Evolution of galaxy stellar masses and star formation rates in the eagle simulations

By Michelle Furlong, Richard G. Bower, Tom Theuns, Joop Schaye, Robert A. Crain, Matthieu Schaller, Claudio Dalla Vecchia, Carlos S. Frenk, Ian G. McCarthy, John C. Helly and 2 more. 2014

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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.

Subfields: Astronomy and Astrophysics, Instrumentation

View Paper: https://www.semanticscholar.org/paper/0d7db54d612453d4addb09c06321648c6ced305c

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Citations in the corpus

The BAHAMAS project: Calibrated hydrodynamical simulations for large-scale structure cosmology (2016, result): “…observations at low and high masses is, however, relatively modest and the level of agreement over this mass range is as good as that reported for other recent (generally much higher resolution) simulation studies such as EAGLE (see Furlong et al. 2015) and Illustris (see Genel et al. 2014).”
The Horizon-AGN simulation: evolution of galaxy properties over cosmic time (2016, methodology): “In the redshift range studied here, most simulations that are similar to HorizonAGN produce reasonably good agreement with data (e.g. Furlong et al. 2015; Genel et al. 2014; Khandai et al. 2015), although a detailed comparison between models is difficult, because all models are typically not…”
The dark nemesis of galaxy formation : why hot haloes trigger black hole growth and bring star formation to an end (2016, methodology): “The reference EAGLE simulation accurately predicts the bimodality of galaxy types and the existence of a tight and rapidly evolving sequence of star formation growth timescales in blue-sequence galaxies (Furlong et al. 2015b; Trayford et al. 2016).”
Theoretical Challenges in Galaxy Formation (2016, background): “…for one of the most successful cosmological galaxy formation simulation suite (the Eagle simulations, Schaye et al. 2015) in terms of matching observed galaxy population properties and their evolution with redshift (Bahé et al. 2016, Furlong et al. 2015, Rahmati et al. 2015, Schaye et al. 2015).”
The star formation activity of IllustrisTNG galaxies: main sequence, UVJ diagram, quenched fractions, and systematics (2018, result): “8, top panels, could be characterized using a Gaussian mixture modeling, as recently proposed for e.g. the Illustris, EAGLE and Mufasa results by Hahn et al. (2018), but it is unclear whether the medians of such multiple Gaussians would identify distinct classes of galaxies or simply represent a num”
Molecular hydrogen abundances of galaxies in the EAGLE simulations (2015, methodology): “This difference is similar to the difference seen by S15 and Furlong et al. (2015) in the z = 0.1 galactic stellar mass function in the same set of simulations.”
(Star)bursts of FIRE: observational signatures of bursty star formation in galaxies (2015, background): “This relation is also important because its normalisation and scatter may provide important constraints on galaxy formation physics (Torrey et al. 2014; Sparre et al. 2015; Furlong et al. 2015; Mitra et al. 2015; but cf. Kelson 2014).”
Colours and luminosities of z = 0.1 galaxies in the eagle simulation (2015, methodology): “In contrast, at higher galaxy masses it is thought to be the feedback from accreting black holes (BHs) that introduces a near exponential cut-off in the GSMF (Bower et al. 2006; Croton et al. 2006).”
Bimodality of low-redshift circumgalactic O VI in non-equilibrium EAGLE zoom simulations (2016, background): “Furthermore, because EAGLE reproduces key stellar and cold ISM properties of galaxies (e.g. S15; Furlong et al. 2015, 2016; Lagos et al. 2015a,b; Trayford et al. 2015; Bahé et al. 2016; Segers et al. 2015), while explicitly following the hydrodynamics, it is an ideal testbed for this study and…”
The COSMOS2015 galaxy stellar mass function . Thirteen billion years of stellar mass assembly in ten snapshots (2017, methodology): “…simulations are often (but not always, see e.g. Dubois et al. 2014) calibrated against the local SMF (e.g. Guo et al. 2011, 2013; Genel et al. 2014; Schaye et al. 2016); measurements at z > 0 are then used to test theoretical predictions (Torrey et al. 2014; Furlong et al. 2015, and many others).”
The milky way total mass profile as inferred from Gaia DR2 (2019, background): “…Duffy et al. 2010; Dutton et al. 2016; Artale et al. 2019); the good agreement between the halo contraction predictions in our three simulations suites reflects the fact that these simulations have galaxy growth histories that match observations (see Furlong et al. 2015, and discussion therein).”
The unexpected diversity of dwarf galaxy rotation curves (2015, background): “We emphasize that, although our simulations do not form ‘cores’, they do produce galaxies whose abundance, structural properties, and evolution seem in good accord with observational constraints (see e.g. Sawala et al. 2014; Schaller et al. 2015; Furlong et al. 2015; Schaye et al. 2015).”
The EAGLE simulations of galaxy formation: the importance of the hydrodynamics scheme (2015, methodology): “…et al. 2015), the H2 and H I properties of galaxies (Lagos et al. 2015, Bahe et al. submitted), the evolution of the galaxy stellar mass function (Furlong et al. 2015), the column density distribution of intergalactic metals (Schaye et al. 2015) and H I (Rahmati et al. 2015) as well as galaxy…”
Size evolution of normal and compact galaxies in the EAGLE simulation (2015, methodology): “An aperture of twice the half-mass radius is used to measure the stellar masses and SFRs, as was applied in previous ILLUSTRIS publications.”
The effect of the metallicity-specific star formation history on double compact object mergers (2019, methodology): “The numbers in the column GSMF refer to 1 = Panter et al. (2004), 2 = Furlong et al. (2015) (single Schechter function), 3 = Furlong et al. (2015) (double Schechter function).”
The APOSTLE simulations: solutions to the Local Group's cosmic puzzles (2015, methodology): “In addition, the EAGLE simulations also successfully reproduce many other properties and scaling laws of observed galaxy populations, including the evolution of the stellar mass function (Furlong et al. 2015), and the luminosities and colours of galaxies (Trayford et al. 2015).”
Deriving Physical Properties from Broadband Photometry with Prospector: Description of the Model and a Demonstration of its Accuracy Using 129 Galaxies in the Local Universe (2016, background): “Hydrodynamical simulations (e.g., Genel et al. 2014; Torrey et al. 2014; Furlong et al. 2015), semi-analytical models (e.g., Mitchell et al. 2014; Henriques et al. 2015), and pure analytic models (e.g., Lilly et al. 2013; Dekel & Burkert 2014) are all systematically offset from observations of…”