R&D of the EM Calorimeter Energy Calibration with Machine Learning based on the low-level features of the Cluster

R&D of the EM Calorimeter Energy Calibration with Machine Learning based on the low-level features of the Cluster

Blog Article

We have developed an energy calibration method using machine learning for the ILC electromagnetic (EM) calorimeter (ECAL), a sampling calorimeter consisting of Silicon-Tungsten layers.In Pet Bowl Stands this method, we use a deep neural network (DNN) for a regression to determine the energy of VItamin Box incident EM particles, improving the energy calibration resolution of the ECAL.The DNN architecture takes cluster hit data as low-level features of the cluster.In this paper, we report the status of our R&D and present results on energy calibration accuracy.