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Sezione

HEP Colloquia 2024

by Nicola Deiosso (CIEMAT (Madrid))

Europe/Rome
Sala Consiliare (Department of Physics)

Sala Consiliare

Department of Physics

Description

First DESI Cosmology results: Cosmological Constraints from DESI BAO DR1 in combination with external datasets

DESI (Dark Energy Spectroscopic Instrument) is a Stage IV ground-based dark energy project that studies baryon acoustic oscillations (BAO) and the growth of structure through redshift-space distortions with a wide-area galaxy and quasar redshift survey. The entire survey will cover a total area of about 14200 square degrees of sky, with a depth in redshift of 0.1 < z < 4.2.
In this talk the first cosmology results of the DESI project will be presented. These have been obtained using BAO from the Data Release 1 (DR1) sample, that contains ~ 6.1 millions of objects like galaxies, quasars and the Lyman-α forest tracers, covering an area of about 7500 square degrees. The BAO scale provides very robust measurements of the angular distance and Hubble parameter over the DESI redishift range.
The DESI data alone are consistent with ΛCDM with Ωm= 0.295 ± 0.015 and a value of the Hubble constant of H0 = (68.52 ± 0.62) km s -1 Mpc-1. When allowing the cosmological constant to vary, we obtain a value of the dark energy equation of state of w = -0.99 ± 0.15, totally consistent with ΛCDM. However, by allowing the dark energy equation of state to change with time, the combination of DESI, CMB, and supernova data seems to favor dark energy not being the cosmological constant (with w0 > -1 and wa < 0). These results on dark energy will be discussed during the talk. Finally, in the case of flat ΛCDM model with the sum of neutrino mass ∑mν free, combining the DESI and CMB data yields an upper limit ∑mν < 0.072 eV at 95% confidence, limit that returns us evidence on the Normal Hierarchy's preference for neutrino mass, considering, however, that this limit is relaxed by considering models that change the background geometry.

Organized by

Prof. Umberto D'Alesio - umberto.dalesio@ca.infn.it
Dr. Nanako Kato - nanako.kato@dsf.unica.it