Likelihood Analysis of CMB Temperature and Polarization Power Spectra
Samira Hamimeche, Antony Lewis
Abstract
Microwave background temperature and polarization observations are a powerful
way to
constrain
cosmological
parameters if the likelihood function can be
calculated accurately. The temperature and polarization fields are correlated,
partial sky coverage correlates power spectrum estimators at different ell, and
the likelihood function for a theory spectrum given a set of observed
estimators is non-Gaussian. An accurate analysis must model all these
properties. Most existing likelihood approximations are good enough for a
temperature-only analysis, however they cannot reliably handle a
temperature-polarization correlations. We give a new general approximation
applicable for correlated Gaussian fields observed on part of the sky. The
approximation models the non-Gaussian form exactly in the ideal full-sky limit
and is fast to evaluate using a pre-computed covariance matrix and set of power
spectrum estimators. We show with simulations that it is good enough to obtain
correct results at ell >~ 30 where an exact calculation becomes impossible. We
also show that some Gaussian approximations give reliable parameter constraints
even though they do not capture the shape of the likelihood function at each
ell accurately. Finally we test the approximations on simulations with
realistically anisotropic noise and asymmetric foreground mask.
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Antony Lewis (2008-07-12)