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Generalized Kohn-Sham iteration on Banach spaces.

Andre LaestadiusMarkus PenzErik I TellgrenMichael RuggenthalerSimen KvaalTrygve Helgaker
Published in: The Journal of chemical physics (2018)
A detailed account of the Kohn-Sham (KS) algorithm from quantum chemistry, formulated rigorously in the very general setting of convex analysis on Banach spaces, is given here. Starting from a Levy-Lieb-type functional, its convex and lower semi-continuous extension is regularized to obtain differentiability. This extra layer allows us to rigorously introduce, in contrast to the common unregularized approach, a well-defined KS iteration scheme. Convergence in a weak sense is then proven. This generalized formulation is applicable to a wide range of different density-functional theories and possibly even to models outside of quantum mechanics.
Keyphrases
  • density functional theory
  • molecular dynamics
  • magnetic resonance
  • machine learning
  • double blind
  • deep learning
  • magnetic resonance imaging
  • computed tomography