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The Sign Learning Kink (SiLK) based Quantum Monte Carlo (QMC)
(2015)
  • Xiaoyao Ma, Louisiana State University
  • Frank Loffler, Louisiana State University
  • Randall W. Hall, Department of Natural Sciences and Mathematics, Dominican University of California
  • Karol kowalski, Pacific Northwest National Laboratory
  • Mark Jarrell
  • Juana Moreno, Louisiana State University
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)
Publication Date
2015
Citation Information
Xiaoyao Ma, Frank Loffler, Randall W. Hall, Karol kowalski, et al.. "The Sign Learning Kink (SiLK) based Quantum Monte Carlo (QMC)" (2015)
Available at: http://works.bepress.com/randall_hall/61/