npj Computational Materials (May 2023)

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

  • Miki Bonacci,
  • Junfeng Qiao,
  • Nicola Spallanzani,
  • Antimo Marrazzo,
  • Giovanni Pizzi,
  • Elisa Molinari,
  • Daniele Varsano,
  • Andrea Ferretti,
  • Deborah Prezzi

DOI
https://doi.org/10.1038/s41524-023-01027-2
Journal volume & issue
Vol. 9, no. 1
pp. 1 – 10

Abstract

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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.