Reconstructing generalized ghost condensate model with dynamical dark energy parametrizations and observational datasets
| dc.creator | Zhang, Jingfei | |
| dc.creator | Zhang, Xin | |
| dc.creator | Liu, Hongya | |
| dc.date | 2006-12-21 | |
| dc.date | 2007-03-21 | |
| dc.date.accessioned | 2026-07-07T11:20:53Z | |
| dc.date.available | 2026-07-07T11:20:53Z | |
| dc.description | Observations of high-redshift supernovae indicate that the universe is accelerating at the present stage, and we refer to the cause for this cosmic acceleration as ``dark energy''. In particular, the analysis of current data of type Ia supernovae (SNIa), cosmic large-scale structure (LSS), and the cosmic microwave background (CMB) anisotropy implies that, with some possibility, the equation-of-state parameter of dark energy may cross the cosmological-constant boundary ($w=-1$) during the recent evolution stage. The model of ``quintom'' has been proposed to describe this $w=-1$ crossing behavior for dark energy. As a single-real-scalar-field model of dark energy, the generalized ghost condensate model provides us with a successful mechanism for realizing the quintom-like behavior. In this paper, we reconstruct the generalized ghost condensate model in the light of three forms of parametrization for dynamical dark energy, with the best-fit results of up-to-date observational data. | |
| dc.description | 8 pages, 3 figures; references added; accepted for publication in Mod. Phys. Lett. A | |
| dc.identifier | https://arxiv.org/abs/astro-ph/0612642 | |
| dc.identifier | http://arxiv.org/abs/astro-ph/0612642 | |
| dc.identifier | Mod.Phys.Lett.A23:139-152,2008 | |
| dc.identifier | doi:10.1142/S0217732308023505 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/194103 | |
| dc.subject | Astrophysics | |
| dc.subject | General Relativity and Quantum Cosmology | |
| dc.subject | High Energy Physics - Phenomenology | |
| dc.subject | High Energy Physics - Theory | |
| dc.title | Reconstructing generalized ghost condensate model with dynamical dark energy parametrizations and observational datasets | |
| dc.type | text |