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Title: Photometric redshift analysis in the Dark Energy Survey Science Verification data

In this study, 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. In addition, 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 datamore » sets.« less
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Publication Date:
Report Number(s):
FERMILAB-PUB-14-260-AE; arXiv:1406.4407
Journal ID: ISSN 0035-8711; 1300797; TRN: US1702472
Grant/Contract Number:
AC02-07CH11359
Type:
Accepted Manuscript
Journal Name:
Monthly Notices of the Royal Astronomical Society
Additional Journal Information:
Journal Volume: 445; Journal Issue: 2; Journal ID: ISSN 0035-8711
Publisher:
Royal Astronomical Society
Research Org:
Argonne National Lab. (ANL), Argonne, IL (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); SLAC National Accelerator Lab., Menlo Park, CA (United States); Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
Sponsoring Org:
USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25)
Contributing Orgs:
DES Collaboration
Country of Publication:
United States
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS; 46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY; Astronomical data bases: surveys; galaxies: distances and redshifts; galaxies: statistics; large-scale structure of Universe
OSTI Identifier:
1374719

Sanchez, 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., Jouvel, S., Lahav, O., Lima, M., Maia, M. A. G., Marti, P., Ogando, R. L. C., Ostrovski, F., Pellegrini, P., Rau, M. M., Sadeh, I., Seitz, S., Sevilla-Noarbe, I., Sypniewski, A., de Vicente, J., Abbot, T., Allam, S. S., Atlee, D., Bernstein, G., Bernstein, J. P., Buckley-Geer, E., Burke, D., Childress, M. J., Davis, T., DePoy, D. L., Dey, A., Desai, S., Diehl, H. T., Doel, P., Estrada, J., Evrard, A., Fernandez, E., Finley, D., Flaugher, B., Frieman, J., Gaztanaga, E., Glazebrook, K., Honscheid, K., Kim, A., Kuehn, K., Kuropatkin, N., Lidman, C., Makler, M., Marshall, J. L., Nichol, R. C., Roodman, A., Sanchez, E., Santiago, B. X., Sako, M., Scalzo, R., Smith, R. C., Swanson, M. E. C., Tarle, G., Thomas, D., Tucker, D. L., Uddin, S. A., Valdes, F., Walker, A., Yuan, F., and Zuntz, J.. Photometric redshift analysis in the Dark Energy Survey Science Verification data. United States: N. p., Web. doi:10.1093/mnras/stu1836.
Sanchez, 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., Jouvel, S., Lahav, O., Lima, M., Maia, M. A. G., Marti, P., Ogando, R. L. C., Ostrovski, F., Pellegrini, P., Rau, M. M., Sadeh, I., Seitz, S., Sevilla-Noarbe, I., Sypniewski, A., de Vicente, J., Abbot, T., Allam, S. S., Atlee, D., Bernstein, G., Bernstein, J. P., Buckley-Geer, E., Burke, D., Childress, M. J., Davis, T., DePoy, D. L., Dey, A., Desai, S., Diehl, H. T., Doel, P., Estrada, J., Evrard, A., Fernandez, E., Finley, D., Flaugher, B., Frieman, J., Gaztanaga, E., Glazebrook, K., Honscheid, K., Kim, A., Kuehn, K., Kuropatkin, N., Lidman, C., Makler, M., Marshall, J. L., Nichol, R. C., Roodman, A., Sanchez, E., Santiago, B. X., Sako, M., Scalzo, R., Smith, R. C., Swanson, M. E. C., Tarle, G., Thomas, D., Tucker, D. L., Uddin, S. A., Valdes, F., Walker, A., Yuan, F., & Zuntz, J.. Photometric redshift analysis in the Dark Energy Survey Science Verification data. United States. doi:10.1093/mnras/stu1836.
Sanchez, 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., Jouvel, S., Lahav, O., Lima, M., Maia, M. A. G., Marti, P., Ogando, R. L. C., Ostrovski, F., Pellegrini, P., Rau, M. M., Sadeh, I., Seitz, S., Sevilla-Noarbe, I., Sypniewski, A., de Vicente, J., Abbot, T., Allam, S. S., Atlee, D., Bernstein, G., Bernstein, J. P., Buckley-Geer, E., Burke, D., Childress, M. J., Davis, T., DePoy, D. L., Dey, A., Desai, S., Diehl, H. T., Doel, P., Estrada, J., Evrard, A., Fernandez, E., Finley, D., Flaugher, B., Frieman, J., Gaztanaga, E., Glazebrook, K., Honscheid, K., Kim, A., Kuehn, K., Kuropatkin, N., Lidman, C., Makler, M., Marshall, J. L., Nichol, R. C., Roodman, A., Sanchez, E., Santiago, B. X., Sako, M., Scalzo, R., Smith, R. C., Swanson, M. E. C., Tarle, G., Thomas, D., Tucker, D. L., Uddin, S. A., Valdes, F., Walker, A., Yuan, F., and Zuntz, J.. 2014. "Photometric redshift analysis in the Dark Energy Survey Science Verification data". United States. doi:10.1093/mnras/stu1836. https://www.osti.gov/servlets/purl/1374719.
@article{osti_1374719,
title = {Photometric redshift analysis in the Dark Energy Survey Science Verification data},
author = {Sanchez, C. and Carrasco Kind, M. and Lin, H. and Miquel, R. and Abdalla, F. B. and Amara, A. and Banerji, M. and Bonnett, C. and Brunner, R. and Capozzi, D. and Carnero, A. and Castander, F. J. and da Costa, L. A. N. and Cunha, C. and Fausti, A. and Gerdes, D. and Greisel, N. and Gschwend, J. and Hartley, W. and Jouvel, S. and Lahav, O. and Lima, M. and Maia, M. A. G. and Marti, P. and Ogando, R. L. C. and Ostrovski, F. and Pellegrini, P. and Rau, M. M. and Sadeh, I. and Seitz, S. and Sevilla-Noarbe, I. and Sypniewski, A. and de Vicente, J. and Abbot, T. and Allam, S. S. and Atlee, D. and Bernstein, G. and Bernstein, J. P. and Buckley-Geer, E. and Burke, D. and Childress, M. J. and Davis, T. and DePoy, D. L. and Dey, A. and Desai, S. and Diehl, H. T. and Doel, P. and Estrada, J. and Evrard, A. and Fernandez, E. and Finley, D. and Flaugher, B. and Frieman, J. and Gaztanaga, E. and Glazebrook, K. and Honscheid, K. and Kim, A. and Kuehn, K. and Kuropatkin, N. and Lidman, C. and Makler, M. and Marshall, J. L. and Nichol, R. C. and Roodman, A. and Sanchez, E. and Santiago, B. X. and Sako, M. and Scalzo, R. and Smith, R. C. and Swanson, M. E. C. and Tarle, G. and Thomas, D. and Tucker, D. L. and Uddin, S. A. and Valdes, F. and Walker, A. and Yuan, F. and Zuntz, J.},
abstractNote = {In this study, 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. In addition, 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.},
doi = {10.1093/mnras/stu1836},
journal = {Monthly Notices of the Royal Astronomical Society},
number = 2,
volume = 445,
place = {United States},
year = {2014},
month = {10}
}