Electromagnetic Calorimeter

Electromagnetic calorimeters (ECALs) are crucial detectors in high-energy physics experiments, measuring the energy of electrons and photons by analyzing the showers they produce. Current research focuses on improving ECAL performance using advanced machine learning techniques, such as deep learning models (including convolutional neural networks, vision transformers, and autoencoders), to enhance particle identification, improve energy resolution, and enable real-time data quality monitoring. These advancements are vital for achieving higher precision in particle physics experiments, particularly at high luminosity colliders like the LHC, where background noise and data volume are significant challenges.