Birth and Stabilization of Phase Clusters by Multiplexing of Adaptive Networks
Birth and Stabilization of Phase Clusters by Multiplexing of Adaptive Networks
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DOI：
10.1103/physrevlett.124.088301
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发表时间：
2020-02-24
影响因子：
8.6
通讯作者：
Schoell, Eckehard
中科院分区：
文献类型：
--
作者：
Berner, Rico;Sawicki, Jakub;Schoell, Eckehard
我们提出了一个概念，以产生和稳定不同的部分同步模式（相位集群）的自适应网络，这是广泛的神经科学和社会科学，以及生物学，工程学和其他学科。我们通过理论分析和计算机模拟表明，在具有对称性的多层网络中的复用可以在它们不稳定或甚至不存在于单层中的情况下诱导各种稳定的相位团簇状态。此外，我们开发了一种方法用于分析的拉普拉斯矩阵的复用网络，它允许洞察这些网络的频谱结构，使减少单层的稳定性问题。我们采用多重分解的多层模式的稳定性提供分析结果。作为本地动态，我们使用的典范仓本相振荡器，这是一个简单的通用模型，并已成功地应用于在广泛的自然和技术系统的同步现象的建模。
We propose a concept to generate and stabilize diverse partial synchronization patterns (phase clusters) in adaptive networks which are widespread in neuroscience and social sciences, as well as biology, engineering, and other disciplines. We show by theoretical analysis and computer simulations that multiplexing in a multilayer network with symmetry can induce various stable phase cluster states in a situation where they are not stable or do not even exist in the single layer. Further, we develop a method for the analysis of Laplacian matrices of multiplex networks which allows for insight into the spectral structure of these networks enabling a reduction to the stability problem of single layers. We employ the multiplex decomposition to provide analytic results for the stability of the multilayer patterns. As local dynamics we use the paradigmatic Kuramoto phase oscillator, which is a simple generic model and has been successfully applied in the modeling of synchronization phenomena in a wide range of natural and technological systems.