Developing trigger algorithms for the CMS Upgrade at the HL-LHC

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A major upgrade of the Large Hadron Collider from 2027 will increase the rate of proton collisions to an unprecedented 10 billion per second. A sophisticated data processing system - the "L1 Trigger" - will process each event to identify interesting collisions for storage and further analysis; events not selected are lost forever. The L1 Trigger is constructed of custom hardware processors using high-speed optical links and FPGA devices. It can receive data at 60 Tb/s and must process each event in less than 10s. In this project we will develop trigger algorithms using both standard techniques and employing machine learning to identify interesting collisions, such as production of a pair of Higgs bosons, for the CMS L1 Trigger. The physics performance of these networks will be studied and optimised using Monte-Carlo simulation. The trade-off between physics performance and inference latency and resource usage will be studied for a range of network types. Ultimately, candidate algorithms will be implemented in FPGAs and demonstrated in real processor boards.