Recovering non-Maxwellian particle velocity distribution functions from collective Thomson-scattered spectra

TL;DR

This paper introduces new open-source tools for analyzing collective Thomson scattering spectra to accurately recover non-Maxwellian particle velocity distribution functions in plasmas, improving parameter extraction over traditional methods.

Contribution

The authors develop and demonstrate numerical tools that model spectra from arbitrary VDFs, enabling more precise plasma parameter extraction in non-Maxwellian conditions.

Findings

Tools outperform standard algorithms on synthetic spectra

Uncertainties and parameter correlations are quantified

Non-Maxwellian deviations significantly impact spectral analysis

Abstract

Collective optical Thomson scattering (TS) is a diagnostic commonly used to characterize plasma parameters. These parameters are typically extracted by a fitting algorithm that minimizes the difference between a measured scattered spectrum and an analytic spectrum calculated from the velocity distribution function (VDF) of the plasma. However, most existing TS analysis algorithms assume the VDFs are Maxwellian, and applying an algorithm which makes this assumption does not accurately extract the plasma parameters of a non-Maxwellian plasma due to the effect of non-Maxwellian deviations on the TS spectra. We present new open-source numerical tools for forward modeling analytic spectra from arbitrary VDFs, and show that these tools are able to more accurately extract plasma parameters from synthetic TS spectra generated by non-Maxwellian VDFs compared to standard TS algorithms. Estimated posterior probability distributions of fits to synthetic spectra for a variety of example non-Maxwellian VDFs are used to determine uncertainties in the extracted plasma parameters, and show that correlations between parameters can significantly affect the accuracy of fits in plasmas with non-Maxwellian VDFs.