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

TLDR: In this article, the authors present results from thirteen cosmological simulations that explore the parameter space of the "Evolution and Assembly of GaLaxies and their Environments" (EAGLE) simulation project.

Abstract: 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.