A method for approximating optimal statistical significances with machine-learned likelihoods

Abstract Machine-learning techniques have become fundamental in high-energy physics and, for new physics searches, it is crucial to know their performance in terms of experimental sensitivity, understood as the statistical significance of the signal-plus-background hypothesis over the background-onl...

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Bibliographic Details
Main Authors: Ernesto Arganda, Xabier Marcano, Víctor Martín Lozano, Anibal D. Medina, Andres D. Perez, Manuel Szewc, Alejandro Szynkman
Format: Article
Language:English
Published: SpringerOpen 2022-11-01
Series:European Physical Journal C: Particles and Fields
Online Access:https://doi.org/10.1140/epjc/s10052-022-10944-3