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Title: Dark Energy Survey Year-1 results: galaxy mock catalogues for BAO

Journal Article · · Monthly Notices of the Royal Astronomical Society
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [3];  [4];  [5]; ORCiD logo [6];  [7];  [8];  [9];  [10];  [7];  [7];  [7];  [11];  [4];  [12];  [13];  [14];  [15];  [16] more »;  [17];  [18];  [19];  [2];  [20];  [21];  [20];  [22];  [17];  [2];  [23];  [24];  [25];  [18];  [14];  [26];  [27];  [28];  [29];  [30];  [14];  [31];  [32];  [22];  [14];  [33];  [34];  [22];  [35];  [36];  [37];  [38];  [34];  [5];  [39];  [39] « less
  1. Institute of Cosmology and Gravitation, Dennis Sciama Building, University of Portsmouth, Portsmouth PO1 3FX, UK; Departamento de Física Teórica, Módulo C-15, Facultad de Ciencias, Universidad Autónoma de Madrid, E-28049 Cantoblanco, Madrid, Spain; Instituto de Física Teórica, UAM-CSIC, Universidad Autonoma de Madrid, E-28049 Cantoblanco, Madrid, Spain
  2. Institut de Ciències de l’Espai, IEEC-CSIC, Campus UAB, Facultat de Ciències, Torre C5 par-2, E-08193 Barcelona, Spain
  3. Center for Cosmology and AstroParticle Physics, The Ohio State University, Columbus, OH 43210, USA
  4. Departamento de Física Teórica, Módulo C-15, Facultad de Ciencias, Universidad Autónoma de Madrid, E-28049 Cantoblanco, Madrid, Spain; Instituto de Física Teórica, UAM-CSIC, Universidad Autonoma de Madrid, E-28049 Cantoblanco, Madrid, Spain
  5. Institute of Cosmology and Gravitation, Dennis Sciama Building, University of Portsmouth, Portsmouth PO1 3FX, UK
  6. Department of Physics, University of Florida, Gainesville, FL 32611, USA; Fermi National Accelerator Laboratory, Batavia, IL 60510, USA; GRAPPA, Institute of Theoretical Physics, University of Amsterdam, Science Park 904, NL-1090 GL Amsterdam, the Netherlands; Lorentz Institute, Leiden University, Niels Bohrweg 2, NL-2333 CA Leiden, the Netherlands
  7. Departamento de Física Matemática, Instituto de Física, Universidade de São Paulo,CP 66318, São Paulo, SP, 05314-970, Brazil; Laboratório Interinstitucional de e-Astronomia, Rua General José Cristino, 77, São Cristóvão, Rio de Janeiro, RJ, 20921-400, Brazil
  8. Departamento de Física Matemática, Instituto de Física, Universidade de São Paulo,CP 66318, São Paulo, SP, 05314-970, Brazil; Laboratório Interinstitucional de e-Astronomia, Rua General José Cristino, 77, São Cristóvão, Rio de Janeiro, RJ, 20921-400, Brazil; ICTP South American Institute for Fundamental Research & Instituto de Física Teórica, Universidade Estadual Paulista, São Paulo, Brazil; Department of Physics, Stanford University, 382 Via Pueblo Mall, Stanford, CA 94305, USA
  9. Institut de Ciències de l’Espai, IEEC-CSIC, Campus UAB, Facultat de Ciències, Torre C5 par-2, E-08193 Barcelona, Spain; School of Physics and Astronomy, Sun Yat-Sen University, Guangzhou 510275, China
  10. Laboratório Interinstitucional de e-Astronomia, Rua General José Cristino, 77, São Cristóvão, Rio de Janeiro, RJ, 20921-400, Brazil; Instituto de Física Teórica, Universidade Estadual Paulista, São Paulo, Brazil
  11. Laboratório Interinstitucional de e-Astronomia, Rua General José Cristino, 77, São Cristóvão, Rio de Janeiro, RJ, 20921-400, Brazil; ICTP South American Institute for Fundamental Research & Instituto de Física Teórica, Universidade Estadual Paulista, São Paulo, Brazil
  12. Max Planck Institute for Extraterrestrial Physics, Giessenbachstrasse, D-85748 Garching, Germany; Universitäts-Sternwarte, Fakultät für Physik, Ludwig-Maximilians Universität München, Scheinerstr. 1, D-81679München, Germany
  13. Department of Physics and Astronomy, University College London, Gower Street, London WC1E 6BT, UK; Department of Physics and Electronics, Rhodes University, PO Box 94, Grahamstown 6140, South Africa
  14. Fermi National Accelerator Laboratory, Batavia, IL 60510, USA
  15. Department of Physics and Astronomy, University College London, Gower Street, London WC1E 6BT, UK; CNRS, UMR 7095, Institut d’Astrophysique de Paris, F-75014 Paris, France; Institut d’Astrophysique de Paris, Sorbonne Universités, UPMC Univ Paris 06, UMR 7095, F-75014 Paris, France
  16. CNRS, UMR 7095, Institut d’Astrophysique de Paris, F-75014 Paris, France; Institut d’Astrophysique de Paris, Sorbonne Universités, UPMC Univ Paris 06, UMR 7095, F-75014 Paris, France
  17. Department of Physics and Astronomy, University College London, Gower Street, London WC1E 6BT, UK
  18. Department of Astronomy, University of Illinois, 1002 W. Green Street, Urbana, IL 61801, USA; National Center for Supercomputing Applications, 1205 West Clark St., Urbana, IL 61801, USA
  19. Institut de Física d’Altes Energies (IFAE), The Barcelona Institute of Science and Technology, Campus UAB, E-08193 Bellaterra (Barcelona) Spain
  20. Kavli Institute for Particle Astrophysics and Cosmology, PO Box 2450, Stanford University, Stanford, CA 94305, USA
  21. Laboratório Interinstitucional de e-Astronomia, Rua General José Cristino, 77, São Cristóvão, Rio de Janeiro, RJ, 20921-400, Brazil; Observatório Nacional, Rua Gal. José Cristino 77, Rio de Janeiro, RJ, 20921-400, Brazil
  22. Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain
  23. Fermi National Accelerator Laboratory, Batavia, IL 60510, USA; Kavli Institute for Cosmological Physics, University of Chicago, Chicago, IL 60637, USA
  24. Department of Astronomy, University of Michigan, Ann Arbor, MI 48109, USA; Department of Physics, University of Michigan, Ann Arbor, MI 48109, USA
  25. Kavli Institute for Particle Astrophysics and Cosmology, PO Box 2450, Stanford University, Stanford, CA 94305, USA; SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA
  26. Department of Physics and Astronomy, University College London, Gower Street, London WC1E 6BT, UK; Department of Physics, ETH Zurich, Wolfgang-Pauli-Strasse 16, CH-8093 Zurich, Switzerland
  27. Santa Cruz Institute for Particle Physics, Santa Cruz, CA 95064, USA
  28. Center for Cosmology and AstroParticle Physics, The Ohio State University, Columbus, OH 43210, USA; Department of Physics, The Ohio State University, Columbus, OH 43210, USA
  29. Astronomy Department, University of Washington, Box 351580, Seattle, WA 98195, USA
  30. Australian Astronomical Observatory, North Ryde, NSW 2113, Australia
  31. Institut de Física d’Altes Energies (IFAE), The Barcelona Institute of Science and Technology, Campus UAB, E-08193 Bellaterra (Barcelona) Spain; Institució Catalana de Recerca i Estudis Avançats, E-08010 Barcelona, Spain
  32. Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA 91109, USA
  33. SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA
  34. Department of Physics, University of Michigan, Ann Arbor, MI 48109, USA
  35. School of Physics and Astronomy, University of Southampton, Southampton SO17 1BJ, UK
  36. Laboratório Interinstitucional de e-Astronomia, Rua General José Cristino, 77, São Cristóvão, Rio de Janeiro, RJ, 20921-400, Brazil; Instituto de Física Gleb Wataghin, Universidade Estadual de Campinas, 13083-859, SP, Campinas, Brazil
  37. Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
  38. National Center for Supercomputing Applications, 1205 West Clark St., Urbana, IL 61801, USA
  39. Cerro Tololo Inter-American Observatory, National Optical Astronomy Observatory, Casilla 603, La Serena, Chile

