cluster catalogs (see Bramel et al. 2000; Kochanek et al. 2003), but is critical for all statistical analyzes using the catalog;]{}

3.  [To provide a robust mass estimator. Traditionally, this has been the Achilles’ Heel of optical catalogs, as richness is a poor indicator of mass; and,]{}

4.  [To cover a large dynamic range in both redshift and mass]{}

I review below one SDSS cluster catalog I am involved with, in collaboration with Chris Miller at CMU, that now meets these four challenges and is comparable in quality to the best X–ray catalogs of clusters ([*e.g.*]{}, the REFLEX catalog of B[" o]{}hringer et al. 2001).

The C4 Algorithm
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The underlying hypothesis of the C4 algorithm is that a cluster or group of galaxies is a clustering of galaxies in both color and space. This is demonstrated in Figure \[cm\] and the reader is referred to Gladders & Yee (2000) for a full discuss of all the evidence in support of this hypothesis. Therefore, by searching for clusters simultaneously in both color and space, the C4 algorithm reduces projection effects to almost zero, while still retaining much power for finding clusters (see Figure \[colorcolor\]).

![The color-magnitude relations for a previously 