Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Evidence for a vast prograde stellar stream in the solar vicinity

Nature Astronomy volume 4, pages 1078–1083 (2020)Cite this article

Subjects

An Author Correction to this article was published on 18 May 2022

This article has been updated

Abstract

Massive dwarf galaxies that merge with the Milky Way on prograde orbits can be dragged into the disk plane before being completely disrupted. Such mergers can contribute to an accreted stellar disk and a dark matter disk. Here we present Nyx, a vast stellar stream in the vicinity of the Sun, which provides the first indication that such an event occurred in the Milky Way. We identify about 90 stars that have coherent radial and prograde motion in this stream using a catalogue of accreted stars built by applying deep learning methods to the Gaia data. Taken together with chemical abundance and orbital information, these results strongly favour the interpretation that Nyx is the remnant of a disrupted dwarf galaxy. Further justified by FIRE hydrodynamic simulations, we demonstrate that prograde streams like Nyx can be found in the disk plane of galaxies and identified using our methods.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Dynamics of the Nyx stars.
Fig. 2: Chemical abundances of the Nyx stars.
Fig. 3: Colour–magnitude diagram of the Nyx stars.
Fig. 4: Example prograde stellar stream in a simulated Milky Way galaxy.

Data availability

The accreted star catalogue used for this analysis is available at https://doi.org/10.5281/zenodo.3579379. The simulation m12f is available at https://fire.northwestern.edu/ananke/. The IDs of the Nyx stars are available as a Supplementary Data file.

Code availability

This analysis makes use of emcee and the extreme deconvolution for the Gaussian mixture model. The Python Markov chain Monte Carlo code emcee is freely available and documented at http://dfm.io/emcee/current/. Extreme deconvolution is freely available at https://github.com/jobovy/extreme-deconvolution. Details regarding the application of these two public codes are provided in ref. 22.

Change history

References

  1. White, S. D. M. & Rees, M. J. Core condensation in heavy halos: a two-stage theory for galaxy formation and clustering. Mon. Not. R. Astron. Soc. 183, 341–358 (1978).

    ADS  Google Scholar 

  2. Johnston, K. V., Hernquist, L. & Bolte, M. Fossil signatures of ancient accretion events in the halo. Astrophys. J. 465, 278–287 (1996).

    ADS  Google Scholar 

  3. Newberg, H. J. & Carlin, J. L. (eds) Tidal Streams in the Local Group and Beyond (Springer, 2016).

  4. Quinn, P. J. & Goodman, J. Sinking satellites of spiral systems. Astrophys. J. 309, 472–495 (1986).

    ADS  Google Scholar 

  5. Walker, I. R., Mihos, J. C. & Hernquist, L. Quantifying the fragility of Galactic Disks in minor mergers. Astrophys. J. 460, 121–135 (1996).

    ADS  Google Scholar 

  6. Read, J. I., Lake, G., Agertz, O. & Debattista, V. P. Thin, thick and dark discs in Λ CDM. Mon. Not. R. Astron. Soc. 389, 1041–1057 (2008).

    ADS  Google Scholar 

  7. Hopkins, P. F., Cox, T. J., Younger, J. D. & Hernquist, L. How do disks survive mergers? Astrophys. J. 691, 1168–1201 (2009).

    ADS  Google Scholar 

  8. Read, J. I., Mayer, L., Brooks, A. M., Governato, F. & Lake, G. A dark matter disc in three cosmological simulations of Milky Way mass galaxies. Mon. Not. R. Astron. Soc. 397, 44–51 (2009).

    ADS  Google Scholar 

  9. Purcell, C. W., Bullock, J. S. & Kaplinghat, M. The dark disk of the Milky Way. Astrophys. J. 703, 2275–2284 (2009).

    ADS  Google Scholar 

  10. Ling, F. S., Nezri, E., Athanassoula, E. & Teyssier, R. Dark matter direct detection signals inferred from a cosmological N-body simulation with baryons. J. Cosmol. Astropart. Phys. 2010, 012 (2010).

    Google Scholar 

  11. Pillepich, A., Kuhlen, M., Guedes, J. & Madau, P. The distribution of dark matter in the Milky Way’s disk. Astrophys. J. 784, 161 (2014).

    ADS  Google Scholar 

  12. Gómez, F. A. et al. Lessons from the Auriga discs: the hunt for the Milky Way as ex situ disc is not yet over. Mon. Not. R. Astron. Soc. 472, 3722–3733 (2017).

