We adapt the smooth tests of goodness-of-fit developed by Rayner and Best to the study of the non-Gaussianity of interferometric observations of the cosmic microwave background (CMB). The interferometric measurements (visibilities) are transformed into signal-to-noise ratio eigenmodes, and then the method is applied directly in Fourier space. This transformation allows us to perform the analysis in different subsets of eigenmodes according to their signalto-noise ratio level. The method can also deal with non-uniform or incomplete coverage of the UV plane. We explore here two possibilities: we analyse either the real and imaginary parts of the complex visibilities (Gaussianly distributed under the Gaussianity hypothesis) or their phases (uniformly distributed under the Gaussianity hypothesis). The power of the method in discriminating between Gaussian and non-Gaussian distributions is studied by using several kinds of non-Gaussian simulations. On the one hand, we introduce a certain degree of non-Gaussianity directly into the Fourier space using the Edgeworth expansion, and afterwards the desired correlation is introduced. On the other hand, we consider interferometric observations of a map with topological defects (cosmic strings). To these previous non-Gaussian simulations we add different noise levels and quantify the required signal-to-noise ratio necessary to achieve a detection of these non-Gaussian features. Finally, we have also studied the ability of the method to constrain the so-called non-linear coupling constant f NL using χ 2 simulations. The whole method is illustrated here by application to simulated data from the Very Small Array interferometer.

Abstract. This paper is concerned with small angular scale experiments for the observation of cosmic microwave background anisotropies. In the absence of beam, the effects of partial coverage and pixelisation are disentangled and analyzed (using simulations). Then, appropriate maps involving the CMB signal plus the synchrotron and dust emissions from the Milky Way are simulated, and an asymmetric beam -which turns following different strategies -is used to smooth the simulated maps. An associated circular beam is defined to estimate the deviations in the angular power spectrum produced by beam asymmetry without rotation and, afterwards, the deviations due to beam rotation are calculated. For a certain large coverage, the deviations due to pure asymmetry and asymmetry plus rotation appear to be very systematic (very similar in each simulation). Possible applications of the main results of this paper to data analysis in large coverage experiments -as PLANCK -are outlined.

We have used the Rayner and Best smooth tests of goodness‐of‐fit to study the Gaussianity of the Very Small Array (VSA) data. These tests are designed to be sensitive to the presence of ‘smooth’ deviations from a given distribution, and are applied to the data transformed into normalized signal‐to‐noise eigenmodes. In a previous work, they have been already adapted and applied to simulated observations of interferometric experiments. In this paper, we extend the practical implementation of the method to deal with mosaiced observations, by introducing the Arnoldi algorithm. This method permits us to solve large eigenvalue problems with low computational cost. Out of the 41 published VSA individual pointings dedicated to cosmological [cosmic microwave background (CMB)] observations, 37 are found to be consistent with Gaussianity, whereas four pointings show deviations from Gaussianity. In two of them, these deviations can be explained as residual systematic effects of a few visibility points which, when corrected, have a negligible impact on the angular power spectrum. The non‐Gaussianity found in the other two (adjacent) pointings seems to be associated to a local deviation of the power spectrum of these fields with respect to the common power spectrum of the complete data set, at angular scales of the third acoustic peak (ℓ= 700–900). No evidence of residual systematics is found in this case, and unsubtracted point sources are not a plausible explanation either. If those visibilities are removed, the differences of 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 differences in the parameter constraints with respect to our published results, except for the physical baryon density, which decreases by 10 per cent. Finally, the method has been also used to analyse the VSA observations in the Corona Borealis supercluster region. Our method finds a clear deviation (99.82 per cent) with respect to Gaussianity in the second‐order moment of the distribution, and which cannot be explained as systematic effects. A detailed study shows that the non‐Gaussianity is produced in scales of ℓ≈ 500, and that this deviation is intrinsic to the data (in the sense that cannot be explained in terms of a Gaussian field with a different power spectrum). This result is consistent with the Gaussianity studies in the Corona Borealis data presented in Génova‐Santos et al. which show a strong decrement that cannot be explained as primordial CMB.

We review two powerful methods to test the Gaussianity of the cosmic microwave background (CMB): one based on the distribution of spherical wavelet coefficients and the other on smooth tests of goodness-of-fit. The spherical wavelet families proposed to analyse the CMB are the Haar and the Mexican Hat ones. The latter is preferred for detecting non-Gaussian homogeneous and isotropic primordial models containing some amount of skewness or kurtosis. Smooth tests of goodness-of-fit have recently been introduced in the field showing some interesting properties. We will discuss the smooth tests of goodness-of-fit developed by Rayner and Best for the univariate as well as for the multivariate analysis.Comment: Proceedings of "The Cosmic Microwave Background and its Polarization", New Astronomy Reviews, (eds. S. Hanany and K.A. Olive), in pres