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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
earth and planetary sciences
Improved constraints on cosmological parameters from Type Ia supernova data
Monthly Notices of the Royal Astronomical Society, Volume 418, No. 4, Year 2011
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Description
We present a new method based on a Bayesian hierarchical model to extract constraints on cosmological parameters from Type Ia supernova (SNIa) data obtained with the SALT-II light-curve fitter. We demonstrate with simulated data sets that our method delivers tighter statistical constraints on the cosmological parameters over 90per cent of the time, that it reduces statistical bias typically by a factor of ~2-3 and that it has better coverage properties than the usual χ2 approach. As a further benefit, a full posterior probability distribution for the dispersion of the intrinsic magnitude of SNe is obtained. We apply this method to recent SNIa data, and by combining them with cosmic microwave background and baryonic acoustic oscillations data, we obtain Ωm= 0.28 ± 0.02, ΩΛ= 0.73 ± 0.01 (assuming w=-1) and Ωm= 0.28 ± 0.01,w=-0.90 ± 0.05 (assuming flatness; statistical uncertainties only). We constrain the intrinsic dispersion of the B-band magnitude of the SNIa population, obtaining σintμ= 0.13 ± 0.01mag. Applications to systematic uncertainties will be discussed in a forthcoming paper. © 2011 The Authors Monthly Notices of the Royal Astronomical Society © 2011 RAS.
Authors & Co-Authors
March, Marisa Cristina
United Kingdom, London
Imperial College London
Trotta, Roberto
United Kingdom, London
Imperial College London
South Africa, Muizenberg
African Institute for Mathematical Sciences
Berkes, P.
United States, Waltham
Brandeis University
Starkman, Glenn D.
United States, Cleveland
Case Western Reserve University
Vaudrevange, P. M.
United States, Cleveland
Case Western Reserve University
Germany, Hamburg
Deutsches Elektronen-synchrotron Desy
Statistics
Citations: 63
Authors: 5
Affiliations: 5
Identifiers
Doi:
10.1111/j.1365-2966.2011.19584.x
ISSN:
00358711
e-ISSN:
13652966
Research Areas
Health System And Policy
Study Design
Cross Sectional Study