Avoiding spurious breaks in binned luminosity functions
Mihai Cara, Matthew L. Lister

TL;DR
The paper identifies and addresses biases in constructing binned luminosity functions of AGN, proposing a flux--redshift binning method to avoid artificial breaks and improve the accuracy of LF modeling.
Contribution
It introduces a flux--redshift binning approach to prevent spurious features in AGN luminosity functions, enhancing the reliability of LF analysis.
Findings
Flux--redshift binning avoids artificial breaks in LFs.
Applying the method to MOJAVE AGN sample removes spurious features.
The approach improves the accuracy of LF parameter estimation.
Abstract
We show that using either the method of Page & Carrera or the well-known method to construct the binned luminosity function (LF) of a flux limited sample of Active Galactic Nuclei (AGN) can produce an artificial flattening (or steepening in the case of negative evolution) of the binned LF for bins intersected by the flux cutoff of the sample. This effect is more pronounced for samples with steep and strongly evolving parent LFs but is still present even for non-evolving LFs. As a result of this distortion of the true LF, fitting a model LF to binned data may lead to errors in the estimation of the parameters and may even prompt the erroneous use of broken power law functions. We compute the expected positions of apparent breaks in the binned LF. We show that these spurious breaks in the binned LFs can be avoided if the binning is done in the flux--redshift plane instead of the…
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