Minimum Spanning Tree cluster analysis of the LMC region above 10 GeV: detection of the SNRs N 49B and N 63A

TL;DR

This study applies Minimum Spanning Tree clustering to 9 years of Fermi-LAT gamma-ray data above 10 GeV in the LMC, successfully identifying known sources and discovering new supernova remnant associations.

Contribution

It introduces a novel application of the Minimum Spanning Tree algorithm for gamma-ray source detection in the LMC region, confirming new SNR associations with likelihood analysis.

Findings

Detection of significant gamma-ray clusters associated with N 49B and N 63A

Most clusters correspond to previously known sources

New SNR associations confirmed with likelihood analysis

Abstract

We present the results of a cluster search in the gamma-ray sky images of the Large Magellanic Cloud region by means of the Minimum Spanning Tree algorithm at energies higher than 10 GeV, using 9 years of Fermi-LAT data. Several significant clusters were found, the majority of which associated with previously known gamma-ray sources. New significant clusters associated with the supernova remnants N 49B and N 63A are also found, and confirmed with a Maximum Likelihood analysis of the Fermi-LAT data.