Abstract
We develop a new ensemble of modular random graphs in which degree-degree
correlations can be different in each module. We present an analytical approach
that allows one to analyze several types of binary dynamics operating on such
networks, and we illustrate our approach using bond percolation, site
percolation, and the Watts threshold model. The new network ensemble
generalizes existing models by allowing a heterogeneous distribution of
degree-degree correlations across modules, which is important for the
consideration of nonidentical interacting networks.
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