Plasma and Fusion Research

Volume 15, 1301001 (2020)

Letters

Sparsity-Promoting Dynamic Mode Decomposition of Plasma Turbulence
Akira KUSABA, Tetsuji KUBOYAMA and Shigeru INAGAKI1)
Computer Centre, Gakushuin University, 1-5-1 Mejiro, Toshima-ku 171-8588, Japan
1)
Research Institute for Applied Mechanics, Kyushu University, 6-1 Kasuga-koen, Kasuga 816-8580, Japan
(Received 3 October 2019 / Accepted 27 November 2019 / Published 6 January 2020)

Abstract

A data-driven approach called sparsity-promoting dynamic mode decomposition (SP-DMD) is applied to the plasma turbulence signals obtained with an azimuthal probe array. The spatiotemporal turbulence can be reasonably decomposed into seven modes which capture the azimuthal bunching of the turbulence. A superiority of the DMD analysis to the conventional stationary analysis is demonstrated.

Keywords

data-driven modelling, spatiotemporal data, dynamic mode decomposition

DOI: 10.1585/pfr.15.1301001

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