Nonequilibrium candidate Monte Carlo is an efficient tool for equilibrium simulation

• Published in: Proceedings of the National Academy of Sciences - PNAS 2011-11, Vol.108 (45), p.E1009-E1018
• Main Authors: Nilmeier, Jerome P, Crooks, Gavin E, Minh, David D. L, Chodera, John D
• Format: Article
• Language: English
• Subjects: Biological Sciences; Correlation analysis; energy; expanded ensembles; Markov chain Monte Carlo; MATHEMATICS AND COMPUTING; Metropolis-Hastings; Models, Theoretical; molecular dynamics; Monte Carlo Method; Monte Carlo simulation; Physical Sciences; PNAS Plus; probability; Probability distribution; Thermodynamics
• ISSN: 0027-8424; 1091-6490
• DOI: 10.1073/pnas.1106094108

Metropolis Monte Carlo simulation is a powerful tool for studying the equilibrium properties of matter. In complex condensed-phase systems, however, it is difficult to design Monte Carlo moves with high acceptance probabilities that also rapidly sample uncorrelated configurations. Here, we introduce a new class of moves based on nonequilibrium dynamics: Candidate configurations are generated through a finite-time process in which a system is actively driven out of equilibrium, and accepted with criteria that preserve the equilibrium distribution. The acceptance rule is similar to the Metropolis acceptance probability, but related to the nonequilibrium work rather than the instantaneous energy difference. Our method is applicable to sampling from both a single thermodynamic state or a mixture of thermodynamic states, and allows both coordinates and thermodynamic parameters to be driven in nonequilibrium proposals. Whereas generating finite-time switching trajectories incurs an additional cost, driving some degrees of freedom while allowing others to evolve naturally can lead to large enhancements in acceptance probabilities, greatly reducing structural correlation times. Using nonequilibrium driven processes vastly expands the repertoire of useful Monte Carlo proposals in simulations of dense solvated systems.