Microcanonical Approach to the Simulation of First-Order Phase Transitions

Abstract

A generalization of the microcanonical ensemble suggests a simple strategy for the simulation of first order phase transitions. At variance with flat-histogram methods, there is no iterative parameters optimization, nor long waits for tunneling between the ordered and the disordered phases. We test the method in the standard benchmark: the Q-states Potts model (Q=10 in 2 dimensions and Q=4 in 3 dimensions), where we develop a cluster algorithm. We obtain accurate results for systems with more than one million of spins, outperforming flat-histogram methods that handle up to tens of thousands of spins.