Aachen 2019 – scientific programme

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T: Fachverband Teilchenphysik

T 22: Poster

T 22.12: Poster

Monday, March 25, 2019, 16:00–18:30, C.A.R.L. Foyer 1. OG

Gamma-Hadron separation using Convolutional Neural Network for the HAWC observatory. — •Edna L. Ruiz-Velasco for the HAWC collaboration — Max Planck Institute for Nuclear Physics, Heidelberg, Germany

The High-Altitude Water Cherenkov (HAWC) is a wide-field of view observatory located in Sierra Negra, México. It is dedicated to study astrophysical sources of very-high energy (VHE) gamma rays from ~0.1 to 100 TeV. The HAWC main array comprises 300 Water Cherenkov Detectors (WCDs) that collect the footprint information of atmospheric air showers at the ground level. The detection of gamma-ray induced air showers poses a big challenge when it comes to the separation from the highly hadronic-dominated background (gamma-hadron separation problem). The standard method for the rejection of hadronic showers in HAWC employs parameters inferred from the reconstruction of these showers and is mostly based on the identification of muon signals. In this contribution we explore the application of Convolutional Neural Networks (CNNs) as a gamma-hadron separation method for HAWC, using the pure topology of the air showers, obtaining with this a high degree of separation power.