PT Journal
AU HAWC Collaboration (Alfaro, Rea
   Salesa Greus, F
TI Gamma/hadron separation with the HAWC observatory
SO Nuclear Instruments & Methods in Physics Research A
JI Nucl. Instrum. Methods Phys. Res. A
PY 2022
BP 166984 - 13pp
VL 1039
DI 10.1016/j.nima.2022.166984
LA English
DE High energy; Crab Nebula; G/H separation; Machine Learning
AB 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.
ER