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Discovery of peculiar radio morphologies with ASKAP using unsupervised machine learning

Published online by Cambridge University Press:  20 October 2022

Nikhel Gupta*
Affiliation:
CSIRO Space & Astronomy, PO Box 1130, Bentley, WA 6102, Australia
Minh Huynh
Affiliation:
CSIRO Space & Astronomy, PO Box 1130, Bentley, WA 6102, Australia International Centre for Radio Astronomy Research (ICRAR), M468, The University of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia
Ray P. Norris
Affiliation:
Western Sydney University, Locked Bag 1797, Penrith, NSW 2751, Australia CSIRO Space & Astronomy, P.O. Box 76, Epping, NSW 1710, Australia
X. Rosalind Wang
Affiliation:
Western Sydney University, Locked Bag 1797, Penrith, NSW 2751, Australia
Andrew M. Hopkins
Affiliation:
Western Sydney University, Locked Bag 1797, Penrith, NSW 2751, Australia Australian Astronomical Optics, Macquarie University, 105 Delhi Rd, North Ryde, NSW 2113, Australia
Heinz Andernach
Affiliation:
Depto. de Astronomía, DCNE, Universidad de Guanajuato, Cjón. de Jalisco s/n, Guanajuato, CP 36023, Mexico
Bärbel S. Koribalski
Affiliation:
Western Sydney University, Locked Bag 1797, Penrith, NSW 2751, Australia CSIRO Space & Astronomy, P.O. Box 76, Epping, NSW 1710, Australia
Tim J. Galvin
Affiliation:
International Centre for Radio Astronomy Research, Curtin University, Bentley, WA 6102, Australia
*
Corresponding author: Nikhel Gupta, Email: Nikhel.Gupta@csiro.au.

Abstract

We present a set of peculiar radio sources detected using an unsupervised machine learning method. We use data from the Australian Square Kilometre Array Pathfinder (ASKAP) telescope to train a self-organizing map (SOM). The radio maps from three ASKAP surveys, Evolutionary Map of Universe pilot survey (EMU-PS), Deep Investigation of Neutral Gas Origins pilot survey (DINGO), and Survey With ASKAP of GAMA-09 + X-ray (SWAG-X), are used to search for the rarest or unknown radio morphologies. We use an extension of the SOM algorithm that implements rotation and flipping invariance on astronomical sources. The SOM is trained using the images of all ‘complex’ radio sources in the EMU-PS which we define as all sources catalogued as ‘multi-component’. The trained SOM is then used to estimate a similarity score for complex sources in all surveys. We select 0.5% of the sources that are most complex according to the similarity metric and visually examine them to find the rarest radio morphologies. Among these, we find two new odd radio circle (ORC) candidates and five other peculiar morphologies. We discuss multiwavelength properties and the optical/infrared counterparts of selected peculiar sources. In addition, we present examples of conventional radio morphologies including: diffuse emission from galaxy clusters, and resolved, bent-tailed, and FR-I and FR-II type radio galaxies. We discuss the overdense environment that may be the reason behind the circular shape of ORC candidates.

Type
Research Article
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of the Astronomical Society of Australia

