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Conditional probability density functional theory

Ryan Pederson, Jielun Chen (陈捷伦), Steven R. White, and Kieron Burke
Phys. Rev. B 105, 245138 – Published 24 June 2022

Abstract

We present conditional probability (CP) density functional theory (DFT) as a formally exact theory. In essence, CP-DFT determines the ground-state energy of a system by finding the CP density from a series of independent Kohn-Sham (KS) DFT calculations. By directly calculating CP densities, we bypass the need for an approximate XC energy functional. In this paper we discuss and derive several key properties of the CP density and corresponding CP-KS potential. Illustrative examples are used throughout to help guide the reader through the various concepts and theory presented. We explore a suitable CP-DFT approximation and discuss exact conditions, limitations, and results for selected examples.

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  • Received 23 March 2022
  • Revised 16 May 2022
  • Accepted 3 June 2022

DOI:https://doi.org/10.1103/PhysRevB.105.245138

©2022 American Physical Society

Physics Subject Headings (PhySH)

Condensed Matter, Materials & Applied Physics

Authors & Affiliations

Ryan Pederson*, Jielun Chen (陈捷伦), and Steven R. White

  • Department of Physics and Astronomy, University of California, Irvine, California 92697, USA

Kieron Burke

  • Department of Chemistry, University of California, Irvine, California 92697, USA and Department of Physics and Astronomy, University of California, Irvine, California 92697, USA

  • *pedersor@uci.edu
  • kieron@uci.edu

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Issue

Vol. 105, Iss. 24 — 15 June 2022

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