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Uncovering the birth of the Milky Way through accurate stellar ages with Gaia

Nature Astronomy volume 3, pages 932–939 (2019)Cite this article

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Abstract

Knowledge of the ages of the stars formed over a galaxy’s lifetime is fundamental to an understanding of its formation and evolution. However, stellar ages are difficult to obtain since they cannot be measured from observations, but require comparison with stellar models1. Alternatively, age distributions can be derived by applying the robust technique of colour–magnitude diagram fitting2, which until now has been used primarily to study nearby galaxies. Accurate distances to individual Milky Way stars now provided by the Gaia spacecraft mission3 have allowed us to derive ages from a thick-disk colour–magnitude diagram and from the two-sequenced colour–magnitude diagram of the kinematically hot local halo4, whose blue sequence has been linked to a major accretion event, Gaia-Enceladus5,6. Because accurate stellar ages were lacking, the time of the merger and its role in our Galaxy’s early evolution remained unclear. Here we show that the stars in both halo sequences share identical age distributions, and are older than most of the thick-disk stars. The sharp halo age distribution cutoff at ten billion years ago can be identified with the time of accretion of Gaia-Enceladus to the Milky Way. Together with state-of-the-art cosmological simulations of galaxy formation7, these robust ages allow us to order the early sequence of events that shaped our Galaxy. We identify the red-sequence stars as the first stars formed within the Milky Way progenitor, and their kinematics indicate that these stars constitute the long-sought in situ halo of the Milky Way.

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Fig. 1: Milky Way halo and thick-disk observed and modelled CMDs.
Fig. 2: Milky Way halo and thick-disk stellar age and iron [Fe/H] distributions.
Fig. 3: Age–metallicity relations for the two halo populations compared to a simulated Milky Way analogue.
Fig. 4: Comparison of the stellar kinematics between observations of Milky Way stars and the simulated Milky Way analogue.

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Data availability

All data analysed in this paper are publicly available. They can be retrieved from the DR2 Gaia archive (http://gea.esac.esa.int/archive/) and from the compiled and supplemented GALAH and LAMOST catalogues66, cross-matched as indicated in the Methods. The datasets containing information not available in public catalogues that is necessary to produce the figures can be retrieved from https://zenodo.org/record/3228143#.XRoQs3qH1mM (extended dataset hereafter). A explanatory README file is included. The extended dataset consists of the following files. (1) For Fig. 1a,b, two tables directly retrieved from the Gaia archive as described in the Methods, supplemented by extinction information on a star-by-star basis; the code used to interpolate the three-dimensional extinction maps41 can be retrieved from https://github.com/edober/dust_maps_3d. (2) For Figs. 1c,d, 2 and 3a, two tables with the derived solution CMDs and two files with the data needed to define the boxes used to select stars in the blue and red sequences of the halo CMD. (3) For Fig. 3b, the necessary tables with the age, metallicity and velocity data for the main progenitor and accreted satellite for realization g15784 of the MaGICC program7. The complete information on the final timestep of that simulation, together with scripts to read and plot the data are also included in the extended dataset.

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Acknowledgements

C.G., C.B.B., M.M. and T.R.-L. acknowledge financial support through the grants (AEI/FEDER, UE) AYA2017-89076-P, AYA2016-77237-C3-1-P and AYA2015-63810-P, as well as by the Ministerio de Ciencia, Innovación y Universidades (MCIU), through the State Budget and by the Consejer a de Economia, Industria, Comercio y Conocimiento of the Canary Islands Autonomous Community, through the Regional Budget. T.R.-L. is supported by a MCIU Juan de la Cierva - Formación grant (FJCI-2016-30342). C.B.B. is supported by a MCIU Ramón y Cajal Fellowship (RYC 2013-12784). S.C. acknowledges support from Premiale INAF ‘MITIC’ and has been supported by INFN (Iniziativa specifica TAsP). V.H. was supported by the Programme National Cosmology et Galaxies (PNCG) of CNRS/INSU with INP and IN2P3, co-funded by CEA and CNES. We used data from the European Space Agency mission Gaia (http://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC; see http://www.cosmos.esa.int/web/gaia/dpac/consortium). Funding for DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. We also used data from the LAMOST and GALAH surveys. Guoshoujing Telescope (the Large Sky Area Multi-Object Fiber Spectroscopic Telescope LAMOST) is a National Major Scientific Project built by the Chinese Academy of Sciences. Funding for the project wasprovided by the National Development and Reform Commission. LAMOST is operated and managed by the National Astronomical Observatories, Chinese Academy of Sciences. The GALAH survey is based on observations made at the Australian Astronomical Observatory, under programmes A/2013B/13, A/2014A/25, A/2015A/19 and A/2017A/18. We acknowledge the traditional owners of the land on which the Australian Astronomical Observatory stands, the Gamilaraay people, and pay our respects to elders past and present.

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Authors and Affiliations

  1. Instituto de Astrofísica de Canarias, La Laguna, Spain

    Carme Gallart, Chris B. Brook, Tomás Ruiz-Lara & Matteo Monelli

  2. Departamento de Astrofísica, Universidad de La Laguna, La Laguna, Spain

    Carme Gallart, Chris B. Brook, Tomás Ruiz-Lara & Matteo Monelli

  3. Université Côte d’Azur, Observatoire de la Côte d’Azur, CNRS, Laboratoire Lagrange, Nice, France

    Edouard J. Bernard & Vanessa Hill

  4. INAF – Astronomical Observatory of Abruzzo, Teramo, Italy

    Santi Cassisi

  5. INFN, Sezione di Pisa, Pisa, Italy

    Santi Cassisi

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Contributions

All authors critically contributed to different aspects of the data analysis and model calculation, and to the interpretation of the results. The writing of the manuscript, to which all authors contributed, was led by C.G. and C.B.B. Specifically, C.G. selected the Gaia samples and performed the CMD fitting, E.J.B. helped with the data selection, wrote the CMD fitting software (TheStorm) based on earlier work with M.M. and C.G., and performed the calculation of the three-dimensional interstellar reddening. C.B.B. contributed the galaxy formation models, which were key to the interpretation of the results. T.R.-L. participated in the CMD fitting, contributed key software for various steps such as the error simulation in the synthetic CMDs, and created the figures. S.C. contributed the software to calculate the synthetic CMD, including all the necessary libraries of stellar models and bolometric correction tables for the Gaia photometric passbands. V.H. selected the spectroscopic samples, which were analysed together with T.R.-L.

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Correspondence to Carme Gallart.

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Gallart, C., Bernard, E.J., Brook, C.B. et al. Uncovering the birth of the Milky Way through accurate stellar ages with Gaia. Nat Astron 3, 932–939 (2019). https://doi.org/10.1038/s41550-019-0829-5

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