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

Abstract

Wide-field imaging surveys such as the Dark Energy Survey (DES) rely on coarse measurements of spectral energy distributions in a few filters to estimate the redshift distribution of source galaxies. In this regime, sample variance, shot noise, and selection effects limit the attainable accuracy of redshift calibration and thus of cosmological constraints. We present a new method to combine wide-field, few-filter measurements with catalogues from deep fields with additional filters and sufficiently low photometric noise to break degeneracies in photometric redshifts. The multiband deep field is used as an intermediary between wide-field observations and accurate redshifts, greatly reducing sample variance, shot noise, and selection effects. Our implementation of the method uses self-organizing maps to group galaxies into phenotypes based on their observed fluxes, and is tested using a mock DES catalogue created from N-body simulations. Here, it yields a typical uncertainty on the mean redshift in each of five tomographic bins for an idealized simulation of the DES Year 3 weak-lensing tomographic analysis of σ Δz = 0.007, which is a 60 per cent improvement compared to the Year 1 analysis. Although the implementation of the method is tailored to DES, its formalism can be applied to other large photometricmore » surveys with a similar observing strategy.« less

Authors:
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [3];  [4];  [5];  [6];  [6];  [7];  [8];  [7];  [9];  [10];  [11];  [12];  [13];  [3];  [14];  [15];  [16];  [17] more »;  [18];  [19];  [15];  [8];  [20];  [21];  [22];  [5];  [23];  [6];  [24];  [25];  [26];  [15];  [19];  [27];  [28];  [29];  [15];  [5];  [27];  [30];  [5];  [21];  [24];  [15];  [31];  [32];  [33];  [34];  [35];  [15];  [36];  [15];  [24];  [6];  [37];  [38];  [21];  [24];  [38];  [8];  [25];  [15];  [5];  [25];  [39];  [40];  [41];  [42];  [43];  [44];  [16];  [45] « less
  1. SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA; Kavli Institute for Particle Astrophysics and Cosmology, P. O. Box 2450, Stanford University, Stanford, CA 94305, USA; École Polytechnique Fédérale de Lausanne, Route Cantonale, CH-1015 Lausanne, Switzerland; Institute of Science, Technology, and Policy, ETH Zurich, Universitätstrasse 41, CH-8092 Zurich, Switzerland
  2. SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA; Kavli Institute for Particle Astrophysics and Cosmology, P. O. Box 2450, Stanford University, Stanford, CA 94305, USA; Descartes Labs, Inc., 100 N Guadelupe St, Santa Fe, NM 87501, USA
  3. SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA; Kavli Institute for Particle Astrophysics and Cosmology, P. O. Box 2450, Stanford University, Stanford, CA 94305, USA; Department of Physics, Stanford University, 382 Via Pueblo Mall, Stanford, CA 94305, USA
  4. Kavli Institute for Particle Astrophysics and Cosmology, P. O. Box 2450, Stanford University, Stanford, CA 94305, USA; Department of Physics, Stanford University, 382 Via Pueblo Mall, Stanford, CA 94305, USA
  5. 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
  6. Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA 19104, USA
  7. Department of Physics, Stanford University, 382 Via Pueblo Mall, Stanford, CA 94305, USA
  8. SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA; Kavli Institute for Particle Astrophysics and Cosmology, P. O. Box 2450, Stanford University, Stanford, CA 94305, USA
  9. Kavli Institute for Particle Astrophysics and Cosmology, P. O. Box 2450, Stanford University, Stanford, CA 94305, USA
  10. Center for Cosmology and Astro-Particle Physics, The Ohio State University, Columbus, OH 43210, USA
  11. Infrared Processing and Analysis Center, Pasadena, CA 91125, USA; Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA 91109, USA
  12. Institució Catalana de Recerca i Estudis Avançats, E-08010 Barcelona, Spain; Institut de Física d’Altes Energies (IFAE), The Barcelona Institute of Science and Technology, Campus UAB, E-08193 Bellaterra (Barcelona), Spain
