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Classification and Redshift Estimation in Multi-Color Surveys

Christian Wolf·Klaus Meisenheimer·Hermann-Josef Röser
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Abstract

We present a photometric method for identifying stars, galaxies and quasars in multi-color surveys and estimating multi-color redshifts for the extragalactic objects. We use a library of >65000 color templates for comparison with observed objects. The method was originally developed for the Calar Alto Deep Imaging Survey (CADIS), but is now used in a variety of survey projects. We checked its performance by spectroscopy of CADIS objects, where it provides high reliability (6 mistakes among 151 objects with R<24), especially for the quasar selection, and redshifts accurate within sigma_z = 0.03 for galaxies and sigma_z = 0.1 for quasars. For an optimization of future surveys, a few model surveys are compared, which use the same amount of telescope time but different filter sets. In summary, medium-band surveys perform superior to broad-band surveys although they collect less photons. A full account of this work is already in print.

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Christian Wolf, Klaus Meisenheimer, Hermann-Josef Röser. 2000-11-14. Classification and Redshift Estimation in Multi-Color Surveys. https://doi.org/10.1007/10849171_40

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