PyQMC: An all-Python real-space quantum Monte Carlo module in PySCF

William A Wheeler; Shivesh Pathak; Kevin G Kleiner; Shunyue Yuan; João N B Rodrigues; Cooper Lorsung; Kittithat Krongchon; Yueqing Chang; Yiqing Zhou; Brian Busemeyer; Kiel T Williams; Alexander Muñoz; Chun Yu Chow; Lucas K Wagner

doi:10.1063/5.0139024

PyQMC: An all-Python real-space quantum Monte Carlo module in PySCF

J Chem Phys. 2023 Mar 21;158(11):114801. doi: 10.1063/5.0139024.

Authors

Affiliations

¹ Department of Materials Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA.
² Center for Computing Research, Sandia National Laboratories, Albuquerque, New Mexico 87123, USA.
³ Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA.
⁴ Department of Applied Physics and Materials Science, California Institute of Technology, Pasadena, California 91125, USA.
⁵ Centro de Ciências Naturais e Humanas, Universidade Federal do ABC-UFABC, Santo André, São Paulo 09210-580, Brazil.
⁶ Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA.
⁷ Department of Physics and Astronomy, Rutgers University, Piscataway, New Jersey 08854, USA.
⁸ Laboratory of Atomic and Solid State Physics, Cornell University, Ithaca, New York 14853, USA.
⁹ Millenium Management, New York, New York 10022, USA.
¹⁰ Dynata, Plano, Texas 75024, USA.

PMID: 36948839
DOI: 10.1063/5.0139024

Abstract

We describe a new open-source Python-based package for high accuracy correlated electron calculations using quantum Monte Carlo (QMC) in real space: PyQMC. PyQMC implements modern versions of QMC algorithms in an accessible format, enabling algorithmic development and easy implementation of complex workflows. Tight integration with the PySCF environment allows for a simple comparison between QMC calculations and other many-body wave function techniques, as well as access to high accuracy trial wave functions.