Plasma and Fusion Research

Volume 14, 1301157 (2019)


Reconstruction of Time Series Observed in Linear Magnetized Plasma PANTA via a Machine Learning Algorithm
Yasuhiro NARIYUKI, Makoto SASAKI1), Tohru HADA2) and Shigeru INAGAKI1)
Faculty of Human Development, University of Toyama, 3190 Gofuku, Toyama City, Toyama 930-8555, Japan
Research Institute for Applied Mechanics, Kyushu University, 6-1 Kasugakoen, Kasuga City, Fukuoka 816-8580, Japan
Faculty of Engineering Sciences, Kyushu University, 6-1 Kasugakoen, Kasuga City, Fukuoka 816-8580, Japan
(Received 24 April 2019 / Accepted 2 August 2019 / Published 9 October 2019)


Reconstruction of turbulence time series in a statistically stationary state is discussed by using a machine learning algorithm. We use data obtained by Langmuir probes in the Plasma Assembly for Nonlinear Turbulence Analysis (PANTA). It is shown that even if the distance between two probes is not adequate to resolve the turbulence, the nonlinear regression via the machine learning can give reconstruction better than those by the linear regression and the linear interpolation. Wave forms and frequency spectra show that drift waves are well reconstructed by the machine learning.


drift wave, linear magnetized plasma, machine learning, turbulence, coarse-grained model

DOI: 10.1585/pfr.14.1301157


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