The Generalized Chaplygin Gas ( GCG ) with the equation of state p = - \frac { A } { { \rho } ^ { \alpha } } was recently proposed as a candidate for dark energy in the Universe .
In this paper we confront the GCG with SNIa data using avaliable samples .
Specifically we have tested the GCG cosmology in three different classes of models with ( 1 ) \Omega _ { m } = 0.3 , \Omega _ { Ch } = 0.7 ; ( 2 ) \Omega _ { m } = 0.05 , \Omega _ { Ch } = 0.95 and ( 3 ) \Omega _ { m } = 0 , \Omega _ { Ch } = 1 , as well as a model without prior assumptions on \Omega _ { m } .
The best fitted models are obtained by minimalizing the \chi ^ { 2 } function .
We supplement our analysis with confidence intervals in the ( A _ { 0 } , \alpha ) plane by marginalizing the probability density functions over remaining parameters assuming uniform priors .
We have also derived one-dimensional probability distribution functions for \Omega _ { Ch } obtained from joint marginalization over \alpha and A _ { 0 } .
The maximum value of such PDF provides the most probable value of \Omega _ { Ch } within the full class of GCG models .
The general conclusion is that SNIa data give support to the Chaplygin gas ( with \alpha = 1 ) .
However noticeable preference of A _ { 0 } values close to 1 means that the \alpha dependence becomes insignificant .
It is reflected on one dimensional PDFs for \alpha which turned out to be flat meaning that the power of present supernovae data to discriminate between various GCG models ( differing by \alpha ) is weak .
Extending our analysis by relaxing the prior assumption of the flatness of the Universe leads to the result that even though the best fitted values of \Omega _ { k } are formally non-zero , still they are close to the flat case .
Our results show clearly that in GCG cosmology distant ( i.e . z > 1 ) supernovae should be brighter than in \Lambda CDM model .
Therefore one can expect that future supernova experiments ( e.g. , SNAP ) having access to higher redshifts will eventually resolve the issue whether the dark energy content of the Universe could be described as a the Chaplygin gas .
Moreover , it would be possible to differentiate between models with various value of \alpha parameter and/or discriminated between GCG , Cardassian and \Lambda CDM models .
This discriminative power of the forthcoming mission has been demonstrated on simulated SNAP data .