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Updated: May 28, 2025

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
Published on: April 8, 2020
Accelerating inverse Kohn-Sham calculations using reduced density matrices
Bikash Kanungo1, Soumi Tribedi2, Paul M Zimmerman2
1Department of Mechanical Engineering, University of Michigan, Ann Arbor, Michigan 48109, USA.
Abstract:
The Ryabinkin-Kohut-Staroverov (RKS) and Kanungo-Zimmerman-Gavini (KZG) methods offer two approaches to find exchange-correlation (XC) potentials from ground state densities. The RKS method utilizes the one- and two-particle reduced density matrices to alleviate any numerical artifacts stemming from a finite basis (e.g., Gaussian- or Slater-type orbitals). The KZG approach relies solely on the density to find the XC potential by combining a systematically convergent finite-element basis with appropriate asymptotic correction on the target density. The RKS method, being designed for a finite basis, offers computational efficiency. The KZG method, using a complete basis, provides higher accuracy. In this work, we combine both methods to simultaneously afford accuracy and efficiency. In particular, we use the RKS solution as an initial guess for the KZG method to attain a significant 3-11× speedup. This work also presents a direct comparison of the XC potentials from the RKS and the KZG method and their relative accuracy on various weakly and strongly correlated molecules, using their ground state solutions from accurate configuration interaction calculations solved in a Slater orbital basis.
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