Controlling edge dynamics in complex networks
Controlling edge dynamics in complex networks
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DOI：
10.1038/nphys2327
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发表时间：
2012-07-01
期刊：
影响因子：
19.6
通讯作者：
Vicsek, Tamas
中科院分区：
文献类型：
--
作者：
Nepusz, Tamas;Vicsek, Tamas
物理、社会、生物和技术系统中不同单元的相互作用自然会产生复杂的网络结构。在过去十年中，网络一直是研究的焦点，在描述其结构和动态特性方面取得了相当大的进展。然而，在研究网络上发生的动力学的可控性方面所做的努力要少得多。在这里，我们引入并评估了一个定义在网络边缘的动力学过程，并证明这个过程的可控性特性与简单的节点动力学有显著差异。对现实世界网络的评估表明，它们中的大多数比其随机化的对应网络更具可控性。我们还发现转录调控网络特别容易控制。解析计算表明，具有无标度度分布的网络比不相关网络具有更好的可控性特性，并且入度和出度的正相关增强了所提出的动力学的可控性。
The interaction of distinct units in physical, social, biological and technological systems naturally gives rise to complex network structures. Networks have constantly been in the focus of research for the past decade, with considerable advances in the description of their structural and dynamical properties. However, much less effort has been devoted to studying the controllability of the dynamics taking place on them. Here we introduce and evaluate a dynamical process defined on the edges of a network, and demonstrate that the controllability properties of this process significantly differ from simple nodal dynamics. Evaluation of real-world networks indicates that most of them are more controllable than their randomized counterparts. We also find that transcriptional regulatory networks are particularly easy to control. Analytic calculations show that networks with scale-free degree distributions have better controllability properties than uncorrelated networks, and positively correlated in- and out-degrees enhance the controllability of the proposed dynamics.