Using Bayesian analysis and Gaussian processes to infer electron temperature and density profiles on the Mega-Ampere Spherical Tokamak experiment
Abstract
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.
- Authors:
-
- Research School of Physical Sciences and Engineering, Australian National University, Canberra ACT 0200 (Australia)
- Publication Date:
- OSTI Identifier:
- 22118647
- Resource Type:
- Journal Article
- Journal Name:
- Review of Scientific Instruments
- Additional Journal Information:
- Journal Volume: 84; Journal Issue: 6; Other Information: (c) 2013 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0034-6748
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 70 PLASMA PHYSICS AND FUSION TECHNOLOGY; 71 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
Citation Formats
Nessi, G. T. von, and Hole, M. J. Using Bayesian analysis and Gaussian processes to infer electron temperature and density profiles on the Mega-Ampere Spherical Tokamak experiment. United States: N. p., 2013.
Web. doi:10.1063/1.4811378.
Nessi, G. T. von, & Hole, M. J. Using Bayesian analysis and Gaussian processes to infer electron temperature and density profiles on the Mega-Ampere Spherical Tokamak experiment. United States. https://doi.org/10.1063/1.4811378
Nessi, G. T. von, and Hole, M. J. 2013.
"Using Bayesian analysis and Gaussian processes to infer electron temperature and density profiles on the Mega-Ampere Spherical Tokamak experiment". United States. https://doi.org/10.1063/1.4811378.
@article{osti_22118647,
title = {Using Bayesian analysis and Gaussian processes to infer electron temperature and density profiles on the Mega-Ampere Spherical Tokamak experiment},
author = {Nessi, G. T. von and Hole, M. J.},
abstractNote = {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.},
doi = {10.1063/1.4811378},
url = {https://www.osti.gov/biblio/22118647},
journal = {Review of Scientific Instruments},
issn = {0034-6748},
number = 6,
volume = 84,
place = {United States},
year = {Sat Jun 15 00:00:00 EDT 2013},
month = {Sat Jun 15 00:00:00 EDT 2013}
}
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