Dark Energy Survey year 1 results: galaxy sample for BAO measurement
Spanish Ramon y Cajal MICINN program ; Ohio State University Center for Cosmology and AstroParticle Physics ; Spanish Ministerio de Economia y Competitividad ; Juan de la Cierva fellowship ; 'Plan Estatal de Investigacion Cientfica y Tecnica y de Innovacion' program of the Spanish government ; U.S. Department of Energy ; U.S. 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 ; Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ) ; Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) ; Ministerio da Ciencia, Tecnologia e Inovacao ; Deutsche Forschungsgemeinschaft ; 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 ; 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 ; OzDES Membership Consortium ; National Science Foundation ; MINECO ; ERDF funds from the European Union ; CERCA program of the Generalitat de Catalunya ; European Research Council under the European Union's Seventh Framework Program (FP7/2007-2013) ; Australian Research Council Centre of Excellence for All-sky Astrophysics (CAASTRO) ; U.S. Department of Energy, Office of Science, and Office of High Energy Physics ; Spanish Ministerio de Economia y Competitividad: ESP2013-48274-C3-1-P ; National Science Foundation: AST-1138766 ; National Science Foundation: AST-1536171 ; MINECO: AYA2015-71825 ; MINECO: ESP2015-66861 ; MINECO: FPA2015-68048 ; MINECO: SEV-2016-0588 ; MINECO: SEV-2016-0597 ; MINECO: MDM-2015-0509 ; European Research Council under the European Union's Seventh Framework Program (FP7/2007-2013): 240672 ; European Research Council under the European Union's Seventh Framework Program (FP7/2007-2013): 291329 ; European Research Council under the European Union's Seventh Framework Program (FP7/2007-2013): 306478 ; Australian Research Council Centre of Excellence for All-sky Astrophysics (CAASTRO): CE110001020 ; U.S. Department of Energy, Office of Science, and Office of High Energy Physics: DE-AC02-07CH11359 ; We define and characterize a sample of 1.3million galaxies extracted from the first year of Dark Energy Survey data, optimized to measure baryon acoustic oscillations (BAO) in the presence of significant redshift uncertainties. The sample is dominated by luminous red galaxies located at redshifts z greater than or similar to 0.6. We define the exact selection using colour and magnitude cuts that balance the need of high number densities and small photometric redshift uncertainties, using the corresponding forecasted BAO distance error as a figure-of-merit in the process. The typical photo z uncertainty varies from 2.3 per cent to 3.6 per cent (in units of 1+z) from z = 0.6 to 1, with number densities from 200 to 130 galaxies per deg(2) in tomographic bins of width Delta z = 0.1. Next, we summarize the validation of the photometric redshift estimation. We characterize and mitigate observational systematics including stellar contamination and show that the clustering on large scales is robust in front of those contaminants. We show that the clustering signal in the autocorrelations and cross-correlations is generally consistent with theoretical models, which serve as an additional test of the redshift distributions.