Catherine Hale

Abstract:

Aims
We combined the LOw-Frequency ARray (LOFAR) Two-metre Sky Survey (LoTSS) second data release (DR2) catalogue with gravitational lensing maps from the cosmic microwave background (CMB) to place constraints on the bias evolution of LoTSS-detected radio galaxies, and on the amplitude of matter perturbations.
Methods
We constructed a flux-limited catalogue from LoTSS DR2, and analysed its harmonic-space cross-correlation with CMB lensing maps from Planck, Cℓgk, as well as its auto-correlation, Cℓgg. We explored the models describing the redshift evolution of the large-scale radio galaxy bias, discriminating between them through the combination of both Cℓgk and Cℓgg. Fixing the bias evolution, we then used these data to place constraints on the amplitude of large-scale density fluctuations, parametrised by σ8.
Results
We report the significance of the Cℓgk signal at a level of 26.6σ. We determined that a linear bias evolution of the form bg(z) = bg,D/D(z), where D(z) is the growth rate, is able to provide a good description of the data, and we measured bg,D = 1.41 ± 0.06 for a sample that is flux limited at 1.5 mJy, for scales ℓ < 250 for Cℓgg, and ℓ < 500 for Cℓgk. At the sample’s median redshift, we obtained b(z = 0.82) = 2.34 ± 0.10. Using σ8 as a free parameter, while keeping other cosmological parameters fixed to the Planck values, we found fluctuations of σ8 = 0.75−0.04+0.05. The result is in agreement with weak lensing surveys, and at 1σ difference with Planck CMB constraints. We also attempted to detect the late-time-integrated Sachs-Wolfe effect with LOFAR data; however, with the current sky coverage, the cross-correlation with CMB temperature maps is consistent with zero. Our results are an important step towards constraining cosmology with radio continuum surveys from LOFAR and other future large radio surveys.

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.