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## Understanding population annealing Monte Carlo simulations

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.