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Color-avoiding percolation and branching processes

Published online by Cambridge University Press:  08 March 2024

Panna Tímea Fekete*
Affiliation:
HUN-REN Alfréd Rényi Institute of Mathematics; Eötvös Loránd University
Roland Molontay*
Affiliation:
Budapest University of Technology and Economics; HUN-REN–BME Stochastics Research Group
Balázs Ráth*
Affiliation:
Budapest University of Technology and Economics; HUN-REN–BME Stochastics Research Group; HUN-REN Alfréd Rényi Institute of Mathematics
Kitti Varga*
Affiliation:
Budapest University of Technology and Economics; HUN-REN–ELTE Egerváry Research Group
*
*Postal address: Reáltanoda u. 14, H-1053 Budapest, Hungary. Email: fekete.panna.timea@renyi.hu
**Postal address: Department of Stochastics, Institute of Mathematics, Budapest University of Technology and Economics, Műegyetem rkp. 3., H-1111 Budapest, Hungary.
**Postal address: Department of Stochastics, Institute of Mathematics, Budapest University of Technology and Economics, Műegyetem rkp. 3., H-1111 Budapest, Hungary.
*****Postal address: Department of Computer Science and Information Theory, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, Pázmány Péter stny. 1/C, H-1117 Budapest, Hungary. Email: vkitti@math.bme.hu

Abstract

We study a variant of the color-avoiding percolation model introduced by Krause et al., namely we investigate the color-avoiding bond percolation setup on (not necessarily properly) edge-colored Erdős–Rényi random graphs. We say that two vertices are color-avoiding connected in an edge-colored graph if, after the removal of the edges of any color, they are in the same component in the remaining graph. The color-avoiding connected components of an edge-colored graph are maximal sets of vertices such that any two of them are color-avoiding connected. We consider the fraction of vertices contained in color-avoiding connected components of a given size, as well as the fraction of vertices contained in the giant color-avoidin g connected component. It is known that these quantities converge, and the limits can be expressed in terms of probabilities associated to edge-colored branching process trees. We provide explicit formulas for the limit of the fraction of vertices contained in the giant color-avoiding connected component, and we give a simpler asymptotic expression for it in the barely supercritical regime. In addition, in the two-colored case we also provide explicit formulas for the limit of the fraction of vertices contained in color-avoiding connected components of a given size.

Type
Original Article
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of Applied Probability Trust

