4,001 research outputs found

    Marginal distributions for cosmic variance limited CMB polarization data

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    We provide computationally convenient expressions for all marginal distributions of the polarization CMB power spectrum distribution P(C_l|sigma_l), where C_l = {C_l^TT, C_l^TE, C_l^EE, C_l^BB} denotes the set of ensemble averaged polarization CMB power spectra, and sigma_l = {sigma_l^TT, sigma_l^TE, sigma_l^EE, sigma_l^BB} the set of the realization specific polarization CMB power spectra. This distribution describes the CMB power spectrum posterior for cosmic variance limited data. The expressions derived here are general, and may be useful in a wide range of applications. Two specific applications are described in this paper. First, we employ the derived distributions within the CMB Gibbs sampling framework, and demonstrate a new conditional CMB power spectrum sampling algorithm that allows for different binning schemes for each power spectrum. This is useful because most CMB experiments have very different signal-to-noise ratios for temperature and polarization. Second, we provide new Blackwell-Rao estimators for each of the marginal polarization distributions, which are relevant to power spectrum and likelihood estimation. Because these estimators represent marginals, they are not affected by the exponential behaviour of the corresponding joint expression, but converge quickly.Comment: 8 pages, 3 figures; minor adjustment, accepted for publication in ApJ

    The two-and three-point correlation functions of the polarized five-year WMAP sky maps

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    We present the two- and three-point real space correlation functions of the five-year WMAP sky maps, and compare the observed functions to simulated LCDM concordance model ensembles. In agreement with previously published results, we find that the temperature correlation functions are consistent with expectations. However, the pure polarization correlation functions are acceptable only for the 33GHz band map; the 41, 61, and 94 GHz band correlation functions all exhibit significant large-scale excess structures. Further, these excess structures very closely match the correlation functions of the two (synchrotron and dust) foreground templates used to correct the WMAP data for galactic contamination, with a cross-correlation statistically significant at the 2sigma-3sigma confidence level. The correlation is slightly stronger with respect to the thermal dust template than with the synchrotron template.Comment: 10 pages, 5 figures, published in ApJ. v2: New title, minor changes to appendix, and fixed some typos. v3: Matches version published in Ap

    Point-Source Power in 3 Year Wilkinson Microwave Anisotropy Probe Data

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    Using a set of multifrequency cross spectra computed from the 3 year WMAP sky maps, we fit for the unresolved point-source contribution. For a white-noise power spectrum, we find a Q-band amplitude of A = 0.011 ± 0.001 μK^2 sr (antenna temperature), significantly smaller than the value of 0.017 ± 0.002 μK^2 sr used to correct the spectra in the WMAP release. Modifying the point-source correction in this way largely resolves the discrepancy that Eriksen et al. found between the WMAP V- and W-band power spectra. Correcting the co-added WMAP spectrum for both the low-l power excess due to a suboptimal likelihood approximation—also reported by Eriksen et al.—and the high-l power deficit due to oversubtracted point sources—presented in this Letter—we find that the net effect in terms of cosmological parameters is an ~0.7 σ shift in n_s to larger values. For the combination of WMAP, BOOMERANG, and ACBAR data, we find ns = 0.969 ± 0.016, lowering the significance of n_s ≠ 1 from ~2.7 σ to ~2.0 σ

    A Markov Chain Monte Carlo Algorithm for analysis of low signal-to-noise CMB data

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    We present a new Monte Carlo Markov Chain algorithm for CMB analysis in the low signal-to-noise regime. This method builds on and complements the previously described CMB Gibbs sampler, and effectively solves the low signal-to-noise inefficiency problem of the direct Gibbs sampler. The new algorithm is a simple Metropolis-Hastings sampler with a general proposal rule for the power spectrum, C_l, followed by a particular deterministic rescaling operation of the sky signal. The acceptance probability for this joint move depends on the sky map only through the difference of chi-squared between the original and proposed sky sample, which is close to unity in the low signal-to-noise regime. The algorithm is completed by alternating this move with a standard Gibbs move. Together, these two proposals constitute a computationally efficient algorithm for mapping out the full joint CMB posterior, both in the high and low signal-to-noise regimes.Comment: Submitted to Ap

    Spatial variations in the spectral index of polarized synchrotron emission in the 9 yr WMAP sky maps

