Automated Selection of Active Orbital Spaces

TL;DR

This paper introduces an automated method for selecting active orbital spaces in quantum-chemical multi-configuration methods, reducing reliance on expert knowledge and enabling more systematic and black-box applications.

Contribution

The authors develop an automated active orbital space selection technique leveraging the iterative density matrix renormalization group, enhancing systematic assessment and reducing manual intervention.

Findings

Automated selection improves accuracy of multi-configuration methods.

Method enables black-box application of complex quantum-chemical models.

Systematic assessment reduces errors from poor orbital choices.

Abstract

One of the key challenges of quantum-chemical multi-configuration methods is the necessity to manually select orbitals for the active space. This selection requires both expertise and experience and can therefore impose severe limitations on the applicability of this most general class of ab initio methods. A poor choice of the active orbital space may yield even qualitatively wrong results. This is obviously a severe problem, especially for wave function methods that are designed to be systematically improvable. Here, we show how the iterative nature of the density matrix renormalization group combined with its capability to include up to about one hundred orbitals in the active space can be exploited for a systematic assessment and selection of active orbitals. These benefits allow us to implement an automated approach for active orbital space selection, which can turn multi-configuration models into black box approaches.