A Foreground Model Independent Estimation of Joint Posterior of CMB E mode Polarization over Large Angular Scales

Ujjal Purkayastha, Vipin Sudevan, Rajib Saha

Published 2020-04-18Version 1

Ever since Cosmic Microwave Background (CMB) signal is being measured by various satellites based observations with increasing experimental accuracies there has been a parallel increase in the demand for a CMB reconstruction technique which can provide accurate estimates of CMB signal and the theoretical angular power spectrum along with reliable statistical error estimates associated with them. In this work, we estimate the joint posterior of CMB E mode signal (S) and corresponding theoretical angular power spectrum (C^E_l) over large angular scales given the simulated polarization observations of future generation COrE satellite mission. To generate samples from the joint distribution we employ the ILC technique with prior information of CMB E mode covariance matrix augmented by a Gibbs sampling technique. We estimate the marginalized densities of S and C^E_l using the samples from full-posterior. The best fit cleaned E mode map and the corresponding angular power spectrum agree well with the input E mode map and the sky power spectrum implying accurate reconstruction using COrE like observations. Using the samples C^E_l of all Gibbs chains we estimate the likelihood function P(C^E_l|D) of any arbitrary C^E_l given simulated observed maps (D) of COrE mission following Blackwell-Rao estimator. The likelihood function can be seamlessly integrated to the cosmological parameter estimation method. Apart from producing an accurate estimate of E mode signal over large angular scales our method also builds a connection between the component reconstruction and reliable cosmological parameter estimation using CMB E mode observations over large angular scales. The entire method does not assume any explicit models for E mode foreground components in order to remove them, which is an attractive property since foreground modelling uncertainty does not pose as a challenge in this case.