  Population annealing is a recent addition to the arsenal of the practitioner
in computer simulations in statistical physics and beyond that is found 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 calibre. 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.
