Wheeler William A, Pathak Shivesh, Kleiner Kevin G, Yuan Shunyue, Rodrigues João N B, Lorsung Cooper, Krongchon Kittithat, Chang Yueqing, Zhou Yiqing, Busemeyer Brian, Williams Kiel T, Muñoz Alexander, Chow Chun Yu, Wagner Lucas K
Department of Materials Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA.
Center for Computing Research, Sandia National Laboratories, Albuquerque, New Mexico 87123, USA.
J Chem Phys. 2023 Mar 21;158(11):114801. doi: 10.1063/5.0139024.
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.
我们描述了一个新的基于Python的开源软件包PyQMC，用于在实空间中使用量子蒙特卡罗（QMC）进行高精度关联电子计算。PyQMC以一种易于理解的格式实现了现代版本的QMC算法，有助于算法开发和复杂工作流程的轻松实现。与PySCF环境的紧密集成允许在QMC计算和其他多体波函数技术之间进行简单比较，还能获取高精度的试探波函数。
