Stochastic Self-Consistent Second-Order Green's Function Method for Correlation Energies of Large Electronic Systems

Daniel Neuhauser*, Roi Baer, Dominika Zgid

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

39 Scopus citations


The second-order Matsubara Green's function method (GF2) is a robust temperature-dependent quantum chemistry approach, extending beyond the random-phase approximation. However, until now the scope of GF2 applications was quite limited as they require computer resources that rise steeply with system size. In each step of the self-consistent GF2 calculation there are two parts: estimating of the self-energy from the previous step's Green's function and updating the Green's function from the self-energy. The first part formally scales as the fifth power of the system size, while the second has a much gentler cubic scaling. Here, we develop a stochastic approach to GF2 (sGF2), which reduces the fifth power scaling of the first step to merely quadratic, leaving the overall sGF2 scaling as cubic. We apply the method to linear hydrogen chains with up to 1000 electrons, showing that the approach is numerically stable, efficient, and accurate. The stochastic errors are very small, on the order of 0.1% or less of the correlation energy for large systems, with only a moderate computational effort. The first iteration of GF2 is an MP2 calculation that is done in linear scaling; hence we obtain an extremely fast stochastic MP2 (sMP2) method as a byproduct. While here we consider finite systems with large band gaps where at low temperatures effects are negligible, the sGF2 formalism is temperature dependent and general and can be applied to finite or periodic systems with small gaps at finite temperatures.

Original languageAmerican English
Pages (from-to)5396-5403
Number of pages8
JournalJournal of Chemical Theory and Computation
Issue number11
StatePublished - 14 Nov 2017

Bibliographical note

Publisher Copyright:
© 2017 American Chemical Society.


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