Using Bayesian analysis and Gaussian processes to infer electron temperature and density profiles on the Mega-Ampere Spherical Tokamak experiment

A unified, Bayesian inference of midplane electron temperature and density profiles using both Thomson 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 l...

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Bibliographic Details
Published in:Review of scientific instruments 2013-06, Vol.84 (6), p.063505-063505
Main Authors: von Nessi, G T, Hole, M J
Format: Article
Language:English
Subjects:
70 PLASMA PHYSICS AND FUSION TECHNOLOGY
CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS
DENSITY
ELECTRON TEMPERATURE
GAUSSIAN PROCESSES
INDIUM FLUORIDES
ION TEMPERATURE
NUMERICAL ANALYSIS
PLASMA DENSITY
PLASMA DIAGNOSTICS
QUADRATURES
SPHERICAL CONFIGURATION
THOMSON SCATTERING
TOKAMAK DEVICES
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Description
Summary:A unified, Bayesian inference of midplane electron temperature and density profiles using both Thomson 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 application of the method to data from the high resolution TS system on the Mega-Ampere Spherical Tokamak, along with a comparison to profiles coming from the standard analysis carried out on that system.
ISSN:0034-6748
1089-7623
DOI:10.1063/1.4811378