Astronomical image processing from large all-sky photometric surveys for the detection and measurement of type Ia supernovae
"Detection of transient events has become an important research subject in today's astronomy. To detect, report and study such phenomena, different informatics approaches have been proposed, among the most important of these are the image processing pipelines. Using the LSST Science Pipeli...
- Autores:
-
Reyes Gómez, Juan Pablo
- Tipo de recurso:
- Doctoral thesis
- Fecha de publicación:
- 2019
- Institución:
- Universidad de los Andes
- Repositorio:
- Séneca: repositorio Uniandes
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.uniandes.edu.co:1992/41233
- Acceso en línea:
- http://hdl.handle.net/1992/41233
- Palabra clave:
- Gran Telescopio para Rastreos Sinópticos - Investigaciones
Procesamiento de imágenes - Investigaciones - Estudio de casos
SNANA (Programa para computador) - Investigaciones
Supernovas (Astronomía) - Detección - Investigaciones
Astronomía infrarroja - Investigaciones
Ingeniería
- Rights
- openAccess
- License
- https://repositorio.uniandes.edu.co/static/pdf/aceptacion_uso_es.pdf
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dc.title.es_CO.fl_str_mv |
Astronomical image processing from large all-sky photometric surveys for the detection and measurement of type Ia supernovae |
title |
Astronomical image processing from large all-sky photometric surveys for the detection and measurement of type Ia supernovae |
spellingShingle |
Astronomical image processing from large all-sky photometric surveys for the detection and measurement of type Ia supernovae Gran Telescopio para Rastreos Sinópticos - Investigaciones Procesamiento de imágenes - Investigaciones - Estudio de casos SNANA (Programa para computador) - Investigaciones Supernovas (Astronomía) - Detección - Investigaciones Astronomía infrarroja - Investigaciones Ingeniería |
title_short |
Astronomical image processing from large all-sky photometric surveys for the detection and measurement of type Ia supernovae |
title_full |
Astronomical image processing from large all-sky photometric surveys for the detection and measurement of type Ia supernovae |
title_fullStr |
Astronomical image processing from large all-sky photometric surveys for the detection and measurement of type Ia supernovae |
title_full_unstemmed |
Astronomical image processing from large all-sky photometric surveys for the detection and measurement of type Ia supernovae |
title_sort |
Astronomical image processing from large all-sky photometric surveys for the detection and measurement of type Ia supernovae |
dc.creator.fl_str_mv |
Reyes Gómez, Juan Pablo |
dc.contributor.advisor.none.fl_str_mv |
Fouchez, Dominique Hernández Hoyos, Marcela |
dc.contributor.author.none.fl_str_mv |
Reyes Gómez, Juan Pablo |
dc.contributor.jury.none.fl_str_mv |
Forero Romero, Jaime Ernesto Gris, Philippe Ealet, Anne Diaconu, Cristinel Hernández Peñaloza, José Tiberio |
dc.subject.keyword.es_CO.fl_str_mv |
Gran Telescopio para Rastreos Sinópticos - Investigaciones |
topic |
Gran Telescopio para Rastreos Sinópticos - Investigaciones Procesamiento de imágenes - Investigaciones - Estudio de casos SNANA (Programa para computador) - Investigaciones Supernovas (Astronomía) - Detección - Investigaciones Astronomía infrarroja - Investigaciones Ingeniería |
dc.subject.armarc.es_CO.fl_str_mv |
Procesamiento de imágenes - Investigaciones - Estudio de casos SNANA (Programa para computador) - Investigaciones Supernovas (Astronomía) - Detección - Investigaciones Astronomía infrarroja - Investigaciones |
dc.subject.themes.none.fl_str_mv |
Ingeniería |
description |
