Reddening-Free Q Indices to Identify Be Star Candidates

Astronomical databases currently provide high-volume spectroscopic and photometric data. While spectroscopic data is better suited to the analysis of many astronomical objects, photometric data is relatively easier to obtain due to shorter telescope usage time. Therefore, there is a growing need to...

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Detalles Bibliográficos
Autores principales: Aidelman, Yael Judith, Escudero, Carlos Gabriel, Ronchetti, Franco, Quiroga, Facundo Manuel, Lanzarini, Laura Cristina
Formato: Objeto de conferencia
Lenguaje:Español
Publicado: 2020
Materias:
Ciencias Astronómicas
Ciencias Informáticas
Stellar Classification
OB-type stars
Be stars
VPHAS+
2MASS
IPHAS
SDSS
LAMOST
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/132374
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-132374
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Español
topic Ciencias Astronómicas
Ciencias Informáticas
Stellar Classification
OB-type stars
Be stars
VPHAS+
2MASS
IPHAS
SDSS
LAMOST
spellingShingle Ciencias Astronómicas
Ciencias Informáticas
Stellar Classification
OB-type stars
Be stars
VPHAS+
2MASS
IPHAS
SDSS
LAMOST
Aidelman, Yael Judith
Escudero, Carlos Gabriel
Ronchetti, Franco
Quiroga, Facundo Manuel
Lanzarini, Laura Cristina
Reddening-Free Q Indices to Identify Be Star Candidates
topic_facet Ciencias Astronómicas
Ciencias Informáticas
Stellar Classification
OB-type stars
Be stars
VPHAS+
2MASS
IPHAS
SDSS
LAMOST
description Astronomical databases currently provide high-volume spectroscopic and photometric data. While spectroscopic data is better suited to the analysis of many astronomical objects, photometric data is relatively easier to obtain due to shorter telescope usage time. Therefore, there is a growing need to use photometric information to automatically identify objects for further detailed studies, specially H α emission line stars such as Be stars. Photometric color-color diagrams (CCDs) are commonly used to identify this kind of objects. However, their identification in CCDs is further complicated by the reddening effect caused by both the circumstellar and interstellar gas. This effect prevents the generalization of candidate identification systems. Therefore, in this work we evaluate the use of neural networks to identify Be star candidates from a set of OB-type stars. The networks are trained using a labeled subset of the VPHAS+ and 2MASS databases, with filters u, g, r, Hα, i, J, H , and K. In order to avoid the reddening effect, we propose and evaluate the use of reddening-free Q indices to enhance the generalization of the model to other databases and objects. To test the validity of the approach, we manually labeled a subset of the database, and use it to evaluate candidate identification models. We also labeled an independent dataset for cross dataset evaluation. We evaluate the recall of the models at a 99% precision level on both test sets. Our results show that the proposed features provide a significant improvement over the original filter magnitudes.
format Objeto de conferencia
Objeto de conferencia
author Aidelman, Yael Judith
Escudero, Carlos Gabriel
Ronchetti, Franco
Quiroga, Facundo Manuel
Lanzarini, Laura Cristina
author_facet Aidelman, Yael Judith
Escudero, Carlos Gabriel
Ronchetti, Franco
Quiroga, Facundo Manuel
Lanzarini, Laura Cristina
author_sort Aidelman, Yael Judith
title Reddening-Free Q Indices to Identify Be Star Candidates
title_short Reddening-Free Q Indices to Identify Be Star Candidates
title_full Reddening-Free Q Indices to Identify Be Star Candidates
title_fullStr Reddening-Free Q Indices to Identify Be Star Candidates
title_full_unstemmed Reddening-Free Q Indices to Identify Be Star Candidates
title_sort reddening-free q indices to identify be star candidates
publishDate 2020
url http://sedici.unlp.edu.ar/handle/10915/132374
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AT ronchettifranco reddeningfreeqindicestoidentifybestarcandidates
AT quirogafacundomanuel reddeningfreeqindicestoidentifybestarcandidates
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bdutipo_str Repositorios
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