Survey Requirements for Accurate and Precise Photometric Redshifts for Type Ia Supernovae

TL;DR

This paper improves a simple photometric redshift estimator for Type Ia supernovae, demonstrating that high accuracy and low bias are achievable with well-sampled lightcurves and specific passbands, impacting future survey designs.

Contribution

It advances an analytic photometric redshift estimator for SNe Ia and evaluates its accuracy under various observational conditions using simulated data.

Findings

Achieves <0.5% accuracy in z_phot with ideal conditions

Adding the g band reduces errors to 2.5%

Dust extinction significantly degrades redshift accuracy

Abstract

In this paper we advance the simple analytic photometric redshift estimator for Type Ia supernovae (SNe Ia) proposed by Wang (2007), and use it to study simulated SN Ia data. We find that better than 0.5% accuracy in z_phot (with RMS[(z_phot-z_spec)/(1+z_spec)]<0.005) is possible for SNe Ia with well sampled lightcurves 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 z_phot (the mean of (z_phot-z_spec)) is 5.4\times 10^{-4}. If dust extinction is taken into consideration in the riz observer-frame lightcurves, the accuracy in z_phot deteriorates to 4.4%, with a bias in z_phot of 8.0\times 10^{-3}. Adding the g band lightcurve improves the accuracy in z_phot to 2.5%, and reduces the bias in z_phot to -1.5\times 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.