MC-PDFT Nuclear Gradients and L-PDFT Energies with Meta and Hybrid Meta On-Top Functionals for Ground- and Excited-State Geometry Optimization and Vertical Excitation Energies
Matthew R. Hennefarth, Younghwan Kim, Bhavnesh Jangid, Jacob Wardzala, Matthew R. Hermes, Donald G. Truhlar, Laura Gagliardi

TL;DR
This paper develops and implements analytic nuclear gradients for MC-PDFT and L-PDFT using new meta-GA and hybrid meta-GA on-top functionals, enabling accurate geometry optimizations and excitation energy calculations for complex molecules.
Contribution
It introduces the first analytic nuclear gradient implementation for MC-PDFT with meta-GA functionals, improving the accuracy of excited-state calculations.
Findings
MC23 functional outperforms other meta-GA functionals for excitation energies.
MC-PDFT with MC23 is comparable to NEVPT2 in accuracy.
MC-PDFT surpasses TD-DFT in vertical excitation energy predictions.
Abstract
Multiconfiguration pair-density functional theory (MC-PDFT) is a post-MCSCF multireference electronic-structure method that explicitly models strong electron correlation, and linearized pair-density functional theory (L-PDFT) is a recently developed multi-state extension that can accurately model conical intersections and locally-avoided crossings. Because MC-PDFT and L-PDFT rely on an on-top energy functional, their accuracy depends on the quality of the on-top functional used. Recent work has introduced translated meta-gradient-approximation (meta-GA) on-top functionals, and specifically the MC23 hybrid meta-GA on-top functional, which is the first on-top functional specifically optimized for MC-PDFT. Here we report the derivation and implementation of analytic nuclear gradients for MC-PDFT calculations using meta-GA and hybrid meta-GA on-top functionals. This development also enables…
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