Benchmarking the accuracy of superconducting pair-pair correlations within Constrained Path Quantum Monte Carlo

TL;DR

This paper evaluates the accuracy of different quantum Monte Carlo methods in measuring superconducting correlations in the Hubbard model, highlighting the strengths and limitations of back propagation and constraint release techniques.

Contribution

It critically compares back propagation and constraint release methods within Constrained Path Quantum Monte Carlo for measuring pair correlations, revealing their respective biases and computational costs.

Findings

Back propagation tends to underestimate superconducting correlations.

Constraint release provides more accurate results but is computationally expensive.

Reintroduces the sign problem, limiting practical use.

Abstract

Ground state properties of the Hubbard model are of fundamental importance to understand the mechanism of unconventional superconductivity in the high-T_c cuprates and other materials. One of the most powerful numerical methods for strongly interacting models is quantum Monte Carlo, which however faces a fundamental limitation, the Fermion sign problem. The sign problem can be mitigated using approximate methods such as Constrained Path Monte Carlo, but additional approximations must be made in order to measure different observables, particularly for operators that do not commute with the Hamiltonian. We examine critically the most commonly used approximation, back propagation, as well as a recently proposed constraint release measurement technique. In comparisons with a variety of systems that can be solved numerically exactly by other methods, we find that back propagation tends to underestimate superconducting pair-pair correlations. The constraint release technique can provide accurate results, with the disadvantages that it much more computationally expensive and reintroduces the sign problem.