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Graph Concatenations to Derive Weighted Fractal Networks

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  • Zhanqi Zhang
  • Yingqing Xiao

Abstract

Given an initial weighted graph , an integer , and scaling factors , we define a sequence of weighted graphs iteratively. Provided that is given for , we let be copies of , whose weighted edges have been scaled by , respectively. Then, is constructed by concatenating with all the copies. The proposed framework shares several properties with fractal sets, and the similarity dimension has a great impact on the topology of the graphs (e.g., node strength distribution). Moreover, the average geodesic distance of increases logarithmically with the system size; thus, this framework also generates the small-world property.

Suggested Citation

  • Zhanqi Zhang & Yingqing Xiao, 2020. "Graph Concatenations to Derive Weighted Fractal Networks," Complexity, Hindawi, vol. 2020, pages 1-9, July.
  • Handle: RePEc:hin:complx:4906878
    DOI: 10.1155/2020/4906878
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