A high-significance detection of non-Gaussianity in the WMAP 3-year data using directional spherical wavelets

Abstract

We repeat the directional spherical real Morlet wavelet analysis used to detect non-Gaussianity in the WMAP 1-year data (McEwen et al. 2005a), on the WMAP 3-year data. The non-Gaussian signal previously detected is indeed present in the 3-year data, although the significance of the detection is reduced. Using our most conservative method for constructing significance measures, we find the significance of the detection of non-Gaussianity drops from 98.3+/-0.4% to 94.9+/-0.7%; the significance drops from 99.3+/-0.3% to 97.2+/-0.5% using a method based on the ${\chi }^2$ statistic. The wavelet analysis allows us to localise most likely sources of non-Gaussianity on the sky. We detect very similar localised regions in the WMAP 1-year and 3-year data, although the regions extracted appear more pronounced in the 3-year data. When all localised regions are excluded from the analysis the 3-year data is consistent with Gaussianity.

5 pages, 5 figures; typographical changes to match version accepted by MNRAS

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