Supervisors: Prof. Claire Shepherd-Themistocleous (RAL/PPD) & Prof. Joel Goldstein (Bristol).
This is a joint studentship between the Particle Physics Department (PPD) at the Rutherford Appleton Laboratory and Bristol University. The PPD group of around 20 staff and students is active across analysis and operations, and the HL-LHC upgrade for CMS.
The CMS experiment is one of two large multipurpose experiments at the Large Hadron Collider at the CERN laboratory in Geneva. The complete LHC data set will have been acquired by the end of Run 3 in 2026 and preparations for the major upgrades required for High Luminosity LHC (HL-LHC) are well underway. The student project will cover both novel searches for physics beyond the standard model (BSM), which will exploit he entire LHC data set, and the development of complex algorithms to be deployed in FPGAs in the hardware trigger for the HL-LHC upgrade.
Many BSM models, such as the NMSSM, have extended Higgs sectors that can include Higgs bosons lighter than the Higgs boson discovered at the LHC in 2012. The project will involve developing methods to search for evidence of BSM physics where such light Higgs boson can be present. Exploiting our long-standing collaboration with theorists within the NExT Institute, we will develop new BSM scenarios to explore using techniques that exploit a variety of neural nets.
The CMS experiment has a very ambitious hardware trigger (L1) upgrade for the HL-LHC. The extensive use of cutting-edge FPGAs enables complex algorithms to be executed at this first stage of decision making for data acquisition. It is now possible to deploy machine learning techniques, such as autoencoders, on FPGAs. The possibility of searching for more generic anomalies in the data at L1 is an exciting way to expand the physics potential at the HL-LHC beyond the already ambitious upgrade programme. The student will work with the large team of experts from PPD and Bristol and in collaboration with data scientists and particle physics theorists at Southampton University on this exciting project.
For more information please contact Prof. Claire Shepherd-Themistocleous (Claire.Shepherd@stfc.ac.uk) and Prof. Joel Goldstein (Joel.Goldstein@cern.ch)
