Maximum likelihood algorithm for approximation of local fluctuational fluxes at the plasma periphery by fractional stable distributions

TL;DR

This paper introduces a maximum likelihood algorithm to estimate fractional stable distribution parameters for plasma edge fluxes, demonstrating good agreement with experimental data and supporting the CTRW model for plasma turbulence.

Contribution

A novel maximum likelihood algorithm for estimating fractional stable distribution parameters from plasma flux data is developed and validated.

Findings

Power-law decay of flux amplitude increments.

Good fit between experimental and theoretical distributions.

Supports CTRW model for plasma turbulence processes.

Abstract

Statistical properties of a local fluctuational fluxes measured at the plasma edge are investigated in the work. It's shown that the amplitudes increments of the local fluctuational fluxes decrease by power law. For approximation of experimental PDFs the fractional stable distributions are used. The new algorithm of statistical estimation of the FSD parameters based on maximum likelihood method is described. By using of the algorithm the parameters of FSD are estimated by using experimental samples. It is shown good agreement between experimental and theoretical distributions. On the basis of this results the conclusion is made about applicability of the CTRW model for description of a processes underlying of the plasma turbulence.