{"paper":{"title":"gamma-ray DBSCAN: a clustering algorithm applied to Fermi-LAT gamma-ray data. I. Detection performances with real and simulated data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["astro-ph.HE"],"primary_cat":"astro-ph.IM","authors_text":"(2) Politecnico di Milano, A. Tramacere (1), C. Vecchio (2) ((1) ISDC, Data Centre for Astrophysics, Italy), Milano, Switzerland, Versoix","submitted_at":"2012-10-01T19:56:19Z","abstract_excerpt":"The Density Based Spatial Clustering of Applications with Noise (DBSCAN) is a topometric algorithm used to cluster spatial data that are affected by background noise. For the first time, we propose the use of this method for the detection of sources in gamma-ray astrophysical images obtained from the Fermi-LAT data, where each point corresponds to the arrival direction of a photon. We investigate the detection performance of the gamma-ray DBSCAN in terms of detection efficiency and rejection of spurious clusters, using a parametric approach, and exploring a large volume of the gamma-ray DBSCAN"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1210.0522","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}