May 2023 arXiv papers — page 136

Simon Scherrer, Seyedali Tabaeiaghdaei, Adrian Perrig

Internet service providers (ISPs) have a variety of quality attributes that determine their attractiveness for data transmission, ranging from quality-of-service metrics such as jitter to security properties such as the presence of DDoS defense systems. ISPs should optimize these attributes in line with their profit objective, i.e., maximize revenue from att

Victor Druet, David Ohayon, Christopher E. Petoukhoff, Yizhou Zhong

Conjugated polymer films that can conduct ionic and electronic charges are central to building soft electronic sensors and actuators. Despite the possible interplay between light absorption and mixed conductivity of these materials in aqueous biological media, no polymer film has ever been used to realize a solar-switchable organic bioelectronic circuit rely

Tillmann Ohm, Mar Canet Solà, Andres Karjus, Maximilian Schich

We introduce the Collection Space Navigator (CSN), a browser-based visualization tool to explore, research, and curate large collections of visual digital artifacts that are associated with multidimensional data, such as vector embeddings or tables of metadata. Media objects such as images are often encoded as numerical vectors, for e.g. based on metadata or

Rebecca Tobin, Glen Pridham, Andrew D. Rutenberg

We model the effects of disease and other exogenous damage during human aging. Even when the exogenous damage is repaired at the end of acute disease, propagated secondary damage remains. We consider both short-term mortality effects due to (acute) exogenous damage and long-term mortality effects due to propagated damage within the context of a generic netwo

Vivek Kumar, Nitish K. Chandra, Kaushik P. Seshadreesan, Alan Scheller-Wolf

In an entanglement distribution network, the function of a quantum switch is to generate elementary entanglement with its clients followed by entanglement swapping to distribute end-to-end entanglement of sufficiently high fidelity between clients. The threshold on entanglement fidelity is any quality-of-service requirement specified by the clients as dictat

Ziwen Zhang, Huiyuan Wang, Wentao Luo, Houjun Mo

Based on the DECaLS shear catalog, we study the scaling relations between halo mass($M_{\rm h}$) and various proxies for SDSS central galaxies, including stellar mass($M_*$), stellar velocity dispersion($\sigma_*$), abundance matching halo mass($M_{\rm AM}$) and satellite velocity dispersion($\sigma_{\rm s}$), and their dependencies on galaxy and group prope

Liam Harcombe, Quanling Deng

The Schr\"{o}dinger equation with random potentials is a fundamental model for understanding the behaviour of particles in disordered systems. Disordered media are characterised by complex potentials that lead to the localisation of wavefunctions, also called Anderson localisation. These wavefunctions may have similar scales of eigenenergies which poses diff

François Remy, Alfiya Khabibullina, Thomas Demeester

This paper shines a light on the potential of definition-based semantic models for detecting idiomatic and semi-idiomatic multiword expressions (MWEs) in clinical terminology. Our study focuses on biomedical entities defined in the UMLS ontology and aims to help prioritize the translation efforts of these entities. In particular, we develop an effective tool

Erik Burman, Lauri Oksanen

We consider a unique continuation problem where the Dirichlet trace of the solution is known to have finite dimension. We prove Lipschitz stability of the unique continuation problem and design a finite element method that exploits the finite dimensionality to enhance stability. Optimal a priori and a posteriori error estimates are shown for the method. The

Weiqing Yan, Yuanyang Zhang, Chenlei Lv, Chang Tang

Multi-view clustering can partition data samples into their categories by learning a consensus representation in unsupervised way and has received more and more attention in recent years. However, most existing deep clustering methods learn consensus representation or view-specific representations from multiple views via view-wise aggregation way, where they

Paul Z. Hanakata, Sourav S. Bhabesh, David Yllanes, David R. Nelson

Crystalline sheets (e.g., graphene and transition metal dichalcogenides) liberated from a substrate are a paradigm for materials at criticality because flexural phonons can fluctuate into the third dimension. Although studies of static critical behaviors (e.g., the scale-dependent elastic constants) are plentiful, investigations of dynamics remain limited. H

Zdeněk Mihula

We find the optimal function norm on the left-hand side of the $m$th order Sobolev type inequality $\|u\|_{Y(\mathbb{H}^n)} \leq C \|\nabla_g^m u\|_{X(\mathbb{H}^n)}$ in the $n$-dimensional hyperbolic space $\mathbb{H}^n$, $1\leq m < n$. The optimal function norm in the inequality among all rearrangement-invariant function norms is completely characterized.

