Testing and selecting dark energy models with lens redshift data

Abstract

In this paper, we compare seven popular dark energy models under the assumption of a flat universe by using the latest observational data of gravitationally-lensed image separations observed in the Cosmic Lens All-Sky Survey (CLASS), the PMN-NVSS Extragalactic Lens Survey (PANELS), the Sloan Digital Sky Survey (SDSS) and other surveys, which are (nearly) complete for the image separation range ${0}^{\ensuremath{'}\ensuremath{'}}.3\ensuremath{\le}\ensuremath{\Delta}\ensuremath{\theta}\ensuremath{\le}{7}^{\ensuremath{'}\ensuremath{'}}$. We combine the 29 lens redshift data with the cosmic microwave background (CMB) observation from the Wilkinson Microwave Anisotropy Probe (WMAP7) results, the baryonic acoustic oscillation (BAO) observation from the spectroscopic Sloan Digital Sky Survey (SDSS) Data Release. The model comparison statistic, the Bayesian information criterion is also applied to assess the worth of the models. This statistic favors models that give a good fit with fewer parameters. Based on this analysis, we find that the simplest cosmological constant model that has only one free parameter is still preferred by the current data. For the other dynamical dark energy models, we find that some of them, such as the Ricci dark energy model, the Affine equation-of-state dark energy, and the generalized Chaplygin gas, can provide good fits to the current data. The Dvali-Gabadadze-Porrati model is the only one-parameter model that can give a rather good fit but also nest $\ensuremath{\Lambda}$ while the three-parameter model, namely, the interactive dark energy, is clearly disfavored by the data, as it is unable to provide a good fit.