Orbital Optimization and Neural-Network-Assisted Configuration Interaction Calculations of Rydberg States
Rydberg excited states of molecules pose a challenge for electronic structure calculations because of their highly diffuse electron distribution. Even large and elaborate atomic basis sets tend to underrepresent the long-range tail, overly confining the Rydberg state. An approach is presented here where the molecular orbitals are variationally optimized for the excited state using a plane wave basis set in a Hartree-Fock calculation, followed by a configuration interaction calculation. The use of excited state optimized orbitals greatly enhances the convergence of the many-body calculation, as illustrated by a full configuration interaction calculation of the 2s Rydberg state of H<sub>2</sub>. A neural-network-based selective configuration interaction approach is then applied to calculations of 3s and 3p states of H<sub>2</sub>O and NH<sub>3</sub>. The obtained values of excitation energy are in close agreement with experimental measurements as well as previous many-body calculations where sufficiently diffuse atomic basis sets were used. Calculations using atomic basis sets lacking extra diffuse functions, such as aug-cc-pVTZ, give significantly higher estimates due to confinement of the Rydberg states.
Institutions
- University of Trieste (IT)
- University of Iceland (IS)
- Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
- Max-Planck-Institut für Kohlenforschung (DE)
- Max Planck Institute for the Science of Light (DE)
Publication Details
- Journal
- Journal of Chemical Theory and Computation
- Published
- 2026-03-23
- DOI
- https://doi.org/10.1021/acs.jctc.5c01837
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 0.00