Study of parametrized dark energy models with a general non-canonical scalar field

Al Mamon, Abdulla; Das, Sudipta

doi:10.1140/epjc/s10052-016-3982-3

Study of parametrized dark energy models with a general non-canonical scalar field

Abdulla Al Mamon
(
- Visva Bharati U.
)
,
Sudipta Das
(
- Visva Bharati U.
)

Dec 11, 2015

20 pages

Published in:

Eur.Phys.J.C 76 (2016) 3, 135

Published: Mar 11, 2016

e-Print:

1512.03608 [gr-qc]

DOI:

10.1140/epjc/s10052-016-3982-3

View in:

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Abstract: (Springer)

In this paper, we consider various dark energy models in the framework of a non-canonical scalar field with a Lagrangian density of the form

\mathcal{L}(\phi , X)=f(\phi )X{\left( \frac{X}{M^{4Pl}}\right) }^{\alpha -1} - V(\phi )

, which provides the standard canonical scalar field model for

\alpha =1

and

f(\phi )=1

. In this particular non-canonical scalar field model, we carry out the analysis for

\alpha =2

. We then obtain cosmological solutions for constant as well as variable equation of state parameter (

\omega _{\phi }(z)

) for dark energy. We also perform the data analysis for three different functional forms of

\omega _{\phi }(z)

by using the combination of SN Ia, BAO, and CMB datasets. We have found that for all the choices of

\omega _{\phi }(z)

, the SN Ia

+

CMB/BAO dataset favors the past decelerated and recent accelerated expansion phase of the universe. Furthermore, using the combined dataset, we have observed that the reconstructed results of

\omega _{\phi }(z)

and q(z) are almost choice independent and the resulting cosmological scenarios are in good agreement with the

\Lambda

CDM model (within the

1\sigma

confidence contour). We have also derived the form of the potentials for each model and the resulting potentials are found to be a quartic potential for constant

\omega _{\phi }

and a polynomial in

\phi

for variable

\omega _{\phi }

.

Note:

22 pages, 13 figures

98.80.Hw
parametrization
dark energy
cosmic background radiation
cosmological model
equation of state
deceleration
statistical

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Figures(13)

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