A Comparative Study of AGN Feedback Algorithms

Abstract

Modelling AGN feedback in numerical simulations is both technically and theoretically challenging, with numerous approaches having been published in the literature. We present a study of five distinct approaches to modelling AGN feedback within gravitohydrodynamic simulations of major mergers of Milky Way-sized galaxies. To constrain differences to only be between AGN feedback models, all simulations start from the same initial conditions and use the same star formation algorithm. Most AGN feedback algorithms have five key aspects: black hole accretion rate, energy feedback rate and method, particle accretion algorithm, black hole advection algorithm, and black hole merger algorithm. All models follow different accretion histories, with accretion rates that differ by up to three orders of magnitude at any given time. We consider models with either thermal or kinetic feedback, with the associated energy deposited locally around the black hole. Each feedback algorithm modifies the gas properties near the black hole to different extents. The particle accretion algorithms usually (but not always) maintain good agreement between the mass accreted by \dot{M} dt and the mass of gas particles removed from the simulation. The black hole advection algorithms dampen inappropriate dragging of the black holes by two-body interactions. Advecting the black hole a limited distance based upon local mass distributions has many desirably properties. The black holes merge when given criteria are met, and we find a range of merger times for different criteria. Using the M_{BH}-σrelation as a diagnostic of the remnants yields three models that lie within the one-sigma scatter of the observed relation and two that fall below it. The wide variation in accretion behaviours of the models reinforces the fact that there remains much to be learnt about the evolution of galactic nuclei. (abridged)