Using Bayesian Analysis and Gaussian Processes to Infer Electron Temperature and Density Profiles on the MAST Experiment
A unified, Bayesian inference of midplane electron temperature and density profiles using both Thompson scattering (TS) and interferometric data is presented. Beyond the Bayesian nature of the analysis, novel features of the inference are the use of a Gaussian process prior to infer a mollification length-scale of inferred profiles and the use of Gauss-Laguerre quadratures to directly calculate the depolarisation term associated with the TS forward model. Results are presented from an...[Show more]
|Collections||ANU Research Publications|
|Source:||Review of Scientific Instruments|
|01_von Nessi_Using_Bayesian_Analysis_and_2013.pdf||Published Version||167.53 kB||Adobe PDF|
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