skip to main content
DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Dark Energy Survey Year 1 results: cross-correlation redshifts – methods and systematics characterization

Abstract

We use numerical simulations to characterize the performance of a clustering-based method to calibrate photometric redshift biases. In particular, we cross-correlate the weak lensing source galaxies from the Dark Energy Survey Year 1 sample with redMaGiC galaxies (luminous red galaxies with secure photometric redshifts) to estimate the redshift distribution of the former sample. The recovered redshift distributions are used to calibrate the photometric redshift bias of standard photo-z methods applied to the same source galaxy sample. We apply the method to two photo-z codes run in our simulated data: Bayesian Photometric Redshift and Directional Neighbourhood Fitting. We characterize the systematic uncertainties of our calibration procedure, and find that these systematic uncertainties dominate our error budget. The dominant systematics are due to our assumption of unevolving bias and clustering across each redshift bin, and to differences between the shapes of the redshift distributions derived by clustering versus photo-zs. The systematic uncertainty in the mean redshift bias of the source galaxy sample is Δz ≲ 0.02, though the precise value depends on the redshift bin under consideration. We discuss possible ways to mitigate the impact of our dominant systematics in future analyses.

Authors:
 [1];  [1];  [2];  [3];  [4];  [5];  [6];  [7];  [8];  [7]; ORCiD logo [4];  [9];  [10];  [1];  [11];  [7];  [3];  [11];  [12];  [11] more »;  [13];  [14];  [15];  [11];  [11];  [12];  [6];  [15];  [16];  [17];  [17];  [18];  [19];  [20];  [21];  [19];  [22];  [23];  [22];  [24];  [22];  [22];  [25];  [14];  [14];  [26];  [27];  [12];  [28];  [29];  [1];  [2];  [10];  [30];  [31];  [32];  [33];  [14];  [7];  [34];  [35];  [33];  [36];  [29];  [14];  [15];  [19];  [10];  [37];  [10];  [38];  [39];  [39];  [2];  [40];  [41];  [14];  [14];  [42];  [30];  [43];  [44];  [45];  [14];  [46];  [47];  [12];  [10];  [6];  [14];  [48];  [49];  [50];  [25];  [14];  [51];  [52];  [53];  [48];  [45];  [22];  [14];  [41];  [25];  [54];  [14];  [10] « less
  1. Institut de Física d'Altes Energies (IFAE), The Barcelona Institute of Science and Technology, Campus UAB, E-08193 Bellaterra (Barcelona), Spain
  2. Kavli Institute for Particle Astrophysics and Cosmology, PO Box 2450, Stanford University, Stanford, CA 94305, USA
  3. Kavli Institute for Cosmological Physics, University of Chicago, Chicago, IL 60637, USA
  4. Universitäts-Sternwarte, Fakultät für Physik, Ludwig-Maximilians Universität München, Scheinerstr. 1, D-81679 München, Germany
  5. Kavli Institute for Particle Astrophysics and Cosmology, PO Box 2450, Stanford University, Stanford, CA 94305, USA; Department of Physics, Stanford University, 382 Via Pueblo Mall, Stanford, CA 94305, USA
  6. Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), E-28040 Madrid, Spain
  7. Institute of Space Sciences, IEEC-CSIC, Campus UAB, Carrer de Can Magrans, s/n, E-08193 Barcelona, Spain
  8. Department of Physics, University of Arizona, Tucson, AZ 85721, USA
  9. 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
  10. Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA 19104, USA
  11. Laboratório Interinstitucional de e-Astronomia -- LIneA, Rua Gal. José Cristino 77, 20921-400 Rio de Janeiro, RJ, Brazil; Observatório Nacional, Rua Gal. José Cristino 77, 20921-400 Rio de Janeiro, RJ, Brazil
  12. 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
  13. 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
  14. Fermi National Accelerator Laboratory, PO Box 500, Batavia, IL 60510, USA
  15. 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
  16. Kavli Institute for Particle Astrophysics and Cosmology, PO Box 2450, Stanford University, 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
  17. ARC Centre of Excellence for All-sky Astrophysics (CAASTRO); School of Mathematics and Physics, University of Queensland, Brisbane, QLD 4072, Australia
  18. Centre for Astrophysics and Supercomputing, Swinburne University of Technology, Victoria 3122, Australia
  19. School of Mathematics and Physics, University of Queensland, Brisbane, QLD 4072, Australia
  20. ARC Centre of Excellence for All-sky Astrophysics (CAASTRO); Sydney Institute for Astronomy, School of Physics A28, The University of Sydney, NSW 2006, Australia
  21. ARC Centre of Excellence for All-sky Astrophysics (CAASTRO); Australian Astronomical Observatory, North Ryde, NSW 2113, Australia
  22. ARC Centre of Excellence for All-sky Astrophysics (CAASTRO); The Research School of Astronomy and Astrophysics, Australian National University, ACT 2601, Australia
  23. ARC Centre of Excellence for All-sky Astrophysics (CAASTRO)
