Volume 606, October 2017
|Number of page(s)||13|
|Section||Cosmology (including clusters of galaxies)|
|Published online||20 October 2017|
Cosmological constraints on the neutrino mass including systematic uncertainties
1 Laboratoire de l’Accélérateur Linéaire, Univ. Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, 91405 Orsay, France
2 Department of Physics and Astronomy, University of the Western Cape, Robert Sobukwe Road, 7535 Bellville, South Africa
Received: 3 April 2017
Accepted: 31 May 2017
When combining cosmological and oscillations results to constrain the neutrino sector, the question of the propagation of systematic uncertainties is often raised. We address this issue in the context of the derivation of an upper bound on the sum of the neutrino masses (Σmν) with recent cosmological data. This work is performed within the ΛCDM model extended to Σmν, for which we advocate the use of three mass-degenerate neutrinos. We focus on the study of systematic uncertainties linked to the foregrounds modelling in cosmological microwave background (CMB) data analysis, and on the impact of the present knowledge of the reionisation optical depth. This is done through the use of different likelihoods built from Planck data. Limits on Σmν are derived with various combinations of data, including the latest baryon acoustic oscillations (BAO) and Type Ia supernovae (SNIa) results. We also discuss the impact of the preference for current CMB data for amplitudes of the gravitational lensing distortions higher than expected within the ΛCDM model, and add the Planck CMB lensing. We then derive a robust upper limit: Σmν< 0.17 eV at 95% CL, including 0.01eV of foreground systematics. We also discuss the neutrino mass repartition and show that today’s data do not allow one to disentangle normal from inverted hierarchy. The impact on the other cosmological parameters is also reported, for different assumptions on the neutrino mass repartition, and different high and low multipole CMB likelihoods.
Key words: cosmological parameters / neutrinos / methods: data analysis
© ESO, 2017
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