# SUPER VII. Morphology and Kinematics of H$\alpha$ emission in AGN host
galaxies at Cosmic noon using SINFONI

D. Kakkad1,2,3, V. Mainieri4, G. Vietri5,6, I. Lamperti7, S. Carniani8, G.
Cresci9, C. Harrison10, A. Marconi9,11, M. Bischetti12,13, C. Cicone14, C.
Circosta15,16, B. Husemann17, A. Man18,19, F. Mannucci9, H. Netzer20, P.
Padovani4,21, M. Perna7,9, A. Puglisi22, J. Scholtz23,24, G. Tozzi11,9, C.
Vignali25,26, L. Zappacosta5
1Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD
21218, USA
2European Southern Observatory, Alonso de Cordova 3107, Vitacura, Casilla
19001, Santiago de Chile, Chile
3Department of Physics, University of Oxford, Denys Wilkinson Building, Keble
Road, Oxford, OX1 3RH, UK
4European Southern Observatory, Karl-Schwarzschild-Strasse 2, Garching bei
München, Germany
5INAF - Osservatorio Astronomico di Roma, Via Frascati 33, 00040, Monte Porzio
Catone, Italy
6INAF - Istituto di Astrofisica Spaziale e Fisica Cosmica Milano, Via A. Corti
12, 20133, Milano, Italy
7Centro de Astrobiología (CAB), CSIC–INTA, Ctra. de Ajalvir Km. 4, 28850
Torrejón de Ardoz, Madrid, Spain
8Scuola Normale Superiore, Piazza dei Cavalieri 7, I-56126 Pisa, Italy
9INAF - Osservatorio Astrofisico di Arcetri, Largo E. Fermi 5, 50125, Firenze,
Italy
10School of Mathematics, Statistics and Physics, Newcastle University,
Newcastle upon Tyne, NE1 7RU, UK
11Dipartimento di Fisica e Astronomia, Universitá di Firenze, Via G. Sansone
1, Sesto Fiorentino, 50019, Firenze, Italy
12Dipartimento di Fisica, Universitá di Trieste, Sezione di Astronomia, Via
G.B. Tiepolo 11, I-34131 Trieste, Italy
13INAF - Osservatorio Astronomico di Trieste, Via G. Tiepolo 11, I-34143
Trieste, Italy
14Institute of Theoretical Astrophysics, University of Oslo, PO Box 1029,
Blindern 0315, Oslo, Norway
15Department of Physics & Astronomy, University College London, Gower Street,
London, WC1E 6BT, UK
16European Space Agency (ESA), European Space Astronomy Centre (ESAC), Camino
Bajo del Castillo s/n, 28692 Villanueva de la Cañada, Madrid, Spain
17Max-Planck-Institut für Astronomie, Königstuhl 17, D-69117 Heidelberg,
Germany
18Dunlap Institute for Astronomy and Astrophysics, University of Toronto, 50
St George Street, Toronto ON, M5S 3H4, Canada
19Department of Physics & Astronomy, University of British Columbia, 6224
Agricultural Road, Vancouver, BC V6T 1Z1, Canada
20School of Physics and Astronomy, Tel-Aviv University, Tel Aviv 69978, Israel
21Affiliated to INAF-Osservatorio di Astrofisica e Scienza dello Spazio, Via
Piero Gobetti 93/3, I-40129 Bologna, Italy
22Centre for Extragalactic Astronomy, Department of Physics, Durham
University, South Road, Durham, DH1 3LE, UK
23Kavli Institute for Cosmology, University of Cambridge, Madingley Road,
Cambridge, CB3 0HA, UK
24Cavendish Laboratory - Astrophysics Group, University of Cambridge, 19 JJ
Thompson Avenue, Cambridge, CB3 0HE, UK
25Dipartimento di Fisica e Astronomia "Augusto Righi", Universitá degli Studi
di Bologna, via P. Gobetti 93/2, 40129 Bologna, Italy
26INAF-Osservatorio di Astrofisica e Scienza dello Spazio di Bologna, Via
Piero Gobetti, 93/3, I-40129, Bologna
E-mail<EMAIL_ADDRESS>
(Accepted XXX. Received YYY; in original form ZZZ)

###### Abstract

We present spatially resolved H$\alpha$ properties of 21 type 1 AGN host
galaxies at z$\sim$2 derived from the SUPER survey. These targets were
observed with the adaptive optics capabilities of the SINFONI spectrograph, a
near-infrared integral field spectrograph, that provided a median spatial
resolution of 0.3″ ($\sim$2 kpc). We model the H$\alpha$ emission line profile
in each pixel to investigate whether it traces gas in the narrow line region
or if it is associated with star formation. To do this, we first investigate
the presence of resolved H$\alpha$ emission by removing the contribution of
the AGN PSF. We find extended H$\alpha$ emission in sixteen out of the 21 type
1 AGN host galaxies (76%). Based on the BPT diagnostics, optical line flux
ratios and the line widths (FWHM), we show that the H$\alpha$ emission in five
galaxies is ionised by the AGN (30%), in four galaxies by star formation (25%)
and for the rest (45%), the ionisation source is unconstrained. Two galaxies
show extended H$\alpha$ FWHM $>$600 km/s, which is interpreted as a part of an
AGN-driven outflow. Morphological and kinematic maps of H$\alpha$ emission in
targets with sufficient signal-to-noise ratio suggest the presence of
rotationally supported disks in six galaxies and possible presence of
companions in four galaxies. In two galaxies, we find an anti-correlation
between the locations of extended H$\alpha$ emission and [O iii]-based ionised
outflows, indicating possible negative feedback at play. However, in the
majority of galaxies, we do not find evidence of outflows impacting H$\alpha$
based star formation.

###### keywords:

galaxies:active – galaxies:high-redshift – galaxies:kinematics and dynamics –
(galaxies:) quasars:supermassive black holes – galaxies:star formation –
galaxies:evolution

††pubyear: 2021††pagerange: SUPER VII. Morphology and Kinematics of H$\alpha$
emission in AGN host galaxies at Cosmic noon using SINFONI–14

##  1 Introduction

The conventional $\Lambda$ cold dark matter ($\Lambda$CDM) paradigm supports a
hierarchical growth of objects i.e., smaller objects are formed first, then
they merge successively into larger bodies. Within this picture, stars and
galaxies are formed when baryons fall into dark matter potential wells,
resulting in shocks followed by radiative cooling of gas (e.g., White & Rees,
1978; Hopkins & Beacom, 2006). Although this paradigm had initial success to
describe a cosmological model for galaxy evolution, feedback processes needed
to be invoked to regulate the formation of stars in the interstellar medium
(ISM). One of the prominent sources of feedback in massive galaxies comes from
the centrally located supermassive black holes (e.g., Kormendy & Richstone,
1995; Richstone et al., 1998; Silk & Rees, 1998).

Models predict that the feedback from these black holes is a result of radio
jets and/or radiation pressure driven winds from the accretion of gas and dust
from the ISM (e.g., Soltan, 1982; Yu & Tremaine, 2002; Fabian, 2012). During
the accretion process, the luminosity of these black holes, also called active
galactic nuclei (AGN) at this stage, can outshine the overall luminosity of
the host galaxy itself. The net effect of these winds could be to relocate or
eject cold molecular gas from the galaxy, dissociate or heat this gas and/or
possibly prevent the inflow of gas from the halo into the ISM. Feedback
processes from both star formation and AGN are largely used in state-of-the-
art cosmological simulations (e.g., Springel, 2005; Hirschmann et al., 2014;
Vogelsberger et al., 2014; Schaye et al., 2015; Steinborn et al., 2015; Dubois
et al., 2016; Pillepich et al., 2018). An indirect manifestation of the
influence that the AGN has on the growth history of its host galaxy is
represented by the observed AGN-galaxy correlations, such as the black hole
mass versus the stellar velocity dispersion ($M_{\rm BH}-\sigma$) and the
black hole mass and bulge mass relation ($M_{\rm BH}-M_{\rm bulge}$) (e.g.,
Gebhardt et al., 2000; Gültekin et al., 2009; Caglar et al., 2020).

Spectroscopic observations of AGN host galaxies over the past decades have
revealed the ubiquitous presence of fast outflows with speeds $>$1000 km s-1
in multiple gas phases across a wide range of redshifts (e.g., Greene et al.,
2011; Venturi et al., 2018; Rojas et al., 2020; Perna et al., 2021; Puglisi et
al., 2021; Ramos Almeida et al., 2021; Tozzi et al., 2021; Gatkine et al.,
2022). Several studies found that these outflows are either driven by the AGN
or star formation, based on the presence of correlations between the outflow
and AGN or host galaxy properties (e.g., Carniani et al., 2015; Fiore et al.,
2017; Fluetsch et al., 2019; Kakkad et al., 2022). However, there are also
studies with different samples that report the absence of such scaling
relations (e.g., Davies et al., 2020; Baron et al., 2020).

To investigate the feedback effects generated by these outflows, we can study
direct or indirect tracers of the host galaxy’s molecular gas supply and/or
star formation. Several studies in the literature have investigated the
overall content and distribution of cold molecular gas with some results
suggesting a systematic difference in the molecular gas fractions between AGN
and non-AGN galaxies (e.g., Brusa et al., 2018; Kakkad et al., 2017; Circosta
et al., 2021; Ellison et al., 2021), while several others (mostly at low
redshift) do not find the same result (e.g., Husemann et al., 2017; Rosario et
al., 2018; Jarvis et al., 2020; Koss et al., 2021). The molecular gas
observations described above have the limitation that the results are mostly
based on individual tracers (such as CO(2-1)), which can give an incomplete
view into the ISM because the molecular gas itself can exist in multiple
phases or can be traced via different excitation levels of CO. Furthermore,
most of these studies do not spatially resolve the molecular gas as the CO
measurements are obtained from integrated apertures. Lastly, the apertures of
extraction are not always uniform which leads to conflicting results in the
literature.

