Random Forest identification of the thin disc, thick disc, and halo Gaia-DR2 white dwarf population

• DOI: 10.1093/mnras/stz814
• Publication Date: 2019-03-19T17:05:39Z
• Authors: S Torres; C Cantero; A Rebassa-Mansergas; G Skorobogatov; F M Jiménez-Esteban; E Solano
• Keywords: Proper motion; Thin disk; Parallax; Thick disk

Gaia-DR2 has provided an unprecedented number of white dwarf candidates our Galaxy. In particular, it is estimated that observed nearly 400 000 these objects and close to 18 up 100 pc from the Sun. This large quantity data requires a thorough analysis in order uncover their main Galactic population properties, particular thin thick disc halo components. Taking advantage recent developments artificial intelligence techniques, we make use detailed Random Forest algorithm analyse 8D space (equatorial coordinates, parallax, proper motion components, photometric magnitudes) accurate by within With aid robust synthesis code, simulated different components optimize information extracted for disentangling The first tested known sample achieving accuracy 85.3 per cent. Our methodology thoroughly compared standard methods based on kinematic criteria demonstrating substantially improves previous approaches. Once trained, then applied sample, identifying 12 227 disc, 1410 95 candidates, which represent proportion 74:25:1, respectively. Hence, numerical spatial densities are |$(3.6\pm 0.4)\times 10^{-3}\, {\rm pc^{-3}}$|⁠, |$(1.2\pm |$(4.8\pm 10^{-5}\, pc^{-3}}$| populations thus obtained most complete volume-limited samples date population.