Recent developments in the PySCF program package

PySCF is a Python-based general-purpose electronic structure platform that supports first-principles simulations of molecules and solids as well as accelerates the development of new methodology and complex computational workflows. This paper explains the design and philosophy behind PySCF that enab...

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Bibliographic Details
Published in:The Journal of chemical physics 2020-07, Vol.153 (2), p.024109-024109
Main Authors: Sun, Qiming, Zhang, Xing, Banerjee, Samragni, Bao, Peng, Barbry, Marc, Blunt, Nick S., Bogdanov, Nikolay A., Booth, George H., Chen, Jia, Cui, Zhi-Hao, Eriksen, Janus J., Gao, Yang, Guo, Sheng, Hermann, Jan, Hermes, Matthew R., Koh, Kevin, Koval, Peter, Lehtola, Susi, Li, Zhendong, Liu, Junzi, Mardirossian, Narbe, McClain, James D., Motta, Mario, Mussard, Bastien, Pham, Hung Q., Pulkin, Artem, Purwanto, Wirawan, Robinson, Paul J., Ronca, Enrico, Sayfutyarova, Elvira R., Scheurer, Maximilian, Schurkus, Henry F., Smith, James E. T., Sun, Chong, Sun, Shi-Ning, Upadhyay, Shiv, Wagner, Lucas K., Wang, Xiao, White, Alec, Whitfield, James Daniel, Williamson, Mark J., Wouters, Sebastian, Yang, Jun, Yu, Jason M., Zhu, Tianyu, Berkelbach, Timothy C., Sharma, Sandeep, Sokolov, Alexander Yu, Chan, Garnet Kin-Lic
Format: Article
Language:English
Subjects:
complete-active space self-consistent field
complex solids
Computer simulation
density functional theory
density matrix renormalization group
Electronic structure
First principles
INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY
Machine learning
Materials science
programming languages
Quantum chemistry
Quantum computing
quantum information
Quantum phenomena
self consistent field methods
Supports
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Description
Summary:PySCF is a Python-based general-purpose electronic structure platform that supports first-principles simulations of molecules and solids as well as accelerates the development of new methodology and complex computational workflows. This paper explains the design and philosophy behind PySCF that enables it to meet these twin objectives. With several case studies, we show how users can easily implement their own methods using PySCF as a development environment. We then summarize the capabilities of PySCF for molecular and solid-state simulations. Finally, we describe the growing ecosystem of projects that use PySCF across the domains of quantum chemistry, materials science, machine learning, and quantum information science.
ISSN:0021-9606
1089-7690
DOI:10.1063/5.0006074