Whether the outflows from the AGN have an impact on the host galaxy or not can
also be revealed by investigating their impact on star formation (see review
by Harrison et al. (2018) and references therein). Cosmological simulations
predict a diverse set of scenarios where the star formation is regulated by
the AGN, which may not result in an obvious observational signature of this
feedback effect on the host galaxies of the AGN population (e.g., Ward et al.,
2022). We briefly mention some examples here and we refer the reader to the
references for further details. Using RAMSES-RT code, Costa et al. (2018) show
that the outflows have the possibility to quench overall star formation (see
also Dubois et al., 2013; Beckmann et al., 2017). Similar results are obtained
in other suite of codes where the outflows have been shown to prevent the
formation of new stars rather than shutting down ongoing star formation as a
mechanism of quenching (e.g., Pillepich et al., 2018). On the other hand,
Zubovas et al. (2013a) shows that it is possible even for stars to be ejected
from the host galaxies, when dense shells formed due to the shocks and
compression from impact of AGN outflows form stars along a radial trajectory.
Such pressure-regulated star formation has been reported in several
theoretical studies and high resolution hydrodynamical simulations (e.g.,
Ishibashi & Fabian, 2012; Silk, 2013; Zubovas et al., 2013b; Dugan et al.,
2014; Bieri et al., 2016). The burst of star formation is then followed by a
period of quenching. Therefore, the AGN outflows could have the simultaneous
capability of both suppressing and enhancing star formation (e.g., Zubovas &
Bourne, 2017). We also note that some of the results from the literature also
report conditions where these outflows show limited impact of AGN feedback on
the gas and star formation in the disk (e.g., Gabor & Bournaud, 2014; Roos et
al., 2015). In summary, simulations predict several possible scenarios on the
impact of outflows on star formation and that there is no universal answer to
how exactly AGN feedback regulates star formation for each galaxy.

The results from theory and simulations reported above can perhaps explain the
diversity in the results, and often conflicting ones, from an observational
perspective (see review on positive and negative feedback in AGN host galaxies
Cresci & Maiolino, 2018). Gas ejection by AGN winds or star formation
quenching in AGN host galaxies has been reported in several low redshift and
high redshift galaxies (e.g., Cano-Díaz et al., 2012; Alatalo et al., 2015;
Guillard et al., 2015; Carniani et al., 2016; Baron et al., 2018; George et
al., 2019). Similar to the predictions made in Pillepich et al. (2018), using
VLT/XSHOOTER and ALMA observations of a z$\sim$2.5 massive radio galaxy, Man
et al. (2019) reported that most of the molecular gas is consumed by stars,
followed by the removal of residual gas by the AGN. On the other hand,
positive feedback has also been observed in the extragalactic sources,
including dwarf galaxies (e.g., Gaibler et al., 2012; Rauch et al., 2013;
Salomé et al., 2015; Maiolino et al., 2017; Gallagher et al., 2019; Nesvadba
et al., 2020; Perna et al., 2020; Bessiere & Ramos Almeida, 2022; Schutte &
Reines, 2022), with some targets that show a simultaneous presence of positive
and negative feedback via spatially resolved integral field spectroscopic
observations at rest-frame optical wavelengths (e.g., Cresci et al., 2015;
Shin et al., 2019). Not all AGN host galaxies with outflows show the impact of
star formation suppression or enhancement, especially when accounting for
studies that make use of integrated spectra (i.e., a global outlook into the
outflows versus star formation paradigm Balmaverde et al., 2016) or when
considering dust obscured star formation (e.g., Scholtz et al., 2020, 2021;
Lamperti et al., 2021). Indeed, the presence of negative or positive feedback
in AGN depends upon the conditions of the ISM, outflows and/or jet power
(e.g., Kalfountzou et al., 2017), which could also explain the diverse sets of
results reported in the literature on the observational front.

Lastly, star formation itself can be calculated via multiple methods, each
tracing different time scales of star formation (e.g., Kennicutt, 1998;
Battisti et al., 2015; Boquien et al., 2015; Catalán-Torrecilla et al., 2015;
Xie & Ho, 2019; Calzetti, 2020; Michiyama et al., 2020; Kim et al., 2022;
Vietri et al., 2022). Furthermore, the results may further change depending on
whether spatially resolved or integrated spectral measurements were made. For
instance, star formation rate (SFR) calculated from the rest-frame ultraviolet
wavelengths probe direct stellar light, while SFR calculated from the far-
infrared wavelengths probes stellar light reprocessed by the dust (e.g.,
Shivaei et al., 2016). In the examples mentioned above, H$\alpha$ is often
used as a star formation tracer for many extra-galactic studies. Although the
H$\alpha$ line might be a reliable tracer in normal star forming galaxies
across a wide range of redshifts, in the AGN host galaxies, there is a
possibility of contamination by the AGN ionisation. Furthermore, we note that
emission in FUV or optical wavelengths trace unobscured star formation and
therefore, dust obscuration effects need to be accounted for to get a complete
picture of the star formation in host galaxies (see also Alaghband-Zadeh et
al., 2016).

In this paper, we try to overcome some of the limitations described above. We
will characterise spatially-resolved properties of the H$\alpha$ emission in a
large sample of moderate to high luminosity AGN at z$\sim$2 (Log $L_{\rm
bol}=$ 45.4–47.9 erg s-1). These AGN show the presence of high velocity
ionised gas outflows in their host galaxies, which was inferred from the [O
iii]$\lambda$5007 emission (Kakkad et al., 2020). We investigate whether the
H$\alpha$ emission is dominated by star formation or AGN ionisation. In the
case where the H$\alpha$ emission is dominated by AGN ionisation, we will
determine whether this emission is also a part of ionised gas outflows in the
narrow line region (NLR). Finally, using the spatially resolved H$\alpha$ and
[O iii]$\lambda$5007 emission ([O iii] hereafter), we investigate whether the
outflows and star formation are co-located and whether this can reveal the
presence of positive or negative feedback in these galaxies.

We adopt the following $\Lambda$CDM parameters throughout this paper: $H_{\rm
o}$ = 70 km s-1, $\Omega_{\rm M}$ = 0.3 and $\Omega_{\Lambda}$ = 0.7. In all
the maps in this paper, North is up and East is to left.

##  2 Sample, Observations and data reduction

The sample in this study is part of the SINFONI survey for Unveiling the
Physics and Effect of Radiative feedback (see Circosta et al., 2018; Kakkad et
al., 2020; Mainieri et al., 2021). SUPER is an ESO large programme with the
SINFONI instrument on board the VLT (Eisenhauer et al., 2003) designed to
characterise the properties of outflows in the ionised gas phase and their
impact on host galaxies in a sample of 39 X-ray selected AGN at z$\sim$2 in
AGN host galaxies at z$\sim$2\. The survey is designed to trace ionised gas
kinematics in the least biased manner by probing a wide range in AGN
bolometric luminosity that span up to four orders of magnitude. The survey
takes advantage of the Adaptive Optics (AO) module and reaches an angular
resolution of $\sim$0.2″, resolving ionised gas kinematics and potentially
star formation down to $\sim$2 kpc scales. Here we provide a brief description
of the sample chosen for this paper and defer the reader to Circosta et al.
(2018) and Vietri et al. (2020) for more details about the parent sample.

The 39 X-ray selected AGN ($L_{\rm 2-10keV}$ > 1042 erg s-1) were obtained
from shallow and deep fields: Chandra Deep Field South (e.g., Luo et al.,
2017), COSMOS-Legacy (e.g., Civano et al., 2016), XMM-XXL (e..g, Georgakakis &
Nandra, 2011; Liu et al., 2016; Menzel et al., 2016), Stripe 82 X-ray survey
(e.g., LaMassa et al., 2016) and WISE/SDSS selected Hyper-luminous quasar
sample (e.g., Bischetti et al., 2017; Vietri et al., 2018). Out of these 39
AGN, 22 are classified as type 1 (56%) based on the presence of broad
H$\beta$, H$\alpha$ and/or MgII lines, characteristic of emission from the
Broad Line Region (BLR). A wide range of ancillary data has allowed us to
accurately compute various AGN properties such as the AGN bolometric
luminosity ($L_{\rm bol}$), the black hole mass ($M_{\rm BH}$), X-ray column
density ($N_{\rm H}$) in most targets and host properties such as SFR and
stellar mass ($M_{\ast}$) in type 2 AGN. Estimation of host galaxy properties
in type 1 AGN has been challenging as the AGN emission dominates the Spectral
Energy Distribution (SED) for a wide range of wavelengths, preventing a robust
estimation of SFR and stellar mass. Furthermore, CO(3-2) and dust continuum
follow-up using sub-mm data from ALMA has also provided constraints on the
molecular gas and dust properties for a sub-sample of SUPER targets (Circosta
et al., 2021; Lamperti et al., 2021).

The SINFONI observations for the SUPER survey were carried out in the H-band
and K-band (or the H+K band in the case of bad weather) to trace the rest-
frame optical emission lines: H$\beta$, [O iii]$\lambda$4959, 5007, [N
ii]$\lambda$6549, 6585, H$\alpha$ and [S ii]$\lambda\lambda$6716, 6731. The
spatial resolution of the Adaptive Optics-assisted observations in the K-band
grating reaches down to 0.2″ (median 0.3″), similar to the H-band data, which
corresponds to a physical scale of $\sim$2 kpc at z$\sim$2\. The H+K grating
observations have a spatial resolution of $\sim$0.9″($\sim$7.5 kpc) and did
not have sufficient offset along the X-direction while nodding during the
observations. This implied that a spatially resolved analysis was only
performed along the Y-direction. Further details about the observations, data
reduction, and results from the [O iii] analysis of the H-band data of type 1
SUPER targets are available in the first SINFONI data release paper (Kakkad et
al., 2020). This paper focuses on the analysis of the H$\alpha$ emission line
in the 21 type 1 SUPER targets, observed with the K-band or H+K band grating
of the SINFONI spectrograph. We focus on the type 1 AGN to have a better
estimate of PSF smearing effects by modelling the emission from the BLR. We
have excluded the type 1 AGN S82X2106 since no signal was detected in our
K-band observations. The targets in this paper have the following ranges in
their black hole and host galaxy properties: log $M_{\ast}/M_{\odot}\sim$
10.38–11.20, SFR $<$94–686 $M_{\odot}$ yr-1, log $L_{\rm bol}$/[erg s-1]
$\sim$ 45.4–47.9, log $M_{\rm BH}/M_{\odot}\sim$ 8.3–10.7, and log $N_{\rm
H}$/cm${}^{2}\sim<$21.25–24.1. Tables with full list of these values for each
target are available in Circosta et al. (2018), Kakkad et al. (2020), and
Vietri et al. (2020).

##  3 Analysis

One of the primary goals of this paper is to investigate whether the observed
H$\alpha$ emission is ionised by star formation or the AGN. We also compare
the H$\alpha$ morphology and kinematics from the K-band data with that of the
[O iii] line presented in Kakkad et al. (2020) to infer if the ionised gas
outflows have an impact on the unobscured star formation.

