Evaluating the Calibration of SN Ia Anchor Datasets with a Bayesian
  Hierarchical Model
  Inter-survey calibration remains an important systematic uncertainty in
cosmological studies using type Ia supernova (SNe Ia). Ideally, each survey
would measure its system throughputs, for instance with bandpass measurements
combined with observations of well-characterized spectrophotometric standard
stars; however, many important nearby-SN surveys have not done this. We
recalibrate these surveys by tying their tertiary survey stars to Pan-STARRS1
g, r, and i, and SDSS/CSP u. This improves upon previous recalibration efforts
by taking the spatially variable zeropoints of each telescope/camera into
account, and applying improved color transformations in the surveys' natural
instrumental photometric systems. Our analysis uses a global hierarchical model
of the data which produces a covariance matrix of magnitude offsets and
bandpass shifts, quantifying and reducing the systematic uncertainties in the
calibration. We call our method CROSS-CALIBration with a Uniform Reanalysis
(X-CALIBUR). This approach gains not only from a sophisticated analysis, but
also from simply tying our calibration to more color calibrators, rather than
just the one color calibrator (BD+17 4708) as many previous efforts have done.
The results presented here have the potential to help understand and improve
calibration uncertainties upcoming SN Ia cosmological analyses.
