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Classifying Jet Cascades with a Muon Using a Neural Network

We constructed a feed-forward neural network to tag jets with a prompt muon from bottom quark decay. Using kinematic variables and the reconstructed jet charge as input variables, we studied the response of the network to backgrounds of other cascades having a muon in the final state. Finally, we analysed the behaviour of this classifier on a di-muon sample as part of a mixing analysis.