Population annealing with weighted averages: A Monte Carlo method for rough free-energy landscapes
Population annealing with weighted averages: A Monte Carlo method for rough free-energy landscapes
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DOI：
10.1103/physreve.82.026704
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发表时间：
2010-08-18
影响因子：
2.4
通讯作者：
Machta, J.
中科院分区：
文献类型：
--
作者：
Machta, J.
描述了Hukushima和IBA引入的人口退火算法。人口退火结合了模拟的退火和Boltzmann在复制品种群中加权差异繁殖，以样本平衡状态。人口退火可以直接获得自由能。结果表明，在许多运行中，可以通过加权平均值获得无偏的测量值，并具有与运行的自由能估计有关的权重因子。人口退火非常适合并行化，对于具有粗糙的自由能景观（例如自旋玻璃）的系统，可能是平行回火的有用替代方法。该方法用于自旋眼镜。
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.