Photometric redshift analysis in the Dark Energy Survey Science Verification data

C. Sánchez; M. Carrasco Kind; H. Lin; R. Miquel; F. B. Abdalla; A. Amara; M. Banerji; C. Bonnett; R. Brunner; D. Capozzi; A. Carnero; F. J. Castander; L. A.N. da Costa; C. Cunha; A. Fausti; D. Gerdes; N. Greisel; J. Gschwend; W. Hartley; S. Jouvel; O. Lahav; M. Lima; M. A.G. Maia; P. Martí; R. L.C. Ogando; F. Ostrovski; P. Pellegrini; M. M. Rau; I. Sadeh; S. Seitz; I. Sevilla-Noarbe; A. Sypniewski; J. de Vicente; T. Abbot; S. S. Allam; D. Atlee; G. Bernstein; J. P. Bernstein; E. Buckley-Geer; D. Burke; M. J. Childress; T. Davis; D. L. DePoy; A. Dey; S. Desai; H. T. Diehl; P. Doel; J. Estrada; A. Evrard; E. Fernández; D. Finley; B. Flaugher; J. Frieman; E. Gaztanaga; K. Glazebrook; K. Honscheid; A. Kim; K. Kuehn; N. Kuropatkin; C. Lidman; M. Makler; J. L. Marshall; R. C. Nichol; A. Roodman; E. Sánchez; B. X. Santiago; M. Sako; R. Scalzo; R. C. Smith; M. E.C. Swanson; G. Tarle; D. Thomas; D. L. Tucker; S. A. Uddin; F. Valdés; A. Walker; F. Yuan; J. Zuntz

doi:10.1093/mnras/stu1836

Photometric redshift analysis in the Dark Energy Survey Science Verification data

C. Sánchez^*, M. Carrasco Kind, H. Lin, R. Miquel, F. B. Abdalla, A. Amara, M. Banerji, C. Bonnett, R. Brunner, D. Capozzi, A. Carnero, F. J. Castander, L. A.N. da Costa, C. Cunha, A. Fausti, D. Gerdes, N. Greisel, J. Gschwend, W. Hartley, S. JouvelO. Lahav, M. Lima, M. A.G. Maia, P. Martí, R. L.C. Ogando, F. Ostrovski, P. Pellegrini, M. M. Rau, I. Sadeh, S. Seitz, I. Sevilla-Noarbe, A. Sypniewski, J. de Vicente, T. Abbot, S. S. Allam, D. Atlee, G. Bernstein, J. P. Bernstein, E. Buckley-Geer, D. Burke, M. J. Childress, T. Davis, D. L. DePoy, A. Dey, S. Desai, H. T. Diehl, P. Doel, J. Estrada, A. Evrard, E. Fernández, D. Finley, B. Flaugher, J. Frieman, E. Gaztanaga, K. Glazebrook, K. Honscheid, A. Kim, K. Kuehn, N. Kuropatkin, C. Lidman, M. Makler, J. L. Marshall, R. C. Nichol, A. Roodman, E. Sánchez, B. X. Santiago, M. Sako, R. Scalzo, R. C. Smith, M. E.C. Swanson, G. Tarle, D. Thomas, D. L. Tucker, S. A. Uddin, F. Valdés, A. Walker, F. Yuan, J. Zuntz

^*Corresponding author for this work

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Abstract

We present results from a study of the photometric redshift performance of the Dark Energy Survey (DES), using the early data from a Science Verification period of observations in late 2012 and early 2013 that provided science-quality images for almost 200 sq. deg. at the nominal depth of the survey. We assess the photometric redshift (photo-z) performance using about 15 000 galaxies with spectroscopic redshifts available from other surveys. These galaxies are used, in different configurations, as a calibration sample, and photo-z's are obtained and studied using most of the existing photo-z codes. A weighting method in a multidimensional colour-magnitude space is applied to the spectroscopic sample in order to evaluate the photo-z performance with sets that mimic the full DES photometric sample, which is on average significantly deeper than the calibration sample due to the limited depth of spectroscopic surveys. Empirical photo-z methods using, for instance, artificial neural networks or random forests, yield the best performance in the tests, achieving core photo-z resolutions σ₆₈ ~ 0.08. Moreover, the results from most of the codes, including template-fitting methods, comfortably meet the DES requirements on photo-z performance, therefore, providing an excellent precedent for future DES data sets.

