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Title: No Galaxy Left Behind: Accurate Measurements with the Faintest Objects in the Dark Energy Survey

Abstract

Accurate statistical measurement with large imaging surveys has traditionally required throwing away a sizable fraction of the data. This is because most measurements have relied on selecting nearly complete samples, where variations in the composition of the galaxy population with seeing, depth, or other survey characteristics are small. Here, we introduce a new measurement method that aims to minimize this wastage, allowing precision measurement for any class of detectable stars or galaxies. Moreover, our proposal was implemented in BALROG, software which embeds fake objects in real imaging to accurately characterize measurement biases. We demonstrate this technique with an angular clustering measurement using Dark Energy Survey (DES) data. We first show that recovery of our injected galaxies depends on a variety of survey characteristics in the same way as the real data. We then construct a flux-limited sample of the faintest galaxies in DES, chosen specifically for their sensitivity to depth and seeing variations. Using the synthetic galaxies as randoms in the Landy–Szalay estimator suppresses the effects of variable survey selection by at least two orders of magnitude. With this correction, our measured angular clustering is found to be in excellent agreement with that of a matched sample from much deeper,more » higher resolution space-based Cosmological Evolution Survey (COSMOS) imaging; over angular scales of 0.°004 < θ < 0.°2, we find a best-fitting scaling amplitude between the DES and COSMOS measurements of 1.00 ± 0.09. We expect this methodology to be broadly useful for extending measurements’ statistical reach in a variety of upcoming imaging surveys.« less

Authors:
 [1]
  1. The Ohio State Univ., Columbus, OH (United States). et al.
Publication Date:
Research Org.:
Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States); Brookhaven National Laboratory (BNL), Upton, NY (United States)
Sponsoring Org.:
USDOE Office of Science (SC), High Energy Physics (HEP)
Contributing Org.:
DES Collaboration
OSTI Identifier:
1221330
Alternate Identifier(s):
OSTI ID: 1254809
Report Number(s):
FERMILAB-PUB-15-307-AE; BNL-112200-2016-JA
Journal ID: ISSN 0035-8711; arXiv eprint number arXiv:1507.08336
Grant/Contract Number:  
AC02-07CH11359; SC00112704
Resource Type:
Accepted Manuscript
Journal Name:
Monthly Notices of the Royal Astronomical Society
Additional Journal Information:
Journal Volume: 457; Journal ID: ISSN 0035-8711
Publisher:
Royal Astronomical Society
Country of Publication:
United States
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS

Citation Formats

Suchyta, E. No Galaxy Left Behind: Accurate Measurements with the Faintest Objects in the Dark Energy Survey. United States: N. p., 2016. Web. doi:10.1093/mnras/stv2953.
Suchyta, E. No Galaxy Left Behind: Accurate Measurements with the Faintest Objects in the Dark Energy Survey. United States. https://doi.org/10.1093/mnras/stv2953
Suchyta, E. Wed . "No Galaxy Left Behind: Accurate Measurements with the Faintest Objects in the Dark Energy Survey". United States. https://doi.org/10.1093/mnras/stv2953. https://www.osti.gov/servlets/purl/1221330.
@article{osti_1221330,
title = {No Galaxy Left Behind: Accurate Measurements with the Faintest Objects in the Dark Energy Survey},
author = {Suchyta, E.},
abstractNote = {Accurate statistical measurement with large imaging surveys has traditionally required throwing away a sizable fraction of the data. This is because most measurements have relied on selecting nearly complete samples, where variations in the composition of the galaxy population with seeing, depth, or other survey characteristics are small. Here, we introduce a new measurement method that aims to minimize this wastage, allowing precision measurement for any class of detectable stars or galaxies. Moreover, our proposal was implemented in BALROG, software which embeds fake objects in real imaging to accurately characterize measurement biases. We demonstrate this technique with an angular clustering measurement using Dark Energy Survey (DES) data. We first show that recovery of our injected galaxies depends on a variety of survey characteristics in the same way as the real data. We then construct a flux-limited sample of the faintest galaxies in DES, chosen specifically for their sensitivity to depth and seeing variations. Using the synthetic galaxies as randoms in the Landy–Szalay estimator suppresses the effects of variable survey selection by at least two orders of magnitude. With this correction, our measured angular clustering is found to be in excellent agreement with that of a matched sample from much deeper, higher resolution space-based Cosmological Evolution Survey (COSMOS) imaging; over angular scales of 0.°004 < θ < 0.°2, we find a best-fitting scaling amplitude between the DES and COSMOS measurements of 1.00 ± 0.09. We expect this methodology to be broadly useful for extending measurements’ statistical reach in a variety of upcoming imaging surveys.},
doi = {10.1093/mnras/stv2953},
journal = {Monthly Notices of the Royal Astronomical Society},
number = ,
volume = 457,
place = {United States},
year = {Wed Jan 27 00:00:00 EST 2016},
month = {Wed Jan 27 00:00:00 EST 2016}
}

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