Polymer simulation by means of tree data-structures and a parsimonious Metropolis algorithm

Abstract

We show how a Monte Carlo method for generating self-avoiding walks on lattice geometries which employs a binary-tree data structure can be adapted for hard-sphere polymers with continuous degrees of freedom. Data suggests that the time per Monte Carlo move scales logarithmically with polymer size. We combine the method with a variant of the Metropolis algorithm and preserve this scaling for Lennard-Jones polymers with untruncated monomer-monomer interaction. We further show how the replica-exchange method can be adapted for the same purpose.

10 pages, 10 figures

References in corpus (4)

• Accurate estimate of the critical exponent $\nu$ for self-avoiding walks via a fast implementation of the pivot algorithm
• Freezing and Collapse of Flexible Polymers on Regular Lattices in Three Dimensions
• High-precision estimate of the hydrodynamic radius for self-avoiding walks
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Cited by in corpus (4)

• Fast, hierarchical, and adaptive algorithm for Metropolis Monte Carlo simulations of long-range interacting systems
• Monte Carlo Simulation of Long Hard-Sphere Polymer Chains in Two to Five Dimensions
• Off-lattice and parallel implementations of the pivot algorithm
• Random knotting in very long off-lattice self-avoiding polygons