A Numerical Method for Sharp-Interface Simulations of Multicomponent Alloy SolidificationWe present a computational method for the simulation of the solidification of multicomponent alloys in the sharp-interface limit. Contrary to the case of binary alloys where a fixed point iteration…Daniil Bochkov, Tresa Pollock, Frederic Gibou·Dec 16, 2021SaveLearn
LBcuda: a high-performance CUDA port of LBsoft for simulation of colloidal systemsWe present LBcuda, a GPU accelerated version of LBsoft, our open-source MPI-based software for the simulation of multi-component colloidal flows. We describe the design principles, the optimization…Fabio Bonaccorso, Marco Lauricella, Andrea Montessori et al.·Dec 15, 2021SaveLearn
An efficient jump-diffusion approximation of the Boltzmann equationA jump-diffusion process along with a particle scheme is devised as an accurate and efficient particle solution to the Boltzmann equation. The proposed process (hereafter Gamma-Boltzmann model) is…Fabian Mies, Mohsen Sadr, Manuel Torrilhon·Dec 14, 2021SaveLearn
Geant4 modeling of the bremsstrahlung converter optimal thickness for studying the radiation damage processes in organic dyes solutionsThis work is dedicated to computer modeling of the parameters of a tungsten converter for studying the processes of radiation damage during the interaction of ionizing radiation with solutions of…Tetiana Malykhina, Vladimir Kovtun, Valentin Kasilov et al.·Dec 14, 2021SaveLearn
Physics-Informed Machine Learning for Optical Modes in CompositesWe demonstrate that embedding physics-driven constraints into machine learning process can dramatically improve accuracy and generalizability of the resulting model. Physics-informed learning is…Abantika Ghosh, Mohannad Elhamod, Jie Bu et al.·Dec 13, 2021SaveLearn
Automatic differentiation approach for reconstructing spectral functions with neural networksReconstructing spectral functions from Euclidean Green's functions is an important inverse problem in physics. The prior knowledge for specific physical systems routinely offers essential…Lingxiao Wang, Shuzhe Shi, Kai Zhou·Dec 12, 2021SaveLearn
A flux reconstruction stochastic Galerkin scheme for hyperbolic conservation lawsThe study of uncertainty propagation poses a great challenge to design numerical solvers with high fidelity. Based on the stochastic Galerkin formulation, this paper addresses the idea and…Tianbai Xiao, Jonas Kusch, Julian Koellermeier et al.·Dec 11, 2021SaveLearn
Spectrum of chain oscillation in Poiseuille flowWe simulate solid particles moving in the two-dimensional channel with the Poiseuille flow. We found that the collective chain excitation emerges with the increasing number of particles in the chain.…Maria Guskova, Lev Shchur·Dec 10, 2021SaveLearn
Transversal Flexoelectricity of Semiconductor Thinfilm under High Strain GradientThe flexoelectric behaviors of solids under high strain gradient can be distinct from that under low strain gradient. Using the generalized Bloch theorem, we investigate theoretically the transversal…Chao He, Jin-Kun Tang, Yang Yang et al.·Dec 10, 2021SaveLearn
Use of Bayesian Optimization to Understand the Structure of NucleiMonte Carlo simulations are widely used in nuclear physics to model experimental systems. In cases where there are significant unknown quantities, such as energies of states, an iterative process of…J. Hooker, J. Kovoor, K. L. Jones et al.·Dec 9, 2021SaveLearn
Application of neural network for exchange-correlation functional interpolationDensity functional theory (DFT) is one of the primary approaches to get a solution to the many-body Schrodinger equation. The essential part of the DFT theory is the exchange-correlation (XC)…Alexander Ryabov, Petr Zhilyaev·Dec 9, 2021SaveLearn
Explicitly antisymmetrized neural network layers for variational Monte Carlo simulationThe combination of neural networks and quantum Monte Carlo methods has arisen as a path forward for highly accurate electronic structure calculations. Previous proposals have combined equivariant…Jeffmin Lin, Gil Goldshlager, Lin Lin·Dec 7, 2021SaveLearn
