论文标题
红龙：星系中的红移变化高斯混合物模型
Red Dragon: A Redshift-Evolving Gaussian Mixture Model for Galaxies
论文作者
论文摘要
精确时代的光聚类宇宙学要求对红色序列（RS）进行精确定义，并在红移之间保持一致。为此，我们介绍了红色龙算法：错误校正的多元高斯混合模型（GMM）。同时使用多种颜色和GMM参数的平稳演变导致红移的连续RS和蓝色云（BC）表征，从而避免了交换RS选择颜色固有的红分的不连续性。基于SDSS星系中的红移中部光谱样品，由Red Dragon定义的RS选择了淬火星系（低特异性恒星形成速率），其均衡精度超过90％。这种用于星系人口分配的方法比颜色或颜色 - 色的空间中的硬切割相比，RS和BC星系之间的自然分离更多。 Red Dragon算法可在bitbucket.org/wkblack/red-dragon-gamma上公开获得。
Precision-era optical cluster cosmology calls for a precise definition of the red sequence (RS), consistent across redshift. To this end, we present the Red Dragon algorithm: an error-corrected multivariate Gaussian mixture model (GMM). Simultaneous use of multiple colors and smooth evolution of GMM parameters result in a continuous RS and blue cloud (BC) characterization across redshift, avoiding the discontinuities of red fraction inherent in swapping RS selection colors. Based on a mid-redshift spectroscopic sample of SDSS galaxies, a RS defined by Red Dragon selects quenched galaxies (low specific star formation rate) with a balanced accuracy of over 90%. This approach to galaxy population assignment gives more natural separations between RS and BC galaxies than hard cuts in color--magnitude or color--color spaces. The Red Dragon algorithm is publicly available at bitbucket.org/wkblack/red-dragon-gamma.
