TY - JOUR
T1 - PySCF
T2 - the Python-based simulations of chemistry framework
AU - Sun, Qiming
AU - Berkelbach, Timothy C.
AU - Blunt, Nick S.
AU - Booth, George H.
AU - Guo, Sheng
AU - Li, Zhendong
AU - Liu, Junzi
AU - McClain, James D.
AU - Sayfutyarova, Elvira R.
AU - Sharma, Sandeep
AU - Wouters, Sebastian
AU - Chan, Garnet Kin Lic
N1 - Publisher Copyright:
© 2017 Wiley Periodicals, Inc.
PY - 2018/1
Y1 - 2018/1
N2 - Python-based simulations of chemistry framework (PySCF) is a general-purpose electronic structure platform designed from the ground up to emphasize code simplicity, so as to facilitate new method development and enable flexible computational workflows. The package provides a wide range of tools to support simulations of finite-size systems, extended systems with periodic boundary conditions, low-dimensional periodic systems, and custom Hamiltonians, using mean-field and post-mean-field methods with standard Gaussian basis functions. To ensure ease of extensibility, PySCF uses the Python language to implement almost all of its features, while computationally critical paths are implemented with heavily optimized C routines. Using this combined Python/C implementation, the package is as efficient as the best existing C or Fortran-based quantum chemistry programs. In this paper, we document the capabilities and design philosophy of the current version of the PySCF package. WIREs Comput Mol Sci 2018, 8:e1340. doi: 10.1002/wcms.1340. This article is categorized under: Structure and Mechanism > Computational Materials Science Electronic Structure Theory > Ab Initio Electronic Structure Methods Software > Quantum Chemistry.
AB - Python-based simulations of chemistry framework (PySCF) is a general-purpose electronic structure platform designed from the ground up to emphasize code simplicity, so as to facilitate new method development and enable flexible computational workflows. The package provides a wide range of tools to support simulations of finite-size systems, extended systems with periodic boundary conditions, low-dimensional periodic systems, and custom Hamiltonians, using mean-field and post-mean-field methods with standard Gaussian basis functions. To ensure ease of extensibility, PySCF uses the Python language to implement almost all of its features, while computationally critical paths are implemented with heavily optimized C routines. Using this combined Python/C implementation, the package is as efficient as the best existing C or Fortran-based quantum chemistry programs. In this paper, we document the capabilities and design philosophy of the current version of the PySCF package. WIREs Comput Mol Sci 2018, 8:e1340. doi: 10.1002/wcms.1340. This article is categorized under: Structure and Mechanism > Computational Materials Science Electronic Structure Theory > Ab Initio Electronic Structure Methods Software > Quantum Chemistry.
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U2 - 10.1002/wcms.1340
DO - 10.1002/wcms.1340
M3 - Article
AN - SCOPUS:85032742040
SN - 1759-0876
VL - 8
JO - Wiley Interdisciplinary Reviews: Computational Molecular Science
JF - Wiley Interdisciplinary Reviews: Computational Molecular Science
IS - 1
M1 - e1340
ER -