Topological Data Analysis and its Application to Drift Wave Turbulence

Anomalous transport is a critical phenomenon in plasmas and predicting its behavior will aid in the design of future fusion devices. Anomalous transport is the result of drift-wave turbulence driven by various gradients perpendicular to the magnetic field. Here we use Topological Data Analysis (TDA) to study the Hasegawa Wakatani (H-W) model, which captures key features of drift-wave turbulence. TDA has been made possible by recent advances in computing and theoretical mathematics and computes the topology of arbitrary data. The goal is to identify topological structures in the H-W model and link them to the physical mechanisms behind drift-wave turbulence. Previous work applying TDA to classical fluid mechanics such as Kolmogorov Flow and Rayleigh-Bénard Convection has been promising. The authors were able to identify periodicity in the flow patterns and classify all states of the systems uniquely using TDA metrics. In this poster we will apply similar techniques to simulations of the H-W model. We look to identify predictors of change in the turbulent transport characteristics and connect these to the traditional descriptions of turbulent flow.