Volume 506, Number 3, November II 2009
|Page(s)||1095 - 1105|
|Section||Cosmology (including clusters of galaxies)|
|Published online||03 September 2009|
Cosmological parameter extraction and biases from type Ia supernova magnitude evolution *
Centre de Physique Théorique, Université de Provence, CNRS de Luminy case 907, 13288 Marseille Cedex 9, France e-mail: firstname.lastname@example.org
2 Centre de Physique des Particules de Marseille, Université de la Mediterranée, CNRS de Luminy case 907, 13288 Marseille Cedex 9, France
Accepted: 11 August 2009
We study different one-parametric models of type Ia supernova magnitude evolution on cosmic time scales. Constraints on cosmological and supernova evolution parameters are obtained by combined fits on the actual data coming from supernovae, the cosmic microwave background, and baryonic acoustic oscillations. We find that the best-fit values imply supernova magnitude evolution such that high-redshift supernovae appear some percent brighter than would be expected in a standard cosmos with a dark energy component. However, the errors on the evolution parameters are of the same order, and data are consistent with nonevolving magnitudes at the level, except for special cases. We simulate a future data scenario where SN magnitude evolution is allowed for, and neglect the possibility of such an evolution in the fit. We find the fiducial models for which the wrong model assumption of nonevolving SN magnitude is not detectable, and for which biases on the fitted cosmological parameters are introduced at the same time. Of the cosmological parameters, the overall mass density has the strongest chances to be biased due to the wrong model assumption. Whereas early-epoch models with a magnitude offset show up to be not too dangerous when neglected in the fitting procedure, late epoch models with have high chances of undetectably biasing the fit results.
Key words: cosmology: cosmological parameters / cosmology: observations / stars: supernovae: general / surveys
© ESO, 2009
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.