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Irreversible contact process on complex networks with dynamical recovery probability

Author

Listed:
  • Zhang, Shuang
  • Wu, Tao
  • Wang, Wei
  • Lin, Tao

Abstract

Contact process is widely used to describe the spreading of virus and information in real-world system. Previous studies on contact process always assumed that the infected node uniformly contacts one neighbor and becomes recovery with a constant recovery probability. In this paper, we propose a novel irreversible spreading model, in which an infected node preferencely contacts a neighbor according to the degrees of neighbors and becomes recovery with a dynamical probability. We propose a heterogeneous mean-field approach to describe the spreading dynamics. On both homogeneous and heterogeneous networks, we find that preferencely contacting the small degree nodes can promote the spreading dynamics, while the spreading dynamics will be greatly suppressed when each susceptible node provides the same volume of resources to the infected nodes. Our suggested theory can well predict the numerical simulations.

Suggested Citation

  • Zhang, Shuang & Wu, Tao & Wang, Wei & Lin, Tao, 2019. "Irreversible contact process on complex networks with dynamical recovery probability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 527(C).
  • Handle: RePEc:eee:phsmap:v:527:y:2019:i:c:s0378437119305084
    DOI: 10.1016/j.physa.2019.121336
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    Cited by:

    1. Chen, Xing & Wu, Tao & Xian, Xingping & Wang, Chao & Yuan, Ye & Ming, Guannan, 2020. "Enhancing robustness of link prediction for noisy complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 555(C).

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