Journal
ASTRONOMICAL JOURNAL
Volume 140, Issue 2, Pages 518-532Publisher
IOP PUBLISHING LTD
DOI: 10.1088/0004-6256/140/2/518
Keywords
cosmology: observations; methods: data analysis; supernovae: general; surveys; techniques: photometric
Categories
Funding
- NSERC
- CIAR
- CNRS
- CEA
- Royal Society
- STFC [ST/H002456/1, ST/H000704/1] Funding Source: UKRI
- Science and Technology Facilities Council [ST/H000704/1, ST/H002456/1] Funding Source: researchfish
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The Supernova Legacy Survey (SNLS) has produced a high-quality, homogeneous sample of Type Ia supernovae (SNe Ia) out to redshifts greater than z = 1. In its first four years of full operation (to 2007 June), the SNLS discovered more than 3000 transient candidates, 373 of which have been spectroscopically confirmed as SNe Ia. Use of these SNe Ia in precision cosmology critically depends on an analysis of the observational biases incurred in the SNLS survey due to the incomplete sampling of the underlying SN Ia population. This paper describes our real-time supernova detection and analysis procedures, and uses detailed Monte Carlo simulations to examine the effects of Malmquist bias and spectroscopic sampling. Such sampling effects are found to become apparent at z similar to 0.6, with a significant shift in the average magnitude of the spectroscopically confirmed SN Ia sample toward brighter values for z greater than or similar to 0.75. We describe our approach to correct for these selection biases in our three-year SNLS cosmological analysis (SNLS3) and present a breakdown of the systematic uncertainties involved.
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