Recent developments in Bayesian inference of tokamak plasma equilibria and high-dimensional stochastic quadratures

We present recent results and technical breakthroughs for the Bayesian inference of tokamak equilibria using force-balance as a prior constraint. Issues surrounding model parameter representation and posterior analysis are discussed and addressed. These points motivate the recent advancements embodi...

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Bibliographic Details
Published in:Plasma physics and controlled fusion 2014-11, Vol.56 (11), p.114011-13
Main Authors: von Nessi, G T, Hole, M J
Format: Article
Language:English
Subjects:
Bayesian
Bayesian analysis
Computer programs
Computer simulation
Controlled fusion
equilibrium
Inference
Masts
plasma
quadrature
Tokamak devices
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Summary:We present recent results and technical breakthroughs for the Bayesian inference of tokamak equilibria using force-balance as a prior constraint. Issues surrounding model parameter representation and posterior analysis are discussed and addressed. These points motivate the recent advancements embodied in the Bayesian Equilibrium Analysis and Simulation Tool (BEAST) software being presently utilized to study equilibria on the Mega-Ampere Spherical Tokamak (MAST) experiment in the UK (von Nessi et al 2012 J. Phys. A 46 185501). State-of-the-art results of using BEAST to study MAST equilibria are reviewed, with recent code advancements being systematically presented though out the manuscript.
ISSN:0741-3335
1361-6587
DOI:10.1088/0741-3335/56/11/114011