Simulating galaxy formation with black hole driven thermal and kinetic feedback

By R. Weinberger, Volker Springel, L. Hernquist, A. Pillepich, F. Marinacci, Rüdiger Pakmor, D. Nelson, Shy Genel, M. Vogelsberger, Jill P. Naiman and 1 more. 2016

684 citations recorded by the source corpus.

The inefficiency of star formation in massive elliptical galaxies is widely believed to be caused by the interactions of an active galactic nucleus (AGN) with the surrounding gas. Achieving a sufficiently rapid reddening of moderately massive galaxies without expelling too many baryons has however proven difficult for hydrodynamical simulations of galaxy formation, prompting us to explore a new model for the accretion and feedback effects of supermassive black holes. For high-accretion rates relative to the Eddington limit, we assume that a fraction of the accreted rest mass energy heats the surrounding gas thermally, similar to the ‘quasar mode’ in previous work. For low-accretion rates, we invoke a new, pure kinetic feedback model that imparts momentum to the surrounding gas in a stochastic manner. These two modes of feedback are motivated both by theoretical conjectures for the existence of different types of accretion flows as well as recent observational evidence for the importance of kinetic AGN winds in quenching galaxies. We find that a large fraction of the injected kinetic energy in this mode thermalizes via shocks in the surrounding gas, thereby providing a distributed heating channel. In cosmological simulations, the resulting model produces red, non-star-forming massive elliptical galaxies, and achieves realistic gas fractions, black hole growth histories and thermodynamic profiles in large haloes.

Subfields: Astronomy and Astrophysics, Computational Mechanics

View Paper: https://www.semanticscholar.org/paper/9fc0b7908ca6fa06c35b6d7e93401cc75761dadc

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Citations in the corpus

First results from the IllustrisTNG simulations: matter and galaxy clustering (2017, methodology): “…to our previous Illustris simulation physics model (Vogelsberger et al. 2013) are an updated kinetic AGN feedback model for the low accretion state (Weinberger et al. 2017b), an improved parametrization of galactic winds (Pillepich et al. 2018), and the inclusion of magnetic fields based on ideal…”
First results from the IllustrisTNG simulations: a tale of two elements - chemical evolution of magnesium and europium (2017, methodology): “…al. 2014a,b; Genel et al. 2014; Sijacki et al. 2015), which employs the moving mesh code AREPO (Springel 2010a) to evolve the gravitational and hydrodynamical equations combined with the galaxy formation physics module described extensively in Weinberger et al. (2017) and Pillepich et al. (2017).”
The optical morphologies of galaxies in the IllustrisTNG simulation: a comparison to Pan-STARRS observations (2018, methodology): “…cosmological simulations run with the moving-mesh code AREPO (Springel 2010; Pakmor et al. 2011, 2016), featuring an updated version of the Illustris galaxy formation model (Vogelsberger et al. 2013; Torrey et al. 2014) described in Weinberger et al. (2017) and Pillepich et al. (2018a).”
The Auriga Project: the properties and formation mechanisms of disc galaxies across cosmic time (2016, background): “This is particularly true for the cases in which the effects of non-linear feedback cycles, especially those driven by AGN, affect a wide range of physical scales (e.g. Springel et al. 2005; Sijacki et al. 2007; Dubois et al. 2013; Weinberger et al. 2017).”
Simulating galaxy formation with the IllustrisTNG model (2017, methodology): “All details related to the seeding, growth and feedback of black holes in the TNG model, including their impact on the galaxy population, are given in the companion paper by Weinberger et al. (2017).”
First results from the IllustrisTNG simulations: the stellar mass content of groups and clusters of galaxies (2017, methodology): “Improvements in the adopted AGN feedback mechanisms at low accretion rates (Weinberger et al. 2017) and the refined galactic winds regulating lower mass galaxies (Pillepich et al. 2018) give us confidence in the TNG model outcome, both in terms of mass budget within the central galaxy as well as in…”
CMB-S4 Science Case, Reference Design, and Project Plan (2019, neutral): “[396, 397], EAGLE [398], and IllustrisTNG-300 [399, 400, 401].”
First results from the IllustrisTNG simulations: radio haloes and magnetic fields (2017, methodology): “This is due to the difference in the implementation of the AGN feedback model (see Weinberger et al. 2017), which is less bursty in the IllustrisTNG simulations compared to the original Illustris model used in Marinacci et al. (2015).”
First results from the TNG50 simulation: galactic outflows driven by supernovae and black hole feedback (2019, background): “…the directionality of the wind-phase mass is entirely random at launch (see Pillepich et al. 2018a), while BH energy injection in the low accretion state kinetic mode, which drives the outflows seen here at high-mass, is also entirely random with each injection event (see Weinberger et al. 2017).”
simba: Cosmological simulations with black hole growth and feedback (2019, result): “(iii) At low- fEdd, IllustrisTNG randomises the direction of the jets at each timestep, rather than always ejecting jets perpendicular to the inner disk.”
First results from the IllustrisTNG simulations: the galaxy colour bimodality (2017, methodology): “In the TNG model, blackholes enter the low-state when their accretion rate relative to Eddington drops below a threshold Ṁ/Ṁedd < χ(MBH) which depends on the blackhole mass (Weinberger et al. 2017, Eqn.”
Active galactic nuclei: what’s in a name? (2017, background): “Tchekhovskoy 2015; Waters and Proga 2016), and the impact of this feedback on host galaxies and halos (e.g. Dubois et al. 2016; McAlpine et al. 2017; Weinberger et al. 2017).”
Impact of supermassive black hole growth on star formation (2017, background): “However, recently simulations have incorporated more complex prescriptions for “feeback” by invoking and testing multiple modes of energy injection[7, 25, 20].”