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Unveiling the distinct formation pathways of the inner and outer discs of the Milky Way with Bayesian Machine Learning

Ciucă, I; Kawata, D; Miglio, A; Davies, GR; Grand, RJJ; (2021) Unveiling the distinct formation pathways of the inner and outer discs of the Milky Way with Bayesian Machine Learning. Monthly Notices of the Royal Astronomical Society , 503 (2) pp. 2814-2824. 10.1093/mnras/stab639. Green open access

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Abstract

We develop a Bayesian Machine Learning framework called BINGO (Bayesian INference for Galactic archaeOlogy) centred around a Bayesian neural network. After being trained on the Apache Point Observatory Galactic Evolution Experiment (APOGEE) and Kepler asteroseismic age data, BINGO is used to obtain precise relative stellar age estimates with uncertainties for the APOGEE stars. We carefully construct a training set to minimize bias and apply BINGO to a stellar population that is similar to our training set. We then select the 17 305 stars with ages from BINGO and reliable kinematic properties obtained from Gaia DR2. By combining the age and chemo-kinematical information, we dissect the Galactic disc stars into three components, namely the thick disc (old, high-[α/Fe], [α/Fe] ≳ 0.12), the thin disc (young, low-[α/Fe]), and the Bridge, which is a region between the thick and thin discs. Our results indicate that the thick disc formed at an early epoch only in the inner region, and the inner disc smoothly transforms to the thin disc. We found that the outer disc follows a different chemical evolution pathway from the inner disc. The outer metal-poor stars only start forming after the compact thick disc phase has completed and the star-forming gas disc extended outwardly with metal-poor gas accretion. We found that in the Bridge region the range of [Fe/H] becomes wider with decreasing age, which suggests that the Bridge region corresponds to the transition phase from the smaller chemically well-mixed thick to a larger thin disc with a metallicity gradient.

Type: Article
Title: Unveiling the distinct formation pathways of the inner and outer discs of the Milky Way with Bayesian Machine Learning
Open access status: An open access version is available from UCL Discovery
DOI: 10.1093/mnras/stab639
Publisher version: https://doi.org/10.1093/mnras/stab639
Language: English
Additional information: Copyright 2021 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Keywords: asteroseismology, Galaxy: abundances, Galaxy: formation
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Space and Climate Physics
URI: https://discovery-pp.ucl.ac.uk/id/eprint/10125453
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