Collective phenomena emerging from the interactions between dynamical processes in multiplex networks

TL;DR

This paper presents a multilayer network framework to analyze how different dynamical processes interact, demonstrating that such interactions can induce phenomena like explosive synchronization and heterogeneous distributions not seen in isolated systems.

Contribution

The authors develop a novel multilayer network approach to model and analyze the interactions between diverse dynamical processes, revealing emergent collective phenomena.

Findings

Multilayer coupling induces explosive synchronization.

Heterogeneous distribution of transport allocations emerges.

Framework applicable to various interacting dynamical processes.

Abstract

We introduce a framework to intertwine dynamical processes of different nature, each with its own distinct network topology, using a multilayer network approach. As an example of collective phenomena emerging from the interactions of multiple dynamical processes, we study a model where neural dynamics and nutrient transport are bidirectionally coupled in such a way that the allocation of the transport process at one layer depends on the degree of synchronization at the other layer, and vice versa. We show numerically, and we prove analytically, that the multilayer coupling induces a spontaneous explosive synchronization and a heterogeneous distribution of allocations, otherwise not present in the two systems considered separately. Our framework can find application to other cases where two or more dynamical processes such as synchronization, opinion formation, information diffusion, or disease spreading, are interacting with each other.