Abstract
Complex nonequilibrium systems are often effectively described by a “statistics of a statistics”, in short, a “superstatistics”. We describe how to proceed from a given experimental time series to a superstatistical description. We argue that many experimental data fall into three different universality classes: superstatistics (Tsallis statistics), inverse superstatistics, and log-normal superstatistics. We discuss how to extract the two relevant well separated superstatistical time scales and , the probability density of the superstatistical parameter , and the correlation function for from the experimental data. We illustrate our approach by applying it to velocity time series measured in turbulent Taylor-Couette flow, which is well described by log-normal superstatistics and exhibits clear time scale separation.
2 More- Received 18 July 2005
DOI:https://doi.org/10.1103/PhysRevE.72.056133
©2005 American Physical Society