In this section
Several of our current PhD candidates and fellow researchers at the Data Science Institute have published, or in the proccess of publishing, papers to present their research.
@article{Martin:2014:03/039,
author = {Martin, J and Ringeval, C and Trotta, R and Vennin, V},
doi = {03/039},
journal = {Journal of Cosmology and Astroparticle Physics},
title = {The best inflationary models after Planck},
url = {http://dx.doi.org/10.1088/1475-7516/2014/03/039},
volume = {2014},
year = {2014}
}
TY - JOUR
AB - We compute the Bayesian evidence and complexity of 193 slow-roll single-field models of inflation using the Planck 2013 Cosmic Microwave Background data, with the aim of establishing which models are favoured from a Bayesian perspective. Our calculations employ a new numerical pipeline interfacing an inflationary effective likelihood with the slow-roll library ASPIC and the nested sampling algorithm MultiNest. The models considered represent a complete and systematic scan of the entire landscape of inflationary scenarios proposed so far. Our analysis singles out the most probable models (from an Occam's razor point of view) that are compatible with Planck data, while ruling out with very strong evidence 34% of the models considered. We identify 26% of the models that are favoured by the Bayesian evidence, corresponding to 15 different potential shapes. If the Bayesian complexity is included in the analysis, only 9% of the models are preferred, corresponding to only 9 different potential shapes. These shapes are all of the plateau type.
AU - Martin,J
AU - Ringeval,C
AU - Trotta,R
AU - Vennin,V
DO - 03/039
PY - 2014///
SN - 1475-7516
TI - The best inflationary models after Planck
T2 - Journal of Cosmology and Astroparticle Physics
UR - http://dx.doi.org/10.1088/1475-7516/2014/03/039
UR - http://hdl.handle.net/10044/1/28629
VL - 2014
ER -
Data Science Institute
William Penney Laboratory
Imperial College London
South Kensington Campus
London SW7 2AZ
United Kingdom
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