Convolutional discrete Fourier transform method for calculating thermal neutron cross section in liquidsBeing exact at both short- and long-time limits, the Gaussian approximation is widely used to calculate neutron incoherent inelastic scattering functions in liquids. However, to overcome a few…Rong Du, Xiao-Xiao Cai·Dec 6, 2021SaveLearn
Introduction and analysis of a method for the investigation of QCD-like tree dataThe properties of decays that take place during jet formation cannot be easily deduced from the final distribution of particles in a detector. In this work, we first simulate a system of particles…Marko Jercic, Ivan Jercic, Nikola Poljak·Dec 3, 2021SaveLearn
Equivariant graph neural networks for fast electron density estimation of molecules, liquids, and solidsElectron density (r) is the fundamental variable in the calculation of ground state energy with density functional theory (DFT). Beyond total energy, features and changes in…Peter Bjørn Jørgensen, Arghya Bhowmik·Dec 1, 2021SaveLearn
Learning Large-Time-Step Molecular Dynamics with Graph Neural NetworksMolecular dynamics (MD) simulation predicts the trajectory of atoms by solving Newton's equation of motion with a numeric integrator. Due to physical constraints, the time step of the integrator need…Tianze Zheng, Weihao Gao, Chong Wang·Nov 30, 2021SaveLearn
A neural ordinary differential equation framework for modeling inelastic stress response via internal state variablesWe propose a neural network framework to preclude the need to define or observe incompletely or inaccurately defined states of a material in order to describe its response. The neural network design…R. E. Jones, A. L. Frankel, K. L. Johnson·Nov 29, 2021SaveLearn
Tailoring High-Frequency Magnonics in Monolayer Chromium TrihalidesMonolayer chromium trihalides, the archetypal two dimensional (2D) magnetic materials, are readily suggested as a promising platform for high frequency magnonics. Here we detail the spin wave…Raí M. Menezes, Denis Šabani, Cihan Bacaksiz et al.·Nov 29, 2021SaveLearn
Neural Symplectic Integrator with Hamiltonian Inductive Bias for the Gravitational N-body ProblemThe gravitational N-body problem, which is fundamentally important in astrophysics to predict the motion of N celestial bodies under the mutual gravity of each other, is usually solved…Maxwell X. Cai, Simon Portegies Zwart, Damian Podareanu·Nov 28, 2021SaveLearn
ElVibRot-MPI: parallel quantum dynamics with Smolyak algorithm for general molecular simulationA parallelized quantum dynamics package using the Smolyak algorithm for general molecular simulation is introduced in this work. The program has no limitation of the Hamiltonian form and provides…Ahai Chen, André Nauts, David Lauvergnat·Nov 26, 2021SaveLearn
TMM-Fast: A Transfer Matrix Computation Package for Multilayer Thin-Film OptimizationAchieving the desired optical response from a multilayer thin-film structure over a broad range of wavelengths and angles of incidence can be challenging. An advanced thin-film structure can consist…Alexander Luce, Ali Mahdavi, Florian Marquardt et al.·Nov 24, 2021SaveLearn
Higher Order Charge Conserving Electromagnetic Finite Element Particle in Cell MethodUntil recently, electromagnetic finite element PIC (EM-FEMPIC) methods that demonstrated charge conservation used explicit field solvers. It is only recently, that a series of papers developed the…Zane D. Crawford, O. H. Ramachandran, Scott O'Connor et al.·Nov 24, 2021SaveLearn
Noise Enhanced Neural Networks for Analytic ContinuationAnalytic continuation maps imaginary-time Green's functions obtained by various theoretical/numerical methods to real-time response functions that can be directly compared with experiments. Analytic…Juan Yao, Ce Wang, Zhiyuan Yao et al.·Nov 24, 2021SaveLearn
Computing the solutions of the van der Pol equation to arbitrary precisionWe describe an extension of the Taylor method for the numerical solution of ODEs that uses Pad\'e approximants to obtain extremely precise numerical results. The accuracy of the results is…Paolo Amore·Nov 23, 2021SaveLearn
A Reversible Unwrapping Algorithm for Constant Pressure Molecular Dynamics SimulationsMolecular simulation technologies have afforded researchers a unique look into the nanoscale interactions driving physical processes. However, a limitation for molecular dynamics (MD) simulations is…Martin Kulke, Josh V Vermaas·Nov 23, 2021SaveLearn