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This content will become publicly available on October 26, 2016

Title: Crowded Cluster Cores. Algorithms for Deblending in Dark Energy Survey Images

Deep optical images are often crowded with overlapping objects. We found that this is especially true in the cores of galaxy clusters, where images of dozens of galaxies may lie atop one another. Accurate measurements of cluster properties require deblending algorithms designed to automatically extract a list of individual objects and decide what fraction of the light in each pixel comes from each object. In this article, we introduce a new software tool called the Gradient And Interpolation based (GAIN) deblender. GAIN is used as a secondary deblender to improve the separation of overlapping objects in galaxy cluster cores in Dark Energy Survey images. It uses image intensity gradients and an interpolation technique originally developed to correct flawed digital images. Our paper is dedicated to describing the algorithm of the GAIN deblender and its applications, but we additionally include modest tests of the software based on real Dark Energy Survey co-add images. GAIN helps to extract an unbiased photometry measurement for blended sources and improve detection completeness, while introducing few spurious detections. When applied to processed Dark Energy Survey data, GAIN serves as a useful quick fix when a high level of deblending is desired.
 [1] ;  [1] ;  [2] ;  [3] ;  [1] ;  [4] ;  [5]
  1. Univ. of Michigan, Ann Arbor, MI (United States)
  2. Pierre and Marie Curie Univ., Paris (France)
  3. Univ. of California, Santa Cruz, CA (United States)
  4. SLAC National Accelerator Lab., Menlo Park, CA (United States)
  5. Univ. of Michigan, Ann Arbor, MI (United States); Korea Astronomy and Space Science Inst., Daejeon (Korea)
Publication Date:
OSTI Identifier:
Report Number(s):
Journal ID: ISSN 0004-6280; arXiv eprint number arXiv:1409.2885
Grant/Contract Number:
Accepted Manuscript
Journal Name:
Publications of the Astronomical Society of the Pacific
Additional Journal Information:
Journal Volume: 127; Journal Issue: 957; Journal ID: ISSN 0004-6280
Astronomical Society of the Pacific
Research Org:
Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States)
Sponsoring Org:
USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25)
Country of Publication:
United States