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Flexibilities of wavelets as a computational basis set for large-scale electronic structure calculations
JournalArticle (Originalarbeit in einer wissenschaftlichen Zeitschrift)
 
ID 4606962
Author(s) Ratcliff, Laura E.; Dawson, William; Fisicaro, Giuseppe; Caliste, Damien; Mohr, Stephan; Degomme, Augustin; Videau, Brice; Cristiglio, Viviana; Stella, Martina; D'Alessandro, Marco; Goedecker, Stefan; Nakajima, Takahito; Deutsch, Thierry; Genovese, Luigi
Author(s) at UniBasel Goedecker, Stefan
Year 2020
Title Flexibilities of wavelets as a computational basis set for large-scale electronic structure calculations
Journal Journal of Chemical Physics
Volume 152
Number 19
Pages / Article-Number 194110
Abstract 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.
Publisher AIP Publishing
ISSN/ISBN 0021-9606 ; 1089-7690
edoc-URL https://edoc.unibas.ch/79492/
Full Text on edoc Restricted
Digital Object Identifier DOI 10.1063/5.0004792
PubMed ID http://www.ncbi.nlm.nih.gov/pubmed/33687268
ISI-Number 000536701800005
Document type (ISI) Journal Article
 
   

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02/05/2024