Scale-free networks emerging from multifractal time series

Marcello A. Budroni, Andrea Baronchelli, and Romualdo Pastor-Satorras
Phys. Rev. E 95, 052311 – Published 16 May 2017

Abstract

Methods connecting dynamical systems and graph theory have attracted increasing interest in the past few years, with applications ranging from a detailed comparison of different kinds of dynamics to the characterization of empirical data. Here we investigate the effects of the (multi)fractal properties of a signal, common in time series arising from chaotic dynamics or strange attractors, on the topology of a suitably projected network. Relying on the box-counting formalism, we map boxes into the nodes of a network and establish analytic expressions connecting the natural measure of a box with its degree in the graph representation. We single out the conditions yielding to the emergence of a scale-free topology and validate our findings with extensive numerical simulations. We finally present a numerical analysis on the properties of weighted and directed network projections.

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  • Received 19 December 2016

DOI:https://doi.org/10.1103/PhysRevE.95.052311

©2017 American Physical Society

Physics Subject Headings (PhySH)

NetworksNonlinear Dynamics

Authors & Affiliations

Marcello A. Budroni1,*, Andrea Baronchelli2, and Romualdo Pastor-Satorras3,†

  • 1Nonlinear Physical Chemistry Unit, Faculté des Sciences, Université libre de Bruxelles (ULB), CP 231-Campus Plaine, 1050 Brussels, Belgium
  • 2Department of Mathematics-City, University of London-Northampton Square, London EC1V 0HB, United Kingdom
  • 3Departament de Física, Universitat Politècnica de Catalunya, Campus Nord B4, 08034 Barcelona, Spain

  • *mbudroni@ulb.ac.be
  • romualdo.pastor@upc.edu

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Issue

Vol. 95, Iss. 5 — May 2017

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