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arXiv · 2208.08454

To Profile or To Marginalize -- A SMEFT Case Study

Ilaria Brivio·Sebastian Bruggisser·Nina Elmer·Emma Geoffray·Michel Luchmann·Tilman Plehn
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Abstract

Global SMEFT analyses have become a key interpretation framework for LHC physics, quantifying how well a large set of kinematic measurements agrees with the Standard Model. This agreement is encoded in measured Wilson coefficients and their uncertainties. A technical challenge of global analyses are correlations. We compare, for the first time, results from a profile likelihood and a Bayesian marginalization for a given data set with a comprehensive uncertainty treatment. Using the validated Bayesian framework we analyse a series of new kinematic measurements. For the updated dataset we find and explain differences between the marginalization and profile likelihood treatments.

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Ilaria Brivio, Sebastian Bruggisser, Nina Elmer, Emma Geoffray, Michel Luchmann, Tilman Plehn. 2022-08-17. To Profile or To Marginalize -- A SMEFT Case Study. https://doi.org/10.21468/scipostphys.16.1.035

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