| Description |
Type Ia supernovae (SNe Ia) have been used as standard candles to measure cosmological distances. The initial discovery of the accelerated expansion of the universe was performed using ∼ 50 SNe Ia. Large SNe surveys have increased the number of spectroscopically-confirmed SNe Ia to over a thousand with redshift coverage beyond z = 1. We are now in the age of abundant photometry without the ability for full follow-up spectroscopy of all SN candidates. SN cosmology using these large samples will increasingly rely on robust photometric classification of SN candidates. Photometric classification will increase the sample by including faint SNe as these are preferentially not observed with follow-up spectroscopy. The primary concern with using photometrically classified SNe Ia in cosmology is when a core-collapse SNe is incorrectly classified as an SN Ia. This can be mitigated by obtaining the host galaxy redshift of each SN candidate and using this information as a prior in the photometric classification, removing one degree of freedom. To test the impact of redshift on photometric classification, I have performed an assessment on photometric classification of candidates from the Sloan Digital Sky Survey-II (SDSS-II) SN Survey. I have tested the classification with and without redshift priors by looking at the change of photometric classification, the effect of data quality on photometric classification, and the effect of SN light curve properties on photometric classification. Following our suggested classification scheme, there are a total of 1038 photometrically classified SNe Ia when using a flat redshift prior and 1002 SNe Ia with the spectroscopic redshift. For 912 (91.0%) candidates classified as likely SNe Ia without redshift information, the classification is unchanged when adding the host galaxy redshift. Finally, I investigate the differences in the interpretation of the light curve properties with and without knowledge of the redshift. When using the SALT2 light curve fitter, I find a 17% increase in the number of fits that converge when using the spectroscopic redshift. Without host galaxy redshifts, I find that SALT2 light curve fits are systematically biased towards lower photometric redshift estimates and redder colors in the limit of low signal-to-noise data. |
