A sound-horizon-free measurement of the Hubble constant from DESI DR2 baryon acoustic oscillations using artificial neural networks

Abstract

We present a model-independent, sound-horizon-free measurement of the Hubble constant $H_0$ using baryon acoustic oscillation tracers from the Dark Energy Spectroscopic Instrument Data Release 2. The function reconstructions are performed using the artificial neural network method, which is a completely data-driven approach that avoids the mild $\Lambda$CDM prior dependence. Our approach is based on the distance duality relation and combines three complementary observational probes, such as Type\,Ia supernovae, cosmic chronometer, and DESI DR2 BAO -- without requiring any knowledge of the sound horizon scale $r_d$ or any assumption about the absolute luminosity of SNe\,Ia. We obtain a joint constraint of $H_0=71.5\pm 2.2$\,km\,s${}^{-1}$\,Mpc${}^{-1}$ at 68\% confidence for 1000 bootstrap realisations and 4096 neurons, which is consistent with the TRGB result and the SH0ES measurement within $0.6\sigma$, consistent with the Planck 2020 result within $2\sigma$. Our results favor a higher value of $H_0$ compared to the Planck CMB inference, adding independent support for the reality of the Hubble tension.

10 pages, 5 figures, version accepted for publication in Physical Review D