Bayesian modelling of the emission spectrum of the JET Li-BES system

TL;DR

This paper introduces a Bayesian model for analyzing the emission spectrum of the JET Li-BES system, enabling accurate inference of lithium line intensity and uncertainties directly from spectral data.

Contribution

It presents a novel Bayesian approach using Gaussian processes to model instrumental effects and infer line intensities without separate background subtraction.

Findings

Accurate inference of Li line intensity and uncertainties.

Elimination of separate background subtraction step.

Analytical solution for line intensity using Bayesian linear inversion.

Abstract

A Bayesian model of the emission spectrum of the JET lithium beam has been developed to infer the intensity of the Li I (2p-2s) line radiation and associated uncertainties. The detected spectrum for each channel of the lithium beam emission spectroscopy (Li-BES) system is here modelled by a single Li line modified by an instrumental function, Bremsstrahlung background, instrumental offset, and interference filter curve. Both the instrumental function and the interference filter curve are modelled with non-parametric Gaussian processes. All free parameters of the model, the intensities of the Li line, Bremsstrahlung background, and instrumental offset, are inferred using Bayesian probability theory with a Gaussian likelihood for photon statistics and electronic background noise. The prior distributions of the free parameters are chosen as Gaussians. Given these assumptions, the intensity of the Li line and corresponding uncertainties are analytically available using a Bayesian linear inversion technique. The proposed approach makes it possible to extract the intensity of Li line without doing a separate background subtraction through modulation of the Li beam.