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Controllability of complex networks  (Yang-Yu Liu, Jean-Jacques Slotine, &
Albert-László Barabási)

The ultimate proof of our understanding of natural or technological systems
is reflected in our ability to control them. Although control theory offers
mathematical tools for steering engineered and natural systems towards a
desired state, a framework to control complex self-organized systems is
lacking. Here we develop analytical tools to study the controllability of an
arbitrary complex directed network, identifying the set of driver nodes with
time-dependent control that 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 emerge in many real complex
systems, are the most difficult to control, but that dense and homogeneous
networks can be controlled using a few driver nodes. Counterintuitively, we
find that in both model and real systems the driver nodes tend to avoid the
high-degree nodes.

John Maloney
The Future of Networks
Tel:  415.902.9676
Fax: 415.276.6074
Skype: jheuristic

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