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Title: Producing a BOSS CMASS sample with DES imaging

Abstract

We present a sample of galaxies with the Dark Energy Survey (DES) photometry that replicates the properties of the BOSS CMASS sample. The CMASS galaxy sample has been well characterized by the Sloan Digital Sky Survey (SDSS) collaboration and was used to obtain the most powerful redshift-space galaxy clustering measurements to date. A joint analysis of redshift-space distortions (such as those probed by CMASS from SDSS) and a galaxy-galaxy lensing measurement for an equivalent sample from DES can provide powerful cosmological constraints. Unfortunately, the DES and SDSS-BOSS footprints have only minimal overlap, primarily on the celestial equator near the SDSS Stripe 82 region. Using this overlap, we build a robust Bayesian model to select CMASS-like galaxies in the remainder of the DES footprint. The newly defined DES-CMASS (DMASS) sample consists of 117,293 effective galaxies covering $$1,244 {\rm deg}^2$$. Through various validation tests, we show that the DMASS sample selected by this model matches well with the BOSS CMASS sample, specifically in the South Galactic cap (SGC) region that includes Stripe 82. Combining measurements of the angular correlation function and the clustering-z distribution of DMASS, we constrain the difference in mean galaxy bias and mean redshift between the BOSS CMASS and DMASS samples to be $$\Delta b = 0.010^{+0.045}_{-0.052}$$ and $$\Delta z = \left( 3.46^{+5.48}_{-5.55} \right) \times 10^{-3}$$ for the SGC portion of CMASS, and $$\Delta b = 0.044^{+0.044}_{-0.043} $$ and $$\Delta z= ( 3.51^{+4.93}_{-5.91}) \times 10^{-3}$$ for the full CMASS sample. These values indicate that the mean bias of galaxies and mean redshift in the DMASS sample is consistent with both CMASS samples within $$1\sigma$$.

