Percolation on a maximally disassortative network

Abstract: We propose a maximally disassortative (MD) network model which realizes a maximally negative degree-degree correlation, and study its percolation transition to discuss the effect of a strong degree-degree correlation on the percolation critical behaviors. Using the generating function method for bipartite networks, we analytically derive the percolation threshold and the order parameter critical exponent, $\beta$. For the MD scale-free networks, whose degree distribution is $P(k) \sim k<sup>{-\gamma}$, we show that the exponent, $\beta$, for the MD networks and corresponding uncorrelated networks are same for $\gamma&gt;3$ but are different for $2&lt;\gamma&lt;3$. A strong degree-degree correlation significantly affects the percolation critical behavior in heavy-tailed scale-free networks. Our analytical results for the critical exponents are numerically confirmed by a finite-size scaling argument.