Population annealing: Theory and application in spin glasses

TL;DR

This paper presents the theory of population annealing, a Monte Carlo method for simulating complex systems like spin glasses, compares it with parallel tempering, and discusses its errors and efficiency.

Contribution

The paper develops the theoretical framework of population annealing and compares its performance to parallel tempering in large-scale spin glass simulations.

Findings

Population annealing effectively simulates spin glasses.

It has similar efficiency to parallel tempering.

The paper discusses systematic and statistical errors.

Abstract

Population annealing is an efficient sequential Monte Carlo algorithm for simulating equilibrium states of systems with rough free energy landscapes. The theory of population annealing is presented, and systematic and statistical errors are discussed. The behavior of the algorithm is studied in the context of large-scale simulations of the three-dimensional Ising spin glass and the performance of the algorithm is compared to parallel tempering. It is found that the two algorithms are similar in efficiency though with different strengths and weaknesses.