2011/03/13 by Charmaine Armitage-Caplan, Joanna Dunkley, Hans Kristian Eriksen +1
Physics and Astronomy · #Amplitude #Cosmic microwave background #Cosmology and Gravitation Theories #Galaxies: Formation, Evolution, Phenomena #Limit (mathematics) #Particle physics theoretical and experimental studies #Planck #Reionization #Sampling (signal processing) #Sky #Spectral index #Synchrotron #astro-ph.CO
paper · pdf · doi:10.1111/j.1365-2966.2011.19307.x
15 pages, 12 figures, submitted to MNRAS
arxiv created 2011/03/13 · openalex publication_date 2011/10/10 · arxiv updated 2015/05/27 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/05
We use Bayesian component estimation methods to examine the prospects of large-scale polarized map and cosmological parameter estimation with simulated Planck data assuming simplified white noise properties. The sky signal is parametrized as the sum of the cosmic microwave background (CMB), synchrotron emission, and thermal dust emission. The synchrotron and dust emission components are modelled as power laws in frequency, with a spatially varying spectral index for synchrotron and a uniform index for dust. Using the Gibbs sampling technique, we estimate the linear polarization Q and U posterior amplitudes of the CMB, synchrotron and dust maps as well as the two spectral indices in ∼4° pixels. We use the recovered CMB map and its covariance in an exact pixel likelihood algorithm to estimate the optical depth to reionization τ, the tensor-to-scalar ratio r, and to construct conditional likelihood slices for CEEℓ and CBBℓ. Given our foreground model, we find σ(τ) ≈ 0.004 for τ= 0.1, σ(r) ≈ 0.03 for a model with r= 0.1, and a 95 per cent upper limit of r < 0.02 for r= 0.0.