Original language	English
Pages (from-to)	1482-1506
Number of pages	25
Journal	Monthly Notices of the Royal Astronomical Society
Volume	445
Issue number	2
DOIs	https://doi.org/10.1093/mnras/stu1836
Publication status	Published - 1 Dec 2014

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Sánchez, C., Carrasco Kind, M., Lin, H., Miquel, R., Abdalla, F. B., Amara, A., Banerji, M., Bonnett, C., Brunner, R., Capozzi, D., Carnero, A., Castander, F. J., da Costa, L. A. N., Cunha, C., Fausti, A., Gerdes, D., Greisel, N., Gschwend, J., Hartley, W., ... Zuntz, J. (2014). Photometric redshift analysis in the Dark Energy Survey Science Verification data. Monthly Notices of the Royal Astronomical Society, 445(2), 1482-1506. https://doi.org/10.1093/mnras/stu1836

@article{b7c900cc167d4035bf9dda83e9f9a9f6,

title = "Photometric redshift analysis in the Dark Energy Survey Science Verification data",

abstract = "We present results from a study of the photometric redshift performance of the Dark Energy Survey (DES), using the early data from a Science Verification period of observations in late 2012 and early 2013 that provided science-quality images for almost 200 sq. deg. at the nominal depth of the survey. We assess the photometric redshift (photo-z) performance using about 15 000 galaxies with spectroscopic redshifts available from other surveys. These galaxies are used, in different configurations, as a calibration sample, and photo-z's are obtained and studied using most of the existing photo-z codes. A weighting method in a multidimensional colour-magnitude space is applied to the spectroscopic sample in order to evaluate the photo-z performance with sets that mimic the full DES photometric sample, which is on average significantly deeper than the calibration sample due to the limited depth of spectroscopic surveys. Empirical photo-z methods using, for instance, artificial neural networks or random forests, yield the best performance in the tests, achieving core photo-z resolutions σ68 ~ 0.08. Moreover, the results from most of the codes, including template-fitting methods, comfortably meet the DES requirements on photo-z performance, therefore, providing an excellent precedent for future DES data sets.",

keywords = "Astronomical data bases: surveys, Galaxies: distances and redshifts, Galaxies: statistics, Large-scale structure of Universe",

author = "C. S{\'a}nchez and {Carrasco Kind}, M. and H. Lin and R. Miquel and Abdalla, {F. B.} and A. Amara and M. Banerji and C. Bonnett and R. Brunner and D. Capozzi and A. Carnero and Castander, {F. J.} and {da Costa}, {L. A.N.} and C. Cunha and A. Fausti and D. Gerdes and N. Greisel and J. Gschwend and W. Hartley and S. Jouvel and O. Lahav and M. Lima and Maia, {M. A.G.} and P. Mart{\'i} and Ogando, {R. L.C.} and F. Ostrovski and P. Pellegrini and Rau, {M. M.} and I. Sadeh and S. Seitz and I. Sevilla-Noarbe and A. Sypniewski and {de Vicente}, J. and T. Abbot and Allam, {S. S.} and D. Atlee and G. Bernstein and Bernstein, {J. P.} and E. Buckley-Geer and D. Burke and Childress, {M. J.} and T. Davis and DePoy, {D. L.} and A. Dey and S. Desai and Diehl, {H. T.} and P. Doel and J. Estrada and A. Evrard and E. Fern{\'a}ndez and D. Finley and B. Flaugher and J. Frieman and E. Gaztanaga and K. Glazebrook and K. Honscheid and A. Kim and K. Kuehn and N. Kuropatkin and C. Lidman and M. Makler and Marshall, {J. L.} and Nichol, {R. C.} and A. Roodman and E. S{\'a}nchez and Santiago, {B. X.} and M. Sako and R. Scalzo and Smith, {R. C.} and Swanson, {M. E.C.} and G. Tarle and D. Thomas and Tucker, {D. L.} and Uddin, {S. A.} and F. Vald{\'e}s and A. Walker and F. Yuan and J. Zuntz",

