Percolation transition in correlated hypergraphs
Disordered Systems and Neural Networks
2009-07-20 v2 Statistical Mechanics
Abstract
Correlations are known to play a crucial role in determining the structure of complex networks. Here we study how their presence affects the computation of the percolation threshold in random hypergraphs. In order to mimic the correlation in real network, we build hypergraphs from a generalized hidden variable ensembles and we study the percolation transition by mapping this problem to the fully connected Potts model with heterogeneous couplings.
Cite
@article{arxiv.0905.4455,
title = {Percolation transition in correlated hypergraphs},
author = {Serena Bradde and Ginestra Bianconi},
journal= {arXiv preprint arXiv:0905.4455},
year = {2009}
}