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Register a new userFrom Correlations of Galaxy Properties to the Physics of Galaxy Formation: A Theoretical Framework
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(Abridged) Motivated by forthcoming data from the Sloan Digital Sky Survey, we present a theoretical framework that can be used to interpret Principal Component Analysis (PCA) of disk galaxy properties. We use the formalism introduced by Mo, Mao, & White to compute the observable properties of galaxies in a number of model populations, varying assumptions about which physical parameters determine structural quantities and star formation histories. We then apply PCA to these model populations. Our baseline model assumes that halo mass, spin parameter, and formation redshift are the governing input parameters and that star formation is determined by surface density through a Schmidt law. In all cases, the first principal component is primarily a measure of the shape of the spectral energy distribution (SED), and it is usually driven by variations in the spin parameter, which influences star formation through the disk surface density. The second and (in some cases) third principal components consist mainly of ``scale parameters like luminosity, disk radius, and circular velocity. However, the detailed division of these scale parameters, the disk surface brightness, and the rotation curve slope among the principal components changes significantly from model to model. Our calculations yield predictions of principal component structure for the baseline model of disk galaxy formation, and a physical interpretation of these predictions. They also show that PCA can test the core assumptions of that model and reveal the presence of additional physical parameters that may govern observable galaxy properties.
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We introduce methods which allow observed galaxy clustering to be used together with observed luminosity or stellar mass functions to constrain the physics of galaxy formation. We show how the projected two-point correlation function of galaxies in a large semi-analytic simulation can be estimated to better than ~10% using only a very small subsample of the subhalo merger trees. This allows measured correlations to be used as constraints in a Monte Carlo Markov Chain exploration of the astrophysical and cosmological parameter space. An important part of our scheme is an analytic profile which captures the simulated satellite distribution extremely well out to several halo virial radii. This is essential to reproduce the correlation properties of the full simulation at intermediate separations. As a first application, we use low-redshift clustering and abundance measurements to constrain a recent version of the Munich semi-analytic model. The preferred values of most parameters are consistent with those found previously, with significantly improved constraints and somewhat shifted best values for parameters that primarily affect spatial distributions. Our methods allow multi-epoch data on galaxy clustering and abundance to be used as joint constraints on galaxy formation. This may lead to significant constraints on cosmological parameters even after marginalising over galaxy formation physics.
We present a new comprehensive model of the physics of galaxy formation designed for large-scale hydrodynamical simulations of structure formation using the moving mesh code AREPO. Our model includes primordial and metal line cooling with self-shielding corrections, stellar evolution and feedback processes, gas recycling, chemical enrichment, a novel subgrid model for the metal loading of outflows, black hole (BH) seeding, BH growth and merging procedures, quasar- and radio-mode feedback, and a prescription for radiative electro-magnetic (EM) feedback from active galactic nuclei (AGN). The metal mass loading of outflows can be adjusted independently of the wind mass loading. This is required to simultaneously reproduce the stellar mass content of low mass haloes and their gas oxygen abundances. Radiative EM AGN feedback is implemented assuming an average spectral energy distribution and a luminosity-dependent scaling of obscuration effects. This form of feedback suppresses star formation more efficiently than continuous thermal quasar-mode feedback alone, but is less efficient than mechanical radio-mode feedback in regulating star formation in massive haloes. We contrast simulation predictions for different variants of our galaxy formation model with key observations. Our best match model reproduces, among other things, the cosmic star formation history, the stellar mass function, the stellar mass - halo mass relation, g-, r-, i-, z-band SDSS galaxy luminosity functions, and the Tully-Fisher relation. We can achieve this success only if we invoke very strong forms of stellar and AGN feedback such that star formation is adequately reduced in both low and high mass systems. In particular, the strength of radio-mode feedback needs to be increased significantly compared to previous studies to suppress efficient cooling in massive, metal-enriched haloes.
We present the most accurate measurement to date of cosmological evolution of the near-infrared galaxy luminosity function, from the local Universe out to z~4. The analysis is based on a large and highly complete sample of galaxies selected from the first data release of the UKIDSS Ultra Deep Survey. Exploiting a master catalogue of K- and z-band selected galaxies over an area of 0.7 square degrees, we analyse a sample of ~50,000 galaxies, all with reliable photometry in 16-bands from the far-ultraviolet to the mid-infrared. The unique combination of large area and depth provided by the Ultra Deep Survey allows us to trace the evolution of the K-band luminosity function with unprecedented accuracy. In particular, via a maximum likelihood analysis we obtain a simple parameterization for the luminosity function and its cosmological evolution, including both luminosity and density evolution, which provides an excellent description of the data from z =0 up to z~4. We find differential evolution for galaxies dependent on galaxy luminosity, revealing once again the ``down-sizing behaviour of galaxy formation. Finally, we compare our results with the predictions of the latest theoretical models of galaxy formation, based both on semi-analytical prescriptions, and on full hydrodynamical simulations.
We investigate how a property of a galaxy correlates most tightly with a property of its host dark matter halo, using state-of-the-art hydrodynamical simulations of galaxy formation EAGLE, Illustris, and IllustrisTNG. Unlike most of the previous work, our analyses focus on all types of galaxies, including both central and satellite galaxies. We find that the stellar mass of a galaxy at the epoch of the peak circular velocity with an evolution correction gives the tightest such correlation to the peak circular velocity $V_{rm peak}$ of the galaxys underling dark matter halo. The evolution of galaxy stellar mass reduces rather than increases scatter in such a relation. We also find that one major source of scatter comes from star stripping due to the strong interactions between galaxies. Even though, we show that the size of scatter predicted by hydrodynamical simulations has a negligible impact on the clustering of dense $V_{rm peak}$-selected subhalo from simulations, which suggests that even the simplest subhalo abundance matching (SHAM), without scatter and any additional free parameter, can provide a robust prediction of galaxy clustering that can agree impressively well with the observations from the SDSS main galaxy survey.
The two-point correlation function has been the standard statistic for quantifying how galaxies are clustered. The statistic uses the positions of galaxies, but not their properties. Clustering as a function of galaxy property, be it type, luminosity, color, etc., is usually studied by analysing a subset of the full population, the galaxies in the subset chosen because they have a similar range of properties. We explore an alternative technique---marked correlations---in which one weights galaxies by some property or `mark when measuring clustering statistics. Marked correlations are particularly well-suited to quantifying how the properties of galaxies correlate with their environment. Therefore, measurements of marked statistics, with luminosity, stellar mass, color, star-formation rate, etc. as the mark, permit sensitive tests of galaxy formation models. We make measurements of such marked statistics in semi-analytic galaxy formation models to illustrate their utility. These measurements show that close pairs of galaxies are expected to be red, to have larger stellar masses, and to have smaller star formation rates. We also show that the simplest unbiased estimator of the particular marked statistic we use extensively is very simple to measure---it does not require construction of a random catalog---and provide an estimate of its variance. Large wide-field surveys of the sky are revolutionizing our view of galaxies and how they evolve. Our results indicate that application of marked statistics to this high quantity of high-quality data will provide a wealth of information about galaxy formation.
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