Excited state mean-field theory without automatic differentiation.

J Chem Phys

Department of Chemistry, University of California, Berkeley, California 94720, USA.

Published: May 2020

We present a formulation of excited state mean-field theory in which the derivatives with respect to the wave function parameters needed for wave function optimization (not to be confused with nuclear derivatives) are expressed analytically in terms of a collection of Fock-like matrices. By avoiding the use of automatic differentiation and grouping Fock builds together, we find that the number of times we must access the memory-intensive two-electron integrals can be greatly reduced. Furthermore, the new formulation allows the theory to exploit the existing strategies for efficient Fock matrix construction. We demonstrate this advantage explicitly via the shell-pair screening strategy with which we achieve a cubic overall cost scaling. Using this more efficient implementation, we also examine the theory's ability to predict charge redistribution during charge transfer excitations. Using the coupled cluster as a benchmark, we find that by capturing orbital relaxation effects and avoiding self-interaction errors, excited state mean field theory out-performs other low-cost methods when predicting the charge density changes of charge transfer excitations.

Download full-text PDF

Source
http://dx.doi.org/10.1063/5.0003438DOI Listing

Publication Analysis

Top Keywords

excited state
12
state mean-field
8
mean-field theory
8
automatic differentiation
8
wave function
8
charge transfer
8
transfer excitations
8
theory
4
theory automatic
4
differentiation formulation
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!