
Consortium
A new model of black hole growth and AGN feedback: an analytic model that explains the phenomenology seen in the EAGLE simulations as well as the observed colour bimodality in the galaxy population. In galaxies less massive than 3×1010 M☉, young stars and supernovae drive a high entropy outflow. Above a halo mass of 1012 M☉ the outflow ceases to be buoyant and star formation is unable to prevent the build-up of gas in the central regions, triggering a strongly non-linear response from the black hole. Its accretion rate rises rapidly, disrupting the incoming supply of cool gas and starving the galaxy of fuel. The host galaxy makes a transition to the red sequence.

A new theory for the nature of the galaxies that reionised the Universe, based on the EAGLE simulations, in which bursts of star formation can create channels through which ionising photons escape. It was shown that carbon-enhanced metal poor (CEMP) stars are the siblings of the stars that reionised the Universe. Today, these may be found in the intracluster light in groups and clusters.
Construction and analysis of synthetic HI rotation curves of dwarf galaxies in the APOSTLE cosmological simulations of Local Group analogues. Using the same techniques employed by observers (e.g. tllted ring modelling), for each individual galaxy a large diversity of rotation curves is obtained, depending on the orientation of the line of sight. These variations arise from non-circular motions in the gas. As a result, the presence of a core in the dark matter distribution is sometimes incorrectly inferred when there is actually a central cusp, as predicted in the simplest Λ-CDM models.
Completion of the C-EAGLE set of 30 galaxy cluster resimulations using the EAGLE code (including examples with self-interacting dark matter). Their X-ray properties, such as the spectroscopic temperature soft-band luminosity, metal content and Sunyaev-Zel’dovich properties, are in agreement with the observed relations.

A new implementation of radiation feedback on galactic scales whereby star formation and the effects of their radiation field on the evolution of the gas are calculated self-consistently.
The first simulations that self-consistently follow the formation and evolution of star clusters and their host galaxy in a full cosmological setting. These “E-MOSAIC” simulations graft the MOSAICS semi-analytic model of star cluster formation and evolution into the EAGLE simulations (see Figure 1).
Simulations of galaxy formation using the EAGLE code in models where the dark matter consists of (warm) sterile neutrinos. Large regions of the sterile neutrino parameter space can be ruled because not enough satellite galaxies are produced.
An explanation for the mass discrepancy-radial acceleration relation (MDAR) of disc galaxies in the context of Λ-CDM and its verification in the EAGLE and APOSTLE hydrodynamics simulations, demonstrating that the MDAR does not require MOND.
Using artificial neural networks to constrain the halo baryon fraction during reionization.Radiative feedback from stars and galaxies has been proposed as a potential solution to many of the tensions with simplistic galaxy formation models based on Λ-CDM, such as the faint end of the UV luminosity function. The total energy budget of radiation could exceed that of galactic winds and supernovae combined, which has driven the development of sophisticated algorithms that evolve both the radiation field and the hydrodynamical response of gas simultaneously, in a cosmological context. In Sullivan, Iliev and Dixon (2018) we probed self-feedback on galactic scales using the adaptive mesh refinement, radiative transfer, hydrodynamics, and N-body code Ramses-RT. Unlike previous studies which assume a homogeneous UV background, we self-consistently evolved both the radiation field and gas to constrain the halo baryon fraction during cosmic reionization. We demonstrated that the characteristic halo mass with mean baryon fraction half the cosmic mean, Mc(z), shows very little variation as a function of mass-weighted ionization fraction. Furthermore, we found that the inclusion of metal cooling and the ability to resolve scales small enough for self-shielding to become efficient leads to a significant drop in Mc when compared to recent studies. Finally, we developed an Artificial Neural Network that is capable of predicting the baryon fraction of haloes based on recent tidal interactions, gas temperature, and mass-weighted ionization fraction. Such a model can be applied to any reionization history, and trivially incorporated into semi-analytical models of galaxy formation.
