Main results of the first experimental campaign in the stellarator W7-X

A summary of the first operational phase (OP1.1) at the stellarator W7-X is given. The operational setup of heating and diagnostics as well the results of experiments are briefly described. Plasma parameters and confinement are better than expected: Te > 8 keV and Ti > 2 keV at ne ≈ 3×1019 m-3 yielding β0 ≈ 2.5 %. The results for ECR heating with X2-mode as well the ECCD are in good agreement with the theory predictions. The heating scenario with the O2-mode alone was successfully first time performed. Stellarator specific regime of core “electron root” confinement was obtained

Bayesian modelling of multiple plasma diagnostics at Wendelstein 7-X

Inference of electron density and temperature has been performed using multiple, diverse sets of plasma diagnostic data at Wendelstein 7-X. Predictive models for the interferometer, Thomson scattering and helium beam emission spectroscopy (He-BES) systems have been developed within the Minerva framework and integrated into a unified model. Electron density and temperature profiles are modelled using Gaussian processes. Calibration factors for the Thomson scattering system and predictive uncertainties are considered as additional unknown parameters. The joint posterior probability distribution for the electron density and temperature profiles as well as Gaussian process hyperparameters and model parameters is explored through a Markov chain Monte Carlo algorithm. Samples from this distribution are numerically marginalised over the hyperparameters and model parameters to yield marginal posterior distributions for the electron density and temperature profiles. The profile inferences incorporate various data combinations from the interferometer and Thomson scattering as well as constraints at the limiter/divertor positions through virtual observations or edge data from He-BES. Additionally, the integration of x-ray imaging crystal spectrometer data into the model for ion temperature profiles is presented. All profiles presented in this study are inferred with optimally selected hyperparameters and model parameters by exploring the joint posterior distribution, inherently applying Bayesian Occam’s razor