Speaker
Description
Abstract Imaging Atmospheric Cherenkov telescopes (IACTs) are designed to detect cosmic gamma rays. As a by-product, IACTs detect Cherenkov flashes generated by millions of hadronic air showers every night. We present the proton energy spectrum from several hundred GeV to several hundred TeV, retrieved from the hadron induced showers detected by the MAGIC telescopes. The protons are discriminated from He and heavy nuclei with machine learning classification. The energy estimation is based on a specially developed deep neural network regressor. In the last decade, Deep Learning methods gained much interest in the scientific community for their ability to extract complex relations in data and process vast quantities of data in a short time. The proton energy spectrum obtained in this work is compared with the spectra obtained by modern cosmic ray experiments.
Keywords
Cherenkov telescopes; Cosmic rays; Protons spectrum; Neural networks
| Subcategory | Experimental Methods & Instrumentation |
|---|---|
| Collaboration | MAGIC |