In Kakkad et al. (2020), we characterised the properties of the ionised gas
kinematics in the NLR of the type 1 AGN from the SUPER sample using the [O
iii]$\lambda$5007 line in the H-band data. We describe the main results from
the H-band data briefly here before presenting the analysis methods used in
this paper. The non-parametric [O iii] velocity dispersion, $w_{80}$, of the
SUPER sample was always above 600 km s-1, a velocity-cut usually indicative of
the presence of ionised gas outflows driven by the AGN. The AGN as a source of
outflow was also confirmed by the presence of strong correlations between the
different ionised gas outflow properies ($w_{80}$, maximum velocity, $v_{\rm
max}$ and mass outflow rates) and the AGN properties ($L_{\rm X}$(2-10 keV),
$L_{\rm bol}$, $M_{\rm BH}$ and $\lambda_{\rm Edd}$). The ionised gas emission
is extended in seven out of eleven targets for which the signal-to-noise in
the [O iii] emission was sufficient enough to perform a PSF de-convolution.
The outflows associated with the ionised gas is extended up to $\sim$6 kpc
from the AGN location, although $<$10% of these outflows have the potential to
escape the gravitational pull of the host galaxy.

###  3.1 Modelling of the integrated spectrum

Figure 1: The top panel shows the integrated spectrum of X_N_160_22 extracted
from a circular aperture of 0.9″ diameter, showing the H$\alpha$ complex i.e.,
[N ii]$\lambda\lambda$6549,6585 and H$\alpha$ lines blended together. The left
panel shows the line fitting model M1, the middle panel M2 and the right panel
M3. The bottom panels show the residuals from the emission line modelling.
Further details on the three models are described in Sect. 3.1. The figure
highlights the differences in the Gaussian models when imposing different
constraints on the fitting routines and that the H$\alpha$ complex modelling
is often degenerate. In all the panels, the grey curve shows the raw spectrum
extracted from the cube (or the residuals in the bottom panel), the red curve
shows the overall model, the blue curves show the H$\alpha$ NLR models, the
magenta curve represents the H$\alpha$ BLR emission and the green curve shows
the [N ii]$\lambda\lambda$6549,6585 emission. The X-axis shows the rest-frame
wavelength and the Y-axis shows the observed flux. The vertical dashed blue
lines show the expected location of [N ii]$\lambda\lambda$6549,6585 and
H$\alpha$ lines based on the redshift of this target. The [S
ii]$\lambda\lambda$6716, 6731 lines remain undetected in most galaxies.

We first construct a model for the integrated spectrum before performing a
pixel-by-pixel analysis of the emission lines in the K-band data. We extract
the integrated spectrum for each object using a circular aperture centred on
the AGN. The peak of the K-band continuum emission is used as an estimate for
the AGN location and the aperture size was chosen to include at least
$\sim$95% of the total emission. We used the spectrum extracted from an
object-free region to estimate the error on the spectrum. We focused the
modelling of the extracted spectrum around the H$\alpha$ and [S ii] emission
line regions.

Modelling the H$\alpha$ emission line profiles of high-redshift type 1 AGN
host galaxies is not straightforward as the [N ii] and H$\alpha$ emission
lines are blended into one broad feature. Each emission line is modelled using
multiple Gaussian functions. The H$\alpha$ emission consists of contributions
from clouds from the BLR, NLR, and emission from the host galaxy. The NLR
component(s) of [N ii]$\lambda$6549, 6585 emission (as well as [S
ii]$\lambda$6716, 6731) can be blended with the different components of the
H$\alpha$ emission. As a result of such complex nature of the emission around
the H$\alpha$ line (referred to as the H$\alpha$ complex hereafter), there is
no unique solution to the emission line model. Therefore, constraints need to
be imposed on different Gaussian parameters in order to obtain a unique
solution. In this section, we explore the different ways of fitting the
H$\alpha$ complex in the type 1 AGN host galaxies, based on methods previously
adopted in the literature. We will then present the arguments that justify the
fitting methodology adopted in this paper.

We model the H$\alpha$ complex using three fitting methods, which we will call
M1, M2 and M3. The three methods differ on some of the constraints imposed on
the emission lines within the H$\alpha$ complex. These constraints are based
on the results of the H$\beta$ and [O iii] emission line models presented in
Kakkad et al. (2020). We start describing the assumptions common to the three
methods used to model the H$\alpha$ complex. The integrated spectrum is
modelled between the rest-frame wavelengths 6200–6900 Å which includes the AGN
continuum emission, [N ii]$\lambda\lambda$6549,6585, H$\alpha$ and [S
ii]$\lambda\lambda$6716,6731 emission lines. The BLR component of H$\alpha$ is
modelled using a broad Gaussian or a broken power law, the choice depending on
the model used to reproduce the H$\beta$ line in the H-band data (see also
Vietri et al., 2020). The NLR components of H$\alpha$ and [N ii]$\lambda
6549,6585$ are modelled using multiple Gaussian functions. A maximum of two
Gaussians were used to reproduce the non-BLR components of each emission line
([N ii]$\lambda$6549, 6585 and H$\alpha$), equal to the number used for the [O
iii] line. In the case when two Gaussians are used for the NLR component, the
Gaussian with the lower width is labelled as the narrow component, while the
one with larger width is labelled as the broad component, without setting
strict lower or upper limits for each component. To distinguish between the
broad Gaussian component from the NLR and the one from the BLR, we will use
the term broad Gaussian for the former and BLR-Gaussian for the latter. The
widths of the narrow (broad) Gaussian components of [N ii] and H$\alpha$ are
coupled to each other and the centroid difference between each component is
fixed based on the expected positions in the rest-frame spectra. Furthermore,
the relative ratio between the fluxes of [N ii]$\lambda$6549 and [N
ii]$\lambda$6585 is fixed to the expected theoretical value of 1:3 (e.g.,
Osterbrock & Ferland, 2006). We do not include fitting models for an iron
component or [S ii]$\lambda\lambda$6716,6731, as they remain undetected or
their contribution is negligible in all the galaxies.

Table 1: This table reports the H$\alpha$ emission line fitting parameters using the M3 model described in Sect. 3.1 (see also Vietri et al., 2020) and whether the emission is extended. (1) Target name, (2) The diameter of the circular aperture used for spectral extraction, Columns (3) & (4) report the width (FWHM) of the individual NLR Gaussian components of the H$\alpha$ line (narrow NLR = $v_{1}$ and broad NLR = $v_{2}$), (5) width (FWHM) of the BLR Gaussian component of H$\alpha$. Columns (6), (7) & (8) report the luminosity of the two NLR components (narrow NLR = $L_{1}$ and broad NLR = $L_{2}$) and the BLR component ($L_{\rm BLR}$), respectively, (9) reports the presence or absence of extended H$\alpha$ emission. The errors are obtained using a Monte Carlo approach and the values reported are the 1$\sigma$ error limits. ∗Targets with the same line fitting results as the M2 model (Table 3). Line modelling for all the targets has been done between rest-frame wavelengths 6200–6900 Å, except J1441+0454 for which the fitting is performed between rest-frame wavelengths 6380–6950 Å. Target | Aperture | FWHM | $L_{\rm H\alpha}$ | Extended H$\alpha$
---|---|---|---|---
|  | $v_{1}$ | $v_{2}$ | $v_{\rm BLR}$ | $L_{1}$ | $L_{2}$ | $L_{\rm BLR}$ |
| arcsec | km/s | km/s | km/s | erg/s | erg/s | erg/s |
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) |
X_N_160_22 | 0.9 | 915$\pm$195 | – | 5730$\pm$156 | 43.44$\pm$0.78 | – | 44.30$\pm$0.03 | Yes
X_N_81_44 | 0.9 | 530$\pm$162 | 2000$\pm$213 | 6621$\pm$324 | 42.82$\pm$0.19 | 43.72$\pm$0.12 | 44.26$\pm$0.02 | Yes
X_N_53_3∗ | 0.8 | 345$\pm$213 | – | 4577$\pm$187 | 42.04$\pm$0.22 | – | 43.70$\pm$0.01 | Yes
X_N_66_23∗ | 0.9 | 150$\pm$150 | – | 5640$\pm$190 | 41.45$\pm$7.8 | – | 43.72$\pm$0.01 | May be
X_N_35_20∗ | 0.5 | 532$\pm$56 | – | 6549$\pm$1188 | 41.97$\pm$0.08 | – | 42.68$\pm$0.08 | No
X_N_12_26∗ | 1.0 | 544$\pm$42 | – | 4615$\pm$99 | 42.80$\pm$0.04 | – | 43.95$\pm$0.01 | Yes
X_N_44_64∗ | 0.5 | 411$\pm$17 | – | 7688$\pm$560 | 42.37$\pm$0.02 | – | 43.03$\pm$0.02 | No
X_N_4_48∗ | 0.7 | 473$\pm$53 | – | 7596$\pm$303 | 42.79$\pm$0.06 | – | 44.18$\pm$0.01 | Yes
X_N_102_35 | 0.3 | – | 1735$\pm$480 | 5418$\pm$246 | – | 42.93$\pm$0.24 | 43.94$\pm$0.03 | No
X_N_115_23 | 0.9 | 413$\pm$55 | 1400$\pm$267 | 7031$\pm$148 | 42.93$\pm$0.08 | 43.25$\pm$0.09 | 44.15$\pm$0.01 | Yes
cid_166 | 0.9 | 395$\pm$126 | 1875$\pm$226 | 6881$\pm$104 | 42.48$\pm$0.27 | 43.76$\pm$0.11 | 44.60$\pm$0.01 | May be
cid_1605∗ | 0.3 | 516$\pm$110 | – | 3802$\pm$80 | 41.96$\pm$0.15 | – | 43.27$\pm$0.01 | Yes
cid_346∗ | 0.9 | 301$\pm$43 | 2916$\pm$156 | 7556$\pm$592 | 42.60$\pm$0.08 | 43.59$\pm$0.16 | 43.86$\pm$0.05 | Yes
cid_1205∗ | 0.8 | 446$\pm$89 | – | 5023$\pm$183 | 42.04$\pm$0.12 | – | 43.46$\pm$0.01 | No
cid_467∗ | 0.3 | 575$\pm$61 | – | 8750$\pm$285 | 42.37$\pm$0.05 | – | 43.86$\pm$0.01 | Yes
J1333+1649 | 1.0 | 615$\pm$572 | 2760$\pm$771 | 6217$\pm$467 | 42.77$\pm$0.67 | 44.74$\pm$1.28 | 45.53$\pm$0.02 | Yes
J1441+0454 | 1.0 | – | 1000$\pm$85 | 5262$\pm$90 | – | 44.18$\pm$0.03 | 44.92$\pm$0.02 | No
J1549+1245 | 1.1 | 376$\pm$221 | 1385$\pm$298 | 7914$\pm$97 | 43.40$\pm$0.30 | 44.36$\pm$0.20 | 45.63$\pm$0.01 | May be
S82X1905 | 1.0 | 660$\pm$58 | – | 4935$\pm$99 | 43.01$\pm$0.04 | – | 44.12$\pm$0.01 | Yes
S82X1940 | 0.8 | 380$\pm$124 | 1428$\pm$710 | 4145$\pm$434 | 42.76$\pm$0.25 | 42.80$\pm$4.53 | 44.25$\pm$0.11 | Yes
S82X2058 | 0.9 | 363$\pm$128 | 1675$\pm$228 | 6616$\pm$184 | 42.13$\pm$0.30 | 42.56$\pm$3.06 | 44.09$\pm$0.02 | Yes

