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Exact exchange-correlation potentials from ground-state electron densities.

Bikash Kanungo1, Paul M Zimmerman2, Vikram Gavini3,4

  • 1Department of Mechanical Engineering, University of Michigan, Ann Arbor, Michigan, 48109, USA.

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|October 5, 2019
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Summary
This summary is machine-generated.

Researchers developed a robust method to calculate exact exchange-correlation potentials from electron densities. This advances density functional theory (DFT) by aiding the development of accurate computational chemistry functionals.

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Area of Science:

  • Computational Chemistry
  • Quantum Mechanics
  • Materials Science

Background:

  • Accurate exchange-correlation functionals are crucial for Density Functional Theory (DFT) to model quantum mechanical behavior.
  • Developing these functionals is challenging due to the complexity of many-electron systems.
  • The inverse DFT problem, mapping electron density to potential, is key for functional development.

Purpose of the Study:

  • To present a numerically robust and accurate scheme for evaluating exact exchange-correlation potentials.
  • To address the unresolved challenge of the inverse DFT problem.
  • To aid the development of improved DFT functionals.

Main Methods:

  • The inverse DFT problem is framed as a constrained optimization problem.
  • A finite-element basis, systematically convergent and complete, is used for discretization.
  • The scheme evaluates exact exchange-correlation potentials from correlated ab-initio densities.

Main Results:

  • Demonstrated accuracy and efficacy for both weakly and strongly correlated molecular systems.
  • Successfully applied to systems with up to 58 electrons.
  • Validated the approach for realistic polyatomic molecules.

Conclusions:

  • The presented scheme offers a numerically robust and accurate solution for the inverse DFT problem.
  • This method facilitates the development of more accurate exchange-correlation functionals.
  • The approach is applicable to a range of molecular systems, including complex ones.