Two phase transitions in modular multiplex networks

TL;DR

This paper investigates the critical phase transitions in modular multiplex networks, revealing diverse behaviors including continuous, abrupt, and mixed-order transitions, and analytically determines the thresholds for module disconnection.

Contribution

It provides a comprehensive analysis of two phase transitions in modular multiplex networks, highlighting the effects of modular organization and interdependence on network robustness.

Findings

Modules become disconnected at a critical threshold.

Some transitions are continuous, others are abrupt.

Mixed-order transitions can occur within the same system.

Abstract

Modular networks, such as critical infrastructures, are often built from distinct, densely connected modules (e.g., cities) that are sparsely interconnected. When such networks are gradually and randomly disrupted under a percolation process, they undergo two critical phase transitions. The first transition occurs when modules become isolated from one another, while the second corresponds to the collapse of the entire network, including the internal connectivity of the modules. Here, we study these phase transitions in modular multiplex networks and compare them with those observed in single-layer modular networks. We focus on models in which the modules are arranged and connected either as a Random Regular network or as a two-dimensional square lattice. We show here that these systems exhibit diverse transition behaviors, with some transitions occurring continuously and others abruptly; notably, one realistic model could display two distinct first-order transitions in the same system. For the modular Random Regular multiplex, we further characterize the spatial transition through its scaling behavior, revealing signatures of a mixed-order phase transitions. In addition, we analytically determine the critical threshold at which modules become disconnected. Our results highlight the crucial role of modular organization and the critical role of interdependence in shaping network vulnerabilities under failures.