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PyADF - A scripting framework for multiscale quantum chemistry.

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Title: PyADF - A scripting framework for multiscale quantum chemistry.
Authors: Jacob, Christoph R.1, Beyhan, S. Maya2, Bulo, Rosa E.2, Gomes, André Severo Pereira3, Götz, Andreas W.4, Kiewisch, Karin2, Sikkema, Jetze2, Visscher, Lucas2
Source: Journal of Computational Chemistry. Jul2011, Vol. 32 Issue 10, p2328-2338. 11p. 7 Diagrams.
Subjects: Quantum chemistry, Python programming language, Simulation methods & models, Quantum theory, Workflow software, Object-oriented programming languages
Abstract: Applications of quantum chemistry have evolved from single or a few calculations to more complicated workflows, in which a series of interrelated computational tasks is performed. In particular multiscale simulations, which combine different levels of accuracy, typically require a large number of individual calculations that depend on each other. Consequently, there is a need to automate such workflows. For this purpose we have developed P YA DF, a scripting framework for quantum chemistry. P YA DF handles all steps necessary in a typical workflow in quantum chemistry and is easily extensible due to its object-oriented implementation in the Python programming language. We give an overview of the capabilities of P YA DF and illustrate its usefulness in quantum-chemical multiscale simulations with a number of examples taken from recent applications. © 2011 Wiley Periodicals, Inc. J Comput Chem, 2011 [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:Applications of quantum chemistry have evolved from single or a few calculations to more complicated workflows, in which a series of interrelated computational tasks is performed. In particular multiscale simulations, which combine different levels of accuracy, typically require a large number of individual calculations that depend on each other. Consequently, there is a need to automate such workflows. For this purpose we have developed P YA DF, a scripting framework for quantum chemistry. P YA DF handles all steps necessary in a typical workflow in quantum chemistry and is easily extensible due to its object-oriented implementation in the Python programming language. We give an overview of the capabilities of P YA DF and illustrate its usefulness in quantum-chemical multiscale simulations with a number of examples taken from recent applications. © 2011 Wiley Periodicals, Inc. J Comput Chem, 2011 [ABSTRACT FROM AUTHOR]
ISSN:01928651
DOI:10.1002/jcc.21810