Mock catalogues are a crucial tool in the analysis of galaxy surveys data, both for the accurate computation of covariance matrices, and for the optimization of analysis methodology and validation of data sets. In this paper, we present a set of 1800 galaxy mock catalogues designed to match the Dark Energy Survey Year-1 BAO sample (Crocce et al. 2017) in abundance, observational volume, redshift distribution and uncertainty, and redshift-dependent clustering. The simulated samples were built upon halogen (Avila et al. 2015) halo catalogues, based on a 2LPT density field with an empirical halo bias. For each of them, a light-cone is constructed by the superposition of snapshots in the redshift range 0.45 < z < 1.4. Uncertainties introduced by so-called photometric redshifts estimators were modelled with a double-skewed-Gaussian curve fitted to the data. We populate haloes with galaxies by introducing a hybrid halo occupation distribution–halo abundance matching model with two free parameters. These are adjusted to achieve a galaxy bias evolution b(z ph) that matches the data at the 1σ level in the range 0.6 < z ph < 1.0. We further analyse the galaxy mock catalogues and compare their clustering to the data using the angular correlation function w(θ), the comoving transverse separation clustering ξμ< 0.8(s⊥) and the angular power spectrum Cℓ, finding them in agreement. This is the first large set of three-dimensional {RA,Dec.,z} galaxy mock catalogues able to simultaneously accurately reproduce the photometric redshift uncertainties and the galaxy clustering.

