CMB lensing reconstruction in the presence of diffuse polarized foregrounds

CMB lensing reconstruction in the presence of diffuse polarized foregrounds

The measurement and characterization of the lensing of the cosmic microwave backgromid (CMB) is key goal of the current and next generation of CMB experiments. We perform a case study of a three-channel balloon-borne CMB experiment observing the sky at (l,b)=(250[degrees], -38[degrees]) and attainin...

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Bibliographic Details
Published in:Journal of cosmology and astroparticle physics 2012-12, Vol.2012 (12), p.1-20
Main Authors: Fantaye, Y, Baccigalupi, C, Leach, S M, Yadav, A PS
Format: Article
Language:eng
Subjects:
ACCURACY
ASTROPHYSICS
ASTROPHYSICS, COSMOLOGY AND ASTRONOMY
Bias
Contaminants
Convergence
COSMIC DUST
COSMOLOGY
Dust
GHZ RANGE
GRAVITATIONAL LENSES
MILKY WAY
POLARIZATION
Reconstruction
RELICT RADIATION
SENSITIVITY
Separation
Spectra
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Summary:The measurement and characterization of the lensing of the cosmic microwave backgromid (CMB) is key goal of the current and next generation of CMB experiments. We perform a case study of a three-channel balloon-borne CMB experiment observing the sky at (l,b)=(250[degrees], -38[degrees]) and attaining a sensitivity of 5.25 mu K-aremin with 8' angular resolution at 150 GHz, in order to assess whether the effect of polarized Galactic dust is expected to be a significant contaminant to the lensing signal reconstructed using the EB quadratic estimator. We find that for our assumed dust model, polarization fractions of about as low as a few percent may lead to a significant dust bias to the lensing convergence power spcctrmn. We investigated a parametric component separation method, proposed by Stompor et al. (2009), as well as a template cleaning method, for mitigating the effect of this dust bias. The template-based method recovers unbiased convergence power spectrum in all polarization fraction cases we considered, while for the component separation technique we find a dust contrast regime in which the accuracy of the profile likelihood spectral index estimate breaks down, and in which external information on the dust frequency scaling is needed. We propose a criterion for putting a requirement on the accuracy with which the dust spectral index must be estimated or constrained, and demonstrate that if this requirement is met, then the dust bias can be removed.
ISSN:1475-7516
1475-7516