  24. ARC Centre of Excellence for All-sky Astrophysics (CAASTRO); Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing, Jiangshu 210008, China
  25. Cerro Tololo Inter-American Observatory, National Optical Astronomy Observatory, Casilla 603, La Serena, Chile
  26. LSST, 933 North Cherry Avenue, Tucson, AZ 85721, USA
  27. Department of Physics and Astronomy, University College London, Gower Street, London WC1E 6BT, UK
  28. ARC Centre of Excellence for All-sky Astrophysics (CAASTRO); INAF -- Osservatorio Astrofisico di Torino, via Osservatorio 20, I-10025 Pino Torinese, Italy
  29. 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
  30. George P. and Cynthia Woods Mitchell Institute for Fundamental Physics and Astronomy, and Department of Physics and Astronomy, Texas A&M University, College Station, TX 77843, USA
  31. Department of Physics, IIT Hyderabad, Kandi, Telangana 502285, India
  32. Department of Physics, California Institute of Technology, Pasadena, CA 91125, USA; Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr, Pasadena, CA 91109, USA
  33. Department of Astronomy, University of Michigan, Ann Arbor, MI 48109, USA; Department of Physics, University of Michigan, Ann Arbor, MI 48109, USA
  34. Kavli Institute for Cosmological Physics, University of Chicago, Chicago, IL 60637, USA; Fermi National Accelerator Laboratory, PO Box 500, Batavia, IL 60510, USA
  35. Instituto de Fisica Teorica UAM/CSIC, Universidad Autonoma de Madrid, E-28049 Madrid, Spain
  36. Department of Astronomy, University of California, Berkeley, 501 Campbell Hall, Berkeley, CA 94720, USA; Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
  37. Astronomy Department, University of Washington, Box 351580, Seattle, WA 98195, USA
  38. Santa Cruz Institute for Particle Physics, Santa Cruz, CA 95064, USA
  39. INAF -- Osservatorio Astrofisico di Torino, via Osservatorio 20, I-10025 Pino Torinese, Italy
  40. Australian Astronomical Observatory, North Ryde, NSW 2113, Australia
  41. Argonne National Laboratory, 9700 South Cass Avenue, Lemont, IL 60439, USA
  42. Laboratório Interinstitucional de e-Astronomia -- LIneA, Rua Gal. José Cristino 77, 20921-400 Rio de Janeiro, RJ, Brazil; Departamento de Física Matemática, Instituto de Física, Universidade de São Paulo, CP 66318, 05314-970 São Paulo, SP, Brazil
  43. Department of Astrophysical Sciences, Princeton University, Peyton Hall, Princeton, NJ 08544, USA
  44. INAF -- Osservatorio Astrofisico di Torino, via Osservatorio 20, I-10025 Pino Torinese, Italy; Department of Astronomy, University of Illinois, 1002 W. Green Street, Urbana, IL 61801, USA
  45. Institute of Cosmology and Gravitation, University of Portsmouth, Portsmouth PO1 3FX, UK
  46. Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr, Pasadena, CA 91109, USA
  47. SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA
  48. Department of Physics, University of Michigan, Ann Arbor, MI 48109, USA
  49. Brookhaven National Laboratory, Bldg 510, Upton, NY 11973, USA
  50. School of Physics and Astronomy, University of Southampton, Southampton SO17 1BJ, UK
  51. Laboratório Interinstitucional de e-Astronomia -- LIneA, Rua Gal. José Cristino 77, 20921-400 Rio de Janeiro, RJ, Brazil; Instituto de Física Gleb Wataghin, Universidade Estadual de Campinas, 13083-859 Campinas, SP, Brazil
  52. Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
  53. National Center for Supercomputing Applications, 1205 West Clark St, Urbana, IL 61801, USA
  54. Universitäts-Sternwarte, Fakultät für Physik, Ludwig-Maximilians Universität München, Scheinerstr. 1, D-81679 München, Germany; Excellence Cluster Universe, Boltzmannstr. 2, D-85748 Garching, Germany; Max Planck Institute for Extraterrestrial Physics, Giessenbachstrasse, D-85748 Garching, Germany
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Brookhaven National Lab. (BNL), Upton, NY (United States); SLAC National Accelerator Lab., Menlo Park, CA (United States); Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC), High Energy Physics (HEP); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
Contributing Org.:
DES Collaboration
OSTI Identifier:
1439283
Alternate Identifier(s):
OSTI ID: 1399673; OSTI ID: 1468040; OSTI ID: 1487083
Report Number(s):
FERMILAB-PUB-17-317-A-AE; arXiv:1709.00992; BNL-114383-2017-JA
Journal ID: ISSN 0035-8711; 1621443; TRN: US1900591
Grant/Contract Number:  
AC02-07CH11359; SC0012704; AC05-00OR22725; AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
Monthly Notices of the Royal Astronomical Society
Additional Journal Information:
Journal Volume: 477; Journal Issue: 2; Journal ID: ISSN 0035-8711
Publisher:
Royal Astronomical Society
Country of Publication:
United States
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS; galaxies: distances and redshifts; cosmology: observations

