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Not only source catalogs are extracted from astronomy observations. Their skycoverage is always carefully recorded and used in statistical analyses, such ascorrelation and luminosity function studies. Here we present a novel method forcatalog matching, which inherently builds on the coverage information forbetter performance and completeness. A modified version of the Zones Algorithmis introduced for matching partially overlapping observations, where irrelevantparts of the data are excluded up front for efficiency. Our design enablessearches to focus on specific areas on the sky to further speed up the process.Another important advantage of the new method over traditional techniques isits ability to quickly detect dropouts, i.e., the missing components that arein the observed regions of the celestial sphere but did not reach the detectionlimit in some observations. These often provide invaluable insight into thespectral energy distribution of the matched sources but rarely available intraditional associations.

Efficient Catalog Matching with Dropout Detection