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 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.