Off-lattice and parallel implementations of the pivot algorithm

Abstract

The pivot algorithm is the most efficient known method for sampling polymer configurations for self-avoiding walks and related models. Here we introduce two recent improvements to an efficient binary tree implementation of the pivot algorithm: an extension to an off-lattice model, and a parallel implementation.

7 pages, 2 figures. Presented at "Recent Developments in Computer Simulation Studies in Condensed Matter Physics" (32nd Annual CSP Workshop) in February 2019, and submitted for the workshop proceedings

References in corpus (3)

• Accurate estimate of the critical exponent $\nu$ for self-avoiding walks via a fast implementation of the pivot algorithm
• Polymer simulation by means of tree data-structures and a parsimonious Metropolis algorithm
• Monte Carlo study of four-dimensional self-avoiding walks of up to one billion steps

Cited by in corpus (1)

• Random knotting in very long off-lattice self-avoiding polygons