Multilayer networks are widespread in natural and manmade systems. Key properties of these networks are their spectral and eigenfunction characteristics, as they determine the critical properties of many dynamics occurring on top of them. Here, we numerically demonstrate that the normalized localization length $\beta$ of the eigenfunctions of multilayer random networks follows a simple scaling law given by $\beta =x^{*}/(1+x^{*})$, with $x^{*}=\gamma {(b_{\mathrm{eff}}^2/L)}^{\delta }$, $\delta \sim 1$, and $b_{\mathrm{eff}}$ being the effective bandwidth of the adjacency matrix of the network, whose size is $L$. The scaling law for $\beta$, that we validate on real-world networks, might help to better understand criticality in multilayer networks and to predict the eigenfunction localization properties of them.

• Received 21 November 2016
• Revised 22 March 2017

DOI:https://doi.org/10.1103/PhysRevE.96.012307