Open AccessUsing neural networks to enhance the Higgs boson signal at hadron colliders
Author(s) -
R. D. Field,
Y. Kanev,
M. Tayebnejad,
P.A. Griffin
Publication year - 1995
Language(s) - English
Resource type - Reports
DOI - 10.2172/179288
Subject(s) - physics , particle physics , higgs boson , jet (fluid) , event (particle physics) , hadron , nuclear physics , large hadron collider , signal (programming language) , quantum chromodynamics , detector , energy (signal processing) , boson , collider , astrophysics , computer science , quantum mechanics , optics , thermodynamics , programming language
Neural networks are used to help distinguish the ZZ {yields} {ell}{sup +}{ell}{sup {minus}}-jet-jet signal produced by the decay of a 400 GeV Higgs boson at a proton-proton collider energy of 15 TeV from the ``ordinary`` QCD Z + jets background. The ideal case where only one event at a time enters the detector (no pile-up) and the case of multiple interactions per beam crossing (pile-up) are examined. In both cases, when used in conjunction with the standard cuts, neural networks provide an additional signal to background enhancement