English

A Simple Phenomenological Emergent Dark Energy Model can Resolve the Hubble Tension

Cosmology and Nongalactic Astrophysics 2020-01-14 v3 General Relativity and Quantum Cosmology High Energy Physics - Phenomenology High Energy Physics - Theory

Abstract

Motivated by the current status of the cosmological observations and significant tensions in the estimated values of some key parameters assuming the standard Λ\LambdaCDM model, we propose a simple but radical phenomenological emergent dark energy model where dark energy has no effective presence in the past and emerges at the later times. Theoretically, in this phenomenological dark energy model with zero degree of freedom (similar to a Λ\LambdaCDM model), one can derive that the equation of state of dark energy increases from 23ln101-\frac{2}{3 {\rm{ln}}\, 10} -1 in the past to 1-1 in the future. We show that by setting a hard-cut 2σ\sigma lower bound prior for the H0H_0 that associates with 97.72%97.72\% probability from the recent local observations~\citep{riess2019large}, this model can satisfy different combinations of cosmological observations at low and high redshifts (SNe Ia, BAO, Ly{α\alpha} BAO and CMB) substantially better than the concordance Λ\LambdaCDM model with Δχbf241.08\Delta \chi^2_{bf} \sim -41.08 and ΔDIC35.38\Delta\,{\rm{DIC}} \sim-35.38. If there are no substantial systematics in SN Ia, BAO or Planck CMB data and assuming reliability of the current local H0H_0 measurements, there is a very high probability that with slightly more precise measurement of the Hubble constant our proposed phenomenological model rules out the cosmological constant with decisive statistical significance and is a strong alternative to explain combination of different cosmological observations. This simple phenomenologically emergent dark energy model can guide theoretically motivated dark energy model building activities.

Keywords

Cite

@article{arxiv.1906.08275,
  title  = {A Simple Phenomenological Emergent Dark Energy Model can Resolve the Hubble Tension},
  author = {Xiaolei Li and Arman Shafieloo},
  journal= {arXiv preprint arXiv:1906.08275},
  year   = {2020}
}

Comments

7 pages, 4 figures, 1 table, published in ApJL