MeerKAT

Abstract:

Faraday rotation measure (RM) is arguably the most practical observational tracer of magnetic fields in the diffuse circumgalactic medium (CGM). We sample synthetic Faraday rotation skies of Milky Way-like galaxies in TNG50 of the IllustrisTNG project by placing an observer inside the galaxies at a solar circle-like position. Our synthetic RM grids emulate specifications of current and upcoming surveys; the NRAO VLA Sky Survey (NVSS), the Polarisation Sky Survey of the Universe's Magnetism (POSSUM), and a future Square Kilometre Array (SKA1-mid) polarization survey. It has been suggested that magnetic fields regulate the survival of high-velocity clouds. However, there is only a small number of observational detections of magnetized clouds thus far. In the first part of the paper, we test conditions for the detection of magnetized circumgalactic clouds. Based on the synthetic RM samplings of clouds in the simulations, we predict upcoming polarimetric surveys will open opportunities for the detection of even low-mass and distant clouds. In the second part of the paper, we investigate the imprint of the CGM in the all-sky RM distribution. We test whether the RM variation produced by the CGM is correlated with global galaxy properties, such as distance to a satellite, specific star formation rate, neutral hydrogen covering fraction, and accretion rate to the supermassive black hole. We argue that the observed fluctuation in the RM measurements on scales less than 1, which has been considered an indication of intergalactic magnetic fields, might in fact incorporate a significant contribution of the Milky Way CGM.

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.