Journal
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
Volume 457, Issue 1, Pages 786-808Publisher
OXFORD UNIV PRESS
DOI: 10.1093/mnras/stv2953
Keywords
methods: data analysis; methods: miscellaneous; techniques: image processing; galaxies: statistics
Categories
Funding
- Ohio State University Graduate Presidential Fellowship
- CCAPP postdoctoral fellowship
- MINECO [FPA2012-39684, AYA2012-39559, ESP2013-48274, FPA2013-47986]
- US Department of Energy [DE-FG02-91ER40690]
- US National Science Foundation
- Ministry of Science and Education of Spain
- Science and Technology Facilities Council of the United Kingdom
- Higher Education Funding Council for England
- National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign
- Kavli Institute of Cosmological Physics at the University of Chicago
- Center for Cosmology and Astro-Particle Physics at The Ohio State University
- Mitchell Institute for Fundamental Physics and Astronomy at Texas AM University
- Financiadora de Estudos e Projetos
- Fundacao Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro
- Conselho Nacional de Desenvolvimento Cientifico e Tecnologico
- Ministerio da Ciencia, Tecnologia e Inovacao
- Deutsche Forschungsgemeinschaft
- DES
- National Science Foundation [AST-1138766]
- Argonne National Laboratory
- University of California at Santa Cruz
- University of Cambridge
- Centro de Investigaciones Energeticas
- Medioambientales y Tecnologicas-Madrid
- University of Chicago
- University College London
- DES-Brazil Consortium
- University of Edinburgh
- Eidgenossische Technische Hochschule (ETH) Zurich
- Fermi National Accelerator Laboratory
- University of Illinois at Urbana-Champaign
- Institut de Ciencies de l'Espai (IEEC/CSIC)
- Institut de Fisica d'Altes Energies
- Lawrence Berkeley National Laboratory
- Ludwig-Maximilians Universitat Munchen
- associated Excellence Cluster Universe
- University of Michigan
- National Optical Astronomy Observatory
- University of Nottingham
- Ohio State University
- University of Pennsylvania
- University of Portsmouth
- SLAC National Accelerator Laboratory
- Stanford University
- University of Sussex
- Texas AM University
- Centro de Excelencia Severo Ochoa [SEV-2012-0234]
- European Research Council under the European Union [240672, 291329, 306478]
- STFC [ST/K00090X/1, ST/K000985/1, ST/M004708/1, ST/M001334/1, ST/M005305/1] Funding Source: UKRI
- Science and Technology Facilities Council [ST/M001334/1, 1244451, ST/K00090X/1, ST/M004708/1, ST/K000985/1] Funding Source: researchfish
- UK Space Agency [ST/K003135/1, ST/N002679/1] Funding Source: researchfish
- ICREA Funding Source: Custom
- Direct For Mathematical & Physical Scien
- Division Of Physics [1125897] Funding Source: National Science Foundation
- Division Of Astronomical Sciences
- Direct For Mathematical & Physical Scien [1536171] Funding Source: National Science Foundation
- Division Of Astronomical Sciences
- Direct For Mathematical & Physical Scien [1138737] Funding Source: National Science Foundation
Ask authors/readers for more resources
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 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 degrees.004 < theta < 0 degrees.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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available