Active space approaches combining coupled-cluster and perturbation theory for ground states and excited states

Abstract

We evaluate the performance of approaches that combine coupled-cluster and perturbation theory based on a predefined active space of orbitals. Coupled-cluster theory is used to treat excitations that are internal to the active space and perturbation theory is used for all other excitations, which are at least partially external to the active space. We consider a variety of schemes that differ in how the internal and external excitations are coupled. Such approaches are presented for ground states and excited states within the equation-of-motion formalism. Results are given for the ionisation potentials and electron affinities of a test set of small molecules and for the correlation energy and band gap of a few periodic solids.

GRAPHICAL ABSTRACT

Keywords:

• Coupled-cluster theory
• active space
• solid-state
• band gap

Acknowledgments

It is a pleasure to dedicate this work to Prof. Jürgen Gauss in honour of his seminal contributions to quantum chemistry and especially coupled-cluster theory. We thank Xiao Wang for helpful discussions and a careful reading of this manuscript. This work was supported in part by the National Science Foundation under Grant No. CHE-1848369. M.F.L. was supported in part by the National Science Foundation Graduate Research Fellowship Grant DGE-1746045. We acknowledge computing resources from Columbia University's Shared Research Computing Facility project, which is supported by NIH Research Facility Improvement Grant 1G20RR030893-01, and associated funds from the New York State Empire State Development, Division of Science Technology and Innovation (NYSTAR) Contract C090171, both awarded April 15, 2010. We also acknowledge computing resources from the Flatiron Institute. The Flatiron Institute is a division of the Simons Foundation.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported in part by the National Science Foundation under Grant No. CHE-1848369. M.F.L. was supported in part by the National Science Foundation Graduate Research Fellowship Grant DGE-1746045. We acknowledge computing resources from Columbia University's Shared Research Computing Facility project, which is supported by NIH Research Facility Improvement Grant 1G20RR030893-01, and associated funds from the New York State Empire State Development, Division of Science Technology and Innovation (NYSTAR) Contract C090171, both awarded April 15, 2010.