Cosmography with DESI-DR1 Cosmic Chronometers: Direct H(z) measurements from Luminous Red Galaxy ages
Carlos A. Álvarez, Marcos M. Cueli, Balakrishna S. Haridasu, Michele Moresco, Martina Torsello, Alessandro Bressan, Lumen Boco, Luigi Danese, Andrea Lapi
Abstract
Providing robust redshift estimates for almost 3 million luminous red galaxies (LRGs), the Dark Energy Spectroscopic Instrument (DESI) offers a unique opportunity to test the expansion rate of the Universe with independent approaches. We apply the cosmic chronometer method to derive new, independent constraints on the Hubble parameter at 0.3<z<1.2 from the differential age evolution of DESI LRGs. We select spectra applying spectroscopic cuts to ensure sample purity and remove contamination by star-forming objects, then build a robust sample of cosmic chronometers (CCs) by stacking to obtain stable, high signal-to-noise (S/N) spectra, which also serves as a democratic binning choice for the t-z plane. Ages are estimated by measuring Lick indices on the stacked spectra and fitting them with a theoretical stellar population model. We obtain t-z relations from which we derive H(z) constraints via two independent approaches: a fit with a pivotal-redshift cosmography, and a direct estimate from the original CC method. The cosmographic fit yields posteriors for the kinematic parameters \Hz0, qz0, jz0\ compatible with currently considered cosmologies, giving a precision-level estimate of H(z). We provide the maximum-a-posteriori (MAP) H(z) estimate, an array of the median confidence region in the H-z plane, and its covariance matrix. We also leverage the redshift distributions of the t-z relation for different velocity dispersion groups to obtain two independent local measurements using the discrete approximation H(z) ≈ -Δz/[Δt (1+z)]; the one from the reddest envelope of CCs gives H(z ≈ 0.61) = 88.5+6.7-12.6 (stat.) 8.1 (syst.) km s-1 Mpc-1. Systematic uncertainties for both the cosmographic and discrete H(z) measurements come from a comprehensive analysis of all methodological choices in the data treatment.
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