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The EAGLE simulations of galaxy formation: public release of halo and galaxy catalogues

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 Added by Stuart McAlpine
 Publication date 2015
  fields Physics
and research's language is English




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We present the public data release of halo and galaxy catalogues extracted from the EAGLE suite of cosmological hydrodynamical simulations of galaxy formation. These simulations were performed with an enhanced version of the GADGET code that includes a modified hydrodynamics solver, time-step limiter and subgrid treatments of baryonic physics, such as stellar mass loss, element-by-element radiative cooling, star formation and feedback from star formation and black hole accretion. The simulation suite includes runs performed in volumes ranging from 25 to 100 comoving megaparsecs per side, with numerical resolution chosen to marginally resolve the Jeans mass of the gas at the star formation threshold. The free parameters of the subgrid models for feedback are calibrated to the redshift z=0 galaxy stellar mass function, galaxy sizes and black hole mass - stellar mass relation. The simulations have been shown to match a wide range of observations for present-day and higher-redshift galaxies. The raw particle data have been used to link galaxies across redshifts by creating merger trees. The indexing of the tree produces a simple way to connect a galaxy at one redshift to its progenitors at higher redshift and to identify its descendants at lower redshift. In this paper we present a relational database which we are making available for general use. A large number of properties of haloes and galaxies and their merger trees are stored in the database, including stellar masses, star formation rates, metallicities, photometric measurements and mock gri images. Complex queries can be created to explore the evolution of more than 10^5 galaxies, examples of which are provided in appendix. (abridged)



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We present results from a subset of simulations from the Evolution and Assembly of GaLaxies and their Environments (EAGLE) suite in which the formulation of the hydrodynamics scheme is varied. We compare simulations that use the same subgrid models without re-calibration of the parameters but employing the standard GADGET flavour of smoothed particle hydrodynamics (SPH) instead of the more recent state-of-the-art ANARCHY formulation of SPH that was used in the fiducial EAGLE runs. We find that the properties of most galaxies, including their masses and sizes, are not significantly affected by the details of the hydrodynamics solver. However, the star formation rates of the most massive objects are affected by the lack of phase mixing due to spurious surface tension in the simulation using standard SPH. This affects the efficiency with which AGN activity can quench star formation in these galaxies and it also leads to differences in the intragroup medium that affect the X-ray emission from these objects. The differences that can be attributed to the hydrodynamics solver are, however, likely to be less important at lower resolution. We also find that the use of a time step limiter is important for achieving the feedback efficiency required to match observations of the low-mass end of the galaxy stellar mass function.
As part of the AGORA High-resolution Galaxy Simulations Comparison Project (Kim et al. 2014, 2016) we have generated a suite of isolated Milky Way-mass galaxy simulations using 9 state-of-the-art gravito-hydrodynamics codes widely used in the numerical galaxy formation community. In these simulations we adopted identical galactic disk initial conditions, and common physics models (e.g., radiative cooling and ultraviolet background by a standardized package). Subgrid physics models such as Jeans pressure floor, star formation, supernova feedback energy, and metal production were carefully constrained. Here we release the simulation data to be freely used by the community. In this release we include the disk snapshots at 0 and 500Myr of evolution per each code as used in Kim et al. (2016), from simulations with and without star formation and feedback. We encourage any member of the numerical galaxy formation community to make use of these resources for their research - for example, compare their own simulations with the AGORA galaxies, with the common analysis yt scripts used to obtain the plots shown in our papers, also available in this release.
We present the full public release of all data from the TNG50, TNG100 and TNG300 simulations of the IllustrisTNG project. IllustrisTNG is a suite of large volume, cosmological, gravo-magnetohydrodynamical simulations run with the moving-mesh code Arepo. TNG includes a comprehensive model for galaxy formation physics, and each TNG simulation self-consistently solves for the coupled evolution of dark matter, cosmic gas, luminous stars, and supermassive blackholes from early time to the present day, z=0. Each of the flagship runs -- TNG50, TNG100, and TNG300 -- are accompanied by lower-resolution and dark-matter only counterparts, and we discuss scientific and numerical cautions and caveats relevant when using TNG. Full volume snapshots are available at 100 redshifts; halo and subhalo catalogs at each snapshot and merger trees are also released. The data volume now directly accessible online is ~1.1 PB, including 2,000 full volume snapshots and ~110,000 high time-resolution subbox snapshots. Data access and analysis examples are available in IDL, Python, and Matlab. We describe improvements and new functionality in the web-based API, including on-demand visualization and analysis of galaxies and halos, exploratory plotting of scaling relations and other relationships between galactic and halo properties, and a new JupyterLab interface. This provides an online, browser-based, near-native data analysis platform which supports user computation with fully local access to TNG data, alleviating the need to download large simulated datasets.
237 - Mark Vogelsberger 2019
Over the last decades, cosmological simulations of galaxy formation have been instrumental for advancing our understanding of structure and galaxy formation in the Universe. These simulations follow the non-linear evolution of galaxies modeling a variety of physical processes over an enormous range of scales. A better understanding of the physics relevant for shaping galaxies, improved numerical methods, and increased computing power have led to simulations that can reproduce a large number of observed galaxy properties. Modern simulations model dark matter, dark energy, and ordinary matter in an expanding space-time starting from well-defined initial conditions. The modeling of ordinary matter is most challenging due to the large array of physical processes affecting this matter component. Cosmological simulations have also proven useful to study alternative cosmological models and their impact on the galaxy population. This review presents a concise overview of the methodology of cosmological simulations of galaxy formation and their different applications.
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 models 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.
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