July 2023 arXiv papers — page 92

Wenhao Ding, Laixi Shi, Yuejie Chi, Ding Zhao

Robustness has been extensively studied in reinforcement learning (RL) to handle various forms of uncertainty such as random perturbations, rare events, and malicious attacks. In this work, we consider one critical type of robustness against spurious correlation, where different portions of the state do not have correlations induced by unobserved confounders

Peter M. McDonald

Let $X$ be a normal, excellent, noetherian scheme over $\operatorname{Spec}\mathbb{Q}$ with a dualizing complex. In this note, we find an alternate characterization of the multiplier ideal of $X$, as defined by de Fernex-Hacon, by considering maps $\pi_*\omega_Y\to\mathcal{O}_X$ where $\pi:Y\to X$ ranges over all regular alterations. As a corollary to this r

Mehdi Zarea, Hikaru Ueki, J. A. Sauls

We present results for the resonant frequency shift and quality factor of disordered Nb SRF cavities driven out of equilibrium by the resonant microwave field. The theory is based on the nonequilibrium theory of superconductivity for the current response to the electromagnetic field at the vacuum-metal interface. We are able to accurately predict the observe

K. U. Can, M. Batelaan, A. Hannaford-Gunn, R. Horsley

The structure of hadrons relevant for deep-inelastic scattering are completely characterised by the Compton amplitude. A direct calculation of the Compton amplitude in a lattice QCD setup provides a way to accessing the structure functions, circumventing the operator mixing and renormalisation issues of the standard operator product expansion approach. In th

David M. J. Lazer, Matthew A. Baum, Yochai Benkler, Adam J. Berinsky

Fake news emerged as an apparent global problem during the 2016 U.S. Presidential election. Addressing it requires a multidisciplinary effort to define the nature and extent of the problem, detect fake news in real time, and mitigate its potentially harmful effects. This will require a better understanding of how the Internet spreads content, how people proc

Gerhard Schindl

We revisit and generalize the geometric procedure of regularizing a sequence of real numbers with respect to a so-called regularizing function. This approach was studied by S. Mandelbrojt and becomes useful and necessary when working with corresponding classes of ultradifferentiable functions defined via weight sequences and analogous weighted spaces. In thi

Devilal Dahal, Raymond Atta-Fynn, Stephen R. Elliott, Parthapratim Biswas

This paper presents a first-principles study of the Debye-Waller factor and the Debye temperature for amorphous silicon ($a$-Si) from lattice-dynamical calculations and direct molecular-dynamics simulations using density-functional theory (DFT). The effects of temperature and structural disorder on the intensity of the diffraction maxima and the vibrational

Joseph Doolittle, Alex McDonough

It is broadly known that any parallelepiped tiles space by translating copies of itself along its edges. In earlier work relating to higher-dimensional sandpile groups, the second author discovered a novel construction which fragments the parallelpiped into a collection of smaller tiles. These tiles fill space with the same symmetry as the larger parallelepi

Mostafa Mirabi

This paper focuses on the characterization of $\aleph_0$-categorical theories of trees in the following sense: for any $\aleph_0$-cateorical theory $T$ of trees there is a tree plan $\Gamma$ such that $T=Th(\Gamma(\omega))$ where $\Gamma(\omega)$ is the generic model of a Fra\"iss\'e class $\mathbf{K}(\Gamma)$ obtained from the tree plan $\Gamma$. Also, it i

Hanyang Jiang, Yao Xie

We present a novel Graph-based debiasing Algorithm for Underreported Data (GRAUD) aiming at an efficient joint estimation of event counts and discovery probabilities across spatial or graphical structures. This innovative method provides a solution to problems seen in fields such as policing data and COVID-$19$ data analysis. Our approach avoids the need for

Yukiko Konishi, Satoshi Minabe

In arXiv:2004.01871 Satake introduced the notions of admissible triplets and good basic invariants for finite complex reflection groups. For irreducible finite Coxeter groups, he showed the existence and the uniqueness of good basic invariants. Moreover he showed that good basic invariants are flat in the sense of K.Saito's flat structure. He also obtained a

Zhecheng Sheng, Raymond Finzel, Michael Lucke, Sheena Dufresne

In healthcare, the ability to care for oneself is reflected in the "Activities of Daily Living (ADL)," which serve as a measure of functional ability (functioning). A lack of functioning may lead to poor living conditions requiring personal care and assistance. To accurately identify those in need of support, assistance programs continuously evaluate partici

