Abstract
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\(\alpha \) 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, H\(\alpha , i, J, H\), 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.
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Notes
- 1.
A color index is defined as the difference of two magnitudes at different wavelengths (\(m_{\lambda _1} - m_{\lambda _2}\)). Magnitude is a unitless measure of the brightness of an object on a logarithmic scale in a defined passband. The brighter an object, the more negative the value of its magnitude.
- 2.
Filter V corresponds to Johnson’s photometric system.
- 3.
The selective absorption coefficient relates the absorption coefficient in the visual, \(A_\mathrm{v}\), with the excess color \(E(B-V)\), through the ratio \(A_\mathrm{v} = R_\mathrm{v}\, E(B-V)\).
- 4.
We note that Purity and Completeness are commonly used as synonyms for Precision and Recall, respectively. These terms are more prevalent in astronomy.
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Acknowledgements
This work is based on data obtained as part of the INT H\(\alpha \) photometric study of the northern galactic plane (IPHAS; https://www.iphas.org), VST Photometric H\(\alpha \) Survey of the Southern Galactic Plane and Bulge (VPHAS+; https://www.vphasplus.org), Two Micron All Sky Survey (2MASS, https://irsa.ipac.caltech.edu/Missions/2mass.html), Sloan Digital Sky Survey (SDSS; https://www.sdss.org) and The Large Sky Area Multi-Object Fibre Spectroscopic Telescope (LAMOST; http://www.lamost.org).
YA is grateful to L. Cidale, G. Baume and A. Smith Castelli for their helpful comments and suggestions.
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Aidelman, Y., Escudero, C., Ronchetti, F., Quiroga, F., Lanzarini, L. (2020). Reddening-Free Q Indices to Identify Be Star Candidates. In: Rucci, E., Naiouf, M., Chichizola, F., De Giusti, L. (eds) Cloud Computing, Big Data & Emerging Topics. JCC-BD&ET 2020. Communications in Computer and Information Science, vol 1291. Springer, Cham. https://doi.org/10.1007/978-3-030-61218-4_8
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