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References

Abbott, T. M. C., et al. 2018, ApJS, 239, 18Google Scholar
Abell, G. O., Corwin, H. G., & Olowin, R. P. 1989, ApJS, 70, 1Google Scholar
Alam, S., et al. 2015, ApJS, 219, 12Google Scholar
Alger, M. J., et al. 2018, MNRAS, 478, 5547Google Scholar
Ananthakrishnan, S., & Pramesh Rao, A. 2001, in 2001 Asia-Pacific Radio Science Conference AP-RASC’01, 237Google Scholar
Becker, R. H., White, R. L., & Helfand, D. J. 1995, ApJ, 450, 559Google Scholar
Bilicki, M., Jarrett, T. H., Peacock, J. A., Cluver, M. E., & Steward, L. 2014, ApJS, 210, 9CrossRefGoogle Scholar
Bleem, L. E., et al. 2015, ApJS, 216, 27Google Scholar
Bleem, L. E., et al. 2019, arXiv e-prints, arXiv:1910.04121Google Scholar
Brett, D. R., West, R. G., & Wheatley, P. J. 2004, MNRAS, 353, 369Google Scholar
Brott, I., & Hauschildt, P. H. 2005, in ESA Special Publication, Vol. 576, The Three-Dimensional Universe with Gaia, ed. C. Turon, K. S. O’Flaherty, & M. A. C. Perryman, 565Google Scholar
Brunner, H., et al. 2021, arXiv e-prints, arXiv:2106.14517Google Scholar
Chow-Martínez, M., Andernach, H., Caretta, C. A., & Trejo-Alonso, J. J. 2014, MNRAS, 445, 4073Google Scholar
Coble, K., et al. 2007, AJ, 134, 897Google Scholar
Colbert, E. J. M., Baum, S. A., Gallimore, J. F., O’Dea, C. P., & Christensen, J. A. 1996, ApJ, 467, 551Google Scholar
Colless, M., et al. 2003, arXiv e-prints, arXiv:0306581Google Scholar
Condon, J. J. 1992, ARA&A, 30, 575Google Scholar
Couto da Silva, T. C., & de Souza, R. E. 2006, A&A, 457, 425Google Scholar
Cutri, R. M., et al. 2021, VizieR Online Data Catalog, II/328Google Scholar
DeBoer, D. R., et al. 2009, IEEE Proceedings, 97, 1507Google Scholar
Díaz-Giménez, E., & Zandivarez, A. 2015, A&A, 578, A61Google Scholar
Durret, F., et al. 2011, A&A, 535, A65CrossRefGoogle Scholar
Eilek, J. A., Burns, J. O., O’Dea, C. P., & Owen, F. N. 1984, ApJ, 278, 37Google Scholar
Ekers, R. D. 2009, in Proceedings of the special session “Accelerating the Rate of Astronomical Discovery” of the 27th IAU General Assembly. August 11–14 2009. Rio de Janeiro, 7Google Scholar
Fanaroff, B. L., & Riley, J. M. 1974, MNRAS, 167, 31PGoogle Scholar
Flewelling, H. A., et al. 2020, ApJS, 251, 7Google Scholar
Galvin, T. J., et al. 2019, PASP, 131, 188009CrossRefGoogle Scholar
Galvin, T. J., et al. 2020, MNRAS, 497, 2730Google Scholar
Garn, T., Green, D. A., Riley, J. M., & Alexander, P. 2009, MNRAS, 397, 1101Google Scholar
Geach, J. E. 2012, MNRAS, 419, 2633Google Scholar
Giovannini, G., et al. 2020, A&A, 640, A108Google Scholar
Grouchy, R. D., Buta, R. J., Salo, H., & Laurikainen, E. 2010, AJ, 139, 2465Google Scholar
Gunn, J. E., & Gott, J. R. 1972, ApJ, 176, 1Google Scholar
Gupta, N., et al. 2017, MNRAS, 467, 3737Google Scholar
Gupta, N., et al. 2020, MNRAS, 494, 1705Google Scholar
Hay, S., O’Sullivan, J., Kot, J., & Granet, C. 2006, in ESA Special Publication, Vol. 626, The European Conference on Antennas and Propagation: EuCAP 2006, ed. H. Lacoste, & L. Ouwehand, 663Google Scholar
Hilton, M., et al. 2021, ApJS, 253, 3Google Scholar
Hotan, A. W., et al. 2021, PASA, 38, e009Google Scholar
Jarrett, T. H., et al. 2000, AJ, 119, 2498Google Scholar
Johnston, S., et al. 2007, PASA, 24, 174Google Scholar
Jonas, J., & MeerKAT Team. 2016, in MeerKAT Science: On the Pathway to the SKA, 1Google Scholar
Jones, D. H., et al. 2009, MNRAS, 399, 683Google Scholar
Kennicutt, R. C., & Evans, N. J. 2012, ARA&A, 50, 531Google Scholar
Koester, B. P., et al. 2007, ApJ, 660, 239Google Scholar
Kohonen, T. 1982, BC, 43, 59Google Scholar
Koribalski, B. S., et al. 2021, MNRAS, 505, L11Google Scholar
Kourkchi, E., & Tully, R. B. 2017, ApJ, 843, 16Google Scholar
Lacki, B. C., Thompson, T. A., & Quataert, E. 2010, ApJ, 717, 1Google Scholar
Lacy, M., et al. 2020, PASP, 132, 035001Google Scholar
Lauer, T. R., Postman, M., Strauss, M. A., Graves, G. J., & Chisari, N. E. 2014, ApJ, 797, 82CrossRefGoogle Scholar
Liu, A., et al. 2021, arXiv e-prints, arXiv:2106.14518Google Scholar
