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Towards high-throughput many-body perturbation theory: efficient algorithms and automated workflows

Authors :
Miki Bonacci
Junfeng Qiao
Nicola Spallanzani
Antimo Marrazzo
Giovanni Pizzi
Elisa Molinari
Daniele Varsano
Andrea Ferretti
Deborah Prezzi
Source :
npj Computational Materials, Vol 9, Iss 1, Pp 1-10 (2023)
Publication Year :
2023
Publisher :
Nature Portfolio, 2023.

Abstract

Abstract The automation of ab initio simulations is essential in view of performing high-throughput (HT) computational screenings oriented to the discovery of novel materials with desired physical properties. In this work, we propose algorithms and implementations that are relevant to extend this approach beyond density functional theory (DFT), in order to automate many-body perturbation theory (MBPT) calculations. Notably, an algorithm pursuing the goal of an efficient and robust convergence procedure for GW and BSE simulations is provided, together with its implementation in a fully automated framework. This is accompanied by an automatic GW band interpolation scheme based on maximally localized Wannier functions, aiming at a reduction of the computational burden of quasiparticle band structures while preserving high accuracy. The proposed developments are validated on a set of representative semiconductor and metallic systems.

Details

Language :
English
ISSN :
20573960
Volume :
9
Issue :
1
Database :
Directory of Open Access Journals
Journal :
npj Computational Materials
Publication Type :
Academic Journal
Accession number :
edsdoj.21f5a90eb1604577acd68b0ad26003e4
Document Type :
article
Full Text :
https://doi.org/10.1038/s41524-023-01027-2