Star/galaxy separation at faint magnitudes : application to a simulated Dark Energy Survey
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , , , , , , , , , , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRGS |
Texto Completo: | http://hdl.handle.net/10183/126984 |
Resumo: | We address the problem of separating stars from galaxies in future large photometric surveys. We focus our analysis on simulations of the Dark Energy Survey (DES). In the first part of the paper, we derive the science requirements on star/galaxy separation, for measurement of the cosmological parameters with the gravitational weak lensing and large-scale structure probes. These requirements are dictated by the need to control both the statistical and systematic errors on the cosmological parameters, and by point spread function calibration. We formulate the requirements in terms of the completeness and purity provided by a given star/galaxy classifier. In order to achieve these requirements at faint magnitudes, we propose a new method for star/galaxy separation in the second part of the paper.We first use principal component analysis to outline the correlations between the objects parameters and extract from it the most relevant information.We then use the reduced set of parameters as input to an Artificial Neural Network. This multiparameter approach improves upon purely morphometric classifiers (such as the classifier implemented in SEXTRACTOR), especially at faint magnitudes: it increases the purity by up to 20 per cent for stars and by up to 12 per cent for galaxies, at i-magnitude fainter than 23. |
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Soumagnac, Maayane TamarAbdalla, Filipe B.Lahav, OferKirk, DonnachaSevilla Noarbe, IgnacioBertin, EmmanuelRowe, Barnaby T. P.Annis, James T.Busha, M. T.Costa, Luiz N. daFrieman, Joshua A.Gaztañaga, EnriqueJarvis, MichaelLin, H.Percival, Will J.Santiago, Basilio XavierSabiu, Cristiano GiovanniWechsler, Risa H.Wolz, LauraYanny, Brian2015-09-18T01:58:29Z20150035-8711http://hdl.handle.net/10183/126984000973413We address the problem of separating stars from galaxies in future large photometric surveys. We focus our analysis on simulations of the Dark Energy Survey (DES). In the first part of the paper, we derive the science requirements on star/galaxy separation, for measurement of the cosmological parameters with the gravitational weak lensing and large-scale structure probes. These requirements are dictated by the need to control both the statistical and systematic errors on the cosmological parameters, and by point spread function calibration. We formulate the requirements in terms of the completeness and purity provided by a given star/galaxy classifier. In order to achieve these requirements at faint magnitudes, we propose a new method for star/galaxy separation in the second part of the paper.We first use principal component analysis to outline the correlations between the objects parameters and extract from it the most relevant information.We then use the reduced set of parameters as input to an Artificial Neural Network. This multiparameter approach improves upon purely morphometric classifiers (such as the classifier implemented in SEXTRACTOR), especially at faint magnitudes: it increases the purity by up to 20 per cent for stars and by up to 12 per cent for galaxies, at i-magnitude fainter than 23.application/pdfengMonthly notices of the Royal Astronomical Society. Oxford. Vol. 450, no. 1 (June 2015), p. 666-680CosmologiaGaláxiasEnergia escuraMapeamentos astronômicosLentes gravitacionaisGravitational lensing: weakMethods: data analysisSurveysCosmology: observationsDark energyLargeScale structure of universeStar/galaxy separation at faint magnitudes : application to a simulated Dark Energy SurveyEstrangeiroinfo: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:UFRGSORIGINAL000973413.pdf000973413.pdfTexto completo (inglês)application/pdf1797603http://www.lume.ufrgs.br/bitstream/10183/126984/1/000973413.pdf17c000c59ab81346c382fa09e480a7f3MD51TEXT000973413.pdf.txt000973413.pdf.txtExtracted Texttext/plain77396http://www.lume.ufrgs.br/bitstream/10183/126984/2/000973413.pdf.txt66ab95c0a9baef28a8b4e638422215a9MD52THUMBNAIL000973413.pdf.jpg000973413.pdf.jpgGenerated Thumbnailimage/jpeg2117http://www.lume.ufrgs.br/bitstream/10183/126984/3/000973413.pdf.jpgdc3d6b56849f1aa7011edc0e5c5ef897MD5310183/1269842023-07-02 03:41:41.411566oai:www.lume.ufrgs.br:10183/126984Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2023-07-02T06:41:41Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false |
dc.title.pt_BR.fl_str_mv |
Star/galaxy separation at faint magnitudes : application to a simulated Dark Energy Survey |