Citation Formats

Gatti, M., Vielzeuf, P., Davis, C., Cawthon, R., Rau, M. M., DeRose, J., De Vicente, J., Alarcon, A., Rozo, E., Gaztanaga, E., Hoyle, B., Miquel, R., Bernstein, G. M., Bonnett, C., Carnero Rosell, A., Castander, F. J., Chang, C., da Costa, L. N., Gruen, D., Gschwend, J., Hartley, W. G., Lin, H., MacCrann, N., Maia, M. A. G., Ogando, R. L. C., Roodman, A., Sevilla-Noarbe, I., Troxel, M. A., Wechsler, R. H., Asorey, J., Davis, T. M., Glazebrook, K., Hinton, S. R., Lewis, G., Lidman, C., Macaulay, E., Möller, A., O'Neill, C. R., Sommer, N. E., Uddin, S. A., Yuan, F., Zhang, B., Abbott, T. M. C., Allam, S., Annis, J., Bechtol, K., Brooks, D., Burke, D. L., Carollo, D., Carrasco Kind, M., Carretero, J., Cunha, C. E., D'Andrea, C. B., DePoy, D. L., Desai, S., Eifler, T. F., Evrard, A. E., Flaugher, B., Fosalba, P., Frieman, J., García-Bellido, J., Gerdes, D. W., Goldstein, D. A., Gruendl, R. A., Gutierrez, G., Honscheid, K., Hoormann, J. K., Jain, B., James, D. J., Jarvis, M., Jeltema, T., Johnson, M. W. G., Johnson, M. D., Krause, E., Kuehn, K., Kuhlmann, S., Kuropatkin, N., Li, T. S., Lima, M., Marshall, J. L., Melchior, P., Menanteau, F., Nichol, R. C., Nord, B., Plazas, A. A., Reil, K., Rykoff, E. S., Sako, M., Sanchez, E., Scarpine, V., Schubnell, M., Sheldon, E., Smith, M., Smith, R. C., Soares-Santos, M., Sobreira, F., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., Tucker, B. E., Tucker, D. L., Vikram, V., Walker, A. R., Weller, J., Wester, W., and Wolf, R. C.. Dark Energy Survey Year 1 results: cross-correlation redshifts – methods and systematics characterization. United States: N. p., 2018. Web. https://doi.org/10.1093/mnras/sty466.
Gatti, M., Vielzeuf, P., Davis, C., Cawthon, R., Rau, M. M., DeRose, J., De Vicente, J., Alarcon, A., Rozo, E., Gaztanaga, E., Hoyle, B., Miquel, R., Bernstein, G. M., Bonnett, C., Carnero Rosell, A., Castander, F. J., Chang, C., da Costa, L. N., Gruen, D., Gschwend, J., Hartley, W. G., Lin, H., MacCrann, N., Maia, M. A. G., Ogando, R. L. C., Roodman, A., Sevilla-Noarbe, I., Troxel, M. A., Wechsler, R. H., Asorey, J., Davis, T. M., Glazebrook, K., Hinton, S. R., Lewis, G., Lidman, C., Macaulay, E., Möller, A., O'Neill, C. R., Sommer, N. E., Uddin, S. A., Yuan, F., Zhang, B., Abbott, T. M. C., Allam, S., Annis, J., Bechtol, K., Brooks, D., Burke, D. L., Carollo, D., Carrasco Kind, M., Carretero, J., Cunha, C. E., D'Andrea, C. B., DePoy, D. L., Desai, S., Eifler, T. F., Evrard, A. E., Flaugher, B., Fosalba, P., Frieman, J., García-Bellido, J., Gerdes, D. W., Goldstein, D. A., Gruendl, R. A., Gutierrez, G., Honscheid, K., Hoormann, J. K., Jain, B., James, D. J., Jarvis, M., Jeltema, T., Johnson, M. W. G., Johnson, M. D., Krause, E., Kuehn, K., Kuhlmann, S., Kuropatkin, N., Li, T. S., Lima, M., Marshall, J. L., Melchior, P., Menanteau, F., Nichol, R. C., Nord, B., Plazas, A. A., Reil, K., Rykoff, E. S., Sako, M., Sanchez, E., Scarpine, V., Schubnell, M., Sheldon, E., Smith, M., Smith, R. C., Soares-Santos, M., Sobreira, F., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., Tucker, B. E., Tucker, D. L., Vikram, V., Walker, A. R., Weller, J., Wester, W., & Wolf, R. C.. Dark Energy Survey Year 1 results: cross-correlation redshifts – methods and systematics characterization. United States. https://doi.org/10.1093/mnras/sty466
Gatti, M., Vielzeuf, P., Davis, C., Cawthon, R., Rau, M. M., DeRose, J., De Vicente, J., Alarcon, A., Rozo, E., Gaztanaga, E., Hoyle, B., Miquel, R., Bernstein, G. M., Bonnett, C., Carnero Rosell, A., Castander, F. J., Chang, C., da Costa, L. N., Gruen, D., Gschwend, J., Hartley, W. G., Lin, H., MacCrann, N., Maia, M. A. G., Ogando, R. L. C., Roodman, A., Sevilla-Noarbe, I., Troxel, M. A., Wechsler, R. H., Asorey, J., Davis, T. M., Glazebrook, K., Hinton, S. R., Lewis, G., Lidman, C., Macaulay, E., Möller, A., O'Neill, C. R., Sommer, N. E., Uddin, S. A., Yuan, F., Zhang, B., Abbott, T. M. C., Allam, S., Annis, J., Bechtol, K., Brooks, D., Burke, D. L., Carollo, D., Carrasco