Weak percolation on multiplex networks with overlapping edges. (November 2022)

• Record Type: Journal Article
• Authors: Baxter, G.J.; da Costa, R.A.; Dorogovtsev, S.N.; Mendes, J.F.F.
• Is Part Of: Chaos, solitons and fractals. Volume 164(2022)
• Publication Date: 2022-11
• Subjects: Complex networks -- Critical phenomena -- Multilayer networks -- Interdependent networks; Chaotic behavior in systems -- Periodicals; Solitons -- Periodicals; Fractals -- Periodicals; Chaotic behavior in systems; Fractals; Solitons; Periodicals; 003.7
• DOI: 10.1016/j.chaos.2022.112619
• Languages: English
• ISSNs: 0960-0779

Abstract

Abstract: We solve the weak percolation problem for multiplex networks with overlapping edges. In weak percolation, a vertex belongs to a connected component if at least one of its neighbors in each of the layers is in this component. This is a weaker condition than for a mutually connected component in interdependent networks, in which any two vertices must be connected by a path within each of the layers. The effect of the overlaps on weak percolation turns out to be opposite to that on the giant mutually connected component. While for the giant mutually connected component, overlaps do not change the critical phenomena, our theory shows that in two layers any (nonzero) concentration of overlaps drives the weak percolation transition to the ordinary percolation universality class. In three layers, the phase diagram of the problem contains two lines – of a continuous phase transition and of a discontinuous one – connected in various ways depending on how the layers overlap. In the case of only doubled overlapped edges, two of the end points of these lines coincide, resulting in a tricritical point like that seen in heterogeneous k -core percolation. Highlights: We consider overlapping edges in weak multiplex percolation, on multi-layer networks. We solve the percolation problem in two- and three- layer networks with overlaps. We find that the critical phenomena are changed by the presence of overlaps. We identify a tricritical point in three-layer networks with double overlaps.