Photometric SN Ia Candidates from the Three-Year SDSS-II SN Survey Data
  We analyze the three-year SDSS-II Superernova (SN) Survey data and identify a
sample of 1070 photometric SN Ia candidates based on their multi-band light
curve data. This sample consists of SN candidates with no spectroscopic
confirmation, with a subset of 210 candidates having spectroscopic redshifts of
their host galaxies measured, while the remaining 860 candidates are purely
photometric in their identification. We describe a method for estimating the
efficiency and purity of photometric SN Ia classification when spectroscopic
confirmation of only a limited sample is available, and demonstrate that SN Ia
candidates from SDSS-II can be identified photometrically with ~91% efficiency
and with a contamination of ~6%. Although this is the largest uniform sample of
SN candidates to date for studying photometric identification, we find that a
larger spectroscopic sample of contaminating sources is required to obtain a
better characterization of the background events. A Hubble diagram using SN
candidates with no spectroscopic confirmation, but with host galaxy
spectroscopic redshifts, yields a distance modulus dispersion that is only ~20
- 40% larger than that of the spectroscopically-confirmed SN Ia sample alone
with no significant bias. A Hubble diagram with purely photometric
classification and redshift-distance measurements, however, exhibit biases that
require further investigation for precision cosmology.
