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On the estimation of percolation thresholds for real networks

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  • Rong, Qingnan
  • Zhang, Jun
  • Sun, Xiaoqian
  • Wandelt, Sebastian

Abstract

The percolation threshold is the critical point at which a giant connected component emerges for the first time in the percolation process. Its theoretical estimation has recently gathered much attention, especially for real networks with complicated structures. However, the theoretical methods so far mainly provide lower bounds of the percolation threshold with non-negligible errors. In this paper, we first generalize the existing message passing algorithm by considering the independence of variables in iteration equations. We then give the exact implicit expressions of the site and bond percolation thresholds based on the correction δs(b). The experimental results show that the correction is strongly related to network structural properties so that we can predict it by the gradient boosting regression model. Finally, we take the predicted correction δs(b) to our theoretical framework and show that our estimates of site and bond percolation thresholds on 209 real networks are more accurate than those of the state-of-the-art methods.

Suggested Citation

  • Rong, Qingnan & Zhang, Jun & Sun, Xiaoqian & Wandelt, Sebastian, 2022. "On the estimation of percolation thresholds for real networks," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    • Handle: RePEc:eee:chsofr:v:158:y:2022:i:c:s0960077922001783
    DOI: 10.1016/j.chaos.2022.111968
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    References listed on IDEAS

    as
    1. Wandelt, Sebastian & Lin, Wei & Sun, Xiaoqian & Zanin, Massimiliano, 2022. "From random failures to targeted attacks in network dismantling," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    2. Wandelt, Sebastian & Shi, Xing & Sun, Xiaoqian, 2021. "Estimation and improvement of transportation network robustness by exploiting communities," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    3. Havlin, Shlomo & Stanley, H. Eugene & Bashan, Amir & Gao, Jianxi & Kenett, Dror Y., 2015. "Percolation of interdependent network of networks," Chaos, Solitons & Fractals, Elsevier, vol. 72(C), pages 4-19.
    4. Filippo Radicchi & Claudio Castellano, 2015. "Breaking of the site-bond percolation universality in networks," Nature Communications, Nature, vol. 6(1), pages 1-7, December.
    5. Wandelt, Sebastian & Sun, Xiaoqian & Menasalvas, Ernestina & Rodríguez-González, Alejandro & Zanin, Massimiliano, 2019. "On the use of random graphs as null model of large connected networks," Chaos, Solitons & Fractals, Elsevier, vol. 119(C), pages 318-325.
    6. Xiaoqian Sun & Sebastian Wandelt, 2021. "Robustness of Air Transportation as Complex Networks:Systematic Review of 15 Years of Research and Outlook into the Future," Sustainability, MDPI, vol. 13(11), pages 1-19, June.
    7. Shang, Yilun, 2021. "Generalized k-cores of networks under attack with limited knowledge," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    8. Li, Zhaoxing & Chen, Li, 2019. "Robustness of multipartite networks in face of random node failure," Chaos, Solitons & Fractals, Elsevier, vol. 121(C), pages 149-159.
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    Cited by:

    1. Liang, Yuan & Qi, Mingze & Huangpeng, Qizi & Duan, Xiaojun, 2023. "Percolation of interlayer feature-correlated multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).

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