Tasmiah Tunazzina, Fairuz Areefin Khan, Anuva Chowdhury

The selection of a suitable plasmonic material is extremely crucial for achieving high-performance photonic crystal fiber-based surface plasmon resonance (PCF-SPR) sensors. However, most numerical investigations to date are limited to PCF-SPR sensors with conventional circularly coated plasmonic metals due to their availability and rigid properties. In this

Patrick Mukala

The Democratic Republic of Congo is a sleeping giant at the heart of Africa. Though endowed with incredible natural resources spanning from significant reserves of gold, diamond, coltan, copper to vast African forests and impressive water resources, it is still considered as one of the poorest countries on the planet. For a long time, its economy has had not

Patrick Mukala

The Information and Communication sector has undoubtedly played a pivotal role in changing the way people live nowadays. Almost every area of our lives is affected by the presence and the use of the new information and communication technologies. In this regard, many researchers' attention has been attracted by the influence or the significant impact of thes

Mihael Hategan-Marandiuc, Andre Merzky, Nicholson Collier, Ketan Maheshwari

It is generally desirable for high-performance computing (HPC) applications to be portable between HPC systems, for example to make use of more performant hardware, make effective use of allocations, and to co-locate compute jobs with large datasets. Unfortunately, moving scientific applications between HPC systems is challenging for various reasons, most no

Jon Grantham, Andrew Granville

We speculate on the distribution of primes in exponentially growing, linear recurrence sequences $(u_n)_{n\geq 0}$ in the integers. By tweaking a heuristic which is successfully used to predict the number of prime values of polynomials, we guess that either there are only finitely many primes $u_n$, or else there exists a constant $c_u>0$ (which we can give

Assef Ghamisi, Todd Charter, Li Ji, Maxime Rivard

Conventional defect detection systems in Automated Fibre Placement (AFP) typically rely on end-to-end supervised learning, necessitating a substantial number of labelled defective samples for effective training. However, the scarcity of such labelled data poses a challenge. To overcome this limitation, we present a comprehensive framework for defect detectio

Weiying Zhao, Charles-Alban Deledalle, Loïc Denis, Henri Maître

Understanding the state of changed areas requires that precise information be given about the changes. Thus, detecting different kinds of changes is important for land surface monitoring. SAR sensors are ideal to fulfil this task, because of their all-time and all-weather capabilities, with good accuracy of the acquisition geometry and without effects of atm

Chunrong Feng, Baoyou Qu, Huaizhong Zhao

In this article, we solve the problem of the long time behaviour of transition probabilities of time-inhomogeneous Markov processes and give a unified approach to stochastic differential equations (SDEs) with periodic, quasi-periodic, almost-periodic forcing and much beyond. We extend Harris's ``small set'' method to the time-inhomogeneous situation with the

Rouzbeh Modarresi Yazdi, Shuzhe Shi, Charles Gale, Sangyong Jeon

Jet-energy loss is an important sign of the creation of Quark-Gluon Plasma in heavy-ion collisions. High transverse momentum ($p_T$) partons are produced at the moment of initial hard scattering and are modified as a result of their propagation through the created medium. We study two models of low-virtuality radiative energy loss: CUJET and MARTINI. This is

Adian Liusie, Potsawee Manakul, Mark J. F. Gales

Current developments in large language models (LLMs) have enabled impressive zero-shot capabilities across various natural language tasks. An interesting application of these systems is in the automated assessment of natural language generation (NLG), a highly challenging area with great practical benefit. In this paper, we explore two options for exploiting

Zhihui Li, Francesco Montomoli, Sanjiv Sharma

In this study, we utilize the emerging Physics Informed Neural Networks (PINNs) approach for the first time to predict the flow field of a compressor cascade. Different from conventional training methods, a new adaptive learning strategy that mitigates gradient imbalance through incorporating adaptive weights in conjunction with dynamically adjusting learnin

Gregory M. Dickinson

Lawmakers around the country are crafting new laws to target "dark patterns" -- user interface designs that trick or coerce users into enabling cell phone location tracking, sharing browsing data, initiating automatic billing, or making whatever other choices their designers prefer. Dark patterns pose a serious problem. In their most aggressive forms, they i

Sina Gholamian, Ali Vahdat

While analyzing scanned documents, handwritten text can overlap with printed text. This overlap causes difficulties during the optical character recognition (OCR) and digitization process of documents, and subsequently, hurts downstream NLP tasks. Prior research either focuses solely on the binary classification of handwritten text or performs a three-class

