A Cluster Algorithm for the $Z_2$ Kalb-Ramond Model

TL;DR

This paper introduces a cluster algorithm for the $Z_2$ Kalb-Ramond model in four dimensions that significantly improves simulation efficiency by reducing critical slowing down and accurately capturing the phase transition behavior.

Contribution

A novel cluster algorithm tailored for the $Z_2$ Kalb-Ramond model that reduces critical slowing down and effectively updates monopole configurations.

Findings

Critical exponent z reduced from >2 to 0.32±0.06

Algorithm dramatically decreases critical slowing down

Effectively updates monopole configurations responsible for phase transition

Abstract

A cluster algorithm is presented for the $Z_2$ Kalb-Ramond plaquette model in four dimensions which dramatically reduces critical slowing. The critical exponent $z$ is reduced from $ z>2$ (standard Metropolis algorithm) to $z= 0.32\pm0.06$. The Cluster algorithm updates the monopole configuration known to be responsible for the second order phase transition.