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Correlation Energy Extrapolation by Many-Body Expansion. | LitMetric

Correlation Energy Extrapolation by Many-Body Expansion.

J Phys Chem A

Department of Chemistry and Ames Laboratory (USDOE), Iowa State University, Ames, Iowa 50011, United States.

Published: February 2017

AI Article Synopsis

  • Accounting for electron correlation is essential for accurate molecular energy calculations, but traditional methods like full configuration interaction (CI) are too computationally heavy for larger chemical systems due to their high expense.
  • A new method called correlation energy extrapolation by many-body expansion (CEEMBE) is introduced, which approximates CI calculations while reducing computational costs and memory needs.
  • CEEMBE shows strong performance in benchmark tests on diatomic fluorine and ozone, achieving results close to CI calculations (within ∼1 millihartree) while using significantly less computational resources.

Article Abstract

Accounting for electron correlation is required for high accuracy calculations of molecular energies. The full configuration interaction (CI) approach can fully capture the electron correlation within a given basis, but it does so at a computational expense that is impractical for all but the smallest chemical systems. In this work, a new methodology is presented to approximate configuration interaction calculations at a reduced computational expense and memory requirement, namely, the correlation energy extrapolation by many-body expansion (CEEMBE). This method combines a MBE approximation of the CI energy with an extrapolated correction obtained from CI calculations using subsets of the virtual orbitals. The extrapolation approach is inspired by, and analogous to, the method of correlation energy extrapolation by intrinsic scaling. Benchmark calculations of the new method are performed on diatomic fluorine and ozone. The method consistently achieves agreement with CI calculations to within a few mhartree and often achieves agreement to within ∼1 millihartree or less, while requiring significantly less computational resources.

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Source
http://dx.doi.org/10.1021/acs.jpca.6b10953DOI Listing

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