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ABSTRACT 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 σint ≲ 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. 

Abstract We present Young Supernova Experimentgrizyphotometry of SN 2021hpr, the third Type Ia supernova sibling to explode in the Cepheid calibrator galaxy, NGC 3147. Siblings are useful for improving SN-host distance estimates and investigating their contributions toward the SN Ia intrinsic scatter (post-standardization residual scatter in distance estimates). We thus develop a principled Bayesian framework for analyzing SN Ia siblings. At its core is the cosmology-independent relative intrinsic scatter parameter,σ_Rel: the dispersion of siblings distance estimates relative to one another within a galaxy. It quantifies the contribution toward the total intrinsic scatter,σ₀, from within-galaxy variations about the siblings’ common properties. It also affects the combined distance uncertainty. We present analytic formulae for computing aσ_Relposterior from individual siblings distances (estimated using any SN model). Applying a newly trainedBayeSNmodel, we fit the light curves of each sibling in NGC 3147 individually, to yield consistent distance estimates. However, the wideσ_Relposterior meansσ_Rel≈σ₀is not ruled out. We thus combine the distances by marginalizing overσ_Relwith an informative prior:σ_Rel∼U(0,σ₀). Simultaneously fitting the trio’s light curves improves constraints on distanceandeach sibling’s individual dust parameters, compared to individual fits. Higher correlation also tightens dust parameter constraints. Therefore,σ_Relmarginalization yields robust estimates of siblings distances for cosmology, as well as dust parameters for sibling–host correlation studies. Incorporating NGC 3147's Cepheid distance yieldsH₀= 78.4 ± 6.5 km s⁻¹Mpc⁻¹. Our work motivates analyses of homogeneous siblings samples, to constrainσ_Reland its SN-model dependence.