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Asymptotic degree distribution of a duplication-deletion random graph model

Probability 2017-02-24 v1 Combinatorics

Abstract

We study a discrete-time duplication-deletion random graph model and analyse its asymptotic degree distribution. The random graphs consists of disjoint cliques. In each time step either a new vertex is brought in with probability 0<p<10<p<1 and attached to an existing clique, chosen with probability proportional to the clique size, or all the edges of a random vertex are deleted with probability 1p1-p. We prove almost sure convergence of the asymptotic degree distribution and find its exact values in terms of a hypergeometric integral, expressed in terms of the parameter pp. In the regime 0<p<120<p<\frac{1}{2} we show that the degree sequence decays exponentially at rate p1p\frac{p}{1-p}, whereas it satisfies a power-law with exponent p2p1\frac{p}{2p-1} if 12<p<1\frac{1}{2}<p<1. At the threshold p=12p=\frac{1}{2} the degree sequence lies between a power-law and exponential decay.

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Cite

@article{arxiv.1408.4268,
  title  = {Asymptotic degree distribution of a duplication-deletion random graph model},
  author = {Erik Thörnblad},
  journal= {arXiv preprint arXiv:1408.4268},
  year   = {2017}
}

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