Speaker
Description
Classification Without Labels (CWoLa) is a Machine Learning strategy which can be used to classify event categories (e.g. quark jet vs gluon jet, or BSM signal vs SM background) starting from mixed event samples, which are inevitable at particle collider experiments. I will illustrate how this strategy can be used to uncover BSM resonance signals which would otherwise be completely buried under large SM backgrounds by taking advantage of as much information as possible in the events, focusing on a toy example where a di-fat jet resonance with unusual jet substructure is hidden amongst standard model dijets. This strategy can be applied directly to data without a requirement for specific signal models, simulated signal or background Monte Carlo events, or carefully chosen cuts.
