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Electronic Journal of Combinatorics
Article . 2006 . Peer-reviewed
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zbMATH Open
Article . 2006
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DBLP
Article . 2006
Data sources: DBLP
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Encores on Cores

Encores on cores
Authors: Julie Cain; Nicholas C. Wormald;

Encores on Cores

Abstract

We give a new derivation of the threshold of appearance of the $k$-core of a random graph. Our method uses a hybrid model obtained from a simple model of random graphs based on random functions, and the pairing or configuration model for random graphs with given degree sequence. Our approach also gives a simple derivation of properties of the degree sequence of the $k$-core of a random graph, in particular its relation to multinomial and hence independent Poisson variables. The method is also applied to $d$-uniform hypergraphs.

Related Organizations
Keywords

degree sequence, Random graphs (graph-theoretic aspects), Poisson variables, random graph

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    popularity
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    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
27
Top 10%
Top 10%
Top 10%
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