Swift GW beyond 10,000 electrons using sparse stochastic compression

Vojtěch Vlček, Wenfei Li, Roi Baer, Eran Rabani, Daniel Neuhauser

Research output: Contribution to journalArticlepeer-review

43 Scopus citations

Abstract

We introduce the concept of sparse stochastic compression, an efficient stochastic sampling of any general function. The technique uses sparse stochastic orbitals (SSOs), short vectors that sample a small number of space points. As a first demonstration, SSOs are applied in conjunction with simple direct projection to accelerate our recent stochastic GW technique; the new developments enable accurate prediction of G0W0 quasiparticle energies and gaps for systems with up to Ne>10,000 electrons, with small statistical errors of ±0.05eV and using less than 2000 core CPU hours. Overall, stochastic GW scales now linearly (and often sublinearly) with Ne.

Original languageAmerican English
Article number075107
JournalPhysical Review B
Volume98
Issue number7
DOIs
StatePublished - 6 Aug 2018

Bibliographical note

Publisher Copyright:
© 2018 American Physical Society.

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