Reconstruction of the cosmic microwave background lensing for Planck
Laboratoire de Physique Subatomique et de Cosmologie (LPSC),
CNRS: UMR5821, IN2P3, Université Joseph Fourier –
Grenoble I, Institut Polytechnique de Grenoble, France e-mail: firstname.lastname@example.org
2 Laboratoire de l'Accélérateur Linéaire (LAL), CNRS: UMR8607, IN2P3, Université Paris-Sud, Orsay, France e-mail: email@example.com,firstname.lastname@example.org
3 Laboratoire AIM (UMR 7158), CEA/DSM-CNRS-Université Paris Diderot, IRFU, SEDI-SAP, Service d'Astrophysique, Centre de Saclay, 91191 Gif-Sur-Yvette Cedex, France e-mail: email@example.com
4 Applied and Computational Mathematics (ACM), California Institute of Technology, 1200 E.California Bvd, M/C 217-50, PASADENA CA-91125, USA e-mail: firstname.lastname@example.org
Accepted: 19 February 2010
Aims. We prepare real-life cosmic microwave background (CMB) lensing extraction with the forthcoming Planck satellite data by studying two systematic effects related to the foreground contamination: the impact of foreground residuals after a component separation on the lensed CMB map, and the impact of removing a large contaminated region of the sky.
Methods. We first use the generalized morphological component analysis (GMCA) method to perform a component separation within a simplified framework, which allows a high statistics Monte-Carlo study. For the second systematic, we apply a realistic mask on the temperature maps and then restore them with a recently developed inpainting technique on the sphere. We investigate the reconstruction of the CMB lensing from the resultant maps using a quadratic estimator in the flat sky limit and on the full sphere.
Results. We find that the foreground residuals from the GMCA method does not significantly alter the lensed signal, which is also true for the mask corrected with the inpainting method, even in the presence of point source residuals.
Key words: cosmic microwave background / large-scale structure of Universe / gravitational lensing: weak / methods: statistical
© ESO, 2010