Modelling the colour evolution of luminous red galaxies - improvements with empirical stellar spectra

Maraston, Claudia; Strömbäck, G.; Thomas, D.; Wake, D. A. and Nichol, R. C. (2009). Modelling the colour evolution of luminous red galaxies - improvements with empirical stellar spectra. Monthly Notices of the Royal Astronomical Society: Letters, 394(1) L107-L111.



Predicting the colours of luminous red galaxies (LRGs) in the Sloan Digital Sky Survey has been a long-standing problem. The g, r, i colours of LRGs are inconsistent with stellar population models over the redshift range 0.1 < z < 0.7. We provide a solution to this problem, through a combination of new astrophysics and a fundamental change to the stellar population modelling. We find that the use of the empirical library of Pickles, in place of theoretical libraries based on model atmosphere calculations, modifies the evolutionary population synthesis predicted colours exactly in the way suggested by the data. The reason is a lower (normalized) flux in the empirical libraries, with respect to the theoretical ones, in the wavelength range 5500–6500 Å. The effect increases with decreasing effective temperature roughly independently of gravity. We also find that other recent libraries such as MILES and STELIB behave the same way. We further verified that [α/Fe ] effects on stellar spectra cannot substitute the effect of the empirical library because they make both colours bluer. The astrophysical part of our solution regards the composition of the stellar populations of these massive LRGs. We find that on top of the previous effect one needs to consider a model in which ∼3 per cent of the stellar mass is in old metal-poor stars. Other solutions such as an overall slightly subsolar metallicity or young stellar populations can be ruled out by the data. The percentage of the metal-poor subpopulation may be affected by the consideration of abundance-ratio effects though in the framework of present calculations the metal-poor option is favoured. Our new model provides a better fit to the colours of LRGs and gives new insight into the formation histories of these most massive galaxies. The new model will also improve the k- and evolutionary corrections for LRGs which are critical for fully exploiting present and future galaxy surveys.

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