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  4. Experimentally testing the dependence of momentum transport on second derivatives using Gaussian process regression

Experimentally testing the dependence of momentum transport on second derivatives using Gaussian process regression

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Author(s)
Chilenski, Mark Alan
•
Greenwald, Martin J
•
Hubbard, Amanda E
•
Hughes Jr, Jerry
•
Lee, J. P.
•
Marzouk, Youssef M
•
Rice, John E
•
White, Anne E.
Date Issued
September 2017
Journal
Nuclear Fusion
Publisher
IOP Publishing
Citation
Chilenski, M.A. et al. “Experimentally Testing the Dependence of Momentum Transport on Second Derivatives Using Gaussian Process Regression.” Nuclear Fusion 57, 12 (September 2017): 126013 © 2017 IAEA, Vienna
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Author's final manuscript
Abstract
It remains an open question to explain the dramatic change in intrinsic rotation induced by slight changes in electron density (White et al 2013 Phys. Plasmas 20 056106). One proposed explanation is that momentum transport is sensitive to the second derivatives of the temperature and density profiles (Lee et al 2015 Plasma Phys. Control. Fusion 57 125006), but it is widely considered to be impossible to measure these higher derivatives. In this paper, we show that it is possible to estimate second derivatives of electron density and temperature using a nonparametric regression technique known as Gaussian process regression. This technique avoids over-constraining the fit by not assuming an explicit functional form for the fitted curve. The uncertainties, obtained rigorously using Markov chain Monte Carlo sampling, are small enough that it is reasonable to explore hypotheses which depend on second derivatives. It is found that the differences in the second derivatives of and between the peaked and hollow rotation cases are rather small, suggesting that changes in the second derivatives are not likely to explain the experimental results.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Massachusetts Institute of Technology. Plasma Science and Fusion Center
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
http://creativecommons.org/licenses/by-nc-sa/4.0/
Persistent DSpace Link
http://hdl.handle.net/1721.1/114540
DOI of Published Version
https://doi.org/10.1088/1741-4326/AA8387
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