matched- lter method

Abstract. We describe an objective and automated method for detecting clusters of galaxies from optical imaging data. This method is a variant of the so-called \matched- lter " technique pioneered by Postman et al. (1996). Simultaneously using positions and apparent mag-nitudes of galaxies, this method can, not only nd cluster candidates, but also estimate their redshifts and richnesses as byproducts of detection. We examine errors in the es-timation of cluster’s position, redshift, and richness with a number of Monte Carlo simulations. No systematic dis-crepancies between the true and estimated values are seen for either redshift or richness. For clusters with z = 0:2 and with richness similar to that of the Coma cluster, typ-ical errors in the estimation of position, redshift, and rich-ness are evaluated as 1000 (one third of the projected core radius), z 0.02, and N=N 12%, respectively. Spurious detection rate of the method is about less than 10 % of those of conventional ones which use only surface density of galaxies. A cluster survey in the North Galactic Pole region is executed to verify the performance charac-teristics of the method with real data. Despite poor quality of the data, two known real clusters are successfully de-tected. No unknown cluster with low or medium redshift (z 0.3) is detected. We expect these methods based on \matched- lter " technique to be essential tools for compil-ing large and homogeneous optically-selected cluster cat-alogs