Distant Cluster Search: Welcoming some Newcomers from the EIS
Abstract
We present a new automated cluster search algorithm, stressing its advantages relatively to others available in the literature. Applying it to the photometric data of the ESO Imaging Survey (EIS, Renzini & da Costa 1997) allowed us to produce, with a high degree of confidence, a new catalogue of cluster candidates up to z approximately equal to 1.1.
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