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Deterministic/Fragmented-Stochastic Exchange for Large-Scale Hybrid DFT Calculations.

Nadine C BradburyTucker AllenMinh NguyenDaniel Neuhauser
Published in: Journal of chemical theory and computation (2023)
We develop an efficient approach to evaluate range-separated exact exchange for grid- or plane-wave-based representations within the generalized Kohn-Sham-density functional theory (GKS-DFT) framework. The Coulomb kernel is fragmented in reciprocal space, and we employ a mixed deterministic-stochastic representation, retaining long-wavelength (low- k ) contributions deterministically and using a sparse ("fragmented") stochastic basis for the high- k part. Coupled with a projection of the Hamiltonian onto a subspace of valence and conduction states from a prior local-DFT calculation, this method allows for the calculation of the long-range exchange of large molecular systems with hundreds and potentially thousands of coupled valence states delocalized over millions of grid points. We find that even a small number of valence and conduction states is sufficient for converging the HOMO and LUMO energies of the GKS-DFT. Excellent tuning of long-range separated hybrids (RSH) is easily obtained in the method for very large systems, as exemplified here for the chlorophyll hexamer of Photosystem II with 1320 electrons.
Keyphrases
  • density functional theory
  • molecular dynamics
  • working memory
  • monte carlo
  • computed tomography
  • magnetic resonance imaging
  • electron transfer