###### Abstract

Growing supermassive black holes (Active Galactic Nuclei; AGN) release energy
with the potential to alter their host galaxies and larger-scale environment;
a process named “AGN feedback”. Feedback is a required component of galaxy
formation models and simulations to explain observed properties of galaxy
populations. We provide a broad overview of observational approaches that are
designed to establish the physical processes that couple AGN energy to the
multi-phase gas, or to find evidence that AGN impact upon galaxy evolution.
The orders-of-magnitude range in spatial, temporal, and temperature scales,
requires a diverse set of observational studies. For example, studying
individual targets in detail sheds light on coupling mechanisms; however,
evidence for long-term impact of AGN is better established within galaxy
populations that are not necessarily currently active. We emphasise how modern
surveys have revealed the importance of radio emission for identifying, and
characterising, feedback mechanisms. At the achieved sensitivities, the
detected radio emission can trace a range of processes, including shocked
interstellar medium caused by AGN outflows (driven by various mechanisms
including radiation pressure, accretion disc winds, and jets). We also
describe how interpreting observations in the context of theoretical work can
be challenging, in part, due to some of the adopted terminology.

###### keywords:

galaxies; active galactic nuclei; feedback; jets; outflows

1 1 0 28 February 2024 3 April 2024 5 April 2024 https://doi.org/
Observational Tests of AGN Feedback: An Overview of Approaches and
Interpretation Observational Tests of Active Galactic Nuclei Feedback: An
Overview of Approaches and Interpretation Chris M. Harrison 1 and Cristina
Ramos Almeida2,3 Chris M. Harrison & Cristina Ramos Almeida Harrison, C.M.;
Ramos Almeida, C. Correspondence<EMAIL_ADDRESS><EMAIL_ADDRESS>
##  1 Introduction

The presence of supermassive black holes (SMBHs) at the centre of galaxies,
including our own Milky Way, is confirmed by measurements of the motions of
stars and gas in galaxy centres, and by the gravitational lensing signatures
within multi-wavelength images (e.g., Ghez et al. (2008); Kormendy and Ho
(2013); Event Horizon Telescope Collaboration et al. (2019); GRAVITY
Collaboration et al. (2020); Nightingale et al. (2023)). These black holes
(BHs) grow through periods of gas accretion, which are known as Active
Galactic Nuclei (AGN), and are identified using observations across the
electromagnetic spectrum Soltan (1982); Marconi et al. (2004); Alexander and
Hickox (2012). The energy released by AGN was discussed as potentially
important for influencing galaxy evolution as early as the 1980s; however, it
is over the last three decades that there has been prolific research into this
so-called “AGN feedback” process (see discussion in Harrison et al. (2018)).

The explosion of interest in AGN feedback was largely triggered by: (1) the
observed correlation between black hole masses and stellar bulge properties
Magorrian et al. (1998); Gebhardt et al. (2000); Ferrarese and Merritt (2000),
which early analytical models sought to explain with the effect of AGN driving
gaseous outflows into their hosts Silk and Rees (1998); King (2003, 2005); (2)
the lower-than-expected rate of gas cooling identified around the most massive
galaxies, which implies a heating source that is attributed to AGN Binney and
Tabor (1995); Ciotti and Ostriker (1997); Peterson et al. (2003) and; (3)
semi-analytical models and hydrodynamic simulations, which invoked AGN to
regulate black hole growth and to reduce the efficiency of star formation (SF)
at the highest stellar masses, as a required process to successfully reproduce
the observed local stellar mass functions, and colour bi-modality, of galaxies
Benson et al. (2003); Springel et al. (2005); Croton et al. (2006); Bower et
al. (2006); Somerville et al. (2008).

Whilst energetic feedback from stellar winds and supernovae are typically
considered sufficient for low mass galaxies (with stellar masses
$\lesssim$1010 solar masses), AGN feedback remains a crucial component of
galaxy evolution theory to explain the massive end of the galaxy population.
This is demonstrated by its ubiquitous role within the current generation of
cosmological simulations (e.g., Schaye et al. (2015); Khandai et al. (2015);
Dubois et al. (2016); Naab and Ostriker (2017); McCarthy et al. (2017); Nelson
et al. (2018); Davé et al. (2019)). Across these simulations, AGN remain the
only known solution to regulate the cooling in dense galaxy environments, and
to sufficiently control the efficiency of star formation for massive galaxies.
Furthermore, within modern models and simulations, AGN are considered
important for establishing other observed properties of galaxies and their
environments. This includes galaxy structures, mass profiles and dynamics, and
many of the properties of the gas observed in and around galaxies (e.g.,
McCarthy et al. (2017); Choi et al. (2018); Davies et al. (2019); Peirani et
al. (2019); van der Vlugt and Costa (2019); Wright et al. (2020); Cochrane et
al. (2023); Obreja et al. (2024)).

Observations are required to test any theoretical ideas and implementations of
AGN feedback within simulations, whilst carefully keeping in mind the
difference between true predictions and observations that were used to
calibrate the models (e.g., Schaye et al. (2015); see Sections 4.3 and 6).
Furthermore, observations should be used to constrain the physical mechanisms
by which the energy released by AGN is able to couple to the gas. Indeed,
there is currently no theoretical consensus on this, with an ongoing
discussion on the relative importance of different mechanisms including:
radiation pressure on dusty gas; accretion disc winds; radio jets; and cosmic
rays (e.g., Zakamska et al. (2016); Ishibashi et al. (2018); Rakshit and Woo
(2018); Jarvis et al. (2019); Costa et al. (2020); Brüggen and Scannapieco
(2020); Venturi et al. (2021); Mandal et al. (2021); Meena et al. (2023);
Calistro Rivera et al. (2023)). Consequently, the literature is full of
observational studies exploring these topics. They range from multi-
wavelength, highly detailed, observations of individual targets through to
statistical tests on large galaxy samples. Due to the diversity of these
studies, it can be challenging to interpret the results within the context of
one another, and within the context of the theoretical ideas around AGN
feedback. We aim to address this challenge in this article by providing a
broad overview of the different observational approaches to test AGN feedback,
and discuss how they can (or can not) be related to one another and to
theoretical predictions.

Observational work on AGN feedback has been reviewed multiple times over the
last decade, including by Alexander and Hickox (2012); Fabian (2012); McNamara
and Nulsen (2012); Kormendy and Ho (2013); Heckman and Best (2014); Harrison
(2017); Morganti (2017); King and Pounds (2015); Harrison et al. (2018);
Hardcastle and Croston (2020); Veilleux et al. (2020); Bourne and Yang (2023);
Krause (2023). These reviews typically focus in depth on one aspect of the
feedback processes (e.g., the role of jets or the properties of the multi-
phase gaseous outflows), and/or they are dedicated to one particular sub-set
of the AGN population (e.g., radio-detected AGN, those in the densest galactic
environments, or the most luminous AGN). This article does not aim to
supersede these previous focused reviews. Instead, we aim to complement them
by providing a more holistic overview of the breadth of observational
approaches taken to search for, and to characterise, AGN feedback. The goal is
to place the different observational approaches within the context of one
another, and to comment upon how they collectively can be used to test, or
refine, different theoretical ideas of feedback.

##  2 A multi-faceted approach to a complex problem

AGN feedback is a problem of many scales. Both black hole growth (AGN) and
stellar growth (star formation) are fed by gas. Therefore, we are interested
in understanding a balance of feeding from, and feedback upon, a gaseous fuel
supply. As discussed below, the relationship between these processes is a
multi-scale problem over many orders of magnitude in spatial, temperature, and
temporal scales. This range of scales is represented in the schematic diagram
shown in Figure 1.

###  2.1 Multiple spatial scales, temperatures, gas phases, and timescales

To assess the relationship between AGN and galaxy formation, we need to
understand physical processes that can be occurring over greater than six
orders of magnitude in spatial scales. The spatial scales of accretion flows
onto SMBHs are sub-parsec. Indeed, the physics that determine both the final
accretion on to black holes and the corresponding energy output can take place
on extremely small scales, down to the innermost stable circular orbit. These
accretion flows are fed from the surrounding circumnuclear region (CNR), which
is considered to be on scales of $\sim$1–10 pc, and is also responsible for
significant obscuration of the central AGN (i.e., the torus Ramos Almeida and
Ricci (2017)). Therefore, the interaction between the AGN and the material in
the CNR can determine both the rate of black hole growth and the ability to
observe AGN emission. Galaxies are typically considered to have their
interstellar medium (ISM) located on scales from a few parsecs up to tens of
kiloparsecs, and star formation primarily occurs within this ISM Tacconi et
al. (2020). If AGN impact directly on the ISM (e.g., by entraining/expelling
it, or by heating/exciting/ionising it; see Section 4), they have the
potential to impact directly upon the efficiency of star formation within the
host galaxy (see Section 5).

Figure 1: A schematic diagram to highlight the orders-of-magnitude range in
temperature (colour-coding of gas clouds, intra-clouds medium and outflows)
and spatial scales of AGN feedback. Gas in a range of phases, with a huge
range in temperatures, can be affected by the energy released by AGN. This can
occur from nuclear scales through to galaxy cluster scales. This large range
in spatial scales naturally corresponds to an equivalently large range in
temporal scales. See discussion in Section 2.

The gas surrounding galaxies, outside of the their discs or ISM, but within
their virial radii, is known as the circumgalactic region (CGM; Tumlinson et
al. (2017)). Broadly speaking, this gas extends from $\sim$10 kpc up to
$\sim$100 kpc. The CGM is a reservoir that can fuel a galaxy’s ISM. It can be
enriched by material that has been expelled from the host galaxy (e.g., by AGN
outflows; Section 4). If an AGN can expel gas from the CGM, this could
ultimately prevent or regulate future star formation in the host (e.g., Davies
et al. (2020)). The medium between galaxies that are located within groups or
clusters can extend up to hundreds of kiloparsecs. This is called the
intragroup medium (IGrM) or intracluster medium (ICM), respectively. AGN can
act as a source of heating on this gas, and the ability for this gas to cool
and flow onto galaxies plays a role in establishing the rate of star formation
(see Section 6).

As summarised in Figure 1, the CNR, ISM, CGM, and IGrM/ICM can all contain gas
at a range of temperatures, and in a range of phases (i.e., molecular, atomic,
or ionised; see e.g., Ramos Almeida and Ricci (2017); Tacconi et al. (2020);
Ganguly et al. (2023)). For example, on spatial scales ranging from tens to
hundreds of parsecs, the cold and dense ISM (i.e., the molecular gas García-
Burillo et al. (2021)) is generally referred to as the circumnuclear disc
(CND). The ionised gas on similar scales and up to $\sim$1 kpc is known as the
narrow-line region (NLR), and up to $\sim$10 kpc as the extended-NLR (ENLR;
see Figure 1). It is the coldest and densest gas that is directly associated
with star formation, relating to temperatures of 10s to 100s of Kelvin.
Therefore, observations that trace atomic and molecular gas are usually
considered necessary for measuring the properties of the available fuel supply
for star formation (see Section 5). However, much of this gas will have cooled
from hotter phases. Furthermore, AGN are expected to heat and expel
considerable gas in hot/ionised phases (e.g., Mukherjee et al. (2018); Costa
et al. (2020); Bourne and Yang (2023)), which may also cool or help trigger
the formation of colder phases (e.g., Richings and Faucher-Giguère (2018)).
Therefore, it is necessary to consider a wide range of gas phases. The
corresponding temperature range may span $>$6 orders of magnitude. This
creates a huge observational challenge. It has only recently become feasible
to obtain multi-phase measurements for representative galaxies samples, yet
the properties of some gas phases still remain largely unconstrained (see
Section 4).

Due to the orders-of-magnitude range of spatial scales expected for the AGN
feedback process (see Figure 1), we naturally have to consider a huge range of
time scales. Furthermore, we observe signatures of historic (not currently
active) AGN events and variability in AGN luminosity (e.g., Peterson (2001);
Lintott et al. (2009); Mostert et al. (2023)). Such observations confirm that
black hole growth, and the resulting energy output, is a variable and
transient process. Indeed, it is better to consider AGN as events in the life-
cycle of a galaxy and not to consider them as objects that persist in time.

The relative amount of time that a black hole is accreting (active), compared
to not accreting (inactive), is sometimes referred to as the ‘duty cycle’;
although its exact definition varies in the literature. There are potentially
multiple relevant time scales (or ‘duty cycles’) for the AGN feedback process,
which may also depend on the ‘accretion mode’ (see Section 3). These can range
from variability on timescales of days–months for the observed high energy AGN
emission Peterson (2001), a proposed typical high-accretion rate period of
growth lasting $\sim$105 years King and Nixon (2015); Schawinski et al.
(2015), through to the idea that AGN could nearly always be active at low
levels for the most massive galaxies Sabater et al. (2019). An important
example study in the context of understanding AGN feedback, Hickox et al.
Hickox et al. (2014), use the simulations of Novak et al. Novak et al. (2011)
to demonstrate that black holes may switch between active (i.e., luminous AGN)
and non active states, on timescales of $\lesssim$1 Myr. This is far shorter
than the typical timescales for star formation of $\gtrsim$100 Myr. This
severely complicates how we can connect a specific observed AGN event to any
impact that it may have on the star formation in its host galaxy (see further
discussion in Sections 5 and 6).

###  2.2 The multi-faceted approach to observational work on AGN feedback

The challenges of scales outlined above, and in Figure 1, necessitate a multi-
faceted approach to observationally test ideas around AGN feedback. Figure 2
provides a schematic overview of the primary regimes involved in addressing
this AGN feedback problem.

Figure 2: A schematic overview of the different regimes needed to tackle the
overall AGN feedback problem with observations (see Section 2.2). This is
presented in the form of a flow chart (left) and a schematic representation of
an AGN-host galaxy embedded in a halo (right). Different colors and numbers
within the flow chart correspond to different regions and processes labelled
on the right panel and with the same colors.

Firstly, it is crucial to establish the demographics of AGN across different
galaxy populations to assess: (a) the energy budget and duty cycles of AGN
events; and (b) the prevalence of different mechanisms of energy injection
into the host galaxies (e.g., jets, winds and radiation). This is labelled
with a “1” in Figure 2, and is discussed further in Section 3. The energy
released by AGN events can have an impact upon the kinematics, distribution,
and excitation/ionisation state of the multi-phase gas (labelled with “2” in
Figure 2). The properties and level of these effects will depend on how
efficiently the energy can couple to the gas on various spatial scales. This
is important to establish with observations, and is discussed in Section 4.
Energy injection into the ISM may have an in-situ, localised affect, on the
ability for gas to form stars. This may have a negative or a positive impact
on the star formation efficiency (labelled “3” in Figure 2) and it is
important to understand the details of this process using high angular
resolution observations (see Section 5). Finally, the cumulative impact of
multiple AGN events could have many long-term effects on the global properties
of the host galaxies and their larger-scale environment (labelled “4” in
Figure 2). Assessing the “imprint” of AGN feedback on these properties is an
important observational test for refining different AGN feedback models
invoked in cosmological simulations, and this is discussed further in Section
6.

##  3 AGN accretion modes and methods of energy injection into the host

To understand the physical process of AGN feedback, requires an understanding
of the prevalence and power of different mechanisms of energy output during
AGN events (see region “1” in Figure 2; discussed in this section) and
constraining how efficiently this energy can couple to the gas (discussed in
Section 4). It is beyond the scope of this article to review AGN demographics,
but we note the importance of establishing a complete census of AGN events
across different galaxy populations and cosmic epochs (see instead, e.g.,
Alexander and Hickox (2012); Hickox and Alexander (2018); Aird et al. (2018);
Hardcastle and Croston (2020)). Here we present a broad overview of the
mechanisms by which AGN may inject energy into their host galaxies (Section
3.1), reflect on what can be learnt on this topic from modern-day radio
surveys (Section 3.2) and briefly comment on these in the context of the
theoretical ‘modes’ of AGN feedback implemented in some simulations (Section
3.3).

Figure 3: A schematic overview of different mechanisms by which AGN can inject
energy into the gas in, and around, their host galaxies. This is shown for two
regimes of accretion: ‘radiatively inefficient’ for lower accretion rates
(left) and ‘radiatively efficient’ for higher accretion rates (right).
Multiple mechanisms co-exist in both regimes. This is described in Section
3.1.

###  3.1 AGN accretion modes and mechanisms of energy output

We will consider two main classes of AGN events: those which are “radiatively
efficient”, where the accreting mass is efficiently converted to radiation,
and those which are “radiatively inefficient”, where the converse is true111We
ignore the possibility of three regimes, with the addition of a distinct
extremely highly accretion rate state (‘super Eddington’), which may be
particularly relevant for early black hole growth, including the origin and
accretion rates of massive black holes in the early Universe that have been
observed with JWST Rennehan et al. (2023); Lupi et al. (2023); Maiolino et al.
(2023).. Although a simplification, and a matter of ongoing research, we can
broadly relate this dichotomy to the accretion rates and the resulting
properties of the accretion flow. Sources with the highest accretion rates,
i.e., those with luminosities $\gtrsim 1$% of their Eddington luminosity are
expected to have a radiatively efficient accretion disc that is geometrically
thin and optically thick. In contrast, black holes with lower accretion rates
are expected to have radiatively inefficient flows that are geometrically
thick and optically thin Shakura and Sunyaev (1973); Esin et al. (1997);
Narayan and Yi (1994). The spin of the black holes may also be crucial in
determining the mechanical power output available through jets Blandford and
Znajek (1977); Sikora et al. (2007). Potential methods of energy injection
from these two AGN classes are summarised in Figure 3.

