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dc.date.accessioned2022-03-17T01:56:47Z
dc.date.available2022-03-17T01:56:47Z
dc.date.issued2022
dc.identifier.citationEverett, S., Yanny, B., Kuropatkin, N., Huff, E. M., Zhang, Y., Myles, J., Masegian, A., Elvin-Poole, J., Allam, S., Bernstein, G. M., Sevilla-Noarbe, I., Splettstoesser, M., Sheldon, E., Jarvis, M., Amon, A., Harrison, I., Choi, A., Hartley, W. G., Alarcon, A., … Wilkinson, R. D. (2022). Dark Energy Survey Year 3 Results: Measuring the Survey Transfer Function with Balrog. Astrophysical Journal, Supplement Series.
dc.identifier.issn0067-0049
dc.identifier.doi10.3847/1538-4365/ac26c1
dc.identifier.urihttp://hdl.handle.net/10150/663557
dc.description.abstractWe describe an updated calibration and diagnostic framework, Balrog, used to directly sample the selection and photometric biases of the Dark Energy Survey (DES) Year 3 (Y3) data set. We systematically inject onto the single-epoch images of a random 20% subset of the DES footprint an ensemble of nearly 30 million realistic galaxy models derived from DES Deep Field observations. These augmented images are analyzed in parallel with the original data to automatically inherit measurement systematics that are often too difficult to capture with generative models. The resulting object catalog is a Monte Carlo sampling of the DES transfer function and is used as a powerful diagnostic and calibration tool for a variety of DES Y3 science, particularly for the calibration of the photometric redshifts of distant "source"galaxies and magnification biases of nearer "lens"galaxies. The recovered Balrog injections are shown to closely match the photometric property distributions of the Y3 GOLD catalog, particularly in color, and capture the number density fluctuations from observing conditions of the real data within 1% for a typical galaxy sample. We find that Y3 colors are extremely well calibrated, typically within ∼1-8 mmag, but for a small subset of objects, we detect significant magnitude biases correlated with large overestimates of the injected object size due to proximity effects and blending. We discuss approaches to extend the current methodology to capture more aspects of the transfer function and reach full coverage of the survey footprint for future analyses. © 2022. The Author(s). Published by the American Astronomical Society.
dc.language.isoen
dc.publisherAmerican Astronomical Society
dc.rightsCopyright © 2022. The Author(s). Published by the American Astronomical Society. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence.
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleDark Energy Survey Year 3 Results: Measuring the Survey Transfer Function with Balrog
dc.typeArticle
dc.typetext
dc.contributor.departmentDepartment of Astronomy, Steward Observatory, University of Arizona
dc.identifier.journalAstrophysical Journal, Supplement Series
dc.description.noteOpen access article
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
dc.eprint.versionFinal published version
dc.source.journaltitleAstrophysical Journal, Supplement Series
refterms.dateFOA2022-03-17T01:56:47Z


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Copyright © 2022. The Author(s). Published by the American Astronomical Society. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence.
Except where otherwise noted, this item's license is described as Copyright © 2022. The Author(s). Published by the American Astronomical Society. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence.