July 2023 arXiv papers — page 48

Dongyao Zhu, Bowen Lei, Jie Zhang, Yanbo Fang

Neural networks trained on distilled data often produce over-confident output and require correction by calibration methods. Existing calibration methods such as temperature scaling and mixup work well for networks trained on original large-scale data. However, we find that these methods fail to calibrate networks trained on data distilled from large source

Jack Jon Hinsch, Assil Bouzid, Jordan Clive Barker, Jessica Jein White

The electrified solid-liquid interface plays an essential role in many renewable energy-related applications, including hydrogen production and utilization. Limitations in computational modelling of the electrified solid-liquid interface have held back the understanding of its properties at the atomic-scale level. In this study, we applied the grand canonica

Tong Mao, Ding-Xuan Zhou

Neural networks activated by the rectified linear unit (ReLU) play a central role in the recent development of deep learning. The topic of approximating functions from H\"older spaces by these networks is crucial for understanding the efficiency of the induced learning algorithms. Although the topic has been well investigated in the setting of deep neural ne

Brendan Wernisch, Mohammed Al Otmi, Egan Beauvais, Janani Sampath

Amorphous polymers are considered promising materials for separations due to their excellent transport properties and low fabrication costs. The separation performance of a membrane material is characterized by its permeability (overall throughput of components), and selectivity (efficiency of separation). Both permeability and selectivity are controlled by

Yunseung Lee, Youngjun Kwak, Jinho Shin

Owing to the advances in image processing technology and large-scale datasets, companies have implemented facial authentication processes, thereby stimulating increased focus on face anti-spoofing (FAS) against realistic presentation attacks. Recently, various attempts have been made to improve face recognition performance using both global and local learnin

Wenwu Jiang, Reut Sofer, Xiang Gao, Alexandre Tkatchenko

An anisotropic interlayer force field that describes the interlayer interactions in homogeneous and heterogeneous interfaces of group-VI transition metal dichalcogenides (MX2 where M = Mo, W and X = S, Se) is presented. The force field is benchmarked against density functional theory calculations for bilayer systems within the Heyd-Scuseria-Ernzerhof hybrid

Urban Larsson, Indrajit Saha, Makoto Yokoo

This paper concerns two-player alternating play combinatorial games (Conway 1976) in the normal-play convention, i.e. last move wins. Specifically, we study impartial vector subtraction games on tuples of nonnegative integers (Golomb 1966), with finite subtraction sets. In case of two move rulesets we find a complete solution, via a certain $\mathcal{P}$-to-

Majid Mahzoon, Ali Shourideh, Ariel Zetlin-Jones

We study the classic principal-agent model when the signal observed by the principal is chosen by the agent. We fully characterize the optimal information structure from an agent's perspective in a general moral hazard setting with limited liability. Due to endogeneity of the contract chosen by the principal, the agent's choice of information is non-trivial.

Futoshi Futami, Tomoharu Iwata

Bayesian inference is often utilized for uncertainty quantification tasks. A recent analysis by Xu and Raginsky 2022 rigorously decomposed the predictive uncertainty in Bayesian inference into two uncertainties, called aleatoric and epistemic uncertainties, which represent the inherent randomness in the data-generating process and the variability due to insu

Julian Roth, Martyna Soszyńska, Thomas Richter, Thomas Wick

In this work, we propose and computationally investigate a monolithic space-time multirate scheme for coupled problems. The novelty lies in the monolithic formulation of the multirate approach as this requires a careful design of the functional framework, corresponding discretization, and implementation. Our method of choice is a tensor-product Galerkin spac

Ulrich Berger, Hideki Tsuiki

We present a logical system CFP (Concurrent Fixed Point Logic) supporting the extraction of nondeterministic and concurrent programs that are provably total and correct. CFP is an intuitionistic first-order logic with inductive and coinductive definitions extended by two propositional operators: Restriction (binary), a strengthening of implication, and a una

Minghan Chu, Weicheng Qian

Reliable prediction of turbulent flows is an important necessity across different fields of science and engineering. In Computational Fluid Dynamics (CFD) simulations, the most common type of models are eddy viscosity models that are computationally inexpensive but introduce a high degree of epistemic error. The Eigenspace Perturbation Method (EPM) attempts

R. Y. Su, J. Y. Huang, N. Dumoulin. Stuyck, M. K. Feng

To push gate performance to levels beyond the thresholds for quantum error correction, it is important to characterize the error sources occurring on quantum gates. However, the characterization of non-Markovian error poses a challenge to current quantum process tomography techniques. Fast Bayesian Tomography (FBT) is a self-consistent gate set tomography pr

