Papadopoulos Lia, Kim Jason Z, Kurths Jürgen, Bassett Danielle S
Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.
Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.
Chaos. 2017 Jul;27(7):073115. doi: 10.1063/1.4994819.
Synchronization of non-identical oscillators coupled through complex networks is an important example of collective behavior, and it is interesting to ask how the structural organization of network interactions influences this process. Several studies have explored and uncovered optimal topologies for synchronization by making purposeful alterations to a network. On the other hand, the connectivity patterns of many natural systems are often not static, but are rather modulated over time according to their dynamics. However, this co-evolution and the extent to which the dynamics of the individual units can shape the organization of the network itself are less well understood. Here, we study initially randomly connected but locally adaptive networks of Kuramoto oscillators. In particular, the system employs a co-evolutionary rewiring strategy that depends only on the instantaneous, pairwise phase differences of neighboring oscillators, and that conserves the total number of edges, allowing the effects of local reorganization to be isolated. We find that a simple rule-which preserves connections between more out-of-phase oscillators while rewiring connections between more in-phase oscillators-can cause initially disordered networks to organize into more structured topologies that support enhanced synchronization dynamics. We examine how this process unfolds over time, finding a dependence on the intrinsic frequencies of the oscillators, the global coupling, and the network density, in terms of how the adaptive mechanism reorganizes the network and influences the dynamics. Importantly, for large enough coupling and after sufficient adaptation, the resulting networks exhibit interesting characteristics, including degree-frequency and frequency-neighbor frequency correlations. These properties have previously been associated with optimal synchronization or explosive transitions in which the networks were constructed using global information. On the contrary, by considering a time-dependent interplay between structure and dynamics, this work offers a mechanism through which emergent phenomena and organization can arise in complex systems utilizing local rules.
通过复杂网络耦合的非相同振荡器的同步是集体行为的一个重要例子,探讨网络相互作用的结构组织如何影响这一过程很有意思。几项研究通过对网络进行有目的的改变来探索和揭示同步的最优拓扑结构。另一方面,许多自然系统的连接模式往往不是静态的,而是根据其动态随时间进行调制。然而,这种共同进化以及单个单元的动态能够塑造网络自身组织的程度还不太为人所理解。在这里,我们研究最初随机连接但局部自适应的Kuramoto振荡器网络。具体而言,该系统采用一种共同进化的重新布线策略,该策略仅依赖于相邻振荡器的瞬时成对相位差,并且保持边的总数不变,从而能够分离局部重组的影响。我们发现一个简单的规则——在重新连接相位更相近的振荡器之间的连接时保留相位更不同的振荡器之间的连接——可以使最初无序的网络组织成更结构化的拓扑结构,从而支持增强的同步动态。我们研究了这个过程如何随时间展开,发现在自适应机制如何重组网络并影响动态方面,它依赖于振荡器的固有频率、全局耦合和网络密度。重要的是,对于足够大的耦合以及经过充分的自适应后,所得到的网络表现出有趣的特性,包括度 - 频率和频率 - 邻域频率相关性。这些特性此前曾与使用全局信息构建的网络中的最优同步或爆发性转变相关联。相反,通过考虑结构与动态之间随时间变化的相互作用,这项工作提供了一种机制,通过该机制在利用局部规则的复杂系统中可以出现涌现现象和组织。