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

Title
Experimentally testing the dependence of momentum transport on second derivatives using Gaussian process regression
Author
이정표
Keywords
momentum transport; Bayesian analysis; Gaussian processes; profile fitting
Issue Date
2017-09
Publisher
IOP PUBLISHING LTD
Citation
NUCLEAR FUSION, v. 57, no. 12, Article no. 126013
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 n(e) and T-e 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.
URI
https://iopscience.iop.org/article/10.1088/1741-4326/aa8387https://repository.hanyang.ac.kr/handle/20.500.11754/115540
ISSN
0029-5515; 1741-4326
DOI
10.1088/1741-4326/aa8387
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > NUCLEAR ENGINEERING(원자력공학과) > Articles
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