Identifying anomalous radio sources in the EMU Pilot Survey using a complexity-based approach

Segal, Gary P.; Parkinson, David; Norris, R. P.; Hopkins, A. M.; Andernach, H.; Alexander, Emma L.; Carretti, E.; Koribalski, B. S.; Legodi, L. S.; Leslie, S. K.; Luo, Yan; Pierce, Jonathon C. S.; Tang, Hongming; Vardoulaki, E.; Vernstrom, Tessa

doi:10.48550/arxiv.2206.14677

Cited by 3 publications

(3 citation statements)

References 33 publications

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“…For example, using self-organizing maps (SOMs; a form of unsupervised machine learning), Mostert et al (2021) scanned the LOFAR Two-meter Sky Survey (LoTSS) images for the highest outlier scores to find sources with rare morphologies, resulting in wide-angle tailed radio galaxies (WATs), narrow-angle tailed radio sources (NATs), relics and halos in galaxy clusters, but no ORCs were detected. Similarly, Segal et al (2022) searched for the most complex radio sources in the EMU Pilot Survey, only finding two known ORCs. Gupta et al (2022) also applied SOMs to a number of ASKAP fields, including the EMU Pilot Survey, finding the already known ORCs and, in addition, two new ORC candidates.…”

Section: Introductionmentioning

confidence: 99%

Insights on the Origin of Odd Radio Circles from Cosmological Simulations

Dolag

Böss

Koribalski

et al. 2023

ApJ

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We investigate shock structures driven by merger events in high-resolution simulations that result in a galaxy with a virial mass M ≈ 1012 M ⊙. We find that the sizes and morphologies of the internal shocks resemble remarkably well those of the newly detected class of odd radio circles (ORCs). This would highlight a so-far overlooked mechanism to form radio rings, shells, and even more complex structures around elliptical galaxies. Mach numbers of  = 2–3 for such internal shocks are in agreement with the spectral indices of the observed ORCs. We estimate that ∼5% of galaxies could undergo merger events, which occasionally lead to such prominent structures within the galactic halo during their lifetime, explaining the low number of observed ORCs. At the time when the shock structures are matching the physical sizes of the observed ORCs, the central galaxies are typically classified as early-type galaxies, with no ongoing star formation, in agreement with observational findings. Although the energy released by such mergers could potentially power the observed radio luminosity already in Milky Way–like halos, our predicted luminosity from a simple, direct shock acceleration model is much smaller than the observed one. Considering the estimated number of candidates from our cosmological simulations and the higher observed energies, we suggest that the proposed scenario is more likely for halo masses around 1013 M ⊙ in agreement with the observed stellar masses of the galaxies at the center of ORCs. Such shocks might be detectable with next-generation X-ray instruments like the Line Emission Mapper (LEM).

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Section: Introductionmentioning

confidence: 99%

Insights on the Origin of Odd Radio Circles from Cosmological Simulations

Dolag

Böss

Koribalski

et al. 2023

ApJ

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“…To approach a solution, Ralph et al (2019) used a convolutional auto-encoder to reduce the impact of affine transformations for the classification of radio galaxies. Similarly, Segal et al (2022) are using autoencoders to measure the complexity of radio galaxies. However, the training of the SOM using the compressed latent vector space of auto-encoders results in the loss of topological information.…”

Section: Self Organizing Mapmentioning

confidence: 99%

Discovery of peculiar radio morphologies with ASKAP using unsupervised machine learning

Gupta

Huynh

Norris

et al. 2022

Publ. Astron. Soc. Aust.

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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.

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“…An alternative to manual search is machine learning: a set of algorithms designed to automatically learn patterns and models from data, which has the potential to assist in rapidly sorting through data to locate interesting sources in large astronomical datasets. Recent unsupervised machine learning approaches have proven very effective at discovering radio ★ E-mail: dr.michelle.lochner@gmail.com galaxies with unusual morphology (Segal et al 2019(Segal et al , 2022Galvin et al 2020;Mostert et al 2021;Gupta et al 2022).…”

Section: Introductionmentioning

confidence: 99%

A unique, ring-like radio source with quadrilateral structure detected with machine learning

Lochner

Rudnick

Heywood

et al. 2023

Monthly Notices of the Royal Astronomical Society

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We report the discovery of a unique object in the MeerKAT Galaxy Cluster Legacy Survey (MGCLS) using the machine learning anomaly detection framework Astronomaly. This strange, ring-like source is 30′ from the MGCLS field centred on Abell 209, and is not readily explained by simple physical models. With an assumed host galaxy at redshift 0.55, the luminosity (1025 W Hz−1) is comparable to powerful radio galaxies. The source consists of a ring of emission 175 kpc across, quadrilateral enhanced brightness regions bearing resemblance to radio jets, two “ears” separated by 368 kpc, and a diffuse envelope. All of the structures appear spectrally steep, ranging from -1.0 to -1.5. The ring has high polarization (25%) except on the bright patches (<10%). We compare this source to the Odd Radio Circles recently discovered in ASKAP data and discuss several possible physical models, including a termination shock from starburst activity, an end-on radio galaxy, and a supermassive black hole merger event. No simple model can easily explain the observed structure of the source. This work, as well as other recent discoveries, demonstrates the power of unsupervised machine learning in mining large datasets for scientifically interesting sources.

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Identifying anomalous radio sources in the EMU Pilot Survey using a complexity-based approach

Cited by 3 publications

References 33 publications

Insights on the Origin of Odd Radio Circles from Cosmological Simulations

Insights on the Origin of Odd Radio Circles from Cosmological Simulations

Discovery of peculiar radio morphologies with ASKAP using unsupervised machine learning

A unique, ring-like radio source with quadrilateral structure detected with machine learning

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