We investigate the evolution of galaxy masses and star formation rates in the Evolution and Assembly of Galaxies and their Environment (EAGLE) simulations. These comprise a suite of hydrodynamical simulations in a $Lambda$CDM cosmogony with subgrid m
odels for radiative cooling, star formation, stellar mass loss, and feedback from stars and accreting black holes. The subgrid feedback was calibrated to reproduce the observed present-day galaxy stellar mass function and galaxy sizes. Here we demonstrate that the simulations reproduce the observed growth of the stellar mass density to within 20 per cent. The simulation also tracks the observed evolution of the galaxy stellar mass function out to redshift z = 7, with differences comparable to the plausible uncertainties in the interpretation of the data. Just as with observed galaxies, the specific star formation rates of simulated galaxies are bimodal, with distinct star forming and passive sequences. The specific star formation rates of star forming galaxies are typically 0.2 to 0.4 dex lower than observed, but the evolution of the rates track the observations closely. The unprecedented level of agreement between simulation and data makes EAGLE a powerful resource to understand the physical processes that govern galaxy formation.
We describe a numerical implementation of star formation in disk galaxies, in which the conversion of cooling gas to stars in the multiphase interstellar medium is governed by the rate at which molecular clouds are formed and destroyed. In the model,
clouds form from thermally unstable ambient gas and get destroyed by feedback from massive stars and thermal conduction. Feedback in the ambient phase cycles gas into a hot galactic fountain or wind. We model the ambient gas hydrodynamically using smoothed particle hydrodynamics (SPH). However, we cannot resolve the Jeans mass in the cold and dense molecular gas and, therefore, represent the cloud phase with ballistic particles that coagulate when colliding. We show that this naturally produces a multiphase medium with cold clouds, a warm disk, hot supernova bubbles and a hot, tenuous halo. Our implementation of this model is based on the Gadget N-Body code. We illustrate the model by evolving an isolated Milky Way-like galaxy and study the properties of a disk formed in a rotating spherical collapse. Many observed properties of disk galaxies are reproduced well, including the molecular cloud mass spectrum, the molecular fraction as a function of radius, the Schmidt law, the stellar density profile and the appearance of a galactic fountain.
We present a method for studying the proximity effect and the density structure around redshift z=2-3 quasars. It is based on the probability distribution of Lyman-alpha pixel optical depths and its evolution with redshift. We validate the method u
sing mock spectra obtained from hydrodynamical simulations, and then apply it to a sample of 12 bright quasars at redshifts 2-3 observed with UVES at the VLT-UT2 Kueyen ESO telescope. These quasars do not show signatures of associated absorption and have a mean monochromatic luminosity of 5.4 10^{31} h^{-2} erg/s/Hz at the Lyman limit. The observed distribution of optical depth within 10 Mpc/h from the QSO is statistically different from that measured in the general intergalactic medium at the same redshift. Such a change will result from the combined effects of the increase in photoionisation rate above the mean UV-background due to the extra ionizing photons from the quasar radiation (proximity effect), and the higher density of the IGM if the quasars reside in overdense regions (as expected from biased galaxy formation). The first factor decreases the optical depth whereas the second one increases the optical depth, but our measurement cannot distinguish a high background from a low overdensity. An overdensity of the order of a few is required if we use the amplitude of the UV-background inferred from the mean Lyman-$alpha$ opacity. If no overdensity is present, then we require the UV-background to be higher, and consistent with the existing measurements based on standard analysis of the proximity effect.
We study the ability of PINOCCHIO (PINpointing Orbit-Crossing Collapsed HIerarchical Objects) to predict the merging histories of dark matter (DM) haloes, comparing the PINOCCHIO predictions with the results of two large N-body simulations run from t
he same set of initial conditions. We focus our attention on quantities most relevant to galaxy formation and large-scale structure studies. PINOCCHIO is able to predict the statistics of merger trees with a typical accuracy of 20 per cent. Its validity extends to higher-order moments of the distribution of progenitors. The agreement is valid also at the object-by-object level, with 70-90 per cent of the progenitors cleanly recognised when the parent halo is cleanly recognised itself. Predictions are presented also for quantities that are usually not reproduced by semi-analytic codes, such as the two-point correlation function of the progenitors of massive haloes and the distribution of initial orbital parameters of merging haloes. For the accuracy of the prediction and for the facility with which merger histories are produced, PINOCCHIO provides a means to generate catalogues of DM haloes which is extremely competitive to large-scale N-body simulations, making it a suitable tool for galaxy formation and large-scale structure studies.