Lukic, V., et al. 2018, MNRAS, 476, 246Google Scholar
Mao, M. Y., Johnston-Hollitt, M., Stevens, J. B., & Wotherspoon, S. J. 2009, MNRAS, 392, 1070CrossRefGoogle Scholar
Maslej-Krešňáková, V., El Bouchefry, K., & Butka, P. 2021, MNRAS, 505, 1464Google Scholar
McConnell, D., et al. 2020, PASA, 37, e048Google Scholar
Meyer, M. 2009, in Panoramic Radio Astronomy: Wide-field 1-2 GHz Research on Galaxy Evolution, 15Google Scholar
Miley, G. K., Perola, G. C., van der Kruit, P. C., & van der Laan, H. 1972, Natur, 237, 269Google Scholar
Mostert, R. I. J., et al. 2021, A&A, 645, A89Google Scholar
Muriel, H., Nicotra, M. A., & Lambas, D. G. 1995, AJ, 110, 1032Google Scholar
Murphy, E. J., et al. 2006, ApJ, 638, 157Google Scholar
Murphy, E. J., et al. 2011, ApJ, 737, 67Google Scholar
Norris, R., et al. 2015, in Advancing Astrophysics with the Square Kilometre Array (AASKA14), 86Google Scholar
Norris, R. P. 2011, JApA, 32, 599Google Scholar
Norris, R. P., Crawford, E., & Macgregor, P. 2021a, Galaxies, 9, 83Google Scholar
Norris, R. P., et al. 2021a, PASA, 38, e046Google Scholar
Norris, R. P., et al. 2021b, PASA, 38, e003Google Scholar
Norris, R. P., et al. 2022, MNRAS, 513, 1300Google Scholar
Oguri, M., et al. 2018, PASJ, 70, S20Google Scholar
Otrupcek, R. E., & Wright, A. E. 1991, PASA, 9, 170Google Scholar
Perley, R. A., Chandler, C. J., Butler, B. J., & Wrobel, J. M. 2011, ApJ, 739, L1Google Scholar
Piffaretti, R., Arnaud, M., Pratt, G. W., Pointecouteau, E., & Melin, J.-B. 2011, A&A, 534, A109CrossRefGoogle Scholar
Planck Collaboration, , et al. 2014, A&A, 571, A29Google Scholar
Planck Collaboration, , et al. 2020, A&A, 641, A6Google Scholar
Pogge, R. W., & Eskridge, P. B. 1993, AJ, 106, 1405Google Scholar
Polsterer, K. L., Gieseke, F., & Igel, C. 2015, in Astronomical Society of the Pacific Conference Series, Vol. 495, Astronomical Data Analysis Software an Systems XXIV (ADASS XXIV), ed. A. R. Taylor, & E. Rosolowsky, 81Google Scholar
Ralph, N. O., et al. 2019, PASP, 131, 108011CrossRefGoogle Scholar
Rozo, E., Rykoff, E. S., Becker, M., Reddick, R. M., & Wechsler, R. H. 2015, MNRAS, 453, 38Google Scholar
Rykoff, E. S., et al. 2016, ApJS, 224, 1Google Scholar
Sakelliou, I., & Merrifield, M. R. 2000, MNRAS, 311, 649Google Scholar
Schlegel, D., et al. 2021, in American Astronomical Society Meeting Abstracts, Vol. 53, American Astronomical Society Meeting Abstracts, 235.03Google Scholar
Segal, G., et al. 2022, arXiv e-prints, arXiv:2206.14677Google Scholar
Seymour, N., et al. 2020, PASA, 37, e013Google Scholar
Skrutskie, M. F., et al. 2006, AJ, 131, 1163Google Scholar
Tingay, S. J., et al. 2013, PASA, 30, e007Google Scholar
Torniainen, I., et al. 2008, A&A, 482, 483Google Scholar
van Haarlem, M. P., et al. 2013, A&A, 556, A2Google Scholar
van Weeren, R. J., et al. 2019, Space Sci. Rev.,215, 16Google Scholar
Vlahakis, C., Eales, S., & Dunne, L. 2007, MNRAS, 379, 1042CrossRefGoogle Scholar
Wayth, R. B., et al. 2018, PASA, 35, e033Google Scholar
Wen, Z. L., & Han, J. L. 2015, ApJ, 807, 178Google Scholar
Wen, Z. L., Han, J. L., & Liu, F. S. 2012, ApJS, 199, 34Google Scholar
Wen, Z. L., Han, J. L., & Yang, F. 2018, MNRAS, 475, 343CrossRefGoogle Scholar
Whiting, M., & Humphreys, B. 2012, PASA, 29, 371Google Scholar
Whiting, M., Voronkov, M., Mitchell, D., & Askap Team, . 2017, in Astronomical Society of the Pacific Conference Series, Vol. 512, Astronomical Data Analysis Software and Systems XXV, ed. N. P. F. Lorente, K. Shortridge, & R. Wayth, 431Google Scholar
Wong, O. I., et al. 2006, MNRAS, 371, 1855Google Scholar
Wright, A. E., Griffith, M. R., Burke, B. F., & Ekers, R. D. 1994, ApJS, 91, 111Google Scholar
Wright, A. H., Hildebrandt, H., van den Busch, J. L., & Heymans, C. 2020, A&A, 637, A100Google Scholar
Wright, E. L., et al. 2010, AJ, 140, 1868Google Scholar
Wu, C., et al. 2019, MNRAS, 482, 1211Google Scholar
Zou, H., Gao, J., Zhou, X., & Kong, X. 2020, VizieR Online Data Catalog, J/ApJS/242/8Google Scholar
Zou, H., et al. 2021, ApJS, 253, 56Google Scholar