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An elementary approach to component sizes in critical random graphs
Published online by Cambridge University Press: 11 November 2022
Abstract
In this article we introduce a simple tool to derive polynomial upper bounds for the probability of observing unusually large maximal components in some models of random graphs when considered at criticality. Specifically, we apply our method to a model of a random intersection graph, a random graph obtained through p-bond percolation on a general d-regular graph, and a model of an inhomogeneous random graph.
Keywords
MSC classification
- Type
- Original Article
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- Copyright
- © The Author(s), 2022. Published by Cambridge University Press on behalf of Applied Probability Trust
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