Photometric Estimates of Redshifts and Distance Moduli for Type Ia Supernovae

TL;DR

This paper introduces a photometric redshift estimation method for Type Ia supernovae that simultaneously fits light curves and redshifts, enabling efficient analysis of large survey data without extensive spectroscopy.

Contribution

The paper presents the LCFIT+Z technique integrated with existing light-curve fitters, improving photometric redshift and distance estimates for supernovae in large surveys.

Findings

Achieves redshift precision comparable to spectroscopic methods.

Effective on both real and simulated supernova data.

Compatible with upcoming large-scale surveys like LSST.

Abstract

Large planned photometric surveys will discover hundreds of thousands of supernovae (SNe), outstripping the resources available for spectroscopic follow-up and necessitating the development of purely photometric methods to exploit these events for cosmological study. We present a light-curve fitting technique for SN Ia photometric redshift (photo-z) estimation in which the redshift is determined simultaneously with the other fit parameters. We implement this "LCFIT+Z" technique within the frameworks of the MLCS2k2 and SALT-II light-curve fit methods and determine the precision on the redshift and distance modulus. This method is applied to a spectroscopically confirmed sample of 296 SNe Ia from the SDSS-II Supernova Survey and 37 publicly available SNe Ia from the Supernova Legacy Survey (SNLS). We have also applied the method to a large suite of realistic simulated light curves for existing and planned surveys, including SDSS, SNLS, and LSST. When intrinsic SN color fluctuations are included, the photo-z precision for the simulation is consistent with that in the data. Finally, we compare the LCFIT+Z photo-z precision with previous results using color-based SN photo-z estimates.