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The principal goals of evolutionary models are (1) to estimate the generalized luminosity function rhom(L, alpha,...| z, nu) of radio sources, (2) to explain significant features in the observed source counts, spectral-index distributions, redshift distributions, etc. (e.g., Kellermann 1972), and (3) to identify new observations that will constrain future models most effectively. Existing data cannot fully determine the evolving luminosity function, so practical models incorporate additional assumptions about source evolution. The computations must be simplified by approximations as well - source spectra are taken to be simple power laws, spectral-index distributions may be replaced by Gaussians or even delta-functions, and evolution may be described by smooth functions with a limited number of free parameters.

A typical model-generating procedure is:

  1. Choose a particular world model to fix the effective distance D and the volume element dV (Section 15.2). The Einstein-de Sitter (Omega = 1) model is most commonly picked, but changing Omega has only a small, easily estimated effect (Peacock 1985).

  2. Guess a form for the evolving luminosity function.

  3. Compute the model local luminosity function, source counts, spectral index distributions, etc. and compare them with the data.

  4. Revise the luminosity function.

  5. Repeat steps (3) and (4) until satisfactory agreement is reached.

Differences between the models produced by different authors reflect their different data sets, assumptions about the type of evolution occurring, computational approximations, and methods for deciding that a model is satisfactory. Steps (2) and (4) are not straightforward, although simplified models (Section 15.9) can make the relations between the input luminosity function parameters and the output observables clearer.

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