Model-independent dark energy reconstruction scheme using the geometrical form of the luminosity-distance relation - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Physical Review D Année : 2006

Model-independent dark energy reconstruction scheme using the geometrical form of the luminosity-distance relation

Résumé

We put forward a new model-independent reconstruction scheme for dark energy which utilizes the expected geometrical features of the luminosity-distance relation. The important advantage of this scheme is that it does not assume explicit ansatzes for cosmological parameters but only some very general cosmological properties via the geometrical features of the reconstructed luminosity-distance relation. Using the recently released supernovae data by the Supernova Legacy Survey together with a phase space representation, we show that the reconstructed luminosity-distance curves best fitting the data correspond to a slightly varying dark energy density with the Universe expanding slightly slower than the LambdaCDM model. However, the LambdaCDM model fits the data at 1sigma significance level and the fact that our best fitting luminosity-distance curve is lower than that of the corresponding LambdaCDM model could be due to systematics. The transition from an accelerating to a decelerating expansion occurs at a redshift larger than z=0.35. Interpreting the dark energy as a minimally coupled scalar field we also reconstruct the scalar field and its potential. We constrain Omegam0 using the baryon acoustic oscillation peak in the SDSS luminous red galaxy sample and find that the best fit is obtained with Omegam0=0.27, in agreement with the CMB data.

Dates et versions

hal-03742896 , version 1 (02-08-2022)

Identifiants

Citer

Stéphane Fay, Reza Tavakol. Model-independent dark energy reconstruction scheme using the geometrical form of the luminosity-distance relation. Physical Review D, 2006, 74, pp.83513. ⟨10.1103/PhysRevD.74.083513⟩. ⟨hal-03742896⟩
5 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More