"Detection of transient events has become an important research subject in today's astronomy. To detect, report and study such phenomena, different informatics approaches have been proposed, among the most important of these are the image processing pipelines. Using the LSST Science Pipelines Stack (or Stack for short), a framework created by the Data Management Team of the Large Synoptic Survey Telescope, we have developed additions to one of these pipelines, focused on supernovae detection on the images from the Canada France Hawaii Telescope. We were able to run a complete pipeline using as input pre-calibrated exposures, performing an image subtraction and then select high quality candidates to be supernovae and transients. We obtained reasonable processing times by parallelizing most stages in the pipeline, and validated the Supernovae-Ia detection using data from the Supernovae Legacy Survey. Finally, we show a reduction of the overall number of source detections up to 80\% the amount in the base pipeline, and we report up to 95\% less light curve candidates, while preserving up to 85\% of Supernovae Ia with high signal present on the same period of time. We also present a simple method to label each detection per object, that allow us to show that the final light curve candidates have a high proportion of positive residuals which can greatly help other transient classification methods."--Tomado del Formato de Documento de Grado. |
publishDate |
2019 |
dc.date.issued.none.fl_str_mv |
2019 |
dc.date.accessioned.none.fl_str_mv |
2020-09-03T08:12:22Z |
dc.date.available.none.fl_str_mv |
2020-09-03T08:12:22Z |
dc.type.spa.fl_str_mv |
Trabajo de grado - Doctorado |
dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
dc.type.coar.spa.fl_str_mv |
http://purl.org/coar/resource_type/c_db06 |
dc.type.content.spa.fl_str_mv |
Text |
dc.type.redcol.spa.fl_str_mv |
http://purl.org/redcol/resource_type/TD |
format |
http://purl.org/coar/resource_type/c_db06 |
dc.identifier.uri.none.fl_str_mv |
http://hdl.handle.net/1992/41233 |
dc.identifier.doi.none.fl_str_mv |
10.57784/1992/41233 |
dc.identifier.pdf.none.fl_str_mv |
u830314.pdf |
dc.identifier.instname.spa.fl_str_mv |
instname:Universidad de los Andes |
dc.identifier.reponame.spa.fl_str_mv |
reponame:Repositorio Institucional Séneca |
dc.identifier.repourl.spa.fl_str_mv |
repourl:https://repositorio.uniandes.edu.co/ |
url |
http://hdl.handle.net/1992/41233 |
identifier_str_mv |
10.57784/1992/41233 u830314.pdf instname:Universidad de los Andes reponame:Repositorio Institucional Séneca repourl:https://repositorio.uniandes.edu.co/ |
dc.language.iso.es_CO.fl_str_mv |
eng |
language |
eng |
dc.rights.uri.*.fl_str_mv |
https://repositorio.uniandes.edu.co/static/pdf/aceptacion_uso_es.pdf |
dc.rights.accessrights.spa.fl_str_mv |
info:eu-repo/semantics/openAccess |
dc.rights.coar.spa.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
rights_invalid_str_mv |
https://repositorio.uniandes.edu.co/static/pdf/aceptacion_uso_es.pdf http://purl.org/coar/access_right/c_abf2 |
eu_rights_str_mv |
openAccess |
dc.format.extent.es_CO.fl_str_mv |
140 hojas |
dc.format.mimetype.es_CO.fl_str_mv |
application/pdf |
dc.publisher.es_CO.fl_str_mv |
Uniandes Aix-Marseille Université, Faculté des Sciences, Ecole Doctorale Physique et Sciences de la Matière |
dc.publisher.program.es_CO.fl_str_mv |
Doctorado en Ingeniería |
dc.publisher.faculty.es_CO.fl_str_mv |
Facultad de Ingeniería |
dc.source.es_CO.fl_str_mv |
instname:Universidad de los Andes reponame:Repositorio Institucional Séneca |
instname_str |
Universidad de los Andes |
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spelling |
Al consultar y hacer uso de este recurso, está aceptando las condiciones de uso establecidas por los autores.https://repositorio.uniandes.edu.co/static/pdf/aceptacion_uso_es.pdfinfo:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Fouchez, Dominiqueb9999750-b389-48f0-8aeb-09ae32200248500Hernández Hoyos, Marcelavirtual::8643-1Reyes Gómez, Juan Pablo11381500Forero Romero, Jaime ErnestoGris, PhilippeEalet, AnneDiaconu, CristinelHernández Peñaloza, José Tiberio2020-09-03T08:12:22Z2020-09-03T08:12:22Z2019http://hdl.handle.net/1992/4123310.57784/1992/41233u830314.pdfinstname:Universidad de los Andesreponame:Repositorio Institucional Sénecarepourl:https://repositorio.uniandes.edu.co/"Detection of transient events has become an important research subject in today's astronomy. To detect, report and study such phenomena, different