Application of transfer entropy to causality detection and synchronization experiments in tokamaks. (30th December 2015)

• Record Type: Journal Article
• Authors: Murari, A.; Peluso, E.; Gelfusa, M.; Garzotti, L.; Frigione, D.; Lungaroni, M.; Pisano, F.; Gaudio, P.
• Other Names: collab.
• Is Part Of: Nuclear fusion. Volume 56:Number 2(2016:Feb.)
• Publication Date: 2015-12-30
• Subjects: transfer entropy -- causality detection -- synchronization experiments -- ELM pacing -- disruption precursors; Nuclear fusion -- Periodicals; 621.48405
• DOI: 10.1088/0029-5515/56/2/026006
• Languages: English
• ISSNs: 0029-5515

Abstract

Abstract: Determination of causal-effect relationships can be a difficult task even in the analysis of time series. This is particularly true in the case of complex, nonlinear systems affected by significant levels of noise. Causality can be modelled as a flow of information between systems, allowing to better predict the behaviour of a phenomenon on the basis of the knowledge of the one causing it. Therefore, information theoretic tools, such as the transfer entropy, have been used in various disciplines to quantify the causal relationship between events. In this paper, Transfer Entropy is applied to determining the information relationship between various phenomena in Tokamaks. The proposed approach provides unique insight about information causality in difficult situations, such as the link between sawteeth and ELMs and ELM pacing experiments. The application to the determination of disruption causes, and therefore to the classification of disruption types, looks also very promising. The obtained results indicate that the proposed method can provide a quantitative and statistically sound criterion to address the causal-effect relationships in various difficult and ambiguous situations if the data is of sufficient quality.