SN and BAO Constraints on (New) Polynomial Dark Energy Parametrizations

In this work we introduce two new polynomial parametrizations of dark energy equation of state, w, and explore their correlation properties. The parameters to fit are the equation of state values at z = 0 and z = 0. 5, which have naturally low correlation and have already been shown to improve the popular Chevallier–Polarski–Linder (CPL) parametrization. We test our models with Type Ia Supernovae (SNeIa) and Baryon Acoustic Oscillations (BAO), in the form of both current and synthetic data. On one hand, we investigate the degree of improvement in dark energy constraints that can be achieved with future data. On the other hand, according to the Bayesian deviance information criterion (DIC), which penalizes large errors and correlations, we show that our models perform better than the CPL re-parametrization proposed by Wang (in terms of z = 0 and z = 0. 5). This is due to the combination of a lower correlation and smaller relative errors. The same holds for a frequentist perspective: our Figure-of-Merit is larger for our parametrizations.