Atomic cluster expansion of scalar, vectorial and tensorial properties and including magnetism and charge transferThe atomic cluster expansion (Drautz, Phys. Rev. B 99, 014104 (2019)) is extended in two ways, the modelling of vectorial and tensorial atomic properties and the inclusion of atomic degrees of…Ralf Drautz·Feb 29, 2020SaveLearn
High-resolution Monte Carlo study of the order-parameter distribution of the three-dimensional Ising modelWe apply extensive Monte Carlo simulations to study the probability distribution P(m) of the order parameter m for the simple cubic Ising model with periodic boundary condition at the transition…Jiahao Xu, Alan M. Ferrenberg, David P. Landau·Feb 29, 2020SaveLearn
VegasFlow: accelerating Monte Carlo simulation across multiple hardware platformsWe present VegasFlow, a new software for fast evaluation of high dimensional integrals based on Monte Carlo integration techniques designed for platforms with hardware accelerators. The growing…Stefano Carrazza, Juan M. Cruz-Martinez·Feb 28, 2020SaveLearn
Controlled Online Optimization Learning (COOL): Finding the ground state of spin Hamiltonians with reinforcement learningReinforcement learning (RL) has become a proven method for optimizing a procedure for which success has been defined, but the specific actions needed to achieve it have not. We apply the so-called…Kyle Mills, Pooya Ronagh, Isaac Tamblyn·Feb 28, 2020SaveLearn
Derivative structure enumeration using binary decision diagramA derivative structure is a nonequivalent substitutional atomic configuration derived from a given primitive cell. The enumeration of derivative structures plays an essential role in searching for…Kohei Shinohara, Atsuto Seko, Takashi Horiyama et al.·Feb 28, 2020SaveLearn
Traps for pinning and scattering of antiferromagnetic skyrmions via magnetic properties engineeringMicromagnetic simulations have been performed to investigate the controllability of the skyrmion position in antiferromagnetic nanotracks with their magnetic properties modified spatially. In this…D. Toscano, I. A. Santece, R. C. O. Guedes et al.·Feb 28, 2020SaveLearn
A coarse-grid projection method for accelerating incompressible MHD flow simulationsCoarse grid projection (CGP) is a multiresolution technique for accelerating numerical calculations associated with a set of nonlinear evolutionary equations along with the stiff Poisson equations.…Ali Kashefi·Feb 28, 2020SaveLearn
AdaptiveBandit: A multi-armed bandit framework for adaptive sampling in molecular simulationsSampling from the equilibrium distribution has always been a major problem in molecular simulations due to the very high dimensionality of conformational space. Over several decades, many approaches…Adrià Pérez, Pablo Herrera-Nieto, Stefan Doerr et al.·Feb 28, 2020SaveLearn
Differentiable Molecular Simulations for Control and LearningMolecular dynamics simulations use statistical mechanics at the atomistic scale to enable both the elucidation of fundamental mechanisms and the engineering of matter for desired tasks. The behavior…Wujie Wang, Simon Axelrod, Rafael Gómez-Bombarelli·Feb 27, 2020SaveLearn
An Energy-stable Finite Element Method for the Simulation of Moving Contact Lines in Two-phase FlowsWe consider the dynamics of two-phase fluids, in particular the moving contact line, on a solid substrate. The dynamics are governed by the sharp-interface model consisting of the incompressible…Quan Zhao, Weiqing Ren·Feb 27, 2020SaveLearn
flatspin: A Large-Scale Artificial Spin Ice SimulatorWe present flatspin, a novel simulator for systems of interacting mesoscopic spins on a lattice, also known as artificial spin ice (ASI). Our magnetic switching criteria enables ASI dynamics to be…Johannes H. Jensen, Anders Strømberg, Odd Rune Lykkebø et al.·Feb 26, 2020SaveLearn
A greedy non-intrusive reduced order model for shallow water equationsIn this work, we develop Non-Intrusive Reduced Order Models (NIROMs) that combine Proper Orthogonal Decomposition (POD) with a Radial Basis Function (RBF) interpolation method to construct efficient…Sourav Dutta, Matthew W. Farthing, Emma Perracchione et al.·Feb 26, 2020SaveLearn
Machine Learning based prediction of noncentrosymmetric crystal materialsNoncentrosymmetric materials play a critical role in many important applications such as laser technology, communication systems,quantum computing, cybersecurity, and etc. However, the experimental…Yuqi Song, Joseph Lindsay, Yong Zhao et al.·Feb 26, 2020SaveLearn
