Discovery of peculiar radio morphologies with ASKAP using unsupervised machine learning. (20th October 2022)
- Record Type:
- Journal Article
- Title:
- Discovery of peculiar radio morphologies with ASKAP using unsupervised machine learning. (20th October 2022)
- Main Title:
- Discovery of peculiar radio morphologies with ASKAP using unsupervised machine learning
- Authors:
- Gupta, Nikhel
Huynh, Minh
Norris, Ray P.
Rosalind Wang, X.
Hopkins, Andrew M.
Andernach, Heinz
Koribalski, Bärbel S.
Galvin, Tim J. - Abstract:
- 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 ORCAbstract: 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. … (more)
- Is Part Of:
- Publications of the Astronomical Society of Australia. Volume 39(2022)
- Journal:
- Publications of the Astronomical Society of Australia
- Issue:
- Volume 39(2022)
- Issue Display:
- Volume 39, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 39
- Issue:
- 2022
- Issue Sort Value:
- 2022-0039-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-10-20
- Subjects:
- galaxies: active -- galaxies: peculiar -- radio continuum: galaxies -- Galaxy: evolution -- methods: data analysis
Astronomy -- Periodicals
Southern sky (Astronomy) -- Periodicals
Astrophysics -- Periodicals
Periodicals
520.5 - Journal URLs:
- http://journals.cambridge.org/action/displayJournal?jid=pas ↗
http://www.publish.csiro.au/?nid=138 ↗ - DOI:
- 10.1017/pasa.2022.44 ↗
- Languages:
- English
- ISSNs:
- 1323-3580
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 24314.xml