Inference of experimental radial impurity transport on Alcator C-Mod: Bayesian parameter estimation and model selection

@article{Sciortino2020InferenceOE,
  title={Inference of experimental radial impurity transport on Alcator C-Mod: Bayesian parameter estimation and model selection},
  author={Francesco Sciortino and N. T. Howard and Earl S. Marmar and Tom{\'a}{\vs} Odstr{\vc}il and N. M. Cao and R.Dux and Youssef M. Marzouk and Lucio M. Milanese and Matthew L. Reinke and John E Rice and P.Rodriguez-Fernandez},
  journal={Nuclear Fusion},
  year={2020},
  volume={60}
}
We present a fully Bayesian approach for the inference of radial profiles of impurity transport coefficients and compare its results to neoclassical, gyrofluid and gyrokinetic modeling. Using nested sampling, the Bayesian impurity transport inference (BITE) framework can handle complex parameter spaces with multiple possible solutions, offering great advantages in interpretative power and reliability with respect to previously demonstrated methods. BITE employs a forward model based on the… 

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