Population annealing is a recent addition to the arsenal of the practitioner in computer simulations in statistical physics and it proves to deal well with systems with complex free-energy landscapes. Above all else, it promises to deliver unrivaled parallel scaling qualities, being suitable for parallel machines of the biggest caliber. Here we study population annealing using as the main example the two-dimensional Ising model, which allows for particularly clean comparisons due to the available exact results and the wealth of published simulational studies employing other approaches. We analyze in depth the accuracy and precision of the method, highlighting its relation to older techniques such as simulated annealing and thermodynamic integration. We introduce intrinsic approaches for the analysis of statistical and systematic errors and provide a detailed picture of the dependence of such errors on the simulation parameters. The results are benchmarked against canonical and parallel tempering simulations.

中文翻译：

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了解总体退火蒙特卡洛模拟

人口退火是统计物理计算机模拟中从业人员的最新手腕，它被证明可以很好地处理具有复杂自由能态势的系统。最重要的是，它承诺提供无与伦比的并行缩放质量，适用于最大口径的并行计算机。在这里，我们使用二维Ising模型作为主要示例来研究种群退火，由于可用的精确结果以及使用其他方法发表的大量模拟研究，该模型可以进行特别干净的比较。我们深入分析了该方法的准确性和精确性，重点介绍了该方法与较旧技术（如模拟退火和热力学积分）的关系。我们介绍了用于统计和系统误差分析的内在方法，并提供了此类误差对仿真参数的依赖性的详细描述。该结果以规范和平行回火模拟为基准。