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Robust and Efficient Spin Purification for Determinantal Configuration Interaction.

B Scott Fales1, Edward G Hohenstein2,3, Benjamin G Levine1

  • 1Department of Chemistry, Michigan State University , East Lansing, Michigan 48824, United States.

Journal of Chemical Theory and Computation
|August 4, 2017
PubMed
Summary
This summary is machine-generated.

Numerical errors in quantum chemistry can cause spin contamination. We tested five purification schemes, finding the first-order spin penalty method optimal for accurate electron spin (⟨Ŝ²⟩) calculations.

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Area of Science:

  • Quantum Chemistry
  • Computational Chemistry
  • Materials Science

Background:

  • Floating-point arithmetic limitations can cause catastrophic failures in quantum chemical algorithms.
  • Numerical errors in Davidson diagonalization can lead to spin contamination, resulting in incorrect electronic structure calculations.

Purpose of the Study:

  • To investigate five purification schemes for ensuring desired electron spin expectation values (⟨Ŝ²⟩) in quantum chemical calculations.
  • To address spin contamination issues in high-accuracy quantum chemistry.

Main Methods:

  • Developed and tested five spin purification schemes: projection, penalty, and iterative approaches.
  • Utilized a graphics processing unit-accelerated algorithm for S²c matrix-vector products.
  • Applied methods to benchmark systems and computed excited states of a silver cluster (Ag₁₉).

Main Results:

  • The first-order spin penalty method demonstrated optimal performance.
  • First-order and Löwdin projection methods also showed fast convergence to the desired spin state.
  • Spin purification was essential for calculating stable excited states of Ag₁₉ using the state-averaged complete active space self-consistent field method.

Conclusions:

  • The first-order spin penalty method is an effective solution for spin contamination in quantum chemistry.
  • These spin purification techniques are valuable for accurate modeling of systems like plasmonic nanomaterials.
  • Multireference methods are crucial for predicting excited states with multiply excited character.