Bayesian model selection on Scalar $\epsilon$-Field Dark Energy

Understand

The main aim of this paper is to analyse minimally-coupled scalar-fields -- quintessence and phantom -- as the main candidates to explain the accelerated expansion of the universe and compare its observables to current cosmological observations; as a byproduct we present its python module.

• This work includes a parameter $\epsilon$ which allows to incorporate both quintessence and phantom fields within the same analysis.
• Examples of the potentials, so far included, are $V(\phi)=V_0\phi^{\mu}e^{\beta \phi^\alpha}$ and $V(\phi)=V_0(\cosh(\alpha \phi)+\beta)$ with $\alpha$, $\mu$ and $\beta$ being free parameters, but the analysis can be easily extended to any other scalar field potential.
• Additional to the field component and the standard content of matter, the study also incorporates the contribution from spatial curvature ($\Omega_k$), as it has been the focus in recent studies.