The Ising Model with Hybrid Monte CarloThe Ising model is a simple statistical model for ferromagnetism. There are analytic solutions for low dimensions and very efficient Monte Carlo methods, such as cluster algorithms, for simulating…Johann Ostmeyer, Evan Berkowitz, Thomas Luu et al.·Dec 6, 2019SaveLearn
A real-time time-dependent density functional tight-binding implementation for semiclassical excited state electron-nuclear dynamics and pump-probe spectroscopy simulationsThe increasing need to simulate the dynamics of photoexcited molecular and nanosystems in the sub-picosecond regime demands new efficient tools able to describe the quantum nature of matter at a low…Franco P. Bonafé, Bálint Aradi, Ben Hourahine et al.·Dec 6, 2019SaveLearn
Contracting Arbitrary Tensor Networks: General Approximate Algorithm and Applications in Graphical Models and Quantum Circuit SimulationsWe present a general method for approximately contracting tensor networks with an arbitrary connectivity. This enables us to release the computational power of tensor networks to wide use in…Feng Pan, Pengfei Zhou, Sujie Li et al.·Dec 6, 2019SaveLearn
Numerical simulation of internal incompressible flows with enhanced variants of dissipative inlet/outlet conditions. Part 1: Mathematical formulations and solution methodsThe paper presents numerical methods for unsteady flows of a viscous incompressible fluid in internal domains with many inlet/outlet sections. The novel variants of dissipative boundary conditions…Jacek Szumbarski·Dec 6, 2019SaveLearn
Single Domain Multiple Decompositions for Particle-in-Cell simulationsAs a multi-purpose Particle-In-Cell (PIC) code, Smilei gathers many different features in a single software. Combining some of them is challenging. In particular, spectral solvers and patch based…Julien Derouillat, Arnaud Beck·Dec 6, 2019SaveLearn
Multisector parabolic-equation approach to compute acoustic scattering by noncanonically shaped impenetrable objectsA lesser-known but powerful application of parabolic equation methods is to the target scattering problem. In this paper, we use noncanonically shaped objects to establish the limits of applicability…Adith Ramamurti, David C. Calvo·Dec 5, 2019SaveLearn
Real-World Oceanographic Simulations on the GPU using a Two-Dimensional Finite-Volume SchemeIn this work, we take a modern high-resolution finite-volume scheme for solving the rotational shallow-water equations and extend it with features required to run real-world ocean simulations. Our…André R. Brodtkorb, Håvard Heitlo Holm·Dec 5, 2019SaveLearn
High order ADER schemes for continuum mechanicsIn this paper we first review the development of high order ADER finite volume and ADER discontinuous Galerkin schemes on fixed and moving meshes, since their introduction in 1999 by Toro et al. We…Saray Busto, Simone Chiocchetti, Michael Dumbser et al.·Dec 4, 2019SaveLearn
FLAME: a library of atomistic modeling environmentsFLAME is a software package to perform a wide range of atomistic simulations for exploring the potential energy surfaces (PES) of complex condensed matter systems. The range of methods include…Maximilian Amsler, Samare Rostami, Hossein Tahmasbi et al.·Dec 4, 2019SaveLearn
Accelerating Surface Tension Calculation in SPH via Particle Classification & Monte Carlo IntegrationSurface tension has a strong influence on the shape of fluid interfaces. We propose a method to calculate the corresponding forces efficiently. In contrast to several previous approaches, we…Fernando Zorrilla, Johannes Sappl, Wolfgang Rauch et al.·Dec 4, 2019SaveLearn
Acoustic scattering by two fluid confocal prolate spheroidsThe exact spheroidal-function series solution for the time-harmonic acoustic scattering of a plane wave by two fluid confocal prolate spheroids is developed and a numerical implementation is…Edmundo Federico Lavia·Dec 3, 2019SaveLearn
Transforming the Lindblad Equation into a System of Linear Equations: Performance Optimization and Parallelization of an AlgorithmWith their constantly increasing peak performance and memory capacity, modern supercomputers offer new perspectives on numerical studies of open many-body quantum systems. These systems are often…Iosif Meyerov, Evgeny Kozinov, Alexey Liniov et al.·Dec 3, 2019SaveLearn
