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Cooling Flow Problem      AGN Jet      Microphysics & Galaxy Evloution


Stellar FB Alters Magnetic Fields     Discrete Effects in Stellar FB

Cooling Flow Problem

How to keep massive galaxies quenched and remained "red and dead" over a large portion of cosmic time?

We investigate this in halos with masses ∼1012−1014 M⊙, using non-cosmological high-resolution hydrodynamic simulations with the FIRE-2 (Feedback In Realistic Environments) stellar feedback model. We show that various proposed "non-AGN" solution mechanisms in the literature, including Type Ia supernovae, shocked AGB winds, other forms of stellar feedback (e.g. cosmic rays), magnetic fields, Spitzer-Braginskii conduction, or "morphological quenching" do not halt or substantially reduce cooling flows nor maintain "quenched" galaxies in this mass range.
The results are published in: MNRAS Vol. 487, Issue 3, p.4393-4408
Before jumping right into a specific, potentially more realistic AGN feedback model, we tested verious simplified toy energy-injection models, where we arbitrarily vary the strength, injection scale, and physical form of the energy. Different scenarios include thermal ``heating,'' direct wind or momentum injection, cosmic ray heating or pressure support, or turbulent ``stirring'' of the intra-cluster medium (ICM). We show that turbulent stirring in the central ~100 kpc, or cosmic-ray injection, can both maintain a stable low-SFR halo for >Gyr timescales with modest energy input, by providing a non-thermal pressure which stably lowers the core density and cooling rates.In both cases, associated thermal-heating processes are negligible. Turbulent stirring preserves cool-core features while mixing condensed core gas into the hotter halo. Pure thermal heating or nuclear isotropic momentum injection require vastly larger energy, are less efficient in lower-mass halos, easily over-heat cores, and require fine-tuning to avoid driving unphysical temperature gradients or gas expulsion from the halo center.
The results are published in: MNRAS Vol. 491, Issue 1, p.1190-1212
Fig.1   The star formation rate (SFR) for a 1014 M⊙, halo. Stellar feedback, magnetic fields, conduction, cosmic ray from supernovae do not quench the galaxy.  AGN toy models with (a) thermal heating with a 30kpc kernel, (b) turbulent stirring confined within 100kpc, and (c) CR injection can stable suppress the SFR.

What Types of AGN Jet Quench?

CR jets require less fine tuning

Our previous work suggested that AGN jets are likely required, but the form of jet energy required to quench remains unclear. This is particularly challenging for galaxy simulations, in which the resolution is orders of magnitude coarser than necessary to form and evolve the jet. On such scales, the uncertain parameters include: jet energy form (kinetic, thermal, and cosmic ray (CR) energy), energy, momentum, and mass flux, magnetic field strength and geometry, jet precession angle and period, opening-angle, and duty cycle. We investigate all of these parameters in a 1014M⊙ halo using high-resolution non-cosmological MHD simulations with the FIRE-2 (Feedback In Realistic Environments) stellar feedback model, conduction, and viscosity. We explore which scenarios match observational constraints and show that CR-dominated jets can most efficiently quench the central galaxy through a combination of CR pressure support and a modification of the thermal instability. Jets with most energy in mildly relativistic (∼ MeV or ∼1010 K) thermal plasma work, but require a factor ∼10 larger energy input. For a fixed energy flux, jets with higher specific energy (longer cooling times) quench more effectively. For this halo size, kinetic jets are less efficient in quenching unless they have wide opening or precession angles. Magnetic fields play a minor role except when the magnetic flux reaches ≳1044 erg s−1 in a kinetic jet model, which causes the jet cocoon to significantly widen, and the quenching to become explosive. We conclude that the criteria for a successful jet model are an optimal energy flux and a sufficiently wide jet cocoon with long enough cooling time at the cooling radius.
Fig. 2   Active galactic nucleus (AGN) jets can suppress cooling flows (and therefore quench star formation) in massive galaxies if the following three criteria are met.

1. Moderate jet energy flux Enough energy for cocoon expansion to balance gas cooling, but not so much energy as to exceed escape velocity at Rcool.

2. Long cooling time within jet cocoon Longer than time to reach Rcool. Can be achieved by thermal or kinetic jets with high specific energy or CR jets.

3. Wide jet cocoon Width of cocoon at Rcool is enough to suppress the cooling flow over a wide solid angle. Can be achieved by jets with a high non-kinetic component, very light kinetic jets, or jets with initially wide angles.

Fluid Microphysics & Galaxy Evolution

Stellar feedback has the dominating effects

Stellar Feedback Alters Magnetic Fields

Stellar feedback strongly alters the amplification and morphology of galactic magnetic fields

Fig. 4   Edge-on and face-on projections of the gas density. Arrows indicate the relative magnitudes and directions of the magnetic field. Different columns correspond to different baryonic physics models. In all maps, the magnetic fields in dense clumps are not only stronger but also more randomly distributed. No-feedback runs fragment most dramatically and therefore exhibit magnetic fields highly concentrated in dense clumps with random directions. Runs that employ the FIRE explicit stellar feedback model have irregular magnetic field distributions owing to supernova shocks, turbulence and outflows driven by stellar feedback, in addition to the greater fragmentation present in these runs compared with the Adiabatic and S&H sub-grid stellar feedback runs. The latter two types of runs generally have smooth, highly ordered gas and magnetic field morphologies.




Diecrete Effects in Stellar Feedback

Individual Supernovae, Hypernovae, and IMF Sampling in Dwarf Galaxies

Fig. 5   Upper left: Stellar mass as a function of cosmic time in our simulations. m10q has ∼ 30 HNe randomly distributed among the SNe over its history. Lower left: SFR averaged over the preceding 100 Myr as a function of time. Upper right: The mass outflow rate as a function of time smoothed over 100 Myr. To estimate the mass outflow rate, we consider all gas particles between 0.08 and 0.1 rvir that have radial velocities greater than 30 km s−1 . Lower right: Outflow mass-loading factor, η ≡ outflow/ SFR, smoothed over 500 Myr. Treating SN feedback as continuous results in higher SFRs – and thus stellar masses – and lower outflow mass loading factors. The final stellar mass of m10q “Default” and “Default 2” runs differ by a factor of ∼ 2. Given such range of stochastic effect, the effect of IMF sampling or HNe is not obvious.