Estimation of the Radial Tungsten Concentration Profiles from Soft X-ray Measurements at WEST with Bayesian Integrated Data Analysis

The accumulation of heavy impurities like tungsten in the plasma core of fusion devices can cause significant radiative power losses or even lead to a disruption. It is therefore crucial to monitor the tungsten impurity concentration. In this paper, we follow the integrated data analysis approach using Bayesian probability theory to jointly estimate tungsten concentration profiles and kinetic profiles from soft X-ray, interferometry and electron cyclotron emission measurements. As the full Bayesian inference using Markov chain Monte Carlo sampling is time-consuming, we also discuss emulation of the inference process using neural networks, with a view to real-time implementation.