Exploring the Latest Union2 SNIa Dataset by Using Model-Independent Parametrization Methods

TL;DR

This study analyzes the Union2 supernova dataset combined with CMB and BAO data using model-independent methods to investigate dark energy's behavior, finding consistency with a cosmological constant but limited data to distinguish models.

Contribution

It applies two model-independent parametrization methods to the Union2 dataset combined with other cosmological data, assessing their effectiveness and implications for dark energy models.

Findings

Union2 dataset is consistent with a cosmological constant at 1σ.

Current data cannot distinguish between parametrization methods.

Simple models fit data better than complex ones.

Abstract

We explore the cosmological consequences of the recently released Union2 sample of 557 Type Ia supernovae (SNIa). Combining this latest SNIa dataset with the Cosmic microwave background (CMB) anisotropy data from the Wilkinson Microwave Anisotropy Probe 7 year (WMAP7) observations and the baryon acoustic oscillation (BAO) results from the Sloan Digital Sky Survey (SDSS) Data Release 7 (DR7), we measure the dark energy density function $f(z)\equiv \rho_{de}(z)/\rho_{de}(0)$ as a free function of redshift. Two model-independent parametrization methods (the binned parametrization and the polynomial interpolation parametrization) are used in this paper. By using the $\chi^2$ statistic and the Bayesian information criterion, we find that the current observational data are still too limited to distinguish which parametrization method is better, and a simple model has advantage in fitting observational data than a complicated model. Moreover, it is found that all these parametrizations demonstrate that the Union2 dataset is still consistent with a cosmological constant at 1$\sigma$ confidence level. Therefore, the Union2 dataset is different from the Constitution SNIa dataset, which more favors a dynamical dark energy.