Partitioning Schemes and Non-Integer Box Sizes for the Box-Counting Algorithm in Multifractal Analysis
Disordered Systems and Neural Networks
2015-03-20 v2
Abstract
We compare different partitioning schemes for the box-counting algorithm in the multifractal analysis by computing the singularity spectrum and the distribution of the box probabilities. As model system we use the Anderson model of localization in two and three dimensions. We show that a partitioning scheme which includes unrestricted values of the box size and an average over all box origins leads to smaller error bounds than the standard method using only integer ratios of the linear system size and the box size which was found by Rodriguez et al. (Eur. Phys. J. B 67, 77-82 (2009)) to yield the most reliable results.
Cite
@article{arxiv.1204.3755,
title = {Partitioning Schemes and Non-Integer Box Sizes for the Box-Counting Algorithm in Multifractal Analysis},
author = {Stefanie Thiem and Michael Schreiber},
journal= {arXiv preprint arXiv:1204.3755},
year = {2015}
}
Comments
10 pages, 13 figures