Research Organization:
SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States); Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Organization:
USDOE Office of Science (SC), High Energy Physics (HEP); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
Contributing Organization:
DES Collaboration
Grant/Contract Number:
AC02-07CH11359; AC05-00OR22725
OSTI ID:
1431578
Alternate ID(s):
OSTI ID: 1468025
Report Number(s):
FERMILAB-PUB-17-587; IFT-UAM-CSIC-17-124; DES-2017-0292; arXiv:1712.06232; 1643782; TRN: US1802321
Journal Information:
Monthly Notices of the Royal Astronomical Society, Vol. 479, Issue 1; ISSN 0035-8711
Publisher:
Royal Astronomical SocietyCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 21 works
Citation information provided by
Web of Science

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Shrinkage Estimation of the Power Spectrum Covariance Matrix text January 2007
Galaxies in LCDM with Halo Abundance Matching: luminosity-velocity relation, baryonic mass-velocity relation, velocity function and clustering text January 2010
A New Method to Correct for Fiber Collisions in Galaxy Two-Point Statistics text January 2011
The clustering of galaxies at z~0.5 in the SDSS-III Data Release 9 BOSS-CMASS sample: a test for the LCDM cosmology text January 2012
Solving Large Scale Structure in Ten Easy Steps with COLA text January 2013
The Effect of Covariance Estimator Error on Cosmological Parameter Constraints text January 2013
An accurate tool for the fast generation of dark matter halo catalogs text January 2013
HMFcalc: An Online Tool for Calculating Dark Matter Halo Mass Functions preprint January 2013
Mock galaxy catalogs using the quick particle mesh method text January 2013
The MICE Grand Challenge Lightcone Simulation I: Dark matter clustering text January 2013
The MICE Grand Challenge Lightcone Simulation II: Halo and Galaxy catalogues text January 2013
Estimating Cosmological Parameter Covariance text January 2014
EZmocks: extending the Zel'dovich approximation to generate mock galaxy catalogues with accurate clustering statistics text January 2014
HALOGEN: A tool for fast generation of mock halo catalogues text January 2014
Planck 2015 results. XIII. Cosmological parameters text January 2015
redMaGiC: Selecting Luminous Red Galaxies from the DES Science Verification Data text January 2015
DNF - Galaxy photometric redshift by Directional Neighbourhood Fitting text January 2015
Approximate methods for the generation of dark matter halo catalogs in the age of precision cosmology preprint January 2016
The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: Observational systematics and baryon acoustic oscillations in the correlation function text January 2016
Precision matrix expansion - efficient use of numerical simulations in estimating errors on cosmological parameters text January 2017
Optimized Clustering Estimators for BAO Measurements Accounting for Significant Redshift Uncertainty text January 2017
Dark Energy Survey Year 1 Results: Photometric Data Set for Cosmology text January 2017
Dark Energy Survey Year 1 Results: Redshift distributions of the weak lensing source galaxies text January 2017
Halo occupation numbers and galaxy bias text January 2000
PTHalos: A fast method for generating mock galaxy distributions text January 2001
Theoretical Models of the Halo Occupation Distribution: Separating Central and Satellite Galaxies text January 2004
HEALPix -- a Framework for High Resolution Discretization, and Fast Analysis of Data Distributed on the Sphere text January 2004
The 2dF Galaxy Redshift Survey: Power-spectrum analysis of the final dataset and cosmological implications text January 2005
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Baryonic Features in the Matter Transfer Function text January 1997
Bayesian photometric redshift estimation text January 1998

Cited By (12)

BAO from angular clustering: optimization and mitigation of theoretical systematics journal July 2018
Dark Energy Survey year 1 results: galaxy sample for BAO measurement journal September 2018
Dark Energy Survey Year 1 results: measurement of the baryon acoustic oscillation scale in the distribution of galaxies to redshift 1 journal December 2018
The redshift-space momentum power spectrum – I. Optimal estimation from peculiar velocity surveys journal May 2019
Dark Energy Survey Year 1 results: measurement of the galaxy angular power spectrum journal June 2019
Comparing approximate methods for mock catalogues and covariance matrices II: power spectrum multipoles journal February 2019
Cosmological inference from galaxy-clustering power spectrum: Gaussianization and covariance decomposition journal March 2019
Dark Energy Survey Year 1 results: Measurement of the baryon acoustic oscillation scale in the distribution of galaxies to redshift 1 text January 2019
BAO from angular clustering: optimization and mitigation of theoretical systematics text January 2018
Cosmological Constraints from Multiple Probes in the Dark Energy Survey text January 2018
Cosmological Inference from Galaxy-Clustering Power Spectrum: Gaussianization and Covariance Decomposition text January 2018
The Redshift-Space Momentum Power Spectrum I: Optimal Estimation From Peculiar Velocity Surveys text January 2019

Figures / Tables (16)


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