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Automatic algorithms for completeness-optimization of Gaussian basis sets.

Susi Lehtola1

  • 1Department of Physics, University of Helsinki, P. O. Box 64, FI-00014 University of Helsinki, Finland; Department of Applied Physics, COMP Center of Excellence, P. O. Box 11100, FI-00076, Aalto, Finland.

Journal of Computational Chemistry
|December 10, 2014
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Summary
This summary is machine-generated.

We present a new C++ implementation for optimizing basis sets in computational chemistry. This method enhances accuracy and efficiency for calculating molecular properties, with recommendations for further improvements.

Keywords:
Gaussianbasis setcompleteness-optimizationcoupled clustergeneral contractionmagnetic shieldingsegmented contractiontotal energy

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Area of Science:

  • Computational chemistry
  • Quantum chemistry

Background:

  • Basis set incompleteness is a major source of error in quantum chemical calculations.
  • The completeness-optimization approach offers a systematic way to mitigate this error.

Purpose of the Study:

  • To present a generic, object-oriented C++ implementation of the completeness-optimization approach within the ERKALE program.
  • To recommend incorporating basis set stability scans into the completeness-optimization procedure.
  • To demonstrate the algorithm's versatility for various properties and computational setups.

Main Methods:

  • Implementation of the completeness-optimization approach in C++.
  • Development of algorithms independent of the specific property or level of theory.
  • Inclusion of routines for general and segmented basis set contraction.
  • Demonstration using argon atom's total energy and nuclear magnetic shielding constant.

Main Results:

  • A flexible and easily interfaced C++ implementation of the completeness-optimization method is now available.
  • The implemented algorithms are demonstrated to be effective for calculating atomic properties.
  • The procedure is shown to be adaptable for generating auxiliary basis sets.

Conclusions:

  • The presented implementation provides a robust tool for generating optimized basis sets, improving computational efficiency and accuracy.
  • Basis set stability scans are recommended for enhancing the completeness-optimization procedure.
  • The method is poised for application in generating cost-efficient basis sets for diverse molecular properties.