%0 Journal Article
%T Gamma/hadron separation with the HAWC observatory
%A HAWC Collaboration (Alfaro, R. et al
%A Salesa Greus, F.
%J Nuclear Instruments & Methods in Physics Research A
%D 2022
%V 1039
%I Elsevier
%@ 0168-9002
%G English
%F HAWCCollaborationAlfaro+SalesaGreus2022
%O WOS:000861747900006
%O exported from refbase (https://references.ific.uv.es/refbase/show.php?record=5371), last updated on Mon, 17 Oct 2022 08:52:02 +0000
%X 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.
%K High energy
%K Crab Nebula
%K G/H separation
%K Machine Learning
%R 10.1016/j.nima.2022.166984
%U https://arxiv.org/abs/2205.12188
%U https://doi.org/10.1016/j.nima.2022.166984
%P 166984 - 13pp