Swift GW beyond 10,000 electrons using sparse stochastic compression

Vojtěch Vlček, Wenfei Li, Roi Baer, Eran Rabani, and Daniel Neuhauser
Phys. Rev. B 98, 075107 – Published 6 August 2018

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.

  • Figure
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  • Received 26 May 2018
  • Revised 18 July 2018

DOI:https://doi.org/10.1103/PhysRevB.98.075107

©2018 American Physical Society

Physics Subject Headings (PhySH)

Condensed Matter, Materials & Applied PhysicsAtomic, Molecular & Optical

Authors & Affiliations

Vojtěch Vlček1,*, Wenfei Li1,†, Roi Baer2,‡, Eran Rabani3,4,§, and Daniel Neuhauser1,∥

  • 1Department of Chemistry and Biochemistry, University of California, Los Angeles, California 90095, USA
  • 2Fritz Haber Center for Molecular Dynamics, Institute of Chemistry, The Hebrew University of Jerusalem, Jerusalem 91904, Israel
  • 3Department of Chemistry, University of California and Materials Science Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
  • 4The Raymond and Beverly Sackler Center for Computational Molecular and Materials Science, Tel Aviv University, Tel Aviv 69978, Israel

  • *Present address: Department of Chemistry and Biochemistry, University of California, Santa Barbara, CA 93106, USA; vlcek@ucsb.edu
  • liwenfei@chem.ucla.edu
  • roi.baer@huji.ac.il
  • §eran.rabani@berkeley.edu
  • dxn@ucla.edu

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Issue

Vol. 98, Iss. 7 — 15 August 2018

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