A Bayesian comparison between $\Lambda$CDM and phenomenologically emergent dark energy models

Abstract

In this work we examine the recently proposed phenomenological emergent dark energy (PEDE) model by \cite{Li:2019yem}, using the latest observational data in both expansion and perturbation levels. Applying the statistical Bayesian evidence as well as the AIC and BIC information criteria, we compare the PEDE model with the concordance $\Lambda$CDM model in both flat and non-flat universes. We combine the observational datasets as (i) expansion data (except CMB), (ii) expansion data (including CMB) and (iii) expansion data jointed to the growth rate dataset. Our statistical results show that the flat- $\Lambda$CDM model is still the best model. In the case of expansion data (including CMB), we observe that the flat- PEDE model is well consistent with observations as well as the concordance $\Lambda$CDM universe. While in the cases of (i) and (iii), the PEDE models in both of the flat and non-flat geometries are not favored. In particular, we see that in the perturbation level the PEDE model can not fit the observations as equally as standard $\Lambda$CDM cosmology. As the ability of the model, we show that the PEDE models can alleviate the tension of Hubble constant value appearing between the local observations and Planck inferred estimation in standard cosmology.

Accepted in EPJC

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