    ADS  Google Scholar 

  13. Ruchti, G. R. et al. The Gaia-ESO survey: a quiescent Milky Way with no significant dark/stellar accreted disc. Mon. Not. R. Astron. Soc. 450, 2874–2887 (2015).

    ADS  Google Scholar 

  14. Ostdiek, B. et al. Cataloging accreted stars within Gaia DR2 using deep learning. Astron. Astrophys. 636, A75 (2020).

    Google Scholar 

  15. Brown, A. G. A. et al. Gaia data release 2. Summary of the contents and survey properties. Astron. Astrophys. 616, A1 (2018).

    Google Scholar 

  16. Sanderson, R. E. et al. Synthetic Gaia surveys from the FIRE cosmological simulations of Milky Way-mass galaxies. Astrophys. J. Suppl. 246, 6 (2020).

    ADS  Google Scholar 

  17. Wetzel, A. R. et al. Reconciling dwarf galaxies with Λ CDM cosmology: simulating a realistic population of satellites around a Milky Way-mass galaxy. Astrophys. J. 827, L23 (2016).

    ADS  Google Scholar 

  18. Hopkins, P. F., Narayanan, D. & Murray, N. The meaning and consequences of star formation criteria in galaxy models with resolved stellar feedback. Mon. Not. R. Astron. Soc. 432, 2647–2653 (2013).

    ADS  Google Scholar 

  19. Hopkins, P. F. et al. FIRE-2 simulations: physics versus numerics in galaxy formation. Mon. Not. R. Astron. Soc. 480, 800–863 (2018).

    ADS  Google Scholar 

  20. Necib, L. et al. Under the FIRElight: stellar tracers of the local dark matter velocity distribution in the Milky Way. Astrophys. J. 883, 27 (2019).

    ADS  Google Scholar 

  21. Kunder, A. et al. The Radial Velocity Experiment (RAVE): fifth data release. Astron. J. 153, 75 (2017).

    ADS  Google Scholar 

  22. Necib, L. et al. Chasing accreted structures within Gaia DR2 using deep learning. Preprint at https://arxiv.org/abs/1907.07681 (2019).

  23. Antoja, T., Figueras, F., Torra, J., Valenzuela, O. & Pichardo, B. in Lecture Notes and Essays in Astrophysics Vol. 4 (eds Ulla, A. & Manteiga, M.) 13–31 (2010).

  24. Mateu, C., Read, J. I. & Kawata, D. Fourteen candidate RR Lyrae star streams in the inner galaxy. Mon. Not. R. Astron. Soc. 474, 4112–4129 (2018).

    ADS  Google Scholar 

  25. Myeong, G. C., Evans, N. W., Belokurov, V., Amorisco, N. C. & Koposov, S. E. Halo substructure in the SDSS-Gaia catalogue: streams and clumps. Mon. Not. R. Astron. Soc. 475, 1537–1548 (2018).

    ADS  Google Scholar 

  26. Koppelman, H., Helmi, A. & Veljanoski, J. One large blob and many streams frosting the nearby stellar halo in Gaia DR2. Astrophys. J. 860, L11 (2018).

    ADS  Google Scholar 

  27. Necib, L., Lisanti, M. & Belokurov, V. Inferred evidence for dark matter kinematic substructure with SDSS-Gaia. Astrophys. J. 874, 3 (2019).

    ADS  Google Scholar 

  28. Casey, A. R. et al. The RAVE-on catalog of stellar atmospheric parameters and chemical abundances for chemo-dynamic studies in the Gaia era. Astrophys. J. 840, 59 (2017).

    ADS  Google Scholar 

  29. Venn, K. A. et al. Stellar chemical signatures and hierarchical galaxy formation. Astron. J. 128, 1177–1195 (2004).

    ADS  Google Scholar 

  30. Tolstoy, E., Hill, V. & Tosi, M. Star-formation histories, abundances, and kinematics of dwarf galaxies in the Local Group. Annu. Rev. Astron. Astrophys. 47, 371–425 (2009).

    ADS  Google Scholar 

  31. Ruchti, G. R., Read, J. I., Feltzing, S., Pipino, A. & Bensby, T. The hunt for the Milky Way as accreted disc. Mon. Not. R. Astron. Soc. 444, 515–526 (2014).