M. Sajid, A. K. Malik, M. Tanveer

In the realm of data classification, broad learning system (BLS) has proven to be a potent tool that utilizes a layer-by-layer feed-forward neural network. However, the traditional BLS treats all samples as equally significant, which makes it less robust and less effective for real-world datasets with noises and outliers. To address this issue, we propose fu

Rafik Karkri, Samir Kabbaj, Hamad Sidi Lafdal

In this paper, we prove the following results. There exists a Banach space without basis which has a Schauder frame. There exists an universal Banach space $B$ (resp. $\tilde{B}$) with a basis (resp. an unconditional basis) such that, a Banach $X$ has a Schauder frame (resp. an unconditional Schauder frame ) if and only if $X$ is isomorphic to a complemented

Xingwen Wang, Chenyu Wu, Zikuan Wang, Wenjian Liu

Open-shell molecules rarely fluoresce, due to their typically faster non-radiative relaxation rates compared to closed-shell ones. Even rarer is the fluorescence from states that have two more unpaired electrons than the open-shell ground state, for example tripdoublet states (a triplet excitation antiferromagnetically coupled to a doublet state). The descri

Guilherme Toledo, Yoni Zohar, Clark Barrett

This work is a part of an ongoing effort to understand the relationships between properties used in theory combination. We here focus on including two properties that are related to shiny theories: the finite model property and stable finiteness. For any combination of properties, we consider the question of whether there exists a theory that exhibits it. Wh

Yannis Voet

Sylvester matrix equations are ubiquitous in scientific computing. However, few solution techniques exist for their generalized multiterm version, as they now arise in an increasingly large number of applications. In this work, we consider algebraic parameter-free preconditioning techniques for the iterative solution of generalized multiterm Sylvester equati

Erasmo Caponio, Dario Corona, Roberto Giambò, Paolo Piccione

We consider an autonomous, indefinite Lagrangian admitting an infinitesimal symmetry whose associated Noether charge is linear in each tangent space. Our focus lies in investigating solutions to the Euler-Lagrange equations having fixed energy and that connect a given point to a flow line of the infinitesimal generator $K$. By utilizing the invariance of the

Lucas Böttcher

Ensemble Kalman inversion (EKI) is a sequential Monte Carlo method used to solve inverse problems within a Bayesian framework. Unlike backpropagation, EKI is a gradient-free optimization method that only necessitates the evaluation of artificial neural networks in forward passes. In this study, we examine the effectiveness of EKI in training neural ordinary

M. A. Ganaie, M. Sajid, A. K. Malik, M. Tanveer

The domain of machine learning is confronted with a crucial research area known as class imbalance learning, which presents considerable hurdles in precise classification of minority classes. This issue can result in biased models where the majority class takes precedence in the training process, leading to the underrepresentation of the minority class. The

Masoud Farhadi, Bhanu Teja Vankayalapati, Rahman Sajadi, Bilal Akin

AC power cycling tests allow the most realistic reliability assessment by applying close to real stress to the device or module under test to meet functional safety standards, which is highly critical for traction applications. This paper presents a comprehensive guideline and shares critical know-how to develop a 120 KVA AC power cycling test setup for high

Bolei Ma, Ercong Nie, Helmut Schmid, Hinrich Schütze

Multilingual pretrained language models (MPLMs) have demonstrated substantial performance improvements in zero-shot cross-lingual transfer across various natural language understanding tasks by finetuning MPLMs on task-specific labelled data of a source language (e.g. English) and evaluating on a wide range of target languages. Recent studies show that promp

Juan C. David Gomez, Amy L. Cochran, Gabriel Zayas-Caban

In many stochastic service systems, decision-makers find themselves making a sequence of decisions, with the number of decisions being unpredictable. To enhance these decisions, it is crucial to uncover the causal impact these decisions have through careful analysis of observational data from the system. However, these decisions are not made independently, a

Cynthia Nunez

Transverse $\Lambda$ polarization observed over four decades ago contradicted expectations from early leading-order perturbative QCD calculations. Measurements of $\Lambda$ polarization from unpolarized $pp$ and $p$A collisions have been previously observed to increase as a function of $x_F$ and $p_T$ up to a few GeV range and approximately independent of be

