We show that neural network classifiers can be helpful to discriminate Higgs production from background at LHC in the Higgs mass range M-H similar to 200 GeV. We employ a common feed-forward neural network trained by the backpropagation algorithm for off-line analysis and the neural chip TOTEM, trained by the Reactive Tabu Search algorithm, which could be used for on-line analysis. (C) 1997 Published by Elsevier Science B.V.
Role of neural networks in the search of the Higgs boson at LHC
MAGGIPINTO, TOMMASO;
1997-01-01
Abstract
We show that neural network classifiers can be helpful to discriminate Higgs production from background at LHC in the Higgs mass range M-H similar to 200 GeV. We employ a common feed-forward neural network trained by the backpropagation algorithm for off-line analysis and the neural chip TOTEM, trained by the Reactive Tabu Search algorithm, which could be used for on-line analysis. (C) 1997 Published by Elsevier Science B.V.File in questo prodotto:
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