Real-time analysis and selection biases in the Supernova Legacy Survey
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 spectroscop...
| Main Authors: | , , , , , , , , , , , , , , , |
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| Format: | Journal article |
| Language: | English |
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2010
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| _version_ | 1797099074013364224 |
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| author | Perrett, K Balam, D Pritchet, C Conley, A Carlberg, R Astier, P Balland, C Basa, S Fouchez, D Guy, J Hardin, D Hook, I Howell, D Pain, R Regnault, N Sullivan, M |
| author_facet | Perrett, K Balam, D Pritchet, C Conley, A Carlberg, R Astier, P Balland, C Basa, S Fouchez, D Guy, J Hardin, D Hook, I Howell, D Pain, R Regnault, N Sullivan, M |
| author_sort | Perrett, K |
| collection | OXFORD |
| description | 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 ∼ 0.6, with a significant shift in the average magnitude of the spectroscopically confirmed SN Ia sample toward brighter values for z ≳ 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. © 2010. The American Astronomical Society. All rights reserved. |
| first_indexed | 2024-03-07T05:18:26Z |
| format | Journal article |
| id | oxford-uuid:de0b2309-ddfa-4e5a-a042-026d1c611c51 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T05:18:26Z |
| publishDate | 2010 |
| record_format | dspace |
| spelling | oxford-uuid:de0b2309-ddfa-4e5a-a042-026d1c611c512022-03-27T09:29:18ZReal-time analysis and selection biases in the Supernova Legacy SurveyJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:de0b2309-ddfa-4e5a-a042-026d1c611c51EnglishSymplectic Elements at Oxford2010Perrett, KBalam, DPritchet, CConley, ACarlberg, RAstier, PBalland, CBasa, SFouchez, DGuy, JHardin, DHook, IHowell, DPain, RRegnault, NSullivan, MThe 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 ∼ 0.6, with a significant shift in the average magnitude of the spectroscopically confirmed SN Ia sample toward brighter values for z ≳ 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. © 2010. The American Astronomical Society. All rights reserved. |
| spellingShingle | Perrett, K Balam, D Pritchet, C Conley, A Carlberg, R Astier, P Balland, C Basa, S Fouchez, D Guy, J Hardin, D Hook, I Howell, D Pain, R Regnault, N Sullivan, M Real-time analysis and selection biases in the Supernova Legacy Survey |
| title | Real-time analysis and selection biases in the Supernova Legacy Survey |
| title_full | Real-time analysis and selection biases in the Supernova Legacy Survey |
| title_fullStr | Real-time analysis and selection biases in the Supernova Legacy Survey |
| title_full_unstemmed | Real-time analysis and selection biases in the Supernova Legacy Survey |
| title_short | Real-time analysis and selection biases in the Supernova Legacy Survey |
| title_sort | real time analysis and selection biases in the supernova legacy survey |
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