2016
DOI: 10.1103/physrevx.6.021002
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Bond Percolation on Multiplex Networks

Abstract: We present an analytical approach for bond percolation on multiplex networks and use it to determine the expected size of the giant connected component and the value of the critical bond occupation probability in these networks. We advocate the relevance of these tools to the modeling of multilayer robustness and contribute to the debate on whether any benefit is to be yielded from studying a full multiplex structure as opposed to its monoplex projection, especially in the seemingly irrelevant case of a bond o… Show more

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Cited by 78 publications
(84 citation statements)
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“…The nature of this phase transition is a clear sign that multilayer networks with interdependencies display a significant fragility with respect to random damage. Several other generalized percolation problems on multiplex networks have been also proposed, including competition between the layers [20,21], weak percolation [22,23], generalized k-core percolation [24], percolation on directed multiplex networks [25], spanning connectivity [26], and bond percolation [27].…”
Section: Introductionmentioning
confidence: 99%
“…The nature of this phase transition is a clear sign that multilayer networks with interdependencies display a significant fragility with respect to random damage. Several other generalized percolation problems on multiplex networks have been also proposed, including competition between the layers [20,21], weak percolation [22,23], generalized k-core percolation [24], percolation on directed multiplex networks [25], spanning connectivity [26], and bond percolation [27].…”
Section: Introductionmentioning
confidence: 99%
“…In these cases the aforementioned functional equation remains the main bottleneck and is typically addressed numerically with the only exception of percolation studies. Some percolation criteria were obtained analytically both in directed networks (in and out percolation [8] and weak percolation [11]) and in multiplex networks (k-core percolation [13], weak percolation [16], a strong mutually connected component [12], and a giant connected component [20]). To date, few results are available on the size distribution of finite connected components in these configuration models.…”
Section: Introductionmentioning
confidence: 99%
“…Figure 2(a) shows that time-delays produce temporal microtransitions, i.e., R(t) versus t exhibits multiple transitions, which also exist in percolation [44][45][46]. When no individuals have time-delays i.e., when f=0.0, the behavior adoption R(t) versus time t grows continuously.…”
Section: Time-delays With Dirac Delta Distributionmentioning
confidence: 99%