Tests of Gaussianity

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

Variograms of the Cosmic Microwave Background Temperature Fluctuations: Confirmation of Deviations from Statistical Isotropy

The Standard Inflationary model predicts an isotropic distribution of the Cosmic Microwave Background temperature fluctuations. Detection of deviations from statistical isotropy would call for a revision of the physics of the early universe. This paper introduces the variogram as a powerful tool to detect and characterize deviations from statistical isotropy in Cosmic Microwave Background maps. Application to the Wilkinson Microwave Anisotropy Probe data clearly shows differences between the northern and the southern hemispheres. The sill and range of the northern hemisphere's variogram are lower than those of the southern hemisphere. Moreover the variogram for the northern hemisphere lies outside the 99% c.l. for scales above ten degrees. Differences between the northern and southern hemispheres in the functional dependence of the variogram with the scale can be used as a validation bench mark for proposed anisotropic cosmological models.Comment: submitted to MNRA

The performance of spherical wavelets to detect non-Gaussianity in the CMB sky

We investigate the performance of spherical wavelets in discriminating between standard inflationary models (Gaussian) and non-Gaussian models. For the later we consider small perturbations of the Gaussian model in which an artificially specified skewness or kurtosis is introduced through the Edgeworth expansion. By combining all the information present in all the wavelet scales with the Fisher discriminant, we find that the spherical Mexican Hat wavelets are clearly superior to the spherical Haar wavelets. The former can detect levels of the skewness and kurtosis of ~1% for 33' resolution, an order of magnitude smaller than the later. Also, as expected, both wavelets are better for discriminating between the models than the direct consideration of moments of the temperature maps. The introduction of instrumental white noise in the maps, S/N=1, does not change the main results of this paper.Comment: 12 pages, 7 figures, accepted by MNRAS with minor change

Predicted Planck Extragalactic Point Source Catalogue

An estimation of the number and amplitude (in flux) of the extragalactic point sources that will be observed by the Planck Mission is presented in this paper. The study is based on the Mexican Hat wavelet formalism introduced by Cayon et al. 2000. Simulations at Planck observing frequencies are analysed, taking into account all the possible cosmological, Galactic and Extragalactic emissions together with noise. With the technique used in this work the Planck Mission will produce a catalogue of extragalactic point sources above fluxes: 1.03 Jy (857 GHz), 0.53 Jy (545 GHz), 0.28 Jy (353 GHz), 0.24 Jy (217 GHz), 0.32 Jy (143 GHz), 0.41 Jy (100 GHz HFI), 0.34 Jy (100 GHz LFI), 0.57 Jy (70 GHz), 0.54 Jy (44 GHz) and 0.54 Jy (30 GHz), which are only slightly model dependent (see text). Amplitudes of these sources are estimated with errors below 15%. Moreover, we also provide a complete catalogue (for the point sources simulation analysed) with errors in the estimation of the amplitude below 10%. In addition we discuss the possibility of identifying different point source populations in the Planck catalogue by estimating their spectral indices.Comment: 13 pages, 2 figures, submitted to MNRA

Lensing effect on polarization in microwave background: extracting convergence power spectrum

Matter inhomogeneities along the line of sight deflect the cosmic microwave background (CMB) photons originating at the last scattering surface at redshift $z \sim 1100$. These distortions modify the pattern of CMB polarization. We identify specific combinations of Stokes $Q$ and $U$ parameters that correspond to spin 0,$\pm 2$ variables and can be used to reconstruct the projected matter density. We compute the expected signal to noise as a function of detector sensitivity and angular resolution. With Planck satellite the detection would be at a few $\sigma$ level. Several times better detector sensitivity would be needed to measure the projected dark matter power spectrum over a wider range of scales, which could provide an independent confirmation of the projected matter power spectrum as measured from other methods.Comment: 17 pages, 5 figures, accepted for publication in PR

