Analytic gradients for multiconfiguration pair-density functional theory with density fitting: Development and application to geometry optimization in the ground and excited states

Thais R. Scott, Meagan S. Oakley, Matthew R. Hermes, Andrew M. Sand, Roland Lindh, Donald G. Truhlar, Laura Gagliardi

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Density fitting reduces the computational cost of both energy and gradient calculations by avoiding the computation and manipulation of four-index electron repulsion integrals. With this algorithm, one can efficiently optimize the geometries of large systems with an accurate multireference treatment. Here, we present the derivation of multiconfiguration pair-density functional theory for energies and analytic gradients with density fitting. Six systems are studied, and the results are compared to those obtained with no approximation to the electron repulsion integrals and to the results obtained by complete active space second-order perturbation theory. With the new approach, there is an increase in the speed of computation with a negligible loss in accuracy. Smaller grid sizes have also been used to reduce the computational cost of multiconfiguration pair-density functional theory with little effect on the optimized geometries and gradient values.

Original languageEnglish (US)
Article number074108
JournalJournal of Chemical Physics
Volume154
Issue number7
DOIs
StatePublished - Feb 21 2021

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