Sparse Representation of Signals: From Astrophysics to Real-time Data Analysis for Fusion Plasmas and System Optimization Analysis for ITER

Efficient, real-time and unsupervised data analysis is one of the key elements for achieving scientific success in complex engineering and physical systems, of which two examples are the JET and ITER tokamaks. There is a wealth of signal processing techniques that are being applied to post-pulse and realtime data analysis in such complex systems, and here we wish to present some examples of the synergies that can be exploited when combining ideas and methods from different fields, such as astronomy and astrophysics and thermonuclear fusion plasmas. One problem which is common to these subjects is the determination of pulsation modes from irregularly sampled time-series. We have used recent techniques of signal processing in astronomy and astrophysics, based on the Sparse Representations of Signals, to solve current questions arising in thermonuclear fusion plasmas. Two examples are the detection of magneto-hydrodynamic instabilities, which is now performed routinely in JET in real-time on a sub-millisecond timescale, and the studies leading to the optimization of the magnetic diagnostic system in ITER. These questions have been solved formulating them as inverse problems, despite the fact that these applicative frameworks are extremely different from the classical use of Sparse Representations, on both the theoretical and computational points of view. Requirements, prospects and ideas for the signal processing and real-time data analysis applications of this method to routine operation of ITER will also be discussed.
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