We now describe the differences in the fitting constraints between the three
methods. In the M1 method, we first fit the H$\alpha$ complex using only the
H$\alpha$ components. The [N ii] line components are added only when the
models from the H$\alpha$ only fit result in significant residuals on visual
inspection. This approach was previously adopted in the literature for the
analysis of the rest-frame optical spectra of one of the high-z quasars (e.g.,
Carniani et al., 2016), where the [N ii] emission is assumed to be undetected
if no significant residuals are present after modelling with only the
H$\alpha$ components. In the M2 method, [N ii] emission line model is
included, irrespective of the presence or absence of residuals from the
H$\alpha$-only fit. The M2 method assumes that the [N ii] emission is always
present within the H$\alpha$ complex. Similar to the M1 method, no other
constraints from the H-band spectra are imposed apart from the common
constraints described in the previous paragraph. The M2 method is explored to
gauge the variation in the fluxes and widths of various H$\alpha$ components
upon inclusion of the [N ii] lines. Lastly in the M3 method, we fit the [N ii]
line in the H$\alpha$ complex, similar to the M2 method. However, three
additional constraints are imposed during the line fitting procedure: (1) The
maximum allowed width of the narrow H$\alpha$ component is the width of the
narrow [O iii] line from the H-band line fitting results. (2) The difference
in the centroid of narrow and broad Gaussian components of H$\alpha$ is kept
the same as the difference in the centroid of narrow and broad Gaussian
components of the [O iii] line. (3) The width of the broad H$\alpha$ component
is kept the same as that of the broad [O iii] components. The method M3 is
similar to the fitting model presented in Vietri et al. (2020), with the
exception that [S ii]$\lambda\lambda$6716,6731 emission line components were
not included. Figure 1 shows the integrated spectrum and the emission line
modelling of X_N_160_22 as an example, using the three methods (left panel:
M1, middle panel: M2 and right panel: M3). The integrated spectra of the rest
of the targets are shown in the Appendix A (Figs. 12 and 13). Below, we
present arguments to support the selection of the M3 method as our baseline
methodology in this paper.

Figure 2: The plots in this figure show the results of the PSF-subtraction
procedure described in Sect. 3.2. The maps show the PSF-subtracted H$\alpha$
channel map and the corresponding right panels show the spectrum extracted
from regions above 3$\sigma$ noise levels (white regions in the channel maps).
The noise levels in each map is obtained from object-free regions. The "X" in
the maps mark the peak of the K-band continuum emission which is used as a
proxy for the AGN location. The magenta shaded region in the spectra show the
channels that were collapsed to obtain the PSF-subtracted images. The vertical
red dashed line shows the expected location of the H$\alpha$ line based on the
redshift of the respective targets. The presence of structure in the PSF-
subtracted map and a visible detection of the emission line in the spectra
would suggest an extended H$\alpha$ feature. Each target in this figure show
signatures of extended H$\alpha$ emission (labelled as "Resolved"), except
X_N_66_23 and cid_166 (labelled as "Resolved?") where the extension is a
possibility but unconfirmed with the current data. Further details are given
in Sect. 3.2.

Figure 3: Same as Fig. 2, for the rest of the targets presented in this paper.
All the targets, except cid_1205 and J1549+1245, show confirmed evidence of
extended H$\alpha$ emission. We detected no extended emission in cid_1205 and
the detection in J1549+1245 is tentative. Figure 4: The plot shows the null-
hypothesis probability for non-correlation between different extended
H$\alpha$ properties and the properties of the black hole and the host galaxy.
The dashed black line shows the 5% line for p-value, used as a demarcation
between the presence or absence of correlations.

Tables 1, 3 and 4 report the fitting parameter values obtained using the three
methods described above (M3, M2 and M1, respectively). In most of the type 1
AGN, the [N ii] emission is required as significant residuals remain from the
H$\alpha$-only fitting procedure. Therefore, in the cases where such residuals
are not observed from the H$\alpha$-only fit, we assume that the [N ii] lines
are actually blended with the overall emission line structure. The presence of
[N ii] lines in most high redshift galaxies is also supported by the results
of the SINS/zC-SINF survey (e.g., Förster Schreiber et al., 2018) where
$\sim$65% of the star forming galaxies had [N ii] detections. However, the M2
method return very high values for the width of the BLR component of the
H$\alpha$ line ($>$9000 km s-1 in some cases), which would result in
unrealistically high black hole masses. This is a direct consequence of
leaving all the emission line component centroids and widths free to vary. The
presence of unrealistic widths and degeneracy in the results are solved using
the M3 method. Therefore, hereafter we will use the M3 method in this paper to
model the H$\alpha$ complex, which is also similar to the methodology adopted
in previous papers from the SUPER survey (e.g., Vietri et al., 2020; Lamperti
et al., 2021).

We employ a Monte Carlo (MC) approach to determine the errors in the fitting
model, where we add noise to the integrated model and repeat the fitting
procedure 100 times to determine the 1$\sigma$ errors on different parameters
(see e.g., Perna et al., 2015; Brusa et al., 2016; Kakkad et al., 2016). The
input noise for the MC is determined from the rms noise in an emission line-
free region in the raw spectrum.

###  3.2 Extended H$\alpha$ emission

Table 2: Properties of the extended H$\alpha$ emission presented in this paper. (1) Target name, (2) The maximum distance from the AGN location where the extended H$\alpha$ is detected at $\geq 3\sigma$ after the PSF subtraction (see Figs. 2 and 3, (3) The width of the PSF-subtracted H$\alpha$ emission line from the extended regions, (4) The extended H$\alpha$ centroid in the spectral space with respect to the expected location of H$\alpha$ based on the [O iii] redshift from Kakkad et al. (2020), (5) The flux ratio, [N ii]/H$\alpha$ from the extended H$\alpha$ spectra from the K-band data, (6) The flux ratio [O iii]/H$\beta$ from the extended [O iii] spectra from the H-band data (Kakkad et al., 2020), (7) The ionisation source of the extended H$\alpha$ emission line regions based on its location in the BPT diagram or the [N ii]/H$\alpha$ flux ratio. Further details in Section 3.3. This table does not show the data for X_N_35_20, X_N_44_64, X_N_102_35, cid_1205, cid_467 and J1441+0454, as these targets are unresolved. Target | RHα | vHα | $v_{\rm shift}$ | log [N ii]/H$\alpha$ | log [O iii]/H$\beta$ | Ionisation source
---|---|---|---|---|---|---
| kpc | km s-1 | km s-1 |  |  |
(1) | (2) | (3) | (4) | (5) | (6) | (7)
X_N_160_22 | 4.5$\pm$0.4 | 112$\pm$30 | 42$\pm$10 |  $<$-0.7 | – | SF
X_N_81_44 | 3.5$\pm$0.4 | 113$\pm$15 | 485$\pm$5 |  $<$-0.8 | – | SF
X_N_53_3 | 5.2$\pm$0.4 | 199$\pm$44 | 33$\pm$17 | -0.6${}^{+0.2}_{-0.4}$ | – | unconstrained
X_N_66_23 | 4.0$\pm$0.4 | 370$\pm$109 | -1200$\pm$300 |  $<$-0.9 | – | SF
X_N_12_26 | 4.5$\pm$0.4 | 241$\pm$45 | 286$\pm$21 |  $<$-0.6 | – | unconstrained
X_N_4_48 | 6.4$\pm$0.4 | 256$\pm$58 | 78$\pm$29 |  $<$-0.4 | – | unconstrained
X_N_115_23 | 4.6$\pm$0.4 | 270$\pm$35 | 19$\pm$15 |  $<$-0.8 | 0.9$\pm$0.3 | AGN
cid_166 | 2.6$\pm$0.4 | 73$\pm$16 | -713$\pm$9 |  $<$-0.5 | – | unconstrained
cid_1605 | 3.9$\pm$0.4 | 351$\pm$140 | 10$\pm$1 |  $<$-0.3 | – | unconstrained
cid_346 | 4.7$\pm$0.4 | 628$\pm$45 | 134$\pm$20 |  $<$-0.4 |  $>$0.5 | AGN
cid_467 | 2.6$\pm$0.4 | 350$\pm$65 | 180$\pm$25 |  $<$-0.7 | – | SF
J1333+1649 | 5.7$\pm$0.4 | 302$\pm$67 | 260$\pm$22 |  $<$-0.5 | 0.7$\pm$0.2 | AGN
J1549+1245 | 9.0$\pm$0.4 | 408$\pm$92 | 1720$\pm$200 |  $<$-0.4 | – | unconstrained
S82X1905 | 4.4$\pm$0.4 | 142$\pm$28 | 143$\pm$12 |  $<$-0.6 |  $>$1.0 | AGN
S82X1940 | 7.8$\pm$0.4 | 784$\pm$98 | 202$\pm$120 |  $<$-0.2 | – | AGN
S82X2058 | 4.4$\pm$0.4 | 436$\pm$68 | 330$\pm$30 |  $<$-0.4 | – | unconstrained

Before performing a pixel-by-pixel analysis of the H$\alpha$ spectrum of the
type 1 targets, it is important to quantify the contribution of beam-smearing
from the AGN PSF to the observed H$\alpha$ emission. This procedure, also
called PSF-subtraction, isolates the underlying contributions from the host
galaxy. Beam smearing results in emission line regions to mimic radial
profiles consistent with PSF profiles, and consequently appear artificially
extended (see e.g., Carniani et al., 2015; Husemann et al., 2016; Luo et al.,
2019). We subtract this contribution from the AGN-PSF using methods similar to
those employed in the analysis of the extended [O iii] emission in the H-band
data in Kakkad et al. (2020).

