Two distinct transitions in spatially embedded multiplex networks

TL;DR

This paper investigates how the characteristic length of links in spatially embedded multiplex networks influences their percolation transitions, revealing two distinct behaviors depending on the link length relative to a critical value.

Contribution

It introduces a realistic model of spatially embedded multiplex networks with constrained link lengths and identifies two types of percolation transitions based on the characteristic length.

Findings

Longer links induce abrupt first-order transitions.

Shorter links lead to continuous percolation transitions.

Percolation threshold varies non-monotonically with link length.

Abstract

Multilayer infrastructure is often interdependent, with nodes in one layer depending on nearby nodes in another layer to function. The links in each layer are often of limited length, due to the construction cost of longer links. Here, we model such systems as a multiplex network composed of two or more layers, each with links of characteristic geographic length, embedded in 2-dimensional space. This is equivalent to a system of interdependent spatially embedded networks in two dimensions in which the connectivity links are constrained in length but varied while the length of the dependency links is always zero. We find two distinct percolation transition behaviors depending on the characteristic length, $\zeta$, of the links. When $\zeta$ is longer than a certain critical value, $\zeta_c$, abrupt, first-order transitions take place, while for $\zeta<\zeta_c$ the transition is continuous. We show that, though in single-layer networks increasing $\zeta$ decreases the percolation threshold $p_c$, in multiplex networks it has the opposite effect: increasing $p_c$ to a maximum at $\zeta=\zeta_c$. By providing a more realistic topological model for spatially embedded interdependent and multiplex networks and highlighting its similarities to lattice-based models, we provide a new direction for more detailed future studies.