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The population annealing algorithm introduced by Hukushima and Iba isdescribed. Population annealing combines simulated annealing and Boltzmannweighted differential reproduction within a population of replicas to sampleequilibrium states. Population annealing gives direct access to the freeenergy. It is shown that unbiased measurements of observables can be obtainedby weighted averages over many runs with weight factors related to the freeenergy estimate from the run. Population annealing is well suited toparallelization and may be a useful alternative to parallel tempering forsystems with rough free energy landscapes such as spin glasses. The method isdemonstrated for spin glasses.

Population Annealing with Weighted Averages: A Monte Carlo Method for Rough Free Energy Landscapes