If the H$\alpha$ emission is unresolved, then the spectrum at any distance
from the AGN will be the same as the spectrum at the AGN location, except for
an overall scaling factor across the spectrum (e.g., Jahnke et al., 2004).
Therefore, we first model the spectrum extracted at the AGN location (circular
aperture of diameter 0.1″ centred on the K-band continuum peak). We will refer
to this spectrum as the "nuclear model". The nuclear model is subtracted from
every pixel across the SINFONI field-of-view, only allowing a variation in the
overall normalisation factor of the spectrum. The kinematic parameters of
different Gaussian components (i.e., the line centroid and the line width) are
kept fixed with respect to the nuclear model. After the subtraction of the PSF
model, we collapsed the channels in the residual data cube at the expected
location of narrow H$\alpha$ emission. The width of the channel window is
optimised for each target separately, based on where we obtain the maximum
residual H$\alpha$ emission. A noisy map (an image with net zero residuals)
indicates that the underlying H$\alpha$ emission is unresolved, while
systematic patterns in these residual maps would suggest that the H$\alpha$
emission is extended. This extended H$\alpha$ emission can be due to star-
formation in the host galaxy, AGN emission or a combination of the two. The
nature and origin of this extended emission will be discussed further in Sect.
3.3.

Figures 2 and 3 shows the results of the PSF-subtraction method for each
target presented in this paper. We do not show the PSF-subtraction results for
the following four targets: X_N_35_20, X_N_44_64, X_N_102_35 and J1441+0454.
Targets X_N_35_20 and X_N_44_64 had low S/N in their H$\alpha$ line in the
integrated spectrum to obtain a reliable estimate on the H$\alpha$ BLR flux
and consequently the PSF. X_N_102_35 was observed in the H+K band and no
residuals were observed in the Y-direction. Lastly, the location of the
H$\alpha$ line in J1441+0454 is contaminated by telluric emission and the PSF-
subtraction did not yield a reliable detection.

All the maps in Figs. 2 and 3 show the PSF-subtracted channel maps at the
expected location of H$\alpha$ emission. The colour map in the H$\alpha$
images is set between $\pm$3$\sigma$, where $\sigma$ is the noise level in the
map determined from object-free locations. The panels on the right side of the
maps show the spectrum extracted from regions at or above 3$\sigma$ in the
H$\alpha$ channel maps. The magenta shaded regions in the spectra show the
channels that were collapsed to obtain the PSF-subtracted H$\alpha$ map. The
vertical dotted red line in the spectra show the expected location of the
H$\alpha$ line based on the [O iii] redshift values reported in Kakkad et al.
(2020).

We confirm the presence of extended H$\alpha$ emission in 13 out of the 21
galaxies and 3 galaxies (X_N_66_23, cid_166 and J1549+1245) show tentative
evidence of extended emission. The detection in X_N_66_23 is classified as a
tentative one, as the extended emission is observed at a blue-shift of
$\sim$-1200 km s-1 from the expected location of the H$\alpha$ line in the
spectra. Similarly, the extended emission in J1549+1245 is detected at a
distance of 9 kpc from the AGN location and the spectral position of the
detection is redshifted by $\sim$+1800 km s-1 with respect to the expected
location of the H$\alpha$ line. Although currently available archival optical
observations do not suggest the presence of companions, this may be due to
their limited spatial resolution. In fact, ALMA CO observations of J1549+1245
have shown the presence of a possible companion south of the AGN location (see
Bischetti et al., 2021). Such extreme velocity shifts have been observed in
previous CO observations of high redshift X-ray AGN sources (e.g., Carniani et
al., 2017). The extended H$\alpha$ detections in X_N_66_23 and J1549+1245 may
suggest emission from tidal tails. In the case of cid_166, the detection is
almost at the limit of the spectral resolution of SINFONI. Furthermore, the
observed residual is blue-shifted by $\sim$700 km s-1 from the expected
location of the H$\alpha$ emission and therefore, the extended emission in
cid_166 has been classified as a tentative detection. cid_1205 is the only
target among the ones observed with AO and with sufficient S/N for the PSF-
subtraction analysis that shows no extended H$\alpha$ emission.

Overall, we find a higher fraction of targets with extended H$\alpha$ emission
($\sim$76% including the tentative detections) than extended [O iii] emission
($\sim$35%). The spatial extent of the H$\alpha$ emission (maximum distance
between the AGN location and the H$\alpha$ emission in the PSF-subtracted
maps), $R_{\rm H\alpha}$ is in the range 3–9 kpc, with a mean value of $\sim$5
kpc. Due to the low signal-to-noise after the PSF-subtraction, we model the
extended H$\alpha$ residual spectrum using single Gaussian functions and
define two parameters: the width (FWHM) of the extended H$\alpha$ emission,
$FWHM_{\rm H\alpha}$ and the velocity shift, $v_{\rm shift}$, between the
expected location of the H$\alpha$ line and actual location of the extended
H$\alpha$ line in the spectra. We find $FWHM_{\rm H\alpha}$ in the range
73–784 km s-1 with a mean width of 312 km s-1. The velocity shift, $v_{\rm
shift}$ is in the range -1200 – 1720 km s-1, with the majority of the targets
showing redshifted H$\alpha$ emission. Only two targets, X_N_66_23 and
cid_166, display blue-shifted extended H$\alpha$ emission and both of these
targets are classified as having a tentative extended emission. The properties
of the extended H$\alpha$ emission are summarized in Table 2.

We investigated whether the properties of the extended H$\alpha$ emission,
namely $R_{\rm H\alpha}$, $FWHM_{\rm H\alpha}$ and $v_{\rm shift}$ show any
correlations with the AGN or host galaxy properties such as $L_{\rm bol}$,
$M_{\rm BH}$, SFR and $M_{\ast}$. We derived the Pearson coefficient and the
p-value (null hypothesis probability for non-correlation) for the individual
relations. The p-values for different correlations are summarised in Fig. 4.
We define a correlation to exist based on p$<$0.05. Accounting for the errors,
$v_{\rm shift}$ correlates with $M_{\rm BH}$ and possibly also with $L_{\rm
bol}$, and SFR. $R_{\rm kpc}$ also shows correlation with $M_{\ast}$ and
possibly with $L_{\rm bol}$. No correlations are found between $FWHM_{\rm
H\alpha}$ and the AGN or host galaxy properties. However, we note that since
these are type 1 targets, the host galaxy properties, namely SFR and
$M_{\ast}$, are highly unconstrained and are only available for 5 targets (see
Circosta et al., 2018). Overall, the $v_{\rm shift}$ parameter seems to
correlate strongly with the AGN properties suggesting that the observed
velocity shift is possibly due to outflowing ionised gas traced with
H$\alpha$. On the other hand, the size of the extended region correlates with
the galaxy mass, consistent with the correlations reported between the size
and stellar mass of galaxies (e.g., van der Wel et al., 2014). Furthermore,
the lack of correlations or weaker correlations in Fig. 4 may also suggest
that the observed H$\alpha$ emission in some galaxies might also be tracing a
companion galaxy i.e., not associated with the X-ray source or the host galaxy
itself. The presence of companions will be further discussed in Sect. 4.

###  3.3 Ionisation source of the extended H$\alpha$ emission

Figure 5: The background images in the maps in the top two rows shows the PSF-
subtracted H$\alpha$ images and the overlaid blue contours show the locations
of extended [O iii] emission. The contour levels are at 98%, 90%, 70% and 50%
of the peak [O iii] flux. In four targets, X_N_115_23, cid_346, J1333+1649 and
S82X1905, the spatial location of the extended H$\alpha$ emission coincides
with that of the [O iii] emission. This made it possible to place the extended
H$\alpha$ emission of these four galaxies in the BPT diagram shown in the
bottom panel. In all these four galaxies, the extended emission is ionised by
the AGN. The black line shows the division between star forming and AGN
ionisation from Kewley et al. (2013). Targets, X_N_81_44 and J1549+1245 do not
show the same location of the [O iii] and H$\alpha$ emission.

Figure 6: Same as Fig. 5 but for targets, X_N_81_44 and J1549+1245, that do
not show the same location of the [O iii] and H$\alpha$ emission.

We now discuss the ionisation source of the extended H$\alpha$ emission, i.e.,
whether the emission is ionised by the AGN, star formation or a combination of
the two, based on the [O iii] results reported in Kakkad et al. (2020) and
PSF-subtracted images and spectra shown in Figs. 2 and 3. We use three
different techniques to infer the ionisation source: (1) We compare the
extended H$\alpha$ morphology with the [O iii] morphology. A similarity
between the two emission regions could suggest that the extended H$\alpha$
emission traces gas in the NLR. (2) As described in Sect. 3.2, we fit the
single Gaussian functions to the extended H$\alpha$ emission to derive the
line width. A large width (e.g., $>$600 km s-1) would mean H$\alpha$ emission
traces outflowing gas. This is supported by the maximum gas velocity of
$\sim$500 km s-1 observed in the case of star formation driven outflows in
high redshift galaxies (see review by Förster Schreiber & Wuyts, 2020), and
therefore using 600 km s-1 as a cut off for AGN-driven outflows is a
conservative assumption. However, we note that galaxy interactions can also
increase the line widths (e.g., Puglisi et al., 2021). Due to the relatively
low S/N of the H$\alpha$ lines compared to integrated spectra, we do not
attempt to fit multiple Gaussian functions to these spectra. (3) Lastly, the
single Gaussian fits to the extended H$\alpha$ emission (Sect. 3.2, Fig. 2)
were used to estimate the flux of the [N ii] and H$\alpha$ lines. The flux
ratios were then placed on the classical Baldwin, Phillips & Telervich (BPT,
see Baldwin et al., 1981; Veilleux & Osterbrock, 1987) diagnostic diagrams to
estimate the probable source of ionisation from expectations based on the
literature (e.g., Kauffmann et al., 2003). For the majority of the galaxies,
extended [O iii] and H$\beta$ emission lines are not detected at the location
of extended H$\alpha$ emission, therefore placing them on the BPT diagrams was
not possible.

