4.7 Article

Building a predictive model of galaxy formation - I. Phenomenological model constrained to the z=0 stellar mass function

期刊

出版社

OXFORD UNIV PRESS
DOI: 10.1093/mnras/stu1630

关键词

galaxies: evolution; galaxies: formation

资金

  1. NSF [1066293]
  2. Alfred P. Sloan Foundation
  3. National Aeronautics and Space Administration
  4. National Science Foundation
  5. US Department of Energy
  6. Japanese Monbukagakusho
  7. Max Planck Society
  8. University of Chicago
  9. Fermilab
  10. Institute for Advanced Study
  11. Japan Participation Group
  12. Johns Hopkins University
  13. Los Alamos National Laboratory
  14. Max-Planck-Institute for Astronomy (MPIA)
  15. Max-Planck-Institute for Astrophysics (MPA)
  16. New Mexico State University
  17. University of Pittsburgh
  18. Princeton University
  19. United States Naval Observatory
  20. University of Washington

向作者/读者索取更多资源

We constrain a highly simplified semi-analytic model of galaxy formation using the z approximate to 0 stellar mass function of galaxies. Particular attention is paid to assessing the role of random and systematic errors in the determination of stellar masses, to systematic uncertainties in the model, and to correlations between bins in the measured and modelled stellar mass functions, in order to construct a realistic likelihood function. We derive constraints on model parameters and explore which aspects of the observational data constrain particular parameter combinations. We find that our model, once constrained, provides a remarkable match to the measured evolution of the stellar mass function to z = 1, although fails dramatically to match the local galaxy HI mass function. Several 'nuisance parameters' contribute significantly to uncertainties in model predictions. In particular, systematic errors in stellar mass estimate are the dominant source of uncertainty in model predictions at z approximate to 1, with additional, non-negligble contributions arising from systematic uncertainties in halo mass functions and the residual uncertainties in cosmological parameters. Ignoring any of these sources of uncertainties could lead to viable models being erroneously ruled out. Additionally, we demonstrate that ignoring the significant covariance between bins the observed stellar mass function leads to significant biases in the constraints derived on model parameters. Careful treatment of systematic and random errors in the constraining data, and in the model being constrained, is crucial if this methodology is to be used to test hypotheses relating to the physics of galaxy formation.

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