Flexibilities of wavelets as a computational basis set for large-scale electronic structure calculations

Ratcliff, Laura E. and Dawson, William and Fisicaro, Giuseppe and Caliste, Damien and Mohr, Stephan and Degomme, Augustin and Videau, Brice and Cristiglio, Viviana and Stella, Martina and D'Alessandro, Marco and Goedecker, Stefan and Nakajima, Takahito and Deutsch, Thierry and Genovese, Luigi. (2020) Flexibilities of wavelets as a computational basis set for large-scale electronic structure calculations. Journal of Chemical Physics, 152 (19). p. 194110.

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Official URL: https://edoc.unibas.ch/79492/

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The BigDFT project was started in 2005 with the aim of testing the advantages of using a Daubechies wavelet basis set for Kohn-Sham (KS) density functional theory (DFT) with pseudopotentials. This project led to the creation of the BigDFT code, which employs a computational approach with optimal features of flexibility, performance, and precision of the results. In particular, the employed formalism has enabled the implementation of an algorithm able to tackle DFT calculations of large systems, up to many thousands of atoms, with a computational effort that scales linearly with the number of atoms. In this work, we recall some of the features that have been made possible by the peculiar properties of Daubechies wavelets. In particular, we focus our attention on the usage of DFT for large-scale systems. We show how the localized description of the KS problem, emerging from the features of the basis set, is helpful in providing a simplified description of large-scale electronic structure calculations. We provide some examples on how such a simplified description can be employed, and we consider, among the case-studies, the SARS-CoV-2 main protease.
Faculties and Departments:05 Faculty of Science > Departement Physik > Physik > Physik (Goedecker)
UniBasel Contributors:Goedecker, Stefan
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:AIP Publishing
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:21 May 2021 01:30
Deposited On:22 Dec 2020 14:34

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