Dynamic critical behavior of cluster algorithms for 2D Ashkin-Teller and Potts models

TL;DR

This paper investigates the dynamic critical behavior of cluster algorithms for 2D Potts and Ashkin-Teller models, revealing near-sharp bounds and relationships between autocorrelation times.

Contribution

It provides new insights into the autocorrelation times and bounds for cluster algorithms applied to 2D Potts and Ashkin-Teller models, including near-sharp bounds and proportionality results.

Findings

Li--Sokal bound is nearly sharp but not exact

Autocorrelation time ratio tends to infinity logarithmically or as a small power

Exponential autocorrelation time is proportional to integrated autocorrelation time

Abstract

We study the dynamic critical behavior of two algorithms: the Swendsen-Wang algorithm for the two-dimensional Potts model with q=2,3,4 and a Swendsen-Wang-type algorithm for the two-dimensional symmetric Ashkin-Teller model on the self-dual curve. We find that the Li--Sokal bound on the autocorrelation time \tau_{{\rm int},{\cal E}} \geq const \times C_H is almost, but not quite sharp. The ratio \tau_{{\rm int},{\cal E}}/C_H appears to tend to infinity either as a logarithm or as a small power (0.05 \ltapprox p \ltapprox 0.12). We also show that the exponential autocorrelation time \tau_{{\rm exp},{\cal E}} is proportional to the integrated autocorrelation time \tau_{{\rm int},{\cal E}}.