  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 wavelength
range 5500-6500 AA. The discrepancy increases with decreasing effective
temperature independently of gravity. This result has general implications for
a variety of studies from globular clusters to high-redshift galaxies. The
astrophysical part of our solution regards the composition of the stellar
populations of these massive Luminous Red Galaxies. We find that on top of the
previous effect one needs to consider a model in which ~3% of the stellar mass
is in old metal-poor stars. Other solutions such as substantial blue Horizontal
Branch at high metallicity or young stellar populations can be ruled out by the
data. Our new model provides a better fit to the g-r and r-i colors of LRGs and
gives new insight into the formation histories of these most massive galaxies.
Our model will also improve the k- and evolutionary corrections for LRGs which
are critical for fully exploiting present and future galaxy surveys.
