Constraining the dark energy equation of state using Bayes theorem ...

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Jul 1, 2016 - provide much more constraining power in comparison to the Lyman-α datasets. ..... Looking at the 2D marginalised node positions in the w(z) .... GetDist and w(z) reconstructions were produced in python with the cubehelix colour ..... Jassal H. K., Bagla J. S., Padmanabhan T., 2004, Monthly Notices of the.
MNRAS 000, 1–9 (2016)

Preprint 4 July 2016

Compiled using MNRAS LATEX style file v3.0

Constraining the dark energy equation of state using Bayes theorem and the Kullback–Leibler divergence S. Hee,1,2? J.A. Vázquez,3 W.J. Handley,1,2 M.P. Hobson1 and A.N. Lasenby1,2 1 2

arXiv:1607.00270v1 [astro-ph.CO] 1 Jul 2016

3

Astrophysics Group, Battcock Centre, Cavendish Laboratory, JJ Thomson Avenue, Cambridge CB3 0HE, UK Kavli Institute for Cosmology Cambridge, Madingley Road, Cambridge, CB3 0HA, UK Brookhaven National Laboratory, 2 Center Road, Upton, NY 11973, USA

Last updated 2016 Jul 1; in original form 2016 July 1

ABSTRACT

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

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