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arXiv · 1110.6535

The effect of different observational data on the constraints of cosmological parameters

Abstract

The constraints on the $Λ$CDM model from type Ia supernova (SNe Ia) data alone and BAO data alone are similar, so it is worthwhile to compare their constraints on the property of dark energy. We apply the SNLS3 compilation of 472 SNe Ia data, the baryon acoustic oscillation measurement of distance, the cosmic microwave background radiation data from the WMAP7, and the Hubble parameter data to study the effect of their different combinations on the fittings of cosmological parameters in the modified holographic dark energy model and the Chevallier-Polarski-Linder model. Neither BAO nor WMAP7 data alone give good constraint on the equation of state parameter of dark energy, but both WMAP7 data and BAO data help SNe Ia data break the degeneracies among the model parameters, hence tighten the constraint on the variation of equation of state parameter $w_a$, and WMAP7 data do the job a little better. Although BAO and WMAP7 data provide reasonably good constraints on $Ω_m$ and $Ω_k$, they are not able to constrain the dynamics of dark energy. On the other hand, SNe Ia data do not provide good constraints on $Ω_m$ and $Ω_k$, but they provide good constraint on the dynamics of dark energy, especially the variation of the equation of state parameter of dark energy, so we need to combine SNe Ia with BAO and WMAP7 data to probe the property of dark energy. The addition of $H(z)$ data helps better constrain the geometry of the Universe $Ω_k$ and the property of dark energy. For the SNLS SNe Ia data, the nuisance parameters $α$ and $β$ are consistent for all different combinations of the above data, and their impacts on the fittings of cosmological parameters are minimal. By fitting the data to different models, $Λ$CDM model is still consistent with all the observational data.

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BibTeXRIS

Yungui Gong, Qing Gao, Zong-Hong Zhu. 2013-02-04. The effect of different observational data on the constraints of cosmological parameters. https://doi.org/10.1093/mnras%2Fstt120

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