For radiatively inefficient AGN events (left side of Figure 3; sometimes
called Low Luminosity AGN; LLAGN), the mechanical energy output greatly
exceeds the radiative output. This is likely to be dominated by collimated
jets of charged particles, although there can be a non-negligible contribution
of magnetically- or thermally-driven isotropic (wide-angle) winds from the
accretion flow and from Compton (X-ray) heating (e.g., Blandford and Payne
(1982); Begelman et al. (1983); Yuan and Narayan (2014); Gan et al. (2014);
Hardcastle and Croston (2020); Almeida et al. (2023)). For radiatively
efficient AGN222The variety of multi-wavelength methods used to identify
radiatively efficient AGN results in a menagerie of AGN classifications and
terminology used in the literature Padovani et al. (2017). Here we consider
two broad classes: quasars and Seyferts. Quasars have high bolometric
luminosities ($L_{\rm AGN}\gtrsim$1045 erg s-1) and lower luminosity AGN are
considered to be Seyferts. Both classes can be type-1, where direct accretion
emission, and the broad line region (BLR), is observed, or type-2 where no
accretion emission or BLR is detected. (right side of Figure 3), the energy
injected into the host can be from multiple mechanisms, including: (1) photo-
ionisation of gas up to CGM scales (e.g., Arrigoni Battaia et al. (2019);
Costa et al. (2022)); (2) in-situ radiation pressure on gas and dust (located
on CNR/torus scales to ISM scales; e.g., Ishibashi et al. (2018); Costa et al.
(2018)); (3) powerful wide-angle winds associated with the accretion discs,
which are likely radiatively-driven through electron scattering or through
ultra-violet line driving (e.g., Murray et al. (1995); Proga et al. (2000);
Costa et al. (2020); Mizumoto et al. (2021)); (4) collimated jets, which could
efficiently couple to the gas on various spatial scales depending on power,
inclination, ISM properties, etc. (e.g., Mukherjee et al. (2018); Tanner and
Weaver (2022); see Section 4.2) and; (5) Compton (X-ray) heating in the region
of the accretion disc, or even further out Sazonov et al. (2005); Gan et al.
(2014) 333We note that the inverse Compton effect could be important for
cooling gas that is above the Compton temperature, including the effect of the
AGN radiation field on the outflowing shocked gas, which could be crucial for
establishing the potential impact of AGN-driven winds King and Pounds (2015);
Bourne and Nayakshin (2013).. Mechanisms (2)–(5) could all result in the
propagation of mechanical energy into the host galaxies by shocking gas and/or
by sweeping up material into an outflow (see Section 4).

In the literature, the terms “wind”, “outflow”, and “jet” can be used
interchangeably in a way that can cause confusion for interpretation. For AGN
we encourage using the term “wind” to describe the launching mechanism
associated with accretion discs and “outflow” to describe ISM/CGM material
that has been swept up/entrained by the various driving mechanisms. The term
“jet” may refer to the initial physical process (relativistic, collimated,
beam of charged particles), or any other collimated outflowing structure, but
this should be carefully defined in each study.

###  3.2 Radio-identified AGN

We consider it important to provide a discussion on radio emission from AGN in
the context of AGN feedback studies. The related terminology can cause some of
the greatest confusion across both observational and theoretical works.

The earliest radio observations were only sensitive to the most powerful
extra-galactic sources which are clearly dominated by jets. The term ‘radio
galaxy’ is sometimes still used to define any galaxies considered to host
radio-detected jets. However, in the modern era of radio astronomy, the origin
of the detected radio emission can trace a wider range of processes (see
below). The terms ‘radio loud’ and ‘radio quiet’ are also commonly used to
classify AGN. Traditionally, radiatively efficient AGN are separated into
these classes based upon the ratio of radio luminosity to an accretion
luminosity (e.g., Kellermann et al. (1989); Xu et al. (1999); Klindt et al.
(2019)). AGN that are dominated by radio emission above some threshold are
classified as ‘radio loud’. However, ‘radio loud’ is sometimes used more
loosely in the literature to refer to galaxies where any radio emission
associated with an AGN is identified, or to simply define if a galaxy is
radio-detected. It is crucial to carefully define what is meant by a ‘radio
galaxy’ or ‘radio loud’ AGN in each individual study, and to take caution in
determining if the radio emission can, or can not, be unambiguously associated
to radio jets.

Due to the relationship between star formation rate (SFR) and associated radio
luminosity in star forming galaxies, it is possible to estimate the expected
contribution of star formation to the total observed radio luminosity (e.g.,
Helou et al. (1985); Ivison et al. (2010)). Therefore, any galaxy with
significant radio emission above this is expected to have radio emission
associated with an AGN, and are sometimes labelled as a ‘radio excess’
galaxy/AGN or as a ‘radio AGN’ (e.g., Best and Heckman (2012); Del Moro et al.
(2013); Macfarlane et al. (2021)). In Figure 4, we provide a schematic
representation of the difference between the traditional ‘radio loud’ criteria
and a radio excess criteria for radiatively efficient AGN. This figure is
motivated by the data presented in Figure 12 in MacFarlane et al. Macfarlane
et al. (2021), who study SDSS quasars with LOFAR observations.444Although the
values in Macfarlane et al. (2021) are generated from a population model, with
values not calculated for individual sources, they do represent the general
observed quasar population trends. We also note, unlike in Macfarlane et al.
(2021), we do not assume that radio emission associated with AGN (as opposed
to star formation), is necessarily attributed to jets.

Figure 4: Schematic representation of the data from Figure 12 in Macfarlane et
al. (2021), showing a comparison between the ‘radio loud’ criteria for quasars
(x-axis) (i.e., $R$ =$L_{\text{5GHz}}$/$L_{\text{4400\AA}}$, with a cut-off
value at $R=10$) and the ratio of radio luminosity attributed to AGN to that
attributed to star formation (y-axis). Sources below the detection threshold
of the surveys would fill out the bottom-left of this diagram.

The traditional definition of ‘radio loud’ effectively identifies galaxies
with powerful jets and it is commonly accepted that $\sim$10–20% of quasars
are ‘radio loud’ (Figure 4, top-right quadrant; e.g., Kellermann et al.
(1989); Zakamska et al. (2004); Kellermann et al. (2016); Macfarlane et al.
(2021)). Nonetheless, it does not necessarily mean that the radiative energy
output is not energetically important for feedback. A ‘radio loud’ quasar is
expected to host powerful accretion disc winds and have significant radiation
pressure (e.g., King and Pounds (2015); Ishibashi et al. (2018); Figure 3).
Furthermore, the ‘radio loud’ definition misses the majority of the
radiatively efficient AGN where the radio emission is AGN dominated (Figure 4,
top-left quadrant).

A crucial point is that populations of radio-detected AGN contain a mixture of
radiatively efficient and radiatively inefficient sources (see Figure 3).
Radio-detected AGN, which exhibit weak or no optical emission lines are known
as “low excitation radio galaxies” (LERGs) and appear to have little-to-no
evidence of radiative emission associated with an accretion flow; this makes
LERGs one candidate class of radiatively inefficient AGN (see review in
Hardcastle and Croston (2020)).555We note that “Low-ionization nuclear
emission-line regions” (LINERs) are another class of galaxies, where the
observed emission is not dominated by photoionisation from AGN, nor from star-
forming regions and a subset of these sources may be associated with
radiatively inefficient AGN (e.g., Heckman (1980); Flohic et al. (2006); Ho
(2009)). Radio-detected AGN that have also signatures of radiatively efficient
accretion are known as “High excitation radio galaxies” (HERGs).

Whilst it is sometimes assumed that excess radio emission (above star
formation) should be attributed to radio jets, this is not necessarily the
case. For example, if AGN-driven outflows cause shocks in the ISM, this can be
another significant contribution to the observed radio luminosity (e.g., Nims
et al. (2015); Zakamska et al. (2016); Panessa et al. (2019)). Whilst
diagnostics such as the ‘radio excess’ criteria and high brightness
temperatures (e.g., Morabito et al. (2022)) can be used to distinguish between
AGN and star formation related emission, it remains observationally
challenging to disentangle emission associated directly with a radio jet and
that from outflow-induced shocks (e.g., Jarvis et al. (2021); Fischer et al.
(2023)). Theoretical predictions will help guide appropriate diagnostics
(e.g., Bicknell et al. (2018); Meenakshi et al. (2022)).

In summary, radio emission associated with AGN events (both radiatively
efficient and radiatively inefficient) is extremely prevalent and could even
be ubiquitous (at least at low levels) for galaxies with the highest stellar
masses (i.e., $\sim$1011 solar masses; Sabater et al. (2019)). The origin of
this radio emission is often ambiguous and detailed work is required to
establish the underlying physical processes and the connection to AGN
feedback.

###  3.3 Connecting observed AGN populations to traditional ‘feedback modes’

We do not attempt to review AGN feedback models in this article. However, we
make some brief notes about interpreting observed AGN populations in the
context of some feedback models. Early semi-analytical models and hydrodynamic
simulations invoked simple prescriptions for AGN feedback (e.g., Springel et
al. (2005); Sijacki et al. (2007); Hopkins et al. (2006); Bower et al. (2006);
Croton et al. (2006); Somerville et al. (2008); Dubois et al. (2010)), which
have been influential on the community thinking about different ‘modes’ of
black hole growth and corresponding ‘modes’ of AGN feedback (see discussion in
e.g., Bower et al. (2012)). For example, the term ‘quasar mode’ (‘radiative
mode’, or ‘starburst mode’) was considered important for rapid periods of
growth (sometimes associated with mergers), with the idea that ISM could be
expelled from the host galaxies. The term ‘radio mode’ (or ‘hot-halo mode’ ,
‘maintenance mode’, or ‘kinetic mode’), was considered important for lower
accretion rate systems, and acts more through a regulation of cooling of the
gas on large scales. Whilst appropriately simple at the time, the direct
connection to observed populations of radio-detected AGN and quasars is not
fully applicable with modern understanding. Furthermore, two distinct modes of
feedback is unlikely to be the complete story.

We have established that during radiatively efficient AGN events, multiple
mechanisms of energy input can result in significant mechanical forms of
energy into the gas, through outflows driven by winds, jets etc. (Figure 3;
Section 3.1). Furthermore, as discussed in Section 3.2, radio emission
associated with AGN is prevalent for both radiatively efficient (high
accretion rate) and radiatively inefficient accretion (low accretion rate)
regimes. Therefore, we should avoid assuming that radio-detected AGN are
universally associated with the traditional ‘radio mode’ of feedback. It
should also be avoided to assume that quasars provide only an ‘ejective’ type
of feedback on the ISM, and are only associated with accretion disc winds or
radiation (cf. the traditional implements of a ‘quasar mode’). Quasars, and
all radiatively efficient AGN, can also regulate gas cooling (’regulative’
feedback), could have an important impact on ejection of gas out to CGM
scales, and can have jets as an important energy injection mechanism (e.g.,
Jarvis et al. (2019); Costa et al. (2020); Oppenheimer et al. (2020); Cicone
et al. (2021); Audibert et al. (2023)).

##  4 Energy-gas coupling: outflow kinematics and energetics

In Section 3 we discussed the potential mechanisms by which AGN can inject
energy into their host galaxies. However, it is important to remember that the
relevance for AGN feedback requires this energy to couple to the multi-phase
gas. Here we summarise observational results on multi-phase gas outflows based
on samples of AGN (Section 4.1), discuss different AGN and galaxy properties
that might have a key impact on the energy-gas coupling (Section 4.2), and
describe how to constrain the outflow energetics and potential for impact from
the observational point of view (Section 4.3).

###  4.1 Multi-phase gas outflows

Gas outflows, one of the clearest and hence most studied forms of AGN
feedback, impact the ISM by removing, heating and/or mixing the gas (see
Figure 1). Hundreds of observational studies report evidence of outflows
observed in different gas phases, including the 1) hot ionised (T${}_{\rm
gas}\sim$105-8 K and n${}_{\rm gas}\sim$106-8 cm-3) using X-ray absorption
lines Longinotti et al. (2013); Tombesi et al. (2013); Chartas et al. (2021);
2) warm ionised (T${}_{\rm gas}\sim$103-5 K and n${}_{\rm gas}\sim$102-5
cm-3), mainly through emission lines detected in the rest-frame UV Murray and
Chiang (1995); Sulentic et al. (2007); Coil et al. (2011); Martin et al.
(2015), optical Harrison et al. (2014); Villar-Martín et al. (2016); Förster
Schreiber et al. (2014, 2019); Rose et al. (2018); Scholtz et al. (2018, 2020)
and near-infrared Rupke and Veilleux (2013); Ramos Almeida et al. (2019);
Speranza et al. (2022); Riffel et al. (2023); 3) neutral atomic (T${}_{\rm
gas}\sim$102-3 K and n${}_{\rm gas}\sim$101-2 cm-3) by means of the H I
absorption line (Morganti et al., 2005, 2016), the sodium doublet absorption
(NaID; Rupke et al. (2005); Cazzoli et al. (2016); Concas et al. (2019) and
the [C II] fine-structure emission Maiolino et al. (2012); Bischetti et al.
(2019); and 4) molecular (T${}_{\rm gas}\sim$101-3 K and n${}_{\rm gas}>$103
cm-3). The latter phase can be probed, for example, using the rotational and
vibrational H2 lines in the near-infrared (hot molecular; Rupke and Veilleux
(2013); Ramos Almeida et al. (2019); Riffel et al. (2023)), the rotational
lines in the mid-infrared (warm molecular; Dasyra and Combes (2011); Riffel et
al. (2020)), the hydroxyl (OH) transitions in the far-infrared Sturm et al.
(2011); Veilleux et al. (2013); Spoon et al. (2013); González-Alfonso et al.
(2017) and the carbon monoxide (CO) emission lines in the (sub)millimeter
Feruglio et al. (2010); Cicone et al. (2014); Pereira-Santaella et al. (2018);
Fluetsch et al. (2019); Lamperti et al. (2022); Ramos Almeida et al. (2022);
Scholtz et al. (2023). These spectral features trace outflows on different
spatial scales, that go from sub-parsec in the case of the hot ionised phase
(i.e., BLR scales), and from hundreds of parsecs to $\sim$10 kpc for the
ionised and molecular gas phases (see Figure 1).

Despite the wealth of observational effort invested in characterising AGN-
driven outflows, the overall majority of studies report single-phase estimates
of their properties that provide an incomplete view of the AGN feedback
phenomenon Cicone et al. (2018). Accurate outflow properties in different gas
phases need to be determined in representative AGN samples to estimate how
much each phase contributes to the overall mass and energy budget. From the
few studies reporting multi-phase outflow properties for samples of AGN (e.g.,
Rupke et al. (2017); Fluetsch et al. (2021); Riffel et al. (2023); Speranza et
al. (2024)), the cold molecular outflows would carry the bulk of the mass,
followed by the neutral and the warm ionised. In the local Universe, the
molecular outflows are slower (v$\lesssim$300-500 km s-1) and more compact
(r$\lesssim$1-2 kpc) than the ionised outflows ($\sim$500–1000 km s-1;
r$\sim$1-10 kpc). In the high redshift Universe (at cosmic noon, i.e.,
z$\sim$1–3, and earlier), most of the works reporting outflow measurements
focus on the ionised gas phase, since the bright optical emission lines are
shifted to the infrared. Integral field spectroscopy of quasars with different
radio luminosities revealed evidence of fast ionised outflows on galaxy scales
Nesvadba et al. (2008); Carniani et al. (2015); Kakkad et al. (2020); Scholtz
et al. (2020); Vayner et al. (2021); Concas et al. (2022); Wylezalek et al.
(2022); Vayner et al. (2024). The neutral atomic and molecular gas phases of
the outflows have also been studied at high redshift, and although some works
report the presence of massive, galaxy-scale high-velocity outflows in
luminous quasars Maiolino et al. (2012); Cicone et al. (2015); Bischetti et
al. (2019); Stacey et al. (2022), overall there is no evidence for them being
a widespread phenomenon, at least those probed by the [C II] emission line
Decarli et al. (2018); Novak et al. (2020). A handful of studies on individual
galaxies reported multi-phase outflow measurements, mainly targeting the cold
molecular and ionised phases Herrera-Camus et al. (2019) but also the ionised
and neutral atomic D’Eugenio et al. (2023). Vayner et al. (2021) characterised
the ionised and cold molecular outflows in four quasars at z$\sim$2 with
powerful jets. They found that, although most of the outflow mass is in the
molecular phase (which is clumpier and more compact), the kinetic energies are
higher in the ionised phase.