  13. Department of Physics, Duke University Durham, NC 27708, USA
  14. Cerro Tololo Inter-American Observatory, National Optical Astronomy Observatory, Casilla 603, La Serena, Chile
  15. Fermi National Accelerator Laboratory, P. O. Box 500, Batavia, IL 60510, USA
  16. Institute of Cosmology and Gravitation, University of Portsmouth, Portsmouth PO1 3FX, UK
  17. LSST, 933 North Cherry Avenue, Tucson, AZ 85721, USA; Physics Department, 2320 Chamberlin Hall, University of Wisconsin-Madison, 1150 University Avenue Madison, WI 53706, USA
  18. Jodrell Bank Center for Astrophysics, School of Physics and Astronomy, University of Manchester, Oxford Road, Manchester M13 9PL, UK
  19. Department of Physics and Astronomy, University College London, Gower Street, London WC1E 6BT, UK
  20. 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
  21. 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
  22. Institut de Física d’Altes Energies (IFAE), The Barcelona Institute of Science and Technology, Campus UAB, E-08193 Bellaterra (Barcelona), Spain
  23. Physics Department, 2320 Chamberlin Hall, University of Wisconsin-Madison, 1150 University Avenue Madison, WI 53706, USA
  24. 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
  25. Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), E-28040 Madrid, Spain
  26. Department of Physics, IIT Hyderabad, Kandi, Telangana 502285, India
  27. Fermi National Accelerator Laboratory, P. O. Box 500, Batavia, IL 60510, USA; Kavli Institute for Cosmological Physics, University of Chicago, Chicago, IL 60637, USA
  28. Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA 91109, USA; Department of Astronomy/Steward Observatory, 933 North Cherry Avenue, Tucson, AZ 85721-0065, USA
  29. Department of Astronomy, University of Michigan, Ann Arbor, MI 48109, USA; Department of Physics, University of Michigan, Ann Arbor, MI 48109, USA
  30. Instituto de Fisica Teorica UAM/CSIC, Universidad Autonoma de Madrid, E-8049 Madrid, Spain
  31. 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
  32. Santa Cruz Institute for Particle Physics, Santa Cruz, CA 95064, USA
  33. 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
  34. Center for Astrophysics, Harvard and Smithsonian, 60 Garden Street, MS 42, Cambridge, MA 02138, USA
  35. Australian Astronomical Optics, Macquarie University, North Ryde, NSW 2113, Australia
  36. 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
  37. 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
  38. Department of Astrophysical Sciences, Princeton University, Peyton Hall, Princeton, NJ 08544, USA
  39. School of Physics and Astronomy, University of Southampton, Southampton SO17 1BJ, UK
  40. Physics Department, Brandeis University, 415 South Street, Waltham, MA 02453, USA
  41. 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, 13083-859 Campinas, SP, Brazil
  42. Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
  43. National Center for Supercomputing Applications, 1205 West Clark St., Urbana, IL 61801, USA
  44. Department of Physics, University of Michigan, Ann Arbor, MI 48109, USA
  45. Argonne National Laboratory, 9700 South Cass Avenue, Lemont, IL 60439, 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) (SC-25); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
Contributing Org.:
DES Collaboration
OSTI Identifier:
1527430
Alternate Identifier(s):
OSTI ID: 1558844; OSTI ID: 1559590; OSTI ID: 1569038
Report Number(s):
arXiv:1901.05005; FERMILAB-PUB-19-011-AE
Journal ID: ISSN 0035-8711; oai:inspirehep.net:1714055
Grant/Contract Number:  
AC02-07CH11359; AC05-00OR22725; AC02-76SF00515
Resource Type:
Accepted Manuscript
Journal Name:
Monthly Notices of the Royal Astronomical Society
Additional Journal Information:
Journal Volume: 489; Journal Issue: 1; Journal ID: ISSN 0035-8711
Publisher:
Royal Astronomical Society
Country of Publication:
United States
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS; gravitational lensing: weak; galaxies: distances and redshifts; dark energy; 72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS; cosmology; photometric redshifts; weak gravitational lensing

