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A local correlation model that yields intrinsically smooth potential-energy surfaces.

Joseph E Subotnik1, Martin Head-Gordon

  • 1Department of Chemistry, University of California, Berkeley, California 94720, USA. subotnik@post.harvard.edu

The Journal of Chemical Physics
|August 27, 2005
PubMed
Summary

This study introduces a novel algorithm for calculating local coupled-cluster doubles (LCCD) energies, ensuring smooth potential-energy surfaces. The method is designed for speed, making it suitable for large-scale computational chemistry applications.

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Area of Science:

  • Computational Chemistry
  • Quantum Chemistry
  • Theoretical Chemistry

Background:

  • Accurate potential-energy surfaces are crucial for understanding chemical reactions.
  • Local coupled-cluster doubles (LCCD) methods offer a balance between accuracy and computational cost.
  • Existing LCCD algorithms can struggle with smooth potential-energy surface generation.

Purpose of the Study:

  • To develop a new algorithm for computing LCCD energies.
  • To ensure the resulting potential-energy surfaces are rigorously smooth.
  • To create a method applicable to large molecular systems.

Main Methods:

  • The algorithm iteratively solves for a subset of correlation amplitudes.
  • Remaining amplitudes are treated using second-order perturbation theory.

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  • Bump functions are employed to smooth the transition between solved and perturbation-treated amplitudes, invoking the implicit function theorem for differentiability.

    • Main Results:

    • The developed algorithm computes LCCD energies that yield rigorously smooth potential-energy surfaces.
    • The method ensures infinite differentiability of the LCCD energy with respect to nuclear coordinates.
    • The approach utilizes localized orthonormal occupied and virtual orbitals, avoiding explicit amplitude domains or redundant orbitals.

    Conclusions:

    • The new algorithm provides a robust method for generating smooth potential-energy surfaces in LCCD calculations.
    • This approach is computationally efficient and scalable for large systems.
    • The methodology is expected to be adaptable to other electron correlation methods.