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Title: Instrumental Response Model and Detrending for the Dark Energy Camera

Abstract

We describe the model for mapping from sky brightness to the digital output of the Dark Energy Camera (DECam) and the algorithms adopted by the Dark Energy Survey (DES) for inverting this model to obtain photometric measures of celestial objects from the raw camera output. This calibration aims for fluxes that are uniform across the camera field of view and across the full angular and temporal span of the DES observations, approaching the accuracy limits set by shot noise for the full dynamic range of DES observations. The DES pipeline incorporates several substantive advances over standard detrending techniques, including principal-components-based sky and fringe subtraction; correction of the "brighter-fatter" nonlinearity; use of internal consistency in on-sky observations to disentangle the influences of quantum efficiency, pixel-size variations, and scattered light in the dome flats; and pixel-by-pixel characterization of instrument spectral response, through combination of internal-consistency constraints with auxiliary calibration data. This article provides conceptual derivations of the detrending/calibration steps, and the procedures for obtaining the necessary calibration data. Other publications will describe the implementation of these concepts for the DES operational pipeline, the detailed methods, and the validation that the techniques can bring DECam photometry and astrometry within $$\approx 2$$ mmag and $$\approx 3$$ mas, respectively, of fundamental atmospheric and statistical limits. In conclusion, the DES techniques should be broadly applicable to wide-field imagers.

Authors:
 [1];  [2];  [3];  [4];  [5];  [6];  [7];  [5];  [6];  [7];  [8];  [2];  [7];  [7]
  1. Univ. of Pennsylvania, Philadelphia, PA (United States)
  2. National Optical Astronomy Observatory, La Serena (Chile)
  3. IIT Hyderabad, Telangana (India)
  4. Stanford Univ., Stanford, CA (United States); SLAC National Accelerator Lab., Menlo Park, CA (United States)
  5. Univ. of Illinois, Urbana, IL (United States); National Center for Supercomputing Applications, Urbana, IL (United States)
  6. National Center for Supercomputing Applications, Urbana, IL (United States)
  7. Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
  8. Excellence Cluster Universe, Garching (Germany); Ludwig-Maximilians Univ. Munchen, Munchen (Germany)
Publication Date:
Research Org.:
SLAC National Accelerator Lab., Menlo Park, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1410603
Grant/Contract Number:
AC02-76SF00515; AST-1615555; SC0007901
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Publications of the Astronomical Society of the Pacific
Additional Journal Information:
Journal Volume: 129; Journal Issue: 981; Journal ID: ISSN 0004-6280
Publisher:
Astronomical Society of the Pacific
Country of Publication:
United States
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS; methods: data analysis; techniques: photometric

Citation Formats

Bernstein, G. M., Abbott, T. M. C., Desai, S., Gruen, D., Gruendl, R. A., Johnson, M. D., Lin, H., Menanteau, F., Morganson, E., Neilsen, E., Paech, K., Walker, A. R., Wester, W., and Yanny, B.. Instrumental Response Model and Detrending for the Dark Energy Camera. United States: N. p., 2017. Web. doi:10.1088/1538-3873/aa858e.
Bernstein, G. M., Abbott, T. M. C., Desai, S., Gruen, D., Gruendl, R. A., Johnson, M. D., Lin, H., Menanteau, F., Morganson, E., Neilsen, E., Paech, K., Walker, A. R., Wester, W., & Yanny, B.. Instrumental Response Model and Detrending for the Dark Energy Camera. United States. doi:10.1088/1538-3873/aa858e.
Bernstein, G. M., Abbott, T. M. C., Desai, S., Gruen, D., Gruendl, R. A., Johnson, M. D., Lin, H., Menanteau, F., Morganson, E., Neilsen, E., Paech, K., Walker, A. R., Wester, W., and Yanny, B.. 2017. "Instrumental Response Model and Detrending for the Dark Energy Camera". United States. doi:10.1088/1538-3873/aa858e.
@article{osti_1410603,
title = {Instrumental Response Model and Detrending for the Dark Energy Camera},
author = {Bernstein, G. M. and Abbott, T. M. C. and Desai, S. and Gruen, D. and Gruendl, R. A. and Johnson, M. D. and Lin, H. and Menanteau, F. and Morganson, E. and Neilsen, E. and Paech, K. and Walker, A. R. and Wester, W. and Yanny, B.},
abstractNote = {We describe the model for mapping from sky brightness to the digital output of the Dark Energy Camera (DECam) and the algorithms adopted by the Dark Energy Survey (DES) for inverting this model to obtain photometric measures of celestial objects from the raw camera output. This calibration aims for fluxes that are uniform across the camera field of view and across the full angular and temporal span of the DES observations, approaching the accuracy limits set by shot noise for the full dynamic range of DES observations. The DES pipeline incorporates several substantive advances over standard detrending techniques, including principal-components-based sky and fringe subtraction; correction of the "brighter-fatter" nonlinearity; use of internal consistency in on-sky observations to disentangle the influences of quantum efficiency, pixel-size variations, and scattered light in the dome flats; and pixel-by-pixel characterization of instrument spectral response, through combination of internal-consistency constraints with auxiliary calibration data. This article provides conceptual derivations of the detrending/calibration steps, and the procedures for obtaining the necessary calibration data. Other publications will describe the implementation of these concepts for the DES operational pipeline, the detailed methods, and the validation that the techniques can bring DECam photometry and astrometry within $\approx 2$ mmag and $\approx 3$ mas, respectively, of fundamental atmospheric and statistical limits. In conclusion, the DES techniques should be broadly applicable to wide-field imagers.},
doi = {10.1088/1538-3873/aa858e},
journal = {Publications of the Astronomical Society of the Pacific},
number = 981,
volume = 129,
place = {United States},
year = 2017,
month = 9
}

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