Ali Baheri

This paper presents an approach for data-driven policy refinement in reinforcement learning, specifically designed for safety-critical applications. Our methodology leverages the strengths of data-driven optimization and reinforcement learning to enhance policy safety and optimality through iterative refinement. Our principal contribution lies in the mathema

Junkai Zeng, Yong-Ju Hai, Hao Liang, Xiu-Hao Deng

Quantum errors in noisy environments remain a major obstacle to advancing quantum information technology. In this work, we expand a recently developed geometric framework, originally utilized for analyzing noise accumulation and creating dynamical error-correcting gates at the control pulse level, to now study noise dynamics at the quantum circuit level. Thr

Mustafa Bakr, Smain Amari

We study the characteristics of azimuthally propagating electromagnetic fields in a cylindrical cavity. It is found that under certain conditions, the transverse components of the electromagnetic field are singular at the center of the cavity but the corresponding electromagnetic field remains of finite energy. The solutions are arranged in branches each of

Zhiheng Li, Yubo Cui, Yu Lin, Zheng Fang

3D single object tracking plays a crucial role in computer vision. Mainstream methods mainly rely on point clouds to achieve geometry matching between target template and search area. However, textureless and incomplete point clouds make it difficult for single-modal trackers to distinguish objects with similar structures. To overcome the limitations of geom

Xupeng Wei, Achilleas Anastasopoulos

Social learning refers to the process by which networked strategic agents learn an unknown state of the world by observing private state-related signals as well as other agents' actions. In their classic work, Bikhchandani, Hirshleifer and Welch showed that information cascades occur in social learning, in which agents blindly follow others' behavior, and co

M. Mallaby-Kay, S. Amodeo, J. C. Hill, M. Aguena

The kinematic and thermal Sunyaev-Zel'dovich (kSZ and tSZ) effects probe the abundance and thermodynamics of ionized gas in galaxies and clusters. We present a new hybrid estimator to measure the kSZ effect by combining cosmic microwave background temperature anisotropy maps with photometric and spectroscopic optical survey data. The method interpolates a ve

Natalia Lindgren, Qiantailang Yuan, Bengt Pipkorn, Svein Kleiven

Vulnerable road users are overrepresented in the worldwide number of road-traffic injury victims. Developing biofidelic male and female pedestrian HBMs representing a range of anthropometries is imperative to follow through with the efforts to increase road safety and propose intervention strategies. In this study, a 50th percentile male and female pedestria

K. H. Au-Yeung, S. Sarkar, T. Kühne, O. Aiboudi

Depending on its adsorption conformation on the Au(111) surface, a zwitterionic single-molecule machine works in two different ways under bias voltage pulses. It is a unidirectional rotor while anchored on the surface. It is a fast-drivable molecule-vehicle (nanocar) while physisorbed. By tuning the surface coverage, the conformation of the molecule can be s

David Kipping

Accurate quantification of the signal-to-noise ratio (SNR) of a given observational phenomenon is central to associated calculations of sensitivity, yield, completeness and occurrence rate. Within the field of exoplanets, the SNR of a transit has been widely assumed to be the formula that one would obtain by assuming a boxcar light curve, yielding an SNR of

Niki Kiriakidou, Christos Diou

Treatment effect estimation is of high-importance for both researchers and practitioners across many scientific and industrial domains. The abundance of observational data makes them increasingly used by researchers for the estimation of causal effects. However, these data suffer from biases, from several weaknesses, leading to inaccurate causal effect estim

Chih Wei Ling, Cheuk Ting Li

For uniform scalar quantization, the error distribution is approximately a uniform distribution over an interval (which is also a 1-dimensional ball). Nevertheless, for lattice vector quantization, the error distribution is uniform not over a ball, but over the basic cell of the quantization lattice. In this paper, we construct vector quantizers with periodi

Óscar Carrión-González, Raphael Moreno, Emmanuel Lellouch, Thibault Cavalié

Neptune's tropospheric winds are among the most intense in the Solar System, but the dynamical mechanisms that produce them remain uncertain. Measuring wind speeds at different pressure levels may help understand the atmospheric dynamics of the planet. The goal of this work is to directly measure winds in Neptune's stratosphere with ALMA Doppler spectroscopy

Natan Semyonov, Rami Puzis, Asaf Shabtai, Gilad Katz

Watermarking is one of the most important copyright protection tools for digital media. The most challenging type of watermarking is the imperceptible one, which embeds identifying information in the data while retaining the latter's original quality. To fulfill its purpose, watermarks need to withstand various distortions whose goal is to damage their integ

