Likelihood methods for CMB experiments

TL;DR

This paper reviews likelihood-based methods for analyzing CMB data across various scales, emphasizing their role in estimating cosmological parameters and handling uncertainties in temperature and polarization measurements.

Contribution

It provides a comprehensive comparison of spatial and harmonic domain likelihood approaches used in CMB data analysis, highlighting their strengths and limitations.

Findings

Comparison of pixel-based and harmonic domain methods

Assessment of each approach's accuracy and computational efficiency

Guidance on selecting likelihood methods for different CMB experiments

Abstract

A great deal of experimental effort is currently being devoted to the precise measurements of the cosmic microwave background (CMB) sky in temperature and polarisation. Satellites, balloon-borne, and ground-based experiments scrutinize the CMB sky at multiple scales, and therefore enable to investigate not only the evolution of the early Universe, but also its late-time physics with unprecedented accuracy. The pipeline leading from time ordered data as collected by the instrument to the final product is highly structured. Moreover, it has also to provide accurate estimates of statistical and systematic uncertainties connected to the specific experiment. In this paper, we review likelihood approaches targeted to the analysis of the CMB signal at different scales, and to the estimation of key cosmological parameters. We consider methods that analyze the data in the spatial (i.e., pixel-based) or harmonic domain. We highlight the most relevant aspects of each approach and compare their performance.