskikand, David B Grayden, Tatiana Kameneva, Anthony N Burkitt

Computational modeling helps neuroscientists to integrate and explain experimental data obtained through neurophysiological and anatomical studies, thus providing a mechanism by which we can better understand and predict the principles of neural computation. Computational modeling of the neuronal pathways of the visual cortex has been successful in developin

Roberto Martínez-Cruz, Debanjan Mahata, Alvaro J. López-López, José Portela

In this study, we investigate using graph neural network (GNN) representations to enhance contextualized representations of pre-trained language models (PLMs) for keyphrase extraction from lengthy documents. We show that augmenting a PLM with graph embeddings provides a more comprehensive semantic understanding of words in a document, particularly for long d

Yuwei Zhang, Ge Li, Zhi Jin, Ying Xing

Automated program repair is a crucial task for improving the efficiency of software developers. Recently, neural-based techniques have demonstrated significant promise in generating correct patches for buggy code snippets. However, most existing approaches arbitrarily treat the buggy context without any analysis to capture the semantic relationship between t

Aram Grigoryan, Markus Möller

In centralized mechanisms and platforms, participants do not fully observe each others' type reports. Hence, if there is a deviation from the promised mechanism, participants may be unable to detect it. We formalize a notion of auditabilty that captures how easy or hard it is to detect deviations from a mechanism. We find a stark contrast between the auditab

Zongmeng Zhang, Wengang Zhou, Jiaxin Shi, Houqiang Li

In passage retrieval system, the initial passage retrieval results may be unsatisfactory, which can be refined by a reranking scheme. Existing solutions to passage reranking focus on enriching the interaction between query and each passage separately, neglecting the context among the top-ranked passages in the initial retrieval list. To tackle this problem,

Zhuoyuan Mao, Raj Dabre, Qianying Liu, Haiyue Song

This paper studies the impact of layer normalization (LayerNorm) on zero-shot translation (ZST). Recent efforts for ZST often utilize the Transformer architecture as the backbone, with LayerNorm at the input of layers (PreNorm) set as the default. However, Xu et al. (2019) has revealed that PreNorm carries the risk of overfitting the training data. Based on

Xiaomin Liu, RongGuo Yang, Jing Zhang, Tiancai Zhang

Optomechanical system is a promising platform to connect different notes of quantum networks, therefore, entanglement generated from it is also of great importance. In this paper, the parameter dependence of optomechanical and optical-optical entanglements generated from the double-longitudinal-mode cavity optomechanical system are discussed and two quadrapa

Will Stafford

Several recent results bring into focus the superintuitionistic nature of most notions of proof-theoretic validity, but little work has been done evaluating the consequences of these results. Proof-theoretic validity claims to offer a formal explication of how inferences follow from the definitions of logic connectives (which are defined by their introductio

Ryosuke Nogami

We extend the Watanabe--Sagawa--Ueda (WSU) uncertainty relations for measurement errors to infinite-dimensional systems. The original WSU formulation provided a definition of measurement errors with a clear physical interpretation based on quantum estimation theory, but was restricted to finite-dimensional systems, excluding important observables such as pos

Jeonghwan Ahn, Seoung-Hun Kang, Mao-Hua Du, Mina Yoon

We investigate the stability of MnPb$_{2}$Bi$_{2}$Te$_{6}$ (MPBT), which is predicted to be a magnetic topological insulator (TI), using density functional theory calculations. Our analysis includes various measures such as enthalpies of formation, Helmholtz free energies, defect formation energies, and dynamical stability. Our thermodynamic analysis shows t

Kiran Sharma, Harsha V. Garine, Satyam Mukherjee

Numerous studies in the literature highlight that women are underrepresented in the scientific domain which further leads to the underrepresentation of women in prestigious publications, authorship positions, and collaboration. However, the representation of women in scientific misconduct has not been studied yet, hence the study aims to investigate the fema

Bikash Thapa, Sunita Barman, Sompriti Bora, Ng. K. Francis

We construct an $S_4$ flavour symmetric minimal inverse seesaw model where the standard model is extended by adding two right-handed and two standard model gauge singlets neutrinos to explain the origin of tiny neutrino masses. The resulting model describes the lepton mass spectra and flavour mixing quite well for the case of the normal hierarchy of neutrino

