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Title: Constraining the dark energy equation of state using Bayes theorem and the Kullback–Leibler divergence

Data-driven model-independent reconstructions of the dark energy equation of state w(z) are presented using Planck 2015 era CMB, BAO, SNIa and Lyman-α data. These reconstructions identify the w(z) behaviour supported by the data and show a bifurcation of the equation of state posterior in the range 1.5 < z < 3. Although the concordance ΛCDM model is consistent with the data at all redshifts in one of the bifurcated spaces, in the other a supernegative equation of state (also known as ‘phantom dark energy’) is identified within the 1.5σ confidence intervals of the posterior distribution. In order to identify the power of different datasets in constraining the dark energy equation of state, we use a novel formulation of the Kullback–Leibler divergence. Moreover, this formalism quantifies the information the data add when moving from priors to posteriors for each possible dataset combination. The SNIa and BAO datasets are shown to provide much more constraining power in comparison to the Lyman-α datasets. Furthermore, SNIa and BAO constrain most strongly around redshift range 0.1 - 0.5, whilst the Lyman-α data constrains weakly over a broader range. We do not attribute the supernegative favouring to any particular dataset, and note that the ΛCDM modelmore » was favoured at more than 2 log-units in Bayes factors over all the models tested despite the weakly preferred w(z) structure in the data.« less
Authors:
 [1] ;  [2] ;  [1] ;  [3] ;  [1]
  1. Battcock Center, Cambridge (United Kingdom). Cavendish Lab.; Kavli Inst. for Cosmology Cambridge (United Kingdom)
  2. Brookhaven National Lab. (BNL), Upton, NY (United States)
  3. Battcock Center, Cambridge (United Kingdom). Cavendish Lab.
Publication Date:
Report Number(s):
BNL-112566-2016-JA
Journal ID: ISSN 0035-8711; KA2301020
Grant/Contract Number:
SC00112704
Type:
Accepted Manuscript
Journal Name:
Monthly Notices of the Royal Astronomical Society
Additional Journal Information:
Journal Name: Monthly Notices of the Royal Astronomical Society; Journal ID: ISSN 0035-8711
Publisher:
Royal Astronomical Society
Research Org:
Brookhaven National Laboratory (BNL), Upton, NY (United States)
Sponsoring Org:
USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25)
Country of Publication:
United States
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS; methods: data analysis; methods: statistical; dark energy; equation of state; cosmological parameters
OSTI Identifier:
1336117