AGN Feedback Process Overview

• AGN feedback is the mechanism where energy from a supermassive black hole influences its galaxy's interstellar and circumgalactic medium.
• It operates through dual modes—radiative (quasar/wind) and kinetic (radio/jet)—each transferring energy via distinct physical processes.
• Observations and simulations reveal that AGN feedback can both suppress and trigger star formation, affecting scaling relations and galaxy evolution.

Active Galactic Nucleus (AGN) feedback comprises the physical processes by which energy output from a supermassive black hole at the center of a galaxy is coupled to the surrounding galactic and circumgalactic medium. This feedback regulates star formation and the thermal and dynamical state of baryonic gas on galactic and larger scales. Two principal modes are recognized: a radiative (quasar/wind) mode manifesting primarily at high accretion rates via intense radiation and winds, and a kinetic (radio/jet) mode distinguished by mechanical energy transfer through collimated relativistic jets. AGN feedback is a central ingredient in models seeking to explain the suppression of cooling flows, the co-evolution of black holes and galaxies, and the observed scaling relations such as the $M_{\rm BH}$–$\sigma$ relation. This entry provides a comprehensive review of the AGN feedback process, focusing on the theoretical framework, feedback channels, dynamical evolution, numerical modeling, evidence for negative and positive feedback, and the impact on galactic and cosmic structure.

1. Theoretical Foundations and Feedback Modes

AGN feedback involves the coupling of the black hole’s accretion energy to the ambient gas via radiation and/or mechanical outflows. Two broad feedback modes are distinguished:

• Radiative (Quasar) Mode: Dominant at near-Eddington accretion rates. Energy is released as radiation and wide-angle winds. Dust absorption can greatly enhance momentum transfer to the interstellar medium (ISM), yielding an outward force of order $L/c$, where $L$ is the AGN luminosity and $c$ is the speed of light. The critical luminosity for driving gas out of an isothermal potential is $L_c = (4 f_g c \sigma^4)/G$, with $f_g$ the gas fraction and $\sigma$ the stellar velocity dispersion.
• Kinetic (Radio) Mode: Relevant at low Eddington ratios, typical in local massive ellipticals and brightest cluster galaxies (BCGs). The AGN powers relativistic jets inflating bubbles in the hot intragalactic/intracluster medium (IGM/ICM), providing heating via $p\,dV$ work, shocks, turbulence, and sound waves. Mechanical energy input is often parameterized as $P_{\mathrm{jet}} \sim 4PV/t_{\mathrm{age}}$, where $P$ is the ambient pressure, $V$ the cavity volume, and $t_{\mathrm{age}}$ the cavity age.

Both modes can operate sequentially or in tandem depending on the duty cycle and accretion state.

2. Turbulent and Thermodynamical Coupling

The conversion of AGN energy to heat of the ambient medium is governed by nonlinear hydrodynamic and magnetohydrodynamic (MHD) processes:

• Turbulent Dissipation: In radio galaxies, relativistic jets decelerate via Kelvin–Helmholtz instabilities, producing turbulent mixing layers that broaden and eventually make the outflow fully turbulent. The resulting energy cascade transfers mechanical energy from large-scale eddies (of size $\ell_1$) through inertial scales until viscous and magnetic dissipation converts it to heat at small scales. The characteristic evolution of the turbulent energy spectrum $E(k)$ is governed by:

$$\left( \frac{\partial}{\partial t} + 2\nu k^2 \right) E(k) = F(k) + \int T(k,p,q,E,\nu) \, dp \, dq$$

where $\nu$ is the dissipation constant, $k$ the wavenumber, $F(k)$ the energy injection from instabilities, and $T$ the nonlinear transfer term. For FR-I sources, this cascade reaches equilibrium after $t_{\rm d} \sim 10^8$ yr, comparable to gas cooling times in massive galaxies (Young, 2010).

