Abstract
The assembly of our Galaxy can be reconstructed using the motions and chemistry of individual stars1,2. Chemo-dynamical studies of the stellar halo near the Sun have indicated the presence of multiple components3, such as streams4 and clumps5, as well as correlations between the stars’ chemical abundances and orbital parameters6–8. Recently, analyses of two large stellar surveys9,10 revealed the presence of a well populated elemental abundance sequence7,11, two distinct sequences in the colour–magnitude diagram12 and a prominent, slightly retrograde kinematic structure13,14 in the halo near the Sun, which may trace an important accretion event experienced by the Galaxy15. However, the link between these observations and their implications for Galactic history is not well understood. Here we report an analysis of the kinematics, chemistry, age and spatial distribution of stars that are mainly linked to two major Galactic components: the thick disk and the stellar halo. We demonstrate that the inner halo is dominated by debris from an object that at infall was slightly more massive than the Small Magellanic Cloud, and which we refer to as Gaia–Enceladus. The stars that originate in Gaia–Enceladus cover nearly the full sky, and their motions reveal the presence of streams and slightly retrograde and elongated trajectories. With an estimated mass ratio of four to one, the merger of the Milky Way with Gaia–Enceladus must have led to the dynamical heating of the precursor of the Galactic thick disk, thus contributing to the formation of this component approximately ten billion years ago. These findings are in line with the results of galaxy formation simulations, which predict that the inner stellar halo should be dominated by debris from only a few massive progenitors2,16.
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Acknowledgements
We are grateful to Á. Villalobos for permission to use his suite of simulations, and to M. Breddels for the software package Vaex (http://vaex.astro.rug.nl), which was used for part of our analyses. We thank H.-W. Rix, D. Hogg and A. Price-Whelan for comments. We have made use of 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 APOGEE survey— a part of Sloan Digital Sky Survey IV, which is managed by the Astrophysical Research Consortium for the Participating Institutions of the Sloan Digital Sky Survey (SDSS) Collaboration (http://www.sdss.org). A.H., H.H.K., D.M. and J.V. acknowledge financial support from a Vici grant from the Netherlands Organisation for Scientific Research (NWO) and A.G.A.B. from the Netherlands Research School for Astronomy (NOVA).
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Nature thanks T. C. Beers, K. V. Johnston and K. Venn for their contribution to the peer review of this work.
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All the authors contributed to the work. A.H. led and contributed to all aspects of the analysis and wrote the manuscript. C.B. compiled the APOGEE data, provided the cross-match to the Gaia data, was involved in the chemical abundance analysis and, together with D.M., analysed the HRD. H.H.K. and J.V. carried out the dynamical analysis and identification of member stars. A.G.A.B. proposed the preparation of this paper, explored the impact of the selection effects and contributed to the writing of the paper, together with the other co-authors.
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Extended data figures and tables
Extended Data Fig. 1 Slices of phase space used to isolate Gaia–Enceladus stars.
a, Energy E versus angular momentum Lz for stars in the 6D Gaia dataset that satisfy the quality criteria described in the text, with ϖ > 0.2 mas (5 kpc from the Sun) and |V − VLSR| > 210 km s−1. The dashed lines indicate the criteria used to select Gaia–Enceladus stars, namely, −1,500 kpc km s−1 < Lz < 150 kpc km s−1 and E > −1.8 × 105 km2 s−2. These criteria follow roughly the structure’s shape (for comparison, see Extended Data Fig. 3b) but are slightly conservative for the upper limit of Lz to prevent too much contamination by the thick disk. However, small shifts—such as those obtained by considering an upper limit of 250 kpc km s−1 or a lower limit of −750 kpc km s−1 for Lz, or E > −2 × 105 km2 s−2—do not result in drastic changes to the results presented in the paper. The colour scale indicates the logarithm of the counts in the bins, with red corresponding to the highest number of counts, yellow and blue to 1/6th and 1/30th of this value, respectively, and purple to empty bins. b, Angular momentum Lz versus the Galactocentric distance R for all stars in the 6D Gaia with ϖ > 0.2 mas. The black points are the halo-star sample shown in a. c, Same as b, but for star particles in the merger simulation18 shown in Fig. 1b. Blue points correspond to stars from the satellite and grey points to the host disk, and the positions and velocities have been scaled as described in the text. In this figure, E, Lz and R have been scaled by the energy (Esun = −1.63 × 105 km2 s−2 in the Galactic potential used), angular momentum (Lz,sun = 1,902.4 kpc km s−1) and Galactocentric distance (Rsun = 8.2 kpc) of the Sun, respectively.
Extended Data Fig. 2 Effect of a zero-point offset in the parallax on Lz.
a, Distribution of the difference between the initial (Lz(init)) and ‘measured’ (Lz(obs); after error convolution) z-angular momentum for stars from the GUMS model with ‘measured’ distances between 5 and 10 kpc and with galactic longitude l = (−60°, −20°). b, Mean value of the difference over the full sky.
Extended Data Fig. 3 Dynamical properties of stars for a smooth dataset.
a, b, Velocity (a) and E–Lz (b) distribution, for a dataset obtained by reshuffling the velocities of the stars plotted in Fig. 1a and in Extended Data Fig. 1a, respectively. Visual comparison to those figures shows that these random sets are less clumped than the observed distributions of the Gaia halo stars. Lz and E in b are scaled as in Extended Data Fig. 1, and the colour scale indicates the logarithm of the counts in the bins, with dark red corresponding to the highest number of counts, yellow and blue to 1/5th and 1/15th of this value, respectively, and purple to empty bins.
Extended Data Fig. 4 Distribution of angles between proper-motion vectors for neighbouring stars in the sky.
The blue and red histograms correspond to Gaia–Enceladus stars and a mock dataset, respectively. This mock dataset uses the positions of the stars in Gaia–Enceladus, but velocities generated randomly according to a multivariate Gaussian distribution43; only velocities that satisfy −1,500 kpc km s−1 < Lz < 150 kpc km s−1 are kept in the mock dataset, as in the real data. For each star, we find its nearest neighbour in the sky and then determine the angle ∆θ between their proper-motion vectors for the data and for the mock dataset. We then count the number of such pairs with a given angle ∆θ.
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Helmi, A., Babusiaux, C., Koppelman, H.H. et al. The merger that led to the formation of the Milky Way’s inner stellar halo and thick disk. Nature 563, 85–88 (2018). https://doi.org/10.1038/s41586-018-0625-x
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DOI: https://doi.org/10.1038/s41586-018-0625-x
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