Bayesian inference of ion velocity distribution function from laser-induced fluorescence spectra

TL;DR

This paper introduces a Bayesian inference method to determine the ion velocity distribution function from laser-induced fluorescence spectra in plasmas, enabling analysis of spatial inhomogeneity and non-equilibrium states.

Contribution

It presents a novel Bayesian approach for selecting the appropriate velocity distribution function form from LIF spectra in inhomogeneous plasmas.

Findings

Successfully applied Bayesian inference to local LIF spectra in magnetized plasma.

Enabled evaluation of spatial inhomogeneity of velocity distributions.

Method is broadly applicable to plasmas and fluids in various states.

Abstract

The velocity distribution function is a statistical description that connects particle kinetics and macroscopic parameters in many-body systems. Laser-induced fluorescence (LIF) spectroscopy is utilized to measure the local velocity distribution function in spatially inhomogeneous plasmas. However, the analytic form of such a function for the system of interest is not always clear under the intricate factors in non-equilibrium states. Here, we propose a novel approach to select the valid form of the velocity distribution function based on Bayesian statistics. We formulate the Bayesian inference of ion velocity distribution function and apply it to LIF spectra locally observed at several positions in a linear magnetized plasma. We demonstrate evaluating the spatial inhomogeneity by verifying each analytic form of the local velocity distribution function. Our approach is widely applicable to experimentally establish the velocity distribution function in plasmas and fluids, including gases and liquids.