4.7 Article

PSI4NUMPY: An Interactive Quantum Chemistry Programming Environment for Reference Implementations and Rapid Development

Journal

JOURNAL OF CHEMICAL THEORY AND COMPUTATION
Volume 14, Issue 7, Pages 3504-3511

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acs.jctc.8b00286

Keywords

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Funding

  1. U.S. National Science Foundation [ACI-1449723, CHE-1566192, CHE-1661604, CHE-1554354]
  2. CAREER award [CHE-1351978]
  3. Software Fellowship from the Molecular Sciences Software Institute - U.S. National Science Foundation [ACI-1547580]
  4. Studienstiftung des Deutschen Volkes
  5. National Science Foundation under the NSF Center for Chemical Evolution [CHE-1504217]
  6. NASA Astrobiology Program under the NSF Center for Chemical Evolution [CHE-1504217]
  7. U.S. Department of Energy [DE-SC0016004]
  8. Research Fellowship of the Alfred P. Sloan Foundation
  9. National Science Foundation [CHE-1465064, DMR-1611382]
  10. Direct For Mathematical & Physical Scien
  11. Division Of Chemistry [1566192] Funding Source: National Science Foundation
  12. Division Of Chemistry
  13. Direct For Mathematical & Physical Scien [1504217] Funding Source: National Science Foundation

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PSI4NUMPY demonstrates the use of efficient computational kernels from the open-source PSI4 program through the popular NUMPY library for linear algebra in Python to facilitate the rapid development of clear, understandable Python computer code for new quantum chemical methods, while maintaining a relatively low execution time. Using these tools, reference implementations have been created for a number of methods, including self-consistent field (SCF), SCF response, many-body perturbation theory, coupled-cluster theory, configuration interaction, and symmetry-adapted perturbation theory. Furthermore, several reference codes have been integrated into Jupyter notebooks, allowing background, underlying theory, and formula information to be associated with the implementation. PSI4NUMPY tools and associated reference implementations can lower the barrier for future development of quantum chemistry methods. These implementations also demonstrate the power of the hybrid C++/Python programming approach employed by the PSI4 program.

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