Deep Learning in di-tau final states

Lead Research Organisation: Lancaster University
Department Name: Physics

Abstract

Higgs decays into two hadronic tau leptons offer a unique opportunity in high energy physics for the ATLAS experiment. They are the only directly accessible Higgs couplings to fermions and offer a relatively large cross section. This can be exploited in measuring the CP properties of the Higgs boson, accessing the Higgs self coupling in the bbtautau final state and using the Higgs as a portal into physics beyond the Standard Model. In this project we will look at the di-tau final state with deep learning methods in order to improve sensitivity for this Higgs decay mode.

Publications

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