4.7 Article

Compatibility of Planck and BICEP2 results in light of inflation

Journal

PHYSICAL REVIEW D
Volume 90, Issue 6, Pages -

Publisher

AMER PHYSICAL SOC
DOI: 10.1103/PhysRevD.90.063501

Keywords

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Funding

  1. ESA Belgian Federal PRODEX [4000103071]
  2. Wallonia-Brussels Federation Grant ARC [11/15-040]
  3. STFC [ST/K001051/1] Funding Source: UKRI
  4. Science and Technology Facilities Council [ST/K001051/1] Funding Source: researchfish

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We investigate the implications for inflation of the detection of B-modes polarization in the cosmic microwave background by BICEP2. We show that the hypothesis of the primordial origin of the measurement is favored only by the first four band powers, while the others would prefer unreasonably large values of the tensor-to-scalar ratio. Using only those four band powers, we carry out a complete analysis in the cosmological and inflationary slow-roll parameter space using the BICEP2 polarization measurements alone and extract the Bayesian evidences and complexities for all the Encyclopedia Inflationaris models. This allows us to determine the most probable and simplest BICEP2 inflationary scenarios. Although this list contains the simplest monomial potentials, it also includes many other scenarios, suggesting that focusing model building efforts on large field models only is unjustified at this stage. We demonstrate that the sets of inflationary models preferred by Planck alone and BICEP2 alone are almost disjoint, indicating a clear tension between the two data sets. We address this tension with a Bayesian measure of compatibility between BICEP2 and Planck. We find that for models favored by Planck the two data sets tend to be incompatible, whereas there is moderate evidence of compatibility for the BICEP2 preferred models. As a result, it would be premature to draw any conclusion on the best Planck models, such as Starobinsky and/or Kahler moduli inflation. For the subset of scenarios not exhibiting data sets incompatibility, we update the evidences and complexities using both data sets together.

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