Fiedler value: The cumulated dynamical contribution value of all edges in a complex network

Jiang, Siyang; Lu, Jun-an; Zhou, Jin; Dai, Qinrui

doi:10.1103/physreve.109.054301

Phys. Rev. E

2024

DOI: 10.1103/physreve.109.054301

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Fiedler value: The cumulated dynamical contribution value of all edges in a complex network

Siyang Jiang,

Jun-an Lu,

Jin Zhou

et al.

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2024

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Cited by 3 publications

References 34 publications

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Approximating the Splitting Point of the Swarmalator Model

Gong,

Zhou,

Huang

2024

Int. J. Bifurcation Chaos

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Swarmalator model attracts the attention of numerous scholars because of its rich dynamical behaviors. We investigate the reason for the phase transition that occurs in a 2D swarmalator model, and conclude that the limit cycle, a reflection of the coexistence of the forces of maintaining and disrupting orders, results in the various clustering phenomena. Through novel mean-field approximation and using the self-consistency argument method, we prove the clustering conditions and the influence of the number of clusters on the existence of clusters, and provide estimates of the cluster size of the splintered phase wave state and the phase transition threshold between the splintered phase wave state and active phase wave state. Due to the widespread presence of nonlinearity, our study is essential to the analysis of clustering phenomena in real physical models.

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Approximating the Splitting Point of the Swarmalator Model

Gong,

Zhou,

Huang

2024

Int. J. Bifurcation Chaos

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Node Centrality Based on Edge Dynamics in a Chaotic Network

Chen,

Zhou,

2024

Int. J. Bifurcation Chaos

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This paper introduces a novel node centrality index based on edge dynamics in a complex network: adjacent edge index. Through the analysis of network dynamics and topology, we provide a neat index to qualify node importance, which is calculated by the eigenvector components corresponding to the Fiedler value of the network. Notably, it identifies nodes whose adjacent edge sets play a significant role in network synchronization. The index indicates that not only a node’s degree but also its location should be considered. To demonstrate the effectiveness of the proposed index, consider a double-star network and a Jazz Musicians network in which chaotic Chua’s circuits as nodes are coupled. By factoring in the dynamic information exchange between nodes and their neighbors, this index offers valuable insights for optimizing strategies in engineering areas such as efficient information dissemination.

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Pinning synchronization of a complex network: Nodes, edges and higher-order edges

Jiang,

Zhou,

et al. 2024

EPL

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In recent years, the interdisciplinary study of complex networks has become increasingly important in fields ranging from biology and physics to sociology and mathematics. This paper focuses on pinning control, an approach essential for achieving coordinated behavior in dynamic networks. We explore recent advancements in pinning control strategies, explaining theoretical frameworks and simulation techniques. Additionally, we discuss the significance of certain structures within networks across different orders. Finally, we conclude with a summary of key insights and propose our outlook on future research.

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Fiedler value: The cumulated dynamical contribution value of all edges in a complex network

Cited by 3 publications

References 34 publications

Approximating the Splitting Point of the Swarmalator Model

Approximating the Splitting Point of the Swarmalator Model

Node Centrality Based on Edge Dynamics in a Chaotic Network

Pinning synchronization of a complex network: Nodes, edges and higher-order edges

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