Constraining the SMEFT with Bayesian reweighting
Samuel van Beek, Emanuele R. Nocera, Juan Rojo, Emma Slade
SciPost Phys. 7, 070 (2019) · published 29 November 2019
- doi: 10.21468/SciPostPhys.7.5.070
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Abstract
We illustrate how Bayesian reweighting can be used to incorporate the constraints provided by new measurements into a global Monte Carlo analysis of the Standard Model Effective Field Theory (SMEFT). This method, extensively applied to study the impact of new data on the parton distribution functions of the proton, is here validated by means of our recent SMEFiT analysis of the top quark sector. We show how, under well-defined conditions and for the SMEFT operators directly sensitive to the new data, the reweighting procedure is equivalent to a corresponding new fit. We quantify the amount of information added to the SMEFT parameter space by means of the Shannon entropy and of the Kolmogorov-Smirnov statistic. We investigate the dependence of our results upon the choice of alternative expressions of the weights.
Cited by 22
Ontology / Topics
See full Ontology or Topics database.Authors / Affiliations: mappings to Contributors and Organizations
See all Organizations.- 1 Samuel van Beek,
- 1 Emanuele Roberto Nocera,
- 1 2 Juan Rojo,
- 3 Emma Slade
- 1 Nationaal instituut voor Subatomaire Fysica / National Institute for Subatomic Physics [NIKHEF]
- 2 Vrije Universiteit Amsterdam / VU University Amsterdam [VU]
- 3 Rudolf Peierls Centre for Theoretical Physics, University of Oxford