Tomohiro Nabika, Kenji Nagata, Shun Katakami, Masaichiro Mizumaki

In this study, we demonstrate a sequential experimental design for spectral measurements by active learning using parametric models as predictors. In spectral measurements, it is necessary to reduce the measurement time because of sample fragility and high energy costs. To improve the efficiency of experiments, sequential experimental designs are proposed, i

Jan Kronqvist, Boda Li, Jan Rolfes, Shudian Zhao

The presented work addresses two-stage stochastic programs (2SPs), a broadly applicable model to capture optimization problems subject to uncertain parameters with adjustable decision variables. In case the adjustable or second-stage variables contain discrete decisions, the corresponding 2SPs are known to be NP-complete. The standard approach of forming a s

Xiaoli Tang, Han Yu

Auction-based Federated Learning (AFL) has attracted extensive research interest due to its ability to motivate data owners to join FL through economic means. Existing works assume that only one data consumer and multiple data owners exist in an AFL marketplace (i.e., a monopoly market). Therefore, data owners bid to join the data consumer for FL. However, t

Yu. O. Kulanchikov, P. S. Vergeles, K. Konstantinova, A. R. Ishteev

Study of the local optical properties using electron beam (e-beam) can provide a valuable information concerning the inspection of the materials quality, the presence of the different phase inclusions and defects. Halide perovskites have been shown to be highly sensitive to external stress conditions like ambient atmosphere, light, and heat. In this paper, t

Sergio Mazzola, Thomas Benz, Björn Forsberg, Luca Benini

Computing systems have shifted towards highly parallel and heterogeneous architectures to tackle the challenges imposed by limited power budgets. These architectures must be supported by novel power management paradigms addressing the increasing design size, parallelism, and heterogeneity while ensuring high accuracy and low overhead. In this work, we propos

Anton Vasilev, Artur Ishteev, Kamilla Konstantinova, Alina Zharkova

The defect-activity in halide perovskites remains a critical factor for the application in optoelectronics. The imperfections (vacancies, anti-sites, interstitials) formed in the lattice of the halide perovskites were considered as a main origin for the corrosion of the interfaces and decomposition process under external stress. At the same time, the self-he

Yuta Moriyama, Takaya Inukai, Tsukasa Hirao, Yusuke Ueda

A methodology for forming a qubit state is essential for quantum applications of room temperature polaritons. While polarization degree of freedom is expected as a possible means for this purpose, the coupling of linearly polarized polariton condensed states has been still a challenging issue. In this study, we show a polarization superposition of a polarito

Nilamani Behera, Avinash Kumar Chaurasiya, Victor H. González, Artem Litvinenko

Nano-constriction based spin Hall nano-oscillators (SHNOs) are at the forefront of spintronics research for emerging technological applications such as oscillator-based neuromorphic computing and Ising Machines. However, their miniaturization to the sub-50 nm width regime results in poor scaling of the threshold current. Here, we show that current shunting t

Stanislav Komorovsky

Although the role of the electron paramagnetic resonance (EPR) g-tensor and hyperfine coupling tensor in the EPR effective spin Hamiltonian is discussed extensively in many textbooks, certain aspects of the theory are missing. In this text we will cover those gaps and thus provide a comprehensive theory about the existence of principal axes of the EPR tensor

Pengyao Xie, Zhihong Ma, Ruiming Du, Xin Yang

Fusion of 3D and MS imaging data has a great potential for high-throughput plant phenotyping of structural and biochemical as well as physiological traits simultaneously, which is important for decision support in agriculture and for crop breeders in selecting the best genotypes. However, lacking of 3D data integrity of various plant canopy structures and lo

A. V. Zlobin, I. Noviski, E. Barzi, P. Ferracin

This paper presents the design concept of the dipole magnet with 50 mm aperture, 20 T nominal field and 13% margin based on a six-layer cos-theta (CT) hybrid coil design. Due to the high stresses and strains in the coil at high field, Stress Management (SM) elements are implemented in the CT coil geometry. The results of magnet magnetic analysis are presente

A. V. Zlobin, I. Novitski, E. Barzi, B. R. Gamage

The design concept of the Electron Ion Collider (EIC), which is under construction at BNL, considers adding a 2nd Interaction Region (IR) and detector to the machine after completion of the present EIC project. Recent progress with development and fabrication of large-aperture high-field magnets based on the Nb3Sn technology for the HL-LHC makes this technol

J. R. Espinosa

An Euclidean bounce describing vacuum decay can be considered as an infinite stack of concentric thin shells to which a thin-wall action can be assigned. The integral over all shells produces then a tunneling action that is precisely the action functional in field space of the so-called tunneling potential formalism. This procedure, which works also when gra

