Stretched exponentials from superstatistics

TL;DR

This paper investigates superstatistics with chi^2-distributed powers of inverse temperature, revealing conditions for power law and stretched exponential distributions, with applications in turbulence and granular media.

Contribution

It introduces and analyzes a novel class of superstatistics based on powers of inverse temperature, expanding understanding of fat-tailed distributions.

Findings

eta > 0 yields power law distributions

eta < 0 leads to stretched exponential distributions

Special cases include Tsallis statistics and exponential of square root energy

Abstract

Distributions exhibiting fat tails occur frequently in many different areas of science. A dynamical reason for fat tails can be a so-called superstatistics, where one has a superposition of local Gaussians whose variance fluctuates on a rather large spatio-temporal scale. After briefly reviewing this concept, we explore in more detail a class of superstatistics that hasn't been subject of many investigations so far, namely superstatistics for which a suitable power beta^eta of the local inverse temperature beta is chi^2-distributed. We show that eta >0 leads to power law distributions, while eta <0 leads to stretched exponentials. The special case eta=1 corresponds to Tsallis statistics and the special case eta=-1 to exponential statistics of the square root of energy. Possible applications for granular media and hydrodynamic turbulence are discussed.