With a few exceptions, the multi-phase outflow masses derived from
observations are modest, but observational limitations might be preventing us
from detecting the most extended and diffuse component of the multi-phase
outflows, which might carry the bulk of their mass and/or energy. For example,
in the case of the cold molecular gas, this diffuse component might be missed
by interferometric observations that do not include short baselines Cicone et
al. (2018). Deep X-ray observations have revealed the presence of hot X-ray-
emitting gas (T${}_{\rm gas}\sim$106-7 K) extending to CGM scales in quasars
(e.g., Veilleux et al. (2014); Greene et al. (2014); Lansbury et al. (2018)),
and diffuse, extended gas on scales of up to $\sim$50 kpc have been reported
for neutral hydrogen around radio galaxies (e.g., Morganti et al. (2013)).
Some of this diffuse emissions might be participating in, or being entrained
by, the outflows. Therefore it would largely increase the outflow mass, and in
the case of the hot ionised gas, its energy. Whilst we wait for new a
generation of X-ray observatory, that will be required to fully characterise
the hottest gaseous phases Russell et al. (2023), indirect approaches will
need to be taken Simionescu et al. (2019); Brownson et al. (2019); Richter
(2020); Richings et al. (2021).

From the observational point of view it is not clear yet whether the different
outflow phases are different faces of the same phenomenon, with certain phases
transitioning to others Costa et al. (2018), or just unrelated events. Deep,
spatially resolved multi-phase outflow measurements of AGN of different
luminosities, hosted in galaxies with different properties and environments,
are necessary for advancing our understanding.

###  4.2 Coupling between energy and gas

According to observational scaling relations found from outflow measurements
of AGN in the local Universe, the more luminous the AGN the more massive and
faster the gas outflows that it drives (e.g., Cicone et al. (2014); Fiore et
al. (2017)). However, these scaling relations were derived from observations
of CO-bright targets known to have strong multi-phase outflows (e.g., Mrk 231
Feruglio et al. (2015), NGC 1068 García-Burillo et al. (2014); Saito et al.
(2022), IC 5063 Tadhunter et al. (2014); Morganti et al. (2015)), some of them
hosted in ultra-luminous galaxies (ULIRGs). More recent works have now started
to populate the AGN luminosity-outflow mass rate plane with less biased AGN
and ULIRG samples Ramos Almeida et al. (2022); Lamperti et al. (2022);
Speranza et al. (2024), and the linear relation vanishes (see left panel of
Figure 5). This indicates that having a high AGN luminosity does not guarantee
the presence of a massive outflow, as the coupling between energy and gas
depends on other factors that we mention below.

Figure 5: Molecular mass outflow rate versus AGN luminosity (left panel). The
dashed line is the fit to the data compiled by Fiore et al. Fiore et al.
(2017). Diamonds are the ULIRGs from Lamperti et al. Lamperti et al. (2022)
and circles the type-2 quasars from Ramos Almeida et al. Ramos Almeida et al.
(2022). The plots on the right are examples of a strong (weak) coupling
scenario, where the jet/wind/ionised outflow subtends a small (large) angle
with the molecular gas disc, launching a massive (modest) molecular outflow,
shown in red. Credit (right panel): Ramos Almeida, A&A, 658, A155 (2022) Ramos
Almeida et al. (2022), reproduced with permission ©ESO.

Aside from AGN luminosity, a key property that determines the level of
coupling between energy and gas is orientation. When a jet and/or disc wind
subtend a small angle relative to the gas disc, the latter is entrained and
the jet/wind energy is transmitted more efficiently (strong coupling scenario
in Figure 5) than when the angle is large (weak coupling scenario). Something
similar can happen when an ionised outflow is coplanar or quasi-coplanar with
a galaxy disc: the molecular gas is then entrained by the ionised outflow,
becoming a molecular outflow, normally directed along the kinematic minor axis
García-Burillo et al. (2021); Ramos Almeida et al. (2022). The importance of
orientation has been shown by hydrodynamic simulations of jet-ISM
interactions: jets almost coplanar with the galaxy discs (strong coupling
scenario in Figure 5) entrain the gas more efficiently than jets subtending a
larger angle (weak coupling scenario), inducing higher outflow velocities and
disturbance Mukherjee et al. (2018); Meenakshi et al. (2022); Talbot et al.
(2021, 2022); Audibert et al. (2023). Jets have been proposed to be
responsible for the enhancement in velocity dispersion in the direction
perpendicular to the jet observed in AGN of different bolometric luminosities
with modest jet powers Couto et al. (2017); Balmaverde et al. (2019, 2022);
Venturi et al. (2021); Girdhar et al. (2022); Ramos Almeida et al. (2022);
Venturi et al. (2023). Another factor with potential influence on the coupling
between jets and ISM is jet power. Simulations show that low-power jets
(P${}_{\rm jet}\lesssim$1045 erg s-1) get trapped for a longer time by the ISM
and disrupt the surrounding gas over a larger volume, and for a longer period,
than jets of higher powers (P${}_{\rm jet}\gtrsim$1045 erg s-1), which are
capable of “drilling” through the ISM Nyland et al. (2018). Therefore, the
low-power jets often detected in radiatively-efficient AGN such as Seyferts
and quasars can be more disruptive and induce more massive outflows than high
power jets Harrison et al. (2015); Morganti et al. (2015); Morganti (2017);
Girdhar et al. (2023); Cresci et al. (2023); Veilleux et al. (2023). Finally,
the distribution of molecular gas is another factor leading to more or less
efficient coupling. Some of the most powerful molecular outflows are found in
ULIRGs Cicone et al. (2014); Feruglio et al. (2010), associated with galaxy
mergers and high nuclear column densities. The latter might favor the launch
of massive molecular outflows by increasing the coupling between the
jets/winds and the ISM Wagner et al. (2016); Costa et al. (2020); Venanzi et
al. (2020). It has been proposed that this dust-enshrouded phase is followed
by an active feedback phase (blow-out phase) Alexander and Hickox (2012);
Glikman et al. (2012); Banerji et al. (2015) that modifies the nuclear
molecular gas distribution, creating cavities that have been predicted by
hydrodynamic simulations of massive galaxies with disc winds Mercedes-Feliz et
al. (2023) and observed in nearby AGN using ALMA Rosario et al. (2019);
Feruglio et al. (2020); García-Burillo et al. (2021) (see Section 5).

Observations of representative samples of AGN of different bolometric and
radio luminosities, hosted in galaxies of different masses and morphological
types, are needed to understand the interplay between the different outflow
gas phases and the impact of the different factors listed above on the
coupling between the outflows and the ambient gas. This requires observing
proposals in different telescopes that are expensive in terms of observing
time and that can be considered “incremental” in terms of science goals, but
we argue that they are necessary to move forward in AGN feedback studies.

###  4.3 Outflow energetics and potential for impact

Here we consider gas outflows as any gas that is not just photoionised,
excited and/or shocked by the AGN, but also kinematically disturbed by it, as
in Davies et al. (2020). Identifying outflows through emission line profiles
is challenging because different gas components across the host galaxy having
different kinematics contribute to the shape of the line profiles: rotation,
stripped material, infalling gas, companion objects, etc (see e.g., Concas et
al. (2022)). The most widely used method consists of assuming that each
kinematic component can be described by a Gaussian (i.e., parametric methods).
In the simplest case scenario, the emission lines can be described by the sum
of a narrow component ($\lesssim$400 km s-1) tracing virial motions, and
another component(s), generally but not necessarily broader and shifted
relative to the systemic velocity, associated with outflowing gas. Using
parametric methods it is possible to measure the properties of each kinematic
component, but in galaxies with complex kinematics it is difficult to ascribe
a physical meaning to each of them (Bessiere and Ramos Almeida, 2022; Hervella
Seoane et al., 2023). In the latter case, non-parametric methods might be more
appropriate Whittle (1985); Harrison et al. (2014); Speranza et al. (2021)
because they make it possible to identify high-velocity gas by measuring
emission line velocities at fixed fractions of either the peak or integrated
line flux (see Figure 4 in Harrison et al. (2014)). We refer the reader to
Hervealla-Seoane et al. Hervella Seoane et al. (2023) for an analysis of the
influence that using different parametric and non-parametric methods have on
the outflow kinematics and energetics.

In the case of the molecular gas, often studied using the CO emission lines
detected in the (sub)-mm regime, outflows usually have lower velocities than
their ionised counterparts Vayner et al. (2021); Ramos Almeida et al. (2022);
Speranza et al. (2024), making it even more difficult to disentangle them from
the virial motions around rotation. Therefore, unless clear emission line
wings are detected (e.g. Cicone et al. (2014); Audibert et al. (2019)), it is
not possible to identify any detected non-circular motion with radial outflows
without a careful analysis of the gas kinematics. The observed moment maps and
position velocity diagrams can be compared to simple rotating disc models in
order identify molecular outflows García-Burillo et al. (2014); Domínguez-
Fernández et al. (2020); Ramos Almeida et al. (2022). Once identified, the
outflow flux can be calculated using more or less conservatives approaches
Audibert et al. (2023). Regardless of the method used to characterise the gas
kinematics, several observational effects including the spectral response and
resolution of the instrument, beam smearing, projection, etc. need to be
considered and accounted for in order to reliably characterise the outflow
properties. These effects, their implications and ways of mitigation have been
largely discussed in the literature Carniani et al. (2015); Husemann et al.
(2016); Harrison et al. (2018).

To infer the potential impact of the outflows on the host galaxies we need to
measure outflow physical properties such as mass, mass rate, and kinetic power
(M, Ṁ, Ėkin). This requires estimates of other quantities such as the outflow
density (see Harrison et al. (2018) for discussion on different methods and
caveats) and metallicity, and to assume an outflow geometry. The latter can be
spherical, (multi-)conical or a slab/shell of certain radial thickness, and it
also has an impact on the derived outflow mass rates Lutz et al. (2020). Other
assumptions that are often made are that the outflow clouds have the same
density and metallicity and no acceleration or deceleration of the outflowing
gas. In the case of the cold molecular outflows estimated from CO emission
lines, an $\alpha_{\rm CO}$ factor needs to be assumed to convert from
measured carbon monoxide luminosities to estimated molecular hydrogen (H2)
masses. Values of $\alpha_{\rm CO}\leq 1$ are usually measured/assumed for
molecular outflows Morganti et al. (2015); García-Burillo et al. (2014); Ramos
Almeida et al. (2022), which is significantly lower than the Galactic factor
($\alpha_{\rm CO}$=4.35; Bolatto et al. (2013)).

The outflow mass rates can be compared with the SFR to derive the mass loading
factor ($\eta$=Ṁ/SFR) and hence have an estimate of the gas mass that is being
evacuated by the outflow compared to that being consumed by star formation.
The trouble is that often the spatial scales corresponding to the outflow (few
kiloparsecs at most) and to integrated SFRs (galaxy scales) are different, and
therefore the mass loading factors might be misleading Ramos Almeida et al.
(2022). The outflow momentum rate (Ṁ$\times$v) divided by the AGN radiation
momentum rate (Lbol/c) can provide information about whether the outflows are
energy or momentum driven King and Pounds (2015); Fiore et al. (2017), and the
kinetic power (Ėkin) is usually compared with either the jet power or the AGN
bolometric luminosity to have an idea of whether the kinetic power of jets
and/or AGN radiation can drive the outflow Harrison et al. (2014); Audibert et
al. (2023); Venturi et al. (2023); Speranza et al. (2024). However, many
factors compound to make it observationally challenging to obtain reliable
measurements of bolometric luminosity. The required bolometric correction
factors, to convert from a luminosity in one wavelength regime to the total
AGN luminosity, remain challenging and uncertain Netzer (2019). Furthermore, a
dominant fraction of AGN may be heavily obscured and can even be completely
missed in many surveys Hickox and Alexander (2018). Finally, as previously
discussed in Section 2, accretion rates and the resulting energy output can be
highly variable, on temporal scales much shorter than the outflow dynamical
timescales. A significant challenge also exists when attempting to determine
the available energy from jets. Scaling relationships have been created
between observed radio luminosities and jet powers, using measurements of the
mechanical work inferred from the jet-induced cavities inside X-ray emitting
atmospheres of massive galaxy environments (e.g., Merloni and Heinz (2007);
Bîrzan et al. (2008); Cavagnolo et al. (2010)). These relationships are used
extensively in the literature to convert a radio luminosity into the available
power from jets as a potential feedback mechanism. However, there are many
systematic uncertainties in these relationships, even for the regimes (i.e.,
jet powers, galaxy environments) from which they were calibrated (e.g.,
Kokotanekov et al. (2017); Croston et al. (2018)). Crucially, it is not-at-all
clear if they can be extended to different galactic environments, or to
different regimes of jets. For example, lower power jets, which are orientated
into a gas rich ISM can quickly be frustrated/disrupted and the observed radio
luminosity may be a poor tracer of jet power (e.g., Mukherjee et al. (2018);
Tanner and Weaver (2022)). Furthermore, the observed radio luminosity may be
the result of many processes, and not simply a direct tracer of jets (Panessa
et al. (2019); Fischer et al. (2023); Section 3.2). Therefore, when using
observed AGN luminosities and jet powers to test theoretical predictions, or
to establish the dominant energy driving mechanisms, it is crucial to consider
all of these systematic uncertainties.

The ratio between the outflow kinetic power and AGN luminosity is often
referred to as the kinetic coupling efficiency and it has been widely used by
the community in an attempt to compare observational results with the
predictions from cosmological simulations. In the seminal work of Di Matteo et
al. Di Matteo et al. (2005), the feedback efficiency ($\epsilon_{f}$; the
fraction of AGN luminosity that couples to the gas in the vicinity of the
black hole) was calibrated to 5%, so the local MBH-$\sigma$ relation was
reproduced by the simulation. As widely discussed in Harrison et al. (2018),
the comparison between the observed kinetic coupling efficiencies (Ėkin/Lbol)
and the $\epsilon_{f}$ values adopted in cosmological simulations is not
straightforward. First, in the case of radiation-driven gas outflows, the
feedback efficiencies are calibrated (to $\sim$0.005-0.15 in more recent
simulations; see Harrison et al. (2018) and references therein) and hence are
not a prediction themselves Bourne and Nayakshin (2013); Crain et al. (2015);
Schaye et al. (2015). Second, only a fraction of the injected energy will be
transformed into outflow kinetic energy depending on the ISM properties, the
gravitational potential, etc. Therefore, only a small kinetic coupling
efficiency may be actually measured from observations. Finally, as several
observational studies show, outflows can be launched/accelerated by compact
jets, even in radiatively efficient AGN, challenging how useful a comparison
to the bolometric AGN output would be in these cases (see Sections 3.3 and
4.1). As discussed in Sections 5 and 6, there are better ways to compare
observations with the predictions from simulations than just taking a fiducial
theoretical value as a reference to determine whether kiloparsec scale
outflows are relevant from an energetic point of view.

##  5 Localised and transient impact on gas and star formation

According to cosmological simulations, it is the cumulative output of several
AGN events that are most relevant for the global and long-term impact on their
host galaxies (see Section 6). The current AGN state of a galaxy is therefore
not a useful proxy for studying the global and long-term impact of AGN
feedback on gas and star formation, at least in the local Universe (see Silk
et al. (2024) for a recent discussion of the potential impact of AGN feedback
across cosmic time). However, by studying currently active AGN, using
spatially-resolved observations, we can obtain crucial information on the
localised impact of AGN feedback (labelled as ‘3’ in Figure 2), which is
needed to understand how the energy couples with the gas, and under which
circumstances it enhances or reduces star formation efficiency.

As already mentioned in Section 2, AGN should be treated as events or episodes
that are much shorter than the typical timescales of star formation. In the
case of the outflows, the dynamical timescales are usually $\sim$1-10 Myr
depending on their velocity and extent (for example, for an unimpeded outflow
expanding at an average velocity of 1000 km s-1 it takes one million years to
reach a radius of one kiloparsec). Therefore, if we aim at investigating the
impact, either positive or negative, that the present outflows have on star
formation, we should be looking at young stellar populations (YSPs), dominated
by O and B stars. The latter can be traced using stellar population modelling
of rest-frame UV/optical spectra Bruzual and Charlot (2003) and also the
polycyclic aromatic hydrocarbon (PAH) features detected in the rest-frame mid-
infrared Peeters et al. (2004). In the case of other star formation tracers
such as H$\alpha$, [Ne II], and the 24 $\mu$m flux it is difficult to
disentangle the contribution from star formation and AGN (e.g., Stanley et al.
(2018); Scholtz et al. (2021); Lamperti et al. (2021)), although it has been
argued that PAHs could also be excited by AGN radiation (Howell et al., 2007;
Jensen et al., 2017). Stellar synthesis modelling is challenging in AGN
because in the case of type-1 AGN the strong continuum dilutes the stellar
absorption features. Type-2 AGN are better suited for this type of analysis,
although scattered AGN light from the obscured nucleus can significantly
contribute to the UV/optical continuum, and therefore can be interpreted as a
YSP Bessiere et al. (2017). This degeneracy can be broken if high order Balmer
lines (e.g., H9, H10, H11 and H12; 3835–3750 Å) are detected, since they are
tracers of young stars. It is also important to account for the nebular
continuum coming from the free–free, free–bound and two photon decay continua
associated with the gas nebula Dickson et al. (1995) to accurately
characterise the YSPs.

