Modeling and computation for non-equilibrium gas dynamics: beyond kinetic relaxation modelThe non-equilibrium gas dynamics is described by the Boltzmann equation, which can be solved numerically through the deterministic and stochastic methods. Due to the complicated collision term of the…Xiaocong Xu, Yipei Chen, Kun Xu·Oct 26, 2020SaveLearn
Multi-resolution lattice Green's function method for incompressible flowsWe propose a multi-resolution strategy that is compatible with the lattice Green's function (LGF) technique for solving viscous, incompressible flows on unbounded domains. The LGF method exploits the…Ke Yu, Benedikt Dorschner, Tim Colonius·Oct 25, 2020SaveLearn
SPHinXsys: an open-source multi-physics and multi-resolution library based on smoothed particle hydrodynamicsIn this paper, we present an open-source multi-resolution and multi-physics library: SPHinXsys (pronunciation: s'finksis) which is an acronym for Smoothed Particle…Chi Zhang, Massoud Rezavand, Yujie Zhu et al.·Oct 23, 2020SaveLearn
Cross-platform programming model for many-core lattice Boltzmann simulationsWe present a novel, hardware-agnostic implementation strategy for lattice Boltzmann (LB) simulations, which yields massive performance on homogeneous and heterogeneous many-core platforms. Based…Jonas Latt, Christophe Coreixas, Joël Beny·Oct 22, 2020SaveLearn
Image Inversion and Uncertainty Quantification for Constitutive Laws of Pattern FormationThe forward problems of pattern formation have been greatly empowered by extensive theoretical studies and simulations, however, the inverse problem is less well understood. It remains unclear how…Hongbo Zhao, Richard D. Braatz, Martin Z. Bazant·Oct 20, 2020SaveLearn
Comparison of the MSMS and NanoShaper molecular surface triangulation codes in the TABI Poisson--Boltzmann solverThe Poisson-Boltzmann (PB) implicit solvent model is a popular framework for studying the electrostatics of biomolecules immersed in water with dissolved salt. In this model the dielectric interface…Leighton Wilson, Robert Krasny·Oct 20, 2020SaveLearn
Serpent neutronics model of Wendelstein 7-X for 14.1 MeV neutronsIn this work, a Serpent 2 neutronics model of the Wendelstein 7-X (W7-X) stellarator is prepared, and an response function for the Scintillating-Fibre neutron detector (SciFi) is calculated using the…Simppa Äkäslompolo, Jan Paul Koschinsky, Joona Kontula et al.·Oct 20, 2020SaveLearn
Computational Aspects of Speed-Dependent Voigt and Rautian ProfilesFor accurate line-by-line modeling of molecular cross sections several physical processes "beyond Voigt" have to be considered. For the speed-dependent Voigt and Rautian profiles (SDV, SDR) and the…Franz Schreier, Philipp Hochstaffl·Oct 19, 2020SaveLearn
Fast and robust all-electron density functional theory calculations in solids using orthogonalized enriched finite elementsWe present a computationally efficient approach to perform systematically convergent real-space all-electron Kohn-Sham DFT calculations for solids using an enriched finite element (FE) basis. The…Nelson D. Rufus, Bikash Kanungo, Vikram Gavini·Oct 19, 2020SaveLearn
The Graph Theoretic Approach for Nodal Cross Section ParameterizationPresently, models for the parameterization of cross sections for nodal diffusion nuclear reactor calculations at different conditions using histories and branches are developed from reactor physics…Brendan Kochunas, Krishna Garikipati, Matthew Duschenes et al.·Oct 19, 2020SaveLearn
Machine Learning with bond information for local structure optimizations in surface scienceLocal optimization of adsorption systems inherently involves different scales: within the substrate, within the molecule, and between molecule and substrate. In this work, we show how the explicit…Estefanía Garijo del Río, Sami Kaappa, José A. Garrido Torres et al.·Oct 19, 2020SaveLearn
VegasFlow: accelerating Monte Carlo simulation across platformsIn this work we demonstrate the usage of the VegasFlow library on multidevice situations: multi-GPU in one single node and multi-node in a cluster. VegasFlow is a new software for fast evaluation of…Juan M. Cruz-Martinez, Stefano Carrazza·Oct 19, 2020SaveLearn
