Skip to main content
Unpublished Paper
Population annealing with weighted averages: A Monte Carlo method for rough free-energy landscapes
Physical Review E (2010)
  • Jonathan Machta, University of Massachusetts Amherst
Abstract
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.
Disciplines
Publication Date
2010
Comments
Prepublished version downloaded from ArXiv. Published version is located at http://journals.aps.org/pre/abstract/10.1103/PhysRevE.82.026704
Citation Information
Jonathan Machta. "Population annealing with weighted averages: A Monte Carlo method for rough free-energy landscapes" Physical Review E (2010)
Available at: http://works.bepress.com/joonathan_machta/35/