Latest Supernova data in the framework of Generalized Chaplygin Gas model

Abstract

We use the most recent Type-Ia Supernova data in order to study the dark energy - dark matter unification approach in the context of the Generalized Chaplygin Gas (GCG) model. Rather surprisingly, we find that data allow models with $\alpha > 1$. We have studied how the GCG adjusts flat and non-flat models, and our results show that GCG is consistent with flat case upto 68% confidence level. Actually this holds even if one relaxes the flat prior assumption. We have also analysed what one should expect from a future experiment such as SNAP. We find that there is a degeneracy between the GCG model and a XCDM model with a phantom-like dark energy component.