Article | Published:

Properties of galaxies reproduced by a hydrodynamic simulation

Nature volume 509, pages 177182 (08 May 2014) | Download Citation

Abstract

Previous simulations of the growth of cosmic structures have broadly reproduced the ‘cosmic web’ of galaxies that we see in the Universe, but failed to create a mixed population of elliptical and spiral galaxies, because of numerical inaccuracies and incomplete physical models. Moreover, they were unable to track the small-scale evolution of gas and stars to the present epoch within a representative portion of the Universe. Here we report a simulation that starts 12 million years after the Big Bang, and traces 13 billion years of cosmic evolution with 12 billion resolution elements in a cube of 106.5 megaparsecs a side. It yields a reasonable population of ellipticals and spirals, reproduces the observed distribution of galaxies in clusters and characteristics of hydrogen on large scales, and at the same time matches the ‘metal’ and hydrogen content of galaxies on small scales.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

References

  1. 1.

    Planck Collaboration. Planck 2013 results. XVI. Cosmological parameters. Preprint at (2013)

  2. 2.

    Dissipational galaxy formation. II — Effects of star formation. Astrophys. J. 391, 502–517 (1992)

  3. 3.

    et al. The physics driving the cosmic star formation history. Mon. Not. R. Astron. Soc. 402, 1536–1560 (2010)

  4. 4.

    , , , & MaGICC discs: matching observed galaxy relationships over a wide stellar mass range. Mon. Not. R. Astron. Soc. 424, 1275–1283 (2012)

  5. 5.

    E pur si muove: Galilean-invariant cosmological hydrodynamical simulations on a moving mesh. Mon. Not. R. Astron. Soc. 401, 791–851 (2010)

  6. 6.

    et al. PRIMUS: Constraints on star formation quenching and galaxy merging, and the evolution of the stellar mass function from z = 0–1. Astrophys. J. 767, 50 (2013)

  7. 7.

    & Dark halo and disk galaxy scaling laws in hierarchical universes. Astrophys. J. 538, 477–488 (2000)

  8. 8.

    et al. The Aquila comparison project: the effects of feedback and numerical methods on simulations of galaxy formation. Mon. Not. R. Astron. Soc. 423, 1726–1749 (2012)

  9. 9.

    et al. The HST eXtreme Deep Field (XDF): combining all ACS and WFC3/IR data on the HUDF region into the deepest field ever. Astrophys. J. Suppl. Ser. 209, 6 (2013)

  10. 10.

    et al. Dark matter substructure within galactic halos. Astrophys. J. 524, L19–L22 (1999)

  11. 11.

    , & Too big to fail? The puzzling darkness of massive Milky Way subhaloes. Mon. Not. R. Astron. Soc. 415, L40–L44 (2011)

  12. 12.

    et al. Measurement of galaxy cluster sizes, radial profiles, and luminosity functions from SDSS photometric data. Astrophys. J. 633, 122–137 (2005)

  13. 13.

    , , , & The radial distribution of galaxies in groups and clusters. Mon. Not. R. Astron. Soc. 423, 104–121 (2012)

  14. 14.

    & Satellites around massive galaxies since z2: confronting the millennium simulation with observations. Astrophys. J. 752, L19 (2012)

  15. 15.

    et al. Galaxy environments over cosmic time: the non-evolving radial galaxy distributions around massive galaxies since z = 1.6. Astrophys. J. 769, 31 (2013)

  16. 16.

    & The radial distribution of galaxies in Λ cold dark matter clusters. Astrophys. J. 618, 557–568 (2005)

  17. 17.

    et al. Properties of the galaxy population in hydrodynamical simulations of clusters. Mon. Not. R. Astron. Soc. 373, 397–410 (2006)

  18. 18.

    , , , & Satellite systems around galaxies in hydrodynamic simulations. Mon. Not. R. Astron. Soc. 374, 16–28 (2007)

  19. 19.

    , , & The galaxy content of SDSS clusters and groups. Astrophys. J. 699, 1333–1353 (2009)

  20. 20.

    , , , & The effect of the environment on the H I scaling relations. Mon. Not. R. Astron. Soc. 415, 1797–1806 (2011)

  21. 21.

