Minimising biases in full configuration interaction quantum Monte Carlo

The Journal of Chemical Physics
W A VigorA J W Thom

Abstract

We show that Full Configuration Interaction Quantum Monte Carlo (FCIQMC) is a Markov chain in its present form. We construct the Markov matrix of FCIQMC for a two determinant system and hence compute the stationary distribution. These solutions are used to quantify the dependence of the population dynamics on the parameters defining the Markov chain. Despite the simplicity of a system with only two determinants, it still reveals a population control bias inherent to the FCIQMC algorithm. We investigate the effect of simulation parameters on the population control bias for the neon atom and suggest simulation setups to, in general, minimise the bias. We show a reweight ing scheme to remove the bias caused by population control commonly used in diffusion Monte Carlo [Umrigar et al., J. Chem. Phys. 99, 2865 (1993)] is effective and recommend its use as a post processing step.

References

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Jan 15, 2011·Physical Review Letters·Alex J W Thom
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Feb 11, 2012·The Journal of Chemical Physics·J S SpencerW M C Foulkes
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Nov 13, 2012·Journal of Chemical Theory and Computation·Csaba DadayClaudia Filippi

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Citations

Mar 10, 2016·The Journal of Chemical Physics·W A VigorA J W Thom
Oct 10, 2015·The Journal of Chemical Physics·N S BluntAli Alavi
Nov 23, 2017·The Journal of Chemical Physics·Verena A Neufeld, Alex J W Thom
Dec 7, 2018·The Journal of Chemical Physics·J S SpencerA J W Thom
Nov 11, 2020·The Journal of Chemical Physics·Mingrui YangJoachim Brand
Jan 27, 2019·Journal of Chemical Theory and Computation·James S SpencerAlex J W Thom
May 6, 2019·Journal of Chemical Theory and Computation·Nick S BluntCharles J C Scott
Oct 26, 2018·Journal of Chemical Theory and Computation·Verena A Neufeld, Alex J W Thom
Jul 23, 2020·Journal of Chemical Theory and Computation·Samuel M GreeneTimothy C Berkelbach
Aug 8, 2019·Journal of Chemical Theory and Computation·Samuel M GreeneTimothy C Berkelbach

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