Scaling behavior of self-avoiding walks on percolation clusters
classification
❄️ cond-mat.dis-nn
cond-mat.soft
keywords
scalingbehaviorclusterspercolationself-avoidingwalksapplyaverages
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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.
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