Self-healing diffusion quantum Monte Carlo algorithms: methods for direct reduction of the fermion sign error in electronic structure calculations
Fernando A. Reboredo, Randolph Q. Hood, Paul R. C. Kent

TL;DR
This paper introduces a novel algorithm for optimizing trial wave-functions in diffusion quantum Monte Carlo, significantly reducing fermion sign errors and improving accuracy in electronic structure calculations.
Contribution
The authors develop a formalism and algorithm that enhance trial wave-function optimization in DMC, leveraging the walker distribution to systematically improve nodal structures.
Findings
Systematic improvement of trial wave-functions in DMC.
Convergence of wave-function overlap to 100%.
Identification of an optimal non-interacting nodal potential.
Abstract
We develop a formalism and present an algorithm for optimization of the trial wave-function used in fixed-node diffusion quantum Monte Carlo (DMC) methods. We take advantage of a basic property of the walker configuration distribution generated in a DMC calculation, to (i) project-out a multi-determinant expansion of the fixed-node ground-state wave function and (ii) to define a cost function that relates the fixed-node ground-state and the non-interacting trial wave functions. We show that (a) locally smoothing out the kink of the fixed-node ground-state wave function at the node generates a new trial wave-function with better nodal structure and (b) we argue that the noise in the fixed-node wave-function resulting from finite sampling plays a beneficial role, allowing the nodes to adjust towards the ones of the exact many-body ground state in a simulated annealing-like process. We…
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