No galaxy left behind: Accurate measurements with the faintest objects in the Dark Energy Survey

The DES Collaboration

doi:10.1093/mnras/stv2953

No galaxy left behind: Accurate measurements with the faintest objects in the Dark Energy Survey

The DES Collaboration

Research output: Contribution to journal › Article › peer-review

72 Scopus citations

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. We introduce a new measurement method that aims to minimize this wastage, allowing precision measurement for any class of detectable stars or galaxies. We have implemented our proposal 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 fluxlimited 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.

Original language	English
Pages (from-to)	786-808
Number of pages	23
Journal	Monthly Notices of the Royal Astronomical Society
Volume	457
Issue number	1
DOIs	https://doi.org/10.1093/mnras/stv2953
State	Published - Jan 11 2016
Externally published	Yes

Funding

The authors are grateful to Chris Hirata and John Beacom for many illuminating discussions, and to Todd Tomashek for guidance on integrating the final catalogues into the Dark Energy Survey science data base. We commend the GALSIM developers for their assistance and for exemplifying perhaps the best code documentation throughout the astronomical community. We thank Anže Slosar and the astrophysics group at Brookhaven National Laboratory for use of computing resources throughout this work. We are indebted to the entire DESDM team for the often underappreciated hard work that they do. We owe much gratitude to the late Steve Price for his beyond generous support of CCAPP for many years. ES is supported by an Ohio State University Graduate Presidential Fellowship. EMH is funded by a CCAPP postdoctoral fellowship. JA is partially supported by MINECO under grant FPA2012-39684. PM is supported by the US Department of Energy under Contract No. DE-FG02-91ER40690. We are grateful for the extraordinary contributions of our CTIO colleagues and the DECam Construction, Commissioning and Science Verification teams in achieving the excellent instrument and telescope conditions that have made this work possible. The success of this project also relies critically on the expertise and dedication of the DESDM group. Funding for the DES Projects has been provided by the US Department of Energy, the US National Science Foundation, the Ministry of Science and Education of Spain, the Science and Technology Facilities Council of the United Kingdom, the Higher Education Funding Council for England, the National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign, the Kavli Institute of Cosmological Physics at the University of Chicago, the Center for Cosmology and Astro-Particle Physics at The Ohio State University, the Mitchell Institute for Fundamental Physics and Astronomy at Texas A&M University, Financiadora de Estudos e Projetos, Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, Conselho Nacional de Desenvolvimento Científico e Tecnológico and the Ministério da Ciência, Tecnologia e Inovação, the Deutsche Forschungsgemeinschaft and the Collaborating Institutions in the DES. The DESDM system is supported by the National Science Foundation under Grant Number AST-1138766. The Collaborating Institutions are Argonne National Laboratory, the University of California at Santa Cruz, the University of Cambridge, Centro de Investigaciones Enérgeticas, Medioambientales y Tecnológicas-Madrid, the University of Chicago, University College London, the DES-Brazil Consortium, the University of Edinburgh, the Eidgenössische Technische Hochschule (ETH) Zürich, Fermi National Accelerator Laboratory, the University of Illinois at Urbana-Champaign, the Institut de Ciències de l''Espai (IEEC/CSIC), the Institut de Física d''Altes Energies, Lawrence Berkeley National Laboratory, the Ludwig-Maximilians Universität München and the associated Excellence Cluster Universe, the University of Michigan, the National Optical Astronomy Observatory, the University of Nottingham, The Ohio State University, the University of Pennsylvania, the University of Portsmouth, SLAC National Accelerator Laboratory, Stanford University, the University of Sussex, and Texas A&M University. The DES participants from Spanish institutions are partially supported by MINECO under grants AYA2012-39559, ESP2013- 48274, FPA2013-47986, and Centro de Excelencia Severo Ochoa SEV-2012-0234. Research leading to these results has received funding from the European Research Council under the European Unions Seventh Framework Programme (FP7/2007-2013) including ERC grant agreements 240672, 291329, and 306478. This paper has gone through internal review by the DES collaboration. The document is identified as FERMILAB-PUB-15-307-AE and DES-2015-0099.