Michael S. Jones, Kirill Shmilovich, Andrew L. Ferguson

Coarse-grained molecular models of proteins permit access to length and time scales unattainable by all-atom models and the simulation of processes that occur on long-time scales such as aggregation and folding. The reduced resolution realizes computational accelerations but an atomistic representation can be vital for a complete understanding of mechanistic

Hansol Kim, Youngjun Kwak, Minyoung Jung, Jinho Shin

Federated learning (FL) is a promising approach for enhancing data privacy preservation, particularly for authentication systems. However, limited round communications, scarce representation, and scalability pose significant challenges to its deployment, hindering its full potential. In this paper, we propose 'ProtoFL', Prototypical Representation Distillati

Vu Nguyen

Wellbore friction is one of the biggest concerns when drilling due to its relation to the total cost. The catenary concept was introduced to reduce wellbore friction, but it requires detailed analyses. This project would fill this gap. A catenary shape is simply the natural shape of a rope, chain, or drill string. The drill string will then hang freely insid

Satwik Kundu, Debarshi Kundu, Swaroop Ghosh

The exponential run time of quantum simulators on classical machines and long queue times and high costs of real quantum devices present significant challenges in the efficient optimization of Variational Quantum Algorithms (VQAs) like Variational Quantum Eigensolver (VQE), Quantum Approximate Optimization Algorithm (QAOA) and Quantum Neural Networks (QNNs).

Eric Leu

Consistent hashing is a technique that can minimize key remapping when the number of hash buckets changes. The paper proposes a fast consistent hash algorithm (called power consistent hash) that has $O(1)$ expected time for key lookup, independent of the number of buckets. Hash values are computed in real time. No search data structure is constructed to stor

Mateusz Łącki, Jakub Zakrzewski

A construction of a quasi-random potential for cold atoms using dark states emerging in $\Lambda$ {level configuration} is proposed. Speckle laser fields are used as a source of randomness. Anderson localisation in such potentials is studied and compared with the known results for the speckle potential itself. It is found out that the localisation length is

Bio Wahabou Kpera, Vincent Lahoche, Dine Ousmane Samary, Seke Fawaaz Zime Yerima

The Ward-Takahashi identities are considered as the generalization of the Noether currents available to quantum field theory and include quantum fluctuation effects. Usually, they take the form of relations between correlation functions, which ultimately correspond to the relation between coupling constants of the theory. For this reason, they play a central

Ivan Vallés-Pérez, Grzegorz Beringer, Piotr Bilinski, Gary Cook

Numerous examples in the literature proved that deep learning models have the ability to work well with multimodal data. Recently, CLIP has enabled deep learning systems to learn shared latent spaces between images and text descriptions, with outstanding zero- or few-shot results in downstream tasks. In this paper we explore the same idea proposed by CLIP bu

Brendan Keith, Thomas M. Surowiec

The proximal Galerkin finite element method is a high-order, low-iteration complexity, nonlinear numerical method that preserves the geometric and algebraic structure of point-wise bound constraints in infinite-dimensional function spaces. This paper introduces the proximal Galerkin method and applies it to solve free boundary problems, enforce discrete maxi

Rick Jeuken, Michael Forbes

This article describes a novel approach to chance-constrained programming based on the sample average approximation (SAA) method. Recent work focuses on heuristic approximations to the SAA problem and we introduce a novel approach which improves on some existing methods. Our Active Set method allows one to solve SAAs of chance-constrained programs with very

Amirhossein Aminimehr, Amirali Molaei, Erik Cambria

Scene recognition based on deep-learning has made significant progress, but there are still limitations in its performance due to challenges posed by inter-class similarities and intra-class dissimilarities. Furthermore, prior research has primarily focused on improving classification accuracy, yet it has given less attention to achieving interpretable, prec

Eitan Tadmor, Anil Zenginoglu

We extend our study of the swarm-based gradient descent method for non-convex optimization, [Lu, Tadmor & Zenginoglu, arXiv:2211.17157], to allow random descent directions. We recall that the swarm-based approach consists of a swarm of agents, each identified with a position, ${\mathbf x}$, and mass, $m$. The key is the transfer of mass from high ground to l

Hanliang Guo, Yi Man, Hai Zhu

Many micro-swimmers propel themselves by rotating micro-cylindrical organelles such as flagella or cilia. These cylindrical organelles almost never live in free space, yet their motions in a confining geometry can be counter-intuitive. For example, one of the intriguing yet classical results in this regard is that a rotating cylinder next to a plane wall doe

