Photometric redshift analysis in the Dark Energy Survey Science Verification data
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...
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| Veröffentlicht in: | Monthly notices of the Royal Astronomical Society 2014-12, Vol.445 (2), p.1482-1506 |
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| creator | 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. Jouvel, S. Lahav, O. Lima, M. Maia, M. A. G. Martí, 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. 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, J. L. Nichol, R. C. Roodman, A. Sánchez, 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. Valdés, F. Walker, A. Yuan, F. Zuntz, J. |
| description | 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 ... ~ 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. (ProQuest: ... denotes formulae/symbols omitted.) |
| doi_str_mv | 10.1093/mnras/stu1836 |
| format | Article |
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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. ; Martí, 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. ; 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, J. L. ; Nichol, R. C. ; Roodman, A. ; Sánchez, E. ; Santiago, B. X. ; Sako, M. ; Scalzo, R. ; Smith, R. C. ; Swanson, M. E. C. ; Tarle, G. ; Thomas, D. ; Tucker, D. 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L. ; Nichol, R. C. ; Roodman, A. ; Sánchez, 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. ; Valdés, F. ; Walker, A. ; Yuan, F. ; Zuntz, J. ; Argonne National Lab. (ANL), Argonne, IL (United States)</creatorcontrib><description>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 ... ~ 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. 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(ANL), Argonne, IL (United States)</creatorcontrib><title>Photometric redshift analysis in the Dark Energy Survey Science Verification data</title><title>Monthly notices of the Royal Astronomical Society</title><description>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 ... ~ 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. (ProQuest: ... denotes formulae/symbols omitted.)</description><subject>Astronomy</subject><subject>ASTRONOMY AND ASTROPHYSICS</subject><subject>Astrophysics</subject><subject>Dark matter</subject><subject>galaxies: distance and redshift statistics</subject><subject>galaxies: statistics</subject><subject>large-scale structure of Universe</subject><subject>Neural networks</subject><subject>Red shift</subject><subject>Sciences of the Universe</subject><subject>surveys</subject><issn>0035-8711</issn><issn>1365-2966</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><recordid>eNo90c1LwzAYBvAgCs7p0XvQm1CXr6bpcczphIGKH9eQpqnN3JKZpIP991Y7PD2XH88L7wPAJUa3GJV0snFBxUlMHRaUH4ERpjzPSMn5MRghRPNMFBifgrMYVwghRgkfgZfn1ie_MSlYDYOpY2ubBJVT6320EVoHU2vgnQpfcO5M-NzD1y7sTB_aGqcN_DDBNlarZL2DtUrqHJw0ah3NxSHH4P1-_jZbZMunh8fZdJnp_nLKSo0rXAvFjNCsQhUWiFekqpXSosiNVnUuGC1wLkjBa6orwhlRhSgQ47WhJR2Dq6HXx2Rl1DYZ3WrvnNFJYspIiX_RzYBatZbbYDcq7KVXVi6mS2ld7CSinOWE0h3u8fWAt8F_dyYmufJd6F8RJeaEYy5ESXuVDUoHH2MwzX8vRvJ3B_m3gzzsQH8A3RV8NA</recordid><startdate>20141201</startdate><enddate>20141201</enddate><creator>Sánchez, C.</creator><creator>Carrasco Kind, M.</creator><creator>Lin, H.</creator><creator>Miquel, R.</creator><creator>Abdalla, F. 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T.</creatorcontrib><creatorcontrib>Doel, P.</creatorcontrib><creatorcontrib>Estrada, J.</creatorcontrib><creatorcontrib>Evrard, A.</creatorcontrib><creatorcontrib>Fernández, E.</creatorcontrib><creatorcontrib>Finley, D.</creatorcontrib><creatorcontrib>Flaugher, B.</creatorcontrib><creatorcontrib>Frieman, J.</creatorcontrib><creatorcontrib>Gaztanaga, E.</creatorcontrib><creatorcontrib>Glazebrook, K.</creatorcontrib><creatorcontrib>Honscheid, K.</creatorcontrib><creatorcontrib>Kim, A.</creatorcontrib><creatorcontrib>Kuehn, K.</creatorcontrib><creatorcontrib>Kuropatkin, N.</creatorcontrib><creatorcontrib>Lidman, C.</creatorcontrib><creatorcontrib>Makler, M.</creatorcontrib><creatorcontrib>Marshall, J. L.</creatorcontrib><creatorcontrib>Nichol, R. C.</creatorcontrib><creatorcontrib>Roodman, A.</creatorcontrib><creatorcontrib>Sánchez, E.</creatorcontrib><creatorcontrib>Santiago, B. X.</creatorcontrib><creatorcontrib>Sako, M.</creatorcontrib><creatorcontrib>Scalzo, R.</creatorcontrib><creatorcontrib>Smith, R. C.</creatorcontrib><creatorcontrib>Swanson, M. E. C.