title |
Star/galaxy separation at faint magnitudes : application to a simulated Dark Energy Survey |
spellingShingle |
Star/galaxy separation at faint magnitudes : application to a simulated Dark Energy Survey Soumagnac, Maayane Tamar Cosmologia Galáxias Energia escura Mapeamentos astronômicos Lentes gravitacionais Gravitational lensing: weak Methods: data analysis Surveys Cosmology: observations Dark energy Large Scale structure of universe |
title_short |
Star/galaxy separation at faint magnitudes : application to a simulated Dark Energy Survey |
title_full |
Star/galaxy separation at faint magnitudes : application to a simulated Dark Energy Survey |
title_fullStr |
Star/galaxy separation at faint magnitudes : application to a simulated Dark Energy Survey |
title_full_unstemmed |
Star/galaxy separation at faint magnitudes : application to a simulated Dark Energy Survey |
title_sort |
Star/galaxy separation at faint magnitudes : application to a simulated Dark Energy Survey |
author |
Soumagnac, Maayane Tamar |
author_facet |
Soumagnac, Maayane Tamar Abdalla, Filipe B. Lahav, Ofer Kirk, Donnacha Sevilla Noarbe, Ignacio Bertin, Emmanuel Rowe, Barnaby T. P. Annis, James T. Busha, M. T. Costa, Luiz N. da Frieman, Joshua A. Gaztañaga, Enrique Jarvis, Michael Lin, H. Percival, Will J. Santiago, Basilio Xavier Sabiu, Cristiano Giovanni Wechsler, Risa H. Wolz, Laura Yanny, Brian |
author_role |
author |
author2 |
Abdalla, Filipe B. Lahav, Ofer Kirk, Donnacha Sevilla Noarbe, Ignacio Bertin, Emmanuel Rowe, Barnaby T. P. Annis, James T. Busha, M. T. Costa, Luiz N. da Frieman, Joshua A. Gaztañaga, Enrique Jarvis, Michael Lin, H. Percival, Will J. Santiago, Basilio Xavier Sabiu, Cristiano Giovanni Wechsler, Risa H. Wolz, Laura Yanny, Brian |
author2_role |
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 |
Soumagnac, Maayane Tamar Abdalla, Filipe B. Lahav, Ofer Kirk, Donnacha Sevilla Noarbe, Ignacio Bertin, Emmanuel Rowe, Barnaby T. P. Annis, James T. Busha, M. T. Costa, Luiz N. da Frieman, Joshua A. Gaztañaga, Enrique Jarvis, Michael Lin, H. Percival, Will J. Santiago, Basilio Xavier Sabiu, Cristiano Giovanni Wechsler, Risa H. Wolz, Laura Yanny, Brian |
dc.subject.por.fl_str_mv |
Cosmologia Galáxias Energia escura Mapeamentos astronômicos Lentes gravitacionais |
topic |
Cosmologia Galáxias Energia escura Mapeamentos astronômicos Lentes gravitacionais Gravitational lensing: weak Methods: data analysis Surveys Cosmology: observations Dark energy Large Scale structure of universe |
dc.subject.eng.fl_str_mv |
Gravitational lensing: weak Methods: data analysis Surveys Cosmology: observations Dark energy Large Scale structure of universe |
description |
We address the problem of separating stars from galaxies in future large photometric surveys. We focus our analysis on simulations of the Dark Energy Survey (DES). In the first part of the paper, we derive the science requirements on star/galaxy separation, for measurement of the cosmological parameters with the gravitational weak lensing and large-scale structure probes. These requirements are dictated by the need to control both the statistical and systematic errors on the cosmological parameters, and by point spread function calibration. We formulate the requirements in terms of the completeness and purity provided by a given star/galaxy classifier. In order to achieve these requirements at faint magnitudes, we propose a new method for star/galaxy separation in the second part of the paper.We first use principal component analysis to outline the correlations between the objects parameters and extract from it the most relevant information.We then use the reduced set of parameters as input to an Artificial Neural Network. This multiparameter approach improves upon purely morphometric classifiers (such as the classifier implemented in SEXTRACTOR), especially at faint magnitudes: it increases the purity by up to 20 per cent for stars and by up to 12 per cent for galaxies, at i-magnitude fainter than 23. |
publishDate |
2015 |
dc.date.accessioned.fl_str_mv |
2015-09-18T01:58:29Z |
dc.date.issued.fl_str_mv |
2015 |
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 |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10183/126984 |
dc.identifier.issn.pt_BR.fl_str_mv |
0035-8711 |
dc.identifier.nrb.pt_BR.fl_str_mv |
000973413 |
identifier_str_mv |
0035-8711 000973413 |
url |
http://hdl.handle.net/10183/126984 |
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. 450, no. 1 (June 2015), p. 666-680 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
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application/pdf |
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