Detection and Characterisation of H-α Emission Lines from Gaia BP/RP Spectra

Details Detection and Characterisation of H-α Emission Lines from Gaia BP/RP Spectra Detection and Characterisation of H-α Emission Lines from Gaia BP/RP Spectra

Dec 2008

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2008aipc.1082...71j&link_type=abstract

CLASSIFICATION AND DISCOVERY IN LARGE ASTRONOMICAL SURVEYS: Proceedings of the International Conference: ``Classification and Di

Computer Science

Databases

Astronomical Catalogs, Atlases, Sky Surveys, Databases, Retrieval Systems, Archives, Etc., Quasars, Active Or Peculiar Galaxies, Objects, And Systems, Interstellar Medium And Nebulae In Milky Way, Neural Networks

Scientific paper

The Gaia probe, set to launch in 2011, will measure an estimated billion astronomical objects, producing an enormous amount of data. One of the data analysis tasks will be the identification and classification of measured objects. A vast majority of them will be ``ordinary'' stars from our Galaxy but a certain percentage will belong to ``peculiar'' objects. We are interested in detecting emission line stars (ELS). The characteristic feature of most ELS is the presence of a H-α emission line in their spectra. In the case of Gaia measurements, the influence of this line could be detected in low resolution prismatic spectra which will be recorded both in blue (BP) and red (RP) spectral region. In this work, we compare different algorithms for detecting and characterising H-α lines in Gaia spectra. These include a simple, integrated flux ratio-based algorithm and several machine learning algorithms, such as neural networks, support vector machines and support vector regression. We study line detection both from single-transit and over-sampled end-of-mission data.

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