Mahmoud Sesa, Hagen Holthusen, Lukas Lamm, Christian Böhm

The development of tissue-engineered cardiovascular implants can improve the lives of large segments of our society who suffer from cardiovascular diseases. Regenerative tissues are fabricated using a process called tissue maturation. Furthermore, it is highly challenging to produce cardiovascular regenerative implants with sufficient mechanical strength to

Aimee Maurais, Terrence Alsup, Benjamin Peherstorfer, Youssef Marzouk

We introduce a multifidelity estimator of covariance matrices formulated as the solution to a regression problem on the manifold of symmetric positive definite matrices. The estimator is positive definite by construction, and the Mahalanobis distance minimized to obtain it possesses properties enabling practical computation. We show that our manifold regress

Richard F. Bass, Krzysztof Burdzy

For $f: [0,1]\to \mathbb R$, we consider $L^f_t$, the local time of space-time Brownian motion on the curve $f$. Let ${\cal S}_\alpha$ be the class of all functions whose H\"older norm of order $\alpha$ is less than or equal to 1. We show that the supremum of $L^f_1$ over $f$ in ${\cal S}_\alpha$ is finite if $\alpha>\frac12$.

Oleg Balakhnov, Sergei Savin, Alexandr Klimchik

Explicit model-predictive control (MPC) is a widely used control design method that employs optimization tools to find control policies offline; commonly it is posed as a semi-definite program (SDP) or as a mixed-integer SDP in the case of hybrid systems. However, mixed-integer SDPs are computationally expensive, motivating alternative formulations, such as

Samapan Bhadury, Arpan Das, Wojciech Florkowski, Gowthama K. K.

Semiclassical expansion of the Wigner function for spin-1/2 fermions having an effective spacetime-dependent mass is used to analyze spin-polarization effects. The existing framework is reformulated to obtain a differential equation directly connecting the particle spin tensor with the effective mass. It reflects the conservation of the total angular momentu

Shamsulhaq Basir, Inanc Senocak

We present a meshless Schwarz-type non-overlapping domain decomposition method based on artificial neural networks for solving forward and inverse problems involving partial differential equations (PDEs). To ensure the consistency of solutions across neighboring subdomains, we adopt a generalized Robin-type interface condition, assigning unique Robin paramet

P. Gambardella, S. S. Dhesi, Sandra Gardonio, Cesare Grazioli

X-ray absorption spectroscopy (XAS) and x-ray magnetic circular dichroism (XMCD) have been used to study transition metal impurities on K and Na films. The multiplet structure of the XAS spectra indicates that Fe, Co, and Ni have localized atomic ground states with predominantly d7, d8, and d9 character, respectively. XMCD shows that the localized impurity s

A. Rod Gover, Matthew J. Gursky

Let $(M^4,g)$ be a smooth, closed, oriented anti-self-dual (ASD) four-manifold. $(M^4,g)$ is said to be unobstructed if the cokernel of the linearization of the self-dual Weyl tensor is trivial. This condition can also be characterized as the vanishing of the second cohomology group of the ASD deformation complex, and is central to understanding the local st

Santiago Correa

In this paper, we discuss energy estimates for a particular class of linear hyperbolic boundary value problems known as weakly regular of real type. Such class, also called WR in the literature, is relevant in many physical situations like the formation of shock waves in isentropic gas dynamics. In this and other WR examples, the failure of the uniform Lopat

David Cushing, David I. Stewart

We develop and deploy a set of constraints for the purpose of calculating minimal sizes of lottery designs. Specifically, we find the minimum number of tickets of size six which are needed to match at least two balls on any draw of size six, whenever there are at most 70 balls.

Yejia Zhang, Pengfei Gu, Nishchal Sapkota, Danny Z. Chen

Modern medical image segmentation methods primarily use discrete representations in the form of rasterized masks to learn features and generate predictions. Although effective, this paradigm is spatially inflexible, scales poorly to higher-resolution images, and lacks direct understanding of object shapes. To address these limitations, some recent works util

Jiten Dhandha, Zoe Faes, Rowan J. Smith

The fragmentation of gas to form stars in molecular clouds is intrinsically linked to the turbulence within them. These internal motions are set at the birth of the cloud and may vary with galactic environment and as the cloud evolves. In this paper, we introduce a new suite of 15 high-resolution 3D molecular cloud simulations using the moving mesh code AREP

