Identification of Gamma-Ray Point Sources in Fermi-LAT Data with Minimum Spanning Tree Algorithm

Abstract

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.

Keywords

• astronomy data analysis
• clustering
• gamma-ray sources