Percolation transition in correlated hypergraphs

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.

References in corpus (3)

• Evolution of scale-free random graphs: Potts model formulation
• Bicomponents and the robustness of networks to failure
• Percolation transition and distribution of connected components in generalized random network ensembles