Junxi Chen, Junhao Dong, Xiaohua Xie, Jianhuang Lai

Adversarial training (AT) is considered the most effective defense against adversarial attacks. However, a recent study revealed that \(\ell_{\infty}\)-norm adversarial training (\(\ell_{\infty}\)-AT) will also induce unevenly distributed input gradients, which is called the inequality phenomenon. This phenomenon makes the \(\ell_{\infty}\)-norm adversariall

Jiaming Ji, Jiayi Zhou, Borong Zhang, Juntao Dai

AI systems empowered by reinforcement learning (RL) algorithms harbor the immense potential to catalyze societal advancement, yet their deployment is often impeded by significant safety concerns. Particularly in safety-critical applications, researchers have raised concerns about unintended harms or unsafe behaviors of unaligned RL agents. The philosophy of

Martin Lara

The merits of a perturbation theory based on a mean to osculating transformation that is pure periodic in the fast angle are investigated. The exact separation of the purely short-period effects of the perturbed Keplerian dynamics from the long-period mean frequencies is achieved by a non-canonical transformation, which, therefore, cannot be computed by Hami

Di Xu, Yang Zhao, Xiang Hao, Xin Meng

We introduce a novel dataset consisting of images depicting pink eggs that have been identified as Pomacea canaliculata eggs, accompanied by corresponding bounding box annotations. The purpose of this dataset is to aid researchers in the analysis of the spread of Pomacea canaliculata species by utilizing deep learning techniques, as well as supporting other

Stefan Grisard, Artur V. Trifonov, Ivan A. Solovev, Dmitri R. Yakovlev

Compositional engineering of the optical properties of hybrid organic-inorganic lead halide perovskites is one of the cornerstones for the realization of efficient solar cells and tailored light-emitting devices. We study the effect of compositional disorder on coherent exciton dynamics in a mixed FA$_{0.9}$Cs$_{0.1}$PbI$_{2.8}$Br$_{0.2}$ perovskite crystal

Sung Une Lee, Harsha Perera, Boming Xia, Yue Liu

The rapid advancement of Artificial Intelligence (AI), represented by ChatGPT, has raised concerns about responsible AI development and utilization. Existing frameworks lack a comprehensive synthesis of AI risk assessment questions. To address this, we introduce QB4AIRA, a novel question bank developed by refining questions from five globally recognized AI r

Heqing Zou, Meng Shen, Chen Chen, Yuchen Hu

Multimodal learning aims to imitate human beings to acquire complementary information from multiple modalities for various downstream tasks. However, traditional aggregation-based multimodal fusion methods ignore the inter-modality relationship, treat each modality equally, suffer sensor noise, and thus reduce multimodal learning performance. In this work, w

U. Dutta, P. Král, M. Míšek, B. Joseph

We present ambient and high-pressure electrical transport and structural properties of recently discovered magnetic Weyl semimetal PrAlGe. Electrical resistivity at ambient pressure shows an anomaly at $T_C$ = 15.1 K related to the ferromagnetic transition. Anomalous Hall effect (AHE) is observed below $T_C$. We observe a 1.4 K/GPa increase of $T_C$ with pre

Wenming Zhang, Yuanchun Liu, Haiyan Du, Ke Han

We report the calibration of a gaseous Time Projection Chamber based on Micromegas charge readout modules with cosmic ray muons, utilizing their penetrating power and relatively uniform energy deposition per unit length. Muon events were selected through track reconstruction to characterize detector performances, such as the drift velocity, electron lifetime

Kaiqiang Lin, Onel Luis Alcaraz López, Hirley Alves, Tong Hao

Radio-frequency wireless energy transfer (WET) is a promising technology to realize wireless-powered underground sensor networks (WPUSNs) and enable sustainable underground monitoring. However, due to the severe attenuation in harsh underground soil and the tight energy budget of the underground sensors, traditional WPUSNs relying on the channel state inform

Muhammad Shaheer, Jose Andres Millan-Romera, Hriday Bavle, Jose Luis Sanchez-Lopez

In this paper, we propose a solution for graph-based global robot simultaneous localization and mapping (SLAM) using architectural plans. Before the start of the robot operation, the previously available architectural plan of the building is converted into our proposed architectural graph (A-Graph). When the robot starts its operation, it uses its onboard LI