[논문]Bayesian modelling of Thomson scattering and multichannel interferometer diagnostics using Gaussian processes

Kwak, Sehyun; Svensson, J.; Bozhenkov, S.; Flanagan, J.; Kempenaars, M.; Boboc, A.; Ghim, Y.-C.

doi:10.1088/1741-4326/ab686e

[해외논문] Bayesian modelling of Thomson scattering and multichannel interferometer diagnostics using Gaussian processes 원문보기

Nuclear fusion. Fusion nucléaire. &n.Illigat;&n.Arligat;derny&n.ibreve; sintez. Fusión nuclear, v.60 no.4, 2020년, pp.046009 -

Kwak, Sehyun (Department of Nuclear and Quantum Engineering, KAIST, Daejeon 34141, Korea, Republic of) , Svensson, J. (Max-Planck-Institut fü) , Bozhenkov, S. (r Plasmaphysik, 17491 Greifswald, Germany) , Flanagan, J. (Max-Planck-Institut fü) , Kempenaars, M. (r Plasmaphysik, 17491 Greifswald, Germany) , Boboc, A. (Culham Centre for Fusion Energy, Culham Science Centre, Abingdon, OX14 3DB, United Kingdom of Great Britain and Northern Ireland) , Ghim, Y.-C. (Culham Centre for Fusion Energy, Culham Science Centre, Abingdon, OX14 3DB, United Kingdom of Great Britain and Northern Ireland)

Abstract ▼ AI-Helper

Electron temperature and density profiles consistent with JET high resolution Thomson scattering (HRTS) and far infrared (FIR) interferometer data are inferred by a Bayesian joint model using Gaussian processes. Forward models predicting diagnostic data including instrument effects such as optics and electronics are developed independently for both diagnostic systems in the Minerva framework, and combined as one joint model. The full joint posterior distribution of the electron temperature and density profiles, the hyperparameters of the Gaussian processes and calibration factor is explored by Markov chain Monte Carlo (MCMC) sampling. The posterior distribution of the electron density (temperature) profile is obtained by marginalising all the possible combinations of the electron temperature (density) profile, the hyperparameters and calibration factor. Therefore, the method removes profile dependency on the hyperparameters completely in addition to eliminating often-used avoidable constraints such as monotonicity and parametrisation on the profiles. The posterior distribution of the calibration factor is also calculated explaining both the HRTS and the FIR interferometer data simultaneously. Thus, absolute electron density can be obtained from the HRTS without additional experiments measuring the calibration factor.

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