Evidence for recent star formation in AGN based on the detection of PAH
features has been reported from kiloparsec scales (Zakamska et al., 2008,
2016; Deo et al., 2009; Diamond-Stanic and Rieke, 2012) to as close as tens of
parsecs from the AGN (Sales et al., 2013; Alonso-Herrero et al., 2014; Esquej
et al., 2014; Ramos Almeida et al., 2014; Esparza-Arredondo et al., 2018).
However, it is important to remember that AGN radiation and shocks might
modify the structure of the aromatic molecules and/or destroy the smallest
grains, hence suppressing the short-wavelength features (6.2, 7.7, and 8.6
$\mu$m; Smith et al. (2007); Diamond-Stanic and Rieke (2010)). Luckily the
larger and neutral molecules that produce the 11.3 and 17 $\mu$m features are
more resilient and they have been found to be enhanced in AGN relative to the
short-wavelength PAHs, at least in Seyfert galaxies (García-Bernete et al.,
2022). At higher AGN luminosities it is not clear if even the largest PAH
molecules can survive the AGN radiation field Martínez-Paredes et al. (2019);
Xie and Ho (2022); Ramos Almeida et al. (2023), but upcoming JWST datasets
will be crucial to study the viability of PAH features as tracers of star
formation in AGN of different luminosities, at different distances from the
AGN, and in and out the outflow/jet regions García-Bernete et al. (2022); Lai
et al. (2022, 2023).

AGN-driven outflows and jets can trigger star formation locally by compressing
the surrounding gas, as it has been shown theoretically (e.g., Silk (2013);
Zubovas and Bourne (2017); Mercedes-Feliz et al. (2023); Raouf et al. (2023))
and observationally using integral field spectroscopy and/or interferometry
(e.g., Cresci et al. (2015); Salomé et al. (2017); Carniani et al. (2016);
Shin et al. (2019); Bessiere and Ramos Almeida (2022)). Mercedes-Feliz et al.
Mercedes-Feliz et al. (2023) used the FIRE simulations incorporating hyper-
refined disc winds to study the impact of quasar outflows with kinetic powers
of 1046 erg s-1 on the circumnuclear disc (CND; scales of $\sim$100 pc; see
Figure 1) of massive galaxies at z$\sim$2\. These outflows drive the formation
of a central gas cavity and increase the local star formation efficiency at
its inner edges, where gas is being compressed. Despite this localised
positive feedback, the simulations show that the outflows reduce the surface
density of star formation across the galaxy (i.e., negative feedback) by
limiting the availability of gas rather than evacuating it Torrey et al.
(2020); Mercedes-Feliz et al. (2023). Recent observational work using data
from legacy integral field spectroscopic surveys report evidence for
suppressed gas fractions and SFRs in the central kiloparsec of galaxies
hosting AGN as compared to matched controls (e.g., Sánchez et al. (2018);
Ellison et al. (2021); Lammers et al. (2023)).

The creation of molecular gas cavities of tens to hundreds of parsecs by AGN-
driven outflows and/or jets is one of the most clear observational evidences
of the direct impact of AGN feedback on the host galaxies Rosario et al.
(2019); Feruglio et al. (2020); García-Burillo et al. (2019, 2021). Using ALMA
CO observations at $\sim$10 pc resolution of a sample of nearby AGN with X-ray
luminosities in the range $\sim$1039-43 erg s-1, García-Burillo et al. García-
Burillo et al. (2021) found that the most luminous AGN within the sample show
evidence for molecular outflows and smaller molecular gas concentrations in
the inner r$\sim$50 pc (torus scales) of the galaxies relative to the inner
r$\sim$200 pc (CND scales) than the less luminous AGN in the sample. They
interpreted these results as the imprint of feedback on the nuclear
distribution of molecular gas: at low AGN luminosities, galaxies build their
nuclear molecular gas reservoirs via accretion of gas, and as accretion and
subsequent feedback become more efficient, jets and winds push molecular gas
outwards, producing the cavities predicted by hydrodynamic simulations (e.g.,
Torrey et al. (2020); Mercedes-Feliz et al. (2023); Raouf et al. (2023)).
These molecular gas cavities, which have been detected in low-J CO transitions
such as CO(1-0) Ruffa et al. (2022), CO(2-1) Rosario et al. (2019); Feruglio
et al. (2020); García-Bernete et al. (2021); Ramos Almeida et al. (2022), and
CO(3-2) García-Burillo et al. (2019, 2021), are filled with ionised and warm
molecular (H2) gas Rosario et al. (2019); García-Burillo et al. (2019);
Feruglio et al. (2020), indicating that the AGN is modifying the properties of
the cold molecular gas on CND scales. Indeed, for AGN observed in more than
one CO transition, such as NGC 1068 García-Burillo et al. (2019), NGC 3100
Ruffa et al. (2022) and the Teacup Audibert et al. (2023) higher gas
excitation is found in the central regions of the galaxies. All these galaxies
have relatively low jet-powers (P${}_{\rm jet}\sim$1043 erg s-1) with
different inclinations relative to the molecular gas discs, which might be
responsible, together with AGN radiation and outflows, for the high gas
excitation in specific regions of the galaxy centers.

In summary, spatially-resolved studies of nearby AGN are revealing the complex
interplay between AGN and the surrounding gas. Obtaining accurate measurements
of this interplay, including outflow energetics and ambient gas and recent
star formation properties, is key to revise the recipes used in simulations.
The high angular resolution and sensitivity of facilities such as ALMA and the
JWST now allow us to obtain spatially-resolved constraints at high redshift
(e.g., D’Eugenio et al. (2023); Tripodi et al. (2024); Übler et al. (2024)).

##  6 Global and long-term cumulative impact of AGN feedback

To assess the relevance of AGN feedback in a cosmological context, requires
statistical studies that search for the imprint of feedback on the overall
galaxy population (labelled ‘4’ in Figure 2).

Some of the best evidence that AGN have a global and long-term impact on
galaxy evolution comes from the observation that AGN jets can offset cooling
in dense galactic environments. Hence, they can regulate the rate at which gas
can cool into galaxies and form stars. X-ray cavities excavated by radio jets
are well studied in local cluster and group environments, and provide direct
indication of the work done as these jet-induced lobes expand into the
ICM/IGrM Boehringer et al. (1993); Bîrzan et al. (2008); McNamara and Nulsen
(2012); Hlavacek-Larrondo et al. (2022). This process, appears to provide the
required amount of heating to balance cooling and may apply for massive early
type galaxies in a wider range of environments and out to $z\sim$1 Best et al.
(2006); Danielson et al. (2012); Hlavacek-Larrondo et al. (2015); Smolčić et
al. (2017); McDonald et al. (2018); Hardcastle et al. (2019). In broad terms,
there appears to be convincing evidence that the cumulative effect of AGN (see
Figure 2) is able to regulate cooling in massive systems, at least in the
densest environments and the latest cosmic times. Nonetheless, some of these
calculations remain uncertain, it is still an open question on how the energy
is communicated to the ICM/IGrM, and the universal applicability across
different environments and accretion states remains a matter of ongoing study
Bîrzan et al. (2017); Werner et al. (2019); Hardcastle and Croston (2020);
Bourne and Yang (2023). Furthermore, whilst this could be an effective
mechanism for maintaining low star formation levels, it may be insufficient to
shut down, i.e., ‘quench’, high star formation levels, which may require a
more ejective form of feedback (e.g., Dubois et al. (2010); McCarthy et al.
(2011); Davies et al. (2020); Zinger et al. (2020)).

One common type of study has been to measure the SFRs, gas fractions, and star
formation efficiencies in samples of AGN host galaxies (see Harrison (2017);
Ward et al. (2022), and references there-in). Some of these studies look for
instantaneous impact of the observed AGN events on either the global (galaxy-
wide) fuel for star formation (the molecular gas content) or directly on the
SFRs. The two broad approaches are to compare these measured properties to
matched samples of inactive galaxies (e.g., Scholtz et al. (2018); Kirkpatrick
et al. (2019); Circosta et al. (2021); Bischetti et al. (2021); Ramos Almeida
et al. (2022); Molyneux et al. (2024)), or to explore these properties as a
function of AGN luminosity or the prevalence of AGN-driven outflows (e.g.,
Rosario et al. (2013); Stanley et al. (2015); Balmaverde et al. (2016); Woo et
al. (2017); Stanley et al. (2017); Wylezalek and Morganti (2018); Shangguan
and Ho (2019); Zhuang et al. (2021); Kim et al. (2022)). There has been some
evidence (although not a consensus) that luminous AGN at cosmic noon have
moderately depleted levels of molecular gas (e.g., Perna et al. (2018);
Circosta et al. (2021)). This potentially indicates that this gas has been
excited to higher transitions (see Section 5) or has been ejected. However,
despite the wide range of approaches, and the different AGN samples, the
general consensus is that radiatively efficient AGN typically reside in gas-
rich, star-forming galaxies. This general picture is also consistent with
statistical studies that look at the galaxy population as a whole; although
not all radiatively efficient AGN live in star-forming galaxies, this is more
likely to be the case for the most luminous AGN (e.g., Aird et al. (2019);
Grimmett et al. (2020)). In contrast, radiatively inefficient AGN are more
likely to be found in quenched (non star-forming) galaxies (e.g., Miraghaei
and Best (2017)).

A comparison to cosmological simulations shows broad agreement with the above
observational result, that high accretion rate AGN typically reside in gas
rich, star-forming galaxies Scholtz et al. (2018); Ward et al. (2022);
Piotrowska et al. (2022); Bluck et al. (2023a). This likely tells us something
about the shared fuel supply and feeding processes needed to invoke a luminous
AGN event. Furthermore, it shows that these type of observations do not rule
out AGN feedback models that are invoked in simulations. Indeed, a measured
instantaneous radiative luminosity of an AGN is likely unconnected to the
eventual global, cumulative, feedback on the host galaxy because an
instantaneous AGN luminosity does not constrain the total (cumulative) energy
injection that could occur during multiple periods of black hole growth (see
Figure 2). This all suggests that molecular global gas content and SFRs of
statistical samples of galaxies hosting radiatively efficient AGN, are not
expected to reveal strong signatures of galaxy-wide (global) AGN feedback
(also see Scholtz et al. (2018); Ward et al. (2022); Piotrowska et al. (2022);
Bluck et al. (2023a, b)). Instead, the global evidence for AGN feedback may be
found in the wider galaxy population, which do not necessarily currently host
an observable AGN event (e.g., Martín-Navarro et al. (2018, 2021)).

AGN feedback is largely required in galaxy evolution theory to explain the
build up of quenched galaxies. Therefore, another approach to investigate the
role of AGN feedback is to consider the galaxy population as a whole, and ask
what is the most important factor/property for a galaxy to be quenched. The
total black hole mass can be considered a tracer of the historic record of the
total radiative energy output by AGN (see Figure 2), because the majority of
black hole growth occurs during radiatively efficient phases. Work has
suggested a strong connection between black hole mass and quiescence in
galaxies, for stellar-mass matched samples, with broad agreement between both
observations and simulations (at least for massive central galaxies, as
opposed to satellite galaxies; Terrazas et al. (2016); Piotrowska et al.
(2022); Bluck et al. (2023a, b)). These works imply that it is the integrated
(cumulative) history of energy injection from AGN that is the most important
for suppressing star formation, and not the instantaneous AGN luminosity.
Nonetheless, caution must be taken when comparing these observations to
simulations that invoke effective feedback prescriptions that are only turned
on above a certain black hole mass (also see Ward et al. (2022)). Furthermore,
significant energy output may occur during AGN events that do not contribute
significantly to black hole growth, for example from jets during radiatively
ineffecient AGN events.

Indeed, an important difference between some feedback models in cosmological
simulations, is if the feedback is most efficient during periods of rapid
black hole growth (cf. a ‘radiatively efficient’ regime), or periods of low
accretion (cf. a ‘radiatively inefficient’ regime). In the former case the
total energy output will be related to the black hole mass, whilst for the
later this is not necessarily the case. Voit et al. Voit et al. (2024) show
that the failure of one particular cosmological simulation to reproduce the
observed black hole mass to halo mass relationship can be attributed to the
fact that the implemented efficient mode of feedback for lifting baryons
(which results in the star-formation quenching) occurs only during periods of
low accretion rates. This appears to be in contrast to observations that
suggest the majority of black hole growth occurs during the quenching process
Chen et al. (2020); Voit et al. (2024). Similar comparisons between
observations of the overall galaxy population and simulations, will be
important to further test and refine the different prescriptions of feedback
models in simulations (e.g., Habouzit et al. (2021); Kondapally et al.
(2023)). Spatially-resolved measurements of star formation, and stellar
populations, on large samples of galaxies in different environments can shed
further insight into the quenching process and the potential role of AGN
across different populations (e.g., Bluck et al. (2020); Lammers et al.
(2023)).

Finally, we note that the effects of AGN feedback may be imprinted on CGM’s
surface brightness profiles of emission-line regions and on the distribution
of metals (e.g., Costa et al. (2022); Obreja et al. (2024)). Different
prescriptions of feedback result in different predicted properties of the CGM
(e.g., Davies et al. (2020); Costa et al. (2022); Khaire et al. (2023); Wright
et al. (2024)). This remains a promising route to further test feedback
prescriptions and bridge the gap between theoretical predictions and
observational studies.

##  7 Concluding remarks

After decades of work, we draw the conclusion that there are no observations
which are inconsistent with the broadest theoretical idea that AGN feedback is
a crucial component of galaxy formation theory for explaining the properties
of massive galaxies. However, obtaining a complete physical picture of how
this process works in the real Universe is an on-going challenge. It is a
multi-scale problem over many orders of magnitude in spatial, temperature, and
time scale (see Figure 1 and Section 2). Therefore, it is inescapable that
multiple observational approaches are required to tackle this problem, using a
range of facilities and a breadth of galaxy samples, for addressing the many
components of the overall process (see Figure 2). Some key takeaway points
from our holistic review are:

  * •

AGN should be considered events and not objects that persist in time. AGN are
self-regulatory and variable; therefore, it may be difficult to directly
relate a single accretion episode to a significant, global impact on galaxy
properties. Ultimately, the properties of a galaxy will be influenced by the
cumulative output of multiple accretion episodes/feedback events (see Section
2).

  * •

Both high accretion rate (‘radiatively efficient’) and low accretion rate
(‘radiatively inefficient’) AGN can have multiple, overlapping mechanisms for
injecting energy into their hosts (see Figure 3). These can contribute to both
ejective and regulative channels of feedback (see Figure 2). Radio emission
can trace a range of feedback mechanisms over a range accretion rates (see
Figures 3 and 4). Therefore, care should be taken when comparing simplified
theoretical feedback modes with observed AGN populations (see Section 3).

  * •

An AGN-driven outflow is gas that has been kinematically disturbed by a
variety of possible driving mechanisms including accretion disc winds,
radiation pressure, and jets. For the outflows to be relevant for feedback
their energy has to couple to the multi-phase gas, and this coupling depends
on several factors including AGN luminosity or jet-power, jet/wind orientation
and ISM properties. More efficient coupling will result in a more significant
impact on the properties/distribution of the gas, both localised and globally
(see Figure 2). Observations of representative samples of AGN of different
luminosities, hosted in galaxies with diverse properties, are needed to
quantify the relevance of the previously mentioned factors on the coupling
(see Section 4).

  * •

Whilst the current AGN state of a galaxy is not a priori a useful proxy for
assessing the impact on global galaxy properties, by studying currently active
AGN, with spatially-resolved observations, we can obtain crucial information
on the physics of localised impact. This is essential to determine how the
energy couples with the gas, and under which circumstances it enhances or
reduces star formation efficiency (see Figure 2 and Section 5).

  * •

Evidence of the cumulative impact of AGN episodes on global galaxy properties
is likely found in the galaxy population as a whole (not necessarily currently
active). Distributions of galaxy properties are important for testing, and
ruling out, different AGN feedback prescriptions implemented in cosmological
simulations (see Section 6).

Over the next decade we expect an explosion of data that will build up an
increasingly complete observational picture of how AGN couple to multi-phase
gas, and the resulting impact of this interaction. With the latest
observatories and instrumentation, this will be possible for ever-more
representative galaxy samples, including for the relatively unexplored lowest
mass galaxies Davis et al. (2022); Bohn et al. (2021); Koudmani et al. (2022);
Arjona-Galvez et al. (2024) and those in the earliest Universe Carniani et al.
(2023); Tripodi et al. (2024). High-resolution simulations, that incorporate
more physics, and that can be compared meaningfully to observations (e.g.,
Costa et al. (2022); Tanner and Weaver (2022); Meenakshi et al. (2022);
Audibert et al. (2023); Bourne and Yang (2023); Mercedes-Feliz et al. (2023);
Dutta et al. (2023)) provide a promising future for understanding physics of
the localised and transient processes of interactions between AGN and their
host galaxies, and the potential cumulative, global, and long-term impact of
these interactions. All aspects of the multi-faceted observational approaches,
summarised in Figure 2, remain important as we strive for a comprehensive
understanding of the role of AGN feedback in galaxy evolution.

The conceptualization, research and writing were carried out jointly by C.M.H
and C.R.A.

C.M.H acknowledges funding from a United Kingdom Research and Innovation grant
(code: MR/V022830/1). C.R.A thanks support by the EU H2020-MSCA-ITN-2019
Project 860744 “BiD4BESt: Big Data applications for black hole Evolution
STudies” and from project PID2022-141105NB-I00 “Tracking active galactic
nuclei feedback from parsec to kiloparsec scales”, funded by MICINN-
AEI/10.13039/501100011033.

