USE OF NEURAL NETS TO MEASURE THE τ POLARIZATION AND ITS BAYESIAN INTERPRETATION

Abstract
We have tested a neural network (NN) technique as a method to determine the helicity of the τ particles in the process: e+e→(Z0, γ*)→τ+τ→(ρν)(ρν). It takes into account in a natural way the fact that both taus have different helicity and gives efficiencies comparable to the Bayesian method. We have found this “academic” example a nice way to introduce the analytical interpretation of the net output, showing that these neural nets techniques are equivalent to a Bayesian Decision Rule.
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