We were able to plot resolved BPT maps for four galaxies, namely X_N_115_23,
cid_346, J1333+1649 and S82X1905, as extended [O iii] emission is also
detected at the location of extended H$\alpha$ as shown in the top two rows of
Fig. 5. The bottom panel in Fig. 5 shows the location of extended emission in
these four galaxies in the [N ii]-BPT diagram. In these four galaxies the
spatial coincidence of the extended H$\alpha$ and [O iii] emission suggests
that we are tracing the NLR rather than the host galaxy disk. That the
ionization source for the extended H$\alpha$ is the AGN rather than star-
formation is further supported by the location of these galaxies in the BPT
diagram (bottom panel in Fig. 5). The [N ii] line remains undetected in the
extended H$\alpha$ region for all the galaxies and therefore, we estimate an
upper limit for the [N ii]/H$\alpha$ ratio. In the case of cid_346 and
S82X1905, we also do not detect H$\beta$ emission in the extended regions and
therefore, a lower limit to the [O iii]/H$\beta$ line ratio is estimated. All
four galaxies are above the region of the BPT where we expect to have star-
formation as the main ionization source. In addition, for cid_346, the width
of the extended H$\alpha$ emission is 628$\pm$45 km s-1, which is above the
limit usually used to distinguish between an outflowing and non-outflowing
gas. This suggests that the observed H$\alpha$ emission is a part of the NLR
outflow. This is also supported by the fact that the ionised outflow is also
detected in the [O iii] line at the same location as the extended H$\alpha$
(see Kakkad et al., 2020). We also note here that the BPT results shown here
for cid_346 may be different compared to the ones presented in Lamperti et al.
(2021), as the extraction apertures for the PSF and the extended H$\alpha$
emission may be different.

For all the other galaxies, as the [O iii] and H$\beta$ lines remain
undetected, they could not be placed in the classical BPT diagram. Therefore,
we estimate the ionisation source based on the limit derived for the [N
ii]/H$\alpha$ line. Four targets, X_N_160_22, X_N_81_44, X_N_66_23 and
cid_467, have log([N ii]/H$\alpha$) values $<$-0.7 and with such low [N
ii]/H$\alpha$ line ratios, it is less likely for these sources to be ionised
by the AGN (see the results from low redshift galaxy sample in Kauffmann et
al., 2003). For one of them, X_N_81_44, we also have evidence that the [O iii]
and H$\alpha$ emission are extended, but are not spatially co-located (Fig. 6,
left panel). We would therefore classify the extended emission in these four
galaxies as most probably ionized by star-formation.

The galaxies where the log([N ii]/H$\alpha$) line ratio $>$-0.7, the source of
ionisation could not be constrained for the extended regions with the current
data. The target, J1549+1245 falls under this category, where the extended [O
iii] and H$\alpha$ emission are not spatially co-located (Fig. 6, right
panel). Therefore, the ionisation source of these targets are labelled as
"unconstrained" in Table 2. An exception is S82X1940 shows an extended
H$\alpha$ emission towards the SE direction from the AGN location (Fig. 3).
This target displays the largest H$\alpha$ line width in the extended region
of $\sim$784$\pm$98 km s-1. The [O iii] emission line analysis of this target
already shows the presence of an ionised outflow (Kakkad et al., 2020) and
therefore, the H$\alpha$ emission most likely also traces the outflowing gas
driven by the AGN. Based on this evidence, we conclude that the observed
extended H$\alpha$ emission in S82X1940 is part of the NLR ionised by the AGN.
In all the cases presented above, we do not rule out the possibility of a
companion galaxy in a merger with the AGN host galaxy.

In summary, out of the 16 type 1 AGN in the SUPER survey that show extended
H$\alpha$ emission, four galaxies ($\sim$25%, $\sim$18% if we include all type
1 AGN, including unresolved galaxies) show that the extended H$\alpha$
emission is most likely ionised by star formation and in five galaxies
($\sim$30%, $\sim$23% if all the type 1 AGN are included) the ionisation is
dominated by the AGN. In the remaining 7 galaxies, the ionisation source of
the extended H$\alpha$ emission remains unconstrained. In two galaxies
(cid_346 and S82X1940), the width of the H$\alpha$ line $>$600 km s-1,
suggesting that the H$\alpha$ emission is tracing ionised outflow driven by
the AGN. However, we cannot exclude the possibility that the turbulence in the
ISM is related to an on-going merger event, for which higher resolution and
deeper data is required. We also note that the width alone should not be used
as an indicator for star forming or AGN origin to the emission, as the spectra
extracted from extended emission line regions are highly limited by noise.

From the analysis presented in this section, we conclude that H$\alpha$
emission in high redshift galaxies does not necessarily trace star formation,
but can also be associated with AGN ionisation or outflows or possible
companions.

Figure 7: The figure shows the spatial locations of the H$\alpha$ emission and
[O iii] based ionised outflows in X_N_81_44 (left panel) and X_N_66_23 (right
panel). The background image shows the PSF-subtracted H$\alpha$ images from
the maps in Fig. 2. The blue contours trace the [O iii] outflows ($w_{80}>$600
km s-1) at levels 600, 700 and 750 km s-1 in X_N_81_44; and 850 and 1050 km
s-1 in X_N_66_23. The extended H$\alpha$ emission in these galaxies is absent
in the direction with highest $w_{80}$ values. The green contours in X_N_81_44
show the archival ALMA band 7 dust continuum emission (from Lamperti et al.
(2021)), that traces dust reheated star formation. The implications of these
observations are furth er discussed in Sect. 3.3. Figure 8: The left panel
shows the narrow H$\alpha$ flux map of X_N_81_44 obtained from the pixel-by-
pixel Gaussian fit of the H$\alpha$ complex. The right panel, on the other
hand, shows the PSF-subtracted H$\alpha$ channel map of the same target. The
figure highlights that the PSF dominates the bulk of the emission close to the
AGN location (marked by the black star).

###  3.4 Impact of ionised outflows on unobscured star formation

To quantify the impact that ionised outflows may have on star formation, we
compare the spatial locations of ionised outflows, traced using the [O iii]
emission presented in Kakkad et al. (2020), with the extended H$\alpha$
emission presented in this paper. We perform this analysis on targets where
both the [O iii] and the H$\alpha$ emission is extended. Furthermore, we limit
this analysis to those targets where the extended H$\alpha$ emission is
consistent with ionisation by star formation, in order to use it as a tracer
of short time-scale ($\sim$10 Myr) unobscured star formation. Based on the
analysis presented in Sects. 3.2 and 3.3, two targets fulfil these criteria:
X_N_81_44 and X_N_66_23. Figure 7 shows the extended H$\alpha$ map tracing
star formation in these two targets, overlaid by [O iii]-based outflow
velocity contours in blue. Only the contours with [O iii] $w_{80}$ values
above 600 km s-1 are shown in Fig. 7. The astrometry of the H-band and K-band
images was registered using the AGN continuum peak emission in the respective
data cubes.

We observe a spatial anti-correlation between the locations of high velocity
[O iii] outflows ($w_{80}>$600 km s-1) and unobscured star formation in
X_N_81_44 and X_N_66_23. These results might suggest that star formation is
being actively shut down in regions with high velocity outflows, a result also
previously reported in the literature (e.g., Cano-Díaz et al., 2012; Carniani
et al., 2016). However, we cannot rule out a scenario where the high velocity
winds compress gas ahead of it, resulting in triggering of star formation in
the edges of the outflow (e.g., Cresci et al., 2015). We note here that the
spatial anti-correlation between high velocity outflows and H$\alpha$ emission
is observed only in the PSF-subtracted H$\alpha$ images and not in the narrow
H$\alpha$ maps obtained using the pixel-by-pixel fit, which will be described
in Sect. 4. The left panel in Fig. 8 shows the H$\alpha$ flux map of
X_N_81_44, obtained from the narrow Gaussian component, which shows that most
of the emission is concentrated close to the AGN location. However, the
emission close to the AGN is dominated by the PSF smearing effect. The right
panel, on the other hand, shows the PSF-subtracted H$\alpha$ channel map,
which removes any emission that might be affected by beam smearing, as
described earlier in Sect. 3.2. The results in Fig. 8 may explain some of the
observed differences, such as the presence or absence of such spatial anti-
correlations found in other high-z AGN host galaxies (e.g., Carniani et al.,
2016; Scholtz et al., 2021).

We note that the spatial resolution of the SINFONI observations prevents us
from investigating the morphology of the H$\alpha$ emission within the 2 kpc
PSF element which was subtracted in the maps shown in Fig. 7. In other words,
the SINFONI data is unable to trace star formation on scales smaller than 2
kpc at these redshifts and therefore, we cannot exclude the presence of on-
going star formation in the central cavity in the maps in Fig. 7. Observations
with upcoming facilities such as ELT/HARMONI will provide the necessary
spatial resolution to resolve regions in sub-kiloparsec scales in these
galaxies, where there could possibly be underlying emission from the host
galaxy.

In X_N_81_44, we also compare the outflow locations with archival high
resolution ($\sim$0.2″) ALMA Band 7 (870 $\mu$m observed-frame, $\sim$260
$\mu$m rest-frame) dust continuum maps from Lamperti et al. (2021). The dust
continuum emission is overlaid as red contours in Fig. 7. The Spectral Energy
Distribution (SED) analysis of X_N_81_44 suggests that $>$99% of the rest-
frame 260$\mu$m emission is from dust heated by star formation and $<$1%
contribution from the AGN-heated dust and synchrotron emission (see Lamperti
et al., 2021). We can, therefore, use the dust continuum maps to trace longer
time scale star formation from dust reheated by the UV radiation from stars
over the last $\sim$100 Myrs.

High redshift galaxies are known to host copious amount of dust, which can
have a significant impact on how we interpret the results on the spatial
distribution of outflow versus star formation (e.g., Fujimoto et al., 2018;
Lamperti et al., 2021; Scholtz et al., 2021). Star formation tracers using
rest-frame optical emission lines, such as H$\alpha$, are susceptible to dust
obscuration and previous work has shown that the dust distribution (obtained
from far-infrared ALMA observations, for instance) and H$\alpha$ distributions
(or rest-frame optical continuum distribution in case of narrow band HST
observations) are different in high redshift galaxies (Hodge et al., 2016;
Lang et al., 2019; Chen et al., 2020). In general, H$\alpha$ distributions
tend to be more extended compared to the dust emission. There is a large
concentration of star formation dominated infrared emission at the centre of
galaxies that one needs to account for (e.g., Hao et al., 2011). This is the
case also for the ALMA dust continuum emission (red contours) for X_N_81_44
(left panel in Fig. 7) that peaks in the central region and extends towards
the H$\alpha$ emission in the SE direction from the AGN. Therefore, based on
the ALMA map, there is no clear anti-correlation between the location of the
ionised outflow and regions with active star formation. However, we note that
the dust obscured star formation traced by sub-mm or far-infrared observations
represents star formation over long timescales of $\sim$100 Myrs. On the
contrary, the outflow timescale is much shorter (105 to a few Myrs, e.g.,
Schawinski et al., 2015). Therefore, we cannot exclude that the possible
impact of the outflow on star formation may be diluted by the large time range
to which the star formation is sensitive to. Furthermore, the ALMA dust-
continuum observations (Lamperti et al., 2021) were not able to resolve
spatial scales below $\sim$2 kpc and therefore, we cannot exclude the presence
of cavities below this physical scale. This limitation could be mitigated with
spatially resolved mid-infrared observations with JWST/MIRI.

