The Sign Learning Kink (SiLK) based Quantum Monte Carlo for Molecular Systems

Document Type

Article

Source

The Journal of Chemical Physics

ISSN

1089-7690

Volume

144

Issue

1

Publication Date

1-1-2015

Department

Natural Sciences and Mathematics

Abstract

Purpose The Sign Learning Kink (SiLK) based Quantum Monte Carlo (QMC) method is based on Feynman's path integral formulation of quantum mechanics, and can reduce the minus sign problem when calculating energies in atomic and molecular systems. The code requires as input the one and two electron integrals, which usually are computed using the NWChem package. Example input files are distributed with this package. The code also requires an parameter file, specifying run-time parameters such as input/output directories, or specific code parameters. For all example inputs a corresponding parameter file is distributed as well. Systems The code has been tuned for cluster systems supporting MPI and Fortran 90 compilers. Contents This package contains the source code and sample data. Acknowledgments This code was developed by Xiaoyao Ma (maxiaoyao@gmail.com) and Frank Löffler (knarf@cct.lsu.edu) with the assistance of Randall Hall (randall.hall@dominican.edu), Karol Kowalski (karol.kowalski@pnnl.gov), Mark Jarrell (jarrellphysics@gmail.com), and Juana Moreno (moreno@phys.lsu.edu)

Comments

Available through arXiv.org

Rights

Copyright 2016, American Institute of Physics.

Publisher Statement

This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics.

PubMed ID

26747795

Link to Full Text

Contact Author

Share

COinS