Abstract
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 [Formula: see text] mixing analysis.
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