Photometric redshift analysis in the Dark Energy Survey science verification data
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Outros Autores: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRGS |
Texto Completo: | http://hdl.handle.net/10183/115354 |
Resumo: | 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. |
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Sánchez Alonso, CarlesCarrasco Kind, MatíasLin, H.Serra Ricart, MiquelAbdalla, Filipe B.Amara, AdamBanerji, M.Bonnet, Christopher CliveBrunner, Robert J.Capozzi, DiegoCarnero Rosell, AurelioCastander Serentill, Francisco JavierCosta, Luiz N. daCunha, Carlos EduardoFausti Neto, AngeloGerdes, David W.Greisel, N.Gschwend, Julia de FigueiredoHartley, WilliamJouvel, StéphanieLahav, OferLima, Marcos Vinicius Borges TeixeiraMaia, Marcio Antonio GeimbaMartí, P.Ogando, Ricardo L.C.Ostrovski, F.Pellegrini, Paulo Sérgio de SouzaRau, Markus MichaelSadeh, IftachSeitz, StellaSevilla Noarbe, IgnacioSypniewski, Adam J.Vicente, J. deAbbott, Timothy M. C.Allam, Sahar S.Atlee, DavidBernstein, Gary M.Bernstein, Joseph P.Buckley-Geer, ElizabethBurke, David LyleChildress, MichaelDavis, Tamara M.DePoy, Darren L.Dey, ArjunDesai, S.Diehl, H. ThomasDoel, PeterEstrada, JuanEvrard, August E.Fernandez, EnriqueFinley, David A.Flaugher, BrennaFrieman, Joshua A.Gaztañaga, EnriqueGlazebrook, KarlHonscheid, K.Kim, A. G.Kuehn, KylerKuropatkin, Nikolay P.Lidman, ChrisMakler, MartínMarshall, Jennifer L.Nichol, Robert C.Roodman, AaronSanchez-Alvaro, EusebioSantiago, Basilio XavierSako, MasaoScalzo, RichardSmith, Robert ChristopherSwanson, Molly E. C.Tarle, GregoryThomas, D.Tucker, Douglas L.Uddin, SyedValdes, FranciscoWalker, AlistairYuan, FangZuntz, J.2015-04-15T01:58:21Z20140035-8711http://hdl.handle.net/10183/115354000963587We 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.application/pdfengMonthly notices of the Royal Astronomical Society. Oxford. Vol. 445, no. 2 (Dec. 2014), p. 1482-1506Mapeamentos astronômicosAstronomical data bases: surveysGalaxies: distances and redshiftsGalaxies: statisticsLarge-scale structure of UniversePhotometric redshift analysis in the Dark Energy Survey science verification dataEstrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSTEXT000963587.pdf.txt000963587.pdf.txtExtracted Texttext/plain130439http://www.lume.ufrgs.br/bitstream/10183/115354/2/000963587.pdf.txta985d63023161fa62a5ed067a4a84acdMD52ORIGINAL000963587.pdf000963587.pdfTexto completo (inglês)application/pdf2832409http://www.lume.ufrgs.br/bitstream/10183/115354/1/000963587.pdf2f50c2a6a57539aea3b0b3c2f818c00cMD51THUMBNAIL000963587.pdf.jpg000963587.pdf.jpgGenerated Thumbnailimage/jpeg2175http://www.lume.ufrgs.br/bitstream/10183/115354/3/000963587.pdf.jpgb522bdad4ceb91682767f9209e845870MD5310183/1153542023-07-02 03:41:59.967222oai:www.lume.ufrgs.br:10183/115354Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2023-07-02T06:41:59Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false |
dc.title.pt_BR.fl_str_mv |
Photometric redshift analysis in the Dark Energy Survey science verification data |
title |
Photometric redshift analysis in the Dark Energy Survey science verification data |
spellingShingle |
