No Arabic abstract
State-of-the-art cosmological hydrodynamical simulations of galaxy formation have reached the point at which their outcomes result in galaxies with ever more realism. Still, the employed sub-grid models include several free parameters such as the density threshold, $n$, to localize the star-forming gas. In this work, we investigate the possibilities to utilize the observed clustered nature of star formation (SF) in order to refine SF prescriptions and constrain the density threshold parameter. To this end, we measure the clustering strength, correlation length and power-law index of the two-point correlation function of young ($tau<50$ Myr) stellar particles and compare our results to observations from the HST Legacy Extragalactic UV Survey (LEGUS). Our simulations reveal a clear trend of larger clustering signal and power-law index and lower correlation length as the SF threshold increases with only mild dependence on galaxy properties such as stellar mass or specific star formation rate. In conclusion, we find that the observed clustering of SF is inconsistent with a low threshold for SF ($n<1$ cm$^{-3}$) and strongly favours a high value for the density threshold of SF ($n>10$ cm$^{-3}$), as for example employed in the NIHAO project.
Recent analyses of mass segregation diagnostics in star forming regions invite a comparison with the output of hydrodynamic simulations of star formation. In this work we investigate the state of mass segregation of stars (i.e. sink particles in the simulations) in the case of hydrodynamical simulations which omit feedback. We first discuss methods to quantify mass segregation in substructured regions, either based on the minimum spanning tree (Allisons Lambda), or through analysis of correlations between stellar mass and local stellar surface number densities. We find that the presence of even a single outlier (i.e. a massive object far from other stars) can cause the Allison Lambda method to describe the system as inversely mass segregated, even where in reality the most massive sink particles are overwhelmingly in the centres of the subclusters. We demonstrate that a variant of the Lambda method is less susceptible to this tendency but also argue for an alternative representation of the data in the plane of stellar mass versus local surface number density. The hydrodynamical simulations show global mass segregation from very early times which continues throughout the simulation, being only mildly influenced during sub-cluster merging. We find that up to approx. 2-3% of the massive sink particles (m > 2.5 Msun) are in relative isolation because they have formed there, although other sink particles can form later in their vicinity. Ejections of massive sinks from subclusters do not contribute to the number of isolated massive sink particles, as the gravitational softening in the calculation suppresses this process.
We study the properties of two bars formed in fully cosmological hydrodynamical simulations of the formation of Milky Way-mass galaxies. In one case, the bar formed in a system with disc, bulge and halo components and is relatively strong and long, as could be expected for a system where the spheroid strongly influences the evolution. The second bar is less strong, shorter, and formed in a galaxy with no significant bulge component. We study the strength and length of the bars, the stellar density profiles along and across the bars and the velocity fields in the bar region. We compare them with the results of dynamical (idealised) simulations and with observations, and find, in general, a good agreement, although we detect some important differences as well. Our results show that more or less realistic bars can form naturally in a $Lambda$CDM cosmology, and open up the possibility to study the bar formation process in a more consistent way than previously done, since the host galaxies grow, accrete matter and significantly evolve during the formation and evolution of the bar.
We explored the role of X-ray binaries composed by a black hole and a massive stellar companion (BHXs) as sources of kinetic feedback by using hydrodynamical cosmological simulations. Following previous results, our BHX model selects low metal-poor stars ($Z = [0,10^{-4}]$) as possible progenitors. The model that better reproduces observations assumes that a $sim 20%$ fraction of low-metallicity black holes are in binary systems which produce BHXs. These sources are estimated to deposit $sim 10^{52}$ erg of kinetic energy per event. With these parameters and in the simulated volume, we find that the energy injected by BHXs represents $sim 30%$ of the total energy released by SNII and BHX events at redshift $zsim7$ and then decreases rapidly as baryons get chemically enriched. Haloes with virial masses smaller than $sim 10^{10} ,M_{odot}$ (or $T_{rm vir} lesssim 10^5 $ K) are the most directly affected ones by BHX feedback. These haloes host galaxies with stellar masses in the range $10^7 - 10^8$ M$_odot$. Our results show that BHX feedback is able to keep the interstellar medium warm, without removing a significant gas fraction, in agreement with previous analytical calculations. Consequently, the stellar-to-dark matter mass ratio is better reproduced at high redshift. Our model also predicts a stronger evolution of the number of galaxies as a function of the stellar mass with redshift when BHX feedback is considered. These findings support previous claims that the BHXs could be an effective source of feedback in early stages of galaxy evolution.
We measure the gas disc thicknesses of the edge-on galaxy NGC 4013 and the less edge-on galaxies (NGC 4157 and 5907) using CO (CARMA/OVRO) and/or HI (EVLA) observations. We also estimate the scale heights of stars and/or the star formation rate (SFR) for our sample of five galaxies using Spitzer IR data (3.6 $mu$m and 24 $mu$m). We derive the average volume densities of the gas and the SFR using the measured scale heights along with radial surface density profiles. Using the volume density that is more physically relevant to the SFR than the surface density, we investigate the existence of a volumetric star formation law (SFL), how the volumetric SFL is different from the surface-density SFL, and how the gas pressure regulates the SFR based on our galaxy sample. We find that the volumetric and surface SFLs in terms of the total gas have significantly different slopes, while the volumetric and surface SFLs in terms of the molecular gas do not show any noticeable difference. The volumetric SFL for the total gas has a flatter power-law slope of 1.26 with a smaller scatter of 0.19 dex compared to the slope (2.05) and the scatter (0.25 dex) of the surface SFL. The molecular gas SFLs have similar slopes of 0.78 (volume density) and 0.77 (surface density) with the same rms scatter. We show that the interstellar gas pressure is strongly correlated with the SFR but find no significant difference between the correlations based on the volume and surface densities.
This article describes a data center hosting a web portal for accessing and sharing the output of large, cosmological, hydro-dynamical simulations with a broad scientific community. It also allows users to receive related scientific data products by directly processing the raw simulation data on a remote computing cluster. The data center has a multi-layer structure: a web portal, a job control layer, a computing cluster and a HPC storage system. The outer layer enables users to choose an object from the simulations. Objects can be selected by visually inspecting 2D maps of the simulation data, by performing highly compounded and elaborated queries or graphically by plotting arbitrary combinations of properties. The user can run analysis tools on a chosen object. These services allow users to run analysis tools on the raw simulation data. The job control layer is responsible for handling and performing the analysis jobs, which are executed on a computing cluster. The innermost layer is formed by a HPC storage system which hosts the large, raw simulation data. The following services are available for the users: (I) {sc ClusterInspect} visualizes properties of member galaxies of a selected galaxy cluster; (II) {sc SimCut} returns the raw data of a sub-volume around a selected object from a simulation, containing all the original, hydro-dynamical quantities; (III) {sc Smac} creates idealised 2D maps of various, physical quantities and observables of a selected object; (IV) {sc Phox} generates virtual X-ray observations with specifications of various current and upcoming instruments.