Citation Formats

Buchs, R., Davis, C., Gruen, D., DeRose, J., Alarcon, A., Bernstein, G. M., Sánchez, C., Myles, J., Roodman, A., Allen, S., Amon, A., Choi, A., Masters, D. C., Miquel, R., Troxel, M. A., Wechsler, R. H., Abbott, T. M. C., Annis, J., Avila, S., Bechtol, K., Bridle, S. L., Brooks, D., Buckley-Geer, E., Burke, D. L., Carnero Rosell, A., Carrasco Kind, M., Carretero, J., Castander, F. J., Cawthon, R., D’Andrea, C. B., da Costa, L. N., De Vicente, J., Desai, S., Diehl, H. T., Doel, P., Drlica-Wagner, A., Eifler, T. F., Evrard, A. E., Flaugher, B., Fosalba, P., Frieman, J., García-Bellido, J., Gaztanaga, E., Gruendl, R. A., Gschwend, J., Gutierrez, G., Hartley, W. G., Hollowood, D. L., Honscheid, K., James, D. J., Kuehn, K., Kuropatkin, N., Lima, M., Lin, H., Maia, M. A. G., March, M., Marshall, J. L., Melchior, P., Menanteau, F., Ogando, R. L. C., Plazas, A. A., Rykoff, E. S., Sanchez, E., Scarpine, V., Serrano, S., Sevilla-Noarbe, I., Smith, M., Soares-Santos, M., Sobreira, F., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., and Vikram, V. Phenotypic redshifts with self-organizing maps: A novel method to characterize redshift distributions of source galaxies for weak lensing. United States: N. p., 2019. Web. doi:10.1093/mnras/stz2162.
Buchs, R., Davis, C., Gruen, D., DeRose, J., Alarcon, A., Bernstein, G. M., Sánchez, C., Myles, J., Roodman, A., Allen, S., Amon, A., Choi, A., Masters, D. C., Miquel, R., Troxel, M. A., Wechsler, R. H., Abbott, T. M. C., Annis, J., Avila, S., Bechtol, K., Bridle, S. L., Brooks, D., Buckley-Geer, E., Burke, D. L., Carnero Rosell, A., Carrasco Kind, M., Carretero, J., Castander, F. J., Cawthon, R., D’Andrea, C. B., da Costa, L. N., De Vicente, J., Desai, S., Diehl, H. T., Doel, P., Drlica-Wagner, A., Eifler, T. F., Evrard, A. E., Flaugher, B., Fosalba, P., Frieman, J., García-Bellido, J., Gaztanaga, E., Gruendl, R. A., Gschwend, J., Gutierrez, G., Hartley, W. G., Hollowood, D. L., Honscheid, K., James, D. J., Kuehn, K., Kuropatkin, N., Lima, M., Lin, H., Maia, M. A. G., March, M., Marshall, J. L., Melchior, P., Menanteau, F., Ogando, R. L. C., Plazas, A. A., Rykoff, E. S., Sanchez, E., Scarpine, V., Serrano, S., Sevilla-Noarbe, I., Smith, M., Soares-Santos, M., Sobreira, F., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., & Vikram, V. Phenotypic redshifts with self-organizing maps: A novel method to characterize redshift distributions of source galaxies for weak lensing. United States. doi:10.1093/mnras/stz2162.
Buchs, R., Davis, C., Gruen, D., DeRose, J., Alarcon, A., Bernstein, G. M., Sánchez, C., Myles, J., Roodman, A., Allen, S., Amon, A., Choi, A., Masters, D. C., Miquel, R., Troxel, M. A., Wechsler, R. H., Abbott, T. M. C., Annis, J., Avila, S., Bechtol, K., Bridle, S. L., Brooks, D., Buckley-Geer, E., Burke, D. L., Carnero Rosell, A., Carrasco Kind, M., Carretero, J., Castander, F. J., Cawthon, R., D’Andrea, C. B., da Costa, L. N., De Vicente, J., Desai, S., Diehl, H. T., Doel, P., Drlica-Wagner, A., Eifler, T. F., Evrard, A. E., Flaugher, B., Fosalba, P., Frieman, J., García-Bellido, J., Gaztanaga, E., Gruendl, R. A., Gschwend, J., Gutierrez, G., Hartley, W. G., Hollowood, D. L., Honscheid, K., James, D. J., Kuehn, K., Kuropatkin, N., Lima, M., Lin, H., Maia, M. A. G., March, M., Marshall, J. L., Melchior, P., Menanteau, F., Ogando, R. L. C., Plazas, A. A., Rykoff, E. S., Sanchez, E., Scarpine, V., Serrano, S., Sevilla-Noarbe, I., Smith, M., Soares-Santos, M., Sobreira, F., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., and Vikram, V. Fri . "Phenotypic redshifts with self-organizing maps: A novel method to characterize redshift distributions of source galaxies for weak lensing". United States. doi:10.1093/mnras/stz2162.
