Search for Higgs bosons decaying to dark matter using advanced artificial intelligence techniques and upgrade of the silicon tracker at ATLAS 

Student: Stephen Randles
Supervisors: Andrew Mehta, Helen Hayward and Monica D’Onofrio (UoL)
Institution: University of Liverpool

The Large Hadron Collider (LHC) is a fantastic success, having been in operation for more than a decade, collecting huge datasets and releasing hundreds of results; the highlight being the discovery of the Higgs boson. At HL-LHC, the machine and deliver 10 times larger datasets for a total integrated luminosity of 4000 fb-1 and will increase its centre-of-mass energy up to 14 TeV. This PhD offers a balance between commissioning the new silicon tracking detector in readiness for the HL-LHC and exploitation of the data currently being taken by searching for Higgs bosons decaying to dark matter using the most up to date artificial intelligence techniques.    

Dark matter and dark energy are the most mysterious entities in the Universe.  If dark matter obtains its mass from the Higgs mechanism (like the fundamental particles of the Standard Model) and is sufficiently light, we should expect the Higgs boson to decay to a pair of dark matter particles, which will travel through the detector undetected.  This is the best way to discover light dark matter at the LHC. Liverpool has had a long involvement in this channel. The student will use the knowledge gained from their LIV-INNO training to use the latest artificial intelligence tools such as a Graph Neural Network (GNN) to improve the efficiency and separation from the main background of ZZ production. The student will modify the GNN, which has been shown by Liverpool researchers to greatly improve tau reconstruction. In addition, the student will extend the analysis to include models where the Higgs boson decays to scalar particles that are long-lived but may partially decay in the detector, thus giving rise to some missing momentum. This unique signature has never been analysed at the LHC. 

The student will make the first system-level performance evaluation of, the UK pixel endcap detector. They will contribute to an intense programme of testing, which will include the first measurements of the performance of pixel modules in their final configurations. Key to this work will be the development of an analysis framework which will allow module electrical test data to be compared to tests performed on individual modules.  The student will use their experience of this testing to evaluate the expected performance of the pixel tracker when installed in the ATLAS detector at the start of operations for HL-LHC.  

The PhD will offer the opportunity to participate in the construction of an experiment and the exploitation of physics data, which is a rare chance and only the optimal timing in between the Run 3 and Run 4 of the LHC will permit. They will also benefit from the unique expertise within the academic and research teams that are working together on the project.