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

DES Collaboration

Research output: Contribution to journalArticle

7 Citations (Scopus)

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 catalogues 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 Δz ~ ±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. Our results provide strong motivation to launch a programme to fully characterize the systematic errors from bias evolution and photo-z shapes in our calibration procedure.

Original languageEnglish (US)
Pages (from-to)2196-2208
Number of pages13
JournalMonthly Notices of the Royal Astronomical Society
Volume477
Issue number2
DOIs
StatePublished - Jun 21 2018

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dark energy
cross correlation
calibration
galaxies
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proposals
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systematic errors
forecasting
catalogs
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science
distribution

Keywords

  • Galaxies: Clusters: General
  • Galaxies: Distances and redshifts

ASJC Scopus subject areas

  • Astronomy and Astrophysics
  • Space and Planetary Science

Cite this

Cross-correlation redshift calibration without spectroscopic calibration samples in DES Science Verification Data. / DES Collaboration.

In: Monthly Notices of the Royal Astronomical Society, Vol. 477, No. 2, 21.06.2018, p. 2196-2208.

Research output: Contribution to journalArticle

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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 catalogues 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 Δz ~ ±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. Our results provide strong motivation to launch a programme to fully characterize the systematic errors from bias evolution and photo-z shapes in our calibration procedure.",
keywords = "Galaxies: Clusters: General, Galaxies: Distances and redshifts",
author = "{DES Collaboration} and C. Davis and Eduardo Rozo and A. Roodman and A. Alarcon and R. Cawthon and M. Gatti and H. Lin and R. Miquel and Rykoff, {E. S.} and Troxel, {M. A.} and P. Vielzeuf and Abbott, {T. M.C.} and Abdalla, {F. B.} and S. Allam and J. Annis and K. Bechtol and A. Benoit-L{\'e}vy and E. Bertin and D. Brooks and E. Buckley-Geer and Burke, {D. L.} and {Carnero Rosell}, A. and Kind, {M. Carrasco} and J. Carretero and Castander, {F. J.} and M. Crocce and Cunha, {C. E.} and D'Andrea, {C. B.} and {da Costa}, {L. N.} and S. Desai and Diehl, {H. T.} and P. Doel and A. Drlica-Wagner and {Fausti Neto}, A. and B. Flaugher and P. Fosalba and J. Frieman and J. Garćia-Bellido and E. Gaztanaga and Gerdes, {D. W.} and T. Giannantonio and D. Gruen and Gruendl, {R. A.} and G. Gutierrez and K. Honscheid and B. Jain and James, {D. J.} and T. Jeltema and E. Krause and K. Kuehn",
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T1 - Cross-correlation redshift calibration without spectroscopic calibration samples in DES Science Verification Data

AU - DES Collaboration

AU - Davis, C.

AU - Rozo, Eduardo

AU - Roodman, A.

AU - Alarcon, A.

AU - Cawthon, R.

AU - Gatti, M.

AU - Lin, H.

AU - Miquel, R.

AU - Rykoff, E. S.

AU - Troxel, M. A.

AU - Vielzeuf, P.

AU - Abbott, T. M.C.

AU - Abdalla, F. B.

AU - Allam, S.

AU - Annis, J.

AU - Bechtol, K.

AU - Benoit-Lévy, A.

AU - Bertin, E.

AU - Brooks, D.

AU - Buckley-Geer, E.

AU - Burke, D. L.

AU - Carnero Rosell, A.

AU - Kind, M. Carrasco

AU - Carretero, J.

AU - Castander, F. J.

AU - Crocce, M.

AU - Cunha, C. E.

AU - D'Andrea, C. B.

AU - da Costa, L. N.

AU - Desai, S.

AU - Diehl, H. T.

AU - Doel, P.

AU - Drlica-Wagner, A.

AU - Fausti Neto, A.

AU - Flaugher, B.

AU - Fosalba, P.

AU - Frieman, J.

AU - Garćia-Bellido, J.

AU - Gaztanaga, E.

AU - Gerdes, D. W.

AU - Giannantonio, T.

AU - Gruen, D.

AU - Gruendl, R. A.

AU - Gutierrez, G.

AU - Honscheid, K.

AU - Jain, B.

AU - James, D. J.

AU - Jeltema, T.

AU - Krause, E.

AU - Kuehn, K.

PY - 2018/6/21

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N2 - 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 catalogues 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 Δz ~ ±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. Our results provide strong motivation to launch a programme to fully characterize the systematic errors from bias evolution and photo-z shapes in our calibration procedure.

AB - 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 catalogues 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 Δz ~ ±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. Our results provide strong motivation to launch a programme to fully characterize the systematic errors from bias evolution and photo-z shapes in our calibration procedure.

KW - Galaxies: Clusters: General

KW - Galaxies: Distances and redshifts

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U2 - 10.1093/mnras/sty787

DO - 10.1093/mnras/sty787

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