Modeling the color evolution of luminous red galaxies - improvements with empirical stellar spectra
Claudia Maraston, Gustav Stromback, Daniel Thomas, David A. Wake,, Robert C. Nichol (University of Portsmouth, University of Durham)

TL;DR
This paper improves the modeling of luminous red galaxy colors by incorporating empirical stellar spectra and considering a small fraction of old metal-poor stars, leading to better agreement with SDSS data.
Contribution
It introduces a novel approach using empirical stellar spectra and a refined stellar population model to accurately predict LRG colors across redshifts.
Findings
Empirical stellar spectra reduce color discrepancies in models.
Adding ~3% old metal-poor stars improves color fits.
Enhanced models better match SDSS LRG observations.
Abstract
Predicting the colors of Luminous Red Galaxies (LRGs) in the Sloan Digital Sky Survey (SDSS) has been a long-standing problem. The g,r,i colors of LRGs are inconsistent with stellar population models over the redshift range 0.1<z<0.7. The g-r colors in the models are on average redder than the data while the r-i colors in the models are bluer towards low redshift. Beyond redshift 0.4, the predicted r-i color becomes instead too red, while the predicted g-r agrees with the data. We provide a solution to this problem, through a combination of new astrophysics and a fundamental change to the stellar population modeling. We find that the use of the empirical library of Pickles (1998) instead of theoretical spectra modifies the predicted colors exactly in the way suggested by the data. The reason is a lower flux in the empirical libraries, with respect to the theoretical ones, in the…
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