SNIa photometric studies in SNLS

TL;DR

This paper discusses a photometric approach to selecting supernova candidates and estimating their redshifts, aiming to improve dark energy studies in large supernova surveys like SNLS, JDEM, and LSST.

Contribution

It introduces a novel photometry-based method for supernova candidate selection and redshift determination, reducing reliance on spectroscopic measurements.

Findings

Photometric redshifts can effectively replace spectroscopic ones in supernova surveys.

The method improves efficiency in supernova candidate selection.

Application to SNLS data demonstrates promising results.

Abstract

The discovery of accelerated expansion using supernova surveys has been one of the most surprising discoveries in cosmology in the past ten years. Present and future surveys, among which SNLS, JDEM or LSST, are based on samples of a few hundreds to a million supernovae. The measurement of their spectroscopic redshifts to investigate dark energy properties is already by far the limiting aspect of such surveys. In this paper, I will discuss and illustrate with SNLS data an approach based solely on photometry to both select supernova candidates and determine their redshift.