Intrinsic SN Ia light curves

A hierarchical framework coherently models multiple random and uncertain effects, including intrinsic supernova (SN) light curve covariances, dust extinction and reddening, and distances. An improved BayeSN Markov Chain Monte Carlo code computes probabilistic inferences for the hierarchical model by sampling the global probability density of parameters describing individual SNe and the population.

We have applied this hierarchical model to optical and NIR data of 127 SNe Ia from PAIRITEL, CfA3, Carnegie Supernova Project, and the literature. We find an apparent population correlation between the host galaxy extinction AV and the ratio of total-to-selective dust absorption RV. For SNe with low dust extinction, A_V_<~0.4, we find R_V_~2.5-2.9, while at high extinctions, A_V_>~1, low values of R_V_<2 are favored.