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On the continuous-time limit of the Barabási–Albert random graph

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  • Pachon, Angelica
  • Polito, Federico
  • Sacerdote, Laura

Abstract

We prove that, via an appropriate scaling, the degree of a fixed vertex in the Barabási–Albert model appeared at a large enough time converges in distribution to a Yule process. Using this relation we explain why the limit degree distribution of a vertex chosen uniformly at random (as the number of vertices goes to infinity), coincides with the limit distribution of the number of species in a genus selected uniformly at random in a Yule model (as time goes to infinity). To prove this result we do not assume that the number of vertices increases exponentially over time (linear rates). On the contrary, we retain their natural growth with a constant rate superimposing to the overall graph structure a suitable set of processes that we call the planted model and introducing an ad-hoc sampling procedure.

Suggested Citation

  • Pachon, Angelica & Polito, Federico & Sacerdote, Laura, 2020. "On the continuous-time limit of the Barabási–Albert random graph," Applied Mathematics and Computation, Elsevier, vol. 378(C).
  • Handle: RePEc:eee:apmaco:v:378:y:2020:i:c:s0096300320301466
    DOI: 10.1016/j.amc.2020.125177
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    References listed on IDEAS

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    1. Andreas Klaus & Shan Yu & Dietmar Plenz, 2011. "Statistical Analyses Support Power Law Distributions Found in Neuronal Avalanches," PLOS ONE, Public Library of Science, vol. 6(5), pages 1-12, May.
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