Finding influential nodes in networks using pinning control: Centrality measures confirmed with electrochemical oscillators.
Finding influential nodes in networks using pinning control: Centrality measures confirmed with electrochemical oscillators.
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DOI：
10.1063/5.0163899
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发表时间：
2023-09
期刊：
影响因子：
2.9
通讯作者：
Walter Bomela;Michael Sebek;Raphael Nagao;Bharat Singhal;István Z Kiss;Jr-Shin Li
中科院分区：
文献类型：
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作者：
Walter Bomela;Michael Sebek;Raphael Nagao;Bharat Singhal;István Z Kiss;Jr-Shin Li
动态单元网络的时空组织可能会崩溃，导致疾病（例如，在大脑中）或大规模故障（例如，电网停电）。然后，功能的重建需要确定最佳干预部位，从该部位可以最有效地重新稳定网络行为。在这里，我们考虑一个这样的场景，其中单元网络具有振荡动力学，这可以通过足够强的耦合和稳定单个单元来抑制，即，钉扎控制我们在控制增益与耦合强度的状态空间中分析了双曲线网络的稳定性，并将最有影响力的节点（MIN）确定为需要最弱耦合的节点，以在非常强的控制增益的限制下稳定网络。一个计算效率高的方法，基于网络拉普拉斯矩阵的Moore-Penrose伪逆，被发现是有效的识别MIN。此外，我们发现，在某些网络中，MIN重新定位时，控制增益发生变化，因此，不同的节点是最有影响力的弱耦合和强耦合网络。提出了一种控制理论措施来识别具有唯一或重定位MINs的网络。我们已经确定了现实世界中的网络与重新定位MIN，如社会和电网网络。实验结果证实了网络的化学反应，在网络中的振荡被有效地抑制通过钉扎的一个单一的反应位点的计算方法确定的。
The spatiotemporal organization of networks of dynamical units can break down resulting in diseases (e.g., in the brain) or large-scale malfunctions (e.g., power grid blackouts). Re-establishment of function then requires identification of the optimal intervention site from which the network behavior is most efficiently re-stabilized. Here, we consider one such scenario with a network of units with oscillatory dynamics, which can be suppressed by sufficiently strong coupling and stabilizing a single unit, i.e., pinning control. We analyze the stability of the network with hyperbolas in the control gain vs coupling strength state space and identify the most influential node (MIN) as the node that requires the weakest coupling to stabilize the network in the limit of very strong control gain. A computationally efficient method, based on the Moore-Penrose pseudoinverse of the network Laplacian matrix, was found to be efficient in identifying the MIN. In addition, we have found that in some networks, the MIN relocates when the control gain is changed, and thus, different nodes are the most influential ones for weakly and strongly coupled networks. A control theoretic measure is proposed to identify networks with unique or relocating MINs. We have identified real-world networks with relocating MINs, such as social and power grid networks. The results were confirmed in experiments with networks of chemical reactions, where oscillations in the networks were effectively suppressed through the pinning of a single reaction site determined by the computational method.