  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.