“Not applicable”

###### Acknowledgements.

We thank the participants of “AGN on the Beach” and “The Importance of Jet-
induced Feedback on Galaxy Scales”, meetings for inspiring the contents of
this article. We thank Ilaria Ruffa for the organisation of the first meeting
and both the organising committee and the Lorentz Center staff for the latter.
We thank Houda Haidar and Tiago Costa for providing insightful comments and
suggestions and Gabriel Pérez Díaz (IAC MultiMedia Service, SMM) for producing
the digital version of Figures 1, 2 and 3. We thank the referees for their
reports which helped us improve the clarity of this article. The authors
declare no conflict of interest. The funders had no role in study or in the
decision to publish the results. References

## References

  * Ghez et al. (2008) Ghez, A.M.; Salim, S.; Weinberg, N.N.; Lu, J.R.; Do, T.; Dunn, J.K.; Matthews, K.; Morris, M.R.; Yelda, S.; Becklin, E.E.; et al.  Measuring Distance and Properties of the Milky Way’s Central Supermassive Black Hole with Stellar Orbits.  ApJ 2008, 689, 1044–1062, [arXiv:astro-ph/0808.2870].  https://doi.org/10.1086/592738.
  * Kormendy and Ho (2013) Kormendy, J.; Ho, L.C.  Coevolution (Or Not) of Supermassive Black Holes and Host Galaxies.  ARA&A 2013, 51, 511–653, [arXiv:astro-ph.CO/1304.7762].  https://doi.org/10.1146/annurev-astro-082708-101811.
  * Event Horizon Telescope Collaboration et al. (2019) Event Horizon Telescope Collaboration.; Akiyama, K.; Alberdi, A.; Alef, W.; Asada, K.; Azulay, R.; Baczko, A.K.; Ball, D.; Baloković, M.; Barrett, J.; et al.  First M87 Event Horizon Telescope Results. I. The Shadow of the Supermassive Black Hole.  ApJ 2019, 875, L1, [arXiv:astro-ph.GA/1906.11238].  https://doi.org/10.3847/2041-8213/ab0ec7.
  * GRAVITY Collaboration et al. (2020) GRAVITY Collaboration.; Abuter, R.; Amorim, A.; Bauböck, M.; Berger, J.P.; Bonnet, H.; Brandner, W.; Cardoso, V.; Clénet, Y.; de Zeeuw, P.T.; et al.  Detection of the Schwarzschild precession in the orbit of the star S2 near the Galactic centre massive black hole.  A&A 2020, 636, L5, [arXiv:astro-ph.GA/2004.07187].  https://doi.org/10.1051/0004-6361/202037813.
  * Nightingale et al. (2023) Nightingale, J.W.; Smith, R.J.; He, Q.; O’Riordan, C.M.; Kegerreis, J.A.; Amvrosiadis, A.; Edge, A.C.; Etherington, A.; Hayes, R.G.; Kelly, A.; et al.  Abell 1201: detection of an ultramassive black hole in a strong gravitational lens.  MNRAS 2023, 521, 3298–3322, [arXiv:astro-ph.GA/2303.15514].  https://doi.org/10.1093/mnras/stad587.
  * Soltan (1982) Soltan, A.  Masses of quasars.  MNRAS 1982, 200, 115–122.  https://doi.org/10.1093/mnras/200.1.115.
  * Marconi et al. (2004) Marconi, A.; Risaliti, G.; Gilli, R.; Hunt, L.K.; Maiolino, R.; Salvati, M.  Local supermassive black holes, relics of active galactic nuclei and the X-ray background.  MNRAS 2004, 351, 169–185, [arXiv:astro-ph/astro-ph/0311619].  https://doi.org/10.1111/j.1365-2966.2004.07765.x.
  * Alexander and Hickox (2012) Alexander, D.M.; Hickox, R.C.  What drives the growth of black holes?  New A Rev. 2012, 56, 93–121, [arXiv:astro-ph.GA/1112.1949].  https://doi.org/10.1016/j.newar.2011.11.003.
  * Harrison et al. (2018) Harrison, C.M.; Costa, T.; Tadhunter, C.N.; Flütsch, A.; Kakkad, D.; Perna, M.; Vietri, G.  AGN outflows and feedback twenty years on.  Nature Astronomy 2018, 2, 198–205, [arXiv:astro-ph.GA/1802.10306].  https://doi.org/10.1038/s41550-018-0403-6.
  * Magorrian et al. (1998) Magorrian, J.; Tremaine, S.; Richstone, D.; Bender, R.; Bower, G.; Dressler, A.; Faber, S.M.; Gebhardt, K.; Green, R.; Grillmair, C.; et al.  The Demography of Massive Dark Objects in Galaxy Centers.  AJ 1998, 115, 2285–2305, [arXiv:astro-ph/astro-ph/9708072].  https://doi.org/10.1086/300353.
  * Gebhardt et al. (2000) Gebhardt, K.; Bender, R.; Bower, G.; Dressler, A.; Faber, S.M.; Filippenko, A.V.; Green, R.; Grillmair, C.; Ho, L.C.; Kormendy, J.; et al.  A Relationship between Nuclear Black Hole Mass and Galaxy Velocity Dispersion.  ApJ 2000, 539, L13–L16, [arXiv:astro-ph/astro-ph/0006289].  https://doi.org/10.1086/312840.
  * Ferrarese and Merritt (2000) Ferrarese, L.; Merritt, D.  A Fundamental Relation between Supermassive Black Holes and Their Host Galaxies.  ApJ 2000, 539, L9–L12, [arXiv:astro-ph/astro-ph/0006053].  https://doi.org/10.1086/312838.
  * Silk and Rees (1998) Silk, J.; Rees, M.J.  Quasars and galaxy formation.  A&A 1998, 331, L1–L4, [arXiv:astro-ph/astro-ph/9801013].  https://doi.org/10.48550/arXiv.astro-ph/9801013.
  * King (2003) King, A.  Black Holes, Galaxy Formation, and the MBH-$\sigma$ Relation.  ApJ 2003, 596, L27–L29, [arXiv:astro-ph/astro-ph/0308342].  https://doi.org/10.1086/379143.
  * King (2005) King, A.  The AGN-Starburst Connection, Galactic Superwinds, and MBH-$\sigma$.  ApJ 2005, 635, L121–L123, [arXiv:astro-ph/astro-ph/0511034].  https://doi.org/10.1086/499430.
  * Binney and Tabor (1995) Binney, J.; Tabor, G.  Evolving cooling flows.  MNRAS 1995, 276, 663–678.  https://doi.org/10.1093/mnras/276.2.663.
  * Ciotti and Ostriker (1997) Ciotti, L.; Ostriker, J.P.  Cooling Flows and Quasars: Different Aspects of the Same Phenomenon? I. Concepts.  ApJ 1997, 487, L105–L108, [arXiv:astro-ph/astro-ph/9706281].  https://doi.org/10.1086/310902.
  * Peterson et al. (2003) Peterson, J.R.; Kahn, S.M.; Paerels, F.B.S.; Kaastra, J.S.; Tamura, T.; Bleeker, J.A.M.; Ferrigno, C.; Jernigan, J.G.  High-Resolution X-Ray Spectroscopic Constraints on Cooling-Flow Models for Clusters of Galaxies.  ApJ 2003, 590, 207–224, [arXiv:astro-ph/astro-ph/0210662].  https://doi.org/10.1086/374830.
  * Benson et al. (2003) Benson, A.J.; Bower, R.G.; Frenk, C.S.; Lacey, C.G.; Baugh, C.M.; Cole, S.  What Shapes the Luminosity Function of Galaxies?  ApJ 2003, 599, 38–49, [arXiv:astro-ph/astro-ph/0302450].  https://doi.org/10.1086/379160.
  * Springel et al. (2005) Springel, V.; Di Matteo, T.; Hernquist, L.  Modelling feedback from stars and black holes in galaxy mergers.  MNRAS 2005, 361, 776–794, [arXiv:astro-ph/astro-ph/0411108].  https://doi.org/10.1111/j.1365-2966.2005.09238.x.
  * Croton et al. (2006) Croton, D.J.; Springel, V.; White, S.D.M.; De Lucia, G.; Frenk, C.S.; Gao, L.; Jenkins, A.; Kauffmann, G.; Navarro, J.F.; Yoshida, N.  The many lives of active galactic nuclei: cooling flows, black holes and the luminosities and colours of galaxies.  MNRAS 2006, 365, 11–28, [arXiv:astro-ph/astro-ph/0508046].  https://doi.org/10.1111/j.1365-2966.2005.09675.x.
  * Bower et al. (2006) Bower, R.G.; Benson, A.J.; Malbon, R.; Helly, J.C.; Frenk, C.S.; Baugh, C.M.; Cole, S.; Lacey, C.G.  Breaking the hierarchy of galaxy formation.  MNRAS 2006, 370, 645–655, [arXiv:astro-ph/astro-ph/0511338].  https://doi.org/10.1111/j.1365-2966.2006.10519.x.
  * Somerville et al. (2008) Somerville, R.S.; Hopkins, P.F.; Cox, T.J.; Robertson, B.E.; Hernquist, L.  A semi-analytic model for the co-evolution of galaxies, black holes and active galactic nuclei.  MNRAS 2008, 391, 481–506, [arXiv:astro-ph/0808.1227].  https://doi.org/10.1111/j.1365-2966.2008.13805.x.
  * Schaye et al. (2015) Schaye, J.; Crain, R.A.; Bower, R.G.; Furlong, M.; Schaller, M.; Theuns, T.; Dalla Vecchia, C.; Frenk, C.S.; McCarthy, I.G.; Helly, J.C.; et al.  The EAGLE project: simulating the evolution and assembly of galaxies and their environments.  MNRAS 2015, 446, 521–554, [arXiv:astro-ph.GA/1407.7040].  https://doi.org/10.1093/mnras/stu2058.
  * Khandai et al. (2015) Khandai, N.; Di Matteo, T.; Croft, R.; Wilkins, S.; Feng, Y.; Tucker, E.; DeGraf, C.; Liu, M.S.  The MassiveBlack-II simulation: the evolution of haloes and galaxies to z $\sim$ 0\.  MNRAS 2015, 450, 1349–1374, [arXiv:astro-ph.CO/1402.0888].  https://doi.org/10.1093/mnras/stv627.
  * Dubois et al. (2016) Dubois, Y.; Peirani, S.; Pichon, C.; Devriendt, J.; Gavazzi, R.; Welker, C.; Volonteri, M.  The HORIZON-AGN simulation: morphological diversity of galaxies promoted by AGN feedback.  MNRAS 2016, 463, 3948–3964, [arXiv:astro-ph.GA/1606.03086].  https://doi.org/10.1093/mnras/stw2265.
  * Naab and Ostriker (2017) Naab, T.; Ostriker, J.P.  Theoretical Challenges in Galaxy Formation.  ARA&A 2017, 55, 59–109, [arXiv:astro-ph.GA/1612.06891].  https://doi.org/10.1146/annurev-astro-081913-040019.
  * McCarthy et al. (2017) McCarthy, I.G.; Schaye, J.; Bird, S.; Le Brun, A.M.C.  The BAHAMAS project: calibrated hydrodynamical simulations for large-scale structure cosmology.  MNRAS 2017, 465, 2936–2965, [arXiv:astro-ph.CO/1603.02702].  https://doi.org/10.1093/mnras/stw2792.
  * Nelson et al. (2018) Nelson, D.; Pillepich, A.; Springel, V.; Weinberger, R.; Hernquist, L.; Pakmor, R.; Genel, S.; Torrey, P.; Vogelsberger, M.; Kauffmann, G.; et al.  First results from the IllustrisTNG simulations: the galaxy colour bimodality.  MNRAS 2018, 475, 624–647, [arXiv:astro-ph.GA/1707.03395].  https://doi.org/10.1093/mnras/stx3040.
  * Davé et al. (2019) Davé, R.; Anglés-Alcázar, D.; Narayanan, D.; Li, Q.; Rafieferantsoa, M.H.; Appleby, S.  SIMBA: Cosmological simulations with black hole growth and feedback.  MNRAS 2019, 486, 2827–2849, [arXiv:astro-ph.GA/1901.10203].  https://doi.org/10.1093/mnras/stz937.
  * Choi et al. (2018) Choi, E.; Somerville, R.S.; Ostriker, J.P.; Naab, T.; Hirschmann, M.  The Role of Black Hole Feedback on Size and Structural Evolution in Massive Galaxies.  ApJ 2018, 866, 91, [arXiv:astro-ph.GA/1809.02143].  https://doi.org/10.3847/1538-4357/aae076.
  * Davies et al. (2019) Davies, J.J.; Crain, R.A.; McCarthy, I.G.; Oppenheimer, B.D.; Schaye, J.; Schaller, M.; McAlpine, S.  The gas fractions of dark matter haloes hosting simulated $\sim$L⋆ galaxies are governed by the feedback history of their black holes.  MNRAS 2019, 485, 3783–3793, [arXiv:astro-ph.GA/1810.07696].  https://doi.org/10.1093/mnras/stz635.
  * Peirani et al. (2019) Peirani, S.; Sonnenfeld, A.; Gavazzi, R.; Oguri, M.; Dubois, Y.; Silk, J.; Pichon, C.; Devriendt, J.; Kaviraj, S.  Total density profile of massive early-type galaxies in HORIZON-AGN simulation: impact of AGN feedback and comparison with observations.  MNRAS 2019, 483, 4615–4627, [arXiv:astro-ph.GA/1801.09754].  https://doi.org/10.1093/mnras/sty3475.
  * van der Vlugt and Costa (2019) van der Vlugt, D.; Costa, T.  How AGN feedback drives the size growth of the first quasars.  MNRAS 2019, 490, 4918–4934, [arXiv:astro-ph.GA/1903.04544].  https://doi.org/10.1093/mnras/stz2944.
  * Wright et al. (2020) Wright, R.J.; Lagos, C.d.P.; Power, C.; Mitchell, P.D.  The impact of stellar and AGN feedback on halo-scale baryonic and dark matter accretion in the EAGLE simulations.  MNRAS 2020, 498, 1668–1692, [arXiv:astro-ph.GA/2006.00924].  https://doi.org/10.1093/mnras/staa2359.
  * Cochrane et al. (2023) Cochrane, R.K.; Anglés-Alcázar, D.; Mercedes-Feliz, J.; Hayward, C.C.; Faucher-Giguère, C.A.; Wellons, S.; Terrazas, B.A.; Wetzel, A.; Hopkins, P.F.; Moreno, J.; et al.  The impact of AGN-driven winds on physical and observable galaxy sizes.  MNRAS 2023, 523, 2409–2421, [arXiv:astro-ph.GA/2303.12858].  https://doi.org/10.1093/mnras/stad1528.
  * Obreja et al. (2024) Obreja, A.; Arrigoni Battaia, F.; Macciò, A.V.; Buck, T.  AGN radiation imprints on the circumgalactic medium of massive galaxies.  MNRAS 2024, 527, 8078–8102, [arXiv:astro-ph.GA/2311.01503].  https://doi.org/10.1093/mnras/stad3410.
  * Zakamska et al. (2016) Zakamska, N.L.; Lampayan, K.; Petric, A.; Dicken, D.; Greene, J.E.; Heckman, T.M.; Hickox, R.C.; Ho, L.C.; Krolik, J.H.; Nesvadba, N.P.H.; et al.  Star formation in quasar hosts and the origin of radio emission in radio-quiet quasars.  MNRAS 2016, 455, 4191–4211, [arXiv:astro-ph.GA/1511.00013].  https://doi.org/10.1093/mnras/stv2571.
  * Ishibashi et al. (2018) Ishibashi, W.; Fabian, A.C.; Maiolino, R.  The energetics of AGN radiation pressure-driven outflows.  MNRAS 2018, 476, 512–519, [arXiv:astro-ph.GA/1801.09700].  https://doi.org/10.1093/mnras/sty236.
  * Rakshit and Woo (2018) Rakshit, S.; Woo, J.H.  A Census of Ionized Gas Outflows in Type 1 AGNs: Gas Outflows in AGNs. V.  ApJ 2018, 865, 5, [arXiv:astro-ph.GA/1808.03415].  https://doi.org/10.3847/1538-4357/aad9f8.
  * Jarvis et al. (2019) Jarvis, M.E.; Harrison, C.M.; Thomson, A.P.; Circosta, C.; Mainieri, V.; Alexander, D.M.; Edge, A.C.; Lansbury, G.B.; Molyneux, S.J.; Mullaney, J.R.  Prevalence of radio jets associated with galactic outflows and feedback from quasars.  MNRAS 2019, 485, 2710–2730, [arXiv:astro-ph.GA/1902.07727].  https://doi.org/10.1093/mnras/stz556.
  * Costa et al. (2020) Costa, T.; Pakmor, R.; Springel, V.  Powering galactic superwinds with small-scale AGN winds.  MNRAS 2020, 497, 5229–5255, [arXiv:astro-ph.GA/2006.05997].  https://doi.org/10.1093/mnras/staa2321.