Kind, M., Carretero, J., Cunha, C. E., D'Andrea, C. B., DePoy, D. L., Desai, S., Eifler, T. F., Evrard, A. E., Flaugher, B., Fosalba, P., Frieman, J., García-Bellido, J., Gerdes, D. W., Goldstein, D. A., Gruendl, R. A., Gutierrez, G., Honscheid, K., Hoormann, J. K., Jain, B., James, D. J., Jarvis, M., Jeltema, T., Johnson, M. W. G., Johnson, M. D., Krause, E., Kuehn, K., Kuhlmann, S., Kuropatkin, N., Li, T. S., Lima, M., Marshall, J. L., Melchior, P., Menanteau, F., Nichol, R. C., Nord, B., Plazas, A. A., Reil, K., Rykoff, E. S., Sako, M., Sanchez, E., Scarpine, V., Schubnell, M., Sheldon, E., Smith, M., Smith, R. C., Soares-Santos, M., Sobreira, F., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., Tucker, B. E., Tucker, D. L., Vikram, V., Walker, A. R., Weller, J., Wester, W., and Wolf, R. C.. Thu . "Dark Energy Survey Year 1 results: cross-correlation redshifts – methods and systematics characterization". United States. https://doi.org/10.1093/mnras/sty466. https://www.osti.gov/servlets/purl/1439283.
@article{osti_1439283,
title = {Dark Energy Survey Year 1 results: cross-correlation redshifts – methods and systematics characterization},
author = {Gatti, M. and Vielzeuf, P. and Davis, C. and Cawthon, R. and Rau, M. M. and DeRose, J. and De Vicente, J. and Alarcon, A. and Rozo, E. and Gaztanaga, E. and Hoyle, B. and Miquel, R. and Bernstein, G. M. and Bonnett, C. and Carnero Rosell, A. and Castander, F. J. and Chang, C. and da Costa, L. N. and Gruen, D. and Gschwend, J. and Hartley, W. G. and Lin, H. and MacCrann, N. and Maia, M. A. G. and Ogando, R. L. C. and Roodman, A. and Sevilla-Noarbe, I. and Troxel, M. A. and Wechsler, R. H. and Asorey, J. and Davis, T. M. and Glazebrook, K. and Hinton, S. R. and Lewis, G. and Lidman, C. and Macaulay, E. and Möller, A. and O'Neill, C. R. and Sommer, N. E. and Uddin, S. A. and Yuan, F. and Zhang, B. and Abbott, T. M. C. and Allam, S. and Annis, J. and Bechtol, K. and Brooks, D. and Burke, D. L. and Carollo, D. and Carrasco Kind, M. and Carretero, J. and Cunha, C. E. and D'Andrea, C. B. and DePoy, D. L. and Desai, S. and Eifler, T. F. and Evrard, A. E. and Flaugher, B. and Fosalba, P. and Frieman, J. and García-Bellido, J. and Gerdes, D. W. and Goldstein, D. A. and Gruendl, R. A. and Gutierrez, G. and Honscheid, K. and Hoormann, J. K. and Jain, B. and James, D. J. and Jarvis, M. and Jeltema, T. and Johnson, M. W. G. and Johnson, M. D. and Krause, E. and Kuehn, K. and Kuhlmann, S. and Kuropatkin, N. and Li, T. S. and Lima, M. and Marshall, J. L. and Melchior, P. and Menanteau, F. and Nichol, R. C. and Nord, B. and Plazas, A. A. and Reil, K. and Rykoff, E. S. and Sako, M. and Sanchez, E. and Scarpine, V. and Schubnell, M. and Sheldon, E. and Smith, M. and Smith, R. C. and Soares-Santos, M. and Sobreira, F. and Suchyta, E. and Swanson, M. E. C. and Tarle, G. and Thomas, D. and Tucker, B. E. and Tucker, D. L. and Vikram, V. and Walker, A. R. and Weller, J. and Wester, W. and Wolf, R. C.},
abstractNote = {We use numerical simulations to characterize the performance of a clustering-based method to calibrate photometric redshift biases. In particular, we cross-correlate the weak lensing source galaxies from the Dark Energy Survey Year 1 sample with redMaGiC galaxies (luminous red galaxies with secure photometric redshifts) to estimate the redshift distribution of the former sample. The recovered redshift distributions are used to calibrate the photometric redshift bias of standard photo-z methods applied to the same source galaxy sample. We apply the method to two photo-z codes run in our simulated data: Bayesian Photometric Redshift and Directional Neighbourhood Fitting. We characterize the systematic uncertainties of our calibration procedure, and find that these systematic uncertainties dominate our error budget. The dominant systematics are due to our assumption of unevolving bias and clustering across each redshift bin, and to differences between the shapes of the redshift distributions derived by clustering versus photo-zs. The systematic uncertainty in the mean redshift bias of the source galaxy sample is Δz ≲ 0.02, though the precise value depends on the redshift bin under consideration. We discuss possible ways to mitigate the impact of our dominant systematics in future analyses.},
doi = {10.1093/mnras/sty466},
journal = {Monthly Notices of the Royal Astronomical Society},
number = 2,
volume = 477,
place = {United States},
year = {2018},
month = {2}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Citation Metrics:
Cited by: 14 works
Citation information provided by
Web of Science

