Asymptotic degree distribution in preferential attachment graph models with multiple type edges

TL;DR

This paper analyzes the asymptotic degree distribution in a multi-type preferential attachment graph model, establishing convergence results, recurrence relations, and extending scale-free properties to multiple edge types.

Contribution

It introduces a generalized model with multiple edge types, proves almost sure convergence of degree distributions, and extends scale-free properties to this multi-type setting.

Findings

Asymptotic degree distribution exists and converges almost surely.

Recurrence equations characterize the degree distribution.

Scale-free property is generalized to multi-type edges.

Abstract

We deal with a general preferential attachment graph model with multiple type edges. The types are chosen randomly, in a way that depends on the evolution of the graph. In the $N$-type case, we define the (generalized) degree of a given vertex as $\boldsymbol{d}=(d_{1},d_{2},\dots,d_{N})$, where $d_{k}\in\mathbb{Z}_{0}^{+}$ is the number of type $k$ edges connected to it. We prove the existence of an a.s.\ asymptotic degree distribution for a general family of preferential attachment random graph models with multi-type edges. More precisely, we show that the proportion of vertices with (generalized) degree $\boldsymbol{d}$ tends to some random variable as the number of steps goes to infinity. We also provide recurrence equations for the asymptotic degree distribution. Finally, we generalize the scale-free property of random graphs to the multi-type case.