An Objective and Automatic Cluster Finder

We describe an objective and automated technique for detecting clusters of galaxies. This technique is based on the matched-filter technique, using position and apparent magnitude of galaxies simultaneously. Redshift and richness of clusters are estimated as byproducts of detection. We examine accuracies in the estimation of cluster position, redshift, and richness by Monte-Carlo simulations. For clusters at $z$=0.2 with richness similar to that of Coma cluster, typical errors in estimating position, redshift, and richness are $\Delta\theta\sim 15''$ (a half of the projected core radius), $\Delta z\sim$0.04, and $\Delta N/N\sim$30%, respectively. Spurious detection rate of this technique is much less than that of previous techniques which use galaxy positions only. A cluster survey in the North Galactic Pole (NGP) region is performed to verify the performance characteristics of the method with real data. Despite poor quality of the data, two known real clusters are successfully detected. No unknown cluster with low or medium redshift ($z\leq$0.3) is detected. We expect this method to be an essential technique for compiling large and homogeneous optically-selected cluster catalogs.