Evolution of correlated multiplexity through stability maximization.

Abstract

Investigating the relation between various structural patterns found in real-world networks and the stability of underlying systems is crucial to understand the importance and evolutionary origin of such patterns. We evolve multiplex networks, comprising antisymmetric couplings in one layer depicting predator-prey relationship and symmetric couplings in the other depicting mutualistic (or competitive) relationship, based on stability maximization through the largest eigenvalue of the corresponding adjacency matrices. We find that there is an emergence of the correlated multiplexity between the mirror nodes as the evolution progresses. Importantly, evolved values of the correlated multiplexity exhibit a dependence on the interlayer coupling strength. Additionally, the interlayer coupling strength governs the evolution of the disassortativity property in the individual layers. We provide analytical understanding to these findings by considering starlike networks representing both the layers. The framework discussed here is useful for understanding principles governing the stability as well as the importance of various patterns in the underlying networks of real-world systems ranging from the brain to ecology which consist of multiple types of interaction behavior.