J/other/PASA/42.ivo://CDS.VizieR/J/other/PASA/42.13CDSAlam A.Pimbblet K.A.Gordon Y.A.2025-10-01T06:29:29Z2025-09-18T10:10:50ZCDS support team

CDS, Observatoire de Strasbourg, 11 rue de l'Universite, F-67000 Strasbourg, France

cds-question@unistra.frradio-galaxiesradio-sourcesradio-continuum-emissiongalaxy-classification-systemsNext generations of radio surveys are expected to identify tens of millions of new sources, and identifying and classifying their morphologies will require novel and more efficient methods. Self-Organising Maps (SOMs), a type of unsupervised machine learning, can be used to address this problem. We map 251259 multi-Gaussian sources from Rapid ASKAP Continuum Survey (RACS) onto a SOM with discrete neurons. Similarity metrics, such as Euclidean distances, can be used to identify the best-matching neuron or unit (BMU) for each input image. We establish a reliability threshold by visually inspecting a subset of input images and their corresponding BMU. We label the individual neurons based on observed morphologies and these labels are included in our value-added catalogue of RACS sources. Sources for which the Euclidean distance to their BMU is =~5 (accounting for approximately 79% of sources) have an estimated >90% reliability for their SOM-derived morphological labels. This reliability falls to less than 70% at Euclidean distances >=7. Beyond this threshold it is unlikely that the morphological label will accurately describe a given source. Our catalogue of complex radio sources from RACS with their SOM-derived morphological labels from this work will be made publicly available.2025PASA...42...13Ahttps://cdsarc.cds.unistra.fr/viz-bin/cat/J/other/PASA/42.13CatalogResearchIsServedByTAP VizieR generic serviceIsServedByConesearch servicerelated-toJ/other/PASA/38.58 : Rapid ASKAP Continuum Survey. II. RACS cat. (Hale+, 2021)https://cds.unistra.fr/vizier-org/licences_vizier.htmlhttps://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/other/PASA/42.13https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/other/PASA/42.13http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/other/PASA/42.13https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/other/PASA/42.13https://vizier.iucaa.in/viz-bin/votable?-source=J/other/PASA/42.13http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/other/PASA/42.13GETtext/xml+votablehttps://tapvizier.cds.unistra.fr/TAPVizieR/tapCone search capability for table J/other/PASA/42.13/somracs (Catalogue of complex radio sources)https://vizier.cds.unistra.fr/viz-bin/conesearch/J/other/PASA/42.13/somracs?https://vizier.iucaa.in/viz-bin/conesearch/J/other/PASA/42.13/somracs?http://vizieridia.saao.ac.za/viz-bin/conesearch/J/other/PASA/42.13/somracs?GETtext/xml+votable180.050000true3.1367769413.912658890.0055555555555555561/33 43 2/1 32-34 64-65 67 72 80 98-100 103 105-106 120 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46533-46535 46848 46850-46851 47317-47319 47324-47326 47940-47941 47943 48501 48503 48828-48830 48860-48862https://cdsarc.cds.unistra.fr/viz-bin/moc/J/other/PASA/42.13?format=asciiOpticalRadiodefaultJ/other/PASA/42.13/somracsCatalogue of complex radio sourcesrecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintNameSource name from RACS-Low, RACS-DR1 JHHMMSS.s+DDMMSS (1)meta.id;meta.maincharIDSource identifier from RACS-Low, RACS_HHMM+NNA_NNNN (1)meta.idcharRA_ICRSRight Ascension (ICRS) from RACS-Low (1)degpos.eq.ra;meta.mainindexedDE_ICRSDeclination (ICRS) from RACS-Low (1)degpos.eq.dec;meta.mainindexedbmuPosition of the best matching unit or neuron in the SOM grid in the format (y, x) (2)stat.fit.paramcharDistEuclEuclidean distance to the BMU (2)stat.fit.paramdoubleMorpLabelMorphological label based on the visual inspection of the individual neurons in the SOM grid (3)src.morph.typecharMatchReliability (in percentage) based on the validation process (4)%meta.code.qualfloat