Prof. Matt Jarvis

Abstract:

The MeerKAT International GigaHertz Tiered Extragalactic Exploration (MIGHTEE) is one of the MeerKAT large survey projects, designed to pathfind SKA key science. MIGHTEE is undertaking deep radio imaging of four well-observed fields (COSMOS, XMM-LSS, ELAIS S1, and CDFS) totaling 20 square degrees to μJy sensitivities. Broad-band imaging observations between 880 and1690 MHz yield total intensity continuum, spectro-polarimetry, and atomic hydrogen spectral imaging. Early science data from MIGHTEE are being released from initial observations of COSMOS and XMM–LSS. This paper describes the spectro-polarimetric observations, the polarization data processing of the MIGHTEE early science fields, and presents polarization data images and catalogues. The catalogues include radio spectral index, redshift information, and Faraday rotation measure synthesis results for 13 267 total intensity radio sources down to a polarized intensity detection limit of ∼20 μJy bm−1. Polarized signals were detected from 324 sources. For the polarized detections, we include a catalogue of Faraday Depth from both Faraday Synthesis and Q, U fitting, as well as total intensity and polarization spectral indices. The distribution of redshift of the total radio sources and detected polarized sources are the same, with median redshifts of 0.86 and 0.82, respectively. Depolarization of the emission at longer-wavelengths is seen to increase with decreasing total-intensity spectral index, implying that depolarization is intrinsic to the radio sources. No evidence is seen for a redshift dependence of the variance of Faraday depth.

Abstract:

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⁻¹ 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 the redshift distribution of SFG and AGN to the SKADS and T-RECS simulations and find more AGN than predicted at z ∼ 1.

Abstract:

Covering ∼ 5600 deg2 to rms sensitivities of ∼70−100 μJy beam−1, the LOFAR Two-metre Sky Survey Data Release 2 (LoTSS-DR2) provides the largest low-frequency (∼150 MHz) radio catalogue to date, making it an excellent tool for large-area radio cosmology studies. In this work, we use LoTSS-DR2 sources to investigate the angular two-point correlation function of galaxies within the survey. We discuss systematics in the data and an improved methodology for generating random catalogues, compared to that used for LoTSS-DR1, before presenting the angular clustering for ∼900 000 sources ≥1.5 mJy and a peak signal-to-noise ≥ 7.5 across ∼80 per cent of the observed area. Using the clustering, we infer the bias assuming two evolutionary models. When fitting angular scales of 0.5 ≤ θ < 5◦, using a linear bias model, we find LoTSS-DR2 sources are biased tracers of the underlying matter, with a bias of bC = 2.14+0.22 −0.20 (assuming constant bias) and bE(z = 0) = 1.79+0.15 −0.14 (for an evolving model, inversely proportional to the growth factor), corresponding to bE = 2.81+0.24 −0.22 at the median redshift of our sample, assuming the LoTSS Deep Fields redshift distribution is representative of our data. This reduces to bC = 2.02+0.17 −0.16 and bE(z = 0) = 1.67+0.12 −0.12 when allowing preferential redshift distributions from the Deep Fields to model our data. Whilst the clustering amplitude is slightly lower than LoTSS-DR1 (≥2 mJy), our study benefits from larger samples and improved redshift estimates.