VDES J2325−5229 a z = 2.7 gravitationally lensed quasar discovered using morphology-independent supervised machine learning

Detalhes bibliográficos
Autor(a) principal: Ostrovski, F.
Data de Publicação: 2017
Outros Autores: McMahon, Richard G., Connolly, Andrew J., Lemon, Cameron A., Auger, Matthew W., Banerji, M., Hung, Johnathan M., Koposov, Sergey E., Lidman, Chris, Reed, Sophie L., Allam, Sahar S., Benoit-Lévy, Aurélien, Bertin, Emmanuel, Brooks, D., Buckley-Geer, Elizabeth, Carnero Rosell, Aurelio, Carrasco Kind, Matías, Carretero Palacios, Jorge, Cunha, Carlos Eduardo, Costa, Luiz N. da, Desai, S., Diehl, H. Thomas, Dietrich, Jörg P., Evrard, August E., Finley, David A., Flaugher, Brenna, Fosalba Vela, Pablo, Frieman, Joshua A., Gerdes, David W., Goldstein, Daniel Abraham, Gruen, Daniel, Gruendl, Robert A., Gutierrez, Gaston R., Honscheid, K., James, David J., Kuehn, Kyler, Kuropatkin, Nikolay P., Lima, Marcos Vinicius Borges Teixeira, Lin, H., Maia, Marcio Antonio Geimba, Marshall, Jennifer L., Martini, Paul, Melchior, Peter M., Miquel, Ramon, Ogando, Ricardo L.C., Plazas Malagón, Andrés Alejandro, Reil, Kevin, Romer, Kathy, Sanchez-Alvaro, Eusebio, Santiago, Basilio Xavier, Scarpine, Victor Emanuel, Sevilla Noarbe, Ignacio, Soares-Santos, Marcelle, Sobreira, Flávia, Suchyta, Eric, Tarle, Gregory, Thomas, D., Tucker, Douglas L., Walker, Alistair
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFRGS
Texto Completo: http://hdl.handle.net/10183/159693
Resumo: We present the discovery and preliminary characterization of a gravitationally lensed quasar with a source redshift zs = 2.74 and image separation of 2.9 arcsec lensed by a foreground zl = 0.40 elliptical galaxy. Since optical observations of gravitationally lensed quasars showthe lens system as a superposition of multiple point sources and a foreground lensing galaxy, we have developed a morphology-independent multi-wavelength approach to the photometric selection of lensed quasar candidates based on Gaussian Mixture Models (GMM) supervised machine learning. Using this technique and gi multicolour photometric observations from the Dark Energy Survey (DES), near-IR JK photometry from the VISTA Hemisphere Survey (VHS) and WISE mid-IR photometry, we have identified a candidate system with two catalogue components with iAB = 18.61 and iAB = 20.44 comprising an elliptical galaxy and two blue point sources. Spectroscopic follow-up with NTT and the use of an archival AAT spectrum show that the point sources can be identified as a lensed quasar with an emission line redshift of z = 2.739 ± 0.003 and a foreground early-type galaxy with z = 0.400 ± 0.002.We model the system as a single isothermal ellipsoid and find the Einstein radius θE ∼ 1.47 arcsec, enclosed mass Menc ∼ 4 × 1011 M and a time delay of ∼52 d. The relatively wide separation, month scale time delay duration and high redshift make this an ideal system for constraining the expansion rate beyond a redshift of 1.