Abdul-Hakeem Omotayo, Mai Gamal, Eman Ehab, Gbetondji Dovonon

Computer vision is a broad field of study that encompasses different tasks (e.g., object detection). Although computer vision is relevant to the African communities in various applications, yet computer vision research is under-explored in the continent and constructs only 0.06% of top-tier publications in the last ten years. In this paper, our goal is to ha

Maria Lazzaroni, Giorgia Chini, Francesco Draicchio, Christian Di Natali

Back-support exoskeletons are commonly used in the workplace to reduce low back pain risk for workers performing demanding activities. However, for the assistance of tasks differing from lifting, back-support exoskeletons potential has not been exploited extensively. This work focuses on the use of an active back-support exoskeleton to assist carrying. Two c

Oliver T. Oayda, Geraint F. Lewis

We present a novel test of the cosmological principle: the idea that, on sufficiently large scales, the universe should appear homogeneous and isotropic to observers comoving with the Hubble flow. This is a fundamental assumption in modern cosmology, underpinning the use of the Friedmann-Lema\^itre-Robertson-Walker metric as part of the concordance $\Lambda$

Jakub Rondoš

We present a necessary condition for a pair of $\mathcal{C}(K)$ spaces to be isomorphic in terms of topological properties of Cantor-Bendixon derivatives of $K$. This in particular gives a completely new information about the perfect kernels of such $K$. In the process, we extend known lower estimates of the Banach-Mazur distance between a pair of spaces of

Jingze Liu, Jiahao Ma

CRISPR-Cas13 is a system that utilizes single stranded RNAs for RNA editing. Prediction of on-target and off-target effects for the CRISPR-Cas13d dependency enables us to design specific single guide RNAs (sgRNAs) that help locate the desired RNA target positions. In this study, we compared the performance of multiple machine learning algorithms in predictin

Garreth Kemp

We discuss a generalized dominance ordering for irreducible representations of the symmetric group $S_{n}$ with the aim of distinguishing the corresponding states in the 1/2-BPS sector of $U(N)$ Super Yang-Mills theory when a certain finite number of Casimir operators are known. Having knowledge of a restricted set of Casimir operators was proposed as a mech

Scott Fredriksson, Akshit Saradagi, George Nikolakopoulos

This article presents a novel approach to identifying and classifying intersections for semantic and topological mapping. More specifically, the proposed novel approach has the merit of generating a semantically meaningful map containing intersections, pathways, dead ends, and pathways leading to unexplored frontiers. Furthermore, the resulting semantic map

Partiswari Maharana Sabita Sahoo

In the present paper, the random series $\sum\limits_{m=0}^\infty c_m C_m(\varpi)q_m^{(\zeta,\eta)}(u)$ in orthogonal Jacobi polynomials $q_m^{(\zeta,\eta)}(u)$ is discussed. The scalars $c_m$ are Fourier--Jacobi coefficients of a function in the weighted space $\mathrm{L}_{[-1,1]}^\mathrm{p}(d\mu_{\zeta,\eta}),\mathrm{p}>1.$ The random variables $C_m(\varpi

Mohammed Bachir, Rongzhen Lyu

We provide new results of first-order necessary conditions of optimality problem in the form of John's theorem and in the form of Karush-Kuhn-Tucker's theorem. We establish our result in a topological vector space for problems with inequality constraints and in a Banach space for problems with equality and inequality constraints. Our contributions consist in

Daniel Marris, Seeralan Sarvaharman, Luca Giuggioli

A variety of transport processes in natural and man-made systems are intrinsically random. To model their stochasticity, lattice random walks have been employed for a long time, mainly by considering Cartesian lattices. However, in many applications in bounded space the geometry of the domain may have profound effects on the dynamics and ought to be accounte

Stefan Höppner, Matthias Tichy

Dedicated model transformation languages are claimed to provide many benefits over the use of general purpose languages for developing model transformations. However, the actual advantages associated with the use of MTLs are poorly understood empirically. There is little knowledge and empirical assessment about what advantages and disadvantages hold and wher

Benjamin Reichenwallner, Peter Meerwald-Stadler

Malware code often resorts to various self-protection techniques to complicate analysis. One such technique is applying Mixed-Boolean Arithmetic (MBA) expressions as a way to create opaque predicates and diversify and obfuscate the data flow. In this work we aim to provide tools for the simplification of nonlinear MBA expressions in a very practical context

M. Fernández-Torreiro, J. A. Rubiño-Martín, C. H. López-Caraballo, R. T. Génova-Santos

Anomalous Microwave Emission (AME) is an important emission component between 10 and 60 GHz that is not yet fully understood. It seems to be ubiquituous in our Galaxy and is observed at a broad range of angular scales. Here we use the new QUIJOTE-MFI wide survey data at 11, 13, 17 and 19 GHz to constrain the AME in the Galactic plane ($|b|<10^\circ$) on degr

