Rich-club network topology to minimize synchronization cost due to phase difference among frequency-synchronized oscillators.

Rich-club network topology to minimize synchronization cost due to phase difference among frequency-synchronized oscillators.
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Rich-club 网络拓扑可最大限度地降低由于频率同步振荡器之间的相位差而导致的同步成本。

DOI:
10.1016/j.physa.2012.11.041
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发表时间:
2012
期刊:
影响因子:
3.3
通讯作者:
渡部喬光
渡部喬光
中科院分区:
物理与天体物理2区
文献类型:
--
作者:
Taro Ikegami;他4名;池上太郎;松田恒平;須永恵美子;SUNAGA Emiko;須永恵美子;須永恵美子;須永恵美子;SUNAGA Emiko;須永恵美子;須永恵美子;須永恵美子;須永恵美子;須永恵美子;SUNAGA Emiko;須永恵美子;仁平ふくみ;仁平ふくみ;Yusuke Kubota and Bob Levine;渡部喬光;渡部喬光

文献摘要

相似文献

以电网和大规模脑网络为例,由相位振荡器组成的网络的一些功能不仅依赖于频率同步,而且依赖于振荡器之间的相位同步。然而,即使在振荡器达到频率同步状态之后,也不总是实现相位同步,这是因为振荡器之间的相位差经常被捕获在非零恒定值。这样的相位差潜在地导致振荡器之间的功率或信息的低效传输,并且避免网络的适当和有效的功能。在本研究中,我们新定义的同步成本,通过使用频率同步振荡器之间的相位差,并探讨最佳的网络结构,最小的同步成本,通过基于rechermining优化。通过使用仓本模型,我们证明了成本最小化的网络与丰富的俱乐部拓扑结构,其中包括密集连接的中心节点和低度的外围节点与中心模块连接。我们还表明,网络拓扑结构的特点是其双峰度分布,这是量化的沃尔夫森的极化指数。
As exemplified by power grids and large-scale brain networks, some functions of networks consisting of phase oscillators rely on not only frequency synchronization, but also phase synchronization among the oscillators. Nevertheless, even after the oscillators reach frequency-synchronized status, the phase synchronization is not always accomplished because the phase difference among the oscillators is often trapped at non-zero constant values. Such phase difference potentially results in inefficient transfer of power or information among the oscillators, and avoids proper and efficient functioning of the networks. In the present study, we newly define synchronization cost by using the phase difference among the frequency-synchronized oscillators, and investigate the optimal network structure with the minimum synchronization cost through rewiring-based optimization. By using the Kuramoto model, we demonstrate that the cost is minimized in a network with a rich-club topology, which comprises the densely-connected center nodes and low-degree peripheral nodes connecting with the center module. We also show that the network topology is characterized by its bimodal degree distribution, which is quantified by Wolfson’s polarization index.