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Title: Cross-correlation redshift calibration without spectroscopic calibration samples in DES Science Verification Data

Abstract

Galaxy cross-correlations with high-fidelity redshift samples hold the potential to precisely calibrate systematic photometric redshift uncertainties arising from the unavailability of complete and representative training and validation samples of galaxies. However, application of this technique in the Dark Energy Survey (DES) is hampered by the relatively low number density, small area, and modest redshift overlap between photometric and spectroscopic samples. We propose instead using photometric catalogs with reliable photometric redshifts for photo-z calibration via cross-correlations. We verify the viability of our proposal using redMaPPer clusters from the Sloan Digital Sky Survey (SDSS) to successfully recover the redshift distribution of SDSS spectroscopic galaxies. We demonstrate how to combine photo-z with cross-correlation data to calibrate photometric redshift biases while marginalizing over possible clustering bias evolution in either the calibration or unknown photometric samples. We apply our method to DES Science Verification (DES SV) data in order to constrain the photometric redshift distribution of a galaxy sample selected for weak lensing studies, constraining the mean of the tomographic redshift distributions to a statistical uncertainty of $$\Delta z \sim \pm 0.01$$. We forecast that our proposal can in principle control photometric redshift uncertainties in DES weak lensing experiments at a level near the intrinsic statistical noise of the experiment over the range of redshifts where redMaPPer clusters are available. Here, our results provide strong motivation to launch a program to fully characterize the systematic errors from bias evolution and photo-z shapes in our calibration procedure.

Authors:
ORCiD logo [1];  [2];  [3];  [4];  [5];  [6];  [7];  [8];  [3];  [9];  [6];  [10];  [11];  [7];  [7];  [12];  [13];  [14];  [15];  [7] more »;  [3];  [16];  [17];  [6];  [4];  [4];  [1];  [18];  [16];  [19];  [7];  [15];  [7];  [20];  [7];  [4];  [21];  [22];  [4];  [23];  [24];  [3];  [17];  [7];  [9];  [18];  [25];  [26];  [1];  [27];  [28];  [7];  [15];  [7];  [29];  [18];  [30];  [31];  [32];  [16];  [33];  [34];  [35];  [7];  [36];  [37];  [35];  [38];  [7];  [39];  [40];  [41];  [37];  [42];  [28];  [10];  [43] « less
  1. Kavli Institute for Particle Astrophysics and Cosmology, PO Box 2450, Stanford University, Stanford, CA 94305, USA
  2. Department of Physics, University of Arizona, Tucson, AZ 85721, USA
  3. 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
  4. Institute of Space Sciences, IEEC-CSIC, Campus UAB, Carrer de Can Magrans, s/n, E-08193 Barcelona, Spain
  5. Kavli Institute for Cosmological Physics, University of Chicago, Chicago, IL 60637, USA
  6. Institut de Física d'Altes Energies (IFAE), The Barcelona Institute of Science and Technology, Campus UAB, E-08193 Bellaterra (Barcelona), Spain
  7. Fermi National Accelerator Laboratory, PO Box 500, Batavia, IL 60510, USA
  8. 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
  9. 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
  10. Cerro Tololo Inter-American Observatory, National Optical Astronomy Observatory, Casilla 603, La Serena, Chile
  11. 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
  12. LSST, 933 North Cherry Avenue, Tucson, AZ 85721, USA
  13. 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; Sorbonne Universités, UPMC Univ Paris 06, UMR 7095, Institut d'Astrophysique de Paris, F-75014 Paris, France
  14. CNRS, UMR 7095, Institut d'Astrophysique de Paris, F-75014 Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR 7095, Institut d'Astrophysique de Paris, F-75014 Paris, France
  15. Department of Physics and Astronomy, University College London, Gower Street, London WC1E 6BT, UK
  16. 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
  17. 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
  18. Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA 19104, USA
  19. Department of Physics, IIT Hyderabad, Kandi, Telangana 502285, India
  20. Laboratório Interinstitucional de e-Astronomia - LIneA, Rua Gal. José Cristino 77, Rio de Janeiro RJ-20921-400, Brazil
  21. Kavli Institute for Cosmological Physics, University of Chicago, Chicago, IL 60637, USA; Fermi National Accelerator Laboratory, PO Box 500, Batavia, IL 60510, USA
  22. Instituto de Fisica Teorica UAM/CSIC, Universidad Autonoma de Madrid, E-28049 Madrid, Spain
  23. Department of Astronomy, University of Michigan, Ann Arbor, MI 48109, USA; Department of Physics, University of Michigan, Ann Arbor, MI 48109, USA
  24. Institute of Astronomy, University of Cambridge, Madingley Road, Cambridge CB3 0HA, UK; Kavli Institute for Cosmology, University of Cambridge, Madingley Road, Cambridge CB3 0HA, UK; Universitäts-Sternwarte, Fakultät für Physik, Ludwig-Maximilians Universität München, Scheinerstr. 1, D-81679 München, Germany
  25. Astronomy Department, University of Washington, Box 351580, Seattle, WA 98195, USA; Cerro Tololo Inter-American Observatory, National Optical Astronomy Observatory, Casilla 603, La Serena, Chile
  26. Santa Cruz Institute for Particle Physics, Santa Cruz, CA 95064, USA
  27. Australian Astronomical Observatory, North Ryde, NSW 2113, Australia
  28. Argonne National Laboratory, 9700 South Cass Avenue, Lemont, IL 60439, USA
  29. 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
  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. 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
  32. Department of Astrophysical Sciences, Princeton University, Peyton Hall, Princeton, NJ 08544, USA
  33. Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA 91109, USA
  34. Department of Physics and Astronomy, Pevensey Building, University of Sussex, Brighton BN1 9QH, UK
  35. Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Av. Complutense 40, 28040 Madrid, Spain
  36. SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA
  37. Department of Physics, University of Michigan, Ann Arbor, MI 48109, USA
  38. School of Physics and Astronomy, University of Southampton, Southampton SO17 1BJ, UK
  39. Instituto de Física Gleb Wataghin, Universidade Estadual de Campinas, 13083-859 Campinas, SP, Brazil; Laboratório Interinstitucional de e-Astronomia - LIneA, Rua Gal. José Cristino 77, Rio de Janeiro RJ-20921-400, Brazil
  40. Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
  41. National Center for Supercomputing Applications, 1205 West Clark St., Urbana, IL 61801, USA
  42. Institute of Cosmology and Gravitation, University of Portsmouth, Portsmouth PO1 3FX, UK
  43. 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; Department of Physics, Stanford University, 382 Via Pueblo Mall, Stanford, CA 94305, USA
Publication Date:
Research Org.:
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:
1454415
Alternate Identifier(s):
OSTI ID: 1468041
Report Number(s):
FERMILAB-PUB-17-284-AE; arXiv:1707.08256
Journal ID: ISSN 0035-8711; 1611648; TRN: US1901011
Grant/Contract Number:  
AC02-07CH11359; AC05-00OR22725
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: clusters: general; galaxies: distances and redshifts

