{"paper":{"title":"A machine-learning method for identifying multi-wavelength counterparts of submillimeter galaxies: training and testing using AS2UDS and ALESS","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.GA","authors_text":"(10) University of British Columbia, (11) Virginia Tech, (12) Leiden University, (13) University of Leicester, (14) Adam Mickiewicz University, (15) Dalhousie University), 2), (2) CEA Durham University, (3) University of Nottingham, (4) Gemini Observatory, (5) ESO, 6), (6) University of Edinburgh, (7) University of Manchester, (8) ASIAA, (9) University of Hertfordshire, A. M. Swinbank (2), A. P. Thomson (7), A. W. Blain (13), B. Gullberg (2), C. Conselice (3), Chian-Chou Chen (5), C. Simpson (4), D. Farrah (11), D. Scott (10), D. T. Maltby (3), E. A. Cooke (2), FangXia An (1, Ian Smail (2), J. E. Geach (9), J. L. Wardlow (2), J. M. Simpson (8), J. S. Dunlop (6), K. E. K. Coppin (9) ((1) Purple Mountain Observatory, M. J. Micha{\\l}owski (14), O. Almaini (3), P. van der Werf (12), R. J. Ivison (5, S. C. Chapman (15), S. M. Stach (2), V. Arumugam (5, W. Hartley (3)","submitted_at":"2018-06-18T18:00:00Z","abstract_excerpt":"We describe the application of the supervised machine-learning algorithms to identify the likely multi-wavelength counterparts to submillimeter sources detected in panoramic, single-dish submillimeter surveys. As a training set, we employ a sample of 695 ($S_{\\rm 870\\mu m}$ >1 mJy) submillimeter galaxies (SMGs) with precise identifications from the ALMA follow-up of the SCUBA-2 Cosmology Legacy Survey's UKIDSS-UDS field (AS2UDS). We show that radio emission, near-/mid-infrared colors, photometric redshift, and absolute $H$-band magnitude are effective predictors that can distinguish SMGs from "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.06859","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"}