Mapping and simulating systematics due to spatially varying observing conditions in DES Science Verification data
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRGS |
Texto Completo: | http://hdl.handle.net/10183/159671 |
Resumo: | Spatially varying depth and the characteristics of observing conditions, such as seeing, airmass, or sky background, are major sources of systematic uncertainties in modern galaxy survey analyses, particularly in deep multi-epochsurveys. We present a framework to extract and project these sources of systematics onto the sky, and apply it to the Dark Energy Survey (DES) to map the observing conditions of the Science Verification (SV) data. The resulting distributions and maps of sources of systematics are used in several analyses of DES–SV to perform detailed null tests with the data, and also to incorporate systematics in survey simulations. We illustrate the complementary nature of these two approaches by comparing the SV data with BCC-UFig, a synthetic sky catalog generated by forward-modeling of the DES–SV images We analyze the BCC-UFig simulation to construct galaxy samples mimicking those used in SV galaxy clustering studies. We show that the spatially varying survey depth imprinted in the observed galaxy densities and the redshift distributions of the SV data are successfully reproduced by the simulation and are well-captured by the maps of observing conditions. The combined use of the maps, the SV data, and the BCC-UFig simulation allows us to quantify the impact of spatial systematics on N(z), the redshift distributions inferred using photometric redshifts. We conclude that spatial systematics in the SV data are mainly due to seeing fluctuations and are under control in current clustering and weak-lensing analyses. However, they will need to be carefully characterized in upcoming phases of DES in order to avoid biasing the inferred cosmological results. The framework presented here is relevant to all multi-epoch surveys and will be essential for exploiting future surveys such as the Large Synoptic Survey Telescope, which will require detailed null tests and realistic end-to-end image simulations to correctly interpret the deep, high-cadence observations of the sky. |
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Leistedt, BorisPeiris, Hiranya V.Elsner, FranzBenoit-Lévy, AurélienAmara, AdamBauer, Anne HollisterBecker, Matthew R.Bonnett, ChristopherBruderer, ClaudioBusha, M. T.Carrasco Kind, MatíasChang, ChihwayCrocce, MartinCosta, Luiz N. daGaztañaga, EnriqueHuff, EricLahav, OferPalmese, A.Percival, Will J.Refregier, AlexandreRoss, A.J.Rozo, EduardoRykoff, EliSánchez Alonso, CarlesSadeh, IftachSevilla Noarbe, IgnacioSobreira, FláviaSuchyta, EricSwanson, Molly E. C.Wechsler, Risa H.Abdalla, Filipe B.Allam, Sahar S.Banerji, M.Bernstein, Gary M.Bernstein, Rebecca A.Bertin, EmmanuelBridle, Sarah LouiseBrooks, D.Buckley-Geer, ElizabethBurke, David LyleCapozzi, DiegoCarnero Rosell, AurelioCarretero Palacios, JorgeCunha, Carlos EduardoD'Andrea, Christopher B.DePoy, Darren L.Desai, S.Diehl, H. ThomasDoel, PeterEifler, TimEvrard, August E.Fausti Neto, AngeloFlaugher, BrennaFosalba Vela, PabloFrieman, Joshua A.Gerdes, David W.Gruen, DanielGruendl, Robert A.Gutierrez, Gaston R.Honscheid, K.James, David J.Jarvis, MichaelKent, Stephen M.Kuehn, KylerKuropatkin, Nikolay P.Li, T. S.Lima, Marcos Vinicius Borges TeixeiraMaia, Marcio Antonio GeimbaMarch, Marisa CristinaMarshall, Jennifer L.Martini, PaulMelchior, Peter M.Miller, Christopher J.Miquel, RamonNichol, Robert C.Nord, Brian DennisOgando, Ricardo L.C.Plazas Malagón, Andrés AlejandroReil, KevinRomer, Anita K.Roodman, AaronSanchez-Alvaro, EusebioSantiago, Basilio XavierScarpine, Victor EmanuelSchubnell, MichaelSmith, Robert ChristopherSoares-Santos, MarcelleTarle, GregoryThaler, Jon J.Thomas, D.Vikram, VinuWalker, AlistairWester, William CarlZhang, YuanyuanZuntz, J.2017-06-20T02:30:23Z20160067-0049http://hdl.handle.net/10183/159671001022682Spatially varying depth and the characteristics of observing conditions, such as seeing, airmass, or sky background, are major sources of systematic uncertainties in modern galaxy survey analyses, particularly in deep multi-epochsurveys. We present a framework to extract and project these sources of systematics