Citation Formats

Davis, C., Rozo, E., Roodman, A., Alarcon, A., Cawthon, R., Gatti, M., Lin, H., Miquel, R., Rykoff, E. S., Troxel, M. A., Vielzeuf, P., Abbott, T. M. C., Abdalla, F. B., Allam, S., Annis, J., Bechtol, K., Benoit-Lévy, A., Bertin, E., Brooks, D., Buckley-Geer, E., Burke, D. L., Carnero Rosell, A., Carrasco Kind, M., Carretero, J., Castander, F. J., Crocce, M., Cunha, C. E., D'Andrea, C. B., da Costa, L. N., Desai, S., Diehl, H. T., Doel, P., Drlica-Wagner, A., Neto, A. Fausti, Flaugher, B., Fosalba, P., Frieman, J., García-Bellido, J., Gaztanaga, E., Gerdes, D. W., Giannantonio, T., Gruen, D., Gruendl, R. A., Gutierrez, G., Honscheid, K., Jain, B., James, D. J., Jeltema, T., Krause, E., Kuehn, K., Kuhlmann, S., Kuropatkin, N., Lahav, O., Li, T. S., Lima, M., March, M., Marshall, J. L., Martini, P., Melchior, P., Ogando, R. L. C., Plazas, A. A., Romer, A. K., Sanchez, E., Scarpine, V., Schindler, R., Schubnell, M., Sevilla-Noarbe, I., Smith, M., Soares-Santos, M., Sobreira, F., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., Vikram, V., Walker, A. R., and Wechsler, R. H. Cross-correlation redshift calibration without spectroscopic calibration samples in DES Science Verification Data. United States: N. p., 2018. Web. https://doi.org/10.1093/mnras/sty787.
Davis, C., Rozo, E., Roodman, A., Alarcon, A., Cawthon, R., Gatti, M., Lin, H., Miquel, R., Rykoff, E. S., Troxel, M. A., Vielzeuf, P., Abbott, T. M. C., Abdalla, F. B., Allam, S., Annis, J., Bechtol, K., Benoit-Lévy, A., Bertin, E., Brooks, D., Buckley-Geer, E., Burke, D. L., Carnero Rosell, A., Carrasco Kind, M., Carretero, J., Castander, F. J., Crocce, M., Cunha, C. E., D'Andrea, C. B., da Costa, L. N., Desai, S., Diehl, H. T., Doel, P., Drlica-Wagner, A., Neto, A. Fausti, Flaugher, B., Fosalba, P., Frieman, J., García-Bellido, J., Gaztanaga, E., Gerdes, D. W., Giannantonio, T., Gruen, D., Gruendl, R. A., Gutierrez, G., Honscheid, K., Jain, B., James, D. J., Jeltema, T., Krause, E., Kuehn, K., Kuhlmann, S., Kuropatkin, N., Lahav, O., Li, T. S., Lima, M., March, M., Marshall, J. L., Martini, P., Melchior, P., Ogando, R. L. C., Plazas, A. A., Romer, A. K., Sanchez, E., Scarpine, V., Schindler, R., Schubnell, M., Sevilla-Noarbe, I., Smith, M., Soares-Santos, M., Sobreira, F., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., Vikram, V., Walker, A. R., & Wechsler, R. H. Cross-correlation redshift calibration without spectroscopic calibration samples in DES Science Verification Data. United States. https://doi.org/10.1093/mnras/sty787
Davis, C., Rozo, E., Roodman, A., Alarcon, A., Cawthon, R., Gatti, M., Lin, H., Miquel, R., Rykoff, E. S., Troxel, M. A., Vielzeuf, P., Abbott, T. M. C., Abdalla, F. B., Allam, S., Annis, J., Bechtol, K., Benoit-Lévy, A., Bertin, E., Brooks, D., Buckley-Geer, E., Burke, D. L., Carnero Rosell, A., Carrasco Kind, M., Carretero, J., Castander, F. J., Crocce, M., Cunha, C. E., D'Andrea, C. B., da Costa, L. N., Desai, S., Diehl, H. T., Doel, P., Drlica-Wagner, A., Neto, A. Fausti, Flaugher, B., Fosalba, P., Frieman, J., García-Bellido, J., Gaztanaga, E., Gerdes, D. W., Giannantonio, T., Gruen, D., Gruendl, R. A., Gutierrez, G., Honscheid, K., Jain, B., James, D. J., Jeltema, T., Krause, E., Kuehn, K., Kuhlmann, S., Kuropatkin, N., Lahav, O., Li, T. S., Lima, M., March, M., Marshall, J. L., Martini, P., Melchior, P., Ogando, R. L. C., Plazas, A. A., Romer, A. K., Sanchez, E., Scarpine, V., Schindler, R., Schubnell, M., Sevilla-Noarbe, I., Smith, M., Soares-Santos, M., Sobreira, F., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., Vikram, V., Walker, A. R., and Wechsler, R. H. Mon . "Cross-correlation redshift calibration without spectroscopic calibration samples in DES Science Verification Data". United States. https://doi.org/10.1093/mnras/sty787. https://www.osti.gov/servlets/purl/1454415.