    & The enrichment history of baryons in the Universe. Mon. Not. R. Astron. Soc. 374, 427–435 (2007)

  22. 22.

    , & The effect of variations in the input physics on the cosmic distribution of metals predicted by simulations. Mon. Not. R. Astron. Soc. 415, 353–371 (2011)

  23. 23.

    , , & A census of metals and baryons in stars in the local Universe. Mon. Not. R. Astron. Soc. 383, 1439–1458 (2008)

  24. 24.

    , , , & The ages and metallicities of galaxies in the local universe. Mon. Not. R. Astron. Soc. 362, 41–58 (2005)

  25. 25.

    , & Scaling relations and the fundamental line of the local group dwarf galaxies. Mon. Not. R. Astron. Soc. 390, 1453–1469 (2008)

  26. 26.

    et al. The universal stellar mass-stellar metallicity relation for dwarf galaxies. Astrophys. J. 779, 102 (2013)

  27. 27.

    , , & Evolution of the cosmological mass density of neutral gas from Sloan Digital Sky Survey II – Data Release 7. Astron. Astrophys. 505, 1087–1098 (2009)

  28. 28.

    et al. The ESO UVES advanced data products quasar sample. II. Cosmological evolution of the neutral gas mass density. Astron. Astrophys. 556, A141 (2013)

  29. 29.

    , , & The Lyman-alpha forest in the cold dark matter model. Astrophys. J. 457, L51 (1996)

  30. 30.

    et al. Damped Lyman α systems in galaxy formation simulations. Mon. Not. R. Astron. Soc. 390, 1349–1371 (2008)

  31. 31.

    , , , & The impact of different physical processes on the statistics of Lyman-limit and damped Lyman α absorbers. Mon. Not. R. Astron. Soc. 436, 2689–2707 (2013)

  32. 32.

    , , , & Metallicity evolution of damped Lyα systems out to z5. Astrophys. J. 755, 89 (2012)

  33. 33.

    et al. Absorption-line systems in simulated galaxies fed by cold streams. Mon. Not. R. Astron. Soc. 418, 1796–1821 (2011)

  34. 34.

    The nature of damped Lyα systems and their hosts in the standard cold dark matter universe. Astrophys. J. 748, 121 (2012)

  35. 35.

    The search for the missing baryons at low redshift. Annu. Rev. Astron. Astrophys. 45, 221–259 (2007)

  36. 36.

    & Calibrating the nonlinear matter power spectrum: requirements for future weak lensing surveys. Astropart. Phys. 23, 369–376 (2005)

  37. 37.

    et al. Euclid assessment study report for the ESA cosmic visions. Preprint at (2009)

  38. 38.

    , , & The effects of galaxy formation on the matter power spectrum: a challenge for precision cosmology. Mon. Not. R. Astron. Soc. 415, 3649–3665 (2011)

  39. 39.

    et al. Stable clustering, the halo model and non-linear cosmological power spectra. Mon. Not. R. Astron. Soc. 341, 1311–1332 (2003)

  40. 40.

    , , , & Revising the Halofit model for the nonlinear matter power spectrum. Astrophys. J. 761, 152 (2012)

  41. 41.

    et al. A fundamental problem in our understanding of low-mass galaxy evolution. Mon. Not. R. Astron. Soc. 426, 2797–2812 (2012)

  42. 42.

    et al. Galaxies on FIRE (Feedback In Realistic Environments): stellar feedback explains cosmologically inefficient star formation. Preprint at (2013)

  43. 43.

    et al. A model for cosmological simulations of galaxy formation physics. Mon. Not. R. Astron. Soc. 436, 3031–3067 (2013)

  44. 44.

    , , & Substructures in hydrodynamical cluster simulations. Mon. Not. R. Astron. Soc. 399, 497–514 (2009)

  45. 45.

    , , & Populating a cluster of galaxies — I. Results at z = 0. Mon. Not. R. Astron. Soc. 328, 726–750 (2001)

  46. 46.