Gianluca Faraco, Guillaume Tahar, Yongquan Zhang

This paper describes the geometry and topology of leaves of the isoperiodic foliation of the stratum $\Omega\mathcal{M}_1(1,1,-2)$. We prove that each leaf is a surface of infinite genus homeomorphic to the Loch Ness monster surface and supports a singular Euclidean structure whose singularities correspond to isoperiodic forms in the lower stratum $\Omega\ma

Sujay Ray, Yuta Murakami, Philipp Werner

Superconductivity in laser-excited correlated electron systems has attracted considerable interest due to reports of light-induced superconducting-like states. Here we explore the possibility of non-thermal superconducting order in strongly interacting multi-orbital Hubbard systems, using non-equilibrium dynamical mean field theory. We find that a staggered

WenboWu, GangZhao, JiangChang, Xiang-XiangXue

In N-body simulations, nearly radial mergers can form shell-like overdensities in the sky position and phase space ($r-v_r$) due to the combination of dynamical friction and tidal stripping. The merger event of Gaia-Sausage-Enceladus has provided a unique opportunity to study the shells in the phase space. To search for them, we integrate the orbits of 5949

Jan Kretzschmar, Mira Pöhlker, Frank Stratmann, Heike Wex

The ability of pollen to enable the glaciation of supercooled liquid water has been demonstrated in laboratory studies; however, the potential large-scale effect of trees and pollen on clouds, precipitation and climate is pressing knowledge to better understand and project clouds in the current and future climate. Combining ground-based measurements of polle

H. Arslan, I. Aulika, A. Sarakovskis, L. Bikse

An experimental investigation was conducted to explore spectroscopic and structural characterization of semiconducting yttrium oxide thin film deposited at 623 K (+/- 5K) utilizing reactive pulsed direct current magnetron sputtering. Based on the results obtained from both x-ray diffraction and transmission electron microscope measurements, yttrium monoxide

E. Katsipoulaki, G. Vailakis, I. Demeridou, D. Karfaridis

Modulation of the Fermi level using an ultraviolet (UV)-assisted photochemical method is demonstrated in tungsten diselenide monolayers. Systematic shifts and relative intensities between charged and neutral exciton species indicate a progressive and controllable decrease of the electron density and switch tungsten diselenide from n-type to a p-type semicond

Jinyu Cai, Jialong Li, Mingyue Zhang, Kenji Tei

In this paper, we address the challenges faced by Value Iteration Networks (VIN) in handling larger input maps and mitigating the impact of accumulated errors caused by increased iterations. We propose a novel approach, Value Iteration Networks with Gated Summarization Module (GS-VIN), which incorporates two main improvements: (1) employing an Adaptive Itera

Hyeok Kyu Kwon, Minwoo Chae

A deep generative model yields an implicit estimator for the unknown distribution or density function of the observation. This paper investigates some statistical properties of the implicit density estimator pursued by VAE-type methods from a nonparametric density estimation framework. More specifically, we obtain convergence rates of the VAE-type density es

Fanny Jourdan, Agustin Picard, Thomas Fel, Laurent Risser

Transformer architectures are complex and their use in NLP, while it has engendered many successes, makes their interpretability or explainability challenging. Recent debates have shown that attention maps and attribution methods are unreliable (Pruthi et al., 2019; Brunner et al., 2019). In this paper, we present some of their limitations and introduce COCK

Philipp Sepin, Jana Kemnitz, Safoura Rezapour Lakani, Daniel Schall

Vibration-based condition monitoring systems are receiving increasing attention due to their ability to accurately identify different conditions by capturing dynamic features over a broad frequency range. However, there is little research on clustering approaches in vibration data and the resulting solutions are often optimized for a single data set. In this

Xing Zhang, Bo Wang, Rui Niu

In this paper, we focus on the general free scalar-tensor gravity with three free coupling functions, which in the near-field region looks like general relativity (GR) plus a fifth force of Yukawa-type induced by the scalar field. We show that the fifth force is always attractive in the theory. We investigate the effects of the attractive fifth force and cal

Đorđe Dangić, Peio Garcia-Goiricelaya, Yue-Wen Fang, Julen Ibañez-Azpiroz

The recent report of near-ambient conditions superconductivity in a nitrogen-doped lutetium hydride has inspired a large number of experimental studies with contradictory results. We model from first principles the physical properties of the possible parent structures of the reported superconductor, LuH$_2$ and LuH$_3$. We show that only the phonon band stru

