Speaker
Description
The Higgs boson remains an object of key interest due to its unique position and role in the Standard Model framework. The cross-sections of three dominant production modes (gluon-gluon fusion, ggH; vector boson fusion, vbfH; and associated production alongside a vector boson or higgsstrahlung, VH) are analysed through the $H\rightarrow\tau\tau$ decay channel. The analysis utilizes a partial Run 3 dataset from the ATLAS Experiment at the LHC and is intended to act as an intermediate step between the successful measurements of the Higgs cross-sections in this decay channel using the full Run 2 dataset, and a full investigation of the data collected in the recently concluded Run 3. Various machine learning techniques, such as the implementation of a multiclass classifier neural network for improved discrimination between signal and background sources will be introduced. Preliminary results from Asimov and hybrid fits will be shown and discussed.