Photometric redshift analysis in the Dark Energy Survey science verification data Sánchez Alonso, Carles Mapeamentos astronômicos Astronomical data bases: surveys Galaxies: distances and redshifts Galaxies: statistics Large-scale structure of Universe |
title_short |
Photometric redshift analysis in the Dark Energy Survey science verification data |
title_full |
Photometric redshift analysis in the Dark Energy Survey science verification data |
title_fullStr |
Photometric redshift analysis in the Dark Energy Survey science verification data |
title_full_unstemmed |
Photometric redshift analysis in the Dark Energy Survey science verification data |
title_sort |
Photometric redshift analysis in the Dark Energy Survey science verification data |
author |
Sánchez Alonso, Carles |
author_facet |
Sánchez Alonso, Carles Carrasco Kind, Matías Lin, H. Serra Ricart, Miquel Abdalla, Filipe B. Amara, Adam Banerji, M. Bonnet, Christopher Clive Brunner, Robert J. Capozzi, Diego Carnero Rosell, Aurelio Castander Serentill, Francisco Javier Costa, Luiz N. da Cunha, Carlos Eduardo Fausti Neto, Angelo Gerdes, David W. Greisel, N. Gschwend, Julia de Figueiredo Hartley, William Jouvel, Stéphanie Lahav, Ofer Lima, Marcos Vinicius Borges Teixeira Maia, Marcio Antonio Geimba Martí, P. Ogando, Ricardo L.C. Ostrovski, F. Pellegrini, Paulo Sérgio de Souza Rau, Markus Michael Sadeh, Iftach Seitz, Stella Sevilla Noarbe, Ignacio Sypniewski, Adam J. Vicente, J. de Abbott, Timothy M. C. Allam, Sahar S. Atlee, David Bernstein, Gary M. Bernstein, Joseph P. Buckley-Geer, Elizabeth Burke, David Lyle Childress, Michael Davis, Tamara M. DePoy, Darren L. Dey, Arjun Desai, S. Diehl, H. Thomas Doel, Peter Estrada, Juan Evrard, August E. Fernandez, Enrique Finley, David A. Flaugher, Brenna Frieman, Joshua A. Gaztañaga, Enrique Glazebrook, Karl Honscheid, K. Kim, A. G. Kuehn, Kyler Kuropatkin, Nikolay P. Lidman, Chris Makler, Martín Marshall, Jennifer L. Nichol, Robert C. Roodman, Aaron Sanchez-Alvaro, Eusebio Santiago, Basilio Xavier Sako, Masao Scalzo, Richard Smith, Robert Christopher Swanson, Molly E. C. Tarle, Gregory Thomas, D. Tucker, Douglas L. Uddin, Syed Valdes, Francisco Walker, Alistair Yuan, Fang Zuntz, J. |
author_role |
author |
author2 |
Carrasco Kind, Matías Lin, H. Serra Ricart, Miquel Abdalla, Filipe B. Amara, Adam Banerji, M. Bonnet, Christopher Clive Brunner, Robert J. Capozzi, Diego Carnero Rosell, Aurelio Castander Serentill, Francisco Javier Costa, Luiz N. da Cunha, Carlos Eduardo Fausti Neto, Angelo Gerdes, David W. Greisel, N. Gschwend, Julia de Figueiredo Hartley, William Jouvel, Stéphanie Lahav, Ofer Lima, Marcos Vinicius Borges Teixeira Maia, Marcio Antonio Geimba Martí, P. Ogando, Ricardo L.C. Ostrovski, F. Pellegrini, Paulo Sérgio de Souza Rau, Markus Michael Sadeh, Iftach Seitz, Stella Sevilla Noarbe, Ignacio Sypniewski, Adam J. Vicente, J. de Abbott, Timothy M. C. Allam, Sahar S. Atlee, David Bernstein, Gary M. Bernstein, Joseph P. Buckley-Geer, Elizabeth Burke, David Lyle Childress, Michael Davis, Tamara M. DePoy, Darren L. Dey, Arjun Desai, S. Diehl, H. Thomas Doel, Peter Estrada, Juan Evrard, August E. Fernandez, Enrique Finley, David A. Flaugher, Brenna Frieman, Joshua A. Gaztañaga, Enrique Glazebrook, Karl Honscheid, K. Kim, A. G. Kuehn, Kyler Kuropatkin, Nikolay P. Lidman, Chris Makler, Martín Marshall, Jennifer L. Nichol, Robert C. Roodman, Aaron Sanchez-Alvaro, Eusebio Santiago, Basilio Xavier Sako, Masao Scalzo, Richard Smith, Robert Christopher Swanson, Molly E. C. Tarle, Gregory Thomas, D. Tucker, Douglas L. Uddin, Syed Valdes, Francisco Walker, Alistair Yuan, Fang Zuntz, J. |
