Speaker
Description
At very high energies, there is a deficiency in the number of muons produced in hadronic extensive air showers (EAS) in simulated interaction models compared to experimental measurements. Imaging atmospheric Cherenkov telescopes (IACTs) can be used to study this ‘muon puzzle’. These telescopes detect the resultant Cherenkov light emitted from the interaction of cosmic rays with atmospheric nuclei. To study this discrepancy, muons must be efficiently identified with sufficient statistics to be able to distinguish different shower models. Presented in this talk is an introduction to how muons are measured with IACTs, the properties of air showers and muons that are useful to develop an efficient model, and the machine learning techniques that will be used.
