Resampling schemes in population annealing -- numerical results
Statistical Mechanics
2022-04-04 v1 Disordered Systems and Neural Networks
Computational Physics
Abstract
Population annealing (PA) is a population-based algorithm that is designed for equilibrium simulations of thermodynamic systems with a rough free energy landscape. It is known to be more efficient in doing so than standard Markov chain Monte Carlo alone. The algorithm has a number of parameters that can be fine-tuned to improve performance. While there is some theoretical and numerical work regarding most of these parameters, there appears to be a gap in the literature concerning the role of resampling in PA. Here, we present a numerical comparison of a number of resampling schemes for PA simulations of the 2D Ising model.
Keywords
Cite
@article{arxiv.2203.16589,
title = {Resampling schemes in population annealing -- numerical results},
author = {Denis Gessert and Martin Weigel and Wolfhard Janke},
journal= {arXiv preprint arXiv:2203.16589},
year = {2022}
}
Comments
6 pages, 4 figures