Bayesian modeling of collisional-radiative models applicable to thermal helium beam plasma diagnostics

Abstract

Thermal helium beam diagnostics using the line ratio spectroscopy method are widely used to infer temperature and density in fusion-relevant edge plasmas. These diagnostics consist of an observational system which measures emitted line radiation from either intrinsic or injected helium plasma impurities. These spectral features are then compared to the output of a collisional-radiative model to infer plasma parameters (Te, ne) from the observed helium radiation. In order to investigate the systematic uncertainties of such a diagnostic, we present the results of a Bayesian treatment of a helium collisional-radiative model (Schmitz et al., 2008) using synthetic data modeled after an existing system on the plasma experiment Wendelstein 7-X (Barbui et al. 2016). From this study, we present a new method for comprehensively combining measurement uncertainties with underlying atomic rate parameter uncertainties in the inference of plasma parameters. Finally, we also demonstrate the utility of this Bayesian approach in targeting sensitivities within the model, allowing determination of high-priority atomic data for future refinement and comparison between differing atomic models.

Keywords

• Bayesian inference
• Collisional-radiative model
• Helium spectroscopy
• Plasma diagnostics