MIGHTEE : total intensity radio continuum imaging and the COSMOS/XMM-LSS Early Science fields

Please read abstract in the article.The UK Science and Technology Facilities Council; the South African Radio Astronomy Observatory; the Leverhulme Trust through an Early Career Research Fellowship; the South African Research Chairs Initiative of the Department of Science and Technology; the National Research Foundation; the Science and Technology Foundation (FCT, Portugal); the UK STFC ; the South African Research Chairs Initiative of the Department of Science and Innovation; the Bundesministerium für Bildung und Forschung (BMBF); the Italian Ministry of Foreign Affairs and International Cooperation; the South African Department of Science and Technology’s National Research Foundation (DST-NRF).https://academic.oup.com/mnrashj2022Physic

MIGHTEE: the nature of the radio-loud AGN population

We study the nature of the faint radio source population detected in the MeerKAT International GHz Tiered Extragalactic Exploration (MIGHTEE) Early Science data in the COSMOS field, focusing on the properties of the radio-loud active galactic nuclei (AGNs). Using the extensive multiwavelength data available in the field, we are able to classify 88 per cent of the 5223 radio sources in the field with host galaxy identifications as AGNs (35 per cent) or star-forming galaxies (54 per cent). We select a sample of radio-loud AGNs with redshifts out to z ∼ 6 and radio luminosities 1020 1). We discuss that both a high black hole mass and black hole spin may be necessary to launch and sustain a dominant radio jet

MIGHTEE: multi-wavelength counterparts in the COSMOS field

In this paper we combine the Early Science radio continuum data from the MeerKAT International GHz Tiered Extragalactic Exploration (MIGHTEE) Survey, with optical and near-infrared data and release the cross-matched catalogues. The radio data used in this work covers 0.86 deg2 of the COSMOS field, reaches a thermal noise of 1.7 μJy/beam and contains 6102 radio components. We visually inspect and cross-match the radio sample with optical and near-infrared data from the Hyper Suprime-Cam (HSC) and UltraVISTA surveys. This allows the properties of active galactic nuclei and star-forming populations of galaxies to be probed out to z≈5. Additionally, we use the likelihood ratio method to automatically cross-match the radio and optical catalogues and compare this to the visually cross-matched catalogue. We find that 94 per cent of our radio source catalogue can be matched with this method, with a reliability of 95 per cent. We proceed to show that visual classification will still remain an essential process for the cross-matching of complex and extended radio sources. In the near future, the MIGHTEE survey will be expanded in area to cover a total of ∼20~deg2; thus the combination of automated and visual identification will be critical. We compare redshift distribution of SFG and AGN to the SKADS and T-RECS simulations and find more AGN than predicted at z∼1

MIGHTEE : are giant radio galaxies more common than we thought?

Please read abstract in the article.DATA AVAILABILITY: The data underlying this article were accessed from the South African Radio Astronomy Observatory (SARAO; www.ska.ac.za).The National Research Foundation (NRF), SARAO. MP, SMR, the UK Science and Technology Facilities Council, the Oxford Hintze Centre for Astrophysical Surveys that is funded through generous support from the Hintze Family Charitable Foundation, the Rhodes University Centre for Radio Astronomy Techniques and Technologies (RATT), the European Union’s Horizon 2020 research and innovation program under a Marie Skłodowska-Curie grant, the Inter-University Institute for Data Intensive Astronomy (IDIA), the South African Research Chairs Initiative of the NRF, the Glasstone Foundation, the Italian Ministry of Foreign Affairs and International Cooperation, the Science and Technology Foundation (FCT, Portugal), the Science and Technology Facilities Council (STFC), the South African Astronomical Observatory, the Bundesministerium für Bildung und Forschung (BMBF), the Inter-University Institute for Data Intensive Astronomy (IDIA) and the ERC-Stg DRANOEL.https://academic.oup.com/mnrashj2022Physic