Improving the efficiency of Monte Carlo simulations of systems that undergo temperature-driven phase transitions

Abstract

Recently, Velazquez and Curilef have proposed a methodology to extend Monte Carlo algorithms based on canonical ensemble, which is aimed to overcome slow sampling problems associated with temperature-driven discontinuous phase transitions. We show in this work that Monte Carlo algorithms extended with this methodology also exhibit a remarkable efficiency near a critical point. Our study is performed for the particular case of 2D four-state Potts model on the square lattice with periodic boundary conditions. This analysis reveals that the extended version of Metropolis importance sample is more efficient than the usual Swendsen-Wang and Wolff cluster algorithms. These results demonstrate the effectiveness of this methodology to improve the efficiency of MC simulations of systems that undergo any type of temperature-driven phase transition.

Version accepted for publicacion in Physical Review E

References in corpus (8)

• Violation of the Zeroth Law of Thermodynamics in Systems with Negative Specific Heat
• Thermodynamic fluctuation relation for temperature and energy
• A New Monte Carlo Method and Its Implications for Generalized Cluster Algorithms
• Equilibrium fluctuation theorems compatible with anomalous response
• Geometrical aspects and connections of the energy-temperature fluctuation relation
• Extending canonical Monte Carlo methods
• Extending canonical Monte Carlo methods II
• Understanding critical behavior in the framework of the extended equilibrium fluctuation theorem

Cited by in corpus (2)

• Remarks about the thermodynamics of astrophysical systems in mutual interaction and related notions
• Extended canonical Monte Carlo methods: Improving accuracy of microcanonical calculations using a re-weighting technique