Modeling Large Populations: Steep Luminosity Functions and Redshift Distribution Artifacts

Mathematics – Logic

Scientific paper

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Scientific paper

The luminosity function (LF) of distant objects and its redshift dependence are important quantities in understanding the physics of the population studied and its cosmological evolution. We show that popular forms of cosmological evolution (power law and exponential dependence) used to model the redshift dependence of the observed luminosity functions can lead to unrealistic low redshift spikes in the model redshift distributions in the case ofsteep (power law index < -2) luminosity functions. We show that the unrealistic spike can be removed i) by choosing a high luminosity cutoff of the luminosity function; ii) by having a LF which becomes shallower at lower luminosities, or iii) by choosing special forms of evolution models. However, the first solution leads to very low predicted space densities and may also lead to incomplete sampling of the parent population. In addition, the observed redshift distribution may not be fitted well by the model even when the Kolmogorov-Smirnov test accepts the model. Some authors use binned model redshift distributions when comparing with observed data, but binning the model can mask these artifacts. We favor the solution in which the LF becomes shallower at lower luminosities but for samples in which the break in the LF cannot be detected, using special forms of the evolution function may be a viable option. We suggest that it is important to always compare the model and observed redshift distributions even when the other distributions seem to be in agreement.

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