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Title:
CMB anisotropy power spectrum using linear combinations of WMAP maps
Authors:
Saha, Rajib; Prunet, Simon; Jain, Pankaj; Souradeep, Tarun
Affiliation:
AA(Department of Physics, Indian Institute of Technology, Kanpur, U.P, 208016, India; Inter-University Centre for Astronomy and Astrophysics, Post Bag 4, Ganeshkhind, Pune 411007, India; Institut d’Astrophysique de Paris, 98 bis Boulevard Arago, F-75014 Paris, France), AB(Institut d’Astrophysique de Paris, 98 bis Boulevard Arago, F-75014 Paris, France), AC(Department of Physics, Indian Institute of Technology, Kanpur, U.P, 208016, India), AD(Inter-University Centre for Astronomy and Astrophysics, Post Bag 4, Ganeshkhind, Pune 411007, India)
Publication:
Physical Review D, vol. 78, Issue 2, id. 023003 (PhRvD Homepage)
Publication Date:
07/2008
Origin:
APS
PACS Keywords:
Background radiations, Data analysis: algorithms and implementation; data management, Observational cosmology
DOI:
10.1103/PhysRevD.78.023003
Bibliographic Code:
2008PhRvD..78b3003S

Abstract

In recent years the goal of estimating different cosmological parameters precisely has set new challenges in the effort to accurately measure the angular power spectrum of the CMB. 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 the CMB angular power spectrum solely from multifrequency observations has been proposed and implemented on the first year WMAP data by Saha et al. 2006. All previous estimates of the power spectrum of the CMB are based upon foreground templates using data sets from different experiments. However, our methodology demonstrates that the CMB angular spectrum can be reliably estimated with precision from a self-contained analysis of the WMAP data. In this work we provide a detailed description of this method. We also study and identify the biases present in our power spectrum estimate. We apply our methodology to extract the power spectrum from the WMAP data.
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