# Statistical description of turbulent transport for flux driven toroidal plasmas

## TL;DR

This paper introduces a new method using ARIMA models to analyze non-Gaussian turbulent transport in plasma simulations, revealing agreement between simulation data and analytical models.

## Contribution

It presents a novel application of ARIMA to separate noise and trends in turbulent transport data, enabling detailed PDF analysis in gyrokinetic simulations.

## Key findings

- Non-Gaussian tails of PDFs match analytical two-fluid model estimates.
- ARIMA effectively isolates oscillatory trends in turbulent transport data.
- Method enhances understanding of turbulent transport statistics.

## Abstract

A novel methodology to analyze non-Gaussian probability distribution functions (PDFs) of intermittent turbulent transport in global full-f gyrokinetic simulations is presented. In this work, the Auto-Regressive Integrated Moving Average (ARIMA) model is applied to time series data of intermittent turbulent heat transport to separate noise and oscillatory trends, allowing for the extraction of non-Gaussian features of the PDFs. It was shown that non-Gaussian tails of the PDFs from first principles based gyrokinetic simulations agree with an analytical estimation based on a two fluid model.