informatics approaches have been proposed, among the most important of these are the image processing pipelines. Using the LSST Science Pipelines Stack (or Stack for short), a framework created by the Data Management Team of the Large Synoptic Survey Telescope, we have developed additions to one of these pipelines, focused on supernovae detection on the images from the Canada France Hawaii Telescope. We were able to run a complete pipeline using as input pre-calibrated exposures, performing an image subtraction and then select high quality candidates to be supernovae and transients. We obtained reasonable processing times by parallelizing most stages in the pipeline, and validated the Supernovae-Ia detection using data from the Supernovae Legacy Survey. Finally, we show a reduction of the overall number of source detections up to 80\% the amount in the base pipeline, and we report up to 95\% less light curve candidates, while preserving up to 85\% of Supernovae Ia with high signal present on the same period of time. We also present a simple method to label each detection per object, that allow us to show that the final light curve candidates have a high proportion of positive residuals which can greatly help other transient classification methods."--Tomado del Formato de Documento de Grado."La detección de objetos transitorios se ha convertido en un tema importante de investigación en la astronomía de hoy. Para detectar, reportar y estudiar dichos fenómenos, diferentes aproximaciones han sido propuestos, entre ellos, el uso de pipelines de procesamiento de imágenes. Usando el LSST Science Pipelines Stack (o Stack), un framework creado por el equipo de datos del LSST, desarrollamos adiciones a uno de dichos pipelines encargado de la detección de supernovas de tipo IA en las imágenes del telescopio CFHT. Logramos correr un pipeline completo, con tiempos reducidos de procesamiento, logrando una reducción de hasta 80% del número de detección dudosas, reportando 95% curvas de luz candidatas y preservando hasta el 85% de las supernovae Ia con alta señal presente."--Tomado del Formato de Documento de Grado.Doctor en IngenieríaDoctorado140 hojasapplication/pdfengUniandesAix-Marseille Université, Faculté des Sciences, Ecole Doctorale Physique et Sciences de la MatièreDoctorado en IngenieríaFacultad de Ingenieríainstname:Universidad de los Andesreponame:Repositorio Institucional SénecaAstronomical image processing from large all-sky photometric surveys for the detection and measurement of type Ia supernovaeTrabajo de grado - Doctoradoinfo:eu-repo/semantics/doctoralThesishttp://purl.org/coar/resource_type/c_db06http://purl.org/coar/version/c_970fb48d4fbd8a85Texthttp://purl.org/redcol/resource_type/TDGran Telescopio para Rastreos Sinópticos - InvestigacionesProcesamiento de imágenes - Investigaciones - Estudio de casosSNANA (Programa para computador) - InvestigacionesSupernovas (Astronomía) - Detección - InvestigacionesAstronomía infrarroja - InvestigacionesIngenieríaPublicationhttps://scholar.google.es/citations?user=9nnSYmMAAAAJvirtual::8643-1https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000326453virtual::8643-130e973c9-1db4-4731-b61b-bc73c4aceecdvirtual::8643-130e973c9-1db4-4731-b61b-bc73c4aceecdvirtual::8643-1TEXTu830314.pdf.txtu830314.pdf.txtExtracted texttext/plain274063https://repositorio.uniandes.edu.co/bitstreams/cbd0764b-b6d6-4f96-98c8-1087e93ea640/download26d55434f6a5a25757181a5f09a7ede6MD54THUMBNAILu830314.pdf.jpgu830314.pdf.jpgIM Thumbnailimage/jpeg16677https://repositorio.uniandes.edu.co/bitstreams/943caac4-a2b1-4bf7-8761-4732a3e93248/downloadadfe4615b45923d6d219c6d19e7d6c0fMD55ORIGINALu830314.pdfapplication/pdf7761588https://repositorio.uniandes.edu.co/bitstreams/d26f8cd4-3b00-495c-a93a-93598755637a/download488a883df0082d6f0a841d6a7f3531f2MD511992/41233oai:repositorio.uniandes.edu.co:1992/412332024-08-26 15:23:06.928https://repositorio.uniandes.edu.co/static/pdf/aceptacion_uso_es.pdfopen.accesshttps://repositorio.uniandes.edu.coRepositorio institucional Sénecaadminrepositorio@uniandes.edu.co |