Galaxy and Mass Assembly (GAMA): Colour and luminosity dependent clustering from calibrated photometric redshifts
L. Christodoulou, C. Eminian, J. Loveday, P. Norberg, I. K. Baldry, P., D. Hurley, S. P. Driver, S. P. Bamford, A. M. Hopkins, J. Liske, J. A., Peacock, J. Bland-Hawthorn, S. Brough, E. Cameron, C. J. Conselice, S. M., Croom, C. S. Frenk, M. Gunawardhana, D. H. Jones

TL;DR
This study measures galaxy clustering dependence on colour and luminosity using photometric redshifts from SDSS, revealing stronger clustering for red, faint galaxies and confirming bias evolution consistent with passive evolution models.
Contribution
It introduces a method to analyze galaxy clustering dependence on colour and luminosity using calibrated photometric redshifts from SDSS data.
Findings
Red galaxies are more strongly clustered at small scales.
Clustering strength is nearly independent of luminosity for blue galaxies.
Bias evolution aligns with passive evolution models.
Abstract
We measure the two-point angular correlation function of a sample of 4,289,223 galaxies with r < 19.4 mag from the Sloan Digital Sky Survey as a function of photometric redshift, absolute magnitude and colour down to M_r - 5log h = -14 mag. Photometric redshifts are estimated from ugriz model magnitudes and two Petrosian radii using the artificial neural network package ANNz, taking advantage of the Galaxy and Mass Assembly (GAMA) spectroscopic sample as our training set. The photometric redshifts are then used to determine absolute magnitudes and colours. For all our samples, we estimate the underlying redshift and absolute magnitude distributions using Monte-Carlo resampling. These redshift distributions are used in Limber's equation to obtain spatial correlation function parameters from power law fits to the angular correlation function. We confirm an increase in clustering strength…
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