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Sparse-Stochastic Fragmented Exchange for Large-Scale Hybrid Time-Dependent Density Functional Theory Calculations.

Mykola SeredaTucker AllenNadine C BradburyKhaled Z IbrahimDaniel Neuhauser
Published in: Journal of chemical theory and computation (2024)
We extend our recently developed sparse-stochastic fragmented exchange formalism for ground-state near-gap hybrid DFT to calculate absorption spectra within linear-response time-dependent generalized Kohn-Sham DFT (LR-GKS-TDDFT) for systems consisting of thousands of valence electrons within a grid-based/plane-wave representation. A mixed deterministic/fragmented-stochastic compression of the exchange kernel, here using long-range explicit exchange functionals, provides an efficient method for accurate optical spectra. Both real-time propagation as well as frequency-resolved Casida-equation-type approaches for spectra are presented, and the method is applied to large molecular dyes.
Keyphrases
  • density functional theory
  • molecular dynamics
  • high resolution
  • neural network
  • clinical trial
  • mass spectrometry