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BasisOpt: A Python package for quantum chemistry basis set optimization.

Robert A Shaw1, J Grant Hill1

  • 1Department of Chemistry, University of Sheffield, Sheffield S3 7HF, United Kingdom.

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|July 25, 2023
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Summary
This summary is machine-generated.

BasisOpt is a new, open-source tool that automates the optimization of basis sets for molecular quantum chemistry calculations. This tool enhances accuracy and efficiency by providing an accessible workflow and visualization for basis set development.

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Area of Science:

  • Computational Chemistry
  • Quantum Chemistry
  • Method Development

Background:

  • Basis sets are crucial for the accuracy and efficiency of molecular quantum chemical calculations.
  • Current basis set development is often hampered by non-public, opaque methodologies and tools.
  • Lack of accessibility limits reproducibility and advancement in computational chemistry.

Purpose of the Study:

  • To introduce BasisOpt, a novel, user-friendly tool for automated basis set optimization.
  • To provide an open and accessible framework for basis set development adaptable to various quantum chemistry programs.
  • To standardize basis set testing and visualize optimization processes and results.

Main Methods:

  • Development of an automated optimization framework (BasisOpt) with an accessible workflow.
  • Implementation of standardized procedures for testing and evaluating optimized basis sets.
  • Integration of visualization tools for optimized basis sets and the optimization trajectory.

Main Results:

  • Demonstrated successful optimization of a density fitting basis set for noble gases (He, Ne, Ar).
  • Showcased re-optimization of def2-SVP basis set exponents for molecular systems, moving beyond atomic optimization.
  • Achieved automatic reduction of a large basis set to a compact (10s5p) composition while minimizing energy for noble gases.

Conclusions:

  • BasisOpt offers a transparent, adaptable, and efficient solution for basis set optimization in quantum chemistry.
  • The tool facilitates the development of novel, high-performance basis sets, advancing computational chemistry.
  • Open accessibility and visualization capabilities promote reproducibility and broader adoption of optimized basis sets.