Rose Davies, Igor V. Lerner, Igor V. Yurkevich

In recent experiments on conductance of one-dimensional (1D) channels in ultra-clean samples, a diverse set of plateaus were found at fractions of the quantum of conductance in zero magnetic field. We consider a discrete model of strongly interacting electrons in a clean 1D system where the current between weak tunneling contacts is carried by fractionally c

Douglas Tesch, Leonardo Rosa Amado, Felipe Meneguzzi

While recent work on online goal recognition efficiently infers goals under low observability, comparatively less work focuses on online goal recognition that works in both discrete and continuous domains. Online goal recognition approaches often rely on repeated calls to the planner at each new observation, incurring high computational costs. Recognizing go

Yishu Zhou, Freek Ruesink, Margaret Pavlovich, Ryan Behunin

New strategies to convert signals between optical and microwave domains could play a pivotal role in advancing both classical and quantum technologies. Through recent studies, electro-optomechanical systems have been used to implement microwave-to-optical conversion using resonant optical systems, resulting in transduction over limited optical bandwidth. Her

A. Kim, S. Diehl, K. Joo, V. Kubarovsky

The new experimental measurements of beam spin asymmetry were performed for the deeply virtual exclusive $\pi^0$ production in a wide kinematic region with the photon virtualities $Q^2$ up to 8 GeV$^2$ and the Bjorken scaling variable $x_B$ in the valence regime. The data were collected by the CEBAF Large Acceptance Spectrometer (CLAS12) at Jefferson Lab wit

Yechao Zhang, Shengshan Hu, Leo Yu Zhang, Junyu Shi

Adversarial examples (AEs) for DNNs have been shown to be transferable: AEs that successfully fool white-box surrogate models can also deceive other black-box models with different architectures. Although a bunch of empirical studies have provided guidance on generating highly transferable AEs, many of these findings lack explanations and even lead to incons

Alisia Lupidi, Yonatan Gideoni, Dulhan Jayalath

Most investigations into double descent have focused on supervised models while the few works studying self-supervised settings find a surprising lack of the phenomenon. These results imply that double descent may not exist in self-supervised models. We show this empirically using a standard and linear autoencoder, two previously unstudied settings. The test

Grgur Kovač, Rémy Portelas, Peter Ford Dominey, Pierre-Yves Oudeyer

Developmental psychologists have long-established the importance of socio-cognitive abilities in human intelligence. These abilities enable us to enter, participate and benefit from human culture. AI research on social interactive agents mostly concerns the emergence of culture in a multi-agent setting (often without a strong grounding in developmental psych

Grgur Kovač, Masataka Sawayama, Rémy Portelas, Cédric Colas

Large Language Models (LLMs) are often misleadingly recognized as having a personality or a set of values. We argue that an LLM can be seen as a superposition of perspectives with different values and personality traits. LLMs exhibit context-dependent values and personality traits that change based on the induced perspective (as opposed to humans, who tend t

Vijay Shankaran Vivekanand, Rajkumar Kubendran

Temporal spike recognition plays a crucial role in various domains, including anomaly detection, keyword spotting and neuroscience. This paper presents a novel algorithm for efficient temporal spike pattern recognition on sparse event series data. The algorithm leverages a combination of reward-modulatory behavior, Hebbian and anti-Hebbian based learning met

Varun Sangwan, Vishesh Kumar Singh, Bibin Christopher

Our research aims to find the best model that uses companies projections and sector performances and how the given company fares accordingly to correctly predict equity share prices for both short and long term goals.

Nick P. Petropoulos

There seems to exist significant similarities between a reactor system and a supply chain from collection to delivery. In the reactor case, neutrons are continuously produced and absorbed in nuclear fuel. In a supply system case, items are continuously collected and continuously delivered to destinations. Stable reactor operation is ensured by keeping the ra

Jörg Rottler, Céline Ruscher, Peter Sollich

We present a method for computing locally varying nonlinear mechanical properties in particle simulations of amorphous solids. Plastic rearrangements outside a probed region are suppressed by introducing an external field that directly penalizes large nonaffine displacements. With increasing strength of the field, plastic deformation can be localized. We cha

Bruno Chagas, Antonio F. B. de A. Prado, Othon C. Winter

Asteroids have called the attention of researchers around the world. Its chemical and physical composition can give us important information about the formation of our Solar System. In addition, the hypothesis of mining some of these objects is considered, since they contain precious metals. However, some asteroids have their orbits close to the orbit of the

