Non-Gaussianity in the Very Small Array CMB maps with Smooth-Goodness-of-fit tests

ABSTRACT We have used the Rayner & Best (1989) smooth tests of goodness-of-fit to studythe Gaussianity of the Very Small Array (VSA) data. These tests are designed to besensitive to the presence of ‘smooth’ deviations from a given distribution, and areapplied to the data transformed into normalised signal-to-noise eigenmodes. In a pre-vious work, they have been already adapted and applied to simulated observations ofinterferometric experiments. In this paper, we extend the practical implementation ofthe method to deal with mosaiced observations, by introducing the Arnoldi algorithm.This method permits us to solve large eigenvalue problems with low computationalcost.Out of the 41 published VSA individual pointings dedicated to cosmological(CMB) observations, 37 are found to be consistent with Gaussianity, whereas fourpointings show deviations from Gaussianity. In two of them, these deviations can beexplained as residual systematic effects of a few visibility points which, when corrected,have a negligible impact on the angular power spectrum. The non-Gaussianity foundin the other two (adjacent) pointings seems to be associated to a local deviation ofthe power spectrum of these fields with respect to the common power spectrum of thecomplete data set, at angular scales of the third acoustic peak (l = 700 − 900). Noevidence of residual systematics is found in this case, and unsubstracted point sourcesare not a plausible explanation either. If those visibilities are removed, the differencesof the new power spectrum with respect to the published one only affect three bins.A cosmological analysis based on this new VSA power spectrum alone shows no dif-ferences in the parameter constraints with respect to our published results, except forthe physical baryon density, which decreases by 10 percent.Finally, the method has been also used to analyse the VSA observations in theCorona Borealis supercluster region. Our method finds a clear deviation (99.82%) withrespect to Gaussianity in the second-order moment of the distribution, and which cannotbe explainedassystematiceffects.A detailed studyshowsthatthe non-Gaussianityis produced in scales of l ≈ 500, and that this deviation is intrinsic to the data (inthe sense that can not be explained in terms of a Gaussian field with a differentpower spectrum). This result is consistent with the Gaussianity studies in the CoronaBorealis data presented in G´enova-Santoset al. (2005), which show a strong decrementwhich cannot be explained as primordial CMB.