Scale-dependent non-Gaussianities in the WMAP data as identified by using surrogates and scaling indices

Understand

We present a model-independent investigation of the WMAP data with respect to scale- dependent non-Gaussianities (NGs) by employing the method of constrained randomization.

• For generating so-called surrogate maps a shuffling scheme is applied to the Fourier phases of the original data, which allows to test for the presence of higher order correlations (HOCs) on well-defined scales.
• Using scaling indices as test statistics we find highly significant signatures for non-Gaussianities when considering all scales.
• We test for NGs in the bands l = [2,20], l = [20,60], l = [60,120] and l = [120,300].