4.7 Article

MUFASA: galaxy formation simulations with meshless hydrodynamics

期刊

出版社

OXFORD UNIV PRESS
DOI: 10.1093/mnras/stw1862

关键词

galaxies: evolution; galaxies: formation

资金

  1. South African Research Chairs Initiative
  2. South African National Research Foundation
  3. NASA ATP grant [NNX12AH86G, NNX14AH35G]
  4. Gordon and Betty Moore Foundation's Data-Driven Discovery Initiative [GBMF4561]
  5. National Science Foundation [ACI-1535651]
  6. Alfred P. Sloan Research Fellowship
  7. NSF [1411920, 1455342]
  8. UWC's Office of the Deputy Vice Chancellor
  9. Direct For Mathematical & Physical Scien
  10. Division Of Astronomical Sciences [1411920] Funding Source: National Science Foundation
  11. NASA [19766, NNX12AH86G] Funding Source: Federal RePORTER

向作者/读者索取更多资源

We present the MUFASA suite of cosmological hydrodynamic simulations, which employs the GIZMO meshless finite mass (MFM) code including H-2-based star formation, nine-element chemical evolution, two-phase kinetic outflows following scalings from the Feedback in Realistic Environments zoom simulations, and evolving halo mass-based quenching. Our fiducial (50 h(-1) Mpc)(3) volume is evolved to z = 0 with a quarter billion elements. The predicted galaxy stellar mass functions (GSMFs) reproduces observations from z = 4 -> 0 to less than or similar to 1.2 sigma in cosmic variance, providing an unprecedented match to this key diagnostic. The cosmic star formation history and stellar mass growth show general agreement with data, with a strong archaeological downsizing trend such that dwarf galaxies form the majority of their stars after z similar to 1. We run 25 and 12.5 h(-1) Mpc volumes to z = 2 with identical feedback prescriptions, the latter resolving all hydrogen-cooling haloes, and the three runs display fair resolution convergence. The specific star formation rates broadly agree with data at z = 0, but are underpredicted at z similar to 2 by a factor of 3, re-emphasizing a longstanding puzzle in galaxy evolution models. We compare runs using MFM and two flavours of smoothed particle hydrodynamics, and show that the GSMF is sensitive to hydrodynamics methodology at the similar to x2 level, which is sub-dominant to choices for parametrizing feedback.

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