Angular power spectrum of CMB anisotropy from WMAP

Details Angular power spectrum of CMB anisotropy from WMAP Angular power spectrum of CMB anisotropy from WMAP

2006-08-09

arxiv.org/abs/astro-ph/0608199v1

New Astron.Rev.50:854-860,2006

Astronomy and Astrophysics

Astrophysics

12 pages, 4 figures; Proceedings of the Fundamental Physics With CMB workshop, UC Irvine, March 23-25, 2006, to be published i

Scientific paper

10.1016/j.newar.2006.09.009

The remarkable improvement in the estimates of different cosmological parameters in recent years has been largely spearheaded by accurate measurements of the angular power spectrum of Cosmic Microwave Background (CMB) radiation. This has required removal of foreground contamination as well as detector noise bias with reliability and precision. Recently, a novel model-independent method for the estimation of CMB angular power spectrum from multi-frequency observations has been proposed and implemented on the first year WMAP (WMAP-1) data by Saha et al.~2006. We review the results from WMAP-1 and also present the new angular power spectrum based on three years of the WMAP data (WMAP-3). Previous estimates have depended on foreground templates built using extraneous observational input to remove foreground contamination. This is the first demonstration that the CMB angular spectrum can be reliably estimated with precision from a self contained analysis of the WMAP data. The primary product of WMAP are the observations of CMB in 10 independent difference assemblies (DA) distributed over 5 frequency bands that have uncorrelated noise. Our method utilizes maximum information available within WMAP data by linearly combining DA maps from different frequencies to remove foregrounds and estimating the power spectrum from the 24 cross power spectra of clean maps that have independent noise. An important merit of the method is that the expected residual power from unresolved point sources is significantly tempered to a constant offset at large multipoles (in contrast to the ~l^2 contribution expected from a Poisson distribution) leading to a small correction at large multipoles. Hence, the power spectrum estimates are less susceptible to uncertainties in the model of point sources.

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