Scaling behavior of self-avoiding walks on percolation clusters
Disordered Systems and Neural Networks
2009-11-13 v2 Soft Condensed Matter
Abstract
The scaling behavior of self-avoiding walks (SAWs) on the backbone of percolation clusters in two, three and four dimensions is studied by Monte Carlo simulations. We apply the pruned-enriched Rosenbluth chain-growth method (PERM). Our numerical results bring about the estimates of critical exponents, governing the scaling laws of disorder averages of the end-to-end distance of SAW configurations. The effects of finite-size scaling are discussed as well.
Keywords
Cite
@article{arxiv.0804.2988,
title = {Scaling behavior of self-avoiding walks on percolation clusters},
author = {Viktoria Blavatska and Wolfhard Janke},
journal= {arXiv preprint arXiv:0804.2988},
year = {2009}
}
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6 pages