Andreas Henrik Frederiksen, Ole Sigmund, Konstantinos Poulios

Inclusion of contact in mechanical designs opens a large range of design possibilities, this includes classical designs with contact, such as gears, couplings, switches, clamps etc. However, incorporation of contact in topology optimization is challenging, as classical contact models are not readily applicable when the boundaries are not defined. This paper

Ricardo Alonso, Milana Pavić-Čolić

This paper explores the $L^{p}$ Lebesgue's integrability propagation, $p\in(1,\infty]$, of a system of space homogeneous Boltzmann equations modelling a multi-component mixture of polyatomic gases based on the continuous internal energy. For typical collision kernels proposed in the literature, $L^p$ moment-entropy-based estimates for the collision operator

Pramit Rej, Abdelghani Errehymy, Mohammed Daoud

In this article, we provide a new model of static charged anisotropic fluid sphere made of a charged perfect fluid in the context of 5D Einstein-Maxwell-Gauss-Bonnet (EMGB) gravity theory. To generate exact solutions of the EMGB field equations, we utilize the well-behaved Tolman-Kuchowicz (TK) {\it ansatz} together with a linear equation of state (EoS) of t

Zina Kamal, Hossein Hassani

Kurdish Sign Language (KuSL) is the natural language of the Kurdish Deaf people. We work on automatic translation between spoken Kurdish and KuSL. Sign languages evolve rapidly and follow grammatical rules that differ from spoken languages. Consequently,those differences should be considered during any translation. We proposed an avatar-based automatic trans

A. Bharali, Mohammad Essa Nazari, Amanullah Nabavi

To avoid extensive lab work on properties of chemical compounds, QSPR/QSAR analysis for topological descriptors is a productive statistical approach to analyze various physicochemical properties of chemical compounds. Many researchers have investigated on correlation of degree-based topological descriptors. In this article we present the predictive ability o

Oscar Corcho, Fajar J. Ekaputra, Ivan Heibi, Clement Jonquet

This work presents a maturity model for assessing catalogues of semantic artefacts, one of the keystones that permit semantic interoperability of systems. We defined the dimensions and related features to include in the maturity model by analysing the current literature and existing catalogues of semantic artefacts provided by experts. In addition, we assess

Lorenzo Tausani, Alberto Testolin, Marco Zorzi

Generative neural networks can produce data samples according to the statistical properties of their training distribution. This feature can be used to test modern computational neuroscience hypotheses suggesting that spontaneous brain activity is partially supported by top-down generative processing. A widely studied class of generative models is that of Re

Federico L. Bottesi, Guillermo R. Zemba

The effective field theory of the Calogero-Sutherland model represents a universality class of quantum hydrodynamic fluids in one spatial dimension. It describes quantum compressible fluids involving both chiralities in which the chiral density field obeys the quantum Benjamin-Ono equation. An extension of this theory to describe a laminar flow of the Caloge

Yuriy Dorn, Nikita Kornilov, Nikolay Kutuzov, Alexander Nazin

The Implicitly Normalized Forecaster (INF) algorithm is considered to be an optimal solution for adversarial multi-armed bandit (MAB) problems. However, most of the existing complexity results for INF rely on restrictive assumptions, such as bounded rewards. Recently, a related algorithm was proposed that works for both adversarial and stochastic heavy-taile

E. Delgado de las Heras, F. J. Martinez-Murcia, I. A. Illán, C. Jiménez-Mesa

This work proposes the use of 3D convolutional variational autoencoders (CVAEs) to trace the changes and symptomatology produced by neurodegeneration in Parkinson's disease (PD). In this work, we present a novel approach to detect and quantify changes in dopamine transporter (DaT) concentration and its spatial patterns using 3D CVAEs on Ioflupane (FPCIT) ima

Ahmad Al-Badawi

In this paper, we study the greybody factors (GFs) for fermions with different spins and bosons in the regular black hole (BH) predicted by a non-minimal Einstein-Yang-Mills (EYM) theory. We investigate the effect of magnetic charge on effective potentials and GFs. For this purpose, we consider the Dirac and Rarita-Schwinger, as well as Klein-Gordon equation

Huriyyah Althunayan, Rahaf Bahlas, Manar Alharbi, Lena Alsuwailem

Toxic language is difficult to define, as it is not monolithic and has many variations in perceptions of toxicity. This challenge of detecting toxic language is increased by the highly contextual and subjectivity of its interpretation, which can degrade the reliability of datasets and negatively affect detection model performance. To fill this void, this pap

