2dFLenS and KiDS: Determining source redshift distributions with cross-correlations

Andrew Johnson, Chris Blake, Alexandra Amon, Thomas Erben, Karl Glazebrook, Joachim Harnois-Deraps, Catherine Heymans, Hendrik Hildebrandt, Shahab Joudaki, Dominik Klaes, Konrad Kuijken, Chris Lidman, Felipe A. Marin, John McFarland, Christopher B. Morrison, David Parkinson, Gregory B. Poole, Mario Radovich, Christian Wolf

Research output: Contribution to journalArticlepeer-review

35 Scopus citations


We develop a statistical estimator to infer the redshift probability distribution of a photometric sample of galaxies from its angular cross-correlation in redshift bins with an overlapping spectroscopic sample. This estimator is a minimum-variance weighted quadratic function of the data: a quadratic estimator. This extends and modifies the methodology presented by McQuinn & White. The derived source redshift distribution is degenerate with the source galaxy bias, which must be constrained via additional assumptions. We apply this estimator to constrain source galaxy redshift distributions in theKilo-Degree imaging survey through crosscorrelation with the spectroscopic 2-degree Field Lensing Survey, presenting results first as a binned step-wise distribution in the range z < 0.8, and then building a continuous distribution using a Gaussian process model. We demonstrate the robustness of our methodology using mock catalogues constructed from N-body simulations, and comparisons with other techniques for inferring the redshift distribution.

Original languageEnglish (US)
Pages (from-to)4118-4132
Number of pages15
JournalMonthly Notices of the Royal Astronomical Society
Issue number4
StatePublished - Mar 11 2017
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Astronomy and Astrophysics
  • Space and Planetary Science


  • Cosmology: observation
  • Large-scale structure of Universe
  • Surveys


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