| Título |
Gamma/hadron separation with the HAWC observatory |
| Tipo |
Revista |
| Sub-tipo |
JCR |
| Descripción |
Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment |
| Resumen |
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. © 2022 |
| Observaciones |
DOI 10.1016/j.nima.2022.166984 |
| Lugar |
Amsterdam |
| País |
Paises Bajos |
| No. de páginas |
Article number 166984 |
| Vol. / Cap. |
v. 1039 |
| Inicio |
2022-09-11 |
| Fin |
|
| ISBN/ISSN |
|