@article{osti_1527430,
title = {Phenotypic redshifts with self-organizing maps: A novel method to characterize redshift distributions of source galaxies for weak lensing},
author = {Buchs, R. and Davis, C. and Gruen, D. and DeRose, J. and Alarcon, A. and Bernstein, G. M. and Sánchez, C. and Myles, J. and Roodman, A. and Allen, S. and Amon, A. and Choi, A. and Masters, D. C. and Miquel, R. and Troxel, M. A. and Wechsler, R. H. and Abbott, T. M. C. and Annis, J. and Avila, S. and Bechtol, K. and Bridle, S. L. 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 Cawthon, R. and D’Andrea, C. B. and da Costa, L. N. and De Vicente, J. and Desai, S. and Diehl, H. T. and Doel, P. and Drlica-Wagner, A. and Eifler, T. F. and Evrard, A. E. and Flaugher, B. and Fosalba, P. and Frieman, J. and García-Bellido, J. and Gaztanaga, E. and Gruendl, R. A. and Gschwend, J. and Gutierrez, G. and Hartley, W. G. and Hollowood, D. L. and Honscheid, K. and James, D. J. and Kuehn, K. and Kuropatkin, N. and Lima, M. and Lin, H. and Maia, M. A. G. and March, M. and Marshall, J. L. and Melchior, P. and Menanteau, F. and Ogando, R. L. C. and Plazas, A. A. and Rykoff, E. S. and Sanchez, E. and Scarpine, V. 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 Vikram, V.},
abstractNote = {Wide-field imaging surveys such as the Dark Energy Survey (DES) rely on coarse measurements of spectral energy distributions in a few filters to estimate the redshift distribution of source galaxies. In this regime, sample variance, shot noise, and selection effects limit the attainable accuracy of redshift calibration and thus of cosmological constraints. We present a new method to combine wide-field, few-filter measurements with catalogues from deep fields with additional filters and sufficiently low photometric noise to break degeneracies in photometric redshifts. The multiband deep field is used as an intermediary between wide-field observations and accurate redshifts, greatly reducing sample variance, shot noise, and selection effects. Our implementation of the method uses self-organizing maps to group galaxies into phenotypes based on their observed fluxes, and is tested using a mock DES catalogue created from N-body simulations. Here, it yields a typical uncertainty on the mean redshift in each of five tomographic bins for an idealized simulation of the DES Year 3 weak-lensing tomographic analysis of σΔz = 0.007, which is a 60 per cent improvement compared to the Year 1 analysis. Although the implementation of the method is tailored to DES, its formalism can be applied to other large photometric surveys with a similar observing strategy.},
doi = {10.1093/mnras/stz2162},
journal = {Monthly Notices of the Royal Astronomical Society},
number = 1,
volume = 489,
place = {United States},
year = {2019},
month = {8}
}

