We present a Gaussianity analysis of the Wilkinson Microwave Anisotropy Probe (WMAP) 5-yr cosmic microwave background (CMB) temperature anisotropy data maps. We use several third-order estimators based on the spherical Mexican hat wavelet. We impose constraints on the local non-linear coupling parameter f(nl) using well-motivated non-Gaussian simulations. We analyse the WMAP maps at resolution of 6.9 arcmin for the Q, V, and W frequency bands. We use the KQ75 mask recommended by the WMAP team which masks out 28 per cent of the sky. The wavelet coefficients are evaluated at 10 different scales from 6.9 to 150 arcmin. With these coefficients, we compute the third order estimators which are used to perform a χ2 analysis. The χ2 statistic is used to test the Gaussianity of the WMAP data as well as to constrain the f(nl) parameter. Our results indicate that the WMAP data are compatible with the Gaussian simulations, and the f(nl) parameter is constrained to −8 < f(nl) < +111 at 95 per cent confidence level (CL) for the combined V+W map. This value has been corrected for the presence of undetected point sources, which add a positive contribution of Δf(nl) = 3 ± 5 in the V+W map. Our results are very similar to those obtained by the WMAP team using the bispectrum.

The authors acknowledge partial financial support from the Spanish Ministerio de Ciencia e Innovación project AYA2007-68058-C03-02. A. C. thanks the Spanish Ministerio de Ciencia e Innovación for a pre-doctoral fellowship. AC thanks the Astronomy Centre at the University of Sussex for their hospitality during a research stay in 2008. SM thanks ASI contract I/016/07/0 ‘COFIS’ and ASI contract Planck LFI activity of Phase E2 for partial financial support. The authors acknowledge the computer resources, technical expertise and assistance provided by the Spanish Supercomputing Network (RES) node at Universidad de Cantabria. We acknowledge the use of LAMBDA support for it is provided by the NASA Office of Space Science. The HEALPIX package was used throughout the data analysis (Górski et al. 2005).

8 pages, 5 figures.-- ArXiv pre-print available at: http://arxiv.org/abs/0807.0231

Peer reviewed