Shortest path discovery of complex networks

Attila Fekete, Gábor Vattay, Márton Pósfai

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

In this Rapid Communication we present an analytic study of sampled networks in the case of some important shortest-path sampling models. We present analytic formulas for the probability of edge discovery in the case of an evolving and a static network model. We also show that the number of discovered edges in a finite network scales much more slowly than predicted by earlier mean-field models. Finally, we calculate the degree distribution of sampled networks and we demonstrate that they are analogous to a destroyed network obtained by randomly removing edges from the original network.

Original languageEnglish
Article number065101
JournalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
Volume79
Issue number6
DOIs
Publication statusPublished - Jun 23 2009

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ASJC Scopus subject areas

  • Statistical and Nonlinear Physics
  • Statistics and Probability
  • Condensed Matter Physics

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