Spectral coarse-graining of complex networks
Disordered Systems and Neural Networks
2009-11-13 v1
Abstract
Reducing the complexity of large systems described as complex networks is key to understand them and a crucial issue is to know which properties of the initial system are preserved in the reduced one. Here we use random walks to design a coarse-graining scheme for complex networks. By construction the coarse-graining preserves the slow modes of the walk, while reducing significantly the size and the complexity of the network. In this sense our coarse-graining allows to approximate large networks by smaller ones, keeping most of their relevant spectral properties.
Cite
@article{arxiv.0706.0812,
title = {Spectral coarse-graining of complex networks},
author = {David Gfeller and Paolo De los Rios},
journal= {arXiv preprint arXiv:0706.0812},
year = {2009}
}