Abstract

We perform a comprehensive study of a class of dark energy models---scalar field models where the effective potential can be described by a polynomial series---exploring their dynamical behavior using the method of flow equations that has previously been applied to inflationary models. Using supernova, baryon oscillation, cosmic microwave background (CMB) and Hubble constant data, and an implicit theoretical prior imposed by the scalar field dynamics, we find that the $\ensuremath{\Lambda}\mathrm{CDM}$ model provides an excellent fit to the data. Constraints on the generic scalar field potential parameters are presented, along with the reconstructed $w(z)$ histories consistent with the data and the theoretical prior. We propose and pursue computationally feasible algorithms to obtain estimates of the principal components of the equation of state, as well as parameters ${w}_{0}$ and ${w}_{a}$. Further, we use the Monte Carlo Markov chain machinery to simulate future data based on the Joint Dark Energy Mission, Planck, and baryon acoustic oscillation surveys and find that the inverse area figure of merit improves nearly by an order of magnitude. Therefore, most scalar field models that are currently consistent with data can be potentially ruled out by future experiments. We also comment on the classification of dark energy models into thawing and freezing in light of the more diverse evolution histories allowed by this general class of potentials.

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