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    We estimate the spectral index, beta, of polarized synchrotron emission as observed in the 9 yr WMAP sky maps using two methods, linear regression ("T-T plot") and maximum likelihood. We partition the sky into 24 disjoint sky regions, and evaluate the spectral index for all polarization angles between 0 deg and 85 deg in steps of 5. Averaging over polarization angles, we derive a mean spectral index of beta_all-sky=-2.99+-0.01 in the frequency range of 23-33 GHz. We find that the synchrotron spectral index steepens by 0.14 from low to high Galactic latitudes, in agreement with previous studies, with mean spectral indices of beta_plane=-2.98+-0.01 and beta_high-lat=-3.12+-0.04. In addition, we find a significant longitudinal variation along the Galactic plane with a steeper spectral index toward the Galactic center and anticenter than toward the Galactic spiral arms. This can be well modeled by an offset sinusoidal, beta(l)=-2.85+0.17sin(2l-90). Finally, we study synchrotron emission in the BICEP2 field, in an attempt to understand whether the claimed detection of large-scale B-mode polarization could be explained in terms of synchrotron contamination. Adopting a spectral index of beta=-3.12, typical for high Galactic latitudes, we find that the most likely bias corresponds to about 2% of the reported signal (r=0.003). The flattest index allowed by the data in this region is beta=-2.5, and under the assumption of a straight power-law frequency spectrum, we find that synchrotron emission can account for at most 20% of the reported BICEP2 signal.Comment: 11 pages, 9 figures, updated to match version published in Ap

    CMB likelihood approximation by a Gaussianized Blackwell-Rao estimator

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    We introduce a new CMB temperature likelihood approximation called the Gaussianized Blackwell-Rao (GBR) estimator. This estimator is derived by transforming the observed marginal power spectrum distributions obtained by the CMB Gibbs sampler into standard univariate Gaussians, and then approximate their joint transformed distribution by a multivariate Gaussian. The method is exact for full-sky coverage and uniform noise, and an excellent approximation for sky cuts and scanning patterns relevant for modern satellite experiments such as WMAP and Planck. A single evaluation of this estimator between l=2 and 200 takes ~0.2 CPU milliseconds, while for comparison, a single pixel space likelihood evaluation between l=2 and 30 for a map with ~2500 pixels requires ~20 seconds. We apply this tool to the 5-year WMAP temperature data, and re-estimate the angular temperature power spectrum, CC_{\ell}, and likelihood, L(C_l), for l<=200, and derive new cosmological parameters for the standard six-parameter LambdaCDM model. Our spectrum is in excellent agreement with the official WMAP spectrum, but we find slight differences in the derived cosmological parameters. Most importantly, the spectral index of scalar perturbations is n_s=0.973 +/- 0.014, 1.9 sigma away from unity and 0.6 sigma higher than the official WMAP result, n_s = 0.965 +/- 0.014. This suggests that an exact likelihood treatment is required to higher l's than previously believed, reinforcing and extending our conclusions from the 3-year WMAP analysis. In that case, we found that the sub-optimal likelihood approximation adopted between l=12 and 30 by the WMAP team biased n_s low by 0.4 sigma, while here we find that the same approximation between l=30 and 200 introduces a bias of 0.6 sigma in n_s.Comment: 10 pages, 7 figures, submitted to Ap

    Sensitivity and foreground modelling for large-scale CMB B-mode polarization satellite missions

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    The measurement of the large-scale B-mode polarization in the cosmic microwave background (CMB) is a fundamental goal of future CMB experiments. However, because of unprecedented sensitivity, future CMB experiments will be much more sensitive to any imperfect modelling of the Galactic foreground polarization in the reconstruction of the primordial B-mode signal. We compare the sensitivity to B-modes of different concepts of CMB satellite missions (LiteBIRD, COrE, COrE+, PRISM, EPIC, PIXIE) in the presence of Galactic foregrounds. In particular, we quantify the impact on the tensor-to-scalar parameter of incorrect foreground modelling in the component separation process. Using Bayesian fitting and Gibbs sampling, we perform the separation of the CMB and Galactic foreground B-modes. The recovered CMB B-mode power spectrum is used to compute the likelihood distribution of the tensor-to-scalar ratio. We focus the analysis to the very large angular scales that can be probed only by CMB space missions, i.e. the Reionization bump, where primordial B-modes dominate over spurious B-modes induced by gravitational lensing. We find that fitting a single modified blackbody component for thermal dust where the "real" sky consists of two dust components strongly bias the estimation of the tensor-to-scalar ratio by more than 5{\sigma} for the most sensitive experiments. Neglecting in the parametric model the curvature of the synchrotron spectral index may bias the estimated tensor-to-scalar ratio by more than 1{\sigma}. For sensitive CMB experiments, omitting in the foreground modelling a 1% polarized spinning dust component may induce a non-negligible bias in the estimated tensor-to-scalar ratio.Comment: 20 pages, 8 figures, 6 tables. Updated to match version accepted by MNRA
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