Geometry of martensite needles in shape memory alloysWe study the geometry of needle-shaped domains in shape-memory alloys. Needle-shaped domains are ubiquitously found in martensites around macroscopic interfaces between regions which are laminated in…Sergio Conti, Martin Lenz, Nora Lüthen et al.·Dec 3, 2019SaveLearn
Physics-informed neural networks for inverse problems in nano-optics and metamaterialsIn this paper we employ the emerging paradigm of physics-informed neural networks (PINNs) for the solution of representative inverse scattering problems in photonic metamaterials and nano-optics…Yuyao Chen, Lu Lu, George Em Karniadakis et al.·Dec 2, 2019SaveLearn
TeaNet: universal neural network interatomic potential inspired by iterative electronic relaxationsA universal interatomic potential for an arbitrary set of chemical elements is urgently needed in computational materials science. Graph convolution neural network (GCN) has rich expressive power,…So Takamoto, Satoshi Izumi, Ju Li·Dec 2, 2019SaveLearn
Diversified properties of carbon substitutions in siliceneThe theoretical framework, which is built from the first-principles results, is successfully developed for investigating emergent two-dimensional (2D) materials, as it is clearly illustrated by…Hai-Duong Pham, Shih-Yang Lin, Godfrey Gumbs et al.·Dec 1, 2019SaveLearn
Data-driven molecular modeling with the generalized Langevin equationThe complexity of molecular dynamics simulations necessitates dimension reduction and coarse-graining techniques to enable tractable computation. The generalized Langevin equation (GLE) describes…Francesca Grogan, Huan Lei, Xiantao Li et al.·Nov 30, 2019SaveLearn
The computation of seismic normal modes with rotation as a quadratic eigenvalue problemA new approach is presented to compute the seismic normal modes of a fully heterogeneous, rotating planet. Special care is taken to separate out the essential spectrum in the presence of a fluid…Jia Shi, Ruipeng Li, Yuanzhe Xi et al.·Nov 30, 2019SaveLearn
ESpinS: A program for classical Monte-Carlo simulations of spin systemsWe present ESpinS (Esfahan Spin Simulation) package to evaluate the thermodynamic properties of spin systems described by a spin model Hamiltonian. In addition to the Heisenberg exchange…Nafise Rezaei, Mojtaba Alaei, Hadi Akbarzadeh·Nov 29, 2019SaveLearn
Progressive-Growing of Generative Adversarial Networks for Metasurface OptimizationGenerative adversarial networks, which can generate metasurfaces based on a training set of high performance device layouts, have the potential to significantly reduce the computational cost of the…Fufang Wen, Jiaqi Jiang, Jonathan A. Fan·Nov 29, 2019SaveLearn
A finite-difference lattice Boltzmann model with second-order accuracy of time and space for incompressible flowIn this paper, a kind of finite-difference lattice Boltzmann method with the second-order accuracy of time and space (T2S2-FDLBM) is proposed. In this method, a new simplified two-stage fourth order…Xinmeng Chen, Zhenhua Chai, Huili Wang et al.·Nov 29, 2019SaveLearn
All-analytical evaluation of the singular integrals involved in the Method of MomentsSurface Integral Equation (SIE) methods routinely require the integration of the singular Green's function or its gradient over Basis Functions (BF) and Testing Functions (TF). Many techniques…Denis Tihon, Christophe Craeye·Nov 28, 2019SaveLearn
Numerically stable eigenmode extraction in 3D periodic metamaterialsA numerical method is presented to compute the eigenmodes supported by three dimensional (3D) metamaterials using the Method of Moments (MoM). The method relies on interstitial equivalent currents…Denis Tihon, Valentina Sozio, Nilufer A. Ozdemir et al.·Nov 28, 2019SaveLearn
Saturated random packing built of arbitrary polygons under random sequential adsorption protocolRandom packings and their properties are a popular and active field of research. Numerical algorithms that can efficiently generate them are useful tools in their study. This paper focuses on random…Michał Cieśla, Piotr Kubala, Ge Zhang·Nov 28, 2019SaveLearn
Deep Density: circumventing the Kohn-Sham equations via symmetry preserving neural networksThe recently developed Deep Potential [Phys. Rev. Lett. 120, 143001, 2018] is a powerful method to represent general inter-atomic potentials using deep neural networks. The success of Deep Potential…Leonardo Zepeda-Núñez, Yixiao Chen, Jiefu Zhang et al.·Nov 27, 2019SaveLearn