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Unbinned multivariate observables for global SMEFT analyses from machine learning

Articolo
Data di Pubblicazione:
2023
Abstract:
Theoretical interpretations of particle physics data, such as the determination of the Wilson coefficients of the Standard Model Effective Field Theory (SMEFT), often involve the inference of multiple parameters from a global dataset. Optimizing such interpretations requires the identification of observables that exhibit the highest possible sensitivity to the underlying theory parameters. In this work we develop a flexible open source frame-work, ML4EFT, enabling the integration of unbinned multivariate observables into global SMEFT fits. As compared to traditional measurements, such observables enhance the sensitivity to the theory parameters by preventing the information loss incurred when binning in a subset of final-state kinematic variables. Our strategy combines machine learning regression and classification techniques to parameterize high-dimensional likelihood ratios, using the Monte Carlo replica method to estimate and propagate methodological uncertainties. As a proof of concept we construct unbinned multivariate observables for top-quark pair and Higgs+Z production at the LHC, demonstrate their impact on the SMEFT parameter space as compared to binned measurements, and study the improved constraints associated to multivariate inputs. Since the number of neural networks to be trained scales quadratically with the number of parameters and can be fully parallelized, the ML4EFT framework is well-suited to construct unbinned multivariate observables which depend on up to tens of EFT coefficients, as required in global fits.
Tipologia CRIS:
03A-Articolo su Rivista
Keywords:
Higgs Properties; SMEFT
Elenco autori:
Ambrosio, Raquel Gomez; ter Hoeve, Jaco; Madigan, Maeve; Rojo, Juan; Sanz, Veronica
Autori di Ateneo:
GOMEZ AMBROSIO Raquel
Link alla scheda completa:
https://iris.unito.it/handle/2318/2056270
Link al Full Text:
https://iris.unito.it/retrieve/handle/2318/2056270/1552940/JHEP03(2023)033.pdf
Pubblicato in:
JOURNAL OF HIGH ENERGY PHYSICS
Journal
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  • Aree Di Ricerca

Dati Generali

URL

https://link.springer.com/article/10.1007/JHEP03(2023)033

Aree Di Ricerca

Settori (4)


PE2_1 - Theory of fundamental interactions - (2024)

SCIENZE MATEMATICHE, CHIMICHE, FISICHE - Cosmologia e Universo

SCIENZE MATEMATICHE, CHIMICHE, FISICHE - Fisica delle Particelle e dei Nuclei

SCIENZE MATEMATICHE, CHIMICHE, FISICHE - Laboratori innovativi, strumentazione e modellizzazione fisica
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