Equilibriumlike extension of the invaded cluster algorithm

TL;DR

This paper introduces an improved invaded cluster algorithm that accurately captures critical fluctuations and self-adjusts to the critical temperature, enhancing equilibrium sampling in Potts models.

Contribution

The authors extend the nonequilibrium invaded cluster algorithm by adding a constraint, enabling correct fluctuation scaling and self-tuning to critical temperature.

Findings

Correct scaling of fluctuations at criticality

Self-adjustment to critical temperature achieved

Effective application to 2D and 3D Potts models

Abstract

We propose an extension of the nonequilibrium invaded cluster (IC) algorithm, which reestablishes a correct scaling of fluctuations at criticality and also self-adjusts to the critical temperature. We show that by introducing a single constraint to the intrinsic quantity of the IC algorithm the temperature becomes well defined and the sampling of the equilibrium ensemble is regained. The procedure is applied to the Potts model in two and three dimensions.