This website contains examples of data-driven quantum chemistry (DDQC) methods from the “Data-Driven acceleration of coupled-cluster and perturbation theory methods” book chapter by Grier M. Jones, P. D. Varuna S. Pathirage, and Konstantinos D. Vogiatzis in Quantum Chemistry in the Age of Machine Learning. Examples on this website include the generation of the potential energy curve of the symmetric O-H bond stretch of water using data-driven coupled-cluster singles and doubles (DDCCSD) and the symmetric angle bend of ozone with data-driven complete active space second-order perturbation theory (DDCASPT2).

Installation

For information on installing the code please refer to the GitHub repository.

Authors

The book chapter, webpage, and GitHub repository are maintained by the group of Dr. Konstantinos Vogiatzis at the University of Tennessee, Knoxville. The original DDCCSD code was written by Dr. Jacob Townsend. The DDCCSD example on this website was developed by P. D. Varuna S. Pathirage and the DDCASPT2 example by Grier M. Jones.

Contact Information

For more information and bug reports, please contact Grier Jones gjones39@vols.utk.edu or Dr. Konstantinos Vogiatzis kvogiatz@utk.edu.

Acknowledgements

We gratefully acknowledge the National Science Foundation (CHE-1800237, CHE-2143354) for financial support of this work.

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