PoS - Proceedings of Science
Volume 395 - 37th International Cosmic Ray Conference (ICRC2021) - CRI - Cosmic Ray Indirect
Feasibility Studies on improved Proton Energy Reconstruction with IACTs
A. Fattorini*, W. Rhode", D. Elsaesser", D. Baack" and M. Noethe"
Full text: Not available
Abstract
Air showers induced by cosmic protons and heavier nuclei constitute the dominant background for very high energy gamma-ray observations of Imaging Air Cherenkov Telescopes (IACTs). Even for strong very high energy gamma-ray sources the signal-to-background ratio in the raw data is typically less than 1:5000. Therefore, a very large statistic of events, induced by cosmic protons and heavier nuclei, is easily available as a byproduct of gamma-ray source observations. In this contribution, we present a feasibility study on improved reconstruction of the energy of primary protons. For the latter purpose, we used a random forest method trained and tested by using Monte Carlo simulations of the MAGIC telescopes, for energies above 70GeV. We employ the aict-tools framework, including machine learning methods for the energy reconstruction. The open-source Python project aict-tools was developed at TU Dortmund and its reconstruction tools are based on scikit-learn predictors. Here, we report on the performance of the proton energy regression with the well-tested and robust random forest approach.
DOI: https://doi.org/10.22323/1.395.0237
How to cite

Metadata are provided both in "article" format (very similar to INSPIRE) as this helps creating very compact bibliographies which can be beneficial to authors and readers, and in "proceeding" format which is more detailed and complete.

Open Access
Creative Commons LicenseCopyright owned by the author(s) under the term of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.