Model free collision aggregation for the computation of escape distributionsMotivated by a heat radiative transport equation, we consider a particle undergoing collisions in a space-time domain and propose a method to sample its escape time, space and direction from the…Laetitia Laguzet, Gabriel Turinici·Mar 15, 2024SaveLearn
Topology optimization of blazed gratings under conical incidenceA topology optimization method is presented and applied to a blazed diffraction grating in reflection under conical incidence. This type of gratings is meant to disperse the incident light on one…Simon Ans, Frédéric Zamkotsian, Guillaume Demésy·Mar 15, 2024SaveLearn
Solving deep-learning density functional theory via variational autoencodersIn recent years, machine learning models, chiefly deep neural networks, have revealed suited to learn accurate energy-density functionals from data. However, problematic instabilities have been shown…Emanuele Costa, Giuseppe Scriva, Sebastiano Pilati·Mar 14, 2024SaveLearn
Anomalous thermal transport and high thermoelectric performance of Cu-based vanadate CuVO3Thermoelectric (TE) conversion technology, capable of transforming heat into electricity, is critical for sustainable energy solutions. Many promising TE materials contain rare or toxic elements, so…Xin Jin, Qiling Ou, Haoran Wei et al.·Mar 14, 2024SaveLearn
PWACG: Partial Wave Analysis Code Generator supporting Newton-conjugate gradient methodThis paper introduces a novel Partial Wave Analysis Code Generator (PWACG) that automatically generates high-performance partial wave analysis codes. This is achieved by leveraging the JAX automatic…Xiang Dong, Yu-Chang Sun, Chu-Cheng Pan et al.·Mar 14, 2024SaveLearn
Sparse Data Structures for Efficient State-to-State Kinetic SimulationsHigher-fidelity entry simulations can be enabled by integrating finer thermo-chemistry models into compressible flow physics. One such class of models are State-to-State (StS) kinetics, which…Ayoub Gouasmi, Scott Murman·Mar 14, 2024SaveLearn
Performance assessment of the effective core potentials under the Fermionic neural network: first and second row elementsThe rapid development of deep learning techniques has driven the emergence of a neural network-based variational Monte Carlo method (referred to as FermiNet), which has manifested high accuracy and…Mengsa Wang, Yuzhi Zhou, Han Wang·Mar 13, 2024SaveLearn
GCMe: Efficient implementation of the Gaussian core model with smeared electrostatic interactions for molecular dynamics simulations of soft matter systemsIn recent years, molecular dynamics (MD) simulations have emerged as a pivotal tool for understanding the structure, dynamics, and phase behavior in charged soft matter systems. To explore phenomena…Benjamin Bobin Ye, Shensheng Chen, Zhen-Gang Wang·Mar 13, 2024SaveLearn
A Real-time Dyson Expansion Scheme: Efficient Inclusion of Dynamical Correlations in Non-equilibrium Spectral PropertiesTime-resolved photoemission spectroscopy is the key technique to probe the real-time non-equilibrium dynamics of electronic states. Theoretical predictions of the time dependent spectral function for…Cian Reeves, Vojtech Vlcek·Mar 11, 2024SaveLearn
Supercomputer model of finite-dimensional quantum electrodynamics applicationsA general scheme is given for supercomputer simulation of quantum processes, which are described by various modifications of finite-dimensional cavity quantum electrodynamics models, including…Wanshun Li, Hui-hui Miao, Yuri Igorevich Ozhigov·Mar 11, 2024SaveLearn
Validation of the GreenX library time-frequency component for efficient GW and RPA calculationsElectronic structure calculations based on many-body perturbation theory (e.g. GW or the random-phase approximation (RPA)) require function evaluations in the complex time and frequency domain, for…Maryam Azizi, Jan Wilhelm, Dorothea Golze et al.·Mar 11, 2024SaveLearn
Feasibility study on solving the Helmholtz equation in 3D with PINNsRoom acoustic simulations at low frequencies often face significant uncertainties of material parameters and boundary conditions due to absorbing material. We discuss the application of…Stefan Schoder, Florian Kraxberger·Mar 11, 2024SaveLearn
