论文标题
确定促进网络动力系统中极端事件的产生的边缘
Identifying edges that facilitate the generation of extreme events in networked dynamical systems
论文作者
论文摘要
Fitzhugh-Nagumo单位复杂网络的集体动力学表现出罕见的高振幅事件（极端事件），前面是所谓的原始事件，在此期间，一定一部分单元变得兴奋。尽管众所周知，需要足够大的激发单元才能将原始事件变成极端事件，但尚不清楚如何将其他单元招募到最终的极端事件中。为了解决这个问题并模仿典型的实验情况，我们研究了时间依赖性相互作用网络中边缘的中心性。我们使用广泛使用的双变量分析技术的单位动力学的时间序列得出了这些网络。使用我们最近提出的边缘中心概念以及基于边缘的网络分解技术，我们观察到招聘主要是通过在基本拓扑中没有等效的某些边缘组来促进的。我们的发现可能有助于提高对自然网络动力学系统中极端事件的产生的理解。
The collective dynamics of complex networks of FitzHugh-Nagumo units exhibits rare and recurrent events of high amplitude (extreme events) that are preceded by so-called proto-events during which a certain fraction of the units become excited. Although it is well known that a sufficiently large fraction of excited units is required to turn a proto-event into an extreme event, it is not yet clear how the other units are being recruited into the final generation of an extreme event. Addressing this question and mimicking typical experimental situations, we investigate the centrality of edges in time-dependent interaction networks. We derived these networks from time series of the units' dynamics employing a widely used bivariate analysis technique. Using our recently proposed edge centrality concepts together with an edge-based network decomposition technique, we observe that the recruitment is primarily facilitated by sets of certain edges that have no equivalent in the underlying topology. Our finding might aid to improve the understanding of generation of extreme events in natural networked dynamical systems.
