Global scheme of sweeping cluster algorithm to sample among topological sectors

TL;DR

This paper introduces a global sweeping cluster Monte Carlo algorithm for efficiently sampling different topological sectors in constrained models like the quantum dimer model, overcoming local restriction limitations.

Contribution

The authors develop a novel global sweeping cluster Monte Carlo method that enables sampling across topological sectors in constrained models, which was previously challenging.

Findings

Successfully samples among topological sectors in quantum dimer models

Provides a generalizable approach for other constrained models

Improves computational efficiency in topological sector sampling

Abstract

Local constraint is closely related to the gauge field, so constrained models are usually effective low energy descriptions and important in condensed matter physics. On the other hand, local restriction hinders the application of numerical algorithms. In addition to the computational difficulties of the constraints, the various topological sectors which cannot be connected through local operators are also one of the key computational difficulties. Taking quantum dimer model as an example in this paper, we construct a global scheme based on sweeping cluster Monte Carlo method, which can sample among different topological sectors. In principle, this method can be generalized to other models.