onto the sky, and apply it to the Dark Energy Survey (DES) to map the observing conditions of the Science Verification (SV) data. The resulting distributions and maps of sources of systematics are used in several analyses of DES–SV to perform detailed null tests with the data, and also to incorporate systematics in survey simulations. We illustrate the complementary nature of these two approaches by comparing the SV data with BCC-UFig, a synthetic sky catalog generated by forward-modeling of the DES–SV images We analyze the BCC-UFig simulation to construct galaxy samples mimicking those used in SV galaxy clustering studies. We show that the spatially varying survey depth imprinted in the observed galaxy densities and the redshift distributions of the SV data are successfully reproduced by the simulation and are well-captured by the maps of observing conditions. The combined use of the maps, the SV data, and the BCC-UFig simulation allows us to quantify the impact of spatial systematics on N(z), the redshift distributions inferred using photometric redshifts. We conclude that spatial systematics in the SV data are mainly due to seeing fluctuations and are under control in current clustering and weak-lensing analyses. However, they will need to be carefully characterized in upcoming phases of DES in order to avoid biasing the inferred cosmological results. The framework presented here is relevant to all multi-epoch surveys and will be essential for exploiting future surveys such as the Large Synoptic Survey Telescope, which will require detailed null tests and realistic end-to-end image simulations to correctly interpret the deep, high-cadence observations of the sky.application/pdfengThe astrophysical journal. Supplement series. Chicago. Vol. 226, no. 2 (Oct. 2016), 24, 13 p.Fotometria astronômicaDeslocamento para o vermelhoAglomerados de galaxiasMapeamentos astronômicosCosmology: observationsGalaxies: distances and redshiftsGalaxies: statisticsLarge-scale structure of universeMapping and simulating systematics due to spatially varying observing conditions in DES 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:UFRGSORIGINAL001022682.pdf001022682.pdfTexto completo (inglês)application/pdf1960851http://www.lume.ufrgs.br/bitstream/10183/159671/1/001022682.pdf8c3a32f4cbfed7a65fec6b511245fd11MD51TEXT001022682.pdf.txt001022682.pdf.txtExtracted Texttext/plain66479http://www.lume.ufrgs.br/bitstream/10183/159671/2/001022682.pdf.txtc167165f5890bcb692e956aac01e3b53MD5210183/1596712023-07-02 03:41:08.311558oai:www.lume.ufrgs.br:10183/159671Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2023-07-02T06:41:08Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false |
dc.title.pt_BR.fl_str_mv |
Mapping and simulating systematics due to spatially varying observing conditions in DES Science Verification data |
title |
Mapping and simulating systematics due to spatially varying observing conditions in DES Science Verification data |
spellingShingle |
Mapping and simulating systematics due to spatially varying observing conditions in DES Science Verification data Leistedt, Boris Fotometria astronômica Deslocamento para o vermelho Aglomerados de galaxias Mapeamentos astronômicos Cosmology: observations Galaxies: distances and redshifts Galaxies: statistics Large-scale structure of universe |
title_short |
Mapping and simulating systematics due to spatially varying observing conditions in DES Science Verification data |
title_full |
Mapping and simulating systematics due to spatially varying observing conditions in DES Science Verification data |
title_fullStr |
Mapping and simulating systematics due to spatially varying observing conditions in DES Science Verification data |
title_full_unstemmed |
Mapping and simulating systematics due to spatially varying observing conditions in DES Science Verification data |
title_sort |
Mapping and simulating systematics due to spatially varying observing conditions in DES Science Verification data |
author |
Leistedt, Boris |
author_facet |
