Search and identification of transient and variable radio sources using MeerKAT observations: a case study on the MAXI J1820+070 field Article Swipe
YOU?
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· 2022
· Open Access
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· DOI: https://doi.org/10.1093/mnras/stac2460
Many transient and variable sources detected at multiple wavelengths are also observed to vary at radio frequencies. However, these samples are typically biased towards sources that are initially detected in wide-field optical, X-ray, or gamma-ray surveys. Many sources that are insufficiently bright at higher frequencies are therefore missed, leading to potential gaps in our knowledge of these sources and missing populations that are not detectable in optical, X-rays, or gamma-rays. Taking advantage of new state-of-the-art radio facilities that provide high-quality wide-field images with fast survey speeds, we can now conduct unbiased surveys for transient and variable sources at radio frequencies. In this paper, we present an unbiased survey using observations obtained by MeerKAT, a mid-frequency (∼GHz) radio array in South Africa’s Karoo Desert. The observations used were obtained as part of a weekly monitoring campaign for X-ray binaries (XRBs) and we focus on the field of MAXI J1820+070. We develop methods to efficiently filter transient and variable candidates that can be directly applied to other data sets. In addition to MAXI J1820+070, we identify four likely active galactic nuclei, one source that could be a Galactic source (pulsar or quiescent XRB) or an AGN, and one variable pulsar. No transient sources, defined as being undetected in deep images, were identified leading to a transient surface density of <3.7 × 10−2 deg−2 at a sensitivity of 1 mJy on time-scales of 1 week at 1.4 GHz.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1093/mnras/stac2460
- https://academic.oup.com/mnras/article-pdf/517/2/2894/46579151/stac2460.pdf
- OA Status
- hybrid
- Cited By
- 11
- References
- 86
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4294714434
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4294714434Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1093/mnras/stac2460Digital Object Identifier
- Title
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Search and identification of transient and variable radio sources using MeerKAT observations: a case study on the MAXI J1820+070 fieldWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-09-01Full publication date if available
- Authors
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A. Rowlinson, J Meijn, Joe Bright, A. J. van der Horst, S. I. Chastain, S Fijma, R. P. Fender, Ian Heywood, R. A. M. J. Wijers, P. A. Woudt, Alex Andersson, G. R. Sivakoff, Evangelia Tremou, Laura DriessenList of authors in order
- Landing page
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https://doi.org/10.1093/mnras/stac2460Publisher landing page
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https://academic.oup.com/mnras/article-pdf/517/2/2894/46579151/stac2460.pdfDirect link to full text PDF
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YesWhether a free full text is available
- OA status
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hybridOpen access status per OpenAlex
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https://academic.oup.com/mnras/article-pdf/517/2/2894/46579151/stac2460.pdfDirect OA link when available
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Physics, Transient (computer programming), Field (mathematics), Variable (mathematics), Astrophysics, Identification (biology), Mathematical analysis, Operating system, Computer science, Mathematics, Pure mathematics, Biology, BotanyTop concepts (fields/topics) attached by OpenAlex
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11Total citation count in OpenAlex
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2025: 3, 2024: 3, 2023: 5Per-year citation counts (last 5 years)
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86Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.No | 199 |
| abstract_inverted_index.We | 149 |
| abstract_inverted_index.an | 106, 193 |
| abstract_inverted_index.as | 129, 203 |
| abstract_inverted_index.at | 7, 15, 43, 98, 222, 233 |
| abstract_inverted_index.be | 161, 184 |
| abstract_inverted_index.by | 112 |
| abstract_inverted_index.in | 30, 53, 66, 119, 206 |
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| abstract_inverted_index.on | 143, 228 |
| abstract_inverted_index.or | 34, 69, 189, 192 |
| abstract_inverted_index.to | 13, 50, 152, 164, 170, 212 |
| abstract_inverted_index.we | 87, 104, 141, 173 |
| abstract_inverted_index.× | 219 |
| abstract_inverted_index.1.4 | 234 |
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| abstract_inverted_index.and | 3, 59, 95, 140, 156, 195 |
| abstract_inverted_index.are | 10, 21, 27, 40, 46, 63 |
| abstract_inverted_index.can | 88, 160 |
| abstract_inverted_index.for | 93, 136 |
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| abstract_inverted_index.AGN, | 194 |
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| abstract_inverted_index.MAXI | 147, 171 |
| abstract_inverted_index.Many | 1, 37 |
| abstract_inverted_index.XRB) | 191 |
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| abstract_inverted_index.fast | 84 |
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| abstract_inverted_index.with | 83 |
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| abstract_inverted_index.South | 120 |
| abstract_inverted_index.X-ray | 137 |
| abstract_inverted_index.array | 118 |
| abstract_inverted_index.being | 204 |
| abstract_inverted_index.could | 183 |
| abstract_inverted_index.field | 145 |
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| abstract_inverted_index.radio | 16, 76, 99, 117 |
| abstract_inverted_index.sets. | 167 |
| abstract_inverted_index.these | 19, 57 |
| abstract_inverted_index.using | 109 |
| abstract_inverted_index.(XRBs) | 139 |
| abstract_inverted_index.10−2 | 220 |
| abstract_inverted_index.Taking | 71 |
| abstract_inverted_index.X-ray, | 33 |
| abstract_inverted_index.active | 177 |
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| abstract_inverted_index.filter | 154 |
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| abstract_inverted_index.(pulsar | 188 |
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| abstract_inverted_index.images, | 208 |
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| abstract_inverted_index.(∼GHz) | 116 |
| abstract_inverted_index.ABSTRACT | 0 |
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| abstract_inverted_index.variable | 4, 96, 157, 197 |
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| abstract_inverted_index.gamma-ray | 35 |
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| abstract_inverted_index.undetected | 205 |
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| cited_by_percentile_year.min | 96 |
| corresponding_author_ids | https://openalex.org/A5072917215 |
| countries_distinct_count | 6 |
| institutions_distinct_count | 14 |
| corresponding_institution_ids | https://openalex.org/I887064364, https://openalex.org/I922237871 |
| citation_normalized_percentile.value | 0.95719534 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |