An improved photometric calibration of the sloan digital sky survey imaging data

Nikhil Padmanabhan, David J. Schlegel, Douglas P. Finkbeiner, J. C. Barentine, Michael R. Blanton, Howard J. Brewington, James E. Gunn, Michael Harvanek, David W. Hogg, Željko Ivezić, David Johnston, Stephen M. Kent, S. J. Kleinman, Gillian R. Knapp, Jurek Krzesinski, Dan Long, Eric H. Neilsen, Atsuko Nitta, Craig Loomis, Robert H. LuptonSam Roweis, Stephanie A. Snedden, Michael A. Strauss, Douglas L. Tucker

Research output: Contribution to journalArticlepeer-review

440 Scopus citations

Abstract

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 Sim;1% relative calibration errors across 8500 deg2 in griz; the errors are ∼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.

Original languageEnglish (US)
Pages (from-to)1217-1233
Number of pages17
JournalAstrophysical Journal
Volume674
Issue number2
DOIs
StatePublished - Feb 20 2008

All Science Journal Classification (ASJC) codes

  • Astronomy and Astrophysics
  • Space and Planetary Science

Keywords

  • Techniques: photometric

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