Effect of noncircularity of experimental beam on CMB parameter estimation

Measurement of Cosmic Microwave Background (CMB) anisotropies has been playing a lead role in precision cosmology by providing some of the tightest constrains on cosmological models and parameters. However, precision can only be meaningful when all major systematic effects are taken into account. No...

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Bibliographic Details
Published in:Journal of cosmology and astroparticle physics 2015-03, Vol.2015 (3), p.48-48, Article 048
Main Authors: Das, Santanu, Mitra, Sanjit, Paulson, Sonu Tabitha
Format: Article
Language:English
Subjects:
ACCURACY
ANISOTROPY
ASTROPHYSICS, COSMOLOGY AND ASTRONOMY
COMPUTERIZED SIMULATION
COSMOLOGICAL MODELS
COSMOLOGY
COUPLING
ENERGY SPECTRA
ERRORS
ITERATIVE METHODS
MONTE CARLO METHOD
MULTIPOLES
RELICT RADIATION
SCALARS
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Summary:Measurement of Cosmic Microwave Background (CMB) anisotropies has been playing a lead role in precision cosmology by providing some of the tightest constrains on cosmological models and parameters. However, precision can only be meaningful when all major systematic effects are taken into account. Non-circular beams in CMB experiments can cause large systematic deviation in the angular power spectrum, not only by modifying the measurement at a given multipole, but also introducing coupling between different multipoles through a deterministic bias matrix. Here we add a mechanism for emulating the effect of a full bias matrix to the PLANCK likelihood code through the parameter estimation code SCoPE. We show that if the angular power spectrum was measured with a non-circular beam, the assumption of circular Gaussian beam or considering only the diagonal part of the bias matrix can lead to huge error in parameter estimation. We demonstrate that, at least for elliptical Gaussian beams, use of scalar beam window functions obtained via Monte Carlo simulations starting from a fiducial spectrum, as implemented in PLANCK analyses for example, leads to only few percent of sigma deviation of the best-fit parameters. However, we notice more significant differences in the posterior distributions for some of the parameters, which would in turn lead to incorrect errorbars. These differences can be reduced, so that the errorbars match within few percent, by adding an iterative reanalysis step, where the beam window function would be recomputed using the best-fit spectrum estimated in the first step.
ISSN:1475-7516
1475-7516
DOI:10.1088/1475-7516/2015/03/048