Figure 9: An example of line modelling in individual pixels in X_N_115_23. The
middle panel shows the H$\alpha$ centroid map and the left and right panel
show the extracted spectrum and the emission line model in two pixels located
by the arrows.

Figure 10: H$\alpha$ NLR component velocity maps of (from top to bottom)
X_N_160_22, X_N_115_23, cid_346 and S82X2058 as examples. The plots for the
rest of the targets are moved to the appendix A (Fig. 14). The left panels
show the H$\alpha$ centroid map, the middle panels the $v_{10}$ map and the
right panels the $w_{80}$ maps. The targets show a diverse set of H$\alpha$
velocity distributions. X_N_160_22, cid_346 and S82X2058 show smooth velocity
gradients in their H$\alpha$ centroid profiles. S82X2058 shows an extended
structure towards the SW of the nucleus, suggesting a possible faint
companion. The H$\alpha$ centroid profile of X_N_115_23 does not show a smooth
rotation-like velocity gradient as in other galaxies, which is consistent with
the finding that the extended H$\alpha$ emission is a part of the NLR (Fig.
2). These maps are discussed further in Sect. 4.

Figure 11: Archival HST/WFC3 images of cid_166 (top panel) and cid_346 (bottom
panel), both type 1 AGN in the SUPER survey. The HST images are obtained with
the F160W filter (near-infrared) and both the images suggest the presence of a
companion. The cid_166 image clearly shows a stream linking the two galaxies.
The blue square in each of the panels show the SINFONI 3″$\times$3″ FoV.
Therefore, current observations presented in this paper do not capture the
presence of these companions.

##  4 Kinematic properties of narrow H$\alpha$ emission

In this section, we describe the pixel-by-pixel H$\alpha$ emission line
modelling for the targets that show extended H$\alpha$ emission after
subtracting the PSF, as described earlier in Sect. 3.2. We primarily derive
the kinematic maps from the BLR component-subtracted emission line models,
namely the H$\alpha$ centroid map (also called moment 1 map) and non-
parametric velocity and velocity dispersion maps i.e. $v_{10}$ and $w_{80}$
maps (see e.g., Harrison et al., 2014; Cresci et al., 2015). We compare these
H$\alpha$ maps with that of the [O iii] emission in the H-band data to
determine whether the H$\alpha$ emission mimics the kinematics of the [O iii]
emitting gas. This comparison can be used to further distinguish between a
star formation or NLR origin to the H$\alpha$ emission.

As described earlier in Sect. 3.1, the H$\alpha$ complex is composed of
several Gaussian functions, each representing the individual components of the
H$\alpha$ and [N ii]$\lambda\lambda$6549, 6585 emission lines. To avoid
degeneracy during the pixel-by-pixel fit, we employ the following constraints
on the individual Gaussian components to model the spatial distribution of the
narrow component of the H$\alpha$ emission, conventionally treated as tracing
the host galaxy star formation. All the constraints described here are fixed
or varied relative to the integrated spectrum fitting results using the M3
model, as described in Sect. 3.1. As the BLR emission is unresolved, we fix
the centroid and the width of the BLR components and only allow a variation in
its peak value. In all but two targets (cid_346 and S82X1940), the spectrum
extracted from the extended regions in the PSF-subtracted cube shows a
H$\alpha$ width (FWHM) of $<$600 km s-1. In these targets where the H$\alpha$
FWHM$<$600 km s-1, we fix the centroid and width of the broad NLR component
and only allow a variation in its peak (similar to the constraint imposed on
the BLR component). The centroid, width and the peak of the narrow NLR
component of the H$\alpha$ line is allowed to vary across the field of view.
In the case of cid_346 and S82X1940, we also allow small variations in the
broad NLR component.

We attempt the pixel-by-pixel analysis of the H$\alpha$ line only for the 15
targets that show extended H$\alpha$ emission from the analysis presented in
Sect. 3.2. Out of these 15 targets, 4 targets (X_N_53_3, X_N_66_23, cid_166
and cid_1605) did not have sufficient S/N per pixel to constrain the
parameters of individual Gaussian components. We note that deriving the PSF-
subtracted maps was possible despite the low S/N in these 4 targets as we
relied on the channel maps and not on Gaussian fits to verify the presence or
absence of residuals. The H$\alpha$ complex in the case of J1333+1649 is
contaminated by telluric features in the wings of the profile and in the case
of J1549+1245, the individual Gaussian components remained unconstrained,
which made the pixel-by-pixel analysis for these two targets unreliable. Fig.
9 shows an example of the line fitting in individual pixels for X_N_115_23 as
an example.

In figure 10, we show the BLR-subtracted H$\alpha$ kinematic maps of
X_N_160_22, X_N_115_23, cid_346 and S82X2058 as examples, while similar plots
for other targets are moved to the Appendix A. The left panels in Fig. 10
shows the H$\alpha$ centroid map, the middle panel shows the 10th percentile
velocity, $v_{10}$ and the right panel shows the H$\alpha$ width containing
80% of the line flux. The kinematic centre for the centroid map is obtained
from the location of the narrow H$\alpha$ emission in the integrated spectrum
(Sect. 3.1). Folding the information derived in Sect. 3.3, we now discuss the
possible origin of the observed kinematic properties of the H$\alpha$ line. We
attempt to distinguish between rotating disk signatures, mergers and
outflowing components. For a rotationally supported disk, we expect a smooth
gradient in the line centroid maps and a centrally peaked velocity dispersion
(in this case, $w_{80}$). On the other hand, galaxies undergoing mergers or
outflows will not necessarily show a centrally peaked velocity dispersion map
and/or an ordered velocity gradient in the centroid map. We discuss a few
examples of targets shown in Fig. 10.

X_N_160_22 does not show extended [O iii] emission, but shows extended
H$\alpha$ emission towards the north of the AGN location, evident in the PSF-
subtracted H$\alpha$ channel map in Fig. 2 and the centroid map in the left
panel of Fig. 10. The centroid map shows a smooth velocity gradient between
$\pm$60 km s-1. The $v_{10}$ and $w_{80}$ maps show maximum velocities of
$<$-600 km s-1 and $>$1000 km s-1, suggesting the presence of AGN outflows,
especially close to the AGN location. Considering that the extended H$\alpha$
emission is consistent with star formation, the H$\alpha$ velocity maps of
X_N_160_22 in Fig. 10 could be interpreted as a superposition of a rotating
medium (centroid map that shows a smooth gradient) and a turbulent medium
($v_{10}$ and $w_{80}$ maps that show high velocities near the AGN location).

In the case of X_N_115_23, the H$\alpha$ centroid value at the AGN location
appears blue-shifted and the $w_{80}$ map does not show a centrally peaked
profile, but shows a smooth gradient. The velocities in the $w_{80}$ map
reaches values between $\sim$850 – $>$1000 km s-1 suggesting that H$\alpha$
emission is tracing gas which is part of an outflow in the NLR. This is also
supported by the fact that the H$\alpha$ and [O iii] emission are spatially
extended in the same direction and that the extended emission is ionised by
the AGN (see BPT map in Fig. 5).

cid_346 shows a smooth velocity gradient in the centroid map with the major
axis orientated roughly along the NE direction and the $w_{80}$ map peaks at
$\sim$1300 km s-1 at the AGN location. The large dispersion value cannot be
explained purely as ordered rotation and therefore, we infer that the observed
H$\alpha$ emission is a combination of rotation from the host galaxy and AGN
outflows. Although the extended H$\alpha$ emission in this galaxy falls under
the AGN ionised region in Fig. 5, the presence of upper limits in the [N
ii]/H$\alpha$ ratio could suggest that star formation may play a role in the
ionisation and kinematics of the observed extended emission. However, the
current data does not allow us to definitely confirm this.

Lastly, S82X2058 shows a smooth velocity gradient in its H$\alpha$ centroid
map, but the centroid velocity profile is extended more towards the SE
direction from the AGN location. Accounting for the localised peak in the
$w_{80}$ map at the AGN location, this target shows a rotating system probably
in an interaction with another galaxy.

To summarize the results on the spatially resolved kinematic analysis of the
H$\alpha$ line: Six galaxies (X_N_160_22, X_N_81_44, X_N_4_48, cid_346,
S82X1940 and S82X2058) show smooth velocity gradients in their H$\alpha$
centroid maps. The velocity dispersion maps in these galaxies ($w_{80}$) show
localized peaks111The $w_{80}$ maps are sensitive to the line models derived
from the multiple Gaussian fits. Also the IFU data is noise limited,
especially in the outskirts of the galaxies and therefore the spatial profiles
in these velocity might not always look smooth, but can suggest underlying
patterns.. This suggests that in these six galaxies, part or most of the
H$\alpha$ emission traces the rotating gas. On the contrary, X_N_12_26,
X_N_115_23 and S82X1905 do not have smooth gradients in their centroid maps.
The extended H$\alpha$ emission in X_N_115_23 and S82X1905 is consistent with
ionisation by the AGN (Sect. 3.3) and therefore the absence of smooth gradient
in the H$\alpha$ centroid profile confirms that the H$\alpha$ emission is
dominated by AGN emission. The extended H$\alpha$ emission in X_N_12_26 is
highly asymmetric around the AGN location, which may suggests the presence of
companion galaxies. This is not a unique case: from the H$\alpha$ kinematic
maps, there are indications of companions also in the case of X_N_4_48,
S82X1940 and S82X2058.