• Thermodynamic Regulation: AGN feedback is favored whenever energy gains (from gravitational contraction or mass capture) exceed losses from cooling, as encapsulated by the minimization of the Gibbs free energy (GFE). The total change in GFE for the system:

$$\Sigma \Delta G = (H-L)\beta \left[1 - (v/c_s)^2\right] \Delta t$$

with $H$ and $L$ the global heating and cooling rates, $c_s$ the sound speed, $v^2$ encompassing contributions from dark matter, stars, and black hole energy capture. Feedback is energetically favored for $(v/c_s)^2 > 1$ (Pope, 2012).

3. Dynamical Evolution and Cyclicity

AGN feedback is inherently cyclical, punctuated by episodic outbursts and periods of quiescence:

• In the kinetic mode, after the onset of turbulence and energy cascade in FR-I jets, most of the energy is deposited not along the jet axis, but across an extended region (~100 kpc), heating the circumgalactic and interstellar medium on a timescale $t_{\rm d} \sim 10^8$ yr (Young, 2010).
• In controlled models where feedback is optimized to minimize total energy input, the solution is a "bang-bang" process where heating is supplied in intermittent, discrete events, with the AGN being active only for a fraction $\delta = 1/k_1$ of the time (with $k_1$ the feedback strength). Lower-mass systems demand more powerful, shorter duration heating events; in more massive clusters the feedback is gentler and nearly continuous (Pope, 2011).
• Duty cycles ($\sim$hundreds of Myr), feedback timescales ($\lesssim 0.2$ Gyr), and the coupling efficiency of luminosity to gas mass ($f_0 \sim 10^{-3}$–$10^{-2}$) set the observed color and gas depletion transitions in early-type galaxies (Kaviraj et al., 2010).

4. Negative and Positive Feedback: Suppression and Triggering

AGN feedback manifests as both "negative" (quenching star formation) and "positive" (triggering star formation), modulated by environmental context and outflow properties:

Feedback Mode	Main Physical Channel	Typical Outcome
Negative	X-ray/radiative heating, jet turbulence	Gas heating, ISM expulsion, SFR suppression
Positive	Jet-induced compression, shell shocks	Triggered star formation in compressed regions

• Negative Feedback: In X-ray selected AGN, the primary mechanism is heating/photo-dissociation of molecular gas, suppressing star formation (Zinn et al., 2013). In semi-analytic and hydrodynamic simulations, AGN feedback is required to deplete cold gas, suppress cooling flows, and quench star formation, particularly in massive systems (Dubois et al., 2011, Zerbo et al., 10 Jul 2024).
• Positive Feedback: Radio-jet AGN show elevated star formation rates, attributed to the compression of ISM by jets, which triggers gravitational instabilities ("jet-induced star formation") (Ishibashi et al., 2012, Zinn et al., 2013). 3D-MHD simulations reveal that AGN winds can create ring-like star-forming regions by compressing clumpy ISM, with feedback polarity (positive or negative) determined by AGN wind power, ISM structure, and the star formation rate (Clavijo-Bohórquez et al., 2023).
• Shell-Driven SF: Radiative pressure-driven shells compress ISM, leading to star formation rates of $\sim$10–100 $M_\odot\,\mathrm{yr}^{-1}$ in the shell, with additional stellar mass of a few $10^9\,M_\odot$ per episode, consistent with observed inside-out growth of massive galaxies (Ishibashi et al., 2012).

5. Feedback Effects Across Scales and Galaxy Types

Feedback impacts and modes shift with environment and mass scale:

• Ellipticals vs. Clusters: In low-mass ellipticals, strong, brief feedback events can expel hot gas; in high-mass clusters, feedback must be more persistent due to deeper potential wells (Pope, 2011). The mechanical power needed for hot gas ejection scales with the depth of the potential, making AGN feedback more able to eject baryons from groups than from massive clusters (Eckert et al., 2021).
• Dwarf Galaxies: AGN feedback can in principle dominate gas ejection for critical halo masses exceeding those accessible to supernova feedback, especially when hosting intermediate-mass black holes, potentially resolving the "cusp–core" and "missing satellites" problems (Dashyan et al., 2017).
• Groups and Baryon Distribution: In galaxy groups, the AGN can inject enough energy to exceed the gravitational binding energy of the hot intragroup medium (IGrM), leading to gas evacuation and lower baryon fractions compared to clusters (Eckert et al., 2021).