Authors:
ORCiD logo [1];  [2]; ORCiD logo [3];  [3];  [1];  [1];  [1];  [4]; ORCiD logo [5];  [6];  [7];  [1];  [8]; ORCiD logo [9];  [10];  [11]; ORCiD logo [12];  [13];  [14];  [15] more »;  [16];  [17];  [8];  [18];  [9];  [18];  [19]; ORCiD logo [20];  [13];  [15];  [8];  [21];  [22];  [21];  [23];  [24];  [15];  [25];  [26]; ORCiD logo [27];  [13];  [19];  [28];  [15]; ORCiD logo [8]; ORCiD logo [27];  [16];  [8];  [29];  [18];  [16];  [30]; ORCiD logo [31];  [32]; ORCiD logo [33];  [34];  [29]; ORCiD logo [35];  [36]; ORCiD logo [37] « less
  1. Center for Cosmology and Astro-Particle Physics, The Ohio State University, Columbus, OH 43210, USA; Department of Physics, The Ohio State University, Columbus, OH 43210, USA
  2. Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109, USA
  3. Center for Cosmology and Astro-Particle Physics, The Ohio State University, Columbus, OH 43210, USA
  4. Department of Physics, Duke University, Durham, NC 27708, USA
  5. Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, PO Box 2450, Stanford, CA 94305, USA
  6. Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109, USA; Department of Astronomy/Steward Observatory, University of Arizona, 933 North Cherry Avenue, Tucson, AZ 85721-0065, USA
  7. Physics Department, University of Wisconsin-Madison, 2320 Chamberlin Hall, 1150 University Avenue, Madison, WI 53706-1390, USA
  8. Fermi National Accelerator Laboratory, PO Box 500, Batavia, IL 60510, USA
  9. Instituto de Fisica Teorica UAM/CSIC, Universidad Autonoma de Madrid, E-28049 Madrid, Spain
  10. 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
  11. Department of Physics and Astronomy, University College London, Gower Street, London WC1E 6BT, UK
  12. Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), E-28040 Madrid, Spain; Laboratório Interinstitucional de e-Astronomia – LIneA, Rua Gal. José Cristino 77, Rio de Janeiro, RJ 20921-400, Brazil
  13. Department of Astronomy, University of Illinois at Urbana-Champaign, 1002 W. Green Street, Urbana, IL 61801, USA; National Center for Supercomputing Applications, 1205 West Clark St, Urbana, IL 61801, USA
  14. Institut de Física d’Altes Energies (IFAE), The Barcelona Institute of Science and Technology, Campus UAB, E-08193 Bellaterra (Barcelona), Spain
  15. Laboratório Interinstitucional de e-Astronomia – LIneA, Rua Gal. José Cristino 77, Rio de Janeiro, RJ 20921-400, Brazil; Observatório Nacional, Rua Gal. José Cristino 77, Rio de Janeiro, RJ 20921-400, Brazil
  16. Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), E-28040 Madrid, Spain
  17. Department of Physics, IIT Hyderabad, Kandi, Telangana 502285, India
  18. Institut d’Estudis Espacials de Catalunya (IEEC), E-08034 Barcelona, Spain; Institute of Space Sciences (ICE, CSIC), Campus UAB, Carrer de Can Magrans, s/n, E-08193 Barcelona, Spain
  19. Department of Astronomy, University of Michigan, Ann Arbor, MI 48109, USA; Department of Physics, University of Michigan, Ann Arbor, MI 48109, USA
  20. Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, PO Box 2450, Stanford, CA 94305, USA; Department of Physics, Stanford University, 382 Via Pueblo Mall, Stanford, CA 94305, USA; SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA
  21. Santa Cruz Institute for Particle Physics, Santa Cruz, CA 95064, USA
  22. Harvard–Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138, USA
  23. Australian Astronomical Optics, Macquarie University, North Ryde, NSW 2113, Australia
  24. Laboratório Interinstitucional de e-Astronomia – LIneA, Rua Gal. José Cristino 77, Rio de Janeiro, RJ 20921-400, Brazil; Departamento de Física Matemática, Instituto de Física, Universidade de São Paulo, CP 66318, São Paulo, SP 05314-970, Brazil
  25. George P. and Cynthia Woods Mitchell Institute for Fundamental Physics and Astronomy, Department of Physics and Astronomy, Texas A&M University, College Station, TX 77843, USA
  26. Center for Cosmology and Astro-Particle Physics, The Ohio State University, Columbus, OH 43210, USA; Department of Astronomy, The Ohio State University, Columbus, OH 43210, USA
  27. Department of Astrophysical Sciences, Princeton University, Peyton Hall, Princeton, NJ 08544, USA
  28. 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
  29. Department of Physics, University of Michigan, Ann Arbor, MI 48109, USA
  30. School of Physics and Astronomy, University of Southampton, Southampton SO17 1BJ, UK
  31. Physics Department, Brandeis University, 415 South Street, Waltham, MA 02453, USA
  32. Laboratório Interinstitucional de e-Astronomia – LIneA, Rua Gal. José Cristino 77, Rio de Janeiro, RJ 20921-400, Brazil; Instituto de Física Gleb Wataghin, Universidade Estadual de Campinas, Campinas, SP 13083-859, Brazil
  33. Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
  34. National Center for Supercomputing Applications, 1205 West Clark St, Urbana, IL 61801, USA
  35. Institute of Cosmology and Gravitation, University of Portsmouth, Portsmouth PO1 3FX, UK
  36. Excellence Cluster Origins, Boltzmannstr 2, D-85748 Garching, Germany; Max Planck Institute for Extraterrestrial Physics, Giessenbachstrasse, D-85748 Garching, Germany; Universitäts-Sternwarte, Fakultät für Physik, Ludwig-Maximilians Universität München, Scheinerstr 1, D-81679 München, Germany
  37. Institute for Astronomy, University of Edinburgh, Edinburgh EH9 3HJ, UK
Publication Date:
Research Org.:
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); Univ. of Michigan, Ann Arbor, MI (United States)
Sponsoring Org.:
USDOE Office of Science (SC), High Energy Physics (HEP); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR); National Aeronautics and Space Administration (NASA); Simons Foundation; National Science Foundation (NSF)
Contributing Org.:
DES Collaboration
OSTI Identifier:
1560914
Alternate Identifier(s):
OSTI ID: 1556980; OSTI ID: 1606729; OSTI ID: 1634025; OSTI ID: 1691463
Report Number(s):
arXiv:1906.01136; DES-2019-0449; FERMILAB-PUB-19-238-AE; arXiv:1906.01136v1
Journal ID: ISSN 0035-8711
Grant/Contract Number:  
AC05-00OR22725; 15-WFIRST15-0008; AST-1138766; AST-1536171; AC02-07CH11359; SC0019193; AC02-76SF00515; AYA2015-71825; ESP2015-66861; FPA2015-68048; SEV-2016-0588; SEV-2016-0597; MDM-2015-0509; 240672; 291329; 306478; FP7/2007-2013; 465376/2014-2
Resource Type:
Published Article
Journal Name:
Monthly Notices of the Royal Astronomical Society
Additional Journal Information:
Journal Name: Monthly Notices of the Royal Astronomical Society Journal Volume: 489 Journal Issue: 2; Journal ID: ISSN 0035-8711
Publisher:
Royal Astronomical Society
Country of Publication:
United Kingdom
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS; methods: data analysis; techniques: photometric; galaxies: general

