Controllability of multiplex, multi-timescale networks

TL;DR

This paper develops a control theory for multilayer, multi-timescale networks, revealing how timescale differences influence the minimum inputs needed for full control, with implications for complex real-world systems.

Contribution

It introduces a novel disjoint path cover approach to determine control inputs in multiplex networks with different timescales, highlighting the impact of timescale separation on controllability.

Findings

Controllability depends on whether control interacts with faster or slower layers.

Timescale separation can either facilitate or hinder control depending on the layer targeted.

A critical timescale difference exists beyond which control requirements stabilize.

Abstract

The paradigm of layered networks is used to describe many real-world systems -- from biological networks, to social organizations and transportation systems. Recently there has been much progress in understanding the general properties of multilayer networks, our understanding of how to control such systems remains limited. One aspect that makes this endeavor challenging is that each layer can operate at a different timescale, thus we cannot directly apply standard ideas from structural control theory of individual networks. Here we address the problem of controlling multilayer and multi-timescale networks focusing on two-layer multiplex networks with one-to-one interlayer coupling. We investigate the case when the control signal is applied to the nodes of one layer. We develop a theory based on disjoint path covers to determine the minimum number of inputs ($N_\T i$) necessary for full control. We show that if both layers operate on the same timescale then the network structure of both layers equally affect controllability. In the presence of timescale separation, controllability is enhanced if the controller interacts with the faster layer: $N_\T i$ decreases as the timescale difference increases up to a critical timescale difference, above which $N_\T i$ remains constant and is completely determined by the faster layer. In contrast, control becomes increasingly difficult if the controller interacts with the layer operating on the slower timescale and increasing timescale separation leads to increased $N_\T i$, again up to a critical value, above which $N_\T i$ still depends on the structure of both layers. By identifying the underlying mechanisms that connect timescale difference and controllability for a simplified model, we provide insight into disentangling how our ability to control real interacting complex systems is affected by a variety of sources of complexity.