Center of Complex Networks Research, Northeastern University and Division of Network Medicine, Harvard University.

“Taming Complexity: Controlling Networks”

Abstract: The ultimate proof of our understanding of biological or technological systems is reflected in our ability to control them. While control theory offers mathematical tools to steer engineered and natural systems towards a desired state, we lack a framework to control complex self-organized systems. Here we explore the controllability of an arbitrary complex network, identifying the set of driver nodes whose time-dependent control can guide the system’s entire dynamics. We apply these tools to several real networks, finding that the number of driver nodes is determined mainly by the network’s degree distribution. We show that sparse inhomogeneous networks, which tend to be observed in most real systems, are the most difficult to control, but dense and homogeneous networks can be controlled via a few driver nodes. Overall issues related to control open a series of new fundamental questions pertaining to our understanding of complex systems.