Citation Formats

Lee, S., Huff, E. M., Ross, A. J., Choi, A., Hirata, C., Honscheid, K., MacCrann, N., Troxel, M. A., Davis, C., Eifler, T. F., Cawthon, R., Elvin-Poole, J., Annis, J., Avila, S., Bertin, E., Brooks, D., Carnero Rosell, A., Carrasco Kind, M., Carretero, J., da Costa, L. N., De Vicente, J., Desai, S., Flaugher, B., Fosalba, P., García-Bellido, J., Gaztanaga, E., Gerdes, D. W., Gruen, D., Gruendl, R. A., Gschwend, J., Gutierrez, G., Hollowood, D. L., James, D. J., Jeltema, T., Kuehn, K., Lima, M., Maia, M. A. G., Marshall, J. L., Martini, P., Melchior, P., Menanteau, F., Miller, C. J., Miquel, R., Ogando, R. L. C., Palmese, A., Plazas, A. A., Sanchez, E., Scarpine, V., Schubnell, M., Serrano, S., Sevilla-Noarbe, I., Smith, M., Soares-Santos, M., Sobreira, F., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., Weller, J., and Zuntz, J. Producing a BOSS CMASS sample with DES imaging. United Kingdom: N. p., 2019. Web. doi:10.1093/mnras/stz2288.
Lee, S., Huff, E. M., Ross, A. J., Choi, A., Hirata, C., Honscheid, K., MacCrann, N., Troxel, M. A., Davis, C., Eifler, T. F., Cawthon, R., Elvin-Poole, J., Annis, J., Avila, S., Bertin, E., Brooks, D., Carnero Rosell, A., Carrasco Kind, M., Carretero, J., da Costa, L. N., De Vicente, J., Desai, S., Flaugher, B., Fosalba, P., García-Bellido, J., Gaztanaga, E., Gerdes, D. W., Gruen, D., Gruendl, R. A., Gschwend, J., Gutierrez, G., Hollowood, D. L., James, D. J., Jeltema, T., Kuehn, K., Lima, M., Maia, M. A. G., Marshall, J. L., Martini, P., Melchior, P., Menanteau, F., Miller, C. J., Miquel, R., Ogando, R. L. C., Palmese, A., Plazas, A. A., Sanchez, E., Scarpine, V., Schubnell, M., Serrano, S., Sevilla-Noarbe, I., Smith, M., Soares-Santos, M., Sobreira, F., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., Weller, J., & Zuntz, J. Producing a BOSS CMASS sample with DES imaging. United Kingdom. https://doi.org/10.1093/mnras/stz2288
Lee, S., Huff, E. M., Ross, A. J., Choi, A., Hirata, C., Honscheid, K., MacCrann, N., Troxel, M. A., Davis, C., Eifler, T. F., Cawthon, R., Elvin-Poole, J., Annis, J., Avila, S., Bertin, E., Brooks, D., Carnero Rosell, A., Carrasco Kind, M., Carretero, J., da Costa, L. N., De Vicente, J., Desai, S., Flaugher, B., Fosalba, P., García-Bellido, J., Gaztanaga, E., Gerdes, D. W., Gruen, D., Gruendl, R. A., Gschwend, J., Gutierrez, G., Hollowood, D. L., James, D. J., Jeltema, T., Kuehn, K., Lima, M., Maia, M. A. G., Marshall, J. L., Martini, P., Melchior, P., Menanteau, F., Miller, C. J., Miquel, R., Ogando, R. L. C., Palmese, A., Plazas, A. A., Sanchez, E., Scarpine, V., Schubnell, M., Serrano, S., Sevilla-Noarbe, I., Smith, M., Soares-Santos, M., Sobreira, F., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., Weller, J., and Zuntz, J. Mon . "Producing a BOSS CMASS sample with DES imaging". United Kingdom. https://doi.org/10.1093/mnras/stz2288.
@article{osti_1560914,
title = {Producing a BOSS CMASS sample with DES imaging},
