Barbour, Gregory; (2022) Improving b-jet identification and searching for additional Higgs bosons with ATLAS. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

The ATLAS experiment at the LHC has completed its run-2 data collection at √s = 13 TeV. An upgrade phase has begun in preparation of the high luminosity LHC. Improvements to the algorithms underpinning data analysis in ATLAS are researched, with a particular focus on data science techniques and machine learning. The research carried out focused on b-tagging, the labelling of jets produced by b decays, and a search for new physics signals in ATLAS data. The use of neutral tracks in the fit of the b-decay topology in existing ATLAS algorithms was studied. No major performance boost was observed. Software development efforts were carried out to improve the design and extensibility of existing b-jet decay topology fitting algorithms. Research into an RNN based b-jet topological reconstruction algorithm was carried out. The optimization studies and performance evaluation techniques are summarized alongside key insights. Such a technique could serve next to existing b-tagging algorithms at ATLAS. Finally, a search was performed for heavier version of the Higgs boson using the 139 fb−1 ATLAS data. Such particles are motivated by several BSM theories. Expected upper limits on the strength of various signal models are given, and expected exclusion contours at 95% confidence level are drawn for the various parameters of the model.

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