Galaxy And Mass Assembly (GAMA): $\mathbf{z \sim 0}$ Galaxy Luminosity Function down to $\mathbf{L \sim 10^{6}~L_\odot}$ via Clustering Based Redshift Inference
Geray S. Karademir, Edward N. Taylor, Chris Blake, Ivan K. Baldry,, Sabine Bellstedt, Maciej Bilicki, Michael J. I. Brown, Michelle E. Cluver,, Simon P. Driver, Hendrik Hildebrandt, Benne W. Holwerda, Andrew M. Hopkins,, Jonathan Loveday, Steven Phillipps, Angus H. Wright

TL;DR
This paper introduces a clustering-based redshift inference method to measure the galaxy luminosity function at redshift zero across a vast luminosity range, revealing a steepening at low luminosities likely due to globular clusters.
Contribution
It presents a novel application of clustering-based redshift inference to extend the galaxy luminosity function measurement to very faint sources down to globular cluster luminosities.
Findings
GLF has a constant slope of about -1.2 for intermediate luminosities.
The GLF steepens sharply at very low luminosities.
Globular clusters dominate the source counts at the faint end.
Abstract
In this study we present a new experimental design using clustering-based redshift inference to measure the evolving galaxy luminosity function (GLF) spanning 5.5 decades from to . We use data from the Galaxy And Mass Assembly (GAMA) survey and the Kilo-Degree Survey (KiDS). We derive redshift distributions in bins of apparent magnitude to the limits of the GAMA-KiDS photometric catalogue: ; more than a decade in luminosity beyond the limits of the GAMA spectroscopic redshift sample via clustering-based redshift inference. This technique uses spatial cross-correlation statistics for a reference set with known redshifts (in our case, the main GAMA sample) to derive the redshift distribution for the target ensemble. For the calibration of the redshift distribution we use a simple parametrisation with an adaptive normalisation…
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