QCD COHERENCE IN TAGGING B-JETS BY NEURAL NETWORKS

We propose a neural network classifier for tagging b jets at the Z0 peak; we include among the input variables infrared sensitive physical observables, such as the charged hadron multiplicity and the energy-multiplicity correlation. A comparison with traditional statistical approaches shows an improvement in the performance.