Microcanonical approach to the simulation of first-order phase transitions

A simple microcanonical strategy for the simulation of first-order phase transitions is proposed. 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 two dimensions and Q=4 in D=3). We develop a cluster algorithm for this model, obtaining accurate results for systems with more than 10(6) spins.