Polymer Simulations with a flat histogram stochastic growth algorithm
Soft Condensed Matter
2007-05-23 v1 Statistical Mechanics
Abstract
We present Monte Carlo simulations of lattice models of polymers. These simulations are intended to demonstrate the strengths of a powerful new flat histogram algorithm which is obtained by adding microcanonical reweighting techniques to the pruned and enriched Rosenbluth method (PERM).
Cite
@article{arxiv.cond-mat/0402549,
title = {Polymer Simulations with a flat histogram stochastic growth algorithm},
author = {Thomas Prellberg and Jaroslaw Krawczyk and Andrew Rechnitzer},
journal= {arXiv preprint arXiv:cond-mat/0402549},
year = {2007}
}
Comments
17th Annual Workshop: Recent Developments in Computer Simulation Studies in Condensed Matter Physics, University of Georgia, GA (February, 2004)