Monte Carlo Simulation of Dense Polymer Melts Using Event Chain Algorithms

TL;DR

This paper introduces an efficient event chain Monte Carlo algorithm for simulating dense polymer melts, achieving high speed and accurate equilibrium behavior, with dynamics comparable to molecular dynamics methods.

Contribution

The paper presents a novel off-lattice Monte Carlo algorithm using event chains and parallelization for dense polymer melts, improving speed and equilibration over existing methods.

Findings

Reproduces correct equilibrium polymer behavior.

Achieves simulation speeds comparable to molecular dynamics.

Displays Rouse and reptation dynamics depending on conditions.

Abstract

We propose an efficient Monte Carlo algorithm for the off-lattice simulation of dense hard sphere polymer melts using cluster moves, called event chains, which allow for a rejection-free treatment of the excluded volume. Event chains also allow for an efficient preparation of initial configurations in polymer melts. We parallelize the event chain Monte Carlo algorithm to further increase simulation speeds and suggest additional local topology-changing moves ("swap" moves) to accelerate equilibration. By comparison with other Monte Carlo and molecular dynamics simulations, we verify that the event chain algorithm reproduces the correct equilibrium behavior of polymer chains in the melt. By comparing intrapolymer diffusion time scales, we show that event chain Monte Carlo algorithms can achieve simulation speeds comparable to optimized molecular dynamics simulations. The event chain Monte Carlo algorithm exhibits Rouse dynamics on short time scales. In the absence of swap moves, we find reptation dynamics on intermediate time scales for long chains.