A Multifrequency approach of the cosmological parameter estimation in presence of extragalactic point sources

TL;DR

This paper introduces a multifrequency method to improve cosmological parameter estimation by effectively modeling and marginalizing over extragalactic point source contamination using Planck data and MCMC analysis.

Contribution

It presents a minimal-parameter model for unresolved point sources and secondary anisotropies, integrated into a robust MCMC framework for unbiased cosmological inference.

Findings

Method effectively accounts for point source contamination.

Constraints on cosmological parameters remain unbiased.

Parameters for unresolved sources are not prior dominated.

Abstract

We present a multifrequency approach which optimizes the constraints on cosmological parameters with respect to extragalactic sources and secondary anisotropies contamination on small scales. We model with a minimal number of parameters the expected dominant contaminations in intensity, such as unresolved point sources and the thermal Sunyaev-Zeldovich effect. The model for unresolved point sources, either Poisson distributed or clustered, uses data from Planck early results. The overall amplitude of these contributions are included in a Markov Chain Monte Carlo analysis for the estimate of cosmological parameters. We show that our method is robust: as long as the main contaminants are taken into account the constraints on the cosmological parameters are unbiased regardless of the realistic uncertainties on the contaminants. We show also that the two parameters modelling unresolved points sources are not prior dominated.