2 December 2022
CERN
Europe/Zurich timezone

Unbinned multivariate observables for global SMEFT analyses from machine learning

Not scheduled
20m
40/S2-B01 - Salle Bohr (CERN)

40/S2-B01 - Salle Bohr

CERN

100
Show room on map

Speaker

Maeve Madigan

Description

Global determinations of the Wilson coefficients of the Standard Model Effective Field Theory (SMEFT) involve the inference of multiple parameters from a global dataset, and are often based on reinterpreting existing binned LHC measurements within the SMEFT framework. Based on our recently developed open-source framework, ML4EFT, we propose a new methodology that can be adopted by experiments in order to present to the community unbinned measurements that are optimised for global SMEFT fits.

Authors

Jaco ter Hoeve (Nikhef and VU Amsterdam) Juan Rojo Maeve Madigan Dr Raquel Gomez Ambrosio (Milano Bicocca) Prof. Veronica Sanz Gonzalez (Universities of Valencia and Sussex)

Presentation materials

There are no materials yet.