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Inducing effect on the percolation transition in complex networks

Author

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  • Jin-Hua Zhao

    (State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences)

  • Hai-Jun Zhou

    (State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences)

  • Yang-Yu Liu

    (Northeastern University
    Center for Cancer Systems Biology, Dana-Farber Cancer Institute)

Abstract

Percolation theory concerns the emergence of connected clusters that percolate through a networked system. Previous studies ignored the effect that a node outside the percolating cluster may actively induce its inside neighbours to exit the percolating cluster. Here we study this inducing effect on the classical site percolation and K-core percolation, showing that the inducing effect always causes a discontinuous percolation transition. We precisely predict the percolation threshold and core size for uncorrelated random networks with arbitrary degree distributions. For low-dimensional lattices the percolation threshold fluctuates considerably over realizations, yet we can still predict the core size once the percolation occurs. The core sizes of real-world networks can also be well predicted using degree distribution as the only input. Our work therefore provides a theoretical framework for quantitatively understanding discontinuous breakdown phenomena in various complex systems.

Suggested Citation

  • Jin-Hua Zhao & Hai-Jun Zhou & Yang-Yu Liu, 2013. "Inducing effect on the percolation transition in complex networks," Nature Communications, Nature, vol. 4(1), pages 1-6, December.
  • Handle: RePEc:nat:natcom:v:4:y:2013:i:1:d:10.1038_ncomms3412
    DOI: 10.1038/ncomms3412
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    Cited by:

    1. Jianxi Gao & Xueming Liu & Daqing Li & Shlomo Havlin, 2015. "Recent Progress on the Resilience of Complex Networks," Energies, MDPI, vol. 8(10), pages 1-24, October.

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