Data

Catalogue of Radio Galaxies in the EMU Pilot Survey

Commonwealth Scientific and Industrial Research Organisation
Gupta, Nikhel ; Norris, Ray ; Hayder, Zeeshan ; Huynh, Minh ; Petersson, Lars ; Hopkins, Andrew ; Wang, Rosalind ; Andernach, Heinz ; Gordon, Yjan ; Riggi, Simone ; Yew, Miranda ; Crawford, Evan ; Koribalski, Baerbel ; Filipovic, Miroslav ; Kapinska, Anna ; Shabala, Stanislav ; Vernstrom, Tessa ; Marvil, Josh
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25919/ypfp-0p69&rft.title=Catalogue of Radio Galaxies in the EMU Pilot Survey&rft.identifier=https://doi.org/10.25919/ypfp-0p69&rft.publisher=Commonwealth Scientific and Industrial Research Organisation&rft.description=This collection presents the first ML generated catalogue of radio galaxies from the 270 square degrees pilot survey of the Evolutionary Map of the Universe (EMU-PS, see related links) conducted with the Australian Square Kilometre Array Pathfinder (ASKAP, see related links) telescope. The detection pipeline employs Gal-DINO computer-vision networks (see related links) to predict the categories of radio morphology, bounding boxes for radio sources, and potential infrared host positions. These networks are trained and evaluated on around 5,000 visually inspected radio galaxies and their infrared hosts, encompassing both compact and extended radio morphologies. The evaluation shows high accuracy, with over 99% of predicted bounding boxes having an Intersection over Union (IoU) larger than 0.5 and 98% of predicted host positions being within 3 arcseconds of the ground truth. The catalogue construction pipeline utilizes the predictions of the trained network on radio and infrared image cutouts based on the catalogue of radio components identified using the Selavy source finder algorithm. It prioritizes components with higher confidence scores, resulting in the identification of 211,625 radio sources, of which 201,211 are classified as compact and unresolved, and 10,414 are categorized as extended radio morphologies. Cross-matching with infrared and optical catalogues reveals infrared cross-matches for 73% and photometric redshifts for 36% of the radio galaxies. The EMU-PS catalogue and detection pipelines presented will contribute to the construction of catalogues for the main EMU survey covering the full southern sky.For more details, see the paper RG-CAT: Detection Pipeline and Catalogue of Radio Galaxies in the EMU Pilot Survey in the PASA journal.If the embargo period is in effect, please email me at nikhel.gupta(at)csiro.au, and I will provide you with a link.&rft.creator=Gupta, Nikhel &rft.creator=Norris, Ray &rft.creator=Hayder, Zeeshan &rft.creator=Huynh, Minh &rft.creator=Petersson, Lars &rft.creator=Hopkins, Andrew &rft.creator=Wang, Rosalind &rft.creator=Andernach, Heinz &rft.creator=Gordon, Yjan &rft.creator=Riggi, Simone &rft.creator=Yew, Miranda &rft.creator=Crawford, Evan &rft.creator=Koribalski, Baerbel &rft.creator=Filipovic, Miroslav &rft.creator=Kapinska, Anna &rft.creator=Shabala, Stanislav &rft.creator=Vernstrom, Tessa &rft.creator=Marvil, Josh &rft.date=2024&rft.edition=v1&rft.relation=https://www.cambridge.org/core/journals/publications-of-the-astronomical-society-of-australia/article/evolutionary-map-of-the-universe-pilot-survey/6FD673731F193C01A133A89602B75F86&rft.relation=https://www.cambridge.org/core/journals/publications-of-the-astronomical-society-of-australia/article/discovery-of-peculiar-radio-morphologies-with-askap-using-unsupervised-machine-learning/ACB0DFCE426EFAFBCEEBB5652A7087C1&rft.relation=https://www.cambridge.org/core/journals/publications-of-the-astronomical-society-of-australia/article/deep-learning-for-morphological-identification-of-extended-radio-galaxies-using-weak-labels/D5F735637BEF8715428C2D3DA6630E03&rft.relation=https://www.cambridge.org/core/journals/publications-of-the-astronomical-society-of-australia/article/radiogalaxynet-dataset-and-novel-computer-vision-algorithms-for-the-detection-of-extended-radio-galaxies-and-infrared-hosts/13E80EA6A425B6AC3D91D06FEC7E7C99&rft_rights=Creative Commons Attribution 4.0 International Licence https://creativecommons.org/licenses/by/4.0/&rft_rights=Data is accessible online and may be reused in accordance with licence conditions&rft_rights=All Rights (including copyright) CSIRO 2024.&rft_subject=catalogue&rft_subject=radio galaxies&rft_subject=AGN&rft_subject=radio surveys&rft_subject=machine learning&rft_subject=object detection&rft_subject=Machine learning not elsewhere classified&rft_subject=Machine learning&rft_subject=INFORMATION AND COMPUTING SCIENCES&rft_subject=Astronomical sciences not elsewhere classified&rft_subject=Astronomical sciences&rft_subject=PHYSICAL SCIENCES&rft.type=dataset&rft.language=English Access the data
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Data is accessible online and may be reused in accordance with licence conditions

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This collection presents the first ML generated catalogue of radio galaxies from the 270 square degrees pilot survey of the Evolutionary Map of the Universe (EMU-PS, see related links) conducted with the Australian Square Kilometre Array Pathfinder (ASKAP, see related links) telescope. The detection pipeline employs Gal-DINO computer-vision networks (see related links) to predict the categories of radio morphology, bounding boxes for radio sources, and potential infrared host positions. These networks are trained and evaluated on around 5,000 visually inspected radio galaxies and their infrared hosts, encompassing both compact and extended radio morphologies. The evaluation shows high accuracy, with over 99% of predicted bounding boxes having an Intersection over Union (IoU) larger than 0.5 and 98% of predicted host positions being within 3 arcseconds of the ground truth. The catalogue construction pipeline utilizes the predictions of the trained network on radio and infrared image cutouts based on the catalogue of radio components identified using the Selavy source finder algorithm. It prioritizes components with higher confidence scores, resulting in the identification of 211,625 radio sources, of which 201,211 are classified as compact and unresolved, and 10,414 are categorized as extended radio morphologies. Cross-matching with infrared and optical catalogues reveals infrared cross-matches for 73% and photometric redshifts for 36% of the radio galaxies. The EMU-PS catalogue and detection pipelines presented will contribute to the construction of catalogues for the main EMU survey covering the full southern sky.

For more details, see the paper "RG-CAT: Detection Pipeline and Catalogue of Radio Galaxies in the EMU Pilot Survey" in the PASA journal.

If the embargo period is in effect, please email me at nikhel.gupta(at)csiro.au, and I will provide you with a link.

Available: 2024-03-21

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Subjects
AGN | Astronomical Sciences | Astronomical Sciences Not Elsewhere Classified | Information and Computing Sciences | Machine Learning | Machine Learning Not Elsewhere Classified | Physical Sciences | catalogue | machine learning | object detection | radio galaxies | radio surveys |

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Identifiers
ACN 633 798 857