Several galaxies presented in this paper show extended H$\alpha$ emission
blue-shifted or redshifted by several hundred km s-1 compared to the systemic
values. For instance, J1549+1245 shows an extended H$\alpha$ component at
$\sim$10 kpc from the AGN location, but this component is red-shifted by
$\sim$1800 km s-1 on extracting the spectra (Figure 3). Although the presence
of large scale outflows cannot be ruled out in this case, the presence of such
extended components might also suggest the presence of companions or the AGN
host galaxies in the process of a merger. Observations of some of the type 1
SUPER AGN in other wavelengths already suggest the presence of companions. For
instance, recent ALMA CO(4-3) observations of J1549+1245 confirmed the
presence of a companion at $>3\sigma$ significance (see Bischetti et al.,
2021) and therefore, the observed extended H$\alpha$ could be a part of a
tidal tail. Furthermore, archival HST observations of cid_166 and cid_346
already indicate possible presence of galaxies nearby (Fig. 11), which
suggests that galaxy interactions may be a common phenomenon at these
redshifts. We note here that cid_346 is surrounded by an extended CO halo,
which could also point to an over-density of galaxies around this source (see
Cicone et al., 2021). Although AGN hosted in interacting systems have been
reported to be rare at 1$<$z$<$2 (e.g., Cisternas et al., 2011; Mainieri et
al., 2011), this may also be due to observational biases or the limitation to
obtain better spatial resolution and high sensitivity at high redshift. In
fact, recent ALMA observations have revealed evidence of quasars residing in
interacting galaxies (e.g., Trakhtenbrot et al., 2017; Banerji et al., 2021).

##  5 Summary and conclusions

We presented the spatially resolved properties of the H$\alpha$ emission from
the K-band ($\sim$2–2.4$\mu$m) VLT/SINFONI observations of 21 type 1 AGN at
z$\sim$2.2 derived from the SUPER survey. The adaptive optics assisted
observations provided a spatial resolution of $\sim$2 kpc that allowed us to
infer the source of ionisation in the extended H$\alpha$ regions, after
accounting for beam-smearing effects due to the PSF. We used resolved BPT
analysis, [N ii]/H$\alpha$ ratios of the extended emission and a comparison
between the H$\alpha$ kinematics with that of the [O iii] emission, obtained
from the H-band observations presented in Kakkad et al. (2020), to infer if
the H$\alpha$ emission traces star formation. Lastly, we investigate if star-
forming regions and high velocity ionised outflows are spatially anti-
correlated. The main results of this paper are summarised below:

  * •

We tested three methods of H$\alpha$ emission line modelling in this paper
because the blending of [N ii]$\lambda\lambda$6549, 6585 and H$\alpha$
emission line components in the integrated spectra of type 1 AGN host galaxies
at z$\sim$2 can lead to degenerate results. We conclude that in order to
obtain unique solutions, the kinematic components of the H$\alpha$ emission
need to be coupled with the [O iii] emission.

  * •

The vast majority of the quasars show extended H$\alpha$ emission ($\sim$76%).
The extended emission is observed out to $\sim$3–9 kpc with a mean value of
$\sim$5 kpc. The width (FWHM) of the H$\alpha$ spectrum, extracted from the
extended regions, is in the range 73–784 km s-1 with a mean width of 312 km
s-1.

  * •

We find a correlation between the velocity shift, defined by the difference
between the extended H$\alpha$ location in the spectra with the expected
location based on its redshift, with the AGN luminosity and black hole mass.
This could indicate that the extended H$\alpha$ emission is dominated by
outflowing gas. The size of the extended H$\alpha$ emission, on the other
hand, shows possible correlations with the stellar mass of the host galaxy,
consistent with size-mass relations reported in the literature.

  * •

In four galaxies, we were able to constrain the flux ratios [O iii]/H$\beta$
and [N ii]/H$\alpha$ at the location of extended H$\alpha$ emission and place
them on the classical BPT maps. The H$\alpha$ emission in these four galaxies
is consistent with ionisation by star formation. For the rest of the targets,
we use [N ii]/H$\alpha$ ratio and the H$\alpha$ FWHM to identify the source of
ionisation. Overall, the extended H$\alpha$ emission in 4 galaxies is
consistent with ionisation by star formation ($\sim$25% of the targets that
show extended emission), in 5 galaxies by the AGN ($\sim$30%) and in 7
galaxies, the ionisation source could not be constrained ($\sim$45%).

  * •

We find a variety of dynamical properties in the host galaxies as traced by
the H$\alpha$ emission. Six out of nine galaxies for which pixel-by-pixel
emission line fitting was possible show smooth velocity gradients in the
H$\alpha$ centroid maps and their BPT diagrams are also consistent with
ionisation by star formation, suggesting that the H$\alpha$ emission traces
the host rotation and not the NLR. In two galaxies, the H$\alpha$ morphology
and kinematic maps are similar to that of [O iii] and along with the fact that
their BPT location is consistent with AGN ionisation, the H$\alpha$ emission
in these two galaxies traces the NLR. In four galaxies, the morphological and
kinematic characteristics of the H$\alpha$ emission may indicate the presence
of companions or AGN hosts being in mergers.

  * •

In two galaxies, we find evidence of negative AGN feedback on scales $>$2 kpc
as the extended H$\alpha$ emission in these galaxies avoid regions with high
velocity [O iii]-based ionised outflows. For the rest of the targets, there is
no strong evidence of AGN outflows having an impact on the host galaxy star
formation using the current data. ALMA Band 7 observations of a fraction of
galaxies show the prevalence of dust heated star formation at the centre of
the galaxy close to the AGN and the ionised outflow. The current SINFONI
observations are not sensitive to resolutions $<$2 kpc, therefore future high
spatial resolution observations with ELT-class IFS instruments such as HARMONI
will be required to constrain the real impact of the outflows by sampling
recent star formation in the proximity of the AGN location.

The current SINFONI K-band observations of most of the galaxies in the SUPER
survey have an on-source exposure time of $\sim$1–2 hours. Deeper observations
are, therefore, required with current or future facilities such as rest-frame
HST/FUV imaging, VLT/ERIS, VLT/HAWKI-GRAAL and ELT/HARMONI to distinguish
between the presence of outflows/inflows and possible presence of companions.
Finally, upcoming JWST observations in Cycle-1 (ID 2177) will use the mid-
infrared IFS capabilities of JWST/MIRI (e.g., Rieke et al., 2015), that will
allow us to detect dust-obscured star formation using the PAH 6.2 $\mu$m
emission, at a spatial resolution similar to those of SINFONI observations
presented in this paper.

## Acknowledgements

The authors would like to thank the anonymous referee for comments that
improved the paper. CMH acknowledges funding from an United Kingdom Research
and Innovation grant (code: MR/V022830/1). A.P. gratefully acknowledges
financial support from STFC through grants ST/T000244/1 and ST/P000541/1.
Based on observations collected at the European organisation for Astronomical
Research in the Southern Hemisphere under ESO programme 196.A-0377. For the
purpose of open access, the authors have applied a Creative Commons
Attribution (CC-BY) license to any author accepted version arising.

## Data Availability

The IFS data products will be made publicly available via ESO Phase 3 data
release.

## References

  * Alaghband-Zadeh et al. (2016) Alaghband-Zadeh S., Banerji M., Hewett P. C., McMahon R. G., 2016, MNRAS, 459, 999
  * Alatalo et al. (2015) Alatalo K., et al., 2015, ApJ, 798, 31
  * Baldwin et al. (1981) Baldwin J. A., Phillips M. M., Terlevich R., 1981, PASP, 93, 5
  * Balmaverde et al. (2016) Balmaverde B., et al., 2016, A&A, 585, A148
  * Banerji et al. (2021) Banerji M., Jones G. C., Carniani S., DeGraf C., Wagg J., 2021, MNRAS, 503, 5583
  * Baron et al. (2018) Baron D., et al., 2018, MNRAS, 480, 3993
  * Baron et al. (2020) Baron D., Netzer H., Davies R. I., Xavier Prochaska J., 2020, MNRAS, 494, 5396
  * Battisti et al. (2015) Battisti A. J., Calzetti D., Johnson B. D., Elbaz D., 2015, ApJ, 800, 143
  * Beckmann et al. (2017) Beckmann R. S., et al., 2017, MNRAS, 472, 949
  * Bessiere & Ramos Almeida (2022) Bessiere P. S., Ramos Almeida C., 2022, arXiv e-prints, p. arXiv:2202.06788
  * Bieri et al. (2016) Bieri R., Dubois Y., Silk J., Mamon G. A., Gaibler V., 2016, MNRAS, 455, 4166
  * Bischetti et al. (2017) Bischetti M., et al., 2017, A&A, 598, A122
  * Bischetti et al. (2021) Bischetti M., et al., 2021, A&A, 645, A33
  * Boquien et al. (2015) Boquien M., et al., 2015, A&A, 578, A8
  * Brusa et al. (2016) Brusa M., et al., 2016, A&A, 588, A58
  * Brusa et al. (2018) Brusa M., et al., 2018, A&A, 612, A29
  * Caglar et al. (2020) Caglar T., et al., 2020, A&A, 634, A114
  * Calzetti (2020) Calzetti D., 2020, Nature Astronomy, 4, 437
  * Cano-Díaz et al. (2012) Cano-Díaz M., Maiolino R., Marconi A., Netzer H., Shemmer O., Cresci G., 2012, A&A, 537, L8
  * Carniani et al. (2015) Carniani S., et al., 2015, A&A, 580, A102
  * Carniani et al. (2016) Carniani S., et al., 2016, A&A, 591, A28
  * Carniani et al. (2017) Carniani S., et al., 2017, A&A, 605, A105
  * Catalán-Torrecilla et al. (2015) Catalán-Torrecilla C., et al., 2015, A&A, 584, A87
  * Chen et al. (2020) Chen C.-C., et al., 2020, A&A, 635, A119
  * Cicone et al. (2021) Cicone C., et al., 2021, A&A, 654, L8
  * Circosta et al. (2018) Circosta C., et al., 2018, A&A, 620, A82
  * Circosta et al. (2021) Circosta C., et al., 2021, A&A, 646, A96
  * Cisternas et al. (2011) Cisternas M., et al., 2011, ApJ, 726, 57
  * Civano et al. (2016) Civano F., et al., 2016, ApJ, 819, 62
  * Costa et al. (2018) Costa T., Rosdahl J., Sijacki D., Haehnelt M. G., 2018, MNRAS, 473, 4197
  * Cresci & Maiolino (2018) Cresci G., Maiolino R., 2018, Nature Astronomy, 2, 179
  * Cresci et al. (2015) Cresci G., et al., 2015, ApJ, 799, 82
  * Davies et al. (2020) Davies R., et al., 2020, arXiv e-prints, p. arXiv:2003.06153
  * Dubois et al. (2013) Dubois Y., Gavazzi R., Peirani S., Silk J., 2013, MNRAS, 433, 3297
  * Dubois et al. (2016) Dubois Y., Peirani S., Pichon C., Devriendt J., Gavazzi R., Welker C., Volonteri M., 2016, MNRAS, 463, 3948
  * Dugan et al. (2014) Dugan Z., Bryan S., Gaibler