FGK and M dwarfs/giants photometric segregation using ML and SVO photometric tools
- 1. Centro de Astrobiología (CAB), CSIC-INTA
- 2. Universidad Militar Nueva Granada, Colombia
- 3. PhD Programme in Astrophysics, Doctoral School, Universidad Autónoma de Madrid
- 4. Observatorio Astronómico Nacional (OAN)
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5.
European Southern Observatory
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6.
Universidad Complutense de Madrid
Description
The Spanish Virtual Observatory (SVO) Filter Profile Service delivers information about photometric filters that have been very useful for the astronomical community in recent years, in research fields ranging from Solar System objects to cosmology. In this work, we explored the potential of adding ML to manage VO data, and compared results with a classical approach. For that, we used the Filter Profile Service and other SVO photometric tools to segregate between dwarfs and giants among FGK and M stars, using J-PAS narrow filters and by adopting machine learning techniques as the Gaussian mixture model and support vector machine. We optimised the separation between luminosity classes, reaching accuracies that classical approach could not deliver.
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Additional details
References
- Allard et al., 2011, arXiv:1011.5405
- Bayo et al., 2008, A&A, 492, 277
- Bonoli et al., 2021, A&A, 653, A31
- Gaia Collaboration et al., 2022, arXiv:2208.00211
- Rodrigo et al., 2024, arXiv:2406.03310