We propose a neural network classifier for tagging b jets at the Z0 peak; we include among the input variables infrared sensitive physical observables, such as the charged hadron multiplicity and the energy-multiplicity correlation. A comparison with traditional statistical approaches shows an improvement in the performance.

QCD COHERENCE IN TAGGING B-JETS BY NEURAL NETWORKS

PASQUARIELLO G
1993

Abstract

We propose a neural network classifier for tagging b jets at the Z0 peak; we include among the input variables infrared sensitive physical observables, such as the charged hadron multiplicity and the energy-multiplicity correlation. A comparison with traditional statistical approaches shows an improvement in the performance.
1993
Istituto di Studi sui Sistemi Intelligenti per l'Automazione - ISSIA - Sede Bari
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/208919
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