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Selfconsistent random phase approximation methods.

Jason M Yu1, Brian D Nguyen1, Jeffrey Tsai1

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Researchers explored self-consistent calculations for ground-state energies using random phase approximation (RPA) within density functional theory. A new method, GKS-spRPA, improves accuracy by better satisfying functional self-consistency (FSC).

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Area of Science:

  • Quantum Chemistry
  • Computational Physics
  • Materials Science

Background:

  • Density functional theory (DFT) is a powerful tool for electronic structure calculations.
  • Random Phase Approximation (RPA) offers a way to calculate correlation energies.
  • Achieving self-consistency in RPA calculations within DFT remains a challenge.

Purpose of the Study:

  • To review recent advancements in self-consistent calculations of ground-state energies using RPA within DFT.
  • To introduce and evaluate the generalized Kohn-Sham semicanonical projected RPA (GKS-spRPA) method.
  • To highlight the importance of functional self-consistency (FSC) for accurate electronic structure calculations.

Main Methods:

  • Review of existing self-consistent RPA schemes and their limitations regarding FSC.
  • Detailed examination of the GKS-spRPA method and its approach to satisfying FSC.
  • Comparative analysis of GKS-spRPA against non-selfconsistent RPA, OEP-RPA, GW, and orbital optimization methods.

Main Results:

  • Existing self-consistent RPA schemes generally violate FSC.
  • GKS-spRPA demonstrates significant improvements in densities, binding energies, and molecular properties.
  • GKS-spRPA accurately predicts ionization potentials and electron affinities.

Conclusions:

  • Functional self-consistency (FSC) is crucial for accurate density functional calculations, especially for explicitly potential-dependent functionals.
  • GKS-spRPA represents a substantial step towards satisfying FSC in RPA calculations.
  • The findings suggest that the Kohn-Sham potential should be defined via FSC for improved accuracy.