Reconstruction of evolved dynamic networks from degree correlations

Steffen Karalus and Joachim Krug
Phys. Rev. E 93, 062306 – Published 10 June 2016

Abstract

We study the importance of local structural properties in networks which have been evolved for a power-law scaling in their Laplacian spectrum. To this end, the degree distribution, two-point degree correlations, and degree-dependent clustering are extracted from the evolved networks and used to construct random networks with the prescribed distributions. In the analysis of these reconstructed networks it turns out that the degree distribution alone is not sufficient to generate the spectral scaling and the degree-dependent clustering has only an indirect influence. The two-point correlations are found to be the dominant characteristic for the power-law scaling over a broader eigenvalue range.

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  • Received 29 March 2016
  • Revised 19 May 2016

DOI:https://doi.org/10.1103/PhysRevE.93.062306

©2016 American Physical Society

Physics Subject Headings (PhySH)

Networks

Authors & Affiliations

Steffen Karalus* and Joachim Krug

  • Institut für Theoretische Physik, Universität zu Köln, Zülpicher Straße 77, D-50937 Köln, Germany

  • *karalus@thp.uni-koeln.de
  • krug@thp.uni-koeln.de

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Issue

Vol. 93, Iss. 6 — June 2016

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