2007/10/19 by R. Campana, Riccardo Campana, Enrico Massaro +7
Medicine · Physics and Astronomy · #Astrophysics and Cosmic Phenomena #Data-Driven Disease Surveillance #Scientific Research and Discoveries #astro-ph
paper · pdf · doi:10.1111/j.1365-2966.2007.12616.x
published as Mon.Not.Roy.Astron.Soc.383:1166-1174,2008 · 10 pages, 7 figures. Accepted for publication in MNRAS
arxiv created 2007/10/19 · openalex publication_date 2007/12/14 · arxiv updated 2009/12/01 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/30
We developed a source detection algorithm based on the Minimal Spanning Tree (MST), that is a graph-theoretical method useful for finding clusters in a given set of points. This algorithm is applied to γ-ray bi-dimensional images where the points correspond to the arrival direction of photons, and the possible sources are associated with the regions where they clusterize. Some filters to select these clusters and to reduce the spurious detections are introduced. An empirical study of the statistical properties of MST on random fields is carried out in order to derive some criteria to estimate the best filter values. We also introduce two parameters useful to verify the goodness of candidate sources. To show how the MST algorithm works in practice, we present an application to an EGRET observation of the Virgo field, at high Galactic latitude and with a low and rather uniform background, in which several sources are detected.