Methods for optimizing and assessing diagnostic capability, demonstrated for collective Thomson scattering (invited)

Commonly diagnostic systems are sensitive to a wide range of parameters, only a subset of which are parameters of interest. Optimal analysis and assessment of diagnostic capability must take account of the sensitivity to the remaining nuisance parameters which may not be accurately known. New least squares type methods of inference in the presence of uncertain nuisance parameters have been developed, along with methods for assessing diagnostic capability and identifying critical nuisance parameter uncertainties. These methods are of a general nature and suitable for complex and computationally demanding forward models. They are demonstrated by application to collective Thomson scattering for fast ion diagnosis in fusion plasmas.