Type Ia Supernova Light Curve Inference: Hierarchical Bayesian Analysis in the Near Infrared

Understand

We present a comprehensive statistical analysis of the properties of Type Ia SN light curves in the near infrared using recent data from PAIRITEL and the literature.

• We construct a hierarchical Bayesian framework, incorporating several uncertainties including photometric error, peculiar velocities, dust extinction and intrinsic variations, for coherent statistical inference.
• SN Ia light curve inferences are drawn from the global posterior probability of parameters describing both individual supernovae and the population conditioned on the entire SN Ia NIR dataset.
• The logical structure of the hierarchical model is represented by a directed acyclic graph.