Comparison of results on $N_\mathrm{eff}$ from various Planck likelihoods

TL;DR

This study compares different Planck likelihood methods for estimating the effective number of relativistic species, highlighting systematic uncertainties mainly due to foreground modeling assumptions.

Contribution

It systematically evaluates how various analysis choices affect $N_{eff}$ estimates, revealing significant systematic uncertainties in current likelihood implementations.

Findings

Systematic uncertainties in $N_{eff}$ are comparable to statistical errors.

Foreground residual modeling assumptions significantly impact $N_{eff}$ estimates.

TE-only likelihoods are less sensitive to foreground residuals.

Abstract

In this paper, we study the estimation of the effective number of relativistic species from a combination of CMB and BAO data. We vary different ingredients of the analysis: the Planck high-$\ell$ likelihoods, the Boltzmann solvers, and the statistical approaches. The variation of the inferred values gives an indication of an additional systematic uncertainty, which is of the same order of magnitude as the error derived from each individual likelihood. We show that this systematic is essentially associated to the assumptions made in the high-$\ell$ likelihoods implementations, in particular for the foreground residuals modellings. We also compare a subset of likelihoods using only the TE power spectra, expected to be less sensitive to foreground residuals.