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Unveiling the stellar halo with TGAS
Published online by Cambridge University Press: 07 March 2018
Abstract
The detailed study of the Galactic stellar halo may hold the key to unlocking the assembly history of the Milky Way. Here, we present a machine learning model for selecting metal poor stars from the TGAS catalogue using 5 dimensional phase-space information, coupled with optical and near-IR photometry. We characterise the degree of substructure in our halo sample in the Solar neighbourhood by measuring the velocity correlation function.
- Type
- Contributed Papers
- Information
- Proceedings of the International Astronomical Union , Volume 12 , Symposium S330: Astrometry and Astrophysics in the Gaia sky , April 2017 , pp. 275 - 276
- Copyright
- Copyright © International Astronomical Union 2018