Rugged Metropolis Sampling with Simultaneous Updating of Two Dynamical Variables
Abstract
The Rugged Metropolis (RM) algorithm is a biased updating scheme, which aims at directly hitting the most likely configurations in a rugged free energy landscape. Details of the one-variable (RM) implementation of this algorithm are presented. This is followed by an extension to simultaneous updating of two dynamical variables (RM). In a test with Met-Enkephalin in vacuum RM improves conventional Metropolis simulations by a factor of about four. Correlations between three or more dihedral angles appear to prevent larger improvements at low temperatures. We also investigate a multi-hit Metropolis scheme, which spends more CPU time on variables with large autocorrelation times.
Cite
@article{arxiv.cond-mat/0502113,
title = {Rugged Metropolis Sampling with Simultaneous Updating of Two Dynamical Variables},
author = {Bernd A. Berg and Huan-Xiang Zhou},
journal= {arXiv preprint arXiv:cond-mat/0502113},
year = {2009}
}
Comments
8 pages, 5 figures. Revisions after referee reports. Additional simulations for temperatures down to 220K