Projects per year
Abstract
Large stellar surveys are revealing the chemodynamical structure of the Galaxy across a vast spatial extent. However, the many millions of low- resolution spectra observed to date are yet to be fully exploited. We employ The Cannon, a data-driven approach for estimating chemical abundances, to obtain detailed abundances from low-resolution (R = 1800) LAMOST spectra, using the GALAH survey as our reference. We deliver five (for dwarfs) or six (for giants) estimated abundances representing five different nucleosynthetic channels, for 3.9 million stars, to a precision of 0.05-0.23 dex. Using wide binary pairs, we demonstrate that our abundance estimates provide chemical discriminating power beyond metallicity alone. We show the coverage of our catalog with radial, azimuthal and dynamical abundance maps and examine the neutron capture abundances across the disk and halo, which indicate different origins for the in situ and accreted halo populations. LAMOST has near-complete Gaia coverage and provides an unprecedented perspective on chemistry across the Milky Way.
Original language | English |
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Article number | 58 |
Pages (from-to) | 1-20 |
Number of pages | 20 |
Journal | Astrophysical Journal |
Volume | 898 |
Issue number | 1 |
DOIs | |
Publication status | Published - 23 Jul 2020 |
Bibliographical note
Copyright 2020 The American Astronomical Society. First published in the Astrophysical Journal, 898(1), 58, 2020. The original publication is available at https://doi.org/10.3847/1538-4357/ab9a46, published by IOP Publishing. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.Fingerprint
Dive into the research topics of 'Abundances in the Milky Way across five nucleosynthetic channels from 4 million LAMOST stars'. Together they form a unique fingerprint.Projects
- 1 Finished
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Tracing the accretion history of the Milky Way with chemical tagging
Zucker, D., Martell, S. & Venn, K.
14/01/18 → 13/01/21
Project: Research