Fast and stable determinant quantum Monte Carlo

We assess numerical stabilization methods employed in fermion many-body quantum Monte Carlo simulations. In particular, we empirically compare various matrix decomposition and inversion schemes to gain control over numerical instabilities arising in the computation of equal-time and time-displace...

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Main Author: Carsten Bauer
Format: Article
Language:English
Published: SciPost 2020-06-01
Series:SciPost Physics Core
Online Access:https://scipost.org/SciPostPhysCore.2.2.011
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author Carsten Bauer
author_facet Carsten Bauer
author_sort Carsten Bauer
collection DOAJ
description We assess numerical stabilization methods employed in fermion many-body quantum Monte Carlo simulations. In particular, we empirically compare various matrix decomposition and inversion schemes to gain control over numerical instabilities arising in the computation of equal-time and time-displaced Green's functions within the determinant quantum Monte Carlo (DQMC) framework. Based on this comparison, we identify a procedure based on pivoted QR decompositions which is both efficient and accurate to machine precision. The Julia programming language is used for the assessment and implementations of all discussed algorithms are provided in the open-source software library StableDQMC.jl [http://github.com/crstnbr/StableDQMC.jl].
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spelling doaj.art-dda1b5efb7e1406d975e8220aaa64b3f2022-12-21T23:04:41ZengSciPostSciPost Physics Core2666-93662020-06-012201110.21468/SciPostPhysCore.2.2.011Fast and stable determinant quantum Monte CarloCarsten BauerWe assess numerical stabilization methods employed in fermion many-body quantum Monte Carlo simulations. In particular, we empirically compare various matrix decomposition and inversion schemes to gain control over numerical instabilities arising in the computation of equal-time and time-displaced Green's functions within the determinant quantum Monte Carlo (DQMC) framework. Based on this comparison, we identify a procedure based on pivoted QR decompositions which is both efficient and accurate to machine precision. The Julia programming language is used for the assessment and implementations of all discussed algorithms are provided in the open-source software library StableDQMC.jl [http://github.com/crstnbr/StableDQMC.jl].https://scipost.org/SciPostPhysCore.2.2.011
spellingShingle Carsten Bauer
Fast and stable determinant quantum Monte Carlo
SciPost Physics Core
title Fast and stable determinant quantum Monte Carlo
title_full Fast and stable determinant quantum Monte Carlo
title_fullStr Fast and stable determinant quantum Monte Carlo
title_full_unstemmed Fast and stable determinant quantum Monte Carlo
title_short Fast and stable determinant quantum Monte Carlo
title_sort fast and stable determinant quantum monte carlo
url https://scipost.org/SciPostPhysCore.2.2.011
work_keys_str_mv AT carstenbauer fastandstabledeterminantquantummontecarlo