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Phys. Rev. D 78, 083013 (2008) [16 pages]

CMB power spectrum estimation using wavelets

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G. Faÿ*, F. Guilloux, M. Betoule, J.-F. Cardoso, J. Delabrouille, and M. Le Jeune
Laboratoire AstroParticule et Cosmologie, UMR 7164, Université Paris 7—Denis Diderot and CNRS, 10, rue A. Domon et L. Duquet, 75205 Paris Cedex 13, France

Received 8 July 2008; published 30 October 2008

Observations of the cosmic microwave background (CMB) provide increasingly accurate information about the structure of the Universe at the recombination epoch. Most of this information is encoded in the angular power spectrum of the CMB. The aim of this work is to propose a versatile and powerful method for spectral estimation on the sphere which can easily deal with nonstationary uncorrelated noise and multiple experiments with various specifications. In this paper, we use needlets (wavelets) on the sphere to construct natural and efficient spectral estimators for partially observed and beamed CMB with nonstationary noise. In the case of a single experiment, we compare this method with pseudo-C methods. The performance of the needlet spectral estimators (NSE) compares very favorably to the best pseudo-C estimators, over the whole multipole range. On simulations with a simple model (CMB+uncorrelated noise with known variance per pixel+mask), they perform uniformly better. Their distinctive ability to aggregate many different experiments, to control the propagation of errors, and to produce a single wideband error bar is highlighted. The needlet spectral estimator is a powerful, tunable tool which is very well suited to the angular power spectrum estimation of spherical data such as incomplete and noisy CMB maps.

© 2008 The American Physical Society

URL:
http://link.aps.org/doi/10.1103/PhysRevD.78.083013
DOI:
10.1103/PhysRevD.78.083013
PACS:
98.80.−k, 95.75.Pq, 98.80.Es

*Laboratoire Paul Painlevé, UMR 8524, Université Lille 1 and CNRS, 59 655 Villeneuve d’Ascq Cedex, France;

gilles.fay@univ-lille1.fr

MODAL’X, Université Paris Ouest—Nanterre La Défense, 200 avenue de la République, 92001 Nanterre Cedex, France and Laboratoire de Probabilités et Modèles Aléatoires, UMR 7599, Université Paris 7—Denis Diderot and CNRS, 175 rue du Chevaleret, 75013 Paris, France.

Laboratoire de Traitement et Communication de l’Information, UMR 5141, Télécom ParisTech and CNRS, 46 rue Barrault, 75634 Paris Cedex, France.