A new scheme for fixed node diffusion quantum Monte Carlo with pseudopotentials: improving reproducibility and reducing the trial-wave-function bias. (arXiv:1907.04432v1 [physics.comp-ph])

Fixed node diffusion quantum Monte Carlo (FN-DMC) is an increasingly used
computational approach for investigating the electronic structure of molecules,
solids, and surfaces with controllable accuracy. It stands out among equally
accurate electronic structure approaches for its favorable cubic scaling with
system size, which often makes FN-DMC the only computationally affordable
high-quality method in large condensed phase systems with more than 100 atoms.
In such systems FN-DMC deploys pseudopotentials to substantially improve
efficiency. In order to deal with non-local terms of pseudopotentials, the
FN-DMC algorithm must use an additional approximation, leading to the so-called
localization error. However, the two available approximations, the locality
approximation (LA) and the T-move approximation (TM), have certain
disadvantages and can make DMC calculations difficult to reproduce. Here we
introduce a third approach, called the determinant localization approximation
(DLA). DLA eliminates reproducibility issues and systematically provides good
quality results and stable simulations that are slightly more efficient than LA
and TM. When calculating energy differences -- such as interaction and
ionization energies -- DLA is also more accurate than the LA and TM approaches.
We believe that DLA paves the way to the automization of FN-DMC and its much
easier application in large systems.

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