CERN openlab’s Post

🎯 CERN openlab summer student project spotlight! This summer, Francisco Resende from the Technical University of Munich is contributing to the upgrade of the ATLAS experiment for the High-Luminosity LHC, the most ambitious upgrade of the experiment yet. As part of the Next Generation Trigger Project he is exploring ways to increase in particular the performance of the muon trigger system, even beyond the original plans for the upgrade.   📈 With the CERN HL-LHC delivering unprecedented data rates, ATLAS needs to significantly improve how it selects muon tracks at the first-level trigger. For the first time, this will include muon tracking data from precision monitored drift-tube (MDT) chambers. Francisco’s project explores how machine learning can be integrated into this real-time environment to boost the experiment’s discovery potential. His work includes: 🔸 Developing and training neural network models to improve muon reconstruction 🔸 Optimising algorithms for deployment on FPGA devices 🔸 Comparing ML-based approaches with the baseline analytic algorithm in terms of trigger efficiency and muon momentum resolution By bridging AI techniques and high-speed detector electronics, Francisco’s research aims to make ATLAS even more capable of capturing rare and exciting physics events in the high-luminosity era. #CERNopenlab #SummerStudentProgramme #ATLASexperiment #MachineLearning #FPGA #ScientificComputing #CERN #NextGenTriggers #HiLumiLHC ATLAS Collaboration