    ADS  Google Scholar 

  32. Andrae, R. et al. Gaia data release 2. First stellar parameters from Apsis. Astron. Astrophys. 616, A8 (2018).

    Google Scholar 

  33. Babusiaux, C. et al. Gaia data release 2. Observational Hertzsprung–Russell diagrams. Astron. Astrophys. 616, A10 (2018).

    Google Scholar 

  34. Dotter, A. MESA Isochrones and Stellar Tracks (MIST) 0: methods for the construction of stellar isochrones. Astrophys. J. Suppl. 222, 8 (2016).

    ADS  Google Scholar 

  35. Choi, J. et al. Mesa Isochrones and Stellar Tracks (MIST). I. Solar-scaled models. Astrophys. J. 823, 102 (2016).

    ADS  Google Scholar 

  36. Martig, M., Minchev, I., Ness, M., Fouesneau, M. & Rix, H.-W. A radial age gradient in the geometrically thick disk of the Milky Way. Astrophys. J. 831, 139 (2016).

    ADS  Google Scholar 

  37. Price-Whelan, A. M. Gala: a Python package for galactic dynamics. J. Open Source Softw. 2, https://doi.org/10.21105/joss.00388 (2017).

  38. Bovy, J. galpy: a Python library for Galactic dynamics. Astrophys. J. Suppl. 216, 29 (2015).

    ADS  Google Scholar 

  39. Li, C. & Zhao, G. The evolution of the Galactic thick disk with the LAMOST survey. Astrophys. J. 850, 25 (2017).

    ADS  Google Scholar 

  40. Dehnen, W. The effect of the outer Lindblad resonance of the Galactic bar on the local stellar velocity distribution. Astron. J. 119, 800–812 (2000).

    ADS  Google Scholar 

  41. Fux, R. Order and chaos in the local disc stellar kinematics induced by the Galactic bar. Astron. Astrophys. 373, 511–535 (2001).

    ADS  Google Scholar 

  42. De Simone, R., Wu, X. & Tremaine, S. The stellar velocity distribution in the solar neighbourhood. Mon. Not. R. Astron. Soc. 350, 627–643 (2004).

    ADS  Google Scholar 

  43. Quillen, A. C. & Minchev, I. The effect of spiral structure on the stellar velocity distribution in the solar neighborhood. Astron. J. 130, 576–585 (2005).

    ADS  Google Scholar 

  44. Minchev, I. et al. Is the Milky Way ringing? The hunt for high-velocity streams. Mon. Not. R. Astron. Soc. 396, L56–L60 (2009).

    ADS  Google Scholar 

  45. Quillen, A. C., Minchev, I., Bland-Hawthorn, J. & Haywood, M. Radial mixing in the outer Milky Way disc caused by an orbiting satellite. Mon. Not. R. Astron. Soc. 397, 1599–1606 (2009).

    ADS  Google Scholar 

  46. Katz, D. et al. Gaia data release 2. Mapping the Milky Way disc kinematics. Astron. Astrophys. 616, A11 (2018).

    Google Scholar 

  47. Helmi, A. et al. Pieces of the puzzle: ancient substructure in the Galactic Disk. Mon. Not. R. Astron. Soc. 365, 1309–1323 (2006).

    ADS  Google Scholar 

  48. Kirby, E. N. et al. The universal stellar mass–stellar metallicity relation for dwarf galaxies. Astrophys. J. 779, 102 (2013).

