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Journal Article

Gamma/Hadron Separation with the HAWC Observatory

MPS-Authors
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Jardin-Blicq,  A.
Division Prof. Dr. James A. Hinton, MPI for Nuclear Physics, Max Planck Society;

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Marandon,  V.
Division Prof. Dr. James A. Hinton, MPI for Nuclear Physics, Max Planck Society;

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Olivera Nieto,  L.
Division Prof. Dr. James A. Hinton, MPI for Nuclear Physics, Max Planck Society;

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Tibolla,  O.
Division Prof. Dr. Werner Hofmann, MPI for Nuclear Physics, Max Planck Society;

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2205.12188.pdf
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Citation

Alfaro, R., Alvarez, C., Álvarez, J. D., Angeles Camacho, J. R., Arteaga-Velázquez, J. C., Avila Rojas, D., et al. (2022). Gamma/Hadron Separation with the HAWC Observatory. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 1039: 166984. doi:10.1016/j.nima.2022.166984.


Cite as: https://hdl.handle.net/21.11116/0000-000C-0091-F
Abstract
The High Altitude Water Cherenkov (HAWC) gamma-ray observatory observes
atmospheric showers produced by incident gamma rays and cosmic rays with energy
from 300 GeV to more than 100 TeV. A crucial phase in analyzing gamma-ray
sources using ground-based gamma-ray detectors like HAWC is to identify the
showers produced by gamma rays or hadrons. The HAWC observatory records roughly
25,000 events per second, with hadrons representing the vast majority
($>99.9\%$) of these events. The standard gamma/hadron separation technique in
HAWC uses a simple rectangular cut involving only two parameters. This work
describes the implementation of more sophisticated gamma/hadron separation
techniques, via machine learning methods (boosted decision trees and neural
networks), and summarizes the resulting improvements in gamma/hadron separation
obtained in HAWC.