    , , & The Arecibo Legacy Fast ALFA Survey: the galaxy population detected by ALFALFA. Astrophys. J. 756, 113 (2012)

  47. 47.

    , & A definitive survey for Lyman limit systems at z 3.5 with the Sloan Digital Sky Survey. Astrophys. J. 718, 392–416 (2010)

  48. 48.

    , , , & Moving mesh cosmology: numerical techniques and global statistics. Mon. Not. R. Astron. Soc. 425, 3024–3057 (2012)

  49. 49.

    , , , & Moving mesh cosmology: the hydrodynamics of galaxy formation. Mon. Not. R. Astron. Soc. 424, 2999–3027 (2012)

  50. 50.

    , , , & Moving-mesh cosmology: characteristics of galaxies and haloes. Mon. Not. R. Astron. Soc. 425, 2027–2048 (2012)

  51. 51.

    et al. Following the flow: tracer particles in astrophysical fluid simulations. Mon. Not. R. Astron. Soc. 435, 1426–1442 (2013)

  52. 52.

    , , , & Moving-mesh cosmology: properties of gas discs. Mon. Not. R. Astron. Soc. 427, 2224–2238 (2012)

  53. 53.

    A new parallel N-body gravity solver: TPM. Astrophys. J. Suppl. Ser. 98, 355 (1995)

  54. 54.

    & A hierarchical O(N log N) force-calculation algorithm. Nature 324, 446–449 (1986)

  55. 55.

    , , & A new calculation of the ionizing background spectrum and the effects of He II reionization. Astrophys. J. 703, 1416–1443 (2009)

  56. 56.

    et al. CLOUDY 90: numerical simulation of plasmas and their spectra. Publ. Astron. Soc. Pacif. 110, 761–778 (1998)

  57. 57.

    , , & On the evolution of the H I column density distribution in cosmological simulations. Mon. Not. R. Astron. Soc. 430, 2427–2445 (2013)

  58. 58.

    The star formation law in galactic disks. Astrophys. J. 344, 685–703 (1989)

  59. 59.

    Galactic stellar and substellar initial mass function. Publ. Astron. Soc. Pacif. 115, 763–795 (2003)

  60. 60.

    & Cosmological smoothed particle hydrodynamics simulations: a hybrid multiphase model for star formation. Mon. Not. R. Astron. Soc. 339, 289–311 (2003)

  61. 61.

    et al. Empirical constraints for the magnitude and composition of galactic winds. Astrophys. Space Sci. 349, 873–879 (2014)

  62. 62.

    , & Energy input from quasars regulates the growth and activity of black holes and their host galaxies. Nature 433, 604–607 (2005)

  63. 63.

    , , & A unified model for AGN feedback in cosmological simulations of structure formation. Mon. Not. R. Astron. Soc. 380, 877–900 (2007)

  64. 64.

    , & The formation of disc galaxies in high-resolution moving-mesh cosmological simulations. Mon. Not. R. Astron. Soc. 437, 1750–1775 (2014)

  65. 65.

    & A line-of-sight integration approach to cosmic microwave background anisotropies. Astrophys. J. 469, 437 (1996)

  66. 66.

    & CAMB: Code for Anisotropies in the Microwave Background. Astrophysics Source Code Library (2011)

  67. 67.

    et al. Nine-year Wilkinson Microwave Anisotropy Probe (WMAP) observations: cosmological parameter results. Astrophys. J. Suppl. Ser. 208, 19 (2013)

  68. 68.

    , & Planck data reconsidered. Preprint at (2013)

  69. 69.

    in Cosmology and Large Scale Structure (eds , , & ) 349 (Elsevier, 1996)

  70. 70.

    Gravitational instability: an approximate theory for large density perturbations. Astron. Astrophys. 5, 84–89 (1970)

  71. 71.

    , & A new calculation of the recombination epoch. Astrophys. J. 523, L1–L5 (1999)

  72. 72.

    , & RECFAST: Calculate the Recombination History of the Universe. Astrophysics Source Code Library (2011)

  73. 73.

    , , & The evolution of large-scale structure in a universe dominated by cold dark matter. Astrophys. J. 292, 371–394 (1985)

  74. 74.

