Psi4NumPy: An Interactive Quantum Chemistry Programming Environment for Reference Implementations and Rapid Development
| Autor: | Alexander G. Heide, Asem Alenaizan, Andrew M. James, Rollin A. King, Boyi Zhang, Adam S. Abbott, Tianyuan Zhang, Leonardo dos Anjos Cunha, Daniel G. A. Smith, Henry F. Schaefer, Lori A. Burns, Eric J. Berquist, Konrad Patkowski, A. Eugene DePrince, Ashutosh Kumar, Daniel Neuhauser, C. David Sherrill, Dominic A. Sirianni, Andrew C. Simmonett, Francesco A. Evangelista, Justin M. Turney, Marvin H. Lechner, Tyler Y. Takeshita, Daniel R. Nascimento, T. Daniel Crawford, Jeffrey B. Schriber, Jonathan M. Waldrop |
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| Rok vydání: | 2018 |
| Předmět: |
Quantum chemical
Source code 010304 chemical physics Programming language Computer science media_common.quotation_subject NumPy Python (programming language) 010402 general chemistry computer.software_genre 01 natural sciences Execution time Quantum chemistry 0104 chemical sciences Computer Science Applications 0103 physical sciences Linear algebra Physical and Theoretical Chemistry Implementation computer media_common computer.programming_language |
| Zdroj: | Journal of chemical theory and computation. 14(7) |
| ISSN: | 1549-9626 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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