Leptoquarks at ATLAS Run III

Student: Mehul Depala
Supervisors: Andrew Mehta, Monica D'Onofrio (UoL)
Institution: University of Liverpool 

The large hadron collider situated at CERN in Geneva, Switzerland is the highest energy particle collider ever built. The machine is currently taking data for its third major running period. The full dataset to be collected during Run III will not only be significantly larger than has been taken so far, but is at higher energy.  

Leptoquarks are particles that have been proposed that carry both quark and lepton quantum numbers. They are a feature of many models that go beyond the Standard Model and are a possible explanation of anomalies for which there is some evidence at experiments designed to study b-quarks.  With this PhD project, we propose to deliver an ambitious new leptoquark pair search that uses multi-variant techniques and focus on the multi-TeV mass regime to get the best out of the Run III data.  

The analysis will include all possible lepton-quark combinations apart from those with third generation fermions (which will be done in other dedicated analyses) so a total of 25 possible decays will be investigated. The jets will be split into light-, charm- and bottom-quark jets using tagging techniques that the student will help to develop as their ‘qualification task’. Leptoquark decays with neutrinos will be included for the first time in addition to electrons and muons. One issue that will be addressed is the poor muon resolution at very high energy. Rather than excluding muons where the momentum determination is poor (as was the case in Run II) we plan to keep these events in the analysis but use event-based quantities rather than the muon momentum for the selection of interesting events. 

The major improvement to the analysis is to use multivariant techniques. In the previous analysis the average mass of the two leptoquarks was used as the final discriminant. This was adequate in the low mass regime where the analysis was optimised. For the new analysis the plan is to use multiple input observables that can better discriminate signal from background events through multivariate techniques and possible graph neural networks. The mass cannot be fully reconstructed in decays involving neutrinos or where the muon resolution is poor, instead several final state observables must be optimally combined. This will capitalise on the expertise on complex data analysis tools within the supervisory team, and the Liverpool group collaboration in AI-focused consortia such as the CHIST-ERA EPSRC-EU grant MUCCA (UK PI Monica D’Onofrio). 

Throughout the project you will have targeted training in data science provided by the University of Liverpool with the Centre for Doctoral Training LIV.INNO. You will also be given the opportunity to carry out an industry placement of six months to broaden your wider research and career skills. 

This project will be carried out over 48 months based at the University of Liverpool but you have the opportunity to spend up to year in CERN. Whilst in the UK, a standard RKUK PhD stipend will be paid, during the time at CERN. A mandatory 6-months industry placement forms part of the project.