  The population annealing algorithm introduced by Hukushima and Iba is
described. Population annealing combines simulated annealing and Boltzmann
weighted differential reproduction within a population of replicas to sample
equilibrium states. Population annealing gives direct access to the free
energy. It is shown that unbiased measurements of observables can be obtained
by weighted averages over many runs with weight factors related to the free
energy estimate from the run. Population annealing is well suited to
parallelization and may be a useful alternative to parallel tempering for
systems with rough free energy landscapes such as spin glasses. The method is
demonstrated for spin glasses.

Statistical Mechanics;Disordered Systems and Neural Networks