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Towards benchmark second-order correlation energies for large atoms. II. Angular extrapolation problems.

J R Flores1, R Słupski, K Jankowski

  • 1Departamento de Química Física, Facultad de Química, Universidad de Vigo, E-36200 Vigo, Pontevedra, Spain.

The Journal of Chemical Physics
|March 18, 2006
PubMed
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We developed asymptotic expansions for extrapolating atomic correlation energies. This method accurately predicts energies for symmetry-adapted pairs, improving upon existing techniques.

Area of Science:

  • Computational Chemistry
  • Quantum Chemistry
  • Atomic Physics

Background:

  • Accurate calculation of electron correlation energies is crucial in quantum chemistry.
  • Atomic second-order Moller-Plesset (MP2) correlation energies are computationally intensive to obtain directly.

Purpose of the Study:

  • To investigate the efficacy of asymptotic expansions (AEs) for angular momentum extrapolation of atomic MP2 correlation energies.
  • To develop a general method for extrapolating correlation energies applicable to various methods and systems.

Main Methods:

  • Defined AEs using partial wave (PW) increments from finite element MP2 (FEM-MP2) and variational perturbation methods.
  • Determined optimal AEs for all symmetry-adapted pairs (SAPs) in large atoms using accurate FEM PW increments.

Related Experiment Videos

  • Assessed the impact of PW increment errors on AE coefficients.

    • Main Results:

    • The first AE coefficient was determined with high accuracy; the second coefficient had larger errors.
    • Identified optimal angular momentum values (lopt) for extrapolation procedures.
    • Found that first AE coefficients align with theoretical expressions for He-type systems, with modifications for specific SAPs.

    Conclusions:

    • The proposed AE method provides highly accurate first AE coefficients for both Slater-type orbital (STO) and FEM Hartree-Fock orbitals.
    • The study offers a robust approach for angular momentum extrapolation of correlation energies.
    • Compared favorably against standard extrapolation techniques, highlighting sources of inaccuracy.