12-23 July 2021
Online
Europe/Berlin timezone

The identification of proton and gamma components in cosmic-rays based on deep learning algorithm

13 Jul 2021, 12:00
1h 30m
04

04

Poster GAI | Gamma Ray Indirect Discussion

Speaker

F Zhang (Southwest Jiaotong University)

Description

The Large High Altitude Air Shower Observatory (LHAASO), is a multi-component experiment located at Daocheng (4410 m a.s.l.), Sichuan province, P.R. China. The identification of gamma rays from protons is an important foundation and premise for gamma ray research. In this paper, we use deep learning algorithm to extract the key features of events directly based on a large amount of original information, and explore the identification power of gamma rays from protons of LHAASO experiment. The Convolutional Neural Network(CNN), Deep Neural Networks(DNN) and Graph Neural Networks (GNN) are trained and tested based on a large number of simulation events respectively. Compared with the traditional methods, we have found that the trained CNN, DNN and GNN models all have improvements in the effect of proton and gamma discrimination.

Collaboration Lhaaso
Subcategory Experimental Methods & Instrumentation

Primary author

F Zhang (Southwest Jiaotong University)

Co-authors

C He (Southwest Jiaotong University) F.R Zhu (Southwest Jiaotong University) J Hou (Southwest Jiaotong University) Y.C Hao (School of Tangshan, Southwest Jiaotong University, )

Presentation Materials

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