author2_role |
author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author |
dc.contributor.author.fl_str_mv |
Sánchez Alonso, Carles Carrasco Kind, Matías Lin, H. Serra Ricart, Miquel Abdalla, Filipe B. Amara, Adam Banerji, M. Bonnet, Christopher Clive Brunner, Robert J. Capozzi, Diego Carnero Rosell, Aurelio Castander Serentill, Francisco Javier Costa, Luiz N. da Cunha, Carlos Eduardo Fausti Neto, Angelo Gerdes, David W. Greisel, N. Gschwend, Julia de Figueiredo Hartley, William Jouvel, Stéphanie Lahav, Ofer Lima, Marcos Vinicius Borges Teixeira Maia, Marcio Antonio Geimba Martí, P. Ogando, Ricardo L.C. Ostrovski, F. Pellegrini, Paulo Sérgio de Souza Rau, Markus Michael Sadeh, Iftach Seitz, Stella Sevilla Noarbe, Ignacio Sypniewski, Adam J. Vicente, J. de Abbott, Timothy M. C. Allam, Sahar S. Atlee, David Bernstein, Gary M. Bernstein, Joseph P. Buckley-Geer, Elizabeth Burke, David Lyle Childress, Michael Davis, Tamara M. DePoy, Darren L. Dey, Arjun Desai, S. Diehl, H. Thomas Doel, Peter Estrada, Juan Evrard, August E. Fernandez, Enrique Finley, David A. Flaugher, Brenna Frieman, Joshua A. Gaztañaga, Enrique Glazebrook, Karl Honscheid, K. Kim, A. G. Kuehn, Kyler Kuropatkin, Nikolay P. Lidman, Chris Makler, Martín Marshall, Jennifer L. Nichol, Robert C. Roodman, Aaron Sanchez-Alvaro, Eusebio Santiago, Basilio Xavier Sako, Masao Scalzo, Richard Smith, Robert Christopher Swanson, Molly E. C. Tarle, Gregory Thomas, D. Tucker, Douglas L. Uddin, Syed Valdes, Francisco Walker, Alistair Yuan, Fang Zuntz, J. |
dc.subject.por.fl_str_mv |
Mapeamentos astronômicos |
topic |
Mapeamentos astronômicos Astronomical data bases: surveys Galaxies: distances and redshifts Galaxies: statistics Large-scale structure of Universe |
dc.subject.eng.fl_str_mv |
Astronomical data bases: surveys Galaxies: distances and redshifts Galaxies: statistics Large-scale structure of Universe |
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 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. |
publishDate |
2014 |
dc.date.issued.fl_str_mv |
2014 |
dc.date.accessioned.fl_str_mv |
2015-04-15T01:58:21Z |
dc.type.driver.fl_str_mv |
Estrangeiro info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
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publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10183/115354 |
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0035-8711 |
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000963587 |
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0035-8711 000963587 |
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http://hdl.handle.net/10183/115354 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartof.pt_BR.fl_str_mv |
Monthly notices of the Royal Astronomical Society. Oxford. Vol. 445, no. 2 (Dec. 2014), p. 1482-1506 |
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info:eu-repo/semantics/openAccess |
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openAccess |
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