id UFRGS-2_70d54be751e27a0c5eaf2119c9315bcd
oai_identifier_str oai:www.lume.ufrgs.br:10183/159693
network_acronym_str UFRGS-2
network_name_str Repositório Institucional da UFRGS
repository_id_str
spelling Ostrovski, F.McMahon, Richard G.Connolly, Andrew J.Lemon, Cameron A.Auger, Matthew W.Banerji, M.Hung, Johnathan M.Koposov, Sergey E.Lidman, ChrisReed, Sophie L.Allam, Sahar S.Benoit-Lévy, AurélienBertin, EmmanuelBrooks, D.Buckley-Geer, ElizabethCarnero Rosell, AurelioCarrasco Kind, MatíasCarretero Palacios, JorgeCunha, Carlos EduardoCosta, Luiz N. daDesai, S.Diehl, H. ThomasDietrich, Jörg P.Evrard, August E.Finley, David A.Flaugher, BrennaFosalba Vela, PabloFrieman, Joshua A.Gerdes, David W.Goldstein, Daniel AbrahamGruen, DanielGruendl, Robert A.Gutierrez, Gaston R.Honscheid, K.James, David J.Kuehn, KylerKuropatkin, Nikolay P.Lima, Marcos Vinicius Borges TeixeiraLin, H.Maia, Marcio Antonio GeimbaMarshall, Jennifer L.Martini, PaulMelchior, Peter M.Miquel, RamonOgando, Ricardo L.C.Plazas Malagón, Andrés AlejandroReil, KevinRomer, KathySanchez-Alvaro, EusebioSantiago, Basilio XavierScarpine, Victor EmanuelSevilla Noarbe, IgnacioSoares-Santos, MarcelleSobreira, FláviaSuchyta, EricTarle, GregoryThomas, D.Tucker, Douglas L.Walker, Alistair2017-06-20T02:30:53Z20170035-8711http://hdl.handle.net/10183/159693001022008We present the discovery and preliminary characterization of a gravitationally lensed quasar with a source redshift zs = 2.74 and image separation of 2.9 arcsec lensed by a foreground zl = 0.40 elliptical galaxy. Since optical observations of gravitationally lensed quasars showthe lens system as a superposition of multiple point sources and a foreground lensing galaxy, we have developed a morphology-independent multi-wavelength approach to the photometric selection of lensed quasar candidates based on Gaussian Mixture Models (GMM) supervised machine learning. Using this technique and gi multicolour photometric observations from the Dark Energy Survey (DES), near-IR JK photometry from the VISTA Hemisphere Survey (VHS) and WISE mid-IR photometry, we have identified a candidate system with two catalogue components with iAB = 18.61 and iAB = 20.44 comprising an elliptical galaxy and two blue point sources. Spectroscopic follow-up with NTT and the use of an archival AAT spectrum show that the point sources can be identified as a lensed quasar with an emission line redshift of z = 2.739 ± 0.003 and a foreground early-type galaxy with z = 0.400 ± 0.002.We model the system as a single isothermal ellipsoid and find the Einstein radius θE ∼ 1.47 arcsec, enclosed mass Menc ∼ 4 × 1011 M and a time delay of ∼52 d. The relatively wide separation, month scale time delay duration and high redshift make this an ideal system for constraining the expansion rate beyond a redshift of 1.application/pdfengMonthly notices of the Royal Astronomical Society. Oxford. Vol. 465, no. 4 (Mar. 2017), p. 4325–4334Lentes gravitacionaisFotometria astronômicaDeslocamento para o vermelhoQuasarsGravitational lensing strongMethods observationalMethods statisticalQuasars generalVDES J2325−5229 a z = 2.7 gravitationally lensed quasar discovered using morphology-independent supervised machine learningEstrangeiroinfo: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:UFRGSORIGINAL001022008.pdf001022008.pdfTexto completo (inglês)application/pdf1324752http://www.lume.ufrgs.br/bitstream/10183/159693/1/001022008.pdf42fe590bea4011d734c2884140a1316eMD51TEXT001022008.pdf.txt001022008.pdf.txtExtracted Texttext/plain53172http://www.lume.ufrgs.br/bitstream/10183/159693/2/001022008.pdf.txtab55fc04bbf87297ca5530edbfd53cf3MD52THUMBNAIL001022008.pdf.jpg001022008.pdf.jpgGenerated Thumbnailimage/jpeg2032http://www.lume.ufrgs.br/bitstream/10183/159693/3/001022008.pdf.jpg0570726d0efaf43c79d819140cd934deMD5310183/1596932023-07-02 03:41:21.033354oai:www.lume.ufrgs.br:10183/159693Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2023-07-02T06:41:21Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false
dc.title.pt_BR.fl_str_mv VDES J2325−5229 a z = 2.7 gravitationally lensed quasar discovered using morphology-independent supervised machine learning
title VDES J2325−5229 a z = 2.7 gravitationally lensed quasar discovered using morphology-independent supervised machine learning
spellingShingle VDES J2325−5229 a z = 2.7 gravitationally lensed quasar discovered using morphology-independent supervised machine learning
Ostrovski, F.
Lentes gravitacionais
Fotometria astronômica
Deslocamento para o vermelho
Quasars
Gravitational lensing strong
Methods observational
Methods statistical
Quasars general
title_short VDES J2325−5229 a z = 2.7 gravitationally lensed quasar discovered using morphology-independent supervised machine learning
title_full VDES J2325−5229 a z = 2.7 gravitationally lensed quasar discovered using morphology-independent supervised machine learning
title_fullStr VDES J2325−5229 a z = 2.7 gravitationally lensed quasar discovered using morphology-independent supervised machine learning
title_full_unstemmed VDES J2325−5229 a z = 2.7 gravitationally lensed quasar discovered using morphology-independent supervised machine learning
title_sort VDES J2325−5229 a z = 2.7 gravitationally lensed quasar discovered using morphology-independent supervised machine learning
author Ostrovski, F.
author_facet Ostrovski, F.
