Craciunescu Teddy, Murari Andrea, Lerche Ernesto, Gelfusa Michela
EUROfusion Consortium, JET, Culham Science Centre, Abingdon OX14 3DB, UK.
National Institute for Laser, Plasma and Radiation Physics, 077126 Măgurele, Romania.
Entropy (Basel). 2020 Jul 16;22(7):775. doi: 10.3390/e22070775.
Advanced time series analysis and causality detection techniques have been successfully applied to the assessment of synchronization experiments in tokamaks, such as Edge Localized Modes (ELMs) and sawtooth pacing. Lag synchronization is a typical strategy for fusion plasma instability control by pace-making techniques. The major difficulty, in evaluating the efficiency of the pacing methods, is the coexistence of the causal effects with the periodic or quasi-periodic nature of the plasma instabilities. In the present work, a set of methods based on the image representation of time series, are investigated as tools for evaluating the efficiency of the pace-making techniques. The main options rely on the Gramian Angular Field (GAF), the Markov Transition Field (MTF), previously used for time series classification, and the Chaos Game Representation (CGR), employed for the visualization of large collections of long time series. The paper proposes an original variation of the Markov Transition Matrix, defined for a couple of time series. Additionally, a recently proposed method, based on the mapping of time series as cross-visibility networks and their representation as images, is included in this study. The performances of the method are evaluated on synthetic data and applied to JET measurements.
先进的时间序列分析和因果关系检测技术已成功应用于托卡马克同步实验的评估，如边界局域模（ELMs）和锯齿波调制。滞后同步是通过调制技术控制聚变等离子体不稳定性的一种典型策略。评估调制方法效率的主要困难在于因果效应与等离子体不稳定性的周期性或准周期性共存。在本工作中，研究了一组基于时间序列图像表示的方法，作为评估调制技术效率的工具。主要选项依赖于格拉姆角场（GAF）、先前用于时间序列分类的马尔可夫转移场（MTF）以及用于可视化大量长时间序列集合的混沌博弈表示（CGR）。本文提出了一种为一对时间序列定义的马尔可夫转移矩阵的原始变体。此外，本研究还纳入了一种最近提出的方法，该方法基于将时间序列映射为交叉可见性网络并将其表示为图像。该方法的性能在合成数据上进行了评估，并应用于JET测量。