Leistedt, Boris Peiris, Hiranya V. Elsner, Franz Benoit-Lévy, Aurélien Amara, Adam Bauer, Anne Hollister Becker, Matthew R. Bonnett, Christopher Bruderer, Claudio Busha, M. T. Carrasco Kind, Matías Chang, Chihway Crocce, Martin Costa, Luiz N. da Gaztañaga, Enrique Huff, Eric Lahav, Ofer Palmese, A. Percival, Will J. Refregier, Alexandre Ross, A.J. Rozo, Eduardo Rykoff, Eli Sánchez Alonso, Carles Sadeh, Iftach Sevilla Noarbe, Ignacio Sobreira, Flávia Suchyta, Eric Swanson, Molly E. C. Wechsler, Risa H. Abdalla, Filipe B. Allam, Sahar S. Banerji, M. Bernstein, Gary M. Bernstein, Rebecca A. Bertin, Emmanuel Bridle, Sarah Louise Brooks, D. Buckley-Geer, Elizabeth Burke, David Lyle Capozzi, Diego Carnero Rosell, Aurelio Carretero Palacios, Jorge Cunha, Carlos Eduardo D'Andrea, Christopher B. DePoy, Darren L. Desai, S. Diehl, H. Thomas Doel, Peter Eifler, Tim Evrard, August E. Fausti Neto, Angelo Flaugher, Brenna Fosalba Vela, Pablo Frieman, Joshua A. Gerdes, David W. Gruen, Daniel Gruendl, Robert A. Gutierrez, Gaston R. Honscheid, K. James, David J. Jarvis, Michael Kent, Stephen M. Kuehn, Kyler Kuropatkin, Nikolay P. Li, T. S. Lima, Marcos Vinicius Borges Teixeira Maia, Marcio Antonio Geimba March, Marisa Cristina Marshall, Jennifer L. Martini, Paul Melchior, Peter M. Miller, Christopher J. Miquel, Ramon Nichol, Robert C. Nord, Brian Dennis Ogando, Ricardo L.C. Plazas Malagón, Andrés Alejandro Reil, Kevin Romer, Anita K. Roodman, Aaron Sanchez-Alvaro, Eusebio Santiago, Basilio Xavier Scarpine, Victor Emanuel Schubnell, Michael Smith, Robert Christopher Soares-Santos, Marcelle Tarle, Gregory Thaler, Jon J. Thomas, D. Vikram, Vinu Walker, Alistair Wester, William Carl Zhang, Yuanyuan Zuntz, J. |
author_role |
author |
author2 |
Peiris, Hiranya V. Elsner, Franz Benoit-Lévy, Aurélien Amara, Adam Bauer, Anne Hollister Becker, Matthew R. Bonnett, Christopher Bruderer, Claudio Busha, M. T. Carrasco Kind, Matías Chang, Chihway Crocce, Martin Costa, Luiz N. da Gaztañaga, Enrique Huff, Eric Lahav, Ofer Palmese, A. Percival, Will J. Refregier, Alexandre Ross, A.J. Rozo, Eduardo Rykoff, Eli Sánchez Alonso, Carles Sadeh, Iftach Sevilla Noarbe, Ignacio Sobreira, Flávia Suchyta, Eric Swanson, Molly E. C. Wechsler, Risa H. Abdalla, Filipe B. Allam, Sahar S. Banerji, M. Bernstein, Gary M. Bernstein, Rebecca A. Bertin, Emmanuel Bridle, Sarah Louise Brooks, D. Buckley-Geer, Elizabeth Burke, David Lyle Capozzi, Diego Carnero Rosell, Aurelio Carretero Palacios, Jorge Cunha, Carlos Eduardo D'Andrea, Christopher B. DePoy, Darren L. Desai, S. Diehl, H. Thomas Doel, Peter Eifler, Tim Evrard, August E. Fausti Neto, Angelo Flaugher, Brenna Fosalba Vela, Pablo Frieman, Joshua A. Gerdes, David W. Gruen, Daniel Gruendl, Robert A. Gutierrez, Gaston R. Honscheid, K. James, David J. Jarvis, Michael Kent, Stephen M. Kuehn, Kyler Kuropatkin, Nikolay P. Li, T. S. Lima, Marcos Vinicius Borges Teixeira Maia, Marcio Antonio Geimba March, Marisa Cristina Marshall, Jennifer L. Martini, Paul Melchior, Peter M. Miller, Christopher J. Miquel, Ramon Nichol, Robert C. Nord, Brian Dennis Ogando, Ricardo L.C. Plazas Malagón, Andrés Alejandro Reil, Kevin Romer, Anita K. Roodman, Aaron Sanchez-Alvaro, Eusebio Santiago, Basilio Xavier Scarpine, Victor Emanuel Schubnell, Michael Smith, Robert Christopher Soares-Santos, Marcelle Tarle, Gregory Thaler, Jon J. Thomas, D. Vikram, Vinu Walker, Alistair Wester, William Carl Zhang, Yuanyuan 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 author author author author author author author author author author author author author author author author author |
dc.contributor.author.fl_str_mv |
Leistedt, Boris Peiris, Hiranya V. Elsner, Franz Benoit-Lévy, Aurélien Amara, Adam Bauer, Anne Hollister Becker, Matthew R. Bonnett, Christopher Bruderer, Claudio Busha, M. T. Carrasco Kind, Matías Chang, Chihway Crocce, Martin Costa, Luiz N. da Gaztañaga, Enrique Huff, Eric Lahav, Ofer Palmese, A. Percival, Will J. Refregier, Alexandre Ross, A.J. Rozo, Eduardo Rykoff, Eli Sánchez Alonso, Carles Sadeh, Iftach Sevilla Noarbe, Ignacio Sobreira, Flávia Suchyta, Eric Swanson, Molly E. C. Wechsler, Risa H. Abdalla, Filipe B. Allam, Sahar S. Banerji, M. Bernstein, Gary M. Bernstein, Rebecca A. Bertin, Emmanuel Bridle, Sarah Louise Brooks, D. Buckley-Geer, Elizabeth Burke, David Lyle Capozzi, Diego Carnero Rosell, Aurelio Carretero Palacios, Jorge Cunha, Carlos Eduardo D'Andrea, Christopher B. DePoy, Darren L. Desai, S. Diehl, H. Thomas Doel, Peter Eifler, Tim Evrard, August E. Fausti Neto, Angelo Flaugher, Brenna Fosalba