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It has been long recognized that, besides being a formidable experiment to observe the primordial cosmic microwave background (CMB) anisotropies, Planck will also have the capability to detect galaxy clusters via their Sunyaev–Zel'dovich (SZ) imprint. In this paper constraints on cosmological parameters derivable from the Planck cluster candidate sample are examined for the first time as a function of cluster sample selection and purity obtained from realistic simulations of the microwave sky at the Planck observing frequency bands, observation process modelling and a cluster extraction pipeline. In particular, we employ a multifrequency matched filtering (MFMF) method to recover clusters from mock simulations of Planck observations. Obtainable cosmological constraints under realistic assumptions of priors and knowledge about cluster redshifts are discussed. Just relying on cluster redshift abundances without making use of recovered cluster fluxes, it is shown that from the Planck cluster catalogue cosmological constraints comparable to the ones derived from recent primordial CMB power spectrum measurements can be achieved. For example, for a concordance Λ cold dark matter (ΛCDM) model and a redshift binning of , the 1σ uncertainties on the values of Ωm and σ8 are and , respectively. Furthermore, we find that the constraint of the matter density depends strongly on the prior which can be imposed on the Hubble parameter by other observational means. [ABSTRACT FROM AUTHOR]

Bayesian model selection is a tool for deciding whether the introduction of a new parameter is warranted by the data. I argue that the usual sampling statistic significance tests for a null hypothesis can be misleading, since they do not take into account the information gained through the data, when updating the prior distribution to the posterior. In contrast, Bayesian model selection offers a quantitative implementation of Occam's razor. I introduce the Savage–Dickey density ratio, a computationally quick method to determine the Bayes factor of two nested models and hence perform model selection. As an illustration, I consider three key parameters for our understanding of the cosmological concordance model. By using Wilkinson Microwave Anisotropy Probe ( WMAP) 3-year data complemented by other cosmological measurements, I show that a non-scale-invariant spectral index of perturbations is favoured for any sensible choice of prior. It is also found that a flat universe is favoured with odds of 29:1 over non-flat models, and that there is strong evidence against a cold dark matter isocurvature component to the initial conditions which is totally (anti)correlated with the adiabatic mode (odds of about 2000:1), but that this is strongly dependent on the prior adopted. These results are contrasted with the analysis of WMAP 1-year data, which were not informative enough to allow a conclusion as to the status of the spectral index. In a companion paper, a new technique to forecast the Bayes factor of a future observation is presented. [ABSTRACT FROM AUTHOR]

We perform a blind multicomponent analysis of the Wilkinson Microwave Anisotropy Probe ( WMAP) 1-yr foreground-cleaned maps using Spectral Matching Independent Component Analysis ( smica). We provide a new estimate of the cosmic microwave background (CMB) power spectrum as well as the amplitude of the CMB anisotropies across frequency channels. We show that the CMB anisotropies are compatible with temperature fluctuations as expected from the standard paradigm. The analysis also allows us to identify and separate a weak residual Galactic emission, present significantly in the Q band outside of the Kp2 1 mask limits, and mainly concentrated at low Galactic latitudes. We produce a map of this residual component by Wiener filtering using estimated parameters. The level of contamination of CMB data by this component is compatible with the WMAP-team estimation of foreground residual contamination. In addition, the multicomponent analysis allows us to estimate jointly the power spectrum of unresolved point-source emission. [ABSTRACT FROM AUTHOR]

We develop the pseudo- Cℓ method for reconstructing the cosmic microwave background (CMB) temperature and polarization auto- and cross-power spectra, and estimate the pseudo- Cℓ covariance matrix for a realistic experiment on the cut sky. We calculate the full coupling equations for all six possible CMB power spectra, relating the observed pseudo- Cℓ values to the underlying all-sky Cℓ values, and test the reconstruction on both full-sky and cut-sky simulated CMB data sets. In particular we consider the reconstruction of the Cℓ from upcoming ground-based polarization experiments covering areas of a few hundred deg2 and find that the method is fast, unbiased and performs well over a wide range of multipoles from to . We then calculate the full covariance matrix between the modes of the pseudo-temperature and polarization power spectra, assuming that the underlying CMB fields are Gaussian randomly distributed. The complexity of the covariance matrix prohibits its rapid calculation, required for parameter estimation. Hence we present an approximation for the covariance matrix in terms of convolutions of the underlying power spectra. The coupling matrices in these expressions can be estimated by fitting to numerical simulations, circumventing direct and slow calculation, and further, inaccurate analytic approximations. We show that these coupling matrices are mostly independent of cosmology, and that the full covariance matrix for all six pseudo- Cℓ power spectra can be quickly and accurately calculated for any given cosmological model using this method. We compare these semi-analytic covariance matrices against simulations and find good agreement, the accuracy of which depends mainly on survey area and the range of cosmological parameters considered. [ABSTRACT FROM AUTHOR]

We presentXspect, a method to obtain estimates of the angular power spectrum of the cosmic microwave background (CMB) temperature anisotropies including analytical error bars developed for theArcheopsexperiment. Cross-power spectra are computed from a set of maps and each of them is in itself an unbiased estimate of the power spectrum as long as the detector noises are uncorrelated. Then, the cross-power spectra are combined into a final temperature power spectrum with error bars analytically derived from the cross-correlation matrix.This method presents three main useful properties: (1) no estimation of the noise power spectrum is needed; (2) complex weighting schemes including sky covering and map noise properties can be easily taken into account, and corrected for, for each input map; and (3) error bars are quickly computed analytically from the data themselves with no Monte Carlo simulations involved.Xspectalso permits the study of common fluctuations between maps from different sky surveys such as CMB, Sunyaev–Zel'dovich effect or mass fluctuations from weak lensing observations. [ABSTRACT FROM AUTHOR]

We estimate the bispectrum of the Very Small Array data from the compact and extended configuration observations released in 2002 December, and compare our results with those obtained from Gaussian simulations. There is a slight excess of large bispectrum values for two individual fields, but this does not appear when the fields are combined. Given our expected level of residual point sources, we do not expect these to be the source of the discrepancy. Using the compact configuration data, we put an upper limit of 5400 on the value of fNL, the non-linear coupling parameter, at 95 per cent confidence. We test our bispectrum estimator using non-Gaussian simulations with a known bispectrum, and recover the input values. [ABSTRACT FROM AUTHOR]