Psi4NumPy: An Interactive Quantum Chemistry Programming Environment for Reference Implementations and Rapid Development

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 r...

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Published in:Journal of chemical theory and computation Vol. 14; no. 7; p. 3504
Main Authors: Smith, Daniel G A, Burns, Lori A, Sirianni, Dominic A, Nascimento, Daniel R, Kumar, Ashutosh, James, Andrew M, Schriber, Jeffrey B, Zhang, Tianyuan, Zhang, Boyi, Abbott, Adam S, Berquist, Eric J, Lechner, Marvin H, Cunha, Leonardo A, Heide, Alexander G, Waldrop, Jonathan M, Takeshita, Tyler Y, Alenaizan, Asem, Neuhauser, Daniel, King, Rollin A, Simmonett, Andrew C, Turney, Justin M, Schaefer, Henry F, Evangelista, Francesco A, DePrince, A Eugene, Crawford, T Daniel, Patkowski, Konrad, Sherrill, C David
Format: Journal Article
Language:English
Published: United States 10.07.2018
ISSN:1549-9626, 1549-9626
Online Access:Get more information
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Summary: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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ISSN:1549-9626
1549-9626
DOI:10.1021/acs.jctc.8b00286