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References

Albert, R., Jeong, H. and Barabási, A.-L. (2000). Error and attack tolerance of complex networks. Nature 406, 378382.CrossRefGoogle ScholarPubMed
Aldous, D. (1997). Brownian excursions, critical random graphs and the multiplicative coalescent. Ann. Prob. 25, 812854.CrossRefGoogle Scholar
Aldous, D. J. (1999). Deterministic and stochastic models for coalescence (aggregation and coagulation): A review of the mean-field theory for probabilists. Bernoulli 5, 348.CrossRefGoogle Scholar
Baxter, G. J. et al. (2010). Bootstrap percolation on complex networks. Phys. Rev. E 82, 011103.CrossRefGoogle ScholarPubMed
Callaway, D. S. et al. (2000). Network robustness and fragility: Percolation on random graphs. Phys. Rev. Lett. 85, 5468.CrossRefGoogle ScholarPubMed
DeVos, M., Johnson, M. and Seymour, P. (2006). Cut coloring and circuit covering. Princeton University. Available at https://web.math.princeton.edu/pds/papers/cutcolouring/paper.pdf.Google Scholar
Dorogovtsev, S. N., Goltsev, A. V. and Mendes, J. F. F. (2006). k-core organization of complex networks. Phys. Rev. Lett. 96, 040601.CrossRefGoogle ScholarPubMed
Fortuin, C. M., Kasteleyn, P. W. and Ginibre, J. (1971). Correlation inequalities on some partially ordered sets. Commun. Math. Phys. 22, 89103.CrossRefGoogle Scholar
Giusfredi, M. and Bagnoli, F. (2019). A self-organized criticality method for the study of coloravoiding percolation. In Internet Science, eds S. El Yacoubi, F. Bagnoli, and G. Pacini, Springer, Berlin, pp. 217–226.Google Scholar
Giusfredi, M. and Bagnoli, F. (2020). From color-avoiding to color-favored percolation in diluted lattices. Future Internet 12, 139.CrossRefGoogle Scholar
Hackett, A. et al. (2016). Bond percolation on multiplex networks. Phys. Rev. X 6, 021002.Google Scholar
Harris, T. E. (1960). A lower bound for the critical probability in a certain percolation process. Math. Proc. Camb. Phil. Soc. 56, 1320.CrossRefGoogle Scholar
Kadović, A. et al. (2018). Bond and site coloravoiding percolation in scale-free networks. Phys. Rev. E 98, 062308.CrossRefGoogle Scholar
König, D. (1927). Über eine Schlussweise aus dem Endlichen ins Unendliche. Acta Sci. Math. 3, 121130.Google Scholar
Krause, S. M., Danziger, M. M. and Zlatić, V. (2016). Hidden connectivity in networks with vulnerable classes of nodes. Phys. Rev. X 6, 041022.Google Scholar
Krause, S. M., Danziger, M. M. and Zlatić, V. (2017). Color-avoiding percolation. Phys. Rev. E 96, 022313.CrossRefGoogle ScholarPubMed
Kryven, I. (2019). Bond percolation in coloured and multiplex networks. Nature Commun. 10, 404.CrossRefGoogle ScholarPubMed
Li, M. et al. (2021). Percolation on complex networks: Theory and application. Phys. Rep. 907, 168.CrossRefGoogle Scholar
Lichev, L. (2023). Color-avoiding percolation of random graphs: between the subcritical and the intermediate regime. Preprint, arXiv:2301.09910 [math.PR].Google Scholar
Lichev, L. and Schapira, B. (2022). Color-avoiding percolation on the Erdős–Rényi random graph. Preprint, arXiv:2211.16086 [math.PR].Google Scholar
López, E. et al. (2007). Limited path percolation in complex networks. Phys. Rev. Lett. 99, 188701.CrossRefGoogle ScholarPubMed
Lyons, R., Pemantle, R. and Peres, Y. (1995). Conceptual proofs of $L\log L$ criteria for mean behavior of branching processes. Ann. Prob. 23, 11251138.Google Scholar
Mahabadi, Z., Varga, L. and Dolan, T. (2021). Network properties for robust multilayer infrastructure systems: A percolation theory review. IEEE Access 9, 135755135773.CrossRefGoogle Scholar
Molontay, R. and Varga, K. (2019). On the complexity of color-avoiding site and bond percolation. In SOFSEM 2019: Theory and Practice of Computer Science, eds B. Catania, R. Královič, J. Nawrocki, and G. Pighizzini. Springer, Berlin, pp. 354–367.CrossRefGoogle Scholar
Penrose, M. D. (1999). On k-connectivity for a geometric random graph. Random Structures Algorithms 15, 145164.3.0.CO;2-G>CrossRefGoogle Scholar
Ráth, B. et al. (2022). Color-avoiding percolation in edge-colored Erdős–Rényi graphs. Preprint, arXiv:2208.12727 [math.PR].Google Scholar
Shang, Y., Luo, W. and Xu, S. (2011). L-hop percolation on networks with arbitrary degree distributions and its applications. Phys. Rev. E 84, 031113.CrossRefGoogle ScholarPubMed
Shao, S. et al. (2015). Percolation of localized attack on complex networks. New J. Phys. 17, 023049.CrossRefGoogle Scholar
Shekhtman, L. M. et al. (2018). Critical field-exponents for secure message-passing in modular networks, New J. Phys. 20, 053001.CrossRefGoogle Scholar
Son, S.-W. et al. (2012). Percolation theory on interdependent networks based on epidemic spreading. Europhys. Lett. 97, 16006.CrossRefGoogle Scholar
Van der Hofstad, R. (2017). Random Graphs and Complex Networks, Vol. 1. Cambridge University Press.Google Scholar
Van der Hofstad, R. (2017). Random Graphs and Complex Networks, Vol. 2. Cambridge University Press.Google Scholar
Yuan, X. et al. (2016). k-core percolation on complex networks: Comparing random, localized, and targeted attacks. Phys. Rev. E 93, 062302.CrossRefGoogle ScholarPubMed