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Self-similarity, small-world, scale-free scaling, disassortativity, and robustness in hierarchical lattices

Author

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  • Z.-Z. Zhang
  • S.-G. Zhou
  • T. Zou

Abstract

In this paper, firstly, we study analytically the topological features of a family of hierarchical lattices (HLs) from the view point of complex networks. We derive some basic properties of HLs controlled by a parameter q: scale-free degree distribution with exponent γ=2+ln 2/(ln q), null clustering coefficient, power-law behavior of grid coefficient, exponential growth of average path length (non-small-world), fractal scaling with dimension d B =ln (2q)/(ln 2), and disassortativity. Our results show that scale-free networks are not always small-world, and support the conjecture that self-similar scale-free networks are not assortative. Secondly, we define a deterministic family of graphs called small-world hierarchical lattices (SWHLs). Our construction preserves the structure of hierarchical lattices, including its degree distribution, fractal architecture, clustering coefficient, while the small-world phenomenon arises. Finally, the dynamical processes of intentional attacks and collective synchronization are studied and the comparisons between HLs and Barabási-Albert (BA) networks as well as SWHLs are shown. We find that the self-similar property of HLs and SWHLs significantly increases the robustness of such networks against targeted damage on hubs, as compared to the very vulnerable non fractal BA networks, and that HLs have poorer synchronizability than their counterparts SWHLs and BA networks. We show that degree distribution of scale-free networks does not suffice to characterize their synchronizability, and that networks with smaller average path length are not always easier to synchronize. Copyright EDP Sciences/Società Italiana di Fisica/Springer-Verlag 2007

Suggested Citation

  • Z.-Z. Zhang & S.-G. Zhou & T. Zou, 2007. "Self-similarity, small-world, scale-free scaling, disassortativity, and robustness in hierarchical lattices," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 56(3), pages 259-271, April.
  • Handle: RePEc:spr:eurphb:v:56:y:2007:i:3:p:259-271
    DOI: 10.1140/epjb/e2007-00107-6
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    Citations

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    Cited by:

    1. Xie, Wen-Jie & Zhou, Wei-Xing, 2011. "Horizontal visibility graphs transformed from fractional Brownian motions: Topological properties versus the Hurst index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(20), pages 3592-3601.
    2. Yang, Yang & Sun, Peng Gang & Hu, Xia & Li, Zhou Jun, 2014. "Closed walks for community detection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 397(C), pages 129-143.
    3. Yinhu Zhai & Jia-Bao Liu & Shaohui Wang, 2017. "Structure Properties of Koch Networks Based on Networks Dynamical Systems," Complexity, Hindawi, vol. 2017, pages 1-7, March.
    4. Li, Tianyu & Yan, Weigen, 2019. "Enumeration of spanning trees of 2-separable networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    5. Maiorino, Enrico & Livi, Lorenzo & Giuliani, Alessandro & Sadeghian, Alireza & Rizzi, Antonello, 2015. "Multifractal characterization of protein contact networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 302-313.
    6. Wang, Xueqin & Yu, Dong & Li, Tianyu & Jia, Ya, 2023. "Logistic stochastic resonance in the Hodgkin–Huxley neuronal system under electromagnetic induction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    7. Zhang, Qian & Xue, Yumei & Wang, Daohua & Niu, Min, 2019. "Asymptotic formula on average path length in a hierarchical scale-free network with fractal structure," Chaos, Solitons & Fractals, Elsevier, vol. 122(C), pages 196-201.

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