Funders	Funder number
Centro de Excelencia Severo Ochoa	SEV-2012-0234
Collaborating Institutions are Argonne National Laboratory
Mitchell Institute for Fundamental Physics and Astronomy at Texas A&M University
Science and Technology Facilities Council of the United Kingdom
National Science Foundation	AST-1138766
U.S. Department of Energy	DE-FG02-91ER40690
University of Illinois at Urbana-Champaign
Stanford University
Fermilab
Lawrence Berkeley National Laboratory
University of California, Santa Cruz
University of Pennsylvania
Ohio State University
University of Chicago
University of Michigan
Texas A and M University	ESP2013- 48274, FPA2013-47986, AYA2012-39559
University of Portsmouth
National Centre for Supercomputing Applications
Seventh Framework Programme	1138766, 240672, 306478, 291329
SLAC National Accelerator Laboratory
Higher Education Funding Council for England
Engineering Research Centers	FERMILAB-PUB-15-307-AE, DES-2015-0099
University College London
European Research Council
University of Nottingham
University of Sussex
University of Edinburgh
Deutsche Forschungsgemeinschaft
Eidgenössische Technische Hochschule Zürich
Ministerio de Economía y Competitividad	FPA2012-39684
Ministério da Ciência, Tecnologia e Inovação
Conselho Nacional de Desenvolvimento Científico e Tecnológico
Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro
Financiadora de Estudos e Projetos
Seventh Framework Programme
Ludwig-Maximilians-Universität München
Ministry of Education and Science of Ukraine
Institut de Física d'Altes Energies

Keywords

Galaxies: statistics
Methods: data analysis
Methods: miscellaneous
Techniques: image processing

Access to Document

10.1093/mnras/stv2953

Cite this

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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. We introduce a new measurement method that aims to minimize this wastage, allowing precision measurement for any class of detectable stars or galaxies. We have implemented our proposal 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 fluxlimited 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.",

keywords = "Galaxies: statistics, Methods: data analysis, Methods: miscellaneous, Techniques: image processing",

author = "{The DES Collaboration} and E. Suchyta and Huff, {E. M.} and J. Aleksi{\'c} and P. Melchior and S. Jouvel and N. MacCrann and Ross, {A. J.} and M. Crocce and E. Gaztanaga and K. Honscheid and B. Leistedt and Peiris, {H. V.} and Rykoff, {E. S.} and E. Sheldon and T. Abbott and Abdalla, {F. B.} and S. Allam and M. Banerji and A. Benoit-L{\'e}vy and E. Bertin and D. Brooks and Burke, {D. L.} and {Carnero Rosell}, A. and {Carrasco Kind}, M. and J. Carretero and Cunha, {C. E.} and D'Andrea, {C. B.} and {Da Costa}, {L. N.} and DePoy, {D. L.} and S. Desai and Diehl, {H. T.} and Dietrich, {J. P.} and P. Doel and Eifler, {T. F.} and J. Estrada and Evrard, {A. E.} and B. Flaugher and P. Fosalba and J. Frieman and Gerdes, {D. W.} and D. Gruen and Gruendl, {R. A.} and James, {D. J.} and M. Jarvis and K. Kuehn and N. Kuropatkin and O. Lahav and M. Lima and Maia, {M. A.G.} and M. March",

note = "Publisher Copyright: {\textcopyright} 2016 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society.",

year = "2016",

month = jan,

day = "11",

doi = "10.1093/mnras/stv2953",

language = "English",

volume = "457",

pages = "786--808",

journal = "Monthly Notices of the Royal Astronomical Society",

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T2 - Accurate measurements with the faintest objects in the Dark Energy Survey

AU - The DES Collaboration

AU - Suchyta, E.

AU - Huff, E. M.

AU - Aleksić, J.

AU - Melchior, P.

AU - Jouvel, S.

AU - MacCrann, N.

AU - Ross, A. J.

AU - Crocce, M.

AU - Gaztanaga, E.

AU - Honscheid, K.

AU - Leistedt, B.

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AU - Abbott, T.

AU - Abdalla, F. B.

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AU - Benoit-Lévy, A.

AU - Bertin, E.

AU - Brooks, D.

AU - Burke, D. L.

AU - Carnero Rosell, A.

AU - Carrasco Kind, M.

AU - Carretero, J.

AU - Cunha, C. E.

AU - D'Andrea, C. B.

AU - Da Costa, L. N.

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AU - Frieman, J.

AU - Gerdes, D. W.

AU - Gruen, D.

AU - Gruendl, R. A.

AU - James, D. J.

AU - Jarvis, M.

AU - Kuehn, K.

AU - Kuropatkin, N.

AU - Lahav, O.

AU - Lima, M.

AU - Maia, M. A.G.

AU - March, M.

PY - 2016/1/11

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N2 - 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. We introduce a new measurement method that aims to minimize this wastage, allowing precision measurement for any class of detectable stars or galaxies. We have implemented our proposal 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 fluxlimited 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.

AB - 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. We introduce a new measurement method that aims to minimize this wastage, allowing precision measurement for any class of detectable stars or galaxies. We have implemented our proposal 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 fluxlimited 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.

KW - Galaxies: statistics

KW - Methods: data analysis

KW - Methods: miscellaneous

KW - Techniques: image processing

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JF - Monthly Notices of the Royal Astronomical Society

IS - 1

ER -

No galaxy left behind: Accurate measurements with the faintest objects in the Dark Energy Survey

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Keywords

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