Vela, Pablo Frieman, Joshua A. Gerdes, David W. Gruen, Daniel Gruendl, Robert A. Gutierrez, Gaston R. Honscheid, K. James, David J. Jarvis, Michael Kent, Stephen M. Kuehn, Kyler Kuropatkin, Nikolay P. Li, T. S. Lima, Marcos Vinicius Borges Teixeira Maia, Marcio Antonio Geimba March, Marisa Cristina Marshall, Jennifer L. Martini, Paul Melchior, Peter M. Miller, Christopher J. Miquel, Ramon Nichol, Robert C. Nord, Brian Dennis Ogando, Ricardo L.C. Plazas Malagón, Andrés Alejandro Reil, Kevin Romer, Anita K. Roodman, Aaron Sanchez-Alvaro, Eusebio Santiago, Basilio Xavier Scarpine, Victor Emanuel Schubnell, Michael Smith, Robert Christopher Soares-Santos, Marcelle Tarle, Gregory Thaler, Jon J. Thomas, D. Vikram, Vinu Walker, Alistair Wester, William Carl Zhang, Yuanyuan Zuntz, J. |
dc.subject.por.fl_str_mv |
Fotometria astronômica Deslocamento para o vermelho Aglomerados de galaxias Mapeamentos astronômicos |
topic |
Fotometria astronômica Deslocamento para o vermelho Aglomerados de galaxias Mapeamentos astronômicos Cosmology: observations Galaxies: distances and redshifts Galaxies: statistics Large-scale structure of universe |
dc.subject.eng.fl_str_mv |
Cosmology: observations Galaxies: distances and redshifts Galaxies: statistics Large-scale structure of universe |
description |
Spatially varying depth and the characteristics of observing conditions, such as seeing, airmass, or sky background, are major sources of systematic uncertainties in modern galaxy survey analyses, particularly in deep multi-epochsurveys. We present a framework to extract and project these sources of systematics onto the sky, and apply it to the Dark Energy Survey (DES) to map the observing conditions of the Science Verification (SV) data. The resulting distributions and maps of sources of systematics are used in several analyses of DES–SV to perform detailed null tests with the data, and also to incorporate systematics in survey simulations. We illustrate the complementary nature of these two approaches by comparing the SV data with BCC-UFig, a synthetic sky catalog generated by forward-modeling of the DES–SV images We analyze the BCC-UFig simulation to construct galaxy samples mimicking those used in SV galaxy clustering studies. We show that the spatially varying survey depth imprinted in the observed galaxy densities and the redshift distributions of the SV data are successfully reproduced by the simulation and are well-captured by the maps of observing conditions. The combined use of the maps, the SV data, and the BCC-UFig simulation allows us to quantify the impact of spatial systematics on N(z), the redshift distributions inferred using photometric redshifts. We conclude that spatial systematics in the SV data are mainly due to seeing fluctuations and are under control in current clustering and weak-lensing analyses. However, they will need to be carefully characterized in upcoming phases of DES in order to avoid biasing the inferred cosmological results. The framework presented here is relevant to all multi-epoch surveys and will be essential for exploiting future surveys such as the Large Synoptic Survey Telescope, which will require detailed null tests and realistic end-to-end image simulations to correctly interpret the deep, high-cadence observations of the sky. |
publishDate |
2016 |
dc.date.issued.fl_str_mv |
2016 |
dc.date.accessioned.fl_str_mv |
2017-06-20T02:30:23Z |
dc.type.driver.fl_str_mv |
Estrangeiro info:eu-repo/semantics/article |
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info:eu-repo/semantics/publishedVersion |
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article |
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publishedVersion |
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http://hdl.handle.net/10183/159671 |
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0067-0049 |
dc.identifier.nrb.pt_BR.fl_str_mv |
001022682 |
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0067-0049 001022682 |
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http://hdl.handle.net/10183/159671 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartof.pt_BR.fl_str_mv |
The astrophysical journal. Supplement series. Chicago. Vol. 226, no. 2 (Oct. 2016), 24, 13 p. |
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