Fitting the Constitution SNIa Data with Redshift Binned Parameterization Method
Abstract
In this work, we explore the cosmological consequences of the recently released Constitution sample of 397 Type Ia supernovae (SNIa). By revisiting the Chevallier-Polarski-Linder (CPL) parameterization, we find that, for fitting the Constitution set alone, the behavior of dark energy (DE) significantly deviate from the cosmological constant , where the equation of state (EOS) and the energy density of DE will rapidly decrease along with the increase of redshift . Inspired by this clue, we separate the redshifts into different bins, and discuss the models of a constant or a constant in each bin, respectively. It is found that for fitting the Constitution set alone, and will also rapidly decrease along with the increase of , which is consistent with the result of CPL model. Moreover, a step function model in which rapidly decreases at redshift presents a significant improvement () over the CPL parameterization, and performs better than other DE models. We also plot the error bars of DE density of this model, and find that this model deviates from the cosmological constant at 68.3% confidence level (CL); this may arise from some biasing systematic errors in the handling of SNIa data, or more interestingly from the nature of DE itself. In addition, for models with same number of redshift bins, a piecewise constant model always performs better than a piecewise constant model; this shows the advantage of using , instead of , to probe the variation of DE.
Keywords
Cite
@article{arxiv.0905.0797,
title = {Fitting the Constitution SNIa Data with Redshift Binned Parameterization Method},
author = {Qing-Guo Huang and Miao Li and Xiao-Dong Li and Shuang Wang},
journal= {arXiv preprint arXiv:0905.0797},
year = {2009}
}
Comments
15 pages, 6 figures, 5 tables, to appear in PRD