​

​HL-LHC UPGRADE of the CMS HARDWARE TRIGGER and SEARCHES for NEW PHYSICS (2019)​​

Co-supervisors:  PPD: C. Shepherd-Themistocleous, Southampton - S. Moretti​

The CMS experiment will upgrade its Level 1 trigger system for High Luminosity (HL-LHC) operation. The upgraded system will, for the first time, be able to perform sophisticated particle reconstruction in hardware using complex algorithms implemented in firmware. The student will work on this challenging trigger, developing algorithms and realizing them in hardware. The student will also perform an analysis searching for new particles predicted beyond the standard model theories with the current data and evaluate the capabilities that the HL-LHC upgrade will enable. Machine learning techniques will be utilized throughout this work. The project combines hardware, physics analysis and theoretical aspects of particle physics. 

CMS TRACK TRIGGER DEVELOPMENT for HL-LHC (2019)​​

Co-supervisors:  PPD: I. Tomalin together with Bristol​

At the future High Luminosity LHC (HL-LHC), the CMS experiment will reconstruct with high-speed electronics, the trajectories of charged particles detected by its silicon tracker. This reconstruction must be done within a few nanoseconds, so these tracks can be used as input to the L1 trigger system, identifying which proton-proton bunch crossings are of sufficient interest for full detector read-out. This is an immensely challenging task, as the tracker will transmit approximately one trillion measurement points to this electronics per second, which must be processed with a sophisticated track reconstruction algorithm. The student will participate in efforts to make this project a reality -- developing and refining the reconstruction algorithm with C++ software studies on simulated CMS p-p events; writing HLS or VHDL firmware to implement the algorithm on programmable FPGA electronics, and testing it during CMS integration tests of prototype tracker modules with the tracker electronics. The student will also interact closely with people developing the L1 trigger system, so as to understand how changes in the track reconstruction would affect the physics performance of CMS. This project will help the student develop many skills that are valued highly both in particle physics and in the wider world.​

​IMPROVING the PERFORMANCE of the CMS ECAL TRIGGER ALGORITHMS FOR HL-LHC PHASE (2019)

Co-supervisors:  PPD: D. Petyt, together with Bristol​

The CMS Electromagnetic Calorimeter (ECAL) is responsible for the triggering, identification and precise reconstruction of electrons and photons at the CERN LHC, which are key to many CMS physics analyses. The goal of the project is to develop new and improved triggering algorithms that take full advantage of the upgrades to the ECAL planned for the High Luminosity phase of the LHC (2026+).

The project is especially suited to those with an interest in detector hardware and electronics, algorithm development and FPGA programming, and Monte Carlo simulations and analysis. The successful applicant will also have the opportunity to participate in physics analysis using CMS data, collaborating with other members of the group.​

SEARCH for BSM PHYSICS and HL-LHC TRIGGER STUDIES (2021)

Co-supervisors:  PPD: ​C. Shepherd-Themistocleous, Bristol University - H. Flaecher​

The LHC is about to start Run 3 and the CMS experiment will be collecting its largest-ever dataset. The student will join the PPD CMS group, of around 20 staff and students, which is active across analysis and operations, and the HL-LHC upgrade for CMS. The student project will cover both novels searches for physics beyond the standard model (BSM) 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 including Higgs bosons lighter than the Higgs boson discovered at the LHC in 2012. The final states that will be exploited will include light Higgs bosons, which will be reconstructed using techniques that make extensive use of neural nets such as Graph NNs. Exploiting our long-standing collaboration with theorists within the NExT Institute, we will develop new BSM scenarios to explore using these techniques. The development of trigger algorithms for the HL-LHC level-1 hardware trigger will exploit our work on track reconstruction in FPGAs to develop novel algorithms that exploit these tracks. HLS will be used to deploy the algorithms in the trigger FPGAs.