Photometric type Ia supernova candidates from the three-year SDSS-II SN Survey data.
SAKO M., BASSETT B., CONNOLLY B., DILDAY B., CAMBELL H., FRIEMAN J.A., GLADNEY L., KESSLER R., LAMPEITL H., MARRINER J., MIQUEL R., NICHOL R.C., SCHNEIDER D.P., SMITH M. and SOLLERMAN J.
Abstract (from CDS):
We analyze the three-year Sloan Digital Sky Survey II (SDSS-II) Supernova (SN) Survey data and identify a sample of 1070 photometric Type Ia supernova (SN Ia) candidates based on their multiband 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, exhibits biases that require further investigation for precision cosmology.
cosmology: observations - supernovae: general - surveys
VizieR on-line data:
<Available at CDS (J/ApJ/738/162): table3.dat table4.dat>