Identification of Gamma-Ray Point Sources in Fermi-LAT Data with Minimum Spanning Tree Algorithm
Gamma rays are the most energetic photons in the electromagnetic spectrum, detected with ground-based and space-based detectors in different energy ranges from sources in our galaxy and beyond. Gamma-ray point sources can be identified by special clustering of these photons. The minimum spanning tre...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Damghan university
2023-12-01
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| Series: | Iranian Journal of Astronomy and Astrophysics |
| Subjects: | |
| Online Access: | https://ijaa.du.ac.ir/article_385_9e13b5118e28445c89addefd40f41ca2.pdf |
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| Summary: | Gamma rays are the most energetic photons in the electromagnetic spectrum, detected with ground-based and space-based detectors in different energy ranges from sources in our galaxy and beyond. Gamma-ray point sources can be identified by special clustering of these photons. The minimum spanning tree (MST) algorithm is a graph-based method in order to find clusters. In this paper, we use the MST algorithm for finding point sources in Fermi gamma-ray space telescope data which is sensitive to photons with energies of 20 MeV up to more than 300 GeV. To this end, we selected eight completely random (10°×10°) fields of Fermi gamma-ray sky and tested the algorithm on the 12-year Fermi-LAT sky (Pass 8) at energy ranges above 3 GeV and above 6 GeV and with different cluster selection criteria. The calculation of Precision and Recall for both fields shows that MST is a useful algorithm in order to identify the point. |
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| ISSN: | 2322-4924 2383-403X |