  * Brüggen and Scannapieco (2020) Brüggen, M.; Scannapieco, E.  The Launching of Cold Clouds by Galaxy Outflows. IV. Cosmic-Ray-driven Acceleration.  ApJ 2020, 905, 19, [arXiv:astro-ph.GA/2010.07308].  https://doi.org/10.3847/1538-4357/abc00f.
  * Venturi et al. (2021) Venturi, G.; Cresci, G.; Marconi, A.; Mingozzi, M.; Nardini, E.; Carniani, S.; Mannucci, F.; Marasco, A.; Maiolino, R.; Perna, M.; et al.  MAGNUM survey: Compact jets causing large turmoil in galaxies. Enhanced line widths perpendicular to radio jets as tracers of jet-ISM interaction.  A&A 2021, 648, A17, [arXiv:astro-ph.GA/2011.04677].  https://doi.org/10.1051/0004-6361/202039869.
  * Mandal et al. (2021) Mandal, A.; Mukherjee, D.; Federrath, C.; Nesvadba, N.P.H.; Bicknell, G.V.; Wagner, A.Y.; Meenakshi, M.  Impact of relativistic jets on the star formation rate: a turbulence-regulated framework.  MNRAS 2021, 508, 4738–4757, [arXiv:astro-ph.GA/2109.13654].  https://doi.org/10.1093/mnras/stab2822.
  * Meena et al. (2023) Meena, B.; Crenshaw, D.M.; Schmitt, H.R.; Revalski, M.; Chapman, Z.; Fischer, T.C.; Kraemer, S.B.; Robinson, J.H.; Falcone, J.; Polack, G.E.  Investigating the Narrow-line Region Dynamics in Nearby Active Galaxies.  ApJ 2023, 943, 98, [arXiv:astro-ph.GA/2212.02513].  https://doi.org/10.3847/1538-4357/aca75f.
  * Calistro Rivera et al. (2023) Calistro Rivera, G.; Alexander, D.M.; Harrison, C.M.; Fawcett, V.A.; Best, P.N.; Williams, W.L.; Hardcastle, M.J.; Rosario, D.J.; Smith, D.J.B.; Arnaudova, M.I.; et al.  Ubiquitous radio emission in quasars: predominant AGN origin and a connection to jets, dust and winds.  arXiv e-prints 2023, p. arXiv:2312.10177, [arXiv:astro-ph.GA/2312.10177].  https://doi.org/10.48550/arXiv.2312.10177.
  * Fabian (2012) Fabian, A.C.  Observational Evidence of Active Galactic Nuclei Feedback.  ARA&A 2012, 50, 455–489, [arXiv:astro-ph.CO/1204.4114].  https://doi.org/10.1146/annurev-astro-081811-125521.
  * McNamara and Nulsen (2012) McNamara, B.R.; Nulsen, P.E.J.  Mechanical feedback from active galactic nuclei in galaxies, groups and clusters.  New Journal of Physics 2012, 14, 055023, [arXiv:astro-ph.CO/1204.0006].  https://doi.org/10.1088/1367-2630/14/5/055023.
  * Heckman and Best (2014) Heckman, T.M.; Best, P.N.  The Coevolution of Galaxies and Supermassive Black Holes: Insights from Surveys of the Contemporary Universe.  ARA&A 2014, 52, 589–660, [arXiv:astro-ph.GA/1403.4620].  https://doi.org/10.1146/annurev-astro-081913-035722.
  * Harrison (2017) Harrison, C.M.  Impact of supermassive black hole growth on star formation.  Nature Astronomy 2017, 1, 0165, [arXiv:astro-ph.GA/1703.06889].  https://doi.org/10.1038/s41550-017-0165.
  * Morganti (2017) Morganti, R.  The many routes to AGN feedback.  Frontiers in Astronomy and Space Sciences 2017, 4, 42, [arXiv:astro-ph.GA/1712.05301].  https://doi.org/10.3389/fspas.2017.00042.
  * King and Pounds (2015) King, A.; Pounds, K.  Powerful Outflows and Feedback from Active Galactic Nuclei.  ARA&A 2015, 53, 115–154, [arXiv:astro-ph.GA/1503.05206].  https://doi.org/10.1146/annurev-astro-082214-122316.
  * Hardcastle and Croston (2020) Hardcastle, M.J.; Croston, J.H.  Radio galaxies and feedback from AGN jets.  New A Rev. 2020, 88, 101539, [arXiv:astro-ph.HE/2003.06137].  https://doi.org/10.1016/j.newar.2020.101539.
  * Veilleux et al. (2020) Veilleux, S.; Maiolino, R.; Bolatto, A.D.; Aalto, S.  Cool outflows in galaxies and their implications.  A&A Rev. 2020, 28, 2, [arXiv:astro-ph.GA/2002.07765].  https://doi.org/10.1007/s00159-019-0121-9.
  * Bourne and Yang (2023) Bourne, M.A.; Yang, H.Y.K.  Recent Progress in Modeling the Macro- and Micro-Physics of Radio Jet Feedback in Galaxy Clusters.  Galaxies 2023, 11, 73, [arXiv:astro-ph.HE/2305.00019].  https://doi.org/10.3390/galaxies11030073.
  * Krause (2023) Krause, M.G.H.  Jet Feedback in Star-Forming Galaxies.  Galaxies 2023, 11, 29.  https://doi.org/10.3390/galaxies11010029.
  * Ramos Almeida and Ricci (2017) Ramos Almeida, C.; Ricci, C.  Nuclear obscuration in active galactic nuclei.  Nature Astronomy 2017, 1, 679–689, [arXiv:astro-ph.GA/1709.00019].  https://doi.org/10.1038/s41550-017-0232-z.
  * Tacconi et al. (2020) Tacconi, L.J.; Genzel, R.; Sternberg, A.  The Evolution of the Star-Forming Interstellar Medium Across Cosmic Time.  ARA&A 2020, 58, 157–203, [arXiv:astro-ph.GA/2003.06245].  https://doi.org/10.1146/annurev-astro-082812-141034.
  * Tumlinson et al. (2017) Tumlinson, J.; Peeples, M.S.; Werk, J.K.  The Circumgalactic Medium.  ARA&A 2017, 55, 389–432, [arXiv:astro-ph.GA/1709.09180].  https://doi.org/10.1146/annurev-astro-091916-055240.
  * Davies et al. (2020) Davies, J.J.; Crain, R.A.; Oppenheimer, B.D.; Schaye, J.  The quenching and morphological evolution of central galaxies is facilitated by the feedback-driven expulsion of circumgalactic gas.  MNRAS 2020, 491, 4462–4480, [arXiv:astro-ph.GA/1908.11380].  https://doi.org/10.1093/mnras/stz3201.
  * Ganguly et al. (2023) Ganguly, S.; Li, Y.; Olivares, V.; Su, Y.; Combes, F.; Prakash, S.; Hamer, S.; Guillard, P.; Ha, T.  The nature of the motions of multiphase filaments in the centers of galaxy clusters.  Frontiers in Astronomy and Space Sciences 2023, 10, 1138613, [arXiv:astro-ph.GA/2304.09879].  https://doi.org/10.3389/fspas.2023.1138613.
  * García-Burillo et al. (2021) García-Burillo, S.; Alonso-Herrero, A.; Ramos Almeida, C.; González-Martín, O.; Combes, F.; Usero, A.; Hönig, S.; Querejeta, M.; Hicks, E.K.S.; Hunt, L.K.; et al.  The Galaxy Activity, Torus, and Outflow Survey (GATOS). I. ALMA images of dusty molecular tori in Seyfert galaxies.  A&A 2021, 652, A98, [arXiv:astro-ph.GA/2104.10227].  https://doi.org/10.1051/0004-6361/202141075.
  * Mukherjee et al. (2018) Mukherjee, D.; Bicknell, G.V.; Wagner, A.Y.; Sutherland, R.S.; Silk, J.  Relativistic jet feedback - III. Feedback on gas discs.  MNRAS 2018, 479, 5544–5566, [arXiv:astro-ph.HE/1803.08305].  https://doi.org/10.1093/mnras/sty1776.
  * Richings and Faucher-Giguère (2018) Richings, A.J.; Faucher-Giguère, C.A.  The origin of fast molecular outflows in quasars: molecule formation in AGN-driven galactic winds.  MNRAS 2018, 474, 3673–3699, [arXiv:astro-ph.GA/1706.03784].  https://doi.org/10.1093/mnras/stx3014.
  * Peterson (2001) Peterson, B.M.  Variability of Active Galactic Nuclei.  In Proceedings of the Advanced Lectures on the Starburst-AGN; Aretxaga, I.; Kunth, D.; Mújica, R., Eds., 2001, p. 3, [arXiv:astro-ph/astro-ph/0109495].  https://doi.org/10.1142/9789812811318_0002.
  * Lintott et al. (2009) Lintott, C.J.; Schawinski, K.; Keel, W.; van Arkel, H.; Bennert, N.; Edmondson, E.; Thomas, D.; Smith, D.J.B.; Herbert, P.D.; Jarvis, M.J.; et al.  Galaxy Zoo: ‘Hanny’s Voorwerp’, a quasar light echo?  MNRAS 2009, 399, 129–140, [arXiv:astro-ph.CO/0906.5304].  https://doi.org/10.1111/j.1365-2966.2009.15299.x.
  * Mostert et al. (2023) Mostert, R.I.J.; Morganti, R.; Brienza, M.; Duncan, K.J.; Oei, M.S.S.L.; Röttgering, H.J.A.; Alegre, L.; Hardcastle, M.J.; Jurlin, N.  Finding AGN remnant candidates based on radio morphology with machine learning.  A&A 2023, 674, A208, [arXiv:astro-ph.GA/2304.05813].  https://doi.org/10.1051/0004-6361/202346035.
  * King and Nixon (2015) King, A.; Nixon, C.  AGN flickering and chaotic accretion.  MNRAS 2015, 453, L46–L47, [arXiv:astro-ph.HE/1507.05960].  https://doi.org/10.1093/mnrasl/slv098.
  * Schawinski et al. (2015) Schawinski, K.; Koss, M.; Berney, S.; Sartori, L.F.  Active galactic nuclei flicker: an observational estimate of the duration of black hole growth phases of $\sim$105 yr.  MNRAS 2015, 451, 2517–2523, [arXiv:astro-ph.GA/1505.06733].  https://doi.org/10.1093/mnras/stv1136.
  * Sabater et al. (2019) Sabater, J.; Best, P.N.; Hardcastle, M.J.; Shimwell, T.W.; Tasse, C.; Williams, W.L.; Brüggen, M.; Cochrane, R.K.; Croston, J.H.; de Gasperin, F.; et al.  The LoTSS view of radio AGN in the local Universe. The most massive galaxies are always switched on.  A&A 2019, 622, A17, [arXiv:astro-ph.GA/1811.05528].  https://doi.org/10.1051/0004-6361/201833883.
  * Hickox et al. (2014) Hickox, R.C.; Mullaney, J.R.; Alexander, D.M.; Chen, C.T.J.; Civano, F.M.; Goulding, A.D.; Hainline, K.N.  Black Hole Variability and the Star Formation-Active Galactic Nucleus Connection: Do All Star-forming Galaxies Host an Active Galactic Nucleus?  ApJ 2014, 782, 9, [arXiv:astro-ph.CO/1306.3218].  https://doi.org/10.1088/0004-637X/782/1/9.
  * Novak et al. (2011) Novak, G.S.; Ostriker, J.P.; Ciotti, L.  Feedback from Central Black Holes in Elliptical Galaxies: Two-dimensional Models Compared to One-dimensional Models.  ApJ 2011, 737, 26, [arXiv:astro-ph.GA/1007.3505].  https://doi.org/10.1088/0004-637X/737/1/26.
  * Hickox and Alexander (2018) Hickox, R.C.; Alexander, D.M.  Obscured Active Galactic Nuclei.  ARA&A 2018, 56, 625–671, [arXiv:astro-ph.GA/1806.04680].  https://doi.org/10.1146/annurev-astro-081817-051803.
  * Aird et al. (2018) Aird, J.; Coil, A.L.; Georgakakis, A.  X-rays across the galaxy population - II. The distribution of AGN accretion rates as a function of stellar mass and redshift.  MNRAS 2018, 474, 1225–1249, [arXiv:astro-ph.HE/1705.01132].  https://doi.org/10.1093/mnras/stx2700.
  * Rennehan et al. (2023) Rennehan, D.; Babul, A.; Moa, B.; Davé, R.  Three regimes of black hole feedback.  arXiv e-prints 2023, p. arXiv:2309.15898, [arXiv:astro-ph.GA/2309.15898].  https://doi.org/10.48550/arXiv.2309.15898.
  * Lupi et al. (2023) Lupi, A.; Quadri, G.; Volonteri, M.; Colpi, M.; Regan, J.A.  Sustained super-Eddington accretion in high-redshift quasars.  arXiv e-prints 2023, p. arXiv:2312.08422, [arXiv:astro-ph.GA/2312.08422].  https://doi.org/10.48550/arXiv.2312.08422.
  * Maiolino et al. (2023) Maiolino, R.; Scholtz, J.; Witstok, J.; Carniani, S.; D’Eugenio, F.; de Graaff, A.; Uebler, H.; Tacchella, S.; Curtis-Lake, E.; Arribas, S.; et al.  A small and vigorous black hole in the early Universe.  arXiv e-prints 2023, p. arXiv:2305.12492, [arXiv:astro-ph.GA/2305.12492].  https://doi.org/10.48550/arXiv.2305.12492.
  * Shakura and Sunyaev (1973) Shakura, N.I.; Sunyaev, R.A.  Black holes in binary systems. Observational appearance.  A&A 1973, 24, 337–355.
  * Esin et al. (1997) Esin, A.A.; McClintock, J.E.; Narayan, R.  Advection-Dominated Accretion and the Spectral States of Black Hole X-Ray Binaries: Application to Nova Muscae 1991.  ApJ 1997, 489, 865–889, [arXiv:astro-ph/astro-ph/9705237].  https://doi.org/10.1086/304829.
  * Narayan and Yi (1994) Narayan, R.; Yi, I.  Advection-dominated Accretion: A Self-similar Solution.  ApJ 1994, 428, L13, [arXiv:astro-ph/astro-ph/9403052].  https://doi.org/10.1086/187381.
  * Blandford and Znajek (1977) Blandford, R.D.; Znajek, R.L.  Electromagnetic extraction of energy from Kerr black holes.  MNRAS 1977, 179, 433–456.  https://doi.org/10.1093/mnras/179.3.433.
  * Sikora et al. (2007) Sikora, M.; Stawarz, Ł.; Lasota, J.P.  Radio Loudness of Active Galactic Nuclei: Observational Facts and Theoretical Implications.  ApJ 2007, 658, 815–828, [arXiv:astro-ph/astro-ph/0604095].  https://doi.org/10.1086/511972.
  * Blandford and Payne (1982) Blandford, R.D.; Payne, D.G.  Hydromagnetic flows from accretion disks and the production of radio jets.  MNRAS 1982, 199, 883–903.  https://doi.org/10.1093/mnras/199.4.883.
  * Begelman et al. (1983) Begelman, M.C.; McKee, C.F.; Shields, G.A.  Compton heated winds and coronae above accretion disks. I. Dynamics.  ApJ 1983, 271, 70–88.  https://doi.org/10.1086/161178.
  * Yuan and Narayan (2014) Yuan, F.; Narayan, R.  Hot Accretion Flows Around Black Holes.  ARA&A 2014, 52, 529–588, [arXiv:astro-ph.HE/1401.0586].  https://doi.org/10.1146/annurev-astro-082812-141003.
  * Gan et al. (2014) Gan, Z.; Yuan, F.; Ostriker, J.P.; Ciotti, L.; Novak, G.S.  Active Galactic Nucleus Feedback in an Isolated Elliptical Galaxy: The Effect of Strong Radiative Feedback in the Kinetic Mode.  ApJ 2014, 789, 150, [arXiv:astro-ph.GA/1403.0670].  https://doi.org/10.1088/0004-637X/789/2/150.
  * Almeida et al. (2023) Almeida, I.; Nemmen, R.; Riffel, R.A.  Quenching star formation with low-luminosity AGN winds.  MNRAS 2023, 526, 217–223, [arXiv:astro-ph.GA/2303.00826].  https://doi.org/10.1093/mnras/stad2673.
  * Padovani et al. (2017) Padovani, P.; Alexander, D.M.; Assef, R.J.; De Marco, B.; Giommi, P.; Hickox, R.C.; Richards, G.T.; Smolčić, V.; Hatziminaoglou, E.; Mainieri, V.; et al.  Active galactic nuclei: what’s in a name?  A&A Rev. 2017, 25, 2, [arXiv:astro-ph.GA/1707.07134].  https://doi.org/10.1007/s00159-017-0102-9.
