Accretion and Feedback Processes in Supermassive Black Holes
thesisposted on 19.12.2012, 13:51 authored by Kastytis Zubovas
Supermassive black holes (SMBHs) have been gradually recognised as important elements of galaxy and cosmic structure evolution. Their connection with the large-scale environment is maintained via feedback processes – communication of a fraction of the accretion luminosity to the host galaxy. Feedback is conjectured to expel gas from galaxies, quench star formation and establish the observed correlations between SMBH mass and host galaxy properties. Efficient feedback requires rapid gas accretion and is therefore usually investigated within the context of quasar activity phases in SMBH evolution. In this Thesis, I investigate several implications of an SMBH wind feedback model, advancing our understanding of feedback processes and the immediate environment of SMBHs. I consider analytically the large-scale outflows and their observable properties. I find that rapidly accreting SMBHs may sweep galaxies clear of gas, turning them into red-and-dead spheroids. I apply the same feedback model to our Galaxy. Its SMBH, Sgr A∗, is currently exceptionally quiescent, although it must have been more active in the past in order to have grown to its present size. I investigate, both analytically and numerically, a short burst of activity which may have occurred ∼ 6 million years ago, producing an outflow which formed two large γ-ray emitting bubbles perpendicular to the Galactic plane. The results show that dynamical footprints of outflows may persist for a long time and provide evidence of past AGN activity in quiescent galaxies. I also present a model for the short-timescale flares observed daily in Sgr A∗, based on tidal disruption and evaporation of asteroids in the vicinity of the SMBH. The model explains some observed flare properties, and thus improves our understanding of the processes occurring close to the SMBH. It also provides predictions for observable effects as the quiescent luminosity of Sgr A∗ varies on long timescales.