Currents in complex polymers: an example of superstatistics for short time series

TL;DR

This paper demonstrates how superstatistical methods can effectively model transient current fluctuations in complex polymers, capturing fat-tailed distributions and local Gaussian behavior in short time series.

Contribution

It introduces a superstatistical approach to analyze short experimental time series of current in polymers, showing its applicability beyond traditional methods.

Findings

Current approximated by local Gaussian processes with fluctuating variance

Marginal density exhibits fat tails well modeled by superstatistics

Techniques applicable to other short time series

Abstract

We apply superstatistical techniques to an experimental time series of measured transient current through a thin Aluminium-PMMA-Aluminium film. We show that in good approximation the current can be approximated by local Gaussian processes with fluctuating variance. The marginal density exhibits `fat tails' and is well modelled by a superstatistical model. Our techniques can be generally applied to other short time series as well.