The effects of gas on morphological transformation in mergers: implications for bulge and disc demographics

By P. Hopkins, R. Somerville, Thomas J. Cox, L. Hernquist, S. Jogee, D. Keres̆, Chung-Pei Ma, Brant Robertson, Kyle R. Stewart. 2009

176 citations recorded by the source corpus.

Transformation of discs into spheroids via mergers is a well-accepted element of galaxy formation models. However, recent simulations have shown that the bulge formation is suppressed in increasingly gas-rich mergers. We investigate the global implications of these results in a cosmological framework, using independent approaches: empirical halo-occupation models (where galaxies are populated in haloes according to observations) and semi-analytic models. In both, ignoring the effects of gas in mergers leads to the overproduction of spheroids:low- and intermediate-mass galaxies are predicted to be bulge-dominated (B/T ∼ 0.5 at < 10 10 M ⊙ , with almost no 'bulgeless' systems), even if they have avoided major mergers. Including the different physical behaviour of gas in mergers immediately leads to a dramatic change: bulge formation is suppressed in low-mass galaxies, observed to be gas-rich (giving B/T ∼ 0.1 at < 10 10 M ⊙ , with a number of bulgeless galaxies in good agreement with observations). Simulations and analytic models which neglect the similarity-breaking behaviour of gas have difficulty reproducing the strong observed morphology-mass relation. However, the observed dependence of gas fractions on mass, combined with suppression of bulge formation in gas-rich mergers, naturally leads to the observed trends. Discrepancies between observations and models that ignore the role of gas increase with redshift; in models that treat gas properly, galaxies are predicted to be less bulge-dominated at high redshifts, in agreement with the observations. We discuss implications for the global bulge mass density and future observational tests.

Subfields: Astronomy and Astrophysics, Computer Vision and Pattern Recognition, Instrumentation

View Paper: https://www.semanticscholar.org/paper/2abd7322179f912900e74c24a98cb0bb1ab83fdd

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Astronomy and Astrophysics

  1. P. Hopkins
  2. L. Hernquist
  3. R. Somerville
  4. A. Dekel
  5. R. Dav'e
  6. Thomas J. Cox
  7. Volker Springel
  8. T. Naab

In Computer Vision and Pattern Recognition

  1. P. Hopkins
  2. Christopher J. Conselice
  3. Kevin Schawinski
  4. R. Somerville
  5. L. Hernquist
  6. Thomas J. Cox
  7. Darren Croton
  8. Kyle R. Stewart

In Instrumentation

  1. P. Hopkins
  2. L. Hernquist
  3. R. Somerville
  4. A. Dekel
  5. R. Dav'e
  6. Thomas J. Cox
  7. P. V. van Dokkum
  8. Joel R. Primack

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