Statistically robust linear and nonlinear wavelet analysis applied to plasma edge turbulence

The analysis of turbulence requires adequate analysis tools. In particular, two general properties of turbulence make the application of standard analysis tools (spectral analysis) difficult: (1) intermittency, which causes the characteristics of turbulence to change on a relatively short time scale, implies that analysis tools must not integrate over time scales longer than the intermittent time scale; (2) nonlinearity, a basic property of all numerical models of chaos and turbulence, requires specially adapted tools for its proper detection. In the present work, we develop a statistically stable formalism for the application of wavelet analysis techniques to the analysis of turbulence. We apply these techniques to the analysis of Langmuir probe data in the plasma edge region of the TJ-IU Torsatron. We draw some tentative conclusions about radial correlation lengths. Further, we analyze the L/H transition at the Continous Current Tokamak and reconstruct a radial profile of bicoherence in the plasma edge in the H-mode.