Supernova Legacy Survey (SNLS) : real time operations and photometric analysis

TL;DR

The paper discusses the SNLS project, focusing on real-time supernova detection, photometric analysis, and strategies to minimize selection biases in a large sample of supernovae for cosmological studies.

Contribution

It introduces the real-time processing pipeline and offline selection methods for supernova candidates in the SNLS, enhancing data quality and bias reduction.

Findings

Successful real-time detection of supernovae

Sample of ~700 Type Ia supernovae expected

Methods to reduce selection biases implemented

Abstract

Type Ia supernovae (SN Ia) have provided the first evidence for an accelerating universe and for the existence of an unknown ``dark energy'' driving this expansion. The 5-year Supernova Legacy Survey (SNLS) will deliver \~700 type Ia supernovae and as many type II supernovae with well-sampled light curves in 4 filters g', r', i' and z'. The current status of the project will be presented, along with the real time processing leading to the discovery and spectroscopic observation of the supernovae. We also present an offline selection of the SN candidates which aims at identifying and eliminating potential selection biases.