Statistical properties of visibility graph of energy dissipation rates in three-dimensional fully developed turbulence

By Chuang Liu, Wei‐Xing Zhou, W. Yuan. 2009

140 citations recorded by the source corpus.

We study the statistical properties of complex networks constructed from time series of energy dissipation rates in three-dimensional fully developed turbulence using the visibility algorithm. The degree distribution is found to have a power-law tail with the tail exponent α=3.0. The exponential relation between the number of the boxes NB and the box size lB based on the edge-covering box-counting method illustrates that the network is not self-similar, which is also confirmed by the hub-hub attraction according to the visibility algorithm. In addition, it is found that the skeleton of the visibility network exhibits excellent allometric scaling with the scaling exponent η=1.163±0.005.

Subfields: Computer Vision and Pattern Recognition, Economics and Econometrics, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/699804a6415b133b2e12d148e20a4dbfef4f967e

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Citations in the corpus

Wavelet Multiresolution Complex Network for Analyzing Multivariate Nonlinear Time Series (2017, background): “…al., 2011; Donges et al., 2012; Gao et al., 2015; 2016; 2017; Shen et al., 2014; Jachan et al., 2009; Nakamura et al., 2016], including turbulence [Liu et al., 2010; Scarsoglio et al., 2016], brain network [Zhang et al., 2016], traffic network [Tang et al., 2016], climate network [Donges et al.,…”
The role of fluctuating modes of autocorrelation in crude oil prices (2014, methodology): “Thus far, the visibility algorithm has been diversely used to investigate stock market indices [13], foreign exchange rates [14], quarterly macroeconomic series [15], and energy dissipation rates [16].”
Complex network approaches to nonlinear time series analysis (2019, background): “Very similar as RN approaches, (H)VGs have been applied to experimental time series from various fields, for instance, energy dissipation rates in fully developed turbulence [273,407,408], financial data [62,314,409–411], physiological time series [61,224,275,278,412,413], seizure detections by EEG ”