Distinguishing deterministic from stochastic processes in magnetospheric time series through the use of Jensen-Shannon measure of complexity.

Time series measured in space plasma environments are a mixture of signals with deterministic and stochastic dynamics. Detecting different dynamics in a signal is a topic of great importance from a theoretical and modelling perspective. For instance, if geomagnetic indices can be shown to be indistinguishable from deterministic chaotic time series, one might be able to model the associated magnetospheric dynamics in terms of less computationally cumbersome systems of equations. In this communication we will provide a basic introduction to concepts originating from Information Theory known as Permutation Entropy (PE) and Jensen-Shannon Complexity (JS). The combined used of these two methods allows us to determine whether time series in space plasma environments can be characterised as stochastic or chaotic processes. As a practical example relevant to space plasmas, we use PE and JS analysis on geomagnetic auroral indices. Our analysis indicates that structures with timescales ranging from a few minutes to 4 hours are indistinguishable from stochastic dynamics. Our results are therefore inconsistent with earlier studies postulating that geomagnetic current patterns could be modelled by low-dimensional dynamical systems with deterministic chaotic properties.