Cosmology from LOFAR Two-metre Sky Survey Data Release 2: angular clustering of radio sources
Cosmology from LOFAR Two-metre Sky Survey Data Release 2: angular clustering of radio sources
复制标题
LOFAR 两米巡天数据发布 2 的宇宙学：无线电源的角聚类
DOI：
10.1093/mnras/stad3088
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发表时间：
2024
影响因子：
4.8
通讯作者：
Hale C
中科院分区：
文献类型：
--
作者：
Hale C
LOFAR两米巡天数据发布2（LoTSS-DR 2）覆盖到均方根灵敏度为1070 − 100 Jy波束-1，提供了迄今为止最大的低频（150 MHz）射电目录，使其成为大面积射电宇宙学研究的绝佳工具。在这项工作中，我们使用LoTSS-DR 2源来研究调查中星系的角两点相关函数。我们讨论了数据中的系统学以及与LoTSS-DR 1相比用于生成随机目录的改进方法，然后在80%的观测面积上呈现了1090 000个≥1.5 mJy的源的角度聚类和峰值信噪比≥ 7.5。使用聚类，我们推断假设两个进化模型的偏见。当使用线性偏置模型拟合的角度尺度时，我们发现LoTSS-DR 2源是底层物质的偏置示踪剂，偏置为（假设恒定偏置）和（对于不断发展的模型，与增长因子成反比），对应于我们样本的中值红移，假设LoTSS深场红移分布代表我们的数据。当允许深场的优先红移分布来模拟我们的数据时，这减少到和。虽然聚集幅度略低于LoTSS-DR 1（≥2 mJy），但我们的研究受益于更大的样本和改进的红移估计。
Coveringto rms sensitivities of ∼70−100Jy 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, using a linear bias model, we find LoTSS-DR2 sources are biased tracers of the underlying matter, with a bias of(assuming constant bias) and(for an evolving model, inversely proportional to the growth factor), corresponding toat the median redshift of our sample, assuming the LoTSS Deep Fields redshift distribution is representative of our data. This reduces toandwhen 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.