PySCF
Computing Applications (HPC) Apache-2.0 (Free)
About
A simulation framework for ab initio electronic structure theory. It supports Hartree-Fock, DFT, Coupled Cluster (CCSD), and CI methods, emphasizing simplicity, extensibility, and efficient handling of large systems.
Key Features
- Methods: HF, DFT, MP2, CCSD, CASSCF, FCI
- Basis: Gaussian basis sets, ECPs
- Periodic: PBC, k-point sampling
- Integration: NumPy, GPU via CuPy
Citation
Sun, Q. et al. PySCF: the Python-based simulations of chemistry framework. WIREs Comput. Mol. Sci. 8, e1340 (2018). DOI:10.1002/wcms.1340
Frequently Asked Questions
What is PySCF?
PySCF is a computing applications (hpc) application available in the Paramus App Store. A simulation framework for ab initio electronic structure theory. It supports Hartree-Fock, DFT, Coupled Cluster (CCSD), and CI methods, emphasizing simplicity, extensibility, and efficient handling of large systems.
Is PySCF free to use?
Yes. PySCF is distributed under the Apache-2.0 (Free) license and is available at no cost through the Paramus App Store.
How do I install PySCF?
PySCF is installed through Paramus Chemistry OS, an on-premise Windows platform for computational chemistry. Open the Paramus App Store in your local installation and select PySCF for one-click deployment.
What are the key features of PySCF?
Key features of PySCF include: Methods: HF, DFT, MP2, CCSD, CASSCF, FCI; Basis: Gaussian basis sets, ECPs; Periodic: PBC, k-point sampling; Integration: NumPy, GPU via CuPy.
What type of application is PySCF?
PySCF belongs to the “Computing Applications (HPC)” category in the Paramus App Store. It runs on Paramus Chemistry OS and can also be accessed through Paramus Cloud for supported workflows.
What platform does PySCF run on?
PySCF runs on Paramus Chemistry OS, a Windows-based on-premise platform that provides local compute power for demanding simulations. It requires a Paramus OS installation with appropriate hardware resources.
Can PySCF be automated or integrated with AI workflows?
Yes. PySCF is available as part of the Paramus ecosystem which supports MCP (Model Context Protocol) tools for AI-driven automation. This enables integration with large language models and automated research pipelines.
How should I cite PySCF in publications?
The recommended citation for PySCF is: Sun, Q. et al. PySCF: the Python-based simulations of chemistry framework. WIREs Comput. Mol. Sci. 8, e1340 (2018). DOI:10.1002/wcms.1340