2023MNRAS.524..235D

The local distance ladder estimate of the Hubble constant (H₀) is important in cosmology, given the recent tension with the early universe inference. We estimate H₀ from the Type Ia supernova (SN Ia) distance ladder, inferring SN Ia distances with the hierarchical Bayesian SED model, BayeSN. This method has a notable advantage of being able to continuously model the optical and near-infrared (NIR) SN Ia light curves simultaneously. We use two independent distance indicators, Cepheids or the tip of the red giant branch (TRGB), to calibrate a Hubble-flow sample of 67 SNe Ia with optical and NIR data. We estimate H₀ = 74.82 ± 0.97 (stat) $\pm \, 0.84$ (sys) km ${\rm s}^{-1}\, {\rm Mpc}^{-1}$ when using the calibration with Cepheid distances to 37 host galaxies of 41 SNe Ia, and 70.92 ± 1.14 (stat) $\pm \, 1.49$ (sys) km ${\rm s}^{-1}\, {\rm Mpc}^{-1}$ when using the calibration with TRGB distances to 15 host galaxies of 18 SNe Ia. For both methods, we find a low intrinsic scatter σ_int ≲ 0.1 mag. We test various selection criteria and do not find significant shifts in the estimate of H₀. Simultaneous modelling of the optical and NIR yields up to ∼15 per cent reduction in H₀ uncertainty compared to the equivalent optical-only cases. With improvements expected in other rungs of the distance ladder, leveraging joint optical-NIR SN Ia data can be critical to reducing the H₀ error budget.