Exploring the Properties of Dark Energy Using Type Ia Supernovae and   Other Datasets
  We reconstruct dark energy properties from two complementary supernova datasets -- the newly released Gold+HST sample and SNLS. The results obtained are consistent with standard $\Lambda$CDM model within $2\sigma$ error bars although the Gold+HST data favour evolving dark energy slightly more than SNLS. Using complementary data from baryon acoustic oscillations and the cosmic microwave background to constrain dark energy, we find that our results in this case are strongly dependent on the present value of the matter density $\Omega_m$. Consequently, no firm conclusions regarding constancy or variability of dark energy density can be drawn from these data alone unless the value of $\Omega_m$ is known to an accuracy of a few percent. However, possible variability is significantly restricted if this data is used in conjunction with supernova data. 
Ujjaini Alam, Varun Sahni and Alexei A. Starobinsky