@article{osti_1454415,
title = {Cross-correlation redshift calibration without spectroscopic calibration samples in DES Science Verification Data},
author = {Davis, C. and Rozo, E. and Roodman, A. and Alarcon, A. and Cawthon, R. and Gatti, M. and Lin, H. and Miquel, R. and Rykoff, E. S. and Troxel, M. A. and Vielzeuf, P. and Abbott, T. M. C. and Abdalla, F. B. and Allam, S. and Annis, J. and Bechtol, K. and Benoit-Lévy, A. and Bertin, E. and Brooks, D. and Buckley-Geer, E. and Burke, D. L. and Carnero Rosell, A. and Carrasco Kind, M. and Carretero, J. and Castander, F. J. and Crocce, M. and Cunha, C. E. and D'Andrea, C. B. and da Costa, L. N. and Desai, S. and Diehl, H. T. and Doel, P. and Drlica-Wagner, A. and Neto, A. Fausti and Flaugher, B. and Fosalba, P. and Frieman, J. and García-Bellido, J. and Gaztanaga, E. and Gerdes, D. W. and Giannantonio, T. and Gruen, D. and Gruendl, R. A. and Gutierrez, G. and Honscheid, K. and Jain, B. and James, D. J. and Jeltema, T. and Krause, E. and Kuehn, K. and Kuhlmann, S. and Kuropatkin, N. and Lahav, O. and Li, T. S. and Lima, M. and March, M. and Marshall, J. L. and Martini, P. and Melchior, P. and Ogando, R. L. C. and Plazas, A. A. and Romer, A. K. and Sanchez, E. and Scarpine, V. and Schindler, R. and Schubnell, M. 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 Vikram, V. and Walker, A. R. and Wechsler, R. H.},
abstractNote = {Galaxy cross-correlations with high-fidelity redshift samples hold the potential to precisely calibrate systematic photometric redshift uncertainties arising from the unavailability of complete and representative training and validation samples of galaxies. However, application of this technique in the Dark Energy Survey (DES) is hampered by the relatively low number density, small area, and modest redshift overlap between photometric and spectroscopic samples. We propose instead using photometric catalogs with reliable photometric redshifts for photo-z calibration via cross-correlations. We verify the viability of our proposal using redMaPPer clusters from the Sloan Digital Sky Survey (SDSS) to successfully recover the redshift distribution of SDSS spectroscopic galaxies. We demonstrate how to combine photo-z with cross-correlation data to calibrate photometric redshift biases while marginalizing over possible clustering bias evolution in either the calibration or unknown photometric samples. We apply our method to DES Science Verification (DES SV) data in order to constrain the photometric redshift distribution of a galaxy sample selected for weak lensing studies, constraining the mean of the tomographic redshift distributions to a statistical uncertainty of $\Delta z \sim \pm 0.01$. We forecast that our proposal can in principle control photometric redshift uncertainties in DES weak lensing experiments at a level near the intrinsic statistical noise of the experiment over the range of redshifts where redMaPPer clusters are available. Here, our results provide strong motivation to launch a program to fully characterize the systematic errors from bias evolution and photo-z shapes in our calibration procedure.},
doi = {10.1093/mnras/sty787},
journal = {Monthly Notices of the Royal Astronomical Society},
number = 2,
volume = 477,
place = {United States},
year = {2018},
month = {3}
}

