PoS - Proceedings of Science
Volume 301 - 35th International Cosmic Ray Conference (ICRC2017) - Session Gamma-Ray Astronomy. GA-instrumentation
A Machine Learning classifier for photon selection with the DAMPE detector
S. Garrappa,* F. Gargano, M.N. Mazziottai, P. Fusco, F. Loparco on behalf of the DAMPE Collaboration
*corresponding author
Full text: pdf
Pre-published on: August 16, 2017
Published on: August 03, 2018
Abstract
The DArk Matter Particle Explorer (DAMPE) has been successfully launched on the December 17th 2015 and it is able to detect electrons and photons with an unprecedented energy resolution in an energy range going from a few GeV up to 10 TeV. In this work we present a machine learning-based method for photon selection in DAMPE. The selection is based on a classifier which uses the information from the DAMPE sub-detectors, and in particular from the large BGO calorimeter. The classifier was trained on Monte Carlo data and its performance was evaluated. We will also present preliminary results using on orbit data.
DOI: https://doi.org/10.22323/1.301.0764
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.