    ADS  Google Scholar 

  49. Sanderson, R. E. et al. Reconciling observed and simulated stellar halo masses. Astrophys. J. 869, 12 (2018).

    ADS  Google Scholar 

Download references

Acknowledgements

We thank A. Helmi, J. Johnson, E. Kirby, N. Laracy, J. Read, N. Shipp and J. Wojno for helpful discussions. This work was performed in part at Aspen Center for Physics, which is supported by National Science Foundation grant PHY-1607611. This research was supported by the Munich Institute for Astro- and Particle Physics (MIAPP) of the DFG cluster of excellence ‘Origin and Structure of the Universe’. This research was supported in part by the National Science Foundation under Grant No. NSF PHY-1748958. L.N. is supported by the DOE under award number DESC0011632, and the Sherman Fairchild fellowship. M.L. is supported by the DOE under contract DESC0007968 and the Cottrell Scholar Program through the Research Corporation for Science Advancement. B.O. and T.C. are supported by the US Department of Energy under grant number DE-SC0011640. M.F. is supported by the Zuckerman STEM Leadership Program and in part by the DOE under grant number DE-SC0011640. S.G.-K. and P.F.H are supported by an Alfred P. Sloan Research Fellowship, NSF Collaborative Research grant number 1715847 and CAREER grant number 1455342, and NASA grants NNX15AT06G, JPL 1589742 and 17-ATP17-0214. A.W. is supported by NASA, through ATP grant 80NSSC18K1097 and HST grants GO-14734 and AR-15057 from STScI, and a Hellman Fellowship from UC Davis. This work utilized the University of Oregon Talapas high-performance computing cluster. Numerical simulations were run on the Caltech compute cluster ‘Wheeler’, allocations from XSEDE TG-AST130039 and PRAC NSF.1713353 supported by the NSF, and NASA HEC SMD-16-7592. R.S. thanks N. Carriero, I. Fisk and D. Simon of the Scientific Computing Core at the Flatiron Institute for their support of the infrastructure housing the synthetic surveys and simulations used for this work. This work has made use of data from the European Space Agency (ESA) mission Gaia (http://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC, http://www.cosmos.esa.int/web/gaia/dpac/consortium). Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. Funding for RAVE has been provided by: the Australian Astronomical Observatory; the Leibniz-Institut für Astrophysik Potsdam (AIP); the Australian National University; the Australian Research Council; the French National Research Agency; the German Research Foundation (SPP 1177 and SFB 881); the European Research Council (ERC-StG 240271 Galactica); the Istituto Nazionale di Astrofisica at Padova; The Johns Hopkins University; the National Science Foundation of the USA (AST-0908326); the W. M. Keck foundation; the Macquarie University; the Netherlands Research School for Astronomy; the Natural Sciences and Engineering Research Council of Canada; the Slovenian Research Agency; the Swiss National Science Foundation; the Science and Technology Facilities Council of the UK; Opticon; Strasbourg Observatory; and the Universities of Groningen, Heidelberg and Sydney. The RAVE website is at https://www.rave-survey.org.

Author information

Authors and Affiliations

  1. Walter Burke Institute for Theoretical Physics, California Institute of Technology, Pasadena, CA, USA

    Lina Necib

  2. Institute of Theoretical Science, Department of Physics, University of Oregon, Eugene, OR, USA

    Bryan Ostdiek & Timothy Cohen

  3. Department of Physics, Princeton University, Princeton, NJ, USA

    Mariangela Lisanti

  4. Raymond and Beverly Sackler School of Physics and Astronomy, Tel-Aviv University, Tel-Aviv, Israel

    Marat Freytsis

  5. School of Natural Sciences, Institute for Advanced Study, Princeton, NJ, USA

    Marat Freytsis

  6. TAPIR, California Institute of Technology, Pasadena, CA, USA

    Shea Garrison-Kimmel & Philip F. Hopkins

  7. Department of Physics, University of California, Davis, CA, USA

    Andrew Wetzel

  8. Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA, USA

    Robyn Sanderson

  9. Center for Computational Astrophysics, Flatiron Institute, New York, NY, USA

    Robyn Sanderson

Authors
  1. Lina Necib
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Bryan Ostdiek
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mariangela Lisanti
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Timothy Cohen
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Marat Freytsis
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Shea Garrison-Kimmel
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Philip F. Hopkins
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Andrew Wetzel
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Robyn Sanderson
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors discussed the results and commented on the manuscript. M.L. and T.C. conceived the project. L.N. built the data analysis pipeline. B.O., T.C. and M.F. conceptualized the machine learning algorithms. B.O. built the deep neural network and produced the accreted stellar catalogue. Interpretation of the results and writing of the original manuscript were done by L.N. and M.L. The FIRE-2 simulation code was built by P.F.H., and run by P.F.H., S.G.-K. and A.W. S.G.-K. and A.W. ran the halo finding algorithm on the simulation, and L.N. identified the mergers as a function of redshift. R.S. built the mock catalogues used in the training of the neural network.

Corresponding author

Correspondence to Lina Necib.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Astronomy thanks Jeffrey Carlin and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Figs. 1–7 and references.

Supplementary Data 1

List of the 232 stars with a probability larger than 0.95 of belonging to Nyx. It includes their Gaia source IDs, their positions in the sky (right ascension, declination) and their magnitudes in the G band.

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Necib, L., Ostdiek, B., Lisanti, M. et al. Evidence for a vast prograde stellar stream in the solar vicinity. Nat Astron 4, 1078–1083 (2020). https://doi.org/10.1038/s41550-020-1131-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41550-020-1131-2

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing