USING A NEURAL-NETWORK IN THE SEARCH FOR THE HIGGS-BOSON

The search for the Standard Model Higgs boson in high energy e(+)e(-) collisions requires analysis techniques which efficiently discriminate against the very large background. A classifier based on a feed-forwa rd neural network has been extensively used in a search in the channel where the Higgs boson is produced in association with neutrinos. The method has significantly improved the sensitivity of the search. With a simple preselection based on event topology followed by a neural net work we have obtained a combined background rejection factor of more t han 29 000 and a selection efficiency for Higgs particle events of 54% , assuming a mass of 55 GeV/c(2) for the Higgs boson. We describe here the details of the analysis with emphasis on the neural network.