Liu Yuyang, Cong Yang, Goswami Dipam, Liu Xialei

In incremental learning, replaying stored samples from previous tasks together with current task samples is one of the most efficient approaches to address catastrophic forgetting. However, unlike incremental classification, image replay has not been successfully applied to incremental object detection (IOD). In this paper, we identify the overlooked problem

Thomas A. Ryttov, Robert Shrock

We present scheme-independent calculations of the anomalous dimensions $\gamma_{\bar\psi\psi,IR}$ and $\gamma_{\bar\chi\chi,IR}$ of fermion bilinear operators $\bar\psi\psi$ and $\bar\chi\chi$ at an infrared fixed point in an asymptotically free SU($N_c$) gauge theory with massless Dirac fermion content consisting of $N_F$ fermions $\psi^a_i$ in the fundamen

Paloma Sodhi, Felix Wu, Ethan R. Elenberg, Kilian Q. Weinberger

A common training technique for language models is teacher forcing (TF). TF attempts to match human language exactly, even though identical meanings can be expressed in different ways. This motivates use of sequence-level objectives for dialogue response generation. In this paper, we study the efficacy of various offline reinforcement learning (RL) methods t

Rana Shahout, Yehonatan Peisakhovsky, Sasha Stoikov, Nikhil Garg

Recommendation systems rely on user-provided data to learn about item quality and provide personalized recommendations. An implicit assumption when aggregating ratings into item quality is that ratings are strong indicators of item quality. In this work, we test this assumption using data collected from a music discovery application. Our study focuses on two

Colby C. Haggerty, Damiano Caprioli, Paul A. Cassak, M. Hasan Barbhuiya

Collisionless plasma shocks are a common feature of many space and astrophysical systems and are sources of high-energy particles and non-thermal emission, channeling as much as 20\% of the shock's energy into non-thermal particles. The generation and acceleration of these non-thermal particles have been extensively studied, however, how these particles feed

Aikaterini-Panagiota Stouka, Thomas Zacharias

One of the most important features of blockchain protocols is decentralization, as their main contribution is that they formulate a distributed ledger that will be maintained and extended without the need of a trusted party. Bitcoin has been criticized for its tendency to centralization, as very few pools control the majority of the hashing power. Pass et al

A. Grazian, K. Boutsia, E. Giallongo, S. Cristiani

One of the key open questions in Cosmology is the nature of the sources that completed the cosmological hydrogen Reionization at z~5.2. High-z primeval galaxies have been long considered the main drivers for Reionization, with a minor role played by high-z AGN. However, in order to confirm this scenario, it is fundamental to measure the photo-ionization rate

James T. Liu, Robert J. Saskowski

We consider the torus reduction of heterotic supergravity in the presence of four-derivative corrections. In particular, the reduction on $T^n$ generically leads to a half-maximal supergravity coupled to $n$ vector multiplets, and we show that it is consistent to truncate out said vector multiplets. This is done by the analysis of both the bosonic equations

Giedre Sabaliauskaite, Annabella Loconsole, Emelie Engström, Michael Unterkalmsteiner

[Context and motivation] When developing software, coordination between different organizational units is essential in order to develop a good quality product, on time and within budget. Particularly, the synchronization between requirements and verification processes is crucial in order to assure that the developed software product satisfies customer requir

Jiangrui Zheng, Xueqing Liu, Guanqun Yang, Mirazul Haque

To protect users from massive hateful content, existing works studied automated hate speech detection. Despite the existing efforts, one question remains: do automated hate speech detectors conform to social media content policies? A platform's content policies are a checklist of content moderated by the social media platform. Because content moderation rule

Kasidis Arunruangsirilert, Jiro Katto

While 5G New Radio (NR) networks offer significant uplink throughput improvements, these gains are primarily realized when User Equipment (UE) connects to high-frequency millimeter wave (mmWave) bands. The growing demand for uplink-intensive applications, such as real-time UHD 4K/8K video streaming and Virtual Reality (VR)/Augmented Reality (AR) content, hig

Anish Mall, Sanchit Kabra, Ankur Lhila, Pawan Ajmera

This research paper presents AMaizeD: An End to End Pipeline for Automatic Maize Disease Detection, an automated framework for early detection of diseases in maize crops using multispectral imagery obtained from drones. A custom hand-collected dataset focusing specifically on maize crops was meticulously gathered by expert researchers and agronomists. The da

Xiangyue Liu, Weiqi Wang, Jesús Pérez-Ríos

In this work, we present a general machine learning approach for full-dimensional potential energy surfaces for tetra-atomic systems. Our method employs an active learning scheme trained on {\it ab initio} points, which size grows based on the accuracy required. The training points are selected based on molecular dynamics simulations, choosing the most suita