Figures / Tables:

Figure 1 Figure 1: True redshift distributions for the simulated weak lensing source samples obtained binning with different photo-z codes, as described in §3.2. The redshift distributions are normalized to unity over the full redshift interval.

Save / Share:

Works referenced in this record:

The Overdensities of Galaxy Environments as a Function of Luminosity and Color
journal, March 2003

  • Hogg, David W.; Blanton, Michael R.; Eisenstein, Daniel J.
  • The Astrophysical Journal, Vol. 585, Issue 1
  • DOI: 10.1086/374238

Detection of Cosmic Magnification with the Sloan Digital Sky Survey
journal, November 2005

  • Scranton, Ryan; Menard, Brice; Richards, Gordon T.
  • The Astrophysical Journal, Vol. 633, Issue 2
  • DOI: 10.1086/431358

Calibrating Redshift Distributions beyond Spectroscopic Limits with Cross‐Correlations
journal, September 2008

  • Newman, Jeffrey A.
  • The Astrophysical Journal, Vol. 684, Issue 1
  • DOI: 10.1086/589982

The VIMOS Public Extragalactic Redshift Survey (VIPERS): Luminosity and stellar mass dependence of galaxy clustering at 0.5 <
journal, August 2013


The Prism Multi-Object Survey (Primus). i. Survey Overview and Characteristics
journal, October 2011

  • Coil, Alison L.; Blanton, Michael R.; Burles, Scott M.
  • The Astrophysical Journal, Vol. 741, Issue 1
  • DOI: 10.1088/0004-637X/741/1/8

On using angular cross-correlations to determine source redshift distributions
journal, July 2013

  • McQuinn, M.; White, M.
  • Monthly Notices of the Royal Astronomical Society, Vol. 433, Issue 4
  • DOI: 10.1093/mnras/stt914

Scale-dependent galaxy bias in the Sloan Digital Sky Survey as a function of luminosity and colour
journal, January 2009


Testing the accuracy of clustering redshifts with simulations
journal, November 2017

  • Scottez, V.; Benoit-Lévy, A.; Coupon, J.
  • Monthly Notices of the Royal Astronomical Society, Vol. 474, Issue 3
  • DOI: 10.1093/mnras/stx3056

PHAT: PHoto- z Accuracy Testing
journal, November 2010


Tomographic magnification of Lyman-break galaxies in the Deep Lens Survey: Tomographic magnification
journal, October 2012


Clustering-based redshift estimation: comparison to spectroscopic redshifts
journal, January 2015

  • Rahman, Mubdi; Ménard, Brice; Scranton, Ryan
  • Monthly Notices of the Royal Astronomical Society, Vol. 447, Issue 4
  • DOI: 10.1093/mnras/stu2636

A bias in cosmic shear from galaxy selection: results from ray-tracing simulations
journal, February 2011


CFHTLenS and RCSLenS: testing photometric redshift distributions using angular cross-correlations with spectroscopic galaxy surveys
journal, September 2016

  • Choi, A.; Heymans, C.; Blake, C.
  • Monthly Notices of the Royal Astronomical Society, Vol. 463, Issue 4
  • DOI: 10.1093/mnras/stw2241

redMaPPer. I. ALGORITHM AND SDSS DR8 CATALOG
journal, April 2014


Reconstructing Redshift Distributions with Cross-Correlations: Tests and an Optimized Recipe
journal, August 2010


The Eleventh and Twelfth data Releases of the Sloan Digital sky Survey: Final data from Sdss-Iii
journal, July 2015

  • Alam, Shadab; Albareti, Franco D.; Prieto, Carlos Allende
  • The Astrophysical Journal Supplement Series, Vol. 219, Issue 1
  • DOI: 10.1088/0067-0049/219/1/12

Lensing corrections to features in the angular two-point correlation function and power spectrum
journal, January 2008


emcee : The MCMC Hammer
journal, March 2013

  • Foreman-Mackey, Daniel; Hogg, David W.; Lang, Dustin
  • Publications of the Astronomical Society of the Pacific, Vol. 125, Issue 925
  • DOI: 10.1086/670067

Template Ultraviolet to Near-Infrared Spectra of Star-forming Galaxies and Their Application to K-Corrections
journal, August 1996

  • Kinney, Anne L.; Calzetti, Daniela; Bohlin, Ralph C.
  • The Astrophysical Journal, Vol. 467
  • DOI: 10.1086/177583

The cosmological simulation code gadget-2
journal, December 2005


Galaxy And Mass Assembly (GAMA): end of survey report and data release 2
journal, July 2015

  • Liske, J.; Baldry, I. K.; Driver, S. P.
  • Monthly Notices of the Royal Astronomical Society, Vol. 452, Issue 2
  • DOI: 10.1093/mnras/stv1436

The Deep2 Galaxy Redshift Survey: Design, Observations, data Reduction, and Redshifts
journal, August 2013

  • Newman, Jeffrey A.; Cooper, Michael C.; Davis, Marc
  • The Astrophysical Journal Supplement Series, Vol. 208, Issue 1
  • DOI: 10.1088/0067-0049/208/1/5

Anisotropic magnification distortion of the 3D galaxy correlation. I. Real space
journal, November 2007


Spectroscopic needs for imaging dark energy experiments
journal, March 2015


The first and second data releases of the Kilo-Degree Survey
journal, October 2015

  • de Jong, Jelte T. A.; Verdoes Kleijn, Gijs A.; Boxhoorn, Danny R.
  • Astronomy & Astrophysics, Vol. 582
  • DOI: 10.1051/0004-6361/201526601

Photometric redshift analysis in the Dark Energy Survey Science Verification data
journal, October 2014

  • Sánchez, C.; Carrasco Kind, M.; Lin, H.
  • Monthly Notices of the Royal Astronomical Society, Vol. 445, Issue 2
  • DOI: 10.1093/mnras/stu1836

