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Precision-era optical cluster cosmology calls for a precise definition of thered sequence (RS), consistent across redshift. To this end, we present the RedDragon algorithm: an error-corrected multivariate Gaussian mixture model (GMM).Simultaneous use of multiple colors and smooth evolution of GMM parametersresult in a continuous RS and blue cloud (BC) characterization across redshift,avoiding the discontinuities of red fraction inherent in swapping RS selectioncolors. Based on a mid-redshift spectroscopic sample of SDSS galaxies, a RSdefined by Red Dragon selects quenched galaxies (low specific star formationrate) with a balanced accuracy of over 90%. This approach to galaxy populationassignment gives more natural separations between RS and BC galaxies than hardcuts in color--magnitude or color--color spaces. The Red Dragon algorithm ispublicly available at bitbucket.org/wkblack/red-dragon-gamma.

Red Dragon: A Redshift-Evolving Gaussian Mixture Model for Galaxies