note = "Publisher Copyright: {\textcopyright} 2014 The Authors.",

year = "2014",

month = dec,

day = "1",

doi = "10.1093/mnras/stu1836",

language = "English",

volume = "445",

pages = "1482--1506",

journal = "Monthly Notices of the Royal Astronomical Society",

issn = "0035-8711",

publisher = "Oxford University Press ",

number = "2",

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Sánchez, C, Carrasco Kind, M, Lin, H, Miquel, R, Abdalla, FB, Amara, A, Banerji, M, Bonnett, C, Brunner, R, Capozzi, D, Carnero, A, Castander, FJ, da Costa, LAN, Cunha, C, Fausti, A, Gerdes, D, Greisel, N, Gschwend, J, Hartley, W, Jouvel, S, Lahav, O, Lima, M, Maia, MAG, Martí, P, Ogando, RLC, Ostrovski, F, Pellegrini, P, Rau, MM, Sadeh, I, Seitz, S, Sevilla-Noarbe, I, Sypniewski, A, de Vicente, J, Abbot, T, Allam, SS, Atlee, D, Bernstein, G, Bernstein, JP, Buckley-Geer, E, Burke, D, Childress, MJ, Davis, T, DePoy, DL, Dey, A, Desai, S, Diehl, HT, Doel, P, Estrada, J, Evrard, A, Fernández, E, Finley, D, Flaugher, B, Frieman, J, Gaztanaga, E, Glazebrook, K, Honscheid, K, Kim, A, Kuehn, K, Kuropatkin, N, Lidman, C, Makler, M, Marshall, JL, Nichol, RC, Roodman, A, Sánchez, E, Santiago, BX, Sako, M, Scalzo, R, Smith, RC, Swanson, MEC, Tarle, G, Thomas, D, Tucker, DL, Uddin, SA, Valdés, F, Walker, A, Yuan, F & Zuntz, J 2014, 'Photometric redshift analysis in the Dark Energy Survey Science Verification data', Monthly Notices of the Royal Astronomical Society, vol. 445, no. 2, pp. 1482-1506. https://doi.org/10.1093/mnras/stu1836

TY - JOUR

T1 - Photometric redshift analysis in the Dark Energy Survey Science Verification data

AU - Sánchez, C.

AU - Carrasco Kind, M.

AU - Lin, H.

AU - Miquel, R.

AU - Abdalla, F. B.

AU - Amara, A.

AU - Banerji, M.

AU - Bonnett, C.

AU - Brunner, R.

AU - Capozzi, D.

AU - Carnero, A.

AU - Castander, F. J.

AU - da Costa, L. A.N.

AU - Cunha, C.

AU - Fausti, A.

AU - Gerdes, D.

AU - Greisel, N.

AU - Gschwend, J.

AU - Hartley, W.

AU - Jouvel, S.

AU - Lahav, O.

AU - Lima, M.

AU - Maia, M. A.G.

AU - Martí, P.

AU - Ogando, R. L.C.

AU - Ostrovski, F.

AU - Pellegrini, P.

AU - Rau, M. M.

AU - Sadeh, I.

AU - Seitz, S.

AU - Sevilla-Noarbe, I.

AU - Sypniewski, A.

AU - de Vicente, J.

AU - Abbot, T.

AU - Allam, S. S.

AU - Atlee, D.

AU - Bernstein, G.

AU - Bernstein, J. P.

AU - Buckley-Geer, E.

