Applications of Bayesian model averaging to the curvature and size of the Universe

  title={Applications of Bayesian model averaging to the curvature and size of the Universe},
  author={Mihran Vardanyan and Roberto Trotta and Joseph I. Silk},
  journal={Monthly Notices of the Royal Astronomical Society: Letters},
Bayesian model averaging is a procedure to obtain parameter constraints that account for the uncertainty about the correct cosmological model. We use recent cosmological observations and Bayesian model averaging to derive tight limits on the curvature parameter, as well as robust lower bounds on the curvature radius of the Universe and its minimum size, while allowing for the possibility of an evolving dark energy component. Because flat models are favoured by Bayesian model selection, we find… 

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