Fitting the trajectories of particles in the equatorial plane of a magnetic dipole with epicycloidsIn this paper we discuss epicycloid approximation of the trajectories of charged particles in axisymmetric magnetic fields. Epicycloid trajectories are natural in the Guiding Center approximation and…Fancong Zeng, Konstantin Kabin, Xiao-Yun Wang et al.·Feb 26, 2020SaveLearn
Ab initio path integral Monte Carlo simulation of the Uniform Electron Gas in the High Energy Density RegimeThe response of the uniform electron gas (UEG) to an external perturbation is of paramount importance for many applications. Recently, highly accurate results for the static density response function…Tobias Dornheim, Zhandos Moldabekov, Jan Vorberger et al.·Feb 26, 2020SaveLearn
Assessing Graph-based Deep Learning Models for Predicting Flash PointFlash points of organic molecules play an important role in preventing flammability hazards and large databases of measured values exist, although millions of compounds remain unmeasured. To rapidly…Xiaoyu Sun, Nathaniel J. Krakauer, Alexander Politowicz et al.·Feb 26, 2020SaveLearn
GPU-Acceleration of the ELPA2 Distributed Eigensolver for Dense Symmetric and Hermitian EigenproblemsThe solution of eigenproblems is often a key computational bottleneck that limits the tractable system size of numerical algorithms, among them electronic structure theory in chemistry and in…Victor Wen-zhe Yu, Jonathan Moussa, Pavel Kůs et al.·Feb 25, 2020SaveLearn
Subcycling of particle orbits in variational, geometric electromagnetic particle-in-cell methodsThis paper investigates subcycling of particle orbits in variational, geometric particle-in-cell methods addressing the Vlasov--Maxwell system in magnetized plasmas. The purpose of subcycling is to…Eero Hirvijoki, Katharina Kormann, Filippo Zonta·Feb 25, 2020SaveLearn
A "String Art" approach to the design and manufacturing of optimal composite materials and structuresIn this paper we report a new promising idea on the design and manufacturing of ply composite structures, tailored to exhibit maximum stiffness under given weight constraints and loading conditions.…Igor A. Ostanin·Feb 25, 2020SaveLearn
Conservative finite-volume framework and pressure-based algorithm for flows of incompressible, ideal-gas and real-gas fluids at all speedsA conservative finite-volume framework, based on a collocated variable arrangement, for the simulation of flows at all speeds, applicable to incompressible, ideal-gas and real-gas fluids is proposed…Fabian Denner, Fabien Evrard, Berend van Wachem·Feb 24, 2020SaveLearn
Enhancing robustness and efficiency of density matrix embedding theory via semidefinite programming and local correlation potential fittingDensity matrix embedding theory (DMET) is a powerful quantum embedding method for solving strongly correlated quantum systems. Theoretically, the performance of a quantum embedding method should be…Xiaojie Wu, Michael Lindsey, Tiangang Zhou et al.·Feb 24, 2020SaveLearn
Non-isothermal Scharfetter-Gummel scheme for electro-thermal transport simulation in degenerate semiconductorsElectro-thermal transport phenomena in semiconductors are described by the non-isothermal drift-diffusion system. The equations take a remarkably simple form when assuming the Kelvin formula for the…Markus Kantner, Thomas Koprucki·Feb 24, 2020SaveLearn
Event Classification with Quantum Machine Learning in High-Energy PhysicsWe present studies of quantum algorithms exploiting machine learning to classify events of interest from background events, one of the most representative machine learning applications in high-energy…Koji Terashi, Michiru Kaneda, Tomoe Kishimoto et al.·Feb 23, 2020SaveLearn
Direct Scheme Calculation of the Kinetic Energy Functional Derivative Using Machine LearningWe report a direct scheme calculation of kinetic energy functional derivative using Machine Learning. Support Vector Regression and Kernel Ridge Regression techniques were independently employed to…H. Saidaoui, S. Kais, S. Rashkeev et al.·Feb 22, 2020SaveLearn
Quantum Element Method for Simulation of Quantum Eigenvalue ProblemsA previously developed quantum reduced-order model is revised and applied, together with the domain decomposition, to develop the quantum element method (QEM), a methodology for fast and accurate…Ming-C. Cheng·Feb 21, 2020SaveLearn