Accurate and precise photometric redshifts ( photo-z ’ s ) of Type Ia supernovae ( SNe Ia ) can enable the use of SNe Ia , measured only with photometry , to probe cosmology .
This dramatically increases the science return of supernova surveys planned for the Large Synoptic Survey Telescope ( LSST ) .
In this paper we describe a significantly improved version of the simple analytic photo-z estimator proposed by Wang ( 2007 ) and further developed by Wang , Narayan , and Wood-Vasey ( 2007 ) .
We apply it to 55,422 simulated SNe Ia generated using the SNANA package with the LSST filters .
We find that the estimated errors on the photo-z ’ s , \sigma _ { z _ { phot } } / ( 1 + z _ { phot } ) , can be used as filters to produce a set of photo-z ’ s that have high precision , accuracy , and purity .
Using SN Ia colors as well as SN Ia peak magnitude in the i band , we obtain a set of photo-z ’ s with 2 percent accuracy ( with \sigma ( z _ { phot } - z _ { spec } ) / ( 1 + z _ { spec } ) = 0.02 ) , a bias in z _ { phot } ( the mean of z _ { phot } - z _ { spec } ) of -9 \times 10 ^ { -5 } , and an outlier fraction ( with \left| ( z _ { phot } - z _ { spec } ) / ( 1 + z _ { spec } ) \right| > 0.1 ) of 0.23 percent , with the requirement that \sigma _ { z _ { phot } } / ( 1 + z _ { phot } ) < 0.01 .
Using the SN Ia colors only , we obtain a set of photo-z ’ s with similar quality by requiring that \sigma _ { z _ { phot } } / ( 1 + z _ { phot } ) < 0.007 ; this leads to a set of photo-z ’ s with 2 percent accuracy , a bias in z _ { phot } of 5.9 \times 10 ^ { -4 } , and an outlier fraction of 0.32 percent .