  * Arrigoni Battaia et al. (2019) Arrigoni Battaia, F.; Hennawi, J.F.; Prochaska, J.X.; Oñorbe, J.; Farina, E.P.; Cantalupo, S.; Lusso, E.  QSO MUSEUM I: a sample of 61 extended Ly $\alpha$-emission nebulae surrounding z $\sim$ 3 quasars.  MNRAS 2019, 482, 3162–3205, [arXiv:astro-ph.GA/1808.10857].  https://doi.org/10.1093/mnras/sty2827.
  * Costa et al. (2022) Costa, T.; Arrigoni Battaia, F.; Farina, E.P.; Keating, L.C.; Rosdahl, J.; Kimm, T.  AGN-driven outflows and the formation of Ly$\alpha$ nebulae around high-z quasars.  MNRAS 2022, 517, 1767–1790, [arXiv:astro-ph.GA/2203.11232].  https://doi.org/10.1093/mnras/stac2432.
  * Costa et al. (2018) Costa, T.; Rosdahl, J.; Sijacki, D.; Haehnelt, M.G.  Quenching star formation with quasar outflows launched by trapped IR radiation.  MNRAS 2018, 479, 2079–2111, [arXiv:astro-ph.GA/1709.08638].  https://doi.org/10.1093/mnras/sty1514.
  * Murray et al. (1995) Murray, N.; Chiang, J.; Grossman, S.A.; Voit, G.M.  Accretion Disk Winds from Active Galactic Nuclei.  ApJ 1995, 451, 498.  https://doi.org/10.1086/176238.
  * Proga et al. (2000) Proga, D.; Stone, J.M.; Kallman, T.R.  Dynamics of Line-driven Disk Winds in Active Galactic Nuclei.  ApJ 2000, 543, 686–696, [arXiv:astro-ph/astro-ph/0005315].  https://doi.org/10.1086/317154.
  * Mizumoto et al. (2021) Mizumoto, M.; Nomura, M.; Done, C.; Ohsuga, K.; Odaka, H.  UV line-driven disc wind as the origin of UltraFast Outflows in AGN.  MNRAS 2021, 503, 1442–1458, [arXiv:astro-ph.HE/2003.01137].  https://doi.org/10.1093/mnras/staa3282.
  * Tanner and Weaver (2022) Tanner, R.; Weaver, K.A.  Simulations of AGN-driven Galactic Outflow Morphology and Content.  AJ 2022, 163, 134, [arXiv:astro-ph.GA/2201.08360].  https://doi.org/10.3847/1538-3881/ac4d23.
  * Sazonov et al. (2005) Sazonov, S.Y.; Ostriker, J.P.; Ciotti, L.; Sunyaev, R.A.  Radiative feedback from quasars and the growth of massive black holes in stellar spheroids.  MNRAS 2005, 358, 168–180, [arXiv:astro-ph/astro-ph/0411086].  https://doi.org/10.1111/j.1365-2966.2005.08763.x.
  * Bourne and Nayakshin (2013) Bourne, M.A.; Nayakshin, S.  Inverse Compton X-ray signature of AGN feedback.  MNRAS 2013, 436, 2346–2351, [arXiv:astro-ph.GA/1306.2636].  https://doi.org/10.1093/mnras/stt1739.
  * Kellermann et al. (1989) Kellermann, K.I.; Sramek, R.; Schmidt, M.; Shaffer, D.B.; Green, R.  VLA Observations of Objects in the Palomar Bright Quasar Survey.  AJ 1989, 98, 1195.  https://doi.org/10.1086/115207.
  * Xu et al. (1999) Xu, C.; Livio, M.; Baum, S.  Radio-loud and Radio-quiet Active Galactic Nuclei.  AJ 1999, 118, 1169–1176, [arXiv:astro-ph/astro-ph/9905322].  https://doi.org/10.1086/301007.
  * Klindt et al. (2019) Klindt, L.; Alexander, D.M.; Rosario, D.J.; Lusso, E.; Fotopoulou, S.  Fundamental differences in the radio properties of red and blue quasars: evolution strongly favoured over orientation.  MNRAS 2019, 488, 3109–3128, [arXiv:astro-ph.GA/1905.12108].  https://doi.org/10.1093/mnras/stz1771.
  * Helou et al. (1985) Helou, G.; Soifer, B.T.; Rowan-Robinson, M.  Thermal infrared and nonthermal radio : remarkable correlation in disks of galaxies.  ApJ 1985, 298, L7–L11.  https://doi.org/10.1086/184556.
  * Ivison et al. (2010) Ivison, R.J.; Magnelli, B.; Ibar, E.; Andreani, P.; Elbaz, D.; Altieri, B.; Amblard, A.; Arumugam, V.; Auld, R.; Aussel, H.; et al.  The far-infrared/radio correlation as probed by Herschel.  A&A 2010, 518, L31, [arXiv:astro-ph.CO/1005.1072].  https://doi.org/10.1051/0004-6361/201014552.
  * Best and Heckman (2012) Best, P.N.; Heckman, T.M.  On the fundamental dichotomy in the local radio-AGN population: accretion, evolution and host galaxy properties.  MNRAS 2012, 421, 1569–1582, [arXiv:astro-ph.CO/1201.2397].  https://doi.org/10.1111/j.1365-2966.2012.20414.x.
  * Del Moro et al. (2013) Del Moro, A.; Alexander, D.M.; Mullaney, J.R.; Daddi, E.; Pannella, M.; Bauer, F.E.; Pope, A.; Dickinson, M.; Elbaz, D.; Barthel, P.D.; et al.  GOODS-Herschel: radio-excess signature of hidden AGN activity in distant star-forming galaxies.  A&A 2013, 549, A59, [arXiv:astro-ph.CO/1210.2521].  https://doi.org/10.1051/0004-6361/201219880.
  * Macfarlane et al. (2021) Macfarlane, C.; Best, P.N.; Sabater, J.; Gürkan, G.; Jarvis, M.J.; Röttgering, H.J.A.; Baldi, R.D.; Calistro Rivera, G.; Duncan, K.J.; Morabito, L.K.; et al.  The radio loudness of SDSS quasars from the LOFAR Two-metre Sky Survey: ubiquitous jet activity and constraints on star formation.  MNRAS 2021, 506, 5888–5907, [arXiv:astro-ph.GA/2107.09141].  https://doi.org/10.1093/mnras/stab1998.
  * Zakamska et al. (2004) Zakamska, N.L.; Strauss, M.A.; Heckman, T.M.; Ivezić, Ž.; Krolik, J.H.  Candidate Type II Quasars from the Sloan Digital Sky Survey. II. From Radio to X-Rays.  AJ 2004, 128, 1002–1016, [arXiv:astro-ph/astro-ph/0406248].  https://doi.org/10.1086/423220.
  * Kellermann et al. (2016) Kellermann, K.I.; Condon, J.J.; Kimball, A.E.; Perley, R.A.; Ivezić, Ž.  Radio-loud and Radio-quiet QSOs.  ApJ 2016, 831, 168, [arXiv:astro-ph.GA/1608.04586].  https://doi.org/10.3847/0004-637X/831/2/168.
  * Heckman (1980) Heckman, T.M.  An Optical and Radio Survey of the Nuclei of Bright Galaxies - Activity in the Normal Galactic Nuclei.  A&A 1980, 87, 152.
  * Flohic et al. (2006) Flohic, H.M.L.G.; Eracleous, M.; Chartas, G.; Shields, J.C.; Moran, E.C.  The Central Engines of 19 LINERs as Viewed by Chandra.  ApJ 2006, 647, 140–160, [arXiv:astro-ph/astro-ph/0604487].  https://doi.org/10.1086/505296.
  * Ho (2009) Ho, L.C.  Radiatively Inefficient Accretion in Nearby Galaxies.  ApJ 2009, 699, 626–637, [arXiv:astro-ph.GA/0906.4104].  https://doi.org/10.1088/0004-637X/699/1/626.
  * Nims et al. (2015) Nims, J.; Quataert, E.; Faucher-Giguère, C.A.  Observational signatures of galactic winds powered by active galactic nuclei.  MNRAS 2015, 447, 3612–3622, [arXiv:astro-ph.GA/1408.5141].  https://doi.org/10.1093/mnras/stu2648.
  * Panessa et al. (2019) Panessa, F.; Baldi, R.D.; Laor, A.; Padovani, P.; Behar, E.; McHardy, I.  The origin of radio emission from radio-quiet active galactic nuclei.  Nature Astronomy 2019, 3, 387–396, [arXiv:astro-ph.GA/1902.05917].  https://doi.org/10.1038/s41550-019-0765-4.
  * Morabito et al. (2022) Morabito, L.K.; Sweijen, F.; Radcliffe, J.F.; Best, P.N.; Kondapally, R.; Bondi, M.; Bonato, M.; Duncan, K.J.; Prandoni, I.; Shimwell, T.W.; et al.  Identifying active galactic nuclei via brightness temperature with sub-arcsecond international LOFAR telescope observations.  MNRAS 2022, 515, 5758–5774, [arXiv:astro-ph.GA/2207.13096].  https://doi.org/10.1093/mnras/stac2129.
  * Jarvis et al. (2021) Jarvis, M.E.; Harrison, C.M.; Mainieri, V.; Alexander, D.M.; Arrigoni Battaia, F.; Calistro Rivera, G.; Circosta, C.; Costa, T.; De Breuck, C.; Edge, A.C.; et al.  The quasar feedback survey: discovering hidden Radio-AGN and their connection to the host galaxy ionized gas.  MNRAS 2021, 503, 1780–1797, [arXiv:astro-ph.GA/2103.00014].  https://doi.org/10.1093/mnras/stab549.
  * Fischer et al. (2023) Fischer, T.C.; Johnson, M.C.; Secrest, N.J.; Crenshaw, D.M.; Kraemer, S.B.  No Small-scale Radio Jets Here: Multiepoch Observations of Radio Continuum Structures in NGC 1068 with the VLBA.  ApJ 2023, 953, 87, [arXiv:astro-ph.GA/2306.15047].  https://doi.org/10.3847/1538-4357/ace1f0.
  * Bicknell et al. (2018) Bicknell, G.V.; Mukherjee, D.; Wagner, A.Y.; Sutherland, R.S.; Nesvadba, N.P.H.  Relativistic jet feedback - II. Relationship to gigahertz peak spectrum and compact steep spectrum radio galaxies.  MNRAS 2018, 475, 3493–3501, [arXiv:astro-ph.GA/1801.06518].  https://doi.org/10.1093/mnras/sty070.
  * Meenakshi et al. (2022) Meenakshi, M.; Mukherjee, D.; Wagner, A.Y.; Nesvadba, N.P.H.; Bicknell, G.V.; Morganti, R.; Janssen, R.M.J.; Sutherland, R.S.; Mandal, A.  Modelling observable signatures of jet-ISM interaction: thermal emission and gas kinematics.  MNRAS 2022, 516, 766–786, [arXiv:astro-ph.GA/2203.10251].  https://doi.org/10.1093/mnras/stac2251.
  * Sijacki et al. (2007) Sijacki, D.; Springel, V.; Di Matteo, T.; Hernquist, L.  A unified model for AGN feedback in cosmological simulations of structure formation.  MNRAS 2007, 380, 877–900, [arXiv:astro-ph/0705.2238].  https://doi.org/10.1111/j.1365-2966.2007.12153.x.
  * Hopkins et al. (2006) Hopkins, P.F.; Hernquist, L.; Cox, T.J.; Di Matteo, T.; Robertson, B.; Springel, V.  A Unified, Merger-driven Model of the Origin of Starbursts, Quasars, the Cosmic X-Ray Background, Supermassive Black Holes, and Galaxy Spheroids.  ApJS 2006, 163, 1–49, [arXiv:astro-ph/astro-ph/0506398].  https://doi.org/10.1086/499298.
  * Dubois et al. (2010) Dubois, Y.; Devriendt, J.; Slyz, A.; Teyssier, R.  Jet-regulated cooling catastrophe.  MNRAS 2010, 409, 985–1001, [arXiv:astro-ph.CO/1004.1851].  https://doi.org/10.1111/j.1365-2966.2010.17338.x.
  * Bower et al. (2012) Bower, R.G.; Benson, A.J.; Crain, R.A.  What shapes the galaxy mass function? Exploring the roles of supernova-driven winds and active galactic nuclei.  MNRAS 2012, 422, 2816–2840, [arXiv:astro-ph.CO/1112.2712].  https://doi.org/10.1111/j.1365-2966.2012.20516.x.
  * Oppenheimer et al. (2020) Oppenheimer, B.D.; Davies, J.J.; Crain, R.A.; Wijers, N.A.; Schaye, J.; Werk, J.K.; Burchett, J.N.; Trayford, J.W.; Horton, R.  Feedback from supermassive black holes transforms centrals into passive galaxies by ejecting circumgalactic gas.  MNRAS 2020, 491, 2939–2952, [arXiv:astro-ph.GA/1904.05904].  https://doi.org/10.1093/mnras/stz3124.
  * Cicone et al. (2021) Cicone, C.; Mainieri, V.; Circosta, C.; Kakkad, D.; Vietri, G.; Perna, M.; Bischetti, M.; Carniani, S.; Cresci, G.; Harrison, C.; et al.  SUPER. VI. A giant molecular halo around a z$\sim$2 quasar.  A&A 2021, 654, L8, [arXiv:astro-ph.GA/2109.02269].  https://doi.org/10.1051/0004-6361/202141611.
  * Audibert et al. (2023) Audibert, A.; Ramos Almeida, C.; García-Burillo, S.; Combes, F.; Bischetti, M.; Meenakshi, M.; Mukherjee, D.; Bicknell, G.; Wagner, A.Y.  Jet-induced molecular gas excitation and turbulence in the Teacup.  A&A 2023, 671, L12, [arXiv:astro-ph.GA/2302.13884].  https://doi.org/10.1051/0004-6361/202345964.
  * Longinotti et al. (2013) Longinotti, A.L.; Krongold, Y.; Kriss, G.A.; Ely, J.; Gallo, L.; Grupe, D.; Komossa, S.; Mathur, S.; Pradhan, A.  The Rise of an Ionized Wind in the Narrow-line Seyfert 1 Galaxy Mrk 335 Observed by XMM-Newton and HST.  ApJ 2013, 766, 104, [arXiv:astro-ph.CO/1301.5463].  https://doi.org/10.1088/0004-637X/766/2/104.
  * Tombesi et al. (2013) Tombesi, F.; Cappi, M.; Reeves, J.N.; Nemmen, R.S.; Braito, V.; Gaspari, M.; Reynolds, C.S.  Unification of X-ray winds in Seyfert galaxies: from ultra-fast outflows to warm absorbers.  MNRAS 2013, 430, 1102–1117, [arXiv:astro-ph.HE/1212.4851].  https://doi.org/10.1093/mnras/sts692.
  * Chartas et al. (2021) Chartas, G.; Cappi, M.; Vignali, C.; Dadina, M.; James, V.; Lanzuisi, G.; Giustini, M.; Gaspari, M.; Strickland, S.; Bertola, E.  Multiphase Powerful Outflows Detected in High-z Quasars.  ApJ 2021, 920, 24, [arXiv:astro-ph.GA/2106.14907].  https://doi.org/10.3847/1538-4357/ac0ef2.
  * Murray and Chiang (1995) Murray, N.; Chiang, J.  Active Galactic Nuclei Disk Winds, Absorption Lines, and Warm Absorbers.  ApJ 1995, 454, L105.  https://doi.org/10.1086/309775.
  * Sulentic et al. (2007) Sulentic, J.W.; Bachev, R.; Marziani, P.; Negrete, C.A.; Dultzin, D.  C IV $\lambda$1549 as an Eigenvector 1 Parameter for Active Galactic Nuclei.  ApJ 2007, 666, 757–777, [arXiv:astro-ph/0705.1895].  https://doi.org/10.1086/519916.
  * Coil et al. (2011) Coil, A.L.; Weiner, B.J.; Holz, D.E.; Cooper, M.C.; Yan, R.; Aird, J.  Outflowing Galactic Winds in Post-starburst and Active Galactic Nucleus Host Galaxies at 0.2 < z < 0.8.  ApJ 2011, 743, 46, [arXiv:astro-ph.CO/1104.0681].  https://doi.org/10.1088/0004-637X/743/1/46.
  * Martin et al. (2015) Martin, C.L.; Dijkstra, M.; Henry, A.; Soto, K.T.; Danforth, C.W.; Wong, J.  The Ly$\alpha$ Line Profiles of Ultraluminous Infrared Galaxies: Fast Winds and Lyman Continuum Leakage.  ApJ 2015, 803, 6, [arXiv:astro-ph.GA/1501.05946].  https://doi.org/10.1088/0004-637X/803/1/6.
  * Harrison et al. (2014) Harrison, C.M.; Alexander, D.M.; Mullaney, J.R.; Swinbank, A.M.  Kiloparsec-scale outflows are prevalent among luminous AGN: outflows and feedback in the context of the overall AGN population.  MNRAS 2014, 441, 3306–3347, [arXiv:astro-ph.GA/1403.3086].  https://doi.org/10.1093/mnras/stu515.
  * Villar-Martín et al. (2016) Villar-Martín, M.; Arribas, S.; Emonts, B.; Humphrey, A.; Tadhunter, C.; Bessiere, P.; Cabrera Lavers, A.; Ramos Almeida, C.  Ionized outflows in luminous type 2 AGNs at z < 0.6: no evidence for significant impact on the host galaxies.  MNRAS 2016, 460, 130–162, [arXiv:astro-ph.GA/1604.04577].  https://doi.org/10.1093/mnras/stw901.
