Hybrid Monte Carlo simulation of polymer chains

TL;DR

This paper introduces a hybrid Monte Carlo method for simulating off-lattice polymer chains, analyzing its efficiency and scaling behavior across different polymer models with varying chain lengths.

Contribution

The paper presents a novel hybrid Monte Carlo algorithm tailored for off-lattice polymer chains, including detailed implementation and performance analysis.

Findings

Computational cost scales as N^{2+z'} with 0.64<z'<0.84.

End-to-end distance scales as N^ν (ln N)^-α.

Algorithm performs efficiently without excessive fine tuning.

Abstract

We develop the hybrid Monte Carlo method for simulations of single off-lattice polymer chains. We discuss implementation and choice of simulation parameters in some detail. The performance of the algorithm is tested on models for homopolymers with short- or long-range self-repulsion, using chains with $16\le N\le 512$ monomers. Without excessive fine tuning, we find that the computational cost grows as $N^{2+z^\prime}$ with $0.64<z^\prime<0.84$. In addition, we report results for the scaling of the end-to-end distance, $r_{1N}\sim N^\nu(\ln N)^{-\alpha}$.