James C. Young, Rudy Arthur, Hywel T. P. Williams

Researchers commonly perform sentiment analysis on large collections of short texts like tweets, Reddit posts or newspaper headlines that are all focused on a specific topic, theme or event. Usually, general-purpose sentiment analysis methods are used. These perform well on average but miss the variation in meaning that happens across different contexts, for

Jaap Eising, Jorge Cortes

This paper deals with the problem of accurately determining guaranteed suboptimal values of an unknown cost function on the basis of noisy measurements. We consider a set-valued variant to regression where, instead of finding a best estimate of the cost function, we reason over all functions compatible with the measurements and apply robust methods explicitl

Anant Mehta, Prajit Sengupta, Divisha Garg, Harpreet Singh

Plant breeders and agricultural researchers can increase crop productivity by identifying desirable features, disease resistance, and nutritional content by analysing the Dry Bean dataset. This study analyses and compares different Support Vector Machine (SVM) classification algorithms, namely linear, polynomial, and radial basis function (RBF), along with o

Pralaypati Ta, Bhumika Gupta, Arihant Jain, Sneha Sree C

Clinical Practice Guidelines (CPGs) for cancer diseases evolve rapidly due to new evidence generated by active research. Currently, CPGs are primarily published in a document format that is ill-suited for managing this developing knowledge. A knowledge model of the guidelines document suitable for programmatic interaction is required. This work proposes an a

Yizhou Zhao, Yuanhong Zeng, Qian Long, Ying Nian Wu

Simulation-to-real is the task of training and developing machine learning models and deploying them in real settings with minimal additional training. This approach is becoming increasingly popular in fields such as robotics. However, there is often a gap between the simulated environment and the real world, and machine learning models trained in simulation

Nader J. Abu-Alrub, Nathir A. Rawashdeh

Radar odometry has been gaining attention in the last decade. It stands as one of the best solutions for robotic state estimation in unfavorable conditions; conditions where other interoceptive and exteroceptive sensors may fall short. Radars are widely adopted, resilient to weather and illumination, and provide Doppler information which make them very attra

Qiana Hunt, Rupali Chandar, Elena Gallo, Matthew Floyd

We conduct one of the largest systematic investigations of bright X-ray binaries (XRBs) in both young star clusters and ancient globular clusters (GCs) using a sample of six nearby, star-forming galaxies. Combining complete CXO X-ray source catalogs with optical PHANGS-HST cluster catalogs, we identify a population of 33 XRBs within or near their parent clus

Xingxing Wei, Yao Huang, Yitong Sun, Jie Yu

Recently, physical adversarial attacks have been presented to evade DNNs-based object detectors. To ensure the security, many scenarios are simultaneously deployed with visible sensors and infrared sensors, leading to the failures of these single-modal physical attacks. To show the potential risks under such scenes, we propose a unified adversarial patch to

Ward Struyve

In canonical quantum gravity the wave function of the universe is static, leading to the so-called problem of time. We summarize here how Bohmian mechanics solves this problem.

Bhargav Adabala, Zlatan Ajanović

In unstructured environments like parking lots or construction sites, due to the large search-space and kinodynamic constraints of the vehicle, it is challenging to achieve real-time planning. Several state-of-the-art planners utilize heuristic search-based algorithms. However, they heavily rely on the quality of the single heuristic function, used to guide

Ward Struyve

Albert and Callender have challenged the received view that theories like classical electrodynamics and non-relativistic quantum mechanics are time reversal invariant. They claim that time reversal should correspond to the mere reversal of the temporal order of the instantaneous states, without any accompanying change of the instantaneous state as in the sta

Marc de Montigny, Pierre-Philippe A. Ouimet, James Pinfold, Ameir Shaa

Minicharged particles (mCPs), hypothetical free particles with effective electric charges much smaller than the elementary charge, $e$, offer a valuable probe of dark sectors and fundamental physics through several clear experimental signatures. Various models of physics beyond the Standard Model predict such particles, the existence of which could help eluc

Iman Saberi, Amirreza Esmaeili, Fatemeh Fard, Fuxiang Chen

Programming languages can benefit from one another by utilizing a pre-trained model for software engineering tasks such as code summarization and method name prediction. While full fine-tuning of Code Language Models (Code-LMs) has been explored for multilingual knowledge transfer, research on Parameter Efficient Fine-Tuning (PEFT) for this purpose is limite

Divya Kumawat, Ardeshir Ebtehaj, Mike Schwank, Jean-Pierre Wigneron

This article expands the tau-omega model to properly simulate L-band microwave emission of the soil-snow-vegetation continuum through a closed-form solution of Maxwell's equations, considering the intervening dry snow layer as a loss-less medium. The feasibility and uncertainty of retrieving vegetation optical depth (VOD) and ground permittivity, given the n

