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We present a calibration of the fundamental plane using SDSS Data Release 8. We analysed about 93000 elliptical galaxies up to $z<0.2$, the largest sample used for the calibration of the fundamental plane so far. We incorporated up-to-date K-corrections and used GalaxyZoo data to classify the galaxies in our sample. We derived independent fundamental plane fits in all five Sloan filters u, g, r, i and z. A direct fit using a volume-weighted least-squares method was applied to obtain the coefficients of the fundamental plane, which implicitly corrects for the Malmquist bias. We achieved an accuracy of 15% for the fundamental plane as a distance indicator. We provide a detailed discussion on the calibrations and their influence on the resulting fits. These re-calibrated fundamental plane relations form a well-suited anchor for large-scale peculiar-velocity studies in the nearby universe. In addition to the fundamental plane, we discuss the redshift distribution of the elliptical galaxies and their global parameters.
We describe redMaPPer, a new red-sequence cluster finder specifically designed to make optimal use of ongoing and near-future large photometric surveys. The algorithm has multiple attractive features: (1) It can iteratively self-train the red-sequenc
We present redshift probability distributions for galaxies in the SDSS DR8 imaging data. We used the nearest-neighbor weighting algorithm presented in Lima et al. 2008 and Cunha et al. 2009 to derive the ensemble redshift distribution N(z), and indiv
We study the relations between the multimodality of galaxy clusters drawn from the SDSS DR8 and the environment where they reside. As cluster environment we consider the global luminosity density field, supercluster membership, and supercluster morph
In order to place constraints on cosmology through optical surveys of galaxy clusters, one must first understand the properties of those clusters. To this end, we introduce the Mass Analysis Tool for Chandra (MATCha), a pipeline which uses a parallel