Automated Identification of Unresolved Binaries using Medium Band Photometry

Details Automated Identification of Unresolved Binaries using Medium Band Photometry Automated Identification of Unresolved Binaries using Medium Band Photometry

Jan 2005

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2005esasp.576..479w&link_type=abstract

"Proceedings of the Gaia Symposium "The Three-Dimensional Universe with Gaia" (ESA SP-576). Held at the Observatoire de Paris-Me

Physics

Classification, Binary Stars, Gaia

Scientific paper

We have simulated Gaia medium band photometry in the 1X system for (synthetic) binaries and single stars for G = 15 to 20 mag end-of-mission as well as single shot photometry. Each binary is a system of five independent physical parameters (the components' masses M1, M2, age, metallicity and extinction), which translates into six parameters needed to define the binary's spectrum (Teff1 , Teff2 , log g1, log g2, [Fe/H], AV ). To see how the underlying grid of parameters influences the classification, we simulated two sets of binary/single stars. Using an automated classification algorithm known as Support Vector Machine, we show that the capability of correctly identifying binaries is a strong function of the signal to noise ratio and the luminosity ratio of the two components. The maximum of correctly identified binaries is reached at logarithmic luminosity ratios of log(Lr) in the range [0.5;1.0]. For these ratios, correct classification rates better than 70% at G = 15 and 16 mag are possible. The differential analysis for the two different parameter distributions further shows that the underlying grid also strongly influences the classification results.

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