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SubHalo Abundance Matching (SHAM) assumes that one (sub)halo property, such as mass Mvir or peak circular velocity Vpeak, determines properties of the galaxy hosted in each (sub)halo such as its luminosity or stellar mass. This assumption implies that the dependence of Galaxy Luminosity Functions (GLFs) and the Galaxy Stellar Mass Function (GSMF) on environmental density is determined by the corresponding halo density dependence. In this paper, we test this by determining from an SDSS sample the observed dependence with environmental density of the ugriz GLFs and GSMF for all galaxies, and for central and satellite galaxies separately. We then show that the SHAM predictions are in remarkable agreement with these observations, even when the galaxy population is divided between central and satellite galaxies. However, we show that SHAM fails to reproduce the correct dependence between environmental density and g-r color for all galaxies and central galaxies, although it better reproduces the color dependence on environmental density of satellite galaxies.
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The application of Bayesian techniques to astronomical data is generally non-trivial because the fitting parameters can be strongly degenerated and the formal uncertainties are themselves uncertain. An example is provided by the contradictory claims over the presence or absence of a universal acceleration scale (g$_dagger$) in galaxies based on Bayesian fits to rotation curves. To illustrate the situation, we present an analysis in which the Newtonian gravitational constant $G_N$ is allowed to vary from galaxy to galaxy when fitting rotation curves from the SPARC database, in analogy to $g_{dagger}$ in the recently debated Bayesian analyses. When imposing flat priors on $G_N$, we obtain a wide distribution of $G_N$ which, taken at face value, would rule out $G_N$ as a universal constant with high statistical confidence. However, imposing an empirically motivated log-normal prior returns a virtually constant $G_N$ with no sacrifice in fit quality. This implies that the inference of a variable $G_N$ (or g$_{dagger}$) is the result of the combined effect of parameter degeneracies and unavoidable uncertainties in the error model. When these effects are taken into account, the SPARC data are consistent with a constant $G_{rm N}$ (and constant $g_dagger$).
It is widely reported, based on clustering measurements of observed active galactic nuclei (AGN) samples, that AGN reside in similar mass host dark matter halos across the bulk of cosmic time, with log $M/M_odot$~12.5-13.0 to z~2.5. We show that this is due in part to the AGN fraction in galaxies rising with increasing stellar mass, combined with AGN observational selection effects that exacerbate this trend. Here, we use AGN specific accretion rate distribution functions determined as a function of stellar mass and redshift for star-forming and quiescent galaxies separately, combined with the latest galaxy-halo connection models, to determine the parent and sub-halo mass distribution function of AGN to various observational limits. We find that while the median (sub-)halo mass of AGN, $approx10^{12}M_odot$, is fairly constant with luminosity, specific accretion rate, and redshift, the full halo mass distribution function is broad, spanning several orders of magnitude. We show that widely used methods to infer a typical dark matter halo mass based on an observed AGN clustering amplitude can result in biased, systematically high host halo masses. While the AGN satellite fraction rises with increasing parent halo mass, we find that the central galaxy is often not an AGN. Our results elucidate the physical causes for the apparent uniformity of AGN host halos across cosmic time and underscore the importance of accounting for AGN selection biases when interpreting observational AGN clustering results. We further show that AGN clustering is most easily interpreted in terms of the relative bias to galaxy samples, not from absolute bias measurements alone.
We explore the connection between the stellar component of galaxies and their host halos during the epoch of reionization ($5 leq zleq10$) using the CROC (Cosmic Reionization on Computers) simulations. We compare simulated galaxies with observations and find that CROC underpredicts the abundance of luminous galaxies when compared to observed UV luminosity functions, and analogously the most massive galaxies when compared to observed stellar mass functions. We can trace the deficit of star formation to high redshifts, where the slope of the star formation rate to stellar mass relation is consistent with observations, but the normalization is systematically low. This results in a star formation rate density and stellar mass density that is systematically offset from observations. However, the less luminous or lower stellar mass objects have luminosities and stellar masses that agree fairly well with observational data. We explore the stellar-to-halo mass ratio, a key quantity that is difficult to measure at high redshifts and that models do not consistently predict. In CROC, the stellar-to-halo mass ratio {it decreases} with redshift, a trend opposite to some abundance matching studies. These discrepancies uncover where future effort should be focused in order to improve the fidelity of modeling cosmic reionization. We also compare the CROC galaxy bias with observational measurements using Lyman-Break Galaxy (LBG) samples. The good agreement of simulation and data shows that the clustering of dark matter halos is properly captured in CROC.
Empirical models of galaxy formation require assumptions about the correlations between galaxy and halo properties. These may be calibrated against observations or inferred from physical models such as hydrodynamical simulations. In this Letter, we use the EAGLE simulation to investigate the correlation of galaxy size with halo properties. We motivate this analysis by noting that the common assumption of angular momentum partition between baryons and dark matter in rotationally supported galaxies overpredicts both the spread in the stellar mass-size relation and the anticorrelation of size and velocity residuals, indicating a problem with the galaxy-halo connection it implies. We find the EAGLE galaxy population to perform significantly better on both statistics, and trace this success to the weakness of the correlations of galaxy size with halo mass, concentration and spin at fixed stellar mass. Using these correlations in empirical models will enable fine-grained aspects of galaxy scalings to be matched.
We present new determinations of the stellar-to-halo mass relation (SHMR) at $z=0-10$ that match the evolution of the galaxy stellar mass function, the SFR$-M_*$ relation,and the cosmic star formation rate. We utilize a compilation of 40 observational studies from the literature and correct them for potential biases. Using our robust determinations of halo mass assembly and the SHMR, we infer star formation histories, merger rates, and structural properties for average galaxies, combining star-forming and quenched galaxies. Our main findings: (1) The halo mass $M_{50}$ above which 50% of galaxies are quenched coincides with sSFR/sMAR$sim1$, where sMAR is the specific halo mass accretion rate. (2) $M_{50}$ increases with redshift, presumably due to cold streams being more efficient at high redshift while virial shocks and AGN feedback become more relevant at lower redshifts. (3) The ratio sSFR/sMAR has a peak value, which occurs around $M_{rm vir}sim2times10^{11}M_{odot}$. (4) The stellar mass density within 1 kpc, $Sigma_1$, is a good indicator of the galactic global sSFR. (5) Galaxies are statistically quenched after they reach a maximum in $Sigma_1$, consistent with theoretical expectations of the gas compaction model; this maximum depends on redshift. (6) In-situ star formation is responsible for most galactic stellar mass growth, especially for lower-mass galaxies. (7) Galaxies grow inside out. The marked change in the slope of the size--mass relation when galaxies became quenched, from $dlog R_{rm eff}/dlog M_*sim0.35$ to $sim2.5$, could be the result of dry minor mergers.
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