author = {Lee, S. and Huff, E. M. and Ross, A. J. and Choi, A. and Hirata, C. and Honscheid, K. and MacCrann, N. and Troxel, M. A. and Davis, C. and Eifler, T. F. and Cawthon, R. and Elvin-Poole, J. and Annis, J. and Avila, S. and Bertin, E. and Brooks, D. and Carnero Rosell, A. and Carrasco Kind, M. and Carretero, J. and da Costa, L. N. and De Vicente, J. and Desai, S. and Flaugher, B. and Fosalba, P. and García-Bellido, J. and Gaztanaga, E. and Gerdes, D. W. and Gruen, D. and Gruendl, R. A. and Gschwend, J. and Gutierrez, G. and Hollowood, D. L. and James, D. J. and Jeltema, T. and Kuehn, K. and Lima, M. and Maia, M. A. G. and Marshall, J. L. and Martini, P. and Melchior, P. and Menanteau, F. and Miller, C. J. and Miquel, R. and Ogando, R. L. C. and Palmese, A. and Plazas, A. A. and Sanchez, E. and Scarpine, V. and Schubnell, M. and Serrano, S. and Sevilla-Noarbe, I. and Smith, M. and Soares-Santos, M. and Sobreira, F. and Suchyta, E. and Swanson, M. E. C. and Tarle, G. and Thomas, D. and Weller, J. and Zuntz, J.},
abstractNote = {We present a sample of galaxies with the Dark Energy Survey (DES) photometry that replicates the properties of the BOSS CMASS sample. The CMASS galaxy sample has been well characterized by the Sloan Digital Sky Survey (SDSS) collaboration and was used to obtain the most powerful redshift-space galaxy clustering measurements to date. A joint analysis of redshift-space distortions (such as those probed by CMASS from SDSS) and a galaxy-galaxy lensing measurement for an equivalent sample from DES can provide powerful cosmological constraints. Unfortunately, the DES and SDSS-BOSS footprints have only minimal overlap, primarily on the celestial equator near the SDSS Stripe 82 region. Using this overlap, we build a robust Bayesian model to select CMASS-like galaxies in the remainder of the DES footprint. The newly defined DES-CMASS (DMASS) sample consists of 117,293 effective galaxies covering $1,244 {\rm deg}^2$. Through various validation tests, we show that the DMASS sample selected by this model matches well with the BOSS CMASS sample, specifically in the South Galactic cap (SGC) region that includes Stripe 82. Combining measurements of the angular correlation function and the clustering-z distribution of DMASS, we constrain the difference in mean galaxy bias and mean redshift between the BOSS CMASS and DMASS samples to be $\Delta b = 0.010^{+0.045}_{-0.052}$ and $\Delta z = \left( 3.46^{+5.48}_{-5.55} \right) \times 10^{-3}$ for the SGC portion of CMASS, and $\Delta b = 0.044^{+0.044}_{-0.043} $ and $\Delta z= ( 3.51^{+4.93}_{-5.91}) \times 10^{-3}$ for the full CMASS sample. These values indicate that the mean bias of galaxies and mean redshift in the DMASS sample is consistent with both CMASS samples within $1\sigma$.},
doi = {10.1093/mnras/stz2288},
journal = {Monthly Notices of the Royal Astronomical Society},
number = 2,
volume = 489,
place = {United Kingdom},
year = {Mon Sep 02 00:00:00 EDT 2019},
month = {Mon Sep 02 00:00:00 EDT 2019}
}

Journal Article:
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https://doi.org/10.1093/mnras/stz2288

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  • Monthly Notices of the Royal Astronomical Society: Letters, Vol. 422, Issue 1
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The 10 Meter South Pole Telescope
journal, May 2011

  • Carlstrom, J. E.; Ade, P. A. R.; Aird, K. A.
  • Publications of the Astronomical Society of the Pacific, Vol. 123, Issue 903
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On the spatial correlations of Abell clusters
journal, September 1984


Dark Energy Survey Year 1 Results: calibration of redMaGiC redshift distributions in DES and SDSS from cross-correlations
journal, September 2018

