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Cosmology from LOFAR Two-metre Sky Survey data release 2: angular clustering of radio sources

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.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1093/mnras/stad3088

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Institution:
University of Oxford
Division:
MPLS
Department:
Physics
Sub department:
Astrophysics
Oxford college:
Christ Church
Role:
Author
ORCID:
0000-0002-4598-9719


Publisher:
Oxford University Press
Journal:
Monthly Notices of the Royal Astronomical Society More from this journal
Volume:
527
Issue:
3
Pages:
6540-6568
Publication date:
2023-10-13
Acceptance date:
2023-10-05
DOI:
EISSN:
1365-2966
ISSN:
0035-8711


Language:
English
Keywords:
Pubs id:
1591790
Local pid:
pubs:1591790
Deposit date:
2024-03-02

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