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A new preconditioner, named "rid", accelerates time-dependent density functional theory (TDDFT) calculations. This efficient method speeds up convergence for excitation energies and polarizabilities in quantum chemistry simulations.

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Area of Science:

  • Quantum Chemistry
  • Computational Chemistry
  • Theoretical Chemistry

Background:

  • Krylov space methods are essential for solving large eigenvalue problems in quantum chemistry.
  • Preconditioners significantly enhance the convergence speed of these iterative methods.
  • Time-dependent density functional theory (TDDFT) relies on efficient computational techniques.

Purpose of the Study:

  • To design and evaluate a novel preconditioner for TDDFT calculations.
  • To improve the efficiency of solving linear systems in quantum chemistry.
  • To accelerate the convergence of excitation energies and polarizabilities.

Main Methods:

  • Systematic design of a new preconditioner based on the TDDFT-ris semiempirical model.
  • Retuning of empirical scaling factors and angular momenta of a minimal auxiliary basis.
  • Inclusion of d-functions in the auxiliary basis, resulting in the "rid" preconditioner.

Main Results:

  • The "rid" preconditioner demonstrates an average convergence in 5-6 iterations.
  • This represents a 2-3 fold speedup compared to conventional diagonal preconditioners.
  • The "rid" preconditioner achieves results comparable to existing methods without compromising accuracy.

Conclusions:

  • The "rid" preconditioner offers a significant improvement in computational efficiency for TDDFT.
  • It is a broadly applicable and effective tool for quantum chemistry simulations.
  • The developed preconditioner accelerates convergence without affecting the quality of the final results.