  • Cawthon, R.; Davis, C.; Gatti, M.
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Extreme deconvolution: Inferring complete distribution functions from noisy, heterogeneous and incomplete observations
journal, June 2011

  • Bovy, Jo; Hogg, David W.; Roweis, Sam T.
  • The Annals of Applied Statistics, Vol. 5, Issue 2B
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The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: BAO measurement from the LOS-dependent power spectrum of DR12 BOSS galaxies
journal, May 2016

  • Gil-Marín, Héctor; Percival, Will J.; Cuesta, Antonio J.
  • Monthly Notices of the Royal Astronomical Society, Vol. 460, Issue 4
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GALAXY-MASS CORRELATIONS ON 10 Mpc SCALES IN THE DEEP LENS SURVEY
journal, October 2012


The Dark Energy Survey: more than dark energy – an overview
journal, March 2016

  • Abbott, T.; Abdalla, F. B.; Aleksic, J.
  • Monthly Notices of the Royal Astronomical Society, Vol. 460, Issue 2, p. 1270-1299
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The Sloan Digital Sky Survey: Technical Summary
journal, September 2000

  • York, Donald G.; Adelman, J.; Anderson, Jr., John E.
  • The Astronomical Journal, Vol. 120, Issue 3
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Cosmological parameter constraints from galaxy–galaxy lensing and galaxy clustering with the SDSS DR7
journal, April 2013

  • Mandelbaum, Rachel; Slosar, Anže; Baldauf, Tobias
  • Monthly Notices of the Royal Astronomical Society, Vol. 432, Issue 2
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A measurement of CMB cluster lensing with SPT and DES year 1 data
journal, February 2018

  • Baxter, E. J.; Raghunathan, S.; Crawford, T. M.
  • Monthly Notices of the Royal Astronomical Society, Vol. 476, Issue 2
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THE SLOAN DIGITAL SKY SURVEY COADD: 275 deg 2 OF DEEP SLOAN DIGITAL SKY SURVEY IMAGING ON STRIPE 82
journal, September 2014

  • Annis, James; Soares-Santos, Marcelle; Strauss, Michael A.
  • The Astrophysical Journal, Vol. 794, Issue 2
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Dark Energy Survey Year 1 results: cross-correlation redshifts – methods and systematics characterization
journal, February 2018

  • Gatti, M.; Vielzeuf, P.; Davis, C.
  • Monthly Notices of the Royal Astronomical Society, Vol. 477, Issue 2
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Unbiased methods for removing systematics from galaxy clustering measurements
journal, December 2015

  • Elsner, Franz; Leistedt, Boris; Peiris, Hiranya V.
  • Monthly Notices of the Royal Astronomical Society, Vol. 456, Issue 2
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Recovering redshift distributions with cross-correlations: pushing the boundaries
journal, April 2013

  • Schmidt, Samuel J.; Ménard, Brice; Scranton, Ryan
  • Monthly Notices of the Royal Astronomical Society, Vol. 431, Issue 4
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Cold dust emission from X-ray AGN in the SCUBA-2 Cosmology Legacy Survey: dependence on luminosity, obscuration and AGN activity
journal, September 2015

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  • Monthly Notices of the Royal Astronomical Society, Vol. 454, Issue 1
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Dark Energy and the Accelerating Universe
journal, September 2008


Cosmological constraints from a combination of galaxy clustering and lensing – I. Theoretical framework
journal, February 2013

  • van den Bosch, Frank C.; More, Surhud; Cacciato, Marcello
  • Monthly Notices of the Royal Astronomical Society, Vol. 430, Issue 2
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The blue tip of the Stellar Locus: Measuring Reddening with the Sloan Digital sky Survey
journal, November 2010

  • Schlafly, Edward F.; Finkbeiner, Douglas P.; Schlegel, David J.
  • The Astrophysical Journal, Vol. 725, Issue 1
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Sdss-Iii: Massive Spectroscopic Surveys of the Distant Universe, the Milky way, and Extra-Solar Planetary Systems
journal, August 2011

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Planck 2015 results : XV. Gravitational lensing
journal, September 2016


The Eighth data Release of the Sloan Digital sky Survey: First data from Sdss-Iii
journal, March 2011

  • Aihara, Hiroaki; Allende Prieto, Carlos; An, Deokkeun
  • The Astrophysical Journal Supplement Series, Vol. 193, Issue 2
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KiDS+2dFLenS+GAMA: testing the cosmological model with the EG statistic
journal, June 2018