    & Stellar population synthesis at the resolution of 2003. Mon. Not. R. Astron. Soc. 344, 1000–1028 (2003)

  75. 75.

    et al. Preparing red-green-blue images from CCD data. Publ. Astron. Soc. Pacif. 116, 133–137 (2004)

Download references

Acknowledgements

V.S. acknowledges support from the DFG Research Centre SFB-881 ‘The Milky Way System’ through project A1, and from the European Research Council under ERC-StG EXAGAL-308037. G.S. acknowledges support from the HST grants programme, no. HST-AR-12856.01-A. Support for program no. 12856 was provided by NASA through a grant from the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. L.H. acknowledges support from NASA grant NNX12AC67G and NSF grant AST-1312095. D.X. acknowledges support from the Alexander von Humboldt Foundation. S.B. was supported by NSF grant AST-0907969. The Illustris simulation was run on the CURIE supercomputer at CEA/France as part of PRACE project RA0844, and the SuperMUC computer at the Leibniz Computing Centre, Germany, as part of GCS-project pr85je. Further simulations were run on the Harvard Odyssey and CfA/ITC clusters, the Ranger and Stampede supercomputers at the Texas Advanced Computing Center through XSEDE, and the Kraken supercomputer at Oak Rridge National Laboratory through XSEDE. Figure 1b is based on observations made with the NASA/ESA Hubble Space Telescope. These data were obtained from the Mikulski Archive for Space Telescopes (MAST) at the Space Telescope Science Institute (STScI). These observations were associated with programs 9,352, 9,425, 9,488, 9,575, 9,793, 9,978, 10,086, 10,189, 10,258, 10,340, 10,530, 11,359, 11,563, 12,060, 12,061, 12,062, 12,099 and 12,177, and compiled for the Hubble eXtreme Deep Field data release version 1.0 (http://archive.stsci.edu/prepds/xdf/). Support for MAST for non-HST data is provided by the NASA Office of Space Science via grant NNX13AC07G and by other grants and contracts.

Author information

Affiliations

  1. Department of Physics, Kavli Institute for Astrophysics and Space Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA

    • M. Vogelsberger
  2. Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, Massachusetts 02138, USA

    • S. Genel
    • , P. Torrey
    • , D. Nelson
    •  & L. Hernquist
  3. Heidelberg Institute for Theoretical Studies, Schloss-Wolfsbrunnenweg 35, 69118 Heidelberg, Germany

    • V. Springel
    •  & D. Xu
  4. Zentrum für Astronomie der Universität Heidelberg, ARI, Mönchhofstrasse 12-14, 69120 Heidelberg, Germany

    • V. Springel
  5. Kavli Institute for Cosmology, and Institute of Astronomy, Madingley Road, Cambridge CB3 0HA, UK

    • D. Sijacki
  6. Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, Maryland 21218, USA

    • G. Snyder
  7. Institute for Advanced Study, 1 Einstein Drive, Princeton, New Jersey 08540, USA

    • S. Bird

Authors

  1. Search for M. Vogelsberger in:

  2. Search for S. Genel in:

  3. Search for V. Springel in:

  4. Search for P. Torrey in:

  5. Search for D. Sijacki in:

  6. Search for D. Xu in:

  7. Search for G. Snyder in:

  8. Search for S. Bird in:

  9. Search for D. Nelson in:

  10. Search for L. Hernquist in:

Contributions

M.V., L.H., D.S., V.S. and S.G. conceived and planned the project. M.V., S.G., D.S. and P.T. developed the galaxy formation model. V.S. developed the AREPO code. M.V. generated initial conditions. V.S., M.V. and S.G. ran the simulations. M.V. performed the main analysis. G.S. and P.T. constructed the mock images. S.B. provided statistics of the inter-galactic medium. D.X. and D.N. provided post-processing tools. M.V., S.G., V.S., P.T. and L.H. interpreted the results. M.V. and S.G. wrote the manuscript with contributions from co-authors.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to M. Vogelsberger.

About this article

Publication history

Received

Accepted

Published

DOI

https://doi.org/10.1038/nature13316

Further reading

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.