Probing non-Gaussianities in the CMB on an incomplete sky using surrogates

We demonstrate the feasibility to generate surrogates by Fourier-based methods for an incomplete data set. This is performed for the case of a CMB analysis, where astrophysical foreground emission, mainly present in the Galactic plane, is a major challenge. The shuffling of the Fourier phases for generating surrogates is now enabled by transforming the spherical harmonics into a new set of basis functions that are orthonormal on the cut sky. The results show that non-Gaussianities and hemispherical asymmetries in the CMB as identified in several former investigations, can still be detected even when the complete Galactic plane (|b| < 30{\deg}) is removed. We conclude that the Galactic plane cannot be the dominant source for these anomalies. The results point towards a violation of statistical isotropy.Comment: 9 pages, 13 figures, accepted by Physical Review

Goodness-of-fit tests of Gaussianity: constraints on the cumulants of the MAXIMA data

In this work, goodness-of-fit tests are adapted and applied to CMB maps to detect possible non-Gaussianity. We use Shapiro-Francia test and two Smooth goodness-of-fit tests: one developed by Rayner and Best and another one developed by Thomas and Pierce. The Smooth tests test small and smooth deviations of a prefixed probability function (in our case this is the univariate Gaussian). Also, the Rayner and Best test informs us of the kind of non-Gaussianity we have: excess of skewness, of kurtosis, and so on. These tests are optimal when the data are independent. We simulate and analyse non-Gaussian signals in order to study the power of these tests. These non-Gaussian simulations are constructed using the Edgeworth expansion, and assuming pixel-to-pixel independence. As an application, we test the Gaussianity of the MAXIMA data. Results indicate that the MAXIMA data are compatible with Gaussianity. Finally, the values of the skewness and kurtosis of MAXIMA data are constrained by |S| \le 0.035 and |K| \le 0.036 at the 99% confidence level.Comment: New Astronomy Reviews, in pres

Filter design for the detection of compact sources based on the Neyman-Pearson detector

This paper considers the problem of compact source detection on a Gaussian background in 1D. Two aspects of this problem are considered: the design of the detector and the filtering of the data. Our detection scheme is based on local maxima and it takes into account not only the amplitude but also the curvature of the maxima. A Neyman-Pearson test is used to define the region of acceptance, that is given by a sufficient linear detector that is independent on the amplitude distribution of the sources. We study how detection can be enhanced by means of linear filters with a scaling parameter and compare some of them (the Mexican Hat wavelet, the matched and the scale-adaptive filters). We introduce a new filter, that depends on two free parameters (biparametric scale-adaptive filter). The value of these two parameters can be determined, given the a priori pdf of the amplitudes of the sources, such that the filter optimizes the performance of the detector in the sense that it gives the maximum number of real detections once fixed the number density of spurious sources. The combination of a detection scheme that includes information on the curvature and a flexible filter that incorporates two free parameters (one of them a scaling) improves significantly the number of detections in some interesting cases. In particular, for the case of weak sources embedded in white noise the improvement with respect to the standard matched filter is of the order of 40%. Finally, an estimation of the amplitude of the source is introduced and it is proven that such an estimator is unbiased and it has maximum efficiency. We perform numerical simulations to test these theoretical ideas and conclude that the results of the simulations agree with the analytical ones.Comment: 15 pages, 13 figures, version accepted for publication in MNRAS. Corrected typos in Tab.

Reconstructing Projected Matter Density from Cosmic Microwave Background

Gravitational lensing distorts the cosmic microwave background (CMB) anisotropies and imprints a characteristic pattern onto it. The distortions depend on the projected matter density between today and redshift $z \sim 1100$. In this paper we develop a method for a direct reconstruction of the projected matter density from the CMB anisotropies. This reconstruction is obtained by averaging over quadratic combinations of the derivatives of CMB field. We test the method using simulations and show that it can successfully recover projected density profile of a cluster of galaxies if there are measurable anisotropies on scales smaller than the characteristic cluster size. In the absence of sufficient small scale power the reconstructed maps have low signal to noise on individual structures, but can give a positive detection of the power spectrum or when cross correlated with other maps of large scale structure. We develop an analytic method to reconstruct the power spectrum including the effects of noise and beam smoothing. Tests with Monte Carlo simulations show that we can recover the input power spectrum both on large and small scales, provided that we use maps with sufficiently low noise and high angular resolution.Comment: 21 pages, 9 figures, submitted to PR