  • Amon, A.; Blake, C.; Heymans, C.
  • Monthly Notices of the Royal Astronomical Society, Vol. 479, Issue 3
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2dFLenS and KiDS: determining source redshift distributions with cross-correlations
journal, November 2016

  • Johnson, Andrew; Blake, Chris; Amon, Alexandra
  • Monthly Notices of the Royal Astronomical Society, Vol. 465, Issue 4
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The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: RSD measurement from the LOS-dependent power spectrum of DR12 BOSS galaxies
journal, May 2016

  • Gil-Marín, Héctor; Percival, Will J.; Brownstein, Joel R.
  • Monthly Notices of the Royal Astronomical Society, Vol. 460, Issue 4
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Weak Lensing for Precision Cosmology
journal, September 2018


A survey of galaxy redshifts. V - The two-point position and velocity correlations
journal, April 1983

  • Davis, M.; Peebles, P. J. E.
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Ameliorating systematic uncertainties in the angular clustering of galaxies: a study using the SDSS-III: Ameliorating systematic uncertainties in w(θ)
journal, September 2011


Forward Global Photometric Calibration of the Dark Energy Survey
journal, December 2017


Galaxy-galaxy weak lensing in the Sloan Digital Sky Survey: intrinsic alignments and shear calibration errors
journal, September 2004

  • Hirata, Christopher M.; Mandelbaum, Rachel; Seljak, Uroš
  • Monthly Notices of the Royal Astronomical Society, Vol. 353, Issue 2
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The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: single-probe measurements from DR12 galaxy clustering – towards an accurate model
journal, June 2017

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  • Monthly Notices of the Royal Astronomical Society, Vol. 471, Issue 2
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ChainConsumer
journal, August 2016


The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: mock galaxy catalogues for the BOSS Final Data Release
journal, January 2016

  • Kitaura, Francisco-Shu; Rodríguez-Torres, Sergio; Chuang, Chia-Hsun
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healpy: equal area pixelization and spherical harmonics transforms for data on the sphere in Python
journal, March 2019

  • Zonca, Andrea; Singer, Leo; Lenz, Daniel
  • Journal of Open Source Software, Vol. 4, Issue 35
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the-wizz: clustering redshift estimation for everyone
journal, February 2017

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  • Monthly Notices of the Royal Astronomical Society, Vol. 467, Issue 3
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SDSS galaxy bias from halo mass-bias relation and its cosmological implications
journal, February 2005


CosmoSIS: Modular cosmological parameter estimation
journal, September 2015


Measuring Reddening with Sloan Digital sky Survey Stellar Spectra and Recalibrating sfd
journal, August 2011


Mapping and Simulating Systematics due to Spatially Varying Observing Conditions in des Science Verification data
journal, October 2016

  • Leistedt, B.; Peiris, H. V.; Elsner, F.
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SDSS-III Baryon Oscillation Spectroscopic Survey Data Release 12: galaxy target selection and large-scale structure catalogues
journal, November 2015

  • Reid, Beth; Ho, Shirley; Padmanabhan, Nikhil
  • Monthly Notices of the Royal Astronomical Society, Vol. 455, Issue 2
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Matplotlib: A 2D Graphics Environment
journal, January 2007


Dark Energy Survey year 1 results: Galaxy clustering for combined probes
journal, August 2018


Bias and variance of angular correlation functions
journal, July 1993

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Probing gravity with a joint analysis of galaxy and CMB lensing and SDSS spectroscopy
journal, October 2018

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Measurements of Ω and Λ from 42 High‐Redshift Supernovae
journal, June 1999

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The Wide-Field Infrared Survey Explorer (Wise): Mission Description and Initial On-Orbit Performance
journal, November 2010


The 2.5 m Telescope of the Sloan Digital Sky Survey
journal, April 2006

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THINK OUTSIDE THE COLOR BOX: PROBABILISTIC TARGET SELECTION AND THE SDSS - XDQSO QUASAR TARGETING CATALOG
journal, February 2011


redMaGiC: selecting luminous red galaxies from the DES Science Verification data
journal, May 2016

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Dark Energy Survey year 1 results: galaxy sample for BAO measurement
journal, September 2018

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  • Monthly Notices of the Royal Astronomical Society, Vol. 482, Issue 2
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