Using wavelets to characterize turbulence in magnetized plasmas
LPMI-UMR 7040 du CNRS, Université Henri Poincaré, France,
and Ernst-Moritz-Arndt Universität Greifswald, Germany
The understanding of turbulence in magnetized plasmas and its role in cross-field transport is still very incomplete. Because intermittency and non linearity are two fundamental properties of turbulence, the standard Fourier methods are not well-suited to its analysis. We shall show that wavelets techniques can offer a very useful alternative. After a presentation of the basic principles of the wavelet decomposition, and a discussion of the various available transforms, i.e. continuous vs discrete, we shall focus on practical application examples. In particular we shall show how wavelet analysis can be useful to characterize self-affinity properties of a data set, which is of great interest not only in plasma turbulence but also in many complex systems. The results obtained from experimental data will be discussed and a comparison with those of the so-called R/S analysis will be given.