Abstract
Here we present a new method that allows the determination of background neutral density profiles based on measurements from neutral particle analyzers (NPA). Bayesian optimization is used to obtain a reliable 5-parameter representation of the inferred profiles. The method has been benchmarked using forward modelling from FIDASIM against measured data. The systematic errors coming from assumptions made in the analysis were evaluated and they are lower than ≲5%. The new method has been tested using data from the ASDEX Upgrade tokamak. When using reconstructed neutral density profiles, good agreement is found between the measured NPA fluxes of neutralized fast ions with predictions based on TRANSP and FIDASIM. Moreover, a clear drop of neutral density is observed at the plasma boundary after edge localized mode (ELM) activity. As suggested by KN1D simulations, this drop is mainly due to an increase of scrape-off layer (SOL) ionization rate, resulting from higher SOL plasma densities and temperatures after the ELM crash. Moreover, the new method allows calculating the local plasma ionization source which will be important for future transport studies.
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