Combining CMB datasets with consistent foreground modelling

TL;DR

This paper develops a unified analysis combining multiple CMB datasets with consistent foreground modelling, enhancing the robustness of cosmological parameter estimation and demonstrating the importance of accurate foreground treatment.

Contribution

It introduces a joint likelihood approach that models all datasets simultaneously, reducing reliance on individual foreground assumptions and improving parameter stability.

Findings

$ m u$CDM parameters are stable across foreground models

Uncertainties in cosmological extensions increase when marginalising over foregrounds

Foreground parameter estimates depend strongly on foreground model assumptions

Abstract

We present a joint cosmological analysis combining data from the Planck satellite, the Atacama Cosmology Telescope, and the South Pole Telescope. We construct a unified likelihood that reproduces the measured temperature and polarisation power spectra by jointly modelling the cosmic microwave background (CMB) signal, Galactic and extragalactic foregrounds, and instrumental systematics across all datasets. We reduce reliance by combining datasets and improve the robustness of parameter estimation by marginalising over the choice of foreground templates. Within this joint analysis, $\Lambda$CDM parameters exhibit remarkable stability with respect to variations in foreground modelling. Parameters for cosmological extensions are more sensitive to these assumptions, with uncertainties increasing by up to 35% in the neutrino sector after marginalising over foreground models. In contrast, the determination of foreground parameters depends more strongly on the assumptions made about the underlying foreground models. Overall, this work demonstrates the feasibility and reliability of a fully joint analysis of current CMB experiments and emphasizes the importance of consistent and accurate foreground modelling for the scientific goals of next-generation, high-sensitivity CMB surveys.