AU - Burke, D.

AU - Childress, M. J.

AU - Davis, T.

AU - DePoy, D. L.

AU - Dey, A.

AU - Desai, S.

AU - Diehl, H. T.

AU - Doel, P.

AU - Estrada, J.

AU - Evrard, A.

AU - Fernández, E.

AU - Finley, D.

AU - Flaugher, B.

AU - Frieman, J.

AU - Gaztanaga, E.

AU - Glazebrook, K.

AU - Honscheid, K.

AU - Kim, A.

AU - Kuehn, K.

AU - Kuropatkin, N.

AU - Lidman, C.

AU - Makler, M.

AU - Marshall, J. L.

AU - Nichol, R. C.

AU - Roodman, A.

AU - Sánchez, E.

AU - Santiago, B. X.

AU - Sako, M.

AU - Scalzo, R.

AU - Smith, R. C.

AU - Swanson, M. E.C.

AU - Tarle, G.

AU - Thomas, D.

AU - Tucker, D. L.

AU - Uddin, S. A.

AU - Valdés, F.

AU - Walker, A.

AU - Yuan, F.

AU - Zuntz, J.

PY - 2014/12/1

Y1 - 2014/12/1

N2 - We present results from a study of the photometric redshift performance of the Dark Energy Survey (DES), using the early data from a Science Verification period of observations in late 2012 and early 2013 that provided science-quality images for almost 200 sq. deg. at the nominal depth of the survey. We assess the photometric redshift (photo-z) performance using about 15 000 galaxies with spectroscopic redshifts available from other surveys. These galaxies are used, in different configurations, as a calibration sample, and photo-z's are obtained and studied using most of the existing photo-z codes. A weighting method in a multidimensional colour-magnitude space is applied to the spectroscopic sample in order to evaluate the photo-z performance with sets that mimic the full DES photometric sample, which is on average significantly deeper than the calibration sample due to the limited depth of spectroscopic surveys. Empirical photo-z methods using, for instance, artificial neural networks or random forests, yield the best performance in the tests, achieving core photo-z resolutions σ68 ~ 0.08. Moreover, the results from most of the codes, including template-fitting methods, comfortably meet the DES requirements on photo-z performance, therefore, providing an excellent precedent for future DES data sets.

AB - We present results from a study of the photometric redshift performance of the Dark Energy Survey (DES), using the early data from a Science Verification period of observations in late 2012 and early 2013 that provided science-quality images for almost 200 sq. deg. at the nominal depth of the survey. We assess the photometric redshift (photo-z) performance using about 15 000 galaxies with spectroscopic redshifts available from other surveys. These galaxies are used, in different configurations, as a calibration sample, and photo-z's are obtained and studied using most of the existing photo-z codes. A weighting method in a multidimensional colour-magnitude space is applied to the spectroscopic sample in order to evaluate the photo-z performance with sets that mimic the full DES photometric sample, which is on average significantly deeper than the calibration sample due to the limited depth of spectroscopic surveys. Empirical photo-z methods using, for instance, artificial neural networks or random forests, yield the best performance in the tests, achieving core photo-z resolutions σ68 ~ 0.08. Moreover, the results from most of the codes, including template-fitting methods, comfortably meet the DES requirements on photo-z performance, therefore, providing an excellent precedent for future DES data sets.

KW - Astronomical data bases: surveys

KW - Galaxies: distances and redshifts

KW - Galaxies: statistics

KW - Large-scale structure of Universe

UR - http://www.scopus.com/inward/record.url?scp=84920880721&partnerID=8YFLogxK

U2 - 10.1093/mnras/stu1836

DO - 10.1093/mnras/stu1836

M3 - Article

SN - 0035-8711

VL - 445

SP - 1482

EP - 1506

JO - Monthly Notices of the Royal Astronomical Society

JF - Monthly Notices of the Royal Astronomical Society

IS - 2

ER -

Photometric redshift analysis in the Dark Energy Survey Science Verification data

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