Optimal percolation in correlated multilayer networks with overlap.

We show that the size of the optimal percolation set of a multilayer network is substantially affected by the presence of interlayer degree correlations and edge overlap. We provide extensive numerical evidence to confirm that the state-of-the-art optimal percolation strategies normally fail to identify minimal percolation sets in synthetic and real-world correlated multilayer networks, thus underestimating their fragility. We propose a family of Pareto-efficient strategies for optimal multilayer percolation, that take into account both intralayer and interlayer heuristics, and can be easily extended to multiplex networks with an arbitrary number of layers. We show that these strategies consistently outperform existing attacking algorithms, providing interesting insights about the interplay of correlations and overlap in determining the hyperfragility of real-world multilayer networks.