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The Dark Energy Survey Image Processing Pipeline
by
Diehl, H. T.
, Buckley-Geer, E.
, Sako, M.
, Paz-Chinchón, F.
, Wester, W.
, Gower, M.
, Allam, S.
, Covarrubias, R.
, Johnson, M. D.
, Petravick, D.
, Menanteau, F.
, Yanny, B.
, Bertin, E.
, Sheldon, E.
, Gruendl, R. A.
, Morganson, E.
, Paech, K.
, Barkhouse, W.
, Daues, G.
, Desai, S.
, Chen, Y.-C.
, Kind, M. Carrasco
, Johnson, M. W. G.
, Bernstein, G. M.
, Li, T. S.
, Benoit-Lévy, A.
, Marriner, J.
, Lin, H.
, Bechtol, K.
, Gruen, D.
, Pond, C.
, Drlica-Wagner, A.
, Mohr, J. J.
, Sobreira, F.
, Armstrong, R.
, Ngeow, C.-C.
, Goldstein, D. A.
, Sevilla-Noarbe, I.
, Tucker, D. L.
, Friedel, D. N.
, Rykoff, E. S.
, Kessler, R.
, Neilsen, E.
in
cosmology: observations
/ Dark energy
/ Data reduction
/ Instrumentation and Detectors
/ Physics
/ Pipelines
/ Polls & surveys
/ surveys
/ techniques: image processing
/ techniques: photometric
2018
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The Dark Energy Survey Image Processing Pipeline
by
Diehl, H. T.
, Buckley-Geer, E.
, Sako, M.
, Paz-Chinchón, F.
, Wester, W.
, Gower, M.
, Allam, S.
, Covarrubias, R.
, Johnson, M. D.
, Petravick, D.
, Menanteau, F.
, Yanny, B.
, Bertin, E.
, Sheldon, E.
, Gruendl, R. A.
, Morganson, E.
, Paech, K.
, Barkhouse, W.
, Daues, G.
, Desai, S.
, Chen, Y.-C.
, Kind, M. Carrasco
, Johnson, M. W. G.
, Bernstein, G. M.
, Li, T. S.
, Benoit-Lévy, A.
, Marriner, J.
, Lin, H.
, Bechtol, K.
, Gruen, D.
, Pond, C.
, Drlica-Wagner, A.
, Mohr, J. J.
, Sobreira, F.
, Armstrong, R.
, Ngeow, C.-C.
, Goldstein, D. A.
, Sevilla-Noarbe, I.
, Tucker, D. L.
, Friedel, D. N.
, Rykoff, E. S.
, Kessler, R.
, Neilsen, E.
in
cosmology: observations
/ Dark energy
/ Data reduction
/ Instrumentation and Detectors
/ Physics
/ Pipelines
/ Polls & surveys
/ surveys
/ techniques: image processing
/ techniques: photometric
2018
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The Dark Energy Survey Image Processing Pipeline
by
Diehl, H. T.
, Buckley-Geer, E.
, Sako, M.
, Paz-Chinchón, F.
, Wester, W.
, Gower, M.
, Allam, S.
, Covarrubias, R.
, Johnson, M. D.
, Petravick, D.
, Menanteau, F.
, Yanny, B.
, Bertin, E.
, Sheldon, E.
, Gruendl, R. A.
, Morganson, E.
, Paech, K.
, Barkhouse, W.
, Daues, G.
, Desai, S.
, Chen, Y.-C.
, Kind, M. Carrasco
, Johnson, M. W. G.
, Bernstein, G. M.
, Li, T. S.
, Benoit-Lévy, A.
, Marriner, J.
, Lin, H.
, Bechtol, K.
, Gruen, D.
, Pond, C.
, Drlica-Wagner, A.
, Mohr, J. J.
, Sobreira, F.
, Armstrong, R.
, Ngeow, C.-C.
, Goldstein, D. A.
, Sevilla-Noarbe, I.
, Tucker, D. L.
, Friedel, D. N.
, Rykoff, E. S.
, Kessler, R.
, Neilsen, E.
in
cosmology: observations
/ Dark energy
/ Data reduction
/ Instrumentation and Detectors
/ Physics
/ Pipelines
/ Polls & surveys
/ surveys
/ techniques: image processing
/ techniques: photometric
2018
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Journal Article
The Dark Energy Survey Image Processing Pipeline
2018
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Overview
The Dark Energy Survey (DES) is a five-year optical imaging campaign with the goal of understanding the origin of cosmic acceleration. DES performs a ∼5000 deg2 survey of the southern sky in five optical bands (g, r, i, z, Y) to a depth of ∼24th magnitude. Contemporaneously, DES performs a deep, time-domain survey in four optical bands (g, r, i, z) over ∼27 deg2. DES exposures are processed nightly with an evolving data reduction pipeline and evaluated for image quality to determine if they need to be retaken. Difference imaging and transient source detection are also performed in the time domain component nightly. On a bi-annual basis, DES exposures are reprocessed with a refined pipeline and coadded to maximize imaging depth. Here we describe the DES image processing pipeline in support of DES science, as a reference for users of archival DES data, and as a guide for future astronomical surveys.
Publisher
The Astronomical Society of the Pacific,IOP Publishing,Astronomical Society of the Pacific
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