{"paper":{"title":"Applying the Background-Source separation algorithm to Chandra Deep Field South data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["astro-ph.CO"],"primary_cat":"astro-ph.IM","authors_text":"F. Guglielmetti, H. Boehringer, P. Rosati, P. Tozzi, R. Fischer","submitted_at":"2012-02-02T10:02:35Z","abstract_excerpt":"A probabilistic two-component mixture model allows one to separate the diffuse background from the celestial sources within a one-step algorithm without data censoring. The background is modeled with a thin-plate spline combined with the satellite's exposure time. Source probability maps are created in a multi-resolution analysis for revealing faint and extended sources. All detected sources are automatically parametrized to produce a list of source positions, fluxes and morphological parameters. The present analysis is applied to the Chandra Deep Field South 2 Ms public released data. Within "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1202.0396","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"}