Recent developments in the PySCF program package.

By Qiming Sun, Xing Zhang, S. Banerjee, Peng Bao, M. Barbry, N. S. Blunt, N. Bogdanov, George H. Booth, Jia Chen, Z. Cui and 39 more. Journal of Chemical Physics, 2020

1,259 citations recorded by the source corpus.

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.

Subfields: Atomic and Molecular Physics, and Optics, Catalysis, Materials Chemistry

View Paper: https://www.semanticscholar.org/paper/0359909680789bed8f541af1b6dd36584e2dcb89

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In Materials Chemistry

1. Jure Leskovec
2. Yuxiao Dong
3. Matthias Fey
4. Hongyu Ren
5. Weihua Hu

Citations in the corpus

• OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs (2021, methodology): “, 2006) or PySCF (Sun et al., 2020), both of which provide cheap but less accurate 3D structure of molecules.”