McMahon, Richard G.
Connolly, Andrew J.
Lemon, Cameron A.
Auger, Matthew W.
Banerji, M.
Hung, Johnathan M.
Koposov, Sergey E.
Lidman, Chris
Reed, Sophie L.
Allam, Sahar S.
Benoit-Lévy, Aurélien
Bertin, Emmanuel
Brooks, D.
Buckley-Geer, Elizabeth
Carnero Rosell, Aurelio
Carrasco Kind, Matías
Carretero Palacios, Jorge
Cunha, Carlos Eduardo
Costa, Luiz N. da
Desai, S.
Diehl, H. Thomas
Dietrich, Jörg P.
Evrard, August E.
Finley, David A.
Flaugher, Brenna
Fosalba Vela, Pablo
Frieman, Joshua A.
Gerdes, David W.
Goldstein, Daniel Abraham
Gruen, Daniel
Gruendl, Robert A.
Gutierrez, Gaston R.
Honscheid, K.
James, David J.
Kuehn, Kyler
Kuropatkin, Nikolay P.
Lima, Marcos Vinicius Borges Teixeira
Lin, H.
Maia, Marcio Antonio Geimba
Marshall, Jennifer L.
Martini, Paul
Melchior, Peter M.
Miquel, Ramon
Ogando, Ricardo L.C.
Plazas Malagón, Andrés Alejandro
Reil, Kevin
Romer, Kathy
Sanchez-Alvaro, Eusebio
Santiago, Basilio Xavier
Scarpine, Victor Emanuel
Sevilla Noarbe, Ignacio
Soares-Santos, Marcelle
Sobreira, Flávia
Suchyta, Eric
Tarle, Gregory
Thomas, D.
Tucker, Douglas L.
Walker, Alistair
author_role author
author2 McMahon, Richard G.
Connolly, Andrew J.
Lemon, Cameron A.
Auger, Matthew W.
Banerji, M.
Hung, Johnathan M.
Koposov, Sergey E.
Lidman, Chris
Reed, Sophie L.
Allam, Sahar S.
Benoit-Lévy, Aurélien
Bertin, Emmanuel
Brooks, D.
Buckley-Geer, Elizabeth
Carnero Rosell, Aurelio
Carrasco Kind, Matías
Carretero Palacios, Jorge
Cunha, Carlos Eduardo
Costa, Luiz N. da
Desai, S.
Diehl, H. Thomas
Dietrich, Jörg P.
Evrard, August E.
Finley, David A.
Flaugher, Brenna
Fosalba Vela, Pablo
Frieman, Joshua A.
Gerdes, David W.
Goldstein, Daniel Abraham
Gruen, Daniel
Gruendl, Robert A.
Gutierrez, Gaston R.
Honscheid, K.
James, David J.
Kuehn, Kyler
Kuropatkin, Nikolay P.
Lima, Marcos Vinicius Borges Teixeira
Lin, H.
Maia, Marcio Antonio Geimba
Marshall, Jennifer L.
Martini, Paul
Melchior, Peter M.
Miquel, Ramon
Ogando, Ricardo L.C.
Plazas Malagón, Andrés Alejandro
Reil, Kevin
Romer, Kathy
Sanchez-Alvaro, Eusebio
Santiago, Basilio Xavier
Scarpine, Victor Emanuel
Sevilla Noarbe, Ignacio
Soares-Santos, Marcelle
Sobreira, Flávia
Suchyta, Eric
Tarle, Gregory
Thomas, D.
Tucker, Douglas L.
Walker, Alistair
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
dc.contributor.author.fl_str_mv Ostrovski, F.
McMahon, Richard G.
Connolly, Andrew J.
Lemon, Cameron A.
Auger, Matthew W.
Banerji, M.
Hung, Johnathan M.
Koposov, Sergey E.
Lidman, Chris
Reed, Sophie L.
Allam, Sahar S.
Benoit-Lévy, Aurélien
Bertin, Emmanuel
Brooks, D.
Buckley-Geer, Elizabeth
Carnero Rosell, Aurelio
Carrasco Kind, Matías
Carretero Palacios, Jorge
Cunha, Carlos Eduardo
Costa, Luiz N. da
Desai, S.
