Menichetti Giulia, Dall'Asta Luca, Bianconi Ginestra
Department of Physics and Astronomy and INFN Sezione di Bologna, Bologna University, Viale Berti Pichat 6/2, 40127 Bologna, Italy.
Department of Applied Science and Technology DISAT, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy and Collegio Carlo Alberto, Via Real Collegio 30, 10024 Moncalieri, Italy.
Phys Rev Lett. 2014 Aug 15;113(7):078701. doi: 10.1103/PhysRevLett.113.078701. Epub 2014 Aug 13.
The problem of controllability of the dynamical state of a network is central in network theory and has wide applications ranging from network medicine to financial markets. The driver nodes of the network are the nodes that can bring the network to the desired dynamical state if an external signal is applied to them. Using the framework of structural controllability, here, we show that the density of nodes with in degree and out degree equal to one and two determines the number of driver nodes in the network. Moreover, we show that random networks with minimum in degree and out degree greater than two, are always fully controllable by an infinitesimal fraction of driver nodes, regardless of the other properties of the degree distribution. Finally, based on these results, we propose an algorithm to improve the controllability of networks.
网络动态状态的可控性问题是网络理论的核心,并且有着广泛的应用,涵盖从网络医学到金融市场等领域。网络的驱动节点是指那些如果施加外部信号就能将网络带入期望动态状态的节点。在此,我们利用结构可控性框架表明,入度和出度分别等于一和二的节点密度决定了网络中驱动节点的数量。此外,我们还表明,最小入度和出度大于二的随机网络,总是能由极小部分的驱动节点实现完全可控,而与度分布的其他属性无关。最后,基于这些结果,我们提出一种算法来提高网络的可控性。