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  • 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

Approximating Photo- z PDFs for Large Surveys
journal, June 2018


ANN z : Estimating Photometric Redshifts Using Artificial Neural Networks
journal, April 2004

  • Collister, Adrian A.; Lahav, Ofer
  • Publications of the Astronomical Society of the Pacific, Vol. 116, Issue 818
  • DOI: 10.1086/383254

Power Spectrum Tomography with Weak Lensing
journal, September 1999

  • Hu, Wayne
  • The Astrophysical Journal, Vol. 522, Issue 1
  • DOI: 10.1086/312210

Galaxy Morphology without Classification: Self‐organizing Maps
journal, August 1997

  • Naim, Avi; Ratnatunga, Kavan U.; Griffiths, Richard E.
  • The Astrophysical Journal Supplement Series, Vol. 111, Issue 2
  • DOI: 10.1086/313022

SOMz: photometric redshift PDFs with self-organizing maps and random atlas
journal, January 2014

  • Carrasco Kind, Matias; Brunner, Robert J.
  • Monthly Notices of the Royal Astronomical Society, Vol. 438, Issue 4
  • DOI: 10.1093/mnras/stt2456

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
  • DOI: 10.1093/mnras/sty1624

Effects of Photometric Redshift Uncertainties on Weak‐Lensing Tomography
journal, January 2006

  • Ma, Zhaoming; Hu, Wayne; Huterer, Dragan
  • The Astrophysical Journal, Vol. 636, Issue 1
  • DOI: 10.1086/497068

Weak Lensing for Precision Cosmology
journal, September 2018


Classifying Gamma‐Ray Bursts using Self‐organizing Maps
journal, February 2002

  • Rajaniemi, H. J.; Mahonen, P.
  • The Astrophysical Journal, Vol. 566, Issue 1
  • DOI: 10.1086/337959

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

Can Self-Organizing Maps Accurately Predict Photometric Redshifts?
journal, March 2012

  • Way, M. J.; Klose, C. D.
  • Publications of the Astronomical Society of the Pacific, Vol. 124, Issue 913
  • DOI: 10.1086/664796

The PAU Survey: early demonstration of photometric redshift performance in the COSMOS field
journal, January 2019

  • Eriksen, M.; Alarcon, A.; Gaztanaga, E.
  • Monthly Notices of the Royal Astronomical Society, Vol. 484, Issue 3
  • DOI: 10.1093/mnras/stz204

Weak gravitational lensing
journal, January 2001


Cosmology with cosmic shear observations: a review
journal, July 2015


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

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

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

A Modified Magnitude System that Produces Well-Behaved Magnitudes, Colors, and Errors Even for Low Signal-to-Noise Ratio Measurements
journal, September 1999

  • Lupton, Robert H.; Gunn, James E.; Szalay, Alexander S.
  • The Astronomical Journal, Vol. 118, Issue 3
  • DOI: 10.1086/301004

Mapping the Galaxy Color–Redshift Relation: Optimal Photometric Redshift Calibration Strategies for Cosmology Surveys
journal, October 2015


Subaru Prime Focus Camera — Suprime-Cam
journal, December 2002

  • Miyazaki, Satoshi; Komiyama, Yutaka; Sekiguchi, Maki
  • Publications of the Astronomical Society of Japan, Vol. 54, Issue 6
  • DOI: 10.1093/pasj/54.6.833

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


Photo-z performance for precision cosmology: Photo-z performance for precision cosmology
journal, May 2010


The Complete Calibration of the Color–Redshift Relation (C3R2) Survey: Analysis and Data Release 2
journal, May 2019

  • Masters, Daniel C.; Stern, Daniel K.; Cohen, Judith G.
  • The Astrophysical Journal, Vol. 877, Issue 2
  • DOI: 10.3847/1538-4357/ab184d

Simultaneous constraints on cosmology and photometric redshift bias from weak lensing and galaxy clustering
journal, September 2016

  • Samuroff, S.; Troxel, M. A.; Bridle, S. L.
  • Monthly Notices of the Royal Astronomical Society: Letters, Vol. 465, Issue 1
  • DOI: 10.1093/mnrasl/slw201

Selection biases in empirical p(z) methods for weak lensing
journal, February 2017

  • Gruen, D.; Brimioulle, F.
  • Monthly Notices of the Royal Astronomical Society, Vol. 468, Issue 1
  • DOI: 10.1093/mnras/stx471