Simulating feedback from Active Galactic Nuclei in galaxies, groups and clusters

UoM administered thesis: Doctoral Thesis

  • Authors:
  • Richard Newton


By performing 542 high resolution N-body+SPH simulations of Milky-Way like galaxies, galaxy groups and clusters of galaxies, we investigate the effect of feedback by anactive galactic nucleus (AGN) on the evolution of these objects and the black holes theyhost. We first analyse the role of AGN within isolated Milky-Way like galaxies and majormergers between them, utilising a selection of methods from the literature, additionallyincluding supernova feedback. We find that AGN and supernova feedback are largelyindependent, and that although current AGN models are highly susceptible to numericaleffects, the temperature to which gas is heated is important for determining the impacton the host. Having investigated the effects on galaxy-scales, we then apply the existingAGN models to idealised equilibrium groups and clusters of galaxies and identify the keycomponents of an AGN model which is active in more massive systems. By simulatingmassive objects we learn of how AGN behave in a radically different regime where theyare thought to perform a maintenance role and support the cluster against radiative cooling. Simulations of existing AGN models find that they do not provide sufficient heatingto the wider cluster environment to prevent catastrophic cooling, whilst over-heating thegalaxy groups. Finally, we develop and introduce an anisotropic feedback method whichsimulates jet AGN feedback, and a hybrid model which includes both jet and quasar feedback. Such descriptions better match observed phenomenology as they produce spatiallyconcentrated feedback which penetrates its surroundings more effectively, producing jetsand bubbles in the cluster gas. Through this work we have found that the inclusion ofAGN is a crucial, if challenging, part of a modern galaxy evolution simulation, which ishighly sensitive to the modelling of feedback.


Original languageEnglish
Awarding Institution
Award date1 Aug 2015