Physics-informed neural networks for solving forward and inverse flow problems via the Boltzmann-BGK formulationIn this study, we employ physics-informed neural networks (PINNs) to solve forward and inverse problems via the Boltzmann-BGK formulation (PINN-BGK), enabling PINNs to model flows in both the…Qin Lou, Xuhui Meng, George Em Karniadakis·Oct 19, 2020SaveLearn
Ab initio relativistic treatment of the intercombination a3-X1+ Cameron system of the CO moleculeThe intercombination a3 - X1+ Cameron system of carbon monoxide has been computationally studied in the framework of multi-reference Fock space coupled cluster method with the use of…Nikolai S. Mosyagin, Alexander V. Oleynichenko, Andrei Zaitsevskii et al.·Oct 17, 2020SaveLearn
FPGAs-as-a-Service Toolkit (FaaST)Computing needs for high energy physics are already intensive and are expected to increase drastically in the coming years. In this context, heterogeneous computing, specifically as-a-service…Dylan Sheldon Rankin, Jeffrey Krupa, Philip Harris et al.·Oct 16, 2020SaveLearn
Towards Reflectivity profile inversion through Artificial Neural NetworksThe goal of Specular Neutron and X-ray Reflectometry is to infer materials Scattering Length Density (SLD) profiles from experimental reflectivity curves. This paper focuses on investigating an…Juan Manuel Carmona-Loaiza, Zamaan Raza·Oct 15, 2020SaveLearn
NanoNET: an extendable Python framework for semi-empirical tight-binding modelsWe present a novel open-source Python framework called NanoNET (Nanoscale Non-equilibrium Electron Transport) for modelling electronic structure and transport. Our method is based on the…M. V. Klymenko, J. A. Vaitkus, J. S. Smith et al.·Oct 15, 2020SaveLearn
Unified gas-kinetic wave-particle methods V: diatomic molecular flowIn this paper, the unified gas-kinetic wave-particle (UGKWP) method is further developed for diatomic gas with the energy exchange between translational and rotational modes for flow study in all…Xiaocong Xu, Yipei Chen, Chang Liu et al.·Oct 14, 2020SaveLearn
Stochastic embeddings of dynamical phenomena through variational autoencodersSystem identification in scenarios where the observed number of variables is less than the degrees of freedom in the dynamics is an important challenge. In this work we tackle this problem by using a…Constantino A. Garcia, Paulo Felix, Jesus M. Presedo et al.·Oct 13, 2020SaveLearn
A Chebyshev-Tau spectral method for normal modes of underwater sound propagation with a layered marine environmentThe normal mode model is one of the most popular approaches for solving underwater sound propagation problems. Among other methods, the finite difference method is widely used in classic normal mode…Houwang Tu, Yongxian Wang, Qiang Lan et al.·Oct 13, 2020SaveLearn
The Adaptive Shift Method in Full Configuration Interaction Quantum Monte Carlo: Development and ApplicationsIn a recent paper, we proposed the adaptive shift method for correcting the undersampling bias of the initiator-FCIQMC. The method allows faster convergence with the number of walkers to the FCI…Khaldoon Ghanem, Kai Guther, Ali Alavi·Oct 12, 2020SaveLearn
Focusing the Latent Heat Release in 3D Phase Field Simulations of Dendritic Crystal GrowthWe investigate a family of phase field models for simulating dendritic growth of a pure supercooled substance. The central object of interest is the reaction term in the Allen-Cahn equation, which is…Pavel Strachota, Aleš Wodecki, Michal Beneš·Oct 12, 2020SaveLearn
Automatic Particle Trajectory Classification in Plasma SimulationsNumerical simulations of plasma flows are crucial for advancing our understanding of microscopic processes that drive the global plasma dynamics in fusion devices, space, and astrophysical systems.…Stefano Markidis, Ivy Peng, Artur Podobas et al.·Oct 11, 2020SaveLearn
Convergence to the fixed-node limit in deep variational Monte CarloVariational quantum Monte Carlo (QMC) is an ab-initio method for solving the electronic Schr\"odinger equation that is exact in principle, but limited by the flexibility of the available ansatzes in…Zeno Schätzle, Jan Hermann, Frank Noé·Oct 11, 2020SaveLearn
Unsupervised Neural Networks for Quantum Eigenvalue ProblemsEigenvalue problems are critical to several fields of science and engineering. We present a novel unsupervised neural network for discovering eigenfunctions and eigenvalues for differential…Henry Jin, Marios Mattheakis, Pavlos Protopapas·Oct 10, 2020SaveLearn