English

A light weight regularization for wave function parameter gradients in quantum Monte Carlo

Computational Physics 2020-02-25 v2 Materials Science Chemical Physics

Abstract

The parameter derivative of the expectation value of the energy, E/p\partial E/\partial p, is a key ingredient in variational quantum Monte Carlo (VMC) wave function optimization methods. In some cases, a na\"ive Monte Carlo estimate of this derivative suffers from an infinite variance which inhibits the efficiency of optimization methods that rely on a stable estimate of the derivative. In this work, we derive a simple regularization of the na\"ive estimator which is trivial to implement in existing VMC codes, has finite variance, and a negligible bias which can be extrapolated to zero bias with no extra cost. We use this estimator to construct an unbiased, finite variance estimation of E/p\partial E/\partial p for a multi-Slater-Jastrow trial wave function on the LiH molecule. This regularized estimator is a simple and efficient estimator of E/p\partial E/\partial p for VMC optimization techniques.

Keywords

Cite

@article{arxiv.2002.01434,
  title  = {A light weight regularization for wave function parameter gradients in quantum Monte Carlo},
  author = {Shivesh Pathak and Lucas K. Wagner},
  journal= {arXiv preprint arXiv:2002.01434},
  year   = {2020}
}
R2 v1 2026-06-23T13:31:06.491Z