Clustering-based redshift estimation: application to VIPERS/CFHTLS
journal, July 2016

  • Scottez, V.; Mellier, Y.; Granett, B. R.
  • Monthly Notices of the Royal Astronomical Society, Vol. 462, Issue 2
  • DOI: 10.1093/mnras/stw1500

calclens: weak lensing simulations for large-area sky surveys and second-order effects in cosmic shear power spectra
journal, August 2013

  • Becker, Matthew R.
  • Monthly Notices of the Royal Astronomical Society, Vol. 435, Issue 1
  • DOI: 10.1093/mnras/stt1352

Weighing the Giants – III. Methods and measurements of accurate galaxy cluster weak-lensing masses
journal, February 2014

  • Applegate, Douglas E.; von der Linden, Anja; Kelly, Patrick L.
  • Monthly Notices of the Royal Astronomical Society, Vol. 439, Issue 1
  • DOI: 10.1093/mnras/stt2129

Leveraging 3d-Hst Grism Redshifts to Quantify Photometric Redshift Performance
journal, May 2016

  • Bezanson, Rachel; Wake, David A.; Brammer, Gabriel B.
  • The Astrophysical Journal, Vol. 822, Issue 1
  • DOI: 10.3847/0004-637X/822/1/30

THE COSMOS2015 CATALOG: EXPLORING THE 1 < z < 6 UNIVERSE WITH HALF A MILLION GALAXIES
journal, June 2016

  • Laigle, C.; McCracken, H. J.; Ilbert, O.
  • The Astrophysical Journal Supplement Series, Vol. 224, Issue 2
  • DOI: 10.3847/0067-0049/224/2/24

THE zCOSMOS 10k-BRIGHT SPECTROSCOPIC SAMPLE
journal, September 2009

  • Lilly, Simon J.; Le Brun, Vincent; Maier, Christian
  • The Astrophysical Journal Supplement Series, Vol. 184, Issue 2
  • DOI: 10.1088/0067-0049/184/2/218

Gravitational lensing and quasar-galaxy correlations
journal, April 1989

  • Narayan, Ramesh
  • The Astrophysical Journal, Vol. 339
  • DOI: 10.1086/185418

The Scale Dependence of Relative Galaxy Bias: Encouragement for the “Halo Model” Description
journal, July 2006

  • Blanton, Michael R.; Eisenstein, Daniel; Hogg, David W.
  • The Astrophysical Journal, Vol. 645, Issue 2
  • DOI: 10.1086/500918

Scale dependence of halo and galaxy bias: Effects in real space
journal, March 2007


TPZ: photometric redshift PDFs and ancillary information by using prediction trees and random forests
journal, May 2013

  • Carrasco Kind, Matias; Brunner, Robert J.
  • Monthly Notices of the Royal Astronomical Society, Vol. 432, Issue 2
  • DOI: 10.1093/mnras/stt574

Estimating the redshift distribution of photometric galaxy samples
journal, October 2008


The Complete Calibration of the Color–Redshift Relation (C3R2) Survey: Survey Overview and Data Release 1
journal, May 2017

  • Masters, Daniel C.; Stern, Daniel K.; Cohen, Judith G.
  • The Astrophysical Journal, Vol. 841, Issue 2
  • DOI: 10.3847/1538-4357/aa6f08

Background sky obscuration by cluster galaxies as a source of systematic error for weak lensing
journal, March 2015

  • Simet, Melanie; Mandelbaum, Rachel
  • Monthly Notices of the Royal Astronomical Society, Vol. 449, Issue 2
  • DOI: 10.1093/mnras/stv313

Accurate photometric redshift probability density estimation – method comparison and application
journal, August 2015

  • Rau, Markus Michael; Seitz, Stella; Brimioulle, Fabrice
  • Monthly Notices of the Royal Astronomical Society, Vol. 452, Issue 4
  • DOI: 10.1093/mnras/stv1567

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
  • DOI: 10.1093/mnras/stt410

Size Bias in Galaxy Surveys
journal, July 2009


Galaxy Clustering in Early Sloan Digital Sky Survey Redshift Data
journal, May 2002

  • Zehavi, Idit; Blanton, Michael R.; Frieman, Joshua A.
  • The Astrophysical Journal, Vol. 571, Issue 1
  • DOI: 10.1086/339893

Galaxies in the Hubble Ultra Deep Field. I. Detection, Multiband Photometry, Photometric Redshifts, and Morphology
journal, July 2006

  • Coe, Dan; Benítez, Narciso; Sánchez, Sebastián F.
  • The Astronomical Journal, Vol. 132, Issue 2
  • DOI: 10.1086/505530

Bayesian Photometric Redshift Estimation
journal, June 2000

  • Benitez, Narciso
  • The Astrophysical Journal, Vol. 536, Issue 2
  • DOI: 10.1086/308947

Using Galaxy Two‐Point Correlation Functions to Determine the Redshift Distributions of Galaxies Binned by Photometric Redshift
journal, November 2006

  • Schneider, Michael; Knox, Lloyd; Zhan, Hu
  • The Astrophysical Journal, Vol. 651, Issue 1
  • DOI: 10.1086/507675

Angular cross-correlation of galaxies: a probe of gravitational lensing by large-scale structure
journal, February 1998


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
  • DOI: 10.1093/mnras/stw3033

The Deep3 Galaxy Redshift Survey: Keck/Deimos Spectroscopy in the Goods-N Field
journal, March 2011