Waiting times for sea level variations in the Port of Trieste: a computational data-driven studyWe report here a series of detailed statistical analyses on the sea level variations in the Port of Trieste using one of the largest existing catalogues that covers more than a century of…Gabriel Tiberiu Pană, Paul-Adrian Gogîţă, Alexandru Nicolin-Żaczek·Mar 11, 2024SaveLearn
A Naive Model of Covid-19 Spread From A Dry CoughHealth experts have suggested that social distancing measures are one of the most effective ways of preventing the spread of Covid-19. Research primarily focused on large Covid filled droplets…Cristian Ramirez Rodriguez·Mar 11, 2024SaveLearn
An Alternative to Stride-Based RNG for Monte Carlo TransportThe techniques used to generate pseudo-random numbers for Monte Carlo (MC) applications bear many implications on the quality and speed of that programs work. As a random number generator (RNG)…Braxton S. Cuneo, Ilham Variansyah·Mar 11, 2024SaveLearn
Global sensitivity analysis in Monte Carlo radiation transportWe consider Global Sensitivity Analysis for Monte Carlo radiation transport applications. GSA is usually combined with Uncertainty Quantification, where the latter quantifies the variability of a…Kayla Clements, Gianluca Geraci, Aaron J Olson et al.·Mar 10, 2024SaveLearn
XFLUIDS: A SYCL-based unified cross-architecture heterogeneous simulation solver for compressible reacting flowsWe present a cross-architecture high-order heterogeneous Navier-Stokes simulation solver, XFluids, for compressible reacting multicomponent flows on different platforms. The multi-component reacting…Jinlong Li, Shucheng Pan·Mar 9, 2024SaveLearn
Accelerating the Convergence of Coupled Cluster Calculations of the Homogeneous Electron Gas Using Bayesian Ridge RegressionThe homogeneous electron gas is a system which has many applications in chemistry and physics. However, its infinite nature makes studies at the many-body level complicated due to long computational…Julie Butler, Morten Hjorth-Jensen, Justin Lietz·Mar 7, 2024SaveLearn
Induced charges in a Thomas-Fermi metal: insights from molecular simulationsWe study the charge induced in a Thomas-Fermi metal by an ion in vacuum, using an atomistic description employed in constant-potential molecular dynamics simulations, and compare the results with the…Swetha Nair, Giovanni Pireddu, Benjamin Rotenberg·Mar 7, 2024SaveLearn
An efficient method for calculating resonant modes in biperiodic photonic structuresMany photonic devices, such as photonic crystal slabs, cross gratings, and periodic metasurfaces, are biperiodic structures with two independent periodic directions, and are sandwiched between two…Nan Zhang, Ya Yan Lu·Mar 7, 2024SaveLearn
Portable GPU implementation of the WP-CCC ion-atom collisions codeWe present our experience of porting the code used in the wave-packet convergent-close-coupling (WP-CCC) approach to run on NVIDIA V100 and AMD MI250X GPUs. The WP-CCC approach is a method used in…I. B. Abdurakhmanov, N. W. Antonio, M. Cytowski et al.·Mar 7, 2024SaveLearn
Multiple scattering simulation via physics-informed neural networksThis work presents a physics-driven machine learning framework for the simulation of acoustic scattering problems. The proposed framework relies on a physics-informed neural network (PINN)…Siddharth Nair, Timothy F. Walsh, Greg Pickrell et al.·Mar 6, 2024SaveLearn
Quantum Many-Body Physics Calculations with Large Language ModelsLarge language models (LLMs) have demonstrated an unprecedented ability to perform complex tasks in multiple domains, including mathematical and scientific reasoning. We demonstrate that with…Haining Pan, Nayantara Mudur, Will Taranto et al.·Mar 5, 2024SaveLearn
A numerical algorithm for solving the coupled Schr\"odinger equations using inverse power methodThe inverse power method is a numerical algorithm to obtain the eigenvectors of a matrix. In this work, we develop an iteration algorithm, based on the inverse power method, to numerically solve the…Jiaxing Zhao, Shuzhe Shi·Mar 5, 2024SaveLearn
Accelerating fourth-generation machine learning potentials by quasi-linear scaling particle mesh charge equilibrationMachine learning potentials (MLP) have revolutionized the field of atomistic simulations by describing the atomic interactions with the accuracy of electronic structure methods at a small fraction of…Moritz Gubler, Jonas A. Finkler, Moritz R. Schäfer et al.·Mar 4, 2024SaveLearn