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First Cosmology Results using Type Ia Supernova from the Dark Energy Survey: Simulations to Correct Supernova Distance Biases | | R. Kessler
; D. Brout
; C. B. D'Andrea
; T. M. Davis
; S. R. Hinton
; A. G. Kim
; J. Lasker
; C. Lidman
; E. Macaulay
; A. Möller
; M. Sako
; D. Scolnic
; M. Smith
; M. Sullivan
; B. Zhang
; P. Andersen
; J. Asorey
; A. Avelino
; J. Calcino
; D. Carollo
; P. Challis
; M. Childress
; A. Clocchiatti
; S. Crawford
; A. V. Filippenko
; R. J. Foley
; K. Glazebrook
; J. K. Hoormann
; E. Kasai
; R. P. Kirshner
; G. F. Lewis
; K. S. Mandel
; M. March
; E. Morganson
; D. Muthukrishna
; P. Nugent
; Y.-C. Pan
; N. E. Sommer
; E. Swann
; R. C. Thomas
; B. E. Tucker
; S. A. Uddin
; T. M. C. Abbott
; S. Allam
; J. Annis
; S. Avila
; M. Banerji
; K. Bechtol
; E. Bertin
; D. Brooks
; E. Buckley-Geer
; D. L. Burke
; A. Carnero Rosell
; M. Carrasco Kind
; J. Carretero
; F. J. Castander
; M. Crocce
; L. N. da Costa
; C. Davis
; J. De Vicente
; S. Desai
; H. T. Diehl
; P. Doel
; T. F. Eifler
; B. Flaugher
; P. Fosalba
; J. Frieman
; J. Garcia-Bellido
; E. Gaztanaga
; D. W. Gerdes
; D. Gruen
; R. A. Gruendl
; G. Gutierrez
; W. G. Hartley
; D. L. Hollowood
; K. Honscheid
; D. J. James
; M. W. G. Johnson
; M. D. Johnson
; E. Krause
; K. Kuehn
; N. Kuropatkin
; O. Lahav
; T. S. Li
; M. Lima
; J. L. Marshall
; P. Martini
; F. Menanteau
; C. J. Miller
; R. Miquel
; B. Nord
; A. A. Plazas
; A. Roodman
; E. Sanchez
; V. Scarpine
; R. Schindler
; M. Schubnell
; S. Serrano
; I. Sevilla-Noarbe
; M. Soares-Santos
; F. Sobreira
; E. Suchyta
; G. Tarle
; D. Thomas
; A. R. Walker
; Y. Zhang
; | | Date: |
7 Nov 2018 | | Abstract: | We describe catalog-level simulations of Type Ia Supernova (SN Ia) light
curves in the Dark Energy Survey Supernova Program (DES-SN), and in
low-redshift samples from the Center for Astrophysics (CfA) and the Carnegie
Supernova Project (CSP). These simulations are used to model biases from
selection effects and light curve analysis, and to determine bias corrections
for SN Ia distance moduli that are used to measure cosmological parameters. To
generate realistic light curves the simulation uses a detailed SN Ia model,
incorporates information from observations (PSF, sky noise, zero point), and
uses summary information (e.g., detection efficiency vs. signal to noise ratio)
based on 10,000 fake SN light curves whose fluxes were overlaid on images and
processed with our analysis pipelines. The quality of the simulation is
illustrated by predicting distributions observed in the data. Averaging within
redshift bins, we find distance modulus biases up to 0.05 mag over the redshift
ranges of the low-z and DES-SN samples. For individual events, particularly
those with extreme red or blue color, distance biases can reach 0.4 mag.
Therefore, accurately determining bias corrections is critical for precision
measurements of cosmological parameters. Files used to make these corrections
are available at this https URL | | Source: | arXiv, 1811.2379 | | Services: | Forum | Review | PDF | Favorites | |
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