  • Cooper, Michael C.; Aird, James A.; Coil, Alison L.
  • The Astrophysical Journal Supplement Series, Vol. 193, Issue 1
  • DOI: 10.1088/0067-0049/193/1/14

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

  • Davis, M.; Peebles, P. J. E.
  • The Astrophysical Journal, Vol. 267
  • DOI: 10.1086/160884

The Rockstar Phase-Space Temporal halo Finder and the Velocity Offsets of Cluster Cores
journal, December 2012


the-wizz: clustering redshift estimation for everyone
journal, February 2017

  • Morrison, C. B.; Hildebrandt, H.; Schmidt, S. J.
  • Monthly Notices of the Royal Astronomical Society, Vol. 467, Issue 3
  • DOI: 10.1093/mnras/stx342

Statistical analysis of galaxy surveys - I. Robust error estimation for two-point clustering statistics
journal, June 2009


Estimating the redshift distribution of photometric galaxy samples - II. Applications and tests of a new method
journal, July 2009


Weak gravitational lensing
journal, January 2001


DNF – Galaxy photometric redshift by Directional Neighbourhood Fitting
journal, April 2016

  • De Vicente, J.; Sánchez, E.; Sevilla-Noarbe, I.
  • Monthly Notices of the Royal Astronomical Society, Vol. 459, Issue 3
  • DOI: 10.1093/mnras/stw857

On the complementarity of galaxy clustering with cosmic shear and flux magnification
journal, November 2013

  • Duncan, Christopher A. J.; Joachimi, Benjamin; Heavens, Alan F.
  • Monthly Notices of the Royal Astronomical Society, Vol. 437, Issue 3
  • DOI: 10.1093/mnras/stt2060

KiDS-450: cosmological parameter constraints from tomographic weak gravitational lensing
journal, November 2016

  • Hildebrandt, H.; Viola, M.; Heymans, C.
  • Monthly Notices of the Royal Astronomical Society, Vol. 465, Issue 2
  • DOI: 10.1093/mnras/stw2805

Inference from the small scales of cosmic shear with current and future Dark Energy Survey data
journal, November 2016

  • MacCrann, N.; Aleksić, J.; Amara, A.
  • Monthly Notices of the Royal Astronomical Society, Vol. 465, Issue 3
  • DOI: 10.1093/mnras/stw2849

Mitigating systematic errors in angular correlation function measurements from wide field surveys
journal, October 2015

  • Morrison, C. B.; Hildebrandt, H.
  • Monthly Notices of the Royal Astronomical Society, Vol. 454, Issue 3
  • DOI: 10.1093/mnras/stv2103

Colors and magnitudes predicted for high redshift galaxies
journal, July 1980

  • Coleman, G. D.; Wu, C. -C.; Weedman, D. W.
  • The Astrophysical Journal Supplement Series, Vol. 43
  • DOI: 10.1086/190674

Clustering of Galaxies in the Hubble Deep Field
journal, June 1997

  • Villumsen, Jens V.; Freudling, Wolfram; da Costa, Luiz N.
  • The Astrophysical Journal, Vol. 481, Issue 2
  • DOI: 10.1086/304072

Bias and variance of angular correlation functions
journal, July 1993

  • Landy, Stephen D.; Szalay, Alexander S.
  • The Astrophysical Journal, Vol. 412
  • DOI: 10.1086/172900

PRIMUS: GALAXY CLUSTERING AS A FUNCTION OF LUMINOSITY AND COLOR AT 0.2 < z < 1
journal, March 2014

  • Skibba, Ramin A.; Smith, M. Stephen M.; Coil, Alison L.
  • The Astrophysical Journal, Vol. 784, Issue 2
  • DOI: 10.1088/0004-637X/784/2/128

Why your model parameter confidences might be too optimistic. Unbiased estimation of the inverse covariance matrix
journal, December 2006


The DEEP2 Galaxy Redshift Survey: Clustering of Galaxies as a Function of Luminosity at z = 1
journal, June 2006

  • Coil, Alison L.; Newman, Jeffrey A.; Cooper, Michael C.
  • The Astrophysical Journal, Vol. 644, Issue 2
  • DOI: 10.1086/503601

Random Forests
journal, January 2001


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

  • Rozo, E.; Rykoff, E. S.; Abate, A.
  • Monthly Notices of the Royal Astronomical Society, Vol. 461, Issue 2
  • DOI: 10.1093/mnras/stw1281

The VIMOS Public Extragalactic Redshift Survey (VIPERS): Measuring non-linear galaxy bias at z ~ 0.8 ⋆
journal, October 2016


miRNALoc: predicting miRNA subcellular localizations based on principal component scores of physico-chemical properties and pseudo compositions of di-nucleotides
journal, September 2020

  • Meher, Prabina Kumar; Satpathy, Subhrajit; Rao, Atmakuri Ramakrishna
  • Scientific Reports, Vol. 10, Issue 1
  • DOI: 10.1038/s41598-020-71381-4

Weak gravitational lensing
journal, January 2017


    Works referencing / citing this record:

    Dark Energy Survey Year 1 Results: A Precise H0 Estimate from DES Y1, BAO, and D/H Data
    journal, July 2018

    • Abbott, T. M. C.; Abdalla, F. B.; Annis, J.
    • Monthly Notices of the Royal Astronomical Society, Vol. 480, Issue 3
    • DOI: 10.1093/mnras/sty1939

