Using Neural Networks to Enhance the Higgs Boson Signal at Hadron Colliders

R. D. Field, Y. Kanev, M. Tayebnejad, and P. A. Griffin
Institute for Fundamental Theory, Department of Physics, University of Florida, Gainesville, FL 32611

Published in Phys. Rev. D53, 2296 (1996).


Neural networks are used to help distinguish the ZZ to lepton-lepton-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.

This research was supported in part by a grant from the U.S. Department of Energy (DoE).
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