Constraints on the Clustering, Biasing and Redshift Distribution of Radio Sources

Details Constraints on the Clustering, Biasing and Redshift Distribution of Radio Sources Constraints on the Clustering, Biasing and Redshift Distribution of Radio Sources

1998-06-25

arxiv.org/abs/astro-ph/9806342v2

Astronomy and Astrophysics

Astrophysics

14 pages, 12 figures, version to appear on MNRAS

Scientific paper

10.1046/j.1365-8711.1999.02596.x

We discuss how different theoretical predictions for the variance $\sigma^2$ of the distribution of radio sources can be matched to measurements from the FIRST survey at different flux limits. The predictions are given by the integration of models for the angular correlation function $w(\theta)$ for three different functional forms of the redshift distribution $N(z)$, different spatial correlation functions and by different evolutions of the bias $b(z)$ with redshift. We also consider the two cases of open and flat Universes. Although the predicted $w(\theta)$ show substantial differences due to differences in the $N(z)$'s, these differences are not significant compared to the uncertainties in the current observations. It turns out that the best fit is provided by models with constant biasing at all times, although the difference between models with epoch-independent bias and models with bias that evolves linearly with redshift is not very large. All models with strong evolution of bias with epoch are ruled out. As a further step we directly calculated $w_{obs}(\theta)$ at 3mJy from the catalogue and matched it with our models for the angular correlation function in the hypothesis that the clustering signal comes from two different populations, namely AGN-powered sources and starbursting galaxies. The results are consistent with a scenario for hierarchical clustering where the fainter starbursting galaxies trace the mass at all epochs, while brighter AGN's are strongly biased, with $b(z)$ evolving linearly with redshift, as suggested by some theories of galaxy formation and evolution.

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