    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.
    • Monthly Notices of the Royal Astronomical Society, Vol. 481, Issue 2
    • DOI: 10.1093/mnras/sty2424

    Dark Energy Survey Year 1 results: weak lensing mass calibration of redMaPPer galaxy clusters
    journal, October 2018

    • McClintock, T.; Varga, T. N.; Gruen, D.
    • Monthly Notices of the Royal Astronomical Society, Vol. 482, Issue 1
    • DOI: 10.1093/mnras/sty2711

    H  i intensity mapping for clustering-based redshift estimation
    journal, October 2018

    • Cunnington, Steven; Harrison, Ian; Pourtsidou, Alkistis
    • Monthly Notices of the Royal Astronomical Society, Vol. 482, Issue 3
    • DOI: 10.1093/mnras/sty2928

    Redshift inference from the combination of galaxy colours and clustering in a hierarchical Bayesian model
    journal, November 2018

    • Sánchez, Carles; Bernstein, Gary M.
    • Monthly Notices of the Royal Astronomical Society, Vol. 483, Issue 2
    • DOI: 10.1093/mnras/sty3222

    Dark Energy Survey Year 1 Results: redshift distributions of the weak-lensing source galaxies
    journal, April 2018

    • Hoyle, B.; Gruen, D.; Bernstein, G. M.
    • Monthly Notices of the Royal Astronomical Society, Vol. 478, Issue 1
    • DOI: 10.1093/mnras/sty957

    Cosmological lensing ratios with DES Y1, SPT, and Planck
    journal, May 2019

    • Prat, J.; Baxter, E.; Shin, T.
    • Monthly Notices of the Royal Astronomical Society, Vol. 487, Issue 1
    • DOI: 10.1093/mnras/stz1309

    Dark Energy Survey Year 1 results: measurement of the galaxy angular power spectrum
    journal, June 2019

    • Camacho, H.; Kokron, N.; Andrade-Oliveira, F.
    • Monthly Notices of the Royal Astronomical Society, Vol. 487, Issue 3
    • DOI: 10.1093/mnras/stz1514

    Phenotypic redshifts with self-organizing maps: A novel method to characterize redshift distributions of source galaxies for weak lensing
    journal, August 2019

    • Buchs, R.; Davis, C.; Gruen, D.
    • Monthly Notices of the Royal Astronomical Society, Vol. 489, Issue 1
    • DOI: 10.1093/mnras/stz2162

    Dark Energy Survey Year 1 results: constraints on intrinsic alignments and their colour dependence from galaxy clustering and weak lensing
    journal, August 2019

    • Samuroff, S.; Blazek, J.; Troxel, M. A.
    • Monthly Notices of the Royal Astronomical Society, Vol. 489, Issue 4
    • DOI: 10.1093/mnras/stz2197

    Producing a BOSS CMASS sample with DES imaging
    journal, September 2019

    • Lee, S.; Huff, E. M.; Ross, A. J.
    • Monthly Notices of the Royal Astronomical Society, Vol. 489, Issue 2
    • DOI: 10.1093/mnras/stz2288

    corrfunc – a suite of blazing fast correlation functions on the CPU
    journal, November 2019

    • Sinha, Manodeep; Garrison, Lehman H.
    • Monthly Notices of the Royal Astronomical Society, Vol. 491, Issue 2
    • DOI: 10.1093/mnras/stz3157

    Optimizing galaxy samples for clustering measurements in photometric surveys
    journal, November 2019

    • Tanoglidis, Dimitrios; Chang, Chihway; Frieman, Joshua
    • Monthly Notices of the Royal Astronomical Society, Vol. 491, Issue 3
    • DOI: 10.1093/mnras/stz3281

    Estimating redshift distributions using hierarchical logistic Gaussian processes
    journal, November 2019

    • Rau, Markus Michael; Wilson, Simon; Mandelbaum, Rachel
    • Monthly Notices of the Royal Astronomical Society, Vol. 491, Issue 4
    • DOI: 10.1093/mnras/stz3295

    Self-consistent redshift estimation using correlation functions without a spectroscopic reference sample
    journal, February 2019

    • Hoyle, Ben; Rau, Markus Michael
    • Monthly Notices of the Royal Astronomical Society, Vol. 485, Issue 3
    • DOI: 10.1093/mnras/stz502

    Mass functions, luminosity functions, and completeness measurements from clustering redshifts
    journal, April 2019

    • Bates, Dominic J.; Tojeiro, Rita; Newman, Jeffrey A.
    • Monthly Notices of the Royal Astronomical Society, Vol. 486, Issue 3
    • DOI: 10.1093/mnras/stz997

    Density split statistics: Cosmological constraints from counts and lensing in cells in DES Y1 and SDSS data
    journal, July 2018


    Dark Energy Survey year 1 results: Galaxy-galaxy lensing
    journal, August 2018


    Dark Energy Survey year 1 results: Cosmological constraints from galaxy clustering and weak lensing
    journal, August 2018


    Dark Energy Survey Year 1 results: Cosmological constraints from cosmic shear
    journal, August 2018


    Dark Energy Survey year 1 results: Constraints on extended cosmological models from galaxy clustering and weak lensing
    journal, June 2019


    Cosmological Constraints from Multiple Probes in the Dark Energy Survey
    journal, May 2019