Survey requirements for accurate and precise photometric redshifts for Type Ia supernovae

Abstract

In this paper we advance the simple analytic photometric redshift estimator for Type Ia supernovae (SNe Ia) proposed by Wang, and use it to study simulated SN Ia data. We find that better than 0.5 per cent accuracy in zphot{with σ[(zphot−zspec)/(1 +zspec)] < 0.005} is possible for SNe Ia with well‐sampled light curves in three observed passbands (riz) with a signal‐to‐noise ratio of 25 at peak brightness, if the extinction by dust is negligible. The corresponding bias in zphot (the mean of zphot−zspec) is 5.4 × 10−4. If dust extinction is taken into consideration in the riz observer‐frame light curves, the accuracy in zphot deteriorates to 4.4 per cent, with a bias in zphot of 8.0 × 10−3. Adding the g‐band light curve improves the accuracy in zphot to 2.5 per cent, and reduces the bias in zphot to − 1.5 × 10−3. Our results have significant implications for the design of future photometric surveys of SNe Ia from both ground and space telescopes. Accurate and precise photometric redshifts boost the cosmological utility of such surveys.

Analytic photometric redshift estimator for Type Ia supernovae from the Large Synoptic Survey Telescope

“…The improvements that we have made to the photo-z estimator in this work reduces the estimated errors on the photo-z's, σz phot /(1 + z phot ), from 2.5% to 2%, compared to Wang, Narayan, & Wood-Vasey (2007). More importantly, it reduces the bias in z phot (the mean of z phot − zspec), from −1.5 × 10 −3 to −9 × 10 −5 (a reduction factor of 16.67).…”

“…The prototype photo-z estimator we use here was developed in Wang (2007) and Wang, Narayan, and Wood-Vasey (2007). This estimator uses the fluxes in griz (or riz) at the epoch of i maximum flux to make an effective K-correction to the i flux.…”

“…The coefficients cj (j = 1, 2, ..., 2n + 3) are found by using a training set of SNe Ia with lightcurves in n passbands and measured spectroscopic redshifts. We use the same modified jackknife technique as in Wang, Narayan, and Wood-Vasey (2007) to estimate the mean and the covariance matrix of cj (see Sec. 4).…”

“…In this paper, we build on the previous work by Wang (2007) and Wang, Narayan, & Wood-Vasey (2007), and present a simple analytic photo-z estimator. We apply this photo-z estimator to 55,422 simulated SNe Ia generated using the SNANA package (Kessler et al 2009b) with the LSST filters.…”

“…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.…”