Deep Learning Approach to Measurement of Higgs Boson CP in the $H\rightarrow \tau \tau $ Decay Channel

The measurement of the Higgs boson CP is amongst the most vital measurements in establishing the nature of the Higgs boson. Of the many decay channels, the ditau final state is one of the most sensitive channels due to the Yukawa coupling allowing access to a potential mixing between CP-even and CP-odd Higgs bosons. While decay modes such as the $\tau \rightarrow \rho^{\pm} \nu$ are well-established in literature, modes such as the $\tau \rightarrow a^{\pm}_1 \nu$ are not so. A new approach to encompass many decay modes has been developed using deep learning neural networks. This article summarises work done in assessing the robustness of the approach with respect to detector resolution effects and potential modelling issues. Also discussed is the Drell–Yan background.