PyQMC: an all-Python real-space quantum Monte Carlo code
ORAL
Abstract
PyQMC is a new, easy-to-use implementation of real-space quantum Monte Carlo (QMC) for highly-accurate simulations of correlated electron systems. The all-Python code enables fast development of new techniques and flexible, complex workflows, such as the recent work from our group on QMC excited states [1]. Integration with the electronic structure package PySCF [2, 3] leverages available tools and facilitates direct comparison with many other ab initio methods. The wide availability of Python libraries offers additional flexibility. With PyQMC's parallelization implementation, cloud resources or HPC can be used with the same code. The vectorized architecture ensures good performance and is GPU ready. PyQMC includes variational Monte Carlo, wave function optimization, and diffusion Monte Carlo on molecules and solids, and is under active development. The code is freely available at https://github.com/WagnerGroup/pyqmc.
1. S. Pathak, et. al. (2020). arXiv preprint arXiv:2009.13556.
2. Q. Sun, et.al. (2018). WIREs Comput. Mol. Sci., 8: e1340. doi:10.1002/wcms.1340
3. Q. Sun, et. al. (2020). J. Chem. Phys., 153, 024109 (2020). doi:10.1063/5.0006074.
1. S. Pathak, et. al. (2020). arXiv preprint arXiv:2009.13556.
2. Q. Sun, et.al. (2018). WIREs Comput. Mol. Sci., 8: e1340. doi:10.1002/wcms.1340
3. Q. Sun, et. al. (2020). J. Chem. Phys., 153, 024109 (2020). doi:10.1063/5.0006074.
*This work is funded by the U.S. National Science Foundation via Award No. 1931258.
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Presenters
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William Wheeler
- University of Illinois at Urbana-Champaign