Speaker
Description
The technology of highly granular calorimeters is one of the innovations that will be implemented in the planned accelerator experiments, for example in the future linear collider. The work is devoted to the study of hadronic showers in the highly granular hadron calorimeter of the ILD detector and the application of machine learning to the improvement of the energy resolution. The artificial neural network was built, the dependencies between the selected input variables were studied. The study was performed using the simulation of single hadrons with energies from 5 to 60 GeV in the ILD detector.