Optimal percolation on multiplex networks

TL;DR

This paper investigates the optimal percolation problem on multiplex networks, revealing how multilayer features like edge overlap and degree correlation significantly influence the identification of critical nodes for network fragmentation.

Contribution

It introduces the analysis of optimal percolation specifically on multiplex networks, highlighting the impact of multilayer characteristics on the problem's solutions.

Findings

Multiplex features alter the set of critical nodes for network fragmentation.

Edge overlap and interlayer degree correlation significantly affect optimal percolation.

The multilayer structure changes the properties of the minimal node set needed for network disintegration.

Abstract

Optimal percolation is the problem of finding the minimal set of nodes such that if the members of this set are removed from a network, the network is fragmented into non-extensive disconnected clusters. The solution of the optimal percolation problem has direct applicability in strategies of immunization in disease spreading processes, and influence maximization for certain classes of opinion dynamical models. In this paper, we consider the problem of optimal percolation on multiplex networks. The multiplex scenario serves to realistically model various technological, biological, and social networks. We find that the multilayer nature of these systems, and more precisely multiplex characteristics such as edge overlap and interlayer degree-degree correlation, profoundly changes the properties of the set of nodes identified as the solution of the optimal percolation problem.