PyCC: A Reference Quantum Chemistry Python Package for Education, Validation, and Rapid Prototyping
Abstract
PyCC is a Python-based quantum chemistry package that emphasizes coupled cluster and related methods. Developed over the last five years, PyCC's purpose is to provide a clear reference implementation that will serve as a validation suite for production code, a platform for rapid prototyping and testing of new methods, and an educational resource for newcomers to the field. The package covers both closed- and open-shell single-determinant references in spatial- and spin-orbital formulations for the coupled cluster hierarchy through triples-including methods such as CC3, as well as for MP2 and CI methods. PyCC provides a broad range of molecular properties such as analytic first and second energy derivatives including gradients, Hessians, polarizabilities and atomic polar tensors, as well as non-energy-derivative properties, such as velocity-gauge atomic polar tensors and diagonal Born-Oppenheimer corrections, plus dynamic linear response functions, and excitation energies. The package includes a number of unique capabilities, such as real-time CC propagation (up through CC3), atomic axial tensors for simulating vibrational circular dichroism spectra at the MP2 and CI levels, and local correlation methods including perturbation-aware correlation domains. The code is designed around a shared Wavefunction base and a method-agnostic derivative layer that enables a new method to inherit the full property set once it supplies its reduced densities and their first-order responses. PyCC is fully open source and available on GitHub under the BSD 3-clause license.
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BibTeX
@misc{crawford2026pycc,
title = {{PyCC: A Reference Quantum Chemistry Python Package for Education, Validation, and Rapid Prototyping}},
author = {T. Daniel Crawford and Benjamin G. Peyton and Zhe Wang and Aparna Krishnan and Brendan M. Shumberger and Jose Madriaga and Joshua Atta-Kumi and Aaron De Clercq and Ritvik Prabhu},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.04107},
eprint = {2610.04107},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.04107},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - PyCC: A Reference Quantum Chemistry Python Package for Education, Validation, and Rapid Prototyping
AU - T. Daniel Crawford
AU - Benjamin G. Peyton
AU - Zhe Wang
AU - Aparna Krishnan
AU - Brendan M. Shumberger
AU - Jose Madriaga
AU - Joshua Atta-Kumi
AU - Aaron De Clercq
AU - Ritvik Prabhu
PY - 2026
DA - 2026/10/02
PB - arXiv
DO - 10.48550/arxiv.2610.04107
UR - https://arxiv.org/abs/2610.04107
AB - PyCC is a Python-based quantum chemistry package that emphasizes coupled cluster and related methods. Developed over the last five years, PyCC's purpose is to provide a clear reference implementation that will serve as a validation suite for production code, a platform for rapid prototyping and testing of new methods, and an educational resource for newcomers to the field. The package covers both closed- and open-shell single-determinant references in spatial- and spin-orbital formulations for the coupled cluster hierarchy through triples-including methods such as CC3, as well as for MP2 and CI methods. PyCC provides a broad range of molecular properties such as analytic first and second energy derivatives including gradients, Hessians, polarizabilities and atomic polar tensors, as well as non-energy-derivative properties, such as velocity-gauge atomic polar tensors and diagonal Born-Oppenheimer corrections, plus dynamic linear response functions, and excitation energies. The package includes a number of unique capabilities, such as real-time CC propagation (up through CC3), atomic axial tensors for simulating vibrational circular dichroism spectra at the MP2 and CI levels, and local correlation methods including perturbation-aware correlation domains. The code is designed around a shared Wavefunction base and a method-agnostic derivative layer that enables a new method to inherit the full property set once it supplies its reduced densities and their first-order responses. PyCC is fully open source and available on GitHub under the BSD 3-clause license.
ER -