Mick Wright, Justin Janquart, Martin Hendry

As the interferometers detecting gravitational waves are upgraded, improving their sensitivity, the probability of observing strong lensing increases. Once a detection is made, it will be critical to gain as much information as possible about the lensing object from these observations. In this work, we present a methodology to rapidly perform model selection

Tim Schopf, Emanuel Gerber, Malte Ostendorff, Florian Matthes

Generic sentence embeddings provide a coarse-grained approximation of semantic textual similarity but ignore specific aspects that make texts similar. Conversely, aspect-based sentence embeddings provide similarities between texts based on certain predefined aspects. Thus, similarity predictions of texts are more targeted to specific requirements and more ea

Ward Struyve

Laws of motion given in terms of differential equations can not always be derived from an action principle, at least not without introducing auxiliary variables. By allowing auxiliary variables, e.g. in the form of Lagrange multipliers, an action is immediately obtained. Here, we consider some ways how this can be done, drawing examples from the literature,

Chirag Modi, Charles Margossian, Yuling Yao, Robert Gower

Variational inference (VI) is a method to approximate the computationally intractable posterior distributions that arise in Bayesian statistics. Typically, VI fits a simple parametric distribution to the target posterior by minimizing an appropriate objective such as the evidence lower bound (ELBO). In this work, we present a new approach to VI based on the

Artur Czumaj, Guichen Gao, Shaofeng H. -C. Jiang, Robert Krauthgamer

We design new parallel algorithms for clustering in high-dimensional Euclidean spaces. These algorithms run in the Massively Parallel Computation (MPC) model, and are fully scalable, meaning that the local memory in each machine may be $n^{\sigma}$ for arbitrarily small fixed $\sigma>0$. Importantly, the local memory may be substantially smaller than the num

Zhaoyuan He, Yifan Yang, Shuozhe Li, Diyuan Dai

Cloud gaming is a multi-billion dollar industry. A client in cloud gaming sends its movement to the game server on the Internet, which renders and transmits the resulting video back. In order to provide a good gaming experience, a latency below 80 ms is required. This means that video rendering, encoding, transmission, decoding, and display have to finish wi

Noopur Zambare

This study presents AIOptimizer, a prototype for a cost-reduction-based software performance optimisation tool. The study focuses on the design elements of AIOptimizer, including user-friendliness, scalability, accuracy, and adaptability. To deliver efficient and user-focused performance optimisation solutions, it promotes the use of robust integration, cont

Chunyan Li, Vladimir V. Konotop, Boris A. Malomed, Yaroslav V. Kartashov

We consider Bose-Einstein condensate (BEC) subject to the action of spin-orbit-coupling (SOC) periodically modulated in the radial direction. In contrast to the commonly known principle that periodic potentials do not create bound states, the binary BEC maintains multiple localized modes in the linear limit, with their chemical potential falling into spectra

Charles Gale, Sangyong Jeon, Daniel Pablos, Mayank Singh

Minijets are ubiquitous in heavy-ion collision experiments. However, they are often excluded from the hydrodynamic simulations of QGP as they do not thermalize at short time scales and are not treated as part of the collective medium. Using a concurrent jet+hydro framework, we show that the minijets could account for a significant portion of particle multipl

Sourya Basu, Moulik Choraria, Lav R. Varshney

We find limits to the Transformer architecture for language modeling and show it has a universal prediction property in an information-theoretic sense. We further analyze performance in non-asymptotic data regimes to understand the role of various components of the Transformer architecture, especially in the context of data-efficient training. We validate ou

Robin Feldmann, Alberto Baiardi, Markus Reiher

We present a symmetry projection technique for enforcing rotational and parity symmetries in nuclear-electronic Hartree-Fock wave functions, which treat electrons and nuclei on equal footing. The molecular Hamiltonian obeys rotational and parity-inversion symmetries, which are, however, broken by expanding in Gaussian basis sets that are fixed in space. We g

Patrick Mukala, Antonio Cerone, Franco Turini

Evidence suggests that Free/Libre Open Source Software (FLOSS) environments provide unlimited learning opportunities. Community members engage in a number of activities both during their interaction with their peers and while making use of the tools available in these environments. A number of studies document the existence of learning processes in FLOSS thr