Pengming Wang, Mikita Sazanovich, Berkin Ilbeyi, Phitchaya Mangpo Phothilimthana

Resource scheduling and allocation is a critical component of many high impact systems ranging from congestion control to cloud computing. Finding more optimal solutions to these problems often has significant impact on resource and time savings, reducing device wear-and-tear, and even potentially improving carbon emissions. In this paper, we focus on a spec

Feng-Lei Fan, Ze-Yu Li, Huan Xiong, Tieyong Zeng

In this work, beyond width and depth, we augment a neural network with a new dimension called height by intra-linking neurons in the same layer to create an intra-layer hierarchy, which gives rise to the notion of height. We call a neural network characterized by width, depth, and height a 3D network. To put a 3D network in perspective, we theoretically and

V. V. Flambaum

According to the Schiff theorem, an external electric field vanishes at atomic nucleus in a neutral atom in a stationary state, i.e. it is completely shielded by electrons. This makes a nuclear electric dipole moment (EDM) unobservable. We show that if atom or molecule is not in a stationary state (e.g. in a superposition of two stationary states), electric

Jingge Xiao, Leonie Basso, Wolfgang Nejdl, Niloy Ganguly

Continuous-time models such as Neural ODEs and Neural Flows have shown promising results in analyzing irregularly sampled time series frequently encountered in electronic health records. Based on these models, time series are typically processed with a hybrid of an initial value problem (IVP) solver and a recurrent neural network within the variational autoe

Taikei Fujii, Takahiko Nobukawa, Tatsushi Shimazaki

Set-valued tableaux, introduced by Buch to express the tableaux-sum formula for stable Grothendieck polynomials, generalize semistandard tableaux. We provide a new recursive proof that the number of set-valued tableaux of a given shape is odd.

Seok Bin Son, Soohyun Park, Joongheon Kim

Clustering data is an unsupervised learning approach that aims to divide a set of data points into multiple groups. It is a crucial yet demanding subject in machine learning and data mining. Its successful applications span various fields. However, conventional clustering techniques necessitate the consideration of balance significance in specific applicatio

Veronika Spieker, Hannah Eichhorn, Kerstin Hammernik, Daniel Rueckert

Motion represents one of the major challenges in magnetic resonance imaging (MRI). Since the MR signal is acquired in frequency space, any motion of the imaged object leads to complex artefacts in the reconstructed image in addition to other MR imaging artefacts. Deep learning has been frequently proposed for motion correction at several stages of the recons

Samik Basu, Aloke Kr. Ghosh

We construct sphere fibrations over $(n-1)$-connected $2n$-manifolds such that the total space is a connected sum of sphere products. More precisely, for $n$ even, we construct fibrations $S^{n-1} \to \#^{k-1}(S^n \times S^{2n-1}) \to M_k$, where $M_k$ is a $(n-1)$-connected $2n$-dimensional Poincar\'{e} duality complex which satisfies $H_n(M_k)\cong \mathbb

Chaorui Yao, Pavlos Nikolopoulos, Christina Fragouli

Group testing enables to identify infected individuals in a population using a smaller number of tests than individual testing. To achieve this, group testing algorithms commonly assume knowledge of the number of infected individuals; nonadaptive and several adaptive algorithms fall in this category. Some adaptive algorithms, like binary splitting, operate w

Mohammed Bachir, Joel Blot

We give a general Lagrange multiplier rule for mathematical programming problems in a Hausdorff locally convex space. We consider infinitely many inequality and equality constraints. Our results gives in particular a generalisation of the result of J. Jahn in \cite{Ja}, replacing Fr\'echet-differentiability assumptions on the functions by the Gateaux-differe

Zhilan Yang, Haoyue Zhang, Peng Xu, Ziren Luo

Onboard electrostatic suspension inertial sensors are important applications for gravity satellites and space gravitational wave detection missions, and it is important to suppress noise in the measurement signal. Due to the complex coupling between the working space environment and the satellite platform, the process of noise generation is extremely complex

Kacper Wrześniewski, Tomasz Ślusarski, Ireneusz Weymann

Dynamical buildup of spin-singlet correlations between the two quantum dots is investigated by means of the time-dependent numerical renormalization group method. By calculating the timeevolution of the spin-spin expectation value upon a quench in the hopping between the quantum dots, we examine the time scales associated with the development of an entangled

Diego Castro, Franck Ruffier, Christophe Eloy

Animal collective behavior is often modeled with self-propelled particles, assuming each individual has ``omniscient'' knowledge of its neighbors. Yet, neighbors may be hidden from view and we do not know the effect of this information loss. To address this question, we propose a visual model of collective behavior where each particle moves according to bio-

