Article
Version 1
Preserved in Portico This version is not peer-reviewed
Late-Transition Constraints in a Geometric Model for Dark Energy
Version 1
: Received: 7 May 2019 / Approved: 8 May 2019 / Online: 8 May 2019 (11:36:01 CEST)
Version 2 : Received: 17 June 2020 / Approved: 18 June 2020 / Online: 18 June 2020 (09:25:41 CEST)
Version 2 : Received: 17 June 2020 / Approved: 18 June 2020 / Online: 18 June 2020 (09:25:41 CEST)
How to cite: Capistrano, A. Late-Transition Constraints in a Geometric Model for Dark Energy. Preprints 2019, 2019050096. https://doi.org/10.20944/preprints201905.0096.v1 Capistrano, A. Late-Transition Constraints in a Geometric Model for Dark Energy. Preprints 2019, 2019050096. https://doi.org/10.20944/preprints201905.0096.v1
Abstract
In a geometric model for dark energy, the Hubble parameter as a function of redshift is modified by the presence of a new term originated from the extrinsic curvature. We investigate a late-transition redshift constrained with the latest datasets on the Cosmic Microwave Background (CBM), Baryon Acoustic Oscillations (BAO), the Pantheon Supernovae type Ia and the Hubble parameter data with redshift ranging from $0.01 < z < 2.3$. Performing the Aikake Information Criterion (AIC) to ascertain the viability of the model from Jeffreys' scale, we apply a joint likelihood analysis with the Markov Chain Monte Carlo (MCMC) method and find that the present model is in very good agreement with observations with a close statistical equivalence with the background $\Lambda$CDM cosmology at 1-$\sigma$ level. In addition, we apply the Bayesian Information Criterion (BIC) to the statistics and we find similar results as compared to AIC. Both tests indicate that mild deviations from $\Lambda$CDM model are allowed, showing no evidence for phantom behaviour.
Keywords
modified Friedman equations, modified gravity, dark energy
Subject
Physical Sciences, Astronomy and Astrophysics
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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