The EAGLE simulations of galaxy formation: calibration of subgrid physics and model variations

By Robert A. Crain, Joop Schaye, Richard G. Bower, Michelle Furlong, Matthieu Schaller, Tom Theuns, Claudio Dalla Vecchia, Carlos S. Frenk, Ian G. McCarthy, John C. Helly and 4 more. 2015

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We present results from thirteen cosmological simulations that explore the parameter space of the "Evolution and Assembly of GaLaxies and their Environments" (EAGLE) simulation project. Four of the simulations follow the evolution of a periodic cube L = 50 cMpc on a side, and each employs a different subgrid model of the energetic feedback associated with star formation. The relevant parameters were adjusted so that the simulations each reproduce the observed galaxy stellar mass function at z = 0.1. Three of the simulations fail to form disc galaxies as extended as observed, and we show analytically that this is a consequence of numerical radiative losses that reduce the efficiency of stellar feedback in high-density gas. Such losses are greatly reduced in the fourth simulation - the EAGLE reference model - by injecting more energy in higher density gas. This model produces galaxies with the observed size distribution, and also reproduces many galaxy scaling relations. In the remaining nine simulations, a single parameter or process of the reference model was varied at a time. We find that the properties of galaxies with stellar mass <~ M* (the "knee" of the galaxy stellar mass function) are largely governed by feedback associated with star formation, while those of more massive galaxies are also controlled by feedback from accretion onto their central black holes. Both processes must be efficient in order to reproduce the observed galaxy population. In general, simulations that have been calibrated to reproduce the low-redshift galaxy stellar mass function will still not form realistic galaxies, but the additional requirement that galaxy sizes be acceptable leads to agreement with a large range of observables.

Subfields: Astronomy and Astrophysics, Instrumentation

View Paper: https://www.semanticscholar.org/paper/8cc875e9ef775f90146b2ec1811d3385007c5379

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Citations in the corpus

First results from the IllustrisTNG simulations: the stellar mass content of groups and clusters of galaxies (2017, positive): “Still, projects like Illustris (Vogelsberger et al. 2014b,a; Genel et al. 2014; Sijacki et al. 2015) and EAGLE (Schaye et al. 2015; Crain et al. 2015) have shown that hydrodynamical simulations with sub-grid models tailored to such resolutions can reproduce many structural properties and scaling…”
The unexpected diversity of dwarf galaxy rotation curves (2015, methodology): “2 C I R C U L A R V E L O C I T Y P RO F I L E S O F S I M U L AT E D G A L A X I E S We discuss here the circular velocity curves of galaxies selected from the EAGLE (Crain et al. 2015; Schaye et al. 2015) and LG (Sawala et al. 2015) simulation projects.”
An ALMA survey of the SCUBA-2 CLS UDS field: physical properties of 707 sub-millimetre galaxies (2019, methodology): “We, therefore, take advantage of the simulated galaxies from the Evolution and Assembly of GaLaxies and their Environments (EAGLE; Schaye et al. 2015; Crain et al. 2015) galaxy formation model to test how well MAGPHYS recovers the intrinsic properties of realistic model galaxies.”
MUFASA: Galaxy Formation Simulations With Meshless Hydrodynamics (2016, methodology): “Crain et al. (2015) describes the process of tuning EAGLE’s input physics in order to obtain this agreement, though it is worth noting that their mass function mostly emerged rather naturally, and much of the tuning was done to match galaxy sizes.”
The APOSTLE simulations: solutions to the Local Group's cosmic puzzles (2015, methodology): “The injected energy is calibrated to reproduce the observed, z = 0 galaxy stellar mass function and sizes (Crain et al. 2015).”
A unified multiwavelength model of galaxy formation (2015, methodology): “…contain various free parameters, which are then adjusted so that, in analogy to semi-analytical models, the predictions from the simulation agree with a predetermined set of observed properties such as the stellar mass function (e.g. Vogelsberger et al. 2014; Schaye et al. 2015; Crain et al. 2015).”
The optical morphologies of galaxies in the IllustrisTNG simulation: a comparison to Pan-STARRS observations (2018, methodology): “This motivated Camps et al. (2016) and Trayford et al. (2017), using the EAGLE cosmological simulation (Schaye et al. 2015; Crain et al. 2015), to implement a post-processing resampling technique to model the expected frequency of young stellar populations at a higher resolution.”
How to Measure Galaxy Star Formation Histories. II. Nonparametric Models (2018, background): “…the gas accretion rate) as in the equilibrium bathtub model (e.g. Davé et al. 2011; Forbes et al. 2014) and cosmological hydrodynamical simulations (Crain et al. 2015; Schaye et al. 2015; Pillepich et al. 2018) or it is set by the timescales of star formation feedback as in the high-resolution…”
The Local Group on FIRE: dwarf galaxy populations across a suite of hydrodynamic simulations (2018, methodology): “…example, apply the EAGLE models for galaxy formation, which are tuned to reproduce the stellar mass function (SMF) and sizes of galaxies at z = 0.1 (Crain et al. 2015; Schaye et al. 2015), to 12 LG-like volumes,2 1The Auriga simulations (Grand et al. 2017), high-resolution magnetohydrodynamic…”
The size evolution of star-forming and quenched galaxies in the IllustrisTNG simulation (2017, background): “Crain et al. (2015) found that galaxy sizes can serve as important constraints on feedback models, Ferrero et al. (2017) showed that realistic sizes and their evolution are crucial for reproducing the Tully-Fisher relation and its evolution, and Desmond et al. (2016) found that galaxy sizes depend…”
Bimodality of low-redshift circumgalactic O VI in non-equilibrium EAGLE zoom simulations (2016, background): “…into the ISM depends on the local gas metallicity (Z) to account for more efficient cooling at higher Z, and the local gas density to compensate for artificial radia- c© 2016 RAS, MNRAS 000, 000–000 tive losses that occur at high density (see S15; Crain et al. 2015, for further motivation).”
Galaxy Alignments: An Overview (2015, methodology): “The implementation of the physics behind these processes will have to mature to a degree that hydrodynamic simulations can simultaneously predict galaxy alignments and basic observables such as the number density of galaxies as a function of their luminosity and the mass-size relation (perhaps via c”
Small scale problems of the $\Lambda$CDM model: a short review (2016, methodology): “Recently, the combination of the large EAGLE simulation programme [140,141] — calibrated on small scales on observed galaxy stellar mass function and present radius but not on the BTFR, with multiple realisations of Local Group-like galaxies in smaller volume, i.”