Eleonore Bach, Friedrich Eisenbrand, Rom Pinchasi

An integer vector $b \in \mathbb{Z}^d$ is a degree sequence if there exists a hypergraph with vertices $\{1,\dots,d\}$ such that each $b_i$ is the number of hyperedges containing $i$. The degree-sequence polytope $\mathscr{Z}^d$ is the convex hull of all degree sequences. We show that all but a $2^{-\Omega(d)}$ fraction of integer vectors in the degree seque

Alessandro Pianelli, Rakesh Dhama, Jaroslaw Judek, Rafal Mazur

All-optical ultrafast switches enabled by artificial materials are considered at the forefront of the next generation of photonic communications and data processing. During the last two decades, the photonic applications, impact, and interest have tremendously increased in the framework of epsilon-near-zero (ENZ) photonics. Here, we experimentally propose a

José Figueroa-O'Farrill, Alfredo Pérez, Stefan Prohazka

We exploit the close relationship between the Carroll and fracton/dipole algebras, together with the method of coadjoint orbits, to define and classify classical Carroll and fracton particles. This approach establishes a Carroll/fracton correspondence and provides an answer to the question "What is a fracton?". Under this correspondence, carrollian energy an

Emma Kun, Imre Bartos, Julia Becker Tjus, Peter L. Biermann

Tensions between the diffuse gamma-ray sky observed by the Fermi Large Area Telescope (LAT) and the diffuse high-energy neutrino sky detected by the IceCube South Pole Neutrino Observatory question our knowledge about high-energy neutrino sources in the gamma-ray regime. While blazars are among the most energetic persistent particle accelerators in the Unive

María Gómez-Rocha, Jai More, Kamil Serafin

We apply the renormalization group procedure for effective particles (RGPEP) to the QCD eigenvalue problem for only heavy quarks. We derive the effective Hamiltonian that acts on the Fock space by solving the RGPEP equation up to second order in powers of the coupling constant. The eigenstates that contain three quarks and two or more gluons are eliminated b

Inge S. Helland

The final version of a new approach to quantum theory is formulated in this paper. The basis is taken to be theoretical variables, variables that may be accessible or inaccessible, i.e., it may be possible or impossible for an observer to assign arbitrarily sharp numerical values to them. In an epistemic process, the accessible variables are just ideal obser

Jan Hombeck, Monique Meuschke, Simon Lieb, Nils Lichtenberg

In recent years, the use of expressive surface visualizations in the representation of vascular structures has gained significant attention. These visualizations provide a comprehensive understanding of complex anatomical structures and are crucial for treatment planning and medical education. However, to aid decision-making, physicians require visualization

A. D. Leu, M. F. Gely, M. A. Weber, M. C. Smith

We use electronic microwave control methods to implement addressed single-qubit gates with high speed and fidelity, for $^{43}\text{Ca}^{+}$ hyperfine "atomic clock" qubits in a cryogenic (100K) surface trap. For a single qubit, we benchmark an error of $1.5$ $\times$ $10^{-6}$ per Clifford gate (implemented using $600~\text{ns}$ $\pi/2$-pulses). For two qub

Thomas Thiemann

Vielbeins are necessary when coupling General Relativity (GR) to fermionic matter. This enhances the gauge group of GR to include local Lorentz transformations. In view of a reduced phase space formulation of quantum gravity, in this work we completely gauge fix that Lorentz gauge symmetry by using a so-called triangular gauge. Having solved the Gauss constr

Ramgopal Agrawal, Federico Corberi, Eugenio Lippiello, Sanjay Puri

We investigate the influence of long-range (LR) interactions on the phase ordering dynamics of the one-dimensional random field Ising model (RFIM). Unlike the usual RFIM, a spin interacts with all other spins through a ferromagnetic coupling that decays as $r^{-(1+\sigma)}$, where $r$ is the distance between two spins. In the absence of LR interactions, the

Marco Falconi, Jonas Lampart, Nikolai Leopold, David Mitrouskas

We consider the time evolution of the renormalized Nelson model, which describes $N$ bosons linearly coupled to a quantized scalar field, in the mean-field limit of many particles $N\gg 1$ with coupling constant proportional to $N^{-1/2}$. First, we show that initial states exhibiting Bose-Einstein condensation for the particles and approximating a coherent

João Rodrigues, Luís Gomes, João Silva, António Branco

To advance the neural encoding of Portuguese (PT), and a fortiori the technological preparation of this language for the digital age, we developed a Transformer-based foundation model that sets a new state of the art in this respect for two of its variants, namely European Portuguese from Portugal (PT-PT) and American Portuguese from Brazil (PT-BR). To devel