Jiaxing Zhang, Zhuomin Chen, Hao Mei, Longchao Da

Graph regression is a fundamental task that has gained significant attention in various graph learning tasks. However, the inference process is often not easily interpretable. Current explanation techniques are limited to understanding Graph Neural Network (GNN) behaviors in classification tasks, leaving an explanation gap for graph regression models. In thi

Yao Fu, Raymond Brock, Daniel Hayden, Chien-Peng Yuan

The forward-backward asymmetry of the Drell-Yan process in dilepton decays at high invariant masses can be used to probe the parton distribution functions at large x. The behavior of three modern PDF sets (CT18NNLO, MSHT20, and NNPDF4.0) are compared, and updated under various scenarios via ePump using proton-proton collision pseudo-data generated at sqrt(s)

S. I. Pavlik

It is shown that the atomic inversion in the Jaynes-Cummings model has an exact representation as an integral over the Hankel contour. For a field in a coherent state, the integral is evaluated using the saddle point method. The trajectories of saddle points as a function of time are on the branches of the multi-valued Lambert function. All of them start at

Jialu Gao, Kaizhe Hu, Guowei Xu, Huazhe Xu

Pre-trained text-to-image generative models can produce diverse, semantically rich, and realistic images from natural language descriptions. Compared with language, images usually convey information with more details and less ambiguity. In this study, we propose Learning from the Void (LfVoid), a method that leverages the power of pre-trained text-to-image m

Shengbo Liu, Wen Wu, Shaofeng Li, Tom H. Luany

We propose a digital twin-assisted adaptive preloading scheme to enhance bandwidth efficiency and user quality of experience (QoE) in short video streaming. We first analyze the relationship between the achievable throughput and video bitrate and critical factors that affect the preloading decision, including the buffer size and bitrate selection. We then co

Sandip Bera

The lattice Hamiltonian with the presence of a chiral magnetic isotropic Dzyaloshinskii-Moriya interaction (DMI) in a square and hexagonal lattice is numerically solved to give the full phase diagram consisting of skyrmions and merons in different parameter planes. The phase diagram provides the actual regions of analytically unresolved asymmetric skyrmions

Alberto Corato, Mohamed Saïdi

In 1981, Uchida proved a conditional version of the Hom-form of the Grothendieck birational anabelian conjecture for number fields. In this paper we prove an m-step solvable conditional version of the Grothendieck birational anabelian conjecture for number fields whereby our conditions are slightly weaker than the ones in Uchida's theorem. Furthermore, as in

Paul Terwilliger

The goal of this article is to display a $Q$-polynomial structure for the Attenuated Space poset $\mathcal A_q(N,M)$. The poset $\mathcal A_q(N,M)$ is briefly described as follows. Start with an $(N+M)$-dimensional vector space $H$ over a finite field with $q$ elements. Fix an $M$-dimensional subspace $h$ of $H$. The vertex set $X$ of $\mathcal A_q(N,M)$ con

Jiaxing Zhang, Dongsheng Luo, Hua Wei

Graph Neural Networks (GNNs) have received increasing attention due to their ability to learn from graph-structured data. However, their predictions are often not interpretable. Post-hoc instance-level explanation methods have been proposed to understand GNN predictions. These methods seek to discover substructures that explain the prediction behavior of a t

E. Eisenriegler

Density profiles are investigated arising in a critical Ising model in two dimensions which is confined to a rectangular domain with uniform or mixed boundary conditions and arbitrary aspect ratio. For the cases in which the two vertical sides of the rectangle have up-spin boundary conditions + and the two horizontal sides with either down-spin boundary cond

Andrej Bauer

I take a constructive look at Dieter Spreen's treatment of effective topological spaces and the Kreisel-Lacombe-Shoenfield-Tseitin (KLST) continuity theorem. Transferring Spreen's ideas from classical computability theory and numbered sets to a constructive setting leads to a theory of topological spaces, in fact two of them: a locale-theoretic one embodied

Carlos E. Frasser

Graph theory and enumerative combinatorics are two branches of mathematical sciences that have developed astonishingly over the past one hundred years. It is especially important to point out that graph theory employs combinatorial techniques to solve key problems of characterization, construction, enumeration and classification of an enormous set of differe

Chunming He, Kai Li, Guoxia Xu, Jiangpeng Yan

Unpaired Medical Image Enhancement (UMIE) aims to transform a low-quality (LQ) medical image into a high-quality (HQ) one without relying on paired images for training. While most existing approaches are based on Pix2Pix/CycleGAN and are effective to some extent, they fail to explicitly use HQ information to guide the enhancement process, which can lead to u

