Scale-free networks emerging from multifractal time series
PublisherAmerican Chemical Society (ACS)
Rights accessOpen Access
European Commission's projectMULTIPLEX - Foundational Research on MULTIlevel comPLEX networks and systems (EC-FP7-317532)
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.
CitationBudroni, M., Baronchelli, A., Pastor-Satorras, R. Scale-free networks emerging from multifractal time series. "Physical review E", 16 Maig 2017, vol. 95, núm. 5, p. 1-8.