Sophie Chemla

Let $k$ be a field of positive characteristic $p>2$. We prove a duality property concerning the kernel of coinduced representations of Lie superalgebras. This property was already proved by M. Duflo for Lie algebras in any characteristic under more restrictive finiteness conditions. It was then generalized to Lie superalgebras in characteristic 0 in previous

Henrik Wiechers, Markus Zobel, Marina Bennati, Igor Tkach

ENDOR spectroscopy is an important tool to determine the complicated three-dimensional structure of biomolecules and in particular enables measurements of intramolecular distances. Usually, spectra are determined by averaging the data matrix, which does not take into account the significant thermal drifts that occur in the measurement process. In contrast, w

Dalibor Pražák, Michael Zelina

We consider incompressible Navier-Stokes equations in a bounded 2D domain, complete with the so-called dynamic slip boundary conditions. Assuming that the data are regular, we show that weak solutions are strong. As an application, we provide an explicit upper bound of the fractal dimension of the global attractor in terms of the physical parameters. These e

Alexander Jarosik, Hajnalka Nádasi, Michael Schwidder, Atsutaka Manabe

We demonstrate an exceptional ability of a high-polarisation 3D ferroelectric liquid to form freely-suspended fluid fibres at room temperature. Unlike fluid threads in modulated smectics and columnar phases, where translational order is a prerequisite for forming liquid fibres, recently discovered ferroelectric nematic forms fibres with solely orientational

Manasvi Lingam, Andreas M. Hein, T. Marshall Eubanks

Nomadic worlds, i.e., objects not gravitationally bound to any star(s), are of great interest to planetary science and astrobiology. They have garnered attention recently due to constraints derived from microlensing surveys and the recent discovery of interstellar planetesimals. In this paper, we roughly estimate the prevalence of nomadic worlds with radii o

F. H. L. Essler, A. J. J. M. de Klerk

We study the statistics of matrix elements of local operators in the basis of energy eigenstates in a paradigmatic integrable many-particle quantum theory, the Lieb-Liniger model of bosons with repulsive delta-function interaction. Using methods of quantum integrability we determine the scaling of matrix elements with system size. As a consequence of the ext

Dimitris Bertsimas, Cheol Woo Kim

We propose an approach based on machine learning to solve two-stage linear adaptive robust optimization (ARO) problems with binary here-and-now variables and polyhedral uncertainty sets. We encode the optimal here-and-now decisions, the worst-case scenarios associated with the optimal here-and-now decisions, and the optimal wait-and-see decisions into what w

Yusen Long

This paper uses the renowned Kechris-Pestov-Todor\v{c}evi\'{c} machinery to show that (big) mapping class groups are not extremely amenable unless the underlying surface is a sphere or a once-punctured sphere, or equivalently when the mapping class group is trivial. The same techniques also show that the pure mapping class groups, as well as compactly suppor

Rafael Pastrana, Deniz Oktay, Ryan P. Adams, Sigrid Adriaenssens

We introduce JAX FDM, a differentiable solver to design mechanically efficient shapes for 3D structures conditioned on target architectural, fabrication and structural properties. Examples of such structures are domes, cable nets and towers. JAX FDM solves these inverse form-finding problems by combining the force density method, differentiable sparsity and

Gianmaria Falasco, Massimiliano Esposito

Starting at the mesoscopic level with a general formulation of stochastic thermodynamics in terms of Markov jump processes, we identify the scaling conditions that ensure the emergence of a (typically nonlinear) deterministic dynamics and an extensive thermodynamics at the macroscopic level. We then use large deviations theory to build a macroscopic fluctuat

Aiqin Yang, Xiangru Tao, Yundi Quan, Peng Zhang

Motivated by advances in hydrogen-rich superconductors in the past decades, we conducted variable-composition structural searches in Mo-H binary system at high pressure. A new composition-pressure phase diagram of thermodynamically stable structures has been derived. Besides all previously discovered superconducting molybdenum hydrides, we also identified se

Shubham Kanodia, Andrea S. J. Lin, Emily Lubar, Samuel Halverson

NEID is a high-resolution red-optical precision radial velocity (RV) spectrograph recently commissioned at the WIYN 3.5 m telescope at Kitt Peak National Observatory, Arizona, USA. NEID has an extremely stable environmental control system, and spans a wavelength range of 380 to 930 nm with two observing modes: a High Resolution (HR) mode at R $\sim$ 112,000

Astrid Rakow

We are in the process of building complex highly autonomous systems that have build-in beliefs, perceive their environment and exchange information. These systems construct their respective world view and based on it they plan their future manoeuvres, i.e., they choose their actions in order to establish their goals based on their prediction of the possible

Omar Antolín Camarena, Andrés Carnero Bravo

It was conjectured by Goyal, Shukla and Singh that the independence complex of the categorical product $K_2\times K_3\times K_n$ has the homotopy type of a wedge of $(n-1)(3n-2)$ spheres of dimension $3$. Here we prove this conjecture by calculating the homotopy type of the independence complex of the graphs $C_{3r}\times K_n$ and $K_2\times K_m\times K_n$.

