基于 CNN 的伽马射线对望远镜轨迹重建研究

IF 1.9 4区物理与天体物理 Q2 ASTRONOMY & ASTROPHYSICS

Astronomy and Computing Pub Date : 2024-05-19 DOI:10.1016/j.ascom.2024.100834

L. Yu , J. Wang , D. Guo , W. Peng , R. Qiao , K. Gong , Y. Liu , J. Wang , C. Zhang , W. Zhang

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引用次数: 0

摘要

MeV 伽马射线望远镜（MGT）是一项概念性飞行任务，旨在提高 MeV 能量范围内伽马射线天文学的探测灵敏度。它由三个子探测器组成：伽马射线转换硅跟踪器、CALOrimeter 和反偶发探测器。本文为 MGT 开发了一种基于卷积神经网络（CNN）的轨迹重建算法。为了训练和测试模型，使用了 Geant4 仿真，在 0.5 GeV 至 10 GeV 能段的九个能量点生成了大量伽马射线事件。最后，显示了角度分辨率、位置分辨率和接受度的重建结果。测试结果表明，与费米-LAT相比，MGT在0.5∼10 GeV范围内的角度分辨率明显提高。

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CNN-based track reconstruction study for gamma-ray pair telescope

MeV Gamma-ray Telescope (MGT) is a conceptual mission aimed at improving the detection sensitivity of gamma-ray astronomy in the MeV energy range. It consists of three sub-detectors: Gamma-ray Conversion silicon tracker, CALOrimeter and Anti-Coincident Detector. In this paper, a track reconstruction algorithm based on Convolutional Neural Networks (CNN) is developed for MGT. In order to train and test the model, Geant4 simulation is used and generates a large number of gamma-ray events at nine energy points in the energy band from 0.5 GeV to 10 GeV. Finally, the reconstruction results of angular resolution, position resolution and acceptance are shown. The testing results indicate that the angular resolution of MGT significantly improves in the $0.5 \sim 10$ GeV range compared with Fermi-LAT.

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来源期刊

Astronomy and Computing ASTRONOMY & ASTROPHYSICSCOMPUTER SCIENCE,-COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

CiteScore

4.10

自引率

8.00%

发文量

期刊介绍： Astronomy and Computing is a peer-reviewed journal that focuses on the broad area between astronomy, computer science and information technology. The journal aims to publish the work of scientists and (software) engineers in all aspects of astronomical computing, including the collection, analysis, reduction, visualisation, preservation and dissemination of data, and the development of astronomical software and simulations. The journal covers applications for academic computer science techniques to astronomy, as well as novel applications of information technologies within astronomy.