An Improved Photometric Calibration Of The Sloan Digital Sky Survey Imaging Data
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We present an algorithm to photometrically calibrate wide-field optical imaging surveys, which simultaneously solves for the calibration parameters and relative stellar fluxes using overlapping observations. The algorithm decouples the problem of "relative'' calibrations from that of "absolute'' calibrations; the absolute calibration is reduced to determining a few numbers for the entire survey. We pay special attention to the spatial structure of the calibration errors, allowing one to isolate particular error modes in downstream analyses. Applying this to the SDSS imaging data, we achieve similar to 1% relative calibration errors across 8500 deg(2) in griz; the errors are similar to 2% for the u band. These errors are dominated by unmodeled atmospheric variations at Apache Point Observatory. These calibrations, dubbed "uber-calibration,'' are now public with SDSS Data Release 6 and will be a part of subsequent SDSS data releases.