Using the PLC and modern algorithms to detect clustering and associations in nearby galaxies

Autores
Feinstein Baigorri, Carlos; Baume, Gustavo Luis; Rodríguez, María Jimena; Vergne, María Marcela
Año de publicación
2017
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
The Hubble Space Telescope (HST) is not affected by the atmospheric seeing, bringing observations that have an amazing spatial resolution that allows us to isolate the individual stars in nearby galaxies. In consequence, to have good photometry of large samples of stars in these objects. Therefore, high accuracy studies of extragalactic stellar associations and clusters could be done. One of most powerful algorithm for detecting clustering in a large amount of data is the Path Linkage Criterion (PLC), Battinelli (1991). We show in this work the results of our implementation of a high speed version of the PLC that was applied to HST data of two galaxies: NGC 300 and NGC 253. Also, we show the results obtained with PLC and others popular methods found in the literature of clustering, applied to the real data and to simulated data.
Instituto de Astrofísica de La Plata
Materia
Ciencias Astronómicas
Path Linkage Criterion
Hubble Space Telescope
Galaxies
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/155357
Acceder
id SEDICI_75eefefaef061f35781d45cae6b41795
oai_identifier_str oai:sedici.unlp.edu.ar:10915/155357
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Using the PLC and modern algorithms to detect clustering and associations in nearby galaxiesFeinstein Baigorri, CarlosBaume, Gustavo LuisRodríguez, María JimenaVergne, María MarcelaCiencias AstronómicasPath Linkage CriterionHubble Space TelescopeGalaxiesThe Hubble Space Telescope (HST) is not affected by the atmospheric seeing, bringing observations that have an amazing spatial resolution that allows us to isolate the individual stars in nearby galaxies. In consequence, to have good photometry of large samples of stars in these objects. Therefore, high accuracy studies of extragalactic stellar associations and clusters could be done. One of most powerful algorithm for detecting clustering in a large amount of data is the Path Linkage Criterion (PLC), Battinelli (1991). We show in this work the results of our implementation of a high speed version of the PLC that was applied to HST data of two galaxies: NGC 300 and NGC 253. Also, we show the results obtained with PLC and others popular methods found in the literature of clustering, applied to the real data and to simulated data.Instituto de Astrofísica de La Plata2017-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf549-551http://sedici.unlp.edu.ar/handle/10915/155357enginfo:eu-repo/semantics/altIdentifier/isbn/978-1-58381-932-6info:eu-repo/semantics/altIdentifier/url/http://www.aspbooks.org/publications/522/549.pdfinfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-22T17:21:15Zoai:sedici.unlp.edu.ar:10915/155357Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-22 17:21:15.756SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Using the PLC and modern algorithms to detect clustering and associations in nearby galaxies
title Using the PLC and modern algorithms to detect clustering and associations in nearby galaxies
spellingShingle Using the PLC and modern algorithms to detect clustering and associations in nearby galaxies
Feinstein Baigorri, Carlos
Ciencias Astronómicas
Path Linkage Criterion
Hubble Space Telescope
Galaxies
title_short Using the PLC and modern algorithms to detect clustering and associations in nearby galaxies
title_full Using the PLC and modern algorithms to detect clustering and associations in nearby galaxies
title_fullStr Using the PLC and modern algorithms to detect clustering and associations in nearby galaxies
title_full_unstemmed Using the PLC and modern algorithms to detect clustering and associations in nearby galaxies
title_sort Using the PLC and modern algorithms to detect clustering and associations in nearby galaxies
dc.creator.none.fl_str_mv Feinstein Baigorri, Carlos
Baume, Gustavo Luis
Rodríguez, María Jimena
Vergne, María Marcela
author Feinstein Baigorri, Carlos
author_facet Feinstein Baigorri, Carlos
Baume, Gustavo Luis
Rodríguez, María Jimena
Vergne, María Marcela
author_role author
author2 Baume, Gustavo Luis
Rodríguez, María Jimena
Vergne, María Marcela
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Astronómicas
Path Linkage Criterion
Hubble Space Telescope
Galaxies
topic Ciencias Astronómicas
Path Linkage Criterion
Hubble Space Telescope
Galaxies
dc.description.none.fl_txt_mv The Hubble Space Telescope (HST) is not affected by the atmospheric seeing, bringing observations that have an amazing spatial resolution that allows us to isolate the individual stars in nearby galaxies. In consequence, to have good photometry of large samples of stars in these objects. Therefore, high accuracy studies of extragalactic stellar associations and clusters could be done. One of most powerful algorithm for detecting clustering in a large amount of data is the Path Linkage Criterion (PLC), Battinelli (1991). We show in this work the results of our implementation of a high speed version of the PLC that was applied to HST data of two galaxies: NGC 300 and NGC 253. Also, we show the results obtained with PLC and others popular methods found in the literature of clustering, applied to the real data and to simulated data.
Instituto de Astrofísica de La Plata
description The Hubble Space Telescope (HST) is not affected by the atmospheric seeing, bringing observations that have an amazing spatial resolution that allows us to isolate the individual stars in nearby galaxies. In consequence, to have good photometry of large samples of stars in these objects. Therefore, high accuracy studies of extragalactic stellar associations and clusters could be done. One of most powerful algorithm for detecting clustering in a large amount of data is the Path Linkage Criterion (PLC), Battinelli (1991). We show in this work the results of our implementation of a high speed version of the PLC that was applied to HST data of two galaxies: NGC 300 and NGC 253. Also, we show the results obtained with PLC and others popular methods found in the literature of clustering, applied to the real data and to simulated data.
publishDate 2017
dc.date.none.fl_str_mv 2017-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/155357
url http://sedici.unlp.edu.ar/handle/10915/155357
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/isbn/978-1-58381-932-6
info:eu-repo/semantics/altIdentifier/url/http://www.aspbooks.org/publications/522/549.pdf
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
549-551
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
_version_ 1846783643235647488
score 12.982451

Publicaciones similares