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Cited by: 6 works
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Figures / Tables:

Figure 1 Figure 1: A comparison of the cross-correlation recovery of the SDSS redshift distribution with their spectroscopic redshifts. The solid line is the actual distribution of galaxies from spectroscopic data. The black points show the recovered SDSS redshift distribution using cross-correlation with a spectroscopic sample of SDSS galaxies as a referencemore » sample. The red points show the corresponding redshift distributions when using redMaPPer galaxy clusters as the reference sample. Both sets of points account for the best-fitting redshift evolution in the clustering bias.« less

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2dFLenS and KiDS: determining source redshift distributions with cross-correlations
journal, November 2016

  • Johnson, Andrew; Blake, Chris; Amon, Alexandra
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  • DOI: 10.1093/mnras/stw3033

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

  • Morrison, C. B.; Hildebrandt, H.; Schmidt, S. J.
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  • DOI: 10.1093/mnras/stx342

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


Galaxy Redshifts from Discrete Optimization of Correlation Functions
journal, November 2016


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

  • Hildebrandt, H.; Viola, M.; Heymans, C.
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  • DOI: 10.1093/mnras/stw2805

redMaPPer – III. A detailed comparison of the Planck 2013 and SDSS DR8 redMaPPer cluster catalogues
journal, April 2015

  • Rozo, E.; Rykoff, E. S.; Bartlett, James G.
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Bias and variance of angular correlation functions
journal, July 1993

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NINE-YEAR WILKINSON MICROWAVE ANISOTROPY PROBE ( WMAP ) OBSERVATIONS: COSMOLOGICAL PARAMETER RESULTS
journal, September 2013

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An implementation of Bayesian lensing shear measurement
journal, July 2014

  • Sheldon, Erin S.
  • Monthly Notices of the Royal Astronomical Society: Letters, Vol. 444, Issue 1
  • DOI: 10.1093/mnrasl/slu104

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

  • Rozo, E.; Rykoff, E. S.; Abate, A.
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  • DOI: 10.1093/mnras/stw1281

Cosmic shear measurements with Dark Energy Survey Science Verification data
journal, July 2016


Redshift distributions of galaxies in the Dark Energy Survey Science Verification shear catalogue and implications for weak lensing
journal, August 2016


The Blanco Cosmology Survey: data Acquisition, Processing, Calibration, Quality Diagnostics, and data Release
journal, September 2012


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


Improving Correlation Function Fitting with Ridge Regression: Application to Cross-Correlation Reconstruction
journal, January 2012


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


Calibrating Photometric Redshift Distributions with Cross-Correlations
journal, November 2010


    Works referencing / citing this record:

    KiDS+VIKING-450: Cosmic shear tomography with optical and infrared data
    journal, January 2020


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


    Broadband Intensity Tomography: Spectral Tagging of the Cosmic UV Background
    journal, June 2019

    • Chiang, Yi-Kuan; Ménard, Brice; Schiminovich, David
    • The Astrophysical Journal, Vol. 877, Issue 2
    • DOI: 10.3847/1538-4357/ab1b35

    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

    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

    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: 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

    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

      Figures/Tables have been extracted from DOE-funded journal article accepted manuscripts.