Diehl, H. Thomas
Dietrich, Jörg P.
Evrard, August E.
Finley, David A.
Flaugher, Brenna
Fosalba Vela, Pablo
Frieman, Joshua A.
Gerdes, David W.
Goldstein, Daniel Abraham
Gruen, Daniel
Gruendl, Robert A.
Gutierrez, Gaston R.
Honscheid, K.
James, David J.
Kuehn, Kyler
Kuropatkin, Nikolay P.
Lima, Marcos Vinicius Borges Teixeira
Lin, H.
Maia, Marcio Antonio Geimba
Marshall, Jennifer L.
Martini, Paul
Melchior, Peter M.
Miquel, Ramon
Ogando, Ricardo L.C.
Plazas Malagón, Andrés Alejandro
Reil, Kevin
Romer, Kathy
Sanchez-Alvaro, Eusebio
Santiago, Basilio Xavier
Scarpine, Victor Emanuel
Sevilla Noarbe, Ignacio
Soares-Santos, Marcelle
Sobreira, Flávia
Suchyta, Eric
Tarle, Gregory
Thomas, D.
Tucker, Douglas L.
Walker, Alistair
dc.subject.por.fl_str_mv Lentes gravitacionais
Fotometria astronômica
Deslocamento para o vermelho
Quasars
topic Lentes gravitacionais
Fotometria astronômica
Deslocamento para o vermelho
Quasars
Gravitational lensing strong
Methods observational
Methods statistical
Quasars general
dc.subject.eng.fl_str_mv Gravitational lensing strong
Methods observational
Methods statistical
Quasars general
description We present the discovery and preliminary characterization of a gravitationally lensed quasar with a source redshift zs = 2.74 and image separation of 2.9 arcsec lensed by a foreground zl = 0.40 elliptical galaxy. Since optical observations of gravitationally lensed quasars showthe lens system as a superposition of multiple point sources and a foreground lensing galaxy, we have developed a morphology-independent multi-wavelength approach to the photometric selection of lensed quasar candidates based on Gaussian Mixture Models (GMM) supervised machine learning. Using this technique and gi multicolour photometric observations from the Dark Energy Survey (DES), near-IR JK photometry from the VISTA Hemisphere Survey (VHS) and WISE mid-IR photometry, we have identified a candidate system with two catalogue components with iAB = 18.61 and iAB = 20.44 comprising an elliptical galaxy and two blue point sources. Spectroscopic follow-up with NTT and the use of an archival AAT spectrum show that the point sources can be identified as a lensed quasar with an emission line redshift of z = 2.739 ± 0.003 and a foreground early-type galaxy with z = 0.400 ± 0.002.We model the system as a single isothermal ellipsoid and find the Einstein radius θE ∼ 1.47 arcsec, enclosed mass Menc ∼ 4 × 1011 M and a time delay of ∼52 d. The relatively wide separation, month scale time delay duration and high redshift make this an ideal system for constraining the expansion rate beyond a redshift of 1.
publishDate 2017
dc.date.accessioned.fl_str_mv 2017-06-20T02:30:53Z
dc.date.issued.fl_str_mv 2017
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/10183/159693
dc.identifier.issn.pt_BR.fl_str_mv 0035-8711
dc.identifier.nrb.pt_BR.fl_str_mv 001022008
identifier_str_mv 0035-8711
001022008
url http://hdl.handle.net/10183/159693
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. 465, no. 4 (Mar. 2017), p. 4325–4334
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFRGS
instname:Universidade Federal do Rio Grande do Sul (UFRGS)
instacron:UFRGS
instname_str Universidade Federal do Rio Grande do Sul (UFRGS)
instacron_str UFRGS
institution UFRGS
reponame_str Repositório Institucional da UFRGS
collection Repositório Institucional da UFRGS
bitstream.url.fl_str_mv http://www.lume.ufrgs.br/bitstream/10183/159693/1/001022008.pdf
http://www.lume.ufrgs.br/bitstream/10183/159693/2/001022008.pdf.txt
http://www.lume.ufrgs.br/bitstream/10183/159693/3/001022008.pdf.jpg
bitstream.checksum.fl_str_mv 42fe590bea4011d734c2884140a1316e
ab55fc04bbf87297ca5530edbfd53cf3
0570726d0efaf43c79d819140cd934de
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
MD5
repository.name.fl_str_mv Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)
repository.mail.fl_str_mv
_version_ 1798487343735242752