  An algorithm is proposed for computing equilibrium averages of Markov chains
which suffer from metastability -- the tendency to remain in one or more
subsets of state space for long time intervals. The algorithm, called the
parallel replica method (or ParRep), uses many parallel processors to explore
these subsets more efficiently. Numerical simulations on a simple model
demonstrate consistency of the method. A proof of consistency is given in an
idealized setting. The parallel replica method can be considered a
generalization of A.F. Voter's parallel replica dynamics, originally developed
to efficiently simulate metastable Langevin stochastic dynamics.
