最优网络的构造、灵敏度指数和同步速度

Jeremie Fish, Jie Sun
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引用次数: 5

摘要

同步的稳定性(或不稳定性)在许多现实世界的系统中都很重要,包括电网、人脑和生物细胞。对于相同的同步,可以对给定数量的节点和链路优化网络的可同步性,可通过允许稳定同步的耦合强度范围来衡量。根据拉普拉斯特征向量的几何简并度,可以将最优网络划分为不同的灵敏度等级,我们将其定义为网络的灵敏度指标。我们介绍了一种有效和明确的方法来构建任意大小的最优网络,在广泛的灵敏度和链路密度范围内。利用耦合混沌振荡器研究了最优网络的同步动力学,结果表明,共谱最优网络的同步速度可能有很大差异。这种动态稳定性的差异与这些网络结构灵敏度的不同密切相关:通常,灵敏度指数高的网络同步速度较慢,并且令人惊讶的是,尽管在线性稳定性分析下理论上是稳定的,但可能根本不同步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Construction,sensitivity index, and synchronization speed of optimal networks
The stability (or instability) of synchronization is important in a number of real world systems, including the power grid, the human brain and biological cells. For identical synchronization, the synchronizability of a network, which can be measured by the range of coupling strength that admits stable synchronization, can be optimized for a given number of nodes and links. Depending on the geometric degeneracy of the Laplacian eigenvectors, optimal networks can be classified into different sensitivity levels, which we define as a network's sensitivity index. We introduce an efficient and explicit way to construct optimal networks of arbitrary size over a wide range of sensitivity and link densities. Using coupled chaotic oscillators, we study synchronization dynamics on optimal networks, showing that cospectral optimal networks can have drastically different speed of synchronization. Such difference in dynamical stability is found to be closely related to the different structural sensitivity of these networks: generally, networks with high sensitivity index are slower to synchronize, and, surprisingly, may not synchronize at all, despite being theoretically stable under linear stability analysis.
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