Extragalactic radio source evolution under the dual - population unification scheme

We show that a dual-population unification scheme provides a successful paradigm with which to describe the evolution and beaming of all bright extragalactic radio sources. The paradigm consists of two intrinsic radio-source populations, based on the two distinct radio-galaxy morphologies of Fanaroff-Riley classes I and II. These represent the 'unbeamed' or 'side-on' parent populations of steep radio spectra; the 'beamed' source types including flat-spectrum quasars and BL Lac objects, arise through the random alignment of their radio-axis to our line-of-sight where Doppler-beaming of the relativistic radio jets produces highly anisotropic radio emission. We develop the model in two stages. In the first stage the source space density as a function of cosmic epoch is determined for the two parent populations, and for this we use low-frequency source-count and identification data to avoid biases due to Doppler-enhanced radio emission. The second stage defines the beaming models for each population, using high-frequency survey data and in particular the 5-GHz source count in which at high flux densities the flat-and steep-spectrum sources contribute in similar measure. We assume that the flat-spectrum objects, quasars and BL Lac objects are 'beamed' versions of FRI and FRII objects in which the close alignment of radio-axis with line-of-sight has changed the radio appearance into a core-dominated (flat-spectrum) object. We adopt a simple parameterisation of the beaming, orient the parent populations at random with a Monte-Carlo process, and use a minimisaton process to determine beaming parameters which yield a best fit to the 5-GHz souce count. The best-fit parameters are found to be in good agreement with those measured observationally for individual radio sources. In this, the model accurately reproduces the change in source-count form with frequency. Indeed the unified-scheme paradigm has great predictive power, and we show how the model successfully describes several additional and independent data sets.