Models of percolation processes on networks currently assume locally tree-like structures at low densities, and are derived exactly only in the thermodynamic limit. Finite size effects and the presence of short loops in real systems however cause a deviation between the empirical percolation threshold pc and its model-predicted value πc. Here we show the existence of an empirical linear relation between pc and πc across a large number of real and model networks. Such a putatively universal relation can then be used to correct the estimated value of πc. We further show how to obtain a more precise relation using the concept of the complement graph, by investigating on the connection between the percolation threshold of a network, pc, and that of its complement, pc.
Autori: | ||
Data di pubblicazione: | 2019 | |
Titolo: | Numerical assessment of the percolation threshold using complement networks | |
Titolo del libro: | COMPLEX NETWORKS 2018: Complex Networks and Their Applications VII | |
Digital Object Identifier (DOI): | http://dx.doi.org/10.1007/978-3-030-05411-3_65 | |
Appare nelle tipologie: | 4.1 Articolo in Atti di convegno |