Huijie Zhang, Anthony Opipari, Xiaotong Chen, Jiyue Zhu

Transparent objects present multiple distinct challenges to visual perception systems. First, their lack of distinguishing visual features makes transparent objects harder to detect and localize than opaque objects. Even humans find certain transparent surfaces with little specular reflection or refraction, like glass doors, difficult to perceive. A second c

Alfred Sopi, Johannes Schneider, Jan vom Brocke

Non-fungible tokens(NFTs) are on the rise. They can represent artworks exhibited for marketing purposes on webpages of companies or online stores -- analogously to physical artworks. Lending of NFTs is an attractive form of passive income for owners but comes with risks (e.g., items are not returned) and costs for escrow agents. Similarly, renters have diffi

Jón Winkel, Ignacio Fernandez-Hernandez, Cillian O'Driscoll

The Assisted Commercial Authentication Service (ACAS) is a semi-assisted signal authentication concept currently being defined for Galileo, based on the E6-C encrypted signal. Leveraging the assumption that the true E6-C encrypted signal always arrives before any inauthentic signal, we define user concepts for signal detection, including vestigial signal sea

Rashed Hasan Ratul, Muhammad Iqbal, Jen-Yi Pan, Mohammad Mahadi Al Deen

The optimization of network performance is vital for the delivery of services using standard cellular technologies for mobile communications. Call setup delay and User Equipment (UE) battery savings significantly influence network performance. Improving these factors is vital for ensuring optimal service delivery. In comparison to traditional circuit-switche

Davide Gaiotto

We employ the protected sphere correlation functions of three-dimensional Super Conformal Field Theories with eight supercharges in order to define a quantization of their Higgs and Coulomb branches of vacua as real phase spaces. We also employ hemisphere correlation functions to define a quantization of certain real loci in the Higgs and Coulomb branches. L

Eduardo Fonseca Mendes, Fellipe Lopes

We develop concentration inequalities for the $l_\infty$ norm of vector linear processes with sub-Weibull, mixingale innovations. This inequality is used to obtain a concentration bound for the maximum entrywise norm of the lag-$h$ autocovariance matrix of linear processes. We apply these inequalities to sparse estimation of large-dimensional VAR(p) systems

T. Vinatier, R. W. Assmann, C. Bruni, F. Burkart

The ARES linac at DESY aims to generate and characterize ultrashort electron bunches (fs to sub-fs duration) with high momentum and arrival time stability for the purpose of applications related to accelerator R&D, e.g. development of advanced and compact diagnostics and accelerating structures, test of new accelerator components, medical applications studie

Giuseppe Di Battista, Fabrizio Grosso, Silvia Montorselli, Maurizio Patrignani

Many data sets, crucial for today's applications, consist essentially of enormous networks, containing millions or even billions of elements. Having the possibility of visualizing such networks is of paramount importance. We propose an algorithmic framework and a visual metaphor, dubbed treebar map, to provide schematic representations of huge networks. Our

Menghao Li, Chunlei Wang, Wenquan Feng, Shuchang Lyu

Visual Grounding (VG) aims at localizing target objects from an image based on given expressions and has made significant progress with the development of detection and vision transformer. However, existing VG methods tend to generate false-alarm objects when presented with inaccurate or irrelevant descriptions, which commonly occur in practical applications

Henning Krause

The notion of support provides an analogue of Stone duality, relating lattices to topological spaces. This note aims to explain in lattice theoretic terms what has been developed in the context of triangulated categories. In particular, the parallel between support via closed and open sets is addressed in terms of Hochster duality. As an application we indic

Basil Kaufmann, Dallin Busby, Chandan Krushna Das, Neeraja Tillu

Objectives: To describe the development and validation of a zero-shot learning natural language processing (NLP) tool for abstracting data from unstructured text contained within PDF documents, such as those found within electronic health records. Materials and Methods: A data abstraction tool based on the GPT-3.5 model from OpenAI was developed and compared

