Imperial College London

ProfessorRobertoTrotta

Faculty of Natural SciencesDepartment of Physics

Visiting Professor
 
 
 
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Contact

 

+44 (0)20 7594 7793r.trotta Website CV

 
 
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Assistant

 

Mrs Sheila Ekudo +44 (0)20 7594 2086

 
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Location

 

1009Blackett LaboratorySouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Martin:2011:10.1103/PhysRevD.83.063524,
author = {Martin, J and Ringeval, C and Trotta, R},
doi = {10.1103/PhysRevD.83.063524},
journal = {Physical Review D},
title = {Hunting down the best model of inflation with Bayesian evidence},
url = {http://dx.doi.org/10.1103/PhysRevD.83.063524},
volume = {83},
year = {2011}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - We present the first calculation of the Bayesian evidence for different prototypical single field inflationary scenarios, including representative classes of small field and large field models. This approach allows us to compare inflationary models in a well-defined statistical way and to determine the current “best model of inflation.” The calculation is performed numerically by interfacing the inflationary code FieldInf with MultiNest. We find that small field models are currently preferred, while large field models having a self-interacting potential of power p>4 are strongly disfavored. The class of small field models as a whole has posterior odds of approximately 31 when compared with the large field class. The methodology and results presented in this article are an additional step toward the construction of a full numerical pipeline to constrain the physics of the early Universe with astrophysical observations. More accurate data (such as the Planck data) and the techniques introduced here should allow us to identify conclusively the best inflationary model.
AU - Martin,J
AU - Ringeval,C
AU - Trotta,R
DO - 10.1103/PhysRevD.83.063524
PY - 2011///
SN - 1550-7998
TI - Hunting down the best model of inflation with Bayesian evidence
T2 - Physical Review D
UR - http://dx.doi.org/10.1103/PhysRevD.83.063524
UR - http://hdl.handle.net/10044/1/29730
VL - 83
ER -