6. Numerical Models and Prescriptions

State-of-the-art models incorporate AGN feedback via sub-grid prescriptions or integrated semi-analytic implementations:

• Dual-Mode Subgrid Models: Cosmological hydrodynamics simulations (e.g., EAGLE, RAMSES) adopt dual feedback modes—thermal (quasar) at high accretion rates and kinetic (jet) at low rates—coupled through black hole accretion prescriptions and SF regulation. Feedback energy is implemented as:

$$\dot{E}_{\mathrm{AGN}} = \epsilon_f \epsilon_r \dot{M}_{\mathrm{BH}} c^2$$

with appropriate choices of, e.g., $\epsilon_f=1$ (radio mode), $\epsilon_r=0.1$ (Dubois et al., 2011, Zerbo et al., 10 Jul 2024).

• Semi-analytic Models: Advanced prescriptions (e.g., FEGA25) combine negative (quenching), positive (triggered SF), and hot gas ejection modes, all governed by the black hole accretion efficiency $\kappa_{\mathrm{AGN}}$, allowing regulation of the hot gas fraction, star formation history, and passive galaxy fraction (Contini et al., 26 Feb 2025). Gas ejection out of halos is parameterized by energy input relative to potential depth, e.g.,

$$M_\mathrm{ejected} \propto (\delta M_\mathrm{BH}/M_\mathrm{BH})\, M_\mathrm{hot}\, (1 - V_{200}/V_\mathrm{scale})$$

7. Observational Signatures and Constraints

Key diagnostics of AGN feedback include:

• X-ray Cavities and Bubbles: Cavities measuring $pV$ enthalpy in the ICM serve as direct evidence for mechanical energy input by radio-mode AGN (Fabian, 2012, Iqbal et al., 2017).
• Emission Line Kinematics: Blue asymmetries and blueshifts in [OIII] emission lines are signatures of outflows, with line shape parameters (skewness, kurtosis) tracing feedback impact. Stronger blue asymmetry and higher Eddington ratios correlate with younger stellar populations (Wang, 2014).
• Scaling Relations: The $M_{\rm BH} \propto \sigma^4$ relation is interpreted as direct evidence of momentum-driven feedback. Observationally, molecular outflow rates, bubble sizes, and excess entropy in clusters constrain model parameters and feedback efficiencies (Combes, 2014, Iqbal et al., 2017).
• Chemical Enrichment: The effective yield, $y_{\rm eff} = Z_{\rm gas}/\ln(1/\mu)$, decreases as AGN feedback drives outflows, suppressing chemical enrichment relative to a closed box; departures from the fundamental metallicity–gas mass–stellar mass plane in simulations quantify AGN feedback effects (Zerbo et al., 10 Jul 2024).

8. Future Prospects and Open Questions

Upcoming instrumentation (e.g., eROSITA, SKA, Athena, XRISM) will improve the sensitivity and scope of feedback diagnostics through:

• High-resolution mapping of hot, warm, and cold gas outflows.
• Direct measurements of turbulence and velocity fields.
• Comprehensive surveys of radio bubbles and X-ray cavities across environments.

Outstanding issues involve quantifying the partitioning of AGN mechanical energy among heating channels, understanding the triggering and suppression balance in different ISM and halo conditions, refining sub-grid models (especially of hot gas ejection), and constraining the duty cycle and efficiency of feedback processes in diverse galactic environments.

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The AGN feedback process encompasses a spectrum of physical channels capable of both suppressing and triggering star formation, regulating baryon fractions, and shaping galaxy evolution, with its macro-structural and micro-physical effects traced by an overview of theoretical modeling, large-scale simulations, and multiwavelength observations.