David Walker, Anthony Skjellum

Modern computer systems are characterized by deep memory hierarchies, composed of main memory, multiple layers of cache, and other specialized types of memory. In parallel and distributed systems, additional memory layers are added to this hierarchy. Achieving good performance for computational science applications, in terms of execution time, depends on the

Luoyao Yu, Lixing Zhu, Ruoqing Zhu, Xuehu Zhu

This paper develops a method to detect model structural changes by applying a Corrected Kernel Principal Component Analysis (CKPCA) to construct the so-called central distribution deviation subspaces. This approach can efficiently identify the mean and distribution changes in these dimension reduction subspaces. We derive that the locations and number change

Aren A. Babikian, Oszkár Semeráth, Dániel Varró

Existing safety assurance approaches for autonomous vehicles (AVs) perform system-level safety evaluation by placing the AV-under-test in challenging traffic scenarios captured by abstract scenario specifications and investigated in realistic traffic simulators. As a first step towards scenario-based testing of AVs, the initial scene of a traffic scenario mu

H. Aratyn, J. F. Gomes, G. V. Lobo, A. H. Zimerman

Under special conditions the Painlev\'e V equation has more than one rational solution solving it with the same parameters. In the setting of formalism that identifies points on orbits of the fundamental shift operators of $A^{(1)}_{3}$ affine Weyl group with rational solutions we derive conditions for such non-uniqueness to occur. We identify the seed solut

Mei Han, Kirati Sriamorn, Qi Yang, Chuanming Zong

This paper proves the following statement: If a convex body can form a fivefold translative tiling in $\mathbb{E}^3$, it must be a parallelotope, a hexagonal prism, a rhombic dodecahedron, an elongated dodecahedron, a truncated octahedron, a cylinder over a particular octagon, or a cylinder over a particular decagon, where the octagon and the decagon are fiv

Bakhyt Aitzhanova, Leonid Makar-Limanov, Ualbai Umirbaev

The Veronese subalgebra $A_0$ of degree $d\geq 2$ of the polynomial algebra $A=K[x_1,x_2,\ldots,x_n]$ over a field $K$ in the variables $x_1,x_2,\ldots,x_n$ is the subalgebra of $A$ generated by all monomials of degree $d$ and the Veronese subalgebra $P_0$ of degree $d\geq 2$ of the free Poisson algebra $P=P\langle x_1,x_2,\ldots,x_n\rangle$ is the subalgebr

Michael Q. Rieck

Deltoid curves appear as consequences of certain procedures in triangle geometry. The best known of these is the construction based on Simson lines, described by Steiner. This is carefully related, in this article, to a less known construction. The standard deltoid in the complex plane and its tangent lines are principle objects of study in this report. It i

Mohamad Idris Wani, Sadan Saquib Khan, Benish Jan, Meraj Ahmad

Relaxation oscillator-based circuits are widely used for interfacing various resistive and capacitive sensors. The electrical equivalent of most resistive and capacitive sensors is represented using a parallel combination of resistor and capacitor. The relaxation oscillator-based circuits are not suitable for parallel R-C sensors. In this paper, we propose a

Alexander Montgomerie-Corcoran, Zhewen Yu, Jianyi Cheng, Christos-Savvas Bouganis

With the ever-growing popularity of Artificial Intelligence, there is an increasing demand for more performant and efficient underlying hardware. Convolutional Neural Networks (CNN) are a workload of particular importance, which achieve high accuracy in computer vision applications. Inside CNNs, a significant number of the post-activation values are zero, re

Sinan Emre Kosunda, Beste Basciftci, Esra Koca

Optimizing car sharing systems under demand uncertainty is an emerging problem for ensuring profitable and sustainable operations of these services while taking into account quality of service concerns. With the increasing adoption of electric vehicles and environmental awareness, this problem requires consideration of a mix fleet of vehicles with gasoline-p

Hong-Zhou Xi, Yi-Wei Jiang, Hua-Xing Chen, Atsushi Hosaka

We study the fully-strange tetraquark states with the exotic quantum numbers $J^{PC} = 0^{+-}$ and $2^{+-}$. We construct their corresponding diquark-antidiquark interpolating currents, and apply the QCD sum rule method to calculate both their diagonal and off-diagonal correlation functions. The obtained results are used to construct some mixing currents tha