</creatorcontrib><creatorcontrib>Tarle, G.</creatorcontrib><creatorcontrib>Thomas, D.</creatorcontrib><creatorcontrib>Tucker, D. L.</creatorcontrib><creatorcontrib>Uddin, S. A.</creatorcontrib><creatorcontrib>Valdés, F.</creatorcontrib><creatorcontrib>Walker, A.</creatorcontrib><creatorcontrib>Yuan, F.</creatorcontrib><creatorcontrib>Zuntz, J.</creatorcontrib><creatorcontrib>Argonne National Lab. (ANL), Argonne, IL (United States)</creatorcontrib><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><collection>OSTI.GOV</collection><jtitle>Monthly notices of the Royal Astronomical Society</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sánchez, C.</au><au>Carrasco Kind, M.</au><au>Lin, H.</au><au>Miquel, R.</au><au>Abdalla, F. B.</au><au>Amara, A.</au><au>Banerji, M.</au><au>Bonnett, C.</au><au>Brunner, R.</au><au>Capozzi, D.</au><au>Carnero, A.</au><au>Castander, F. J.</au><au>da Costa, L. A. N.</au><au>Cunha, C.</au><au>Fausti, A.</au><au>Gerdes, D.</au><au>Greisel, N.</au><au>Gschwend, J.</au><au>Hartley, W.</au><au>Jouvel, S.</au><au>Lahav, O.</au><au>Lima, M.</au><au>Maia, M. A. G.</au><au>Martí, P.</au><au>Ogando, R. L. C.</au><au>Ostrovski, F.</au><au>Pellegrini, P.</au><au>Rau, M. M.</au><au>Sadeh, I.</au><au>Seitz, S.</au><au>Sevilla-Noarbe, I.</au><au>Sypniewski, A.</au><au>de Vicente, J.</au><au>Abbot, T.</au><au>Allam, S. S.</au><au>Atlee, D.</au><au>Bernstein, G.</au><au>Bernstein, J. P.</au><au>Buckley-Geer, E.</au><au>Burke, D.</au><au>Childress, M. J.</au><au>Davis, T.</au><au>DePoy, D. L.</au><au>Dey, A.</au><au>Desai, S.</au><au>Diehl, H. T.</au><au>Doel, P.</au><au>Estrada, J.</au><au>Evrard, A.</au><au>Fernández, E.</au><au>Finley, D.</au><au>Flaugher, B.</au><au>Frieman, J.</au><au>Gaztanaga, E.</au><au>Glazebrook, K.</au><au>Honscheid, K.</au><au>Kim, A.</au><au>Kuehn, K.</au><au>Kuropatkin, N.</au><au>Lidman, C.</au><au>Makler, M.</au><au>Marshall, J. L.</au><au>Nichol, R. C.</au><au>Roodman, A.</au><au>Sánchez, E.</au><au>Santiago, B. X.</au><au>Sako, M.</au><au>Scalzo, R.</au><au>Smith, R. C.</au><au>Swanson, M. E. C.</au><au>Tarle, G.</au><au>Thomas, D.</au><au>Tucker, D. L.</au><au>Uddin, S. A.</au><au>Valdés, F.</au><au>Walker, A.</au><au>Yuan, F.</au><au>Zuntz, J.</au><aucorp>Argonne National Lab. (ANL), Argonne, IL (United States)</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Photometric redshift analysis in the Dark Energy Survey Science Verification data</atitle><jtitle>Monthly notices of the Royal Astronomical Society</jtitle><date>2014-12-01</date><risdate>2014</risdate><volume>445</volume><issue>2</issue><spage>1482</spage><epage>1506</epage><pages>1482-1506</pages><issn>0035-8711</issn><eissn>1365-2966</eissn><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 ... ~ 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. (ProQuest: ... denotes formulae/symbols omitted.)</abstract><cop>London</cop><pub>Oxford University Press</pub><doi>10.1093/mnras/stu1836</doi><tpages>25</tpages><orcidid>https://orcid.org/0000-0001-7316-4573</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0035-8711 |
| ispartof | Monthly notices of the Royal Astronomical Society, 2014-12, Vol.445 (2), p.1482-1506 |
| issn | 0035-8711 1365-2966 |
| language | eng |
| recordid | cdi_osti_scitechconnect_1342919 |
| source | Oxford Journals Open Access Collection |
| subjects | Astronomy ASTRONOMY AND ASTROPHYSICS Astrophysics Dark matter galaxies: distance and redshift statistics galaxies: statistics large-scale structure of Universe Neural networks Red shift Sciences of the Universe surveys |
| title | Photometric redshift analysis in the Dark Energy Survey Science Verification data |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-01T18%3A59%3A19IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_osti_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Photometric%20redshift%20analysis%20in%20the%20Dark%20Energy%20Survey%20Science%20Verification%20data&rft.jtitle=Monthly%20notices%20of%20the%20Royal%20Astronomical%20Society&rft.au=S%C3%A1nchez,%20C.&rft.aucorp=Argonne%20National%20Lab.%20(ANL),%20Argonne,%20IL%20(United%20States)&rft.date=2014-12-01&rft.volume=445&rft.issue=2&rft.spage=1482&rft.epage=1506&rft.pages=1482-1506&rft.issn=0035-8711&rft.eissn=1365-2966&rft_id=info:doi/10.1093/mnras/stu1836&rft_dat=%3Cproquest_osti_%3E3501890491%3C/proquest_osti_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1626168893&rft_id=info:pmid/&rfr_iscdi=true |