What can be learned about dark energy evolution? - Université Toulouse III - Paul Sabatier - Toulouse INP Accéder directement au contenu
Pré-Publication, Document De Travail Année : 2008

What can be learned about dark energy evolution?

Résumé

We examine constraints obtained from SNIa surveys on a two parameter model of dark energy in which the equation of state $w (z) = P(z) / \rho (z)$ undergoes a transition over a period significantly shorter than the Hubble time. We find that a transition between $w \sim -0.2$ and $w \sim -1$ (the first value being somewhat arbitrary) is allowed at redshifts as low as $0.1$, despite the fact that data extend beyond $z \sim 1$. Surveys with the precision anticipated for space experiments should allow only slight improvement on this constraint, as a transition occurring at a redshift as low as $\sim 0.17$ could still remain undistinguishable from a standard cosmological constant. The addition of a prior on the matter density $\Omega_\MAT = 0.3$ only modestly improves the constraints. Even deep space experiments would still fail to identify a rapid transition at a redshift above $0.5$. These results illustrate that a Hubble diagram of distant SNIa alone will not reveal the actual nature of dark energy at a redshift above $0.2$ and that only the local dynamics of the quintessence field can be infered from a SNIa Hubble diagram. Combinations, however, seem to be very efficient: we found that the combination of present day CMB data and SNIa already excludes a transition at redshifts below $0.8$.
Fichier principal
Vignette du fichier
paper.pdf (301.82 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-00019488 , version 1 (22-02-2006)
hal-00019488 , version 2 (31-03-2006)
hal-00019488 , version 3 (26-05-2008)

Identifiants

Citer

Marian Douspis, Yves Zolnierowski, Alain Blanchard, Alain Riazuelo. What can be learned about dark energy evolution?. 2008. ⟨hal-00019488v3⟩
312 Consultations
466 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More