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MIGHTEE: The Continuum Survey Data Release 1

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abstract

The MeerKAT International GHz Tiered Extragalactic Exploration Survey (MIGHTEE) is one of the large survey projects using the MeerKAT telescope, covering four fields that have a wealth of ancillary data available. We present Data Release 1 of the MIGHTEE continuum survey, releasing total intensity images and catalogues over $\sim$20 deg$^2$, across three fields at $\sim$1.2-1.3 GHz. This includes 4.2 deg$^2$ over the Cosmic Evolution Survey (COSMOS) field, 14.4 deg$^2$ over the XMM Large-Scale Structure (XMM-LSS) field and deeper imaging over 1.5 deg$^2$ of the Extended Chandra Deep Field South (CDFS). We release images at both a lower resolution (7-9 arcsec) and higher resolution ($\sim 5$ arcsec). These images have central rms sensitivities of $\sim$1.3$-$2.7 $\mu $Jy beam$^{-1}$ ($\sim$1.2$-$3.6 $\mu $Jy beam$^{-1}$) in the lower (higher) resolution images respectively. We also release catalogues comprised of $\sim$144~000 ($\sim$114 000) sources using the lower (higher) resolution images. We compare the astrometry and flux-density calibration with the Early Science data in the COSMOS and XMM-LSS fields and previous radio observations in the CDFS field, finding broad agreement. Furthermore, we extend the source counts at the $\sim$10 $\mu$Jy level to these larger areas ($\sim 20$ deg$^2$) and, using the areal coverage of MIGHTEE we measure the sample variance for differing areas of sky. We find a typical sample variance of 10-20 per cent for 0.3 and 0.5 sq. deg. sub-regions at $S_{1.4} \leq 200$ $\mu $Jy, which increases at brighter flux densities, given the lower source density and expected higher galaxy bias for these sources.

fields

astro-ph.IM 1

years

2026 1

verdicts

ACCEPT 1

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Source Finding and Characterisation for SKAO Science

astro-ph.IM · 2026-07-04 · accept · novelty 2.0

A review of classical and ML source-finding and morphological classification techniques for SKAO-scale continuum and spectral-line surveys, with emphasis on limitations and pipeline needs.

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  • Source Finding and Characterisation for SKAO Science astro-ph.IM · 2026-07-04 · accept · none · ref 120 · internal anchor

    A review of classical and ML source-finding and morphological classification techniques for SKAO-scale continuum and spectral-line surveys, with emphasis on limitations and pipeline needs.