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Asahi, Yuichi; Fujii, Keisuke*
Purazuma, Kaku Yugo Gakkai-Shi, 97(2), p.86 - 92, 2021/02
The 5D gyrokinetic simulation data has been analyzed with the data-driven analysis methods. By defining an entropy-like quantity with singular values, we have quantitatively evaluated the randomness of the plasma state. We found that the randomness of plasma increases after the avalanche like transport and then gradually decrease. Since the decrease of the randomness is expected to be relevant to the phase space structure formation, we have developed a method to extract the phase space structures from the time series of 5D data. The relationship between the avalanche-like transport and phase space structures is discussed based on the contribution of each principal component to the energy transport.
Asahi, Yuichi; Fujii, Keisuke*; Heim, D. M.*; Maeyama, Shinya*; Garbet, X.*; Grandgirard, V.*; Sarazin, Y.*; Dif-Pradalier, G.*; Idomura, Yasuhiro; Yagi, Masatoshi*
Physics of Plasmas, 28(1), p.012304_1 - 012304_21, 2021/01
Times Cited Count：4 Percentile：40.28(Physics, Fluids & Plasmas)This article demonstrates a data compression technique for the time series of five dimensional distribution function data based on Principal Component Analysis (PCA). Phase space bases and corresponding coefficients are constructed by PCA in order to reduce the data size and the dimensionality. It is shown that about 83% of the variance of the original five dimensional distribution can be expressed with 64 components. This leads to the compression of the degrees of freedom from 
to 
. One of the important findings - resulting from the detailed analysis of the contribution of each principal component to the energy flux - deals with avalanche events, which are found to be mostly driven by coherent structures in the phase space, indicating the key role of resonant particles.
