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The cut metric, random graphs, and branching processes

Abstract:
In this paper we study the component structure of random graphs with independence between the edges. Under mild assumptions, we determine whether there is a giant component, and find its asymptotic size when it exists. We assume that the sequence of matrices of edge probabilities converges to an appropriate limit object (a kernel), but only in a very weak sense, namely in the cut metric. Our results thus generalize previous results on the phase transition in the already very general inhomogeneous random graph model we introduced recently, as well as related results of Bollob\'as, Borgs, Chayes and Riordan, all of which involve considerably stronger assumptions. We also prove corresponding results for random hypergraphs; these generalize our results on the phase transition in inhomogeneous random graphs with clustering.
Publication status:
Published

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Publisher copy:
10.1007/s10955-010-9982-z

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Journal:
J. Statistical Physics 140 (2010), 289--335 More from this journal
Volume:
140
Issue:
2
Pages:
289-335
Publication date:
2009-01-14
DOI:
EISSN:
1572-9613
ISSN:
0022-4715


Language:
English
Keywords:
Pubs id:
pubs:65318
UUID:
uuid:ebf81da9-a7bd-4a1f-8c27-fc1030e6638b
Local pid:
pubs:65318
Source identifiers:
65318
Deposit date:
2012-12-19

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