Exploring firstorder phase transitions with population annealing
Abstract
Population annealing is a hybrid of sequential and Markov chain Monte Carlo methods geared towards the efficient parallel simulation of systems with complex freeenergy landscapes. Systems with firstorder phase transitions are among the problems in computational physics that are difficult to tackle with standard methods such as localupdate simulations in the canonical ensemble, for example with the Metropolis algorithm. It is hence interesting to see whether such transitions can be more easily studied using population annealing. We report here our preliminary observations from population annealing runs for the twodimensional Potts model with q > 4, where it undergoes a firstorder transition.
 Publication:

European Physical Journal Special Topics
 Pub Date:
 April 2017
 DOI:
 10.1140/epjst/e2016603894
 arXiv:
 arXiv:1704.01888
 Bibcode:
 2017EPJST.226..595B
 Keywords:

 Physics  Computational Physics;
 Condensed Matter  Soft Condensed Matter;
 Condensed Matter  Statistical Mechanics;
 High Energy Physics  Lattice
 EPrint:
 10 pages, 3 figures, 3 tables