Amrendra Kumar, Utkarsh Shashank, Suman Kumar Maharana, John Rex Mohan

Interfacial two-dimensional electron gas (2DEG) formed at the perovskite-type oxide, such as SrTiO3, has attracted significant attention due to its properties of ferromagnetism, superconductivity, and its potential application in oxide-based low-power consumption electronics. Recent studies have investigated spin-to-charge conversion at the STO interface wit

Ruslan Prozorov

A simplified model of anisotropic magnetic susceptibility in the Meissner-London vortex-free state of cuboidal superconducting samples is presented. Using this model, precision measurements of the magnetic response in three perpendicular directions of a magnetic field with respect to primary crystal axes, can be used to extract the components of the London p

Longchao Da, Hao Mei, Romir Sharma, Hua Wei

Traffic signal control (TSC) is a complex and important task that affects the daily lives of millions of people. Reinforcement Learning (RL) has shown promising results in optimizing traffic signal control, but current RL-based TSC methods are mainly trained in simulation and suffer from the performance gap between simulation and the real world. In this pape

C. A. Bertulani, D. Bhandari, F. S. Navarra

We study the production of the dimuonium (also known as true muonium) in two and three photon fusion processes in nucleus--nucleus collisions at the CERN Large Hadron Collider (LHC) energies. A new formalism is introduced for the production process and valuable new information is extracted which will be helpful in proposals of future experiments. We explore

Arpita Paul, Avik Kumar Das, Manas Rakshit, Ankita Ray Chowdhury

Arrhythmia, an abnormal cardiac rhythm, is one of the most common types of cardiac disease. Automatic detection and classification of arrhythmia can be significant in reducing deaths due to cardiac diseases. This work proposes a multi-class arrhythmia detection algorithm using single channel electrocardiogram (ECG) signal. In this work, heart rate variabilit

Joyce A. Guzik, Jason Jackiewicz, Nancy R. Evans

Cepheids have long been used as standard candles to determine distances around the Milky Way and to nearby galaxies. A discrepancy still remains for Hubble Constant determinations using Cepheids vs. the cosmic microwave background or calibrations to the tip of the red-giant branch. Therefore, refinement of Cepheid period-luminosity relations continues to be

Moslem Ahmadvand, Ligong Bian, Soroush Shakeri

Recently, pulsar timing array experiments reported the observation of a stochastic gravitational wave background in the nanohertz range frequency band. We show that such a signal can be originated from a cosmological first-order phase transition (PT) within a well-motivated heavy (visible) QCD axion model. Considering the Peccei-Quinn symmetry breaking at th

S. Mohanty, J. Babu, Y. Furukawa, R. Nath

The structural and magnetic properties of the geometrically frustrated spin-$1/2$ capped-kagome antiferromagnet (RbCl)Cu$_{5}$P$_{2}$O$_{10}$ are investigated via temperature dependent x-ray diffraction, magnetization, heat capacity, and $^{31}$P NMR experiments on a polycrystalline sample. It undergoes a structural transition at around $T_{\rm t} \simeq 310

Cheng Shang, Hongchao Li

Motivated by entanglement protection, our work utilizes a resonance effect to enhance optomechanical entanglement in the coherent-state representation. We propose a filtering model to filter out the significant detuning components between a thermal-mechanical mode and its surrounding heat baths in the weak coupling limit. We reveal that protecting continuous

Xingbo Wang, Renfei Huang, Zhihua Jin, Tianqing Fang

Recently, large pretrained language models have achieved compelling performance on commonsense benchmarks. Nevertheless, it is unclear what commonsense knowledge the models learn and whether they solely exploit spurious patterns. Feature attributions are popular explainability techniques that identify important input concepts for model outputs. However, comm

J. Rivera-Dean, P. Stammer, A. S. Maxwell, Th. Lamprou

We present a comprehensive theoretical investigation of high-order harmonic generation in H$_2^+$ molecular ions within a quantum optical framework. Our study focuses on characterizing various quantum optical and quantum information measures, highlighting the versatility of HHG in two-center molecules towards quantum technology applications. We demonstrate t

Rafael M. Fernandes, Vanuildo S. de Carvalho, Turan Birol, Rodrigo G. Pereira

In an altermagnet, the symmetry that relates configurations with flipped magnetic moments is a rotation. This makes it qualitatively different from a ferromagnet, where no such symmetry exists, or a collinear antiferromagnet, where this symmetry is a lattice translation. In this paper, we investigate the impact of the crystalline environment, enabled by the

