Performance of Automatic Active Space Selection for Electronic Excitation Energies

TL;DR

This paper benchmarks an automatic active space selection method for electronic excitation energy calculations, demonstrating its effectiveness and providing practical guidance for improved accuracy and efficiency in quantum chemistry computations.

Contribution

It introduces and evaluates the Active Space Finder software for automatic active space construction in CASSCF calculations, enhancing state balance and computational performance.

Findings

The method produces accurate excitation energies across multiple datasets.

Automatic selection improves efficiency over manual active space choice.

Practical recommendations for setting configurations are provided.

Abstract

Computation of electronic spectra is one of the most important applications of methods capturing static electron correlation, including complete-active-space self-consistent field (CASSCF) and post-CASSCF theories. Performance of these techniques critically depends on the active space construction, both in terms of accuracy and computational effort. In this work we benchmark the performance of automatic active space construction, as implemented in the Active Space Finder software, for the computation of electronic excitation energies. The multi-step procedure constructs meaningful molecular orbitals and selects the most suitable active space based on information from more approximate correlated calculations. It aims to tackle a key difficulty in computing excitation energies with CASSCF: choosing active spaces that are balanced for several electronic states. The Active Space Finder is tested with several established data sets of small and medium-sized molecules and shows encouraging results. We evaluate multiple setting configurations and provide practical recommendations.