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

6533b7ddfe1ef96bd12735fc

RESEARCH PRODUCT

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

Ernesto Arganda Xabier Marcano Víctor Martín Lozano Anibal D. Medina Andres D. Perez Manuel Szewc Alejandro Szynkman

subject

Physics and Astronomy (miscellaneous)Gluons boosted particle FOS: Physical sciences Top Quark 530 High Energy Physics - Experiment High Energy Physics - Experiment (hep-ex)High Energy Physics - Phenomenology (hep-ph)statistical analysis ddc:530 numerical calculations Engineering (miscellaneous)Monte Carlo Instrumentation and Methods for Astrophysics (astro-ph.IM)new physics Física dijet: final state final state [dijet]sensitivity High Energy Physics - Phenomenology machine learning CERN LHC Coll Physics - Data Analysis Statistics and Probability Substructure Astrophysics - Instrumentation and Methods for Astrophysics Data Analysis Statistics and Probability (physics.data-an)

description

The European physical journal / C 82(11), 993 (2022). doi:10.1140/epjc/s10052-022-10944-3

year	journal	country	edition	language
2022-11-05

https://dx.doi.org/10.48550/arxiv.2205.05952

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