Jerzy Lukierski, Anna Pachoł

We introduce the perturbative $\hbar$-power series ($\hbar$ = Planck constant) providing the algebraic solutions of $D=4$ quantum Snyder and Yang models which describe relativistic quantum space-times and Lorentz-covariant quantum phase spaces. We argue that if in these series the zero order ($\hbar $-independent) terms are non-vanishing they describe the sp

Disha Ghandwani, Swarnadip Ghosh, Trevor Hastie, Art B. Owen

The crossed random effects model is widely used, finding applications in various fields such as longitudinal studies, e-commerce, and recommender systems, among others. However, these models encounter scalability challenges, as the computational time for standard algorithms grows superlinearly with the number N of observations in the data set, commonly $\Ome

Farzam Tajdari, Toon Huysmans, Xinhe Yao, Jun Xu

4D scans of dynamic deformable human body parts help researchers have a better understanding of spatiotemporal features. However, reconstructing 4D scans based on multiple asynchronous cameras encounters two main challenges: 1) finding the dynamic correspondences among different frames captured by each camera at the timestamps of the camera in terms of dynam

Xiang-Ping Jiang, Rui Qi, Sheng Yang, Yayun Hu

In one-dimensional (1D) disorder-free interacting systems, a sufficiently strong linear potential can induce localization of the many-body eigenstates, a phenomenon dubbed as Stark many-body localization (MBL). In this paper, we investigate the fate of Stark MBL in 1D spinless fermions systems with long-range interactions, specifically focusing on the role o

Zeyuan He, Kentaro Hayakawa, Makoto Ohsaki

This note is a complete library of symbolic parametrized expressions for both real and complexified configuration spaces of a spherical 4-bar linkage. Building upon the previous work from Izmestiev, (2016, Section 2), this library expands on the expressions by incorporating all four folding angles across all possible linkage length choices, along with the po

Jannik Kossen, Yarin Gal, Tom Rainforth

The predictions of Large Language Models (LLMs) on downstream tasks often improve significantly when including examples of the input--label relationship in the context. However, there is currently no consensus about how this in-context learning (ICL) ability of LLMs works. For example, while Xie et al. (2021) liken ICL to a general-purpose learning algorithm

Masoud Kaveh, Mohammad Reza Mosavi, Diego Martin, Saeed Aghapour

Security has become a main concern for the smart grid to move from research and development to industry. The concept of security has usually referred to resistance to threats by an active or passive attacker. However, since smart meters (SMs) are often placed in unprotected areas, physical security has become one of the important security goals in the smart

Susmita Das

We study completely non-unitary contractions $T$ with finite dimensional defect spaces $\mathcal{D}_T$ and $\mathcal{D}_{T^*}$. We present a complete classification of all such contractions $T$ that satisfy a generalized property of Hardy shift operator: $\mathcal{D}_T\subseteq\mathcal{D}_{T^*}$. We show that $T$ is analytic if and only if it has no non-zero

Liangyuan Chen, Yajiang Chen, Zhang Wenhui, Zhou Shuhua

Recently a novel surface pair-density-wave (PDW) superconducting state has been discovered in Refs. [Phys. Rev. Lett. \textbf{122}, 165302 (2019)] and Phys. Rev. B \textbf{101}, 054506 (2020)], which may go through a distinct multiple phase transition (MPT) when the superconductivity fades away from bulk to the boundary (e.g. edges and corners). Based on the

Yongxin Zhou, Fabien Ringeval, François Portet

Automatic dialogue summarization is a well-established task with the goal of distilling the most crucial information from human conversations into concise textual summaries. However, most existing research has predominantly focused on summarizing factual information, neglecting the affective content, which can hold valuable insights for analyzing, monitoring

Sotiris Stamkos, Spiros Patsourakos, Angelos Vourlidas, Ioannis A. Daglis

In order to advance our understanding of the dynamic interactions between coronal mass ejections (CMEs) and the magnetized solar wind, we investigate the impact of magnetic erosion on the well-known aerodynamic drag force acting on CMEs traveling faster than the ambient solar wind. In particular, we start by generating empirical relationships for the basic p

Muhammad Muneeb Saad, Mubashir Husain Rehmani, Ruairi O'Reilly

In biomedical image analysis, data imbalance is common across several imaging modalities. Data augmentation is one of the key solutions in addressing this limitation. Generative Adversarial Networks (GANs) are increasingly being relied upon for data augmentation tasks. Biomedical image features are sensitive to evaluating the efficacy of synthetic images. Th