  * Förster Schreiber et al. (2014) Förster Schreiber, N.M.; Genzel, R.; Newman, S.F.; Kurk, J.D.; Lutz, D.; Tacconi, L.J.; Wuyts, S.; Bandara, K.; Burkert, A.; Buschkamp, P.; et al.  The Sins/zC-Sinf Survey of z ~2 Galaxy Kinematics: Evidence for Powerful Active Galactic Nucleus-Driven Nuclear Outflows in Massive Star-Forming Galaxies.  ApJ 2014, 787, 38, [arXiv:astro-ph.CO/1311.2596].  https://doi.org/10.1088/0004-637X/787/1/38.
  * Förster Schreiber et al. (2019) Förster Schreiber, N.M.; Übler, H.; Davies, R.L.; Genzel, R.; Wisnioski, E.; Belli, S.; Shimizu, T.; Lutz, D.; Fossati, M.; Herrera-Camus, R.; et al.  The KMOS3D Survey: Demographics and Properties of Galactic Outflows at z = 0.6-2.7.  ApJ 2019, 875, 21, [arXiv:astro-ph.GA/1807.04738].  https://doi.org/10.3847/1538-4357/ab0ca2.
  * Rose et al. (2018) Rose, M.; Tadhunter, C.; Ramos Almeida, C.; Rodríguez Zaurín, J.; Santoro, F.; Spence, R.  Quantifying the AGN-driven outflows in ULIRGs (QUADROS)–I: VLT/Xshooter observations of nine nearby objects.  Monthly Notices of the Royal Astronomical Society 2018, 474, 128–156.
  * Scholtz et al. (2018) Scholtz, J.; Alexander, D.M.; Harrison, C.M.; Rosario, D.J.; McAlpine, S.; Mullaney, J.R.; Stanley, F.; Simpson, J.; Theuns, T.; Bower, R.G.; et al.  Identifying the subtle signatures of feedback from distant AGN using ALMA observations and the EAGLE hydrodynamical simulations.  MNRAS 2018, 475, 1288–1305.  https://doi.org/10.1093/mnras/stx3177.
  * Scholtz et al. (2020) Scholtz, J.; Harrison, C.M.; Rosario, D.J.; Alexander, D.M.; Chen, C.C.; Kakkad, D.; Mainieri, V.; Tiley, A.L.; Turner, O.; Cirasuolo, M.; et al.  KASHz: No evidence for ionised outflows instantaneously suppressing star formation in moderate luminosity AGN at z $\sim$ 1.4-2.6.  MNRAS 2020, 492, 3194–3216, [arXiv:astro-ph.GA/2001.02242].  https://doi.org/10.1093/mnras/staa030.
  * Rupke and Veilleux (2013) Rupke, D.S.N.; Veilleux, S.  Breaking the Obscuring Screen: A Resolved Molecular Outflow in a Buried QSO.  ApJ 2013, 775, L15, [arXiv:astro-ph.CO/1308.4988].  https://doi.org/10.1088/2041-8205/775/1/L15.
  * Ramos Almeida et al. (2019) Ramos Almeida, C.; Acosta-Pulido, J.A.; Tadhunter, C.N.; González-Fernández, C.; Cicone, C.; Fernández-Torreiro, M.  A near-infrared study of the multiphase outflow in the type-2 quasar J1509+0434.  MNRAS 2019, 487, L18–L23, [arXiv:astro-ph.GA/1905.06288].  https://doi.org/10.1093/mnrasl/slz072.
  * Speranza et al. (2022) Speranza, G.; Ramos Almeida, C.; Acosta-Pulido, J.A.; Riffel, R.A.; Tadhunter, C.; Pierce, J.C.S.; Rodríguez-Ardila, A.; Coloma Puga, M.; Brusa, M.; Musiimenta, B.; et al.  Warm molecular and ionized gas kinematics in the type-2 quasar J0945+1737.  A&A 2022, 665, A55, [arXiv:astro-ph.GA/2206.15347].  https://doi.org/10.1051/0004-6361/202243585.
  * Riffel et al. (2023) Riffel, R.A.; Storchi-Bergmann, T.; Riffel, R.; Bianchin, M.; Zakamska, N.L.; Ruschel-Dutra, D.; Bentz, M.C.; Burtscher, L.; Crenshaw, D.M.; Dahmer-Hahn, L.G.; et al.  The AGNIFS survey: spatially resolved observations of hot molecular and ionized outflows in nearby active galaxies.  MNRAS 2023, 521, 1832–1848, [arXiv:astro-ph.GA/2302.11324].  https://doi.org/10.1093/mnras/stad599.
  * Morganti et al. (2005) Morganti, R.; Tadhunter, C.N.; Oosterloo, T.A.  Fast neutral outflows in powerful radio galaxies: a major source of feedback in massive galaxies.  A&A 2005, 444, L9–L13, [arXiv:astro-ph/astro-ph/0510263].  https://doi.org/10.1051/0004-6361:200500197.
  * Morganti et al. (2016) Morganti, R.; Veilleux, S.; Oosterloo, T.; Teng, S.H.; Rupke, D.  Another piece of the puzzle: The fast H I outflow in Mrk 231.  A&A 2016, 593, A30, [arXiv:astro-ph.GA/1606.01640].  https://doi.org/10.1051/0004-6361/201628978.
  * Rupke et al. (2005) Rupke, D.S.; Veilleux, S.; Sanders, D.B.  Outflows in Active Galactic Nucleus/Starburst-Composite Ultraluminous Infrared Galaxies1,.  ApJ 2005, 632, 751–780, [arXiv:astro-ph/astro-ph/0507037].  https://doi.org/10.1086/444451.
  * Cazzoli et al. (2016) Cazzoli, S.; Arribas, S.; Maiolino, R.; Colina, L.  Neutral gas outflows in nearby [U]LIRGs via optical NaD feature.  A&A 2016, 590, A125, [arXiv:astro-ph.GA/1602.08505].  https://doi.org/10.1051/0004-6361/201526788.
  * Concas et al. (2019) Concas, A.; Popesso, P.; Brusa, M.; Mainieri, V.; Thomas, D.  Two-face(s): ionized and neutral gas winds in the local Universe.  A&A 2019, 622, A188, [arXiv:astro-ph.GA/1710.08423].  https://doi.org/10.1051/0004-6361/201732152.
  * Maiolino et al. (2012) Maiolino, R.; Gallerani, S.; Neri, R.; Cicone, C.; Ferrara, A.; Genzel, R.; Lutz, D.; Sturm, E.; Tacconi, L.J.; Walter, F.; et al.  Evidence of strong quasar feedback in the early Universe.  MNRAS 2012, 425, L66–L70, [arXiv:astro-ph.CO/1204.2904].  https://doi.org/10.1111/j.1745-3933.2012.01303.x.
  * Bischetti et al. (2019) Bischetti, M.; Maiolino, R.; Carniani, S.; Fiore, F.; Piconcelli, E.; Fluetsch, A.  Widespread QSO-driven outflows in the early Universe.  A&A 2019, 630, A59, [arXiv:astro-ph.GA/1806.00786].  https://doi.org/10.1051/0004-6361/201833557.
  * Dasyra and Combes (2011) Dasyra, K.M.; Combes, F.  Turbulent and fast motions of H2 gas in active galactic nuclei.  A&A 2011, 533, L10, [arXiv:astro-ph.CO/1108.2888].  https://doi.org/10.1051/0004-6361/201117730.
  * Riffel et al. (2020) Riffel, R.A.; Zakamska, N.L.; Riffel, R.  Active galactic nuclei winds as the origin of the H2 emission excess in nearby galaxies.  MNRAS 2020, 491, 1518–1529, [arXiv:astro-ph.GA/1909.11742].  https://doi.org/10.1093/mnras/stz3137.
  * Sturm et al. (2011) Sturm, E.; González-Alfonso, E.; Veilleux, S.; Fischer, J.; Graciá-Carpio, J.; Hailey-Dunsheath, S.; Contursi, A.; Poglitsch, A.; Sternberg, A.; Davies, R.; et al.  Massive Molecular Outflows and Negative Feedback in ULIRGs Observed by Herschel-PACS.  ApJ 2011, 733, L16, [arXiv:astro-ph.CO/1105.1731].  https://doi.org/10.1088/2041-8205/733/1/L16.
  * Veilleux et al. (2013) Veilleux, S.; Meléndez, M.; Sturm, E.; Gracia-Carpio, J.; Fischer, J.; González-Alfonso, E.; Contursi, A.; Lutz, D.; Poglitsch, A.; Davies, R.; et al.  Fast Molecular Outflows in Luminous Galaxy Mergers: Evidence for Quasar Feedback from Herschel.  ApJ 2013, 776, 27, [arXiv:astro-ph.CO/1308.3139].  https://doi.org/10.1088/0004-637X/776/1/27.
  * Spoon et al. (2013) Spoon, H.W.W.; Farrah, D.; Lebouteiller, V.; González-Alfonso, E.; Bernard-Salas, J.; Urrutia, T.; Rigopoulou, D.; Westmoquette, M.S.; Smith, H.A.; Afonso, J.; et al.  Diagnostics of AGN-Driven Molecular Outflows in ULIRGs from Herschel-PACS Observations of OH at 119 $\mu$m.  ApJ 2013, 775, 127, [arXiv:astro-ph.CO/1307.6224].  https://doi.org/10.1088/0004-637X/775/2/127.
  * González-Alfonso et al. (2017) González-Alfonso, E.; Fischer, J.; Spoon, H.W.W.; Stewart, K.P.; Ashby, M.L.N.; Veilleux, S.; Smith, H.A.; Sturm, E.; Farrah, D.; Falstad, N.; et al.  Molecular Outflows in Local ULIRGs: Energetics from Multitransition OH Analysis.  ApJ 2017, 836, 11, [arXiv:astro-ph.GA/1612.08181].  https://doi.org/10.3847/1538-4357/836/1/11.
  * Feruglio et al. (2010) Feruglio, C.; Maiolino, R.; Piconcelli, E.; Menci, N.; Aussel, H.; Lamastra, A.; Fiore, F.  Quasar feedback revealed by giant molecular outflows.  A&A 2010, 518, L155, [arXiv:astro-ph.CO/1006.1655].  https://doi.org/10.1051/0004-6361/201015164.
  * Cicone et al. (2014) Cicone, C.; Maiolino, R.; Sturm, E.; Graciá-Carpio, J.; Feruglio, C.; Neri, R.; Aalto, S.; Davies, R.; Fiore, F.; Fischer, J.; et al.  Massive molecular outflows and evidence for AGN feedback from CO observations.  A&A 2014, 562, A21, [arXiv:astro-ph.CO/1311.2595].  https://doi.org/10.1051/0004-6361/201322464.
  * Pereira-Santaella et al. (2018) Pereira-Santaella, M.; Colina, L.; García-Burillo, S.; Combes, F.; Emonts, B.; Aalto, S.; Alonso-Herrero, A.; Arribas, S.; Henkel, C.; Labiano, A.; et al.  Spatially resolved cold molecular outflows in ULIRGs.  A&A 2018, 616, A171, [arXiv:astro-ph.GA/1805.03667].  https://doi.org/10.1051/0004-6361/201833089.
  * Fluetsch et al. (2019) Fluetsch, A.; Maiolino, R.; Carniani, S.; Marconi, A.; Cicone, C.; Bourne, M.A.; Costa, T.; Fabian, A.C.; Ishibashi, W.; Venturi, G.  Cold molecular outflows in the local Universe and their feedback effect on galaxies.  MNRAS 2019, 483, 4586–4614, [arXiv:astro-ph.GA/1805.05352].  https://doi.org/10.1093/mnras/sty3449.
  * Lamperti et al. (2022) Lamperti, I.; Pereira-Santaella, M.; Perna, M.; Colina, L.; Arribas, S.; García-Burillo, S.; González-Alfonso, E.; Aalto, S.; Alonso-Herrero, A.; Combes, F.; et al.  Physics of ULIRGs with MUSE and ALMA: The PUMA project. IV. No tight relation between cold molecular outflow rates and AGN luminosities.  A&A 2022, 668, A45, [arXiv:astro-ph.GA/2209.03380].  https://doi.org/10.1051/0004-6361/202244054.
  * Ramos Almeida et al. (2022) Ramos Almeida, C.; Bischetti, M.; García-Burillo, S.; Alonso-Herrero, A.; Audibert, A.; Cicone, C.; Feruglio, C.; Tadhunter, C.N.; Pierce, J.C.S.; Pereira-Santaella, M.; et al.  The diverse cold molecular gas contents, morphologies, and kinematics of type-2 quasars as seen by ALMA.  A&A 2022, 658, A155, [arXiv:astro-ph.GA/2111.13578].  https://doi.org/10.1051/0004-6361/202141906.
  * Scholtz et al. (2023) Scholtz, J.; Maiolino, R.; Jones, G.C.; Carniani, S.  Evidence of extended cold molecular gas and dust haloes around z 2.3 extremely red quasars with ALMA.  MNRAS 2023, 519, 5246–5262, [arXiv:astro-ph.GA/2212.03270].  https://doi.org/10.1093/mnras/stac3787.
  * Cicone et al. (2018) Cicone, C.; Brusa, M.; Ramos Almeida, C.; Cresci, G.; Husemann, B.; Mainieri, V.  The largely unconstrained multiphase nature of outflows in AGN host galaxies.  Nature Astronomy 2018, 2, 176–178, [arXiv:astro-ph.GA/1802.10308].  https://doi.org/10.1038/s41550-018-0406-3.
  * Rupke et al. (2017) Rupke, D.S.N.; Gültekin, K.; Veilleux, S.  Quasar-mode Feedback in Nearby Type 1 Quasars: Ubiquitous Kiloparsec-scale Outflows and Correlations with Black Hole Properties.  ApJ 2017, 850, 40, [arXiv:astro-ph.GA/1708.05139].  https://doi.org/10.3847/1538-4357/aa94d1.
  * Fluetsch et al. (2021) Fluetsch, A.; Maiolino, R.; Carniani, S.; Arribas, S.; Belfiore, F.; Bellocchi, E.; Cazzoli, S.; Cicone, C.; Cresci, G.; Fabian, A.C.; et al.  Properties of the multiphase outflows in local (ultra)luminous infrared galaxies.  MNRAS 2021, 505, 5753–5783, [arXiv:astro-ph.GA/2006.13232].  https://doi.org/10.1093/mnras/stab1666.
  * Speranza et al. (2024) Speranza, G.; Ramos Almeida, C.; Acosta-Pulido, J.A.; Audibert, A.; Holden, L.R.; Tadhunter, C.N.; Lapi, A.; González-Martín, O.; Brusa, M.; López, I.E.; et al.  Multiphase characterization of AGN winds in five local type-2 quasars.  A&A 2024, 681, A63, [arXiv:astro-ph.GA/2311.10132].  https://doi.org/10.1051/0004-6361/202347715.
  * Nesvadba et al. (2008) Nesvadba, N.P.H.; Lehnert, M.D.; De Breuck, C.; Gilbert, A.M.; van Breugel, W.  Evidence for powerful AGN winds at high redshift: dynamics of galactic outflows in radio galaxies during the “Quasar Era”.  A&A 2008, 491, 407–424, [arXiv:astro-ph/0809.5171].  https://doi.org/10.1051/0004-6361:200810346.
  * Carniani et al. (2015) Carniani, S.; Marconi, A.; Maiolino, R.; Balmaverde, B.; Brusa, M.; Cano-Díaz, M.; Cicone, C.; Comastri, A.; Cresci, G.; Fiore, F.; et al.  Ionised outflows in z ~2.4 quasar host galaxies.  A&A 2015, 580, A102, [arXiv:astro-ph.GA/1506.03096].  https://doi.org/10.1051/0004-6361/201526557.
  * Kakkad et al. (2020) Kakkad, D.; Mainieri, V.; Vietri, G.; Carniani, S.; Harrison, C.M.; Perna, M.; Scholtz, J.; Circosta, C.; Cresci, G.; Husemann, B.; et al.  SUPER. II. Spatially resolved ionised gas kinematics and scaling relations in z $\sim$ 2 AGN host galaxies.  A&A 2020, 642, A147, [arXiv:astro-ph.GA/2008.01728].  https://doi.org/10.1051/0004-6361/202038551.
  * Vayner et al. (2021) Vayner, A.; Zakamska, N.L.; Riffel, R.A.; Alexandroff, R.; Cosens, M.; Hamann, F.; Perrotta, S.; Rupke, D.S.N.; Bergmann, T.S.; Veilleux, S.; et al.  Powerful winds in high-redshift obscured and red quasars.  MNRAS 2021, 504, 4445–4459, [arXiv:astro-ph.GA/2101.04688].  https://doi.org/10.1093/mnras/stab1176.
  * Concas et al. (2022) Concas, A.; Maiolino, R.; Curti, M.; Hayden-Pawson, C.; Cirasuolo, M.; Jones, G.C.; Mercurio, A.; Belfiore, F.; Cresci, G.; Cullen, F.; et al.  Being KLEVER at cosmic noon: Ionized gas outflows are inconspicuous in low-mass star-forming galaxies but prominent in massive AGN hosts.  MNRAS 2022, 513, 2535–2562, [arXiv:astro-ph.GA/2203.11958].  https://doi.org/10.1093/mnras/stac1026.