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On the galaxy stellar mass function, the mass-metallicity relation, and the implied baryonic mass function
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A comparison between published field galaxy stellar mass functions (GSMFs) shows that the cosmic stellar mass density is in the range 4--8 per cent of the baryon density (assuming Omega_b = 0.045). There remain significant sources of uncertainty for the dust correction and underlying stellar mass-to-light ratio even assuming a reasonable universal stellar initial mass function. We determine the z < 0.05 GSMF using the New York University - Value-Added Galaxy Catalog sample of 49968 galaxies derived from the Sloan Digital Sky Survey and various estimates of stellar mass. The GSMF shows clear evidence for a low-mass upturn and is fitted with a double Schechter function that has alpha_2 =~ -1.6. At masses below ~ 10^8.5 Msun, the GSMF may be significantly incomplete because of missing low surface-brightness galaxies. One interpretation of the stellar mass-metallicity relation is that it is primarily caused by a lower fraction of available baryons converted to stars in low-mass galaxies. Using this principal, we determine a simple relationship between baryonic mass and stellar mass and present an `implied baryonic mass function'. This function has a faint-end slope, alpha_2 =~ -1.9. Thus, we find evidence that the slope of the low-mass end of the galaxy mass function could plausibly be as steep as the halo mass function. We illustrate the relationship between halo baryonic mass function --> galaxy baryonic mass function --> GSMF. This demonstrates the requirement for peak galaxy formation efficiency at baryonic masses ~ 10^11 Msun corresponding to a minimum in feedback effects. The baryonic-infall efficiency may have levelled off at lower masses.
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Cited by 1 Pith paper
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Dark-matter-induced transients over cosmic time: The role of star formation history profiles
A closed-form formula for star formation histories in galactocentric radial shells is derived from empirical galaxy scaling relations and two star formation history models.
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