Related papers: Joint Bayesian component separation and CMB power …

We analyze the three-year WMAP temperature anisotropy data seeking to confirm the power spectrum and likelihoods published by the WMAP team. We apply five independent implementations of four algorithms to the power spectrum estimation and…

We present a Bayesian parametric component separation method for polarised microwave sky maps. We solve jointly for the primary cosmic microwave background (CMB) signal and the main Galactic polarised foreground components. For the latter,…

We propose a rigorous, non-perturbative, Bayesian framework which enables one jointly to test Gaussianity and estimate the power spectrum of CMB anisotropies. It makes use of the Hilbert space of an harmonic oscillator to set up an exact…

In order to extract cosmological information from observations of the millimeter and submillimeter sky, foreground components must first be removed to produce an estimate of the cosmic microwave background (CMB). We developed a…

We consider the shape of the likelihood and posterior surfaces to be used when fitting cosmological models to CMB temperature and polarisation power spectra measured from experiments. In the limit of an all-sky survey with Gaussian…

Residual error in calibration coefficients corresponding to observed CMB maps is an important issue while estimating a pure CMB signal. A component separation method, if these errors in the input foreground contaminated CMB maps are not…

In these proceedings, we discuss the extraction, in WMAP 5 year data, of a clean CMB map, of foreground emission (dominated by emission of the interstellar medium of our galaxy), and of the tiny signal from Sunyaev Zel'dovich effect in the…

We present a joint cosmological analysis combining data from the Planck satellite, the Atacama Cosmology Telescope, and the South Pole Telescope. We construct a unified likelihood that reproduces the measured temperature and polarisation…

We investigate the extent to which foreground cleaned CMB maps can be used to estimate the cosmological parameters at small scales. We use the SMICA method, a blind separation technique which works directly at the spectral level. In this…

We examine power spectrum estimation from wide-sense stationary signals received at different wireless sensors. We organize multiple sensors into several groups, where each group estimates the temporal correlation only at particular lags,…

Divergence is not only an important mathematical concept in information theory, but also applied to machine learning problems such as low-dimensional embedding, manifold learning, clustering, classification, and anomaly detection. We…

We show that the popular ILC approach is unstable in respect to the division of the sample of map pixels to the set of ``homogeneous'' subsamples. For suitable choice of such subsamples we can obtain the restored CMB signal with amplitudes…

The cosmic microwave background (CMB) power spectrum is a powerful cosmological probe as it entails almost all the statistical information of the CMB perturbations. Having access to only one sky, the CMB power spectrum measured by our…

Foreground removal techniques for CMB analyses make specific assumptions about the properties of foregrounds in temperature and in polarization. By investigating the statistics of foreground components more understanding about the degree to…

A new method for estimating the angular power spectrum C_l from cosmic microwave background (CMB) maps is presented, which has the following desirable properties: (1) It is unbeatable in the sense that no other method can measure C_l with…

We discuss a method for a model independent reconstruction of the CMB temperature fluctuation power spectrum on small and intermediate scales that is geared to individual experiments. The importance of off-diagonal correlations for…

Line-intensity mapping (LIM) is an emerging cosmological technique that traces large-scale structure through the integrated spectral-line emission of unresolved sources. Reconstructing unbiased sky maps requires careful joint treatment of…

We investigate the performance of the parametric Maximum Likelihood component separation method in the context of the CMB B-mode signal detection and its characterization by small-scale CMB suborbital experiments. We consider…

We develop a new Bayesian method for estimating white noise levels in CMB sky maps, and apply this algorithm to the 5-year WMAP data. We assume that the amplitude of the noise RMS is scaled by a constant value, alpha, relative to a…

We introduce a new estimator of the CMB lensing power spectrum, together with its likelihood, based on iterative lensing reconstruction. Despite the increased complexity of the lensing maps, this estimator shares similarities with the…