No Arabic abstract
We present the XFaster analysis package. XFaster is a fast, iterative angular power spectrum estimator based on a diagonal approximation to the quadratic Fisher matrix estimator. XFaster uses Monte Carlo simulations to compute noise biases and filter transfer functions and is thus a hybrid of both Monte Carlo and quadratic estimator methods. In contrast to conventional pseudo-$C_ell$ based methods, the algorithm described here requires a minimal number of simulations, and does not require them to be precisely representative of the data to estimate accurate covariance matrices for the bandpowers. The formalism works with polarization-sensitive observations and also data sets with identical, partially overlapping, or independent survey regions. The method was first implemented for the analysis of BOOMERanG data, and also used as part of the Planck analysis. Here, we describe the full, publicly available analysis package, written in Python, as developed for the analysis of data from the 2015 flight of the SPIDER instrument. The package includes extensions for self-consistently estimating null spectra and for estimating fits for Galactic foreground contributions. We show results from the extensive validation of XFaster using simulations, and its application to the SPIDER data set.
The power spectrum is obtained for the Kolmogorov stochasticity parameter map for WMAPs cosmic microwave background (CMB) radiation temperature datasets. The interest for CMB Kolmogorov map is that it can carry direct information about voids in the matter distribution, so that the correlations in the distribution of voids have to be reflected in the power spectrum. Although limited by the angular resolution of the WMAP, this analysis shows the possibility of acquiring this crucial information via CMB maps. Even the already obtained behavior, some of which is absent in the simulated maps, can influence the development of views on the void correlations at the large-scale web formation.
We develop two methods for estimating the power spectrum, C_l, of the cosmic microwave background (CMB) from data and apply them to the COBE/DMR and Saskatoon datasets. One method involves a direct evaluation of the likelihood function, and the other is an estimator that is a minimum-variance weighted quadratic function of the data. Applied iteratively, the quadratic estimator is not distinct from likelihood analysis, but is rather a rapid means of finding the power spectrum that maximizes the likelihood function. Our results bear this out: direct evaluation and quadratic estimation converge to the same C_ls. The quadratic estimator can also be used to directly determine cosmological parameters and their uncertainties. While the two methods both require O(N^3) operations, the quadratic is much faster, and both are applicable to datasets with arbitrary chopping patterns and noise correlations. We also discuss approximations that may reduce it to O(N^2) thus making it practical for forthcoming megapixel datasets.
We investigate the impact of instrumental systematic errors in interferometric measurements of the cosmic microwave background (CMB) temperature and polarization power spectra. We simulate interferometric CMB observations to generate mock visibilities and estimate power spectra using the statistically optimal maximum likelihood technique. We define a quadratic error measure to determine allowable levels of systematic error that do not induce power spectrum errors beyond a given tolerance. As an example, in this study we focus on differential pointing errors. The effects of other systematics can be simulated by this pipeline in a straightforward manner. We find that, in order to accurately recover the underlying B-modes for r=0.01 at 28<l<384, Gaussian-distributed pointing errors must be controlled to 0.7^circ rms for an interferometer with an antenna configuration similar to QUBIC, in agreement with analytical estimates. Only the statistical uncertainty for 28<l<88 would be changed at ~10% level. With the same instrumental configuration, we find the pointing errors would slightly bias the 2-sigma upper limit of the tensor-to-scalar ratio r by ~10%. We also show that the impact of pointing errors on the TB and EB measurements is negligibly small.
Estimation of the B-mode angular power spectrum of polarized anisotropies of the cosmic microwave background (CMB) is a key step towards a full exploitation of the scientific potential of this probe. In the context of pseudo-spectrum methods the major challenge is related to a contamination of the B-mode spectrum estimate with residual power of much larger E-mode. This so-called E-to-B leakage is unavoidably present whenever an incomplete sky map is only available, as is the case for any realistic observation. The leakage has to be then minimized or removed and ideally in such a way that neither a bias nor extra variance is introduced. In this paper, we compare from these two perspectives three different methods proposed recently in this context Refs. Smith 2006, Zhao & Baskaran 2010, Kim & Naselsky 2010, which we first introduce within a common algebraic framework of the so-called chi-fields and then study their performance on two different experimental configurations - one corresponding to a small-scale experiment covering 1% of the sky motivated by current ground-based or balloon-borne experiments and another - to a nearly full-sky experiment, e.g., a possible CMB B-mode satellite mission. We find that though all these methods allow to reduce significantly the level of the E-to-B leakage, it is the method of Smith 2006, which at the same time ensures the smallest error bars in all experimental configurations studied here, owing to the fact that it permits straightforwardly for an optimization of the sky apodization of the polarization maps used for the estimation. For a satellite-like experiment, this method enables a detection of B-mode power spectrum at large angular scales but only after appropriate binning. The method of Zhao & Baskaran 2010 is a close runner-up in the case of a nearly full sky coverage.
Gravitational lensing due to the large-scale distribution of matter in the cosmos distorts the primordial Cosmic Microwave Background (CMB) and thereby induces new, small-scale $B$-mode polarization. This signal carries detailed information about the distribution of all the gravitating matter between the observer and CMB last scattering surface. We report the first direct evidence for polarization lensing based on purely CMB information, from using the four-point correlations of even- and odd-parity $E$- and $B$-mode polarization mapped over $sim30$ square degrees of the sky measured by the POLARBEAR experiment. These data were analyzed using a blind analysis framework and checked for spurious systematic contamination using null tests and simulations. Evidence for the signal of polarization lensing and lensing $B$-modes is found at 4.2$sigma$ (stat.+sys.) significance. The amplitude of matter fluctuations is measured with a precision of $27%$, and is found to be consistent with the Lambda Cold Dark Matter ($Lambda$CDM) cosmological model. This measurement demonstrates a new technique, capable of mapping all gravitating matter in the Universe, sensitive to the sum of neutrino masses, and essential for cleaning the lensing $B$-mode signal in searches for primordial gravitational waves.