Photometric redshift analysis in the Dark Energy Survey Science Verification data

C. Sanchez; 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. Abbott; 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; 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. Sanchez, 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. Abbott, 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, 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

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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 (SV) 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 performance using about 15000 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 multi-dimensional color-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 $\sigma_{68} \sim 0.08$. 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
Journal	Monthly Notices of the Royal Astronomical Society
Volume	445
Issue number	2
Early online date	10 Oct 2014
DOIs	https://doi.org/10.1093/mnras/stu1836
Publication status	Published - 1 Dec 2014

Keywords

astro-ph.IM
astro-ph.CO
RCUK
STFC
ST/K00090X/1

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10.1093/mnras/stu1836

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This article has been accepted for publication in 'Monthly notices of the Royal Astronomical Society ©: 2014 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society. All rights reserved.
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Sanchez, C., Kind, M. C., Lin, H., Miquel, R., Abdalla, F. B., Amara, A., Banerji, M., Bonnett, C., Brunner, R., Capozzi, D., Carnero, A., Castander, F. J., Costa, L. A. N. D., 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{1a5f398f8975473f818b352abdaa4f4c,

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 (SV) 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 performance using about 15000 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 multi-dimensional color-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 $\sigma_{68} \sim 0.08$. 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 = "astro-ph.IM, astro-ph.CO, RCUK, STFC, ST/K00090X/1",

author = "C. Sanchez and Kind, {M. Carrasco} 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 Costa, {L. A. N. da} 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 Vicente, {J. de} and T. Abbott 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 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 = "This version accounts for minor comments in the journal review. This article has been accepted for publication in 'Monthly notices of the Royal Astronomical Society {\textcopyright}: 2014 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society. All rights reserved.",

year = "2014",

month = dec,

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doi = "10.1093/mnras/stu1836",

language = "English",

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pages = "1482--1506",

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

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Sanchez, C, Kind, MC, Lin, H, Miquel, R, Abdalla, FB, Amara, A, Banerji, M, Bonnett, C, Brunner, R, Capozzi, D, Carnero, A, Castander, FJ, Costa, LAND, 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, Vicente, JD, Abbott, 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, 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 - Sanchez, C.

AU - Kind, M. Carrasco

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 - Costa, L. A. N. da

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 - Vicente, J. de

AU - Abbott, 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 - 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.

N1 - This version accounts for minor comments in the journal review. This article has been accepted for publication in 'Monthly notices of the Royal Astronomical Society ©: 2014 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society. All rights reserved.

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 (SV) 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 performance using about 15000 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 multi-dimensional color-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 $\sigma_{68} \sim 0.08$. 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 (SV) 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 performance using about 15000 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 multi-dimensional color-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 $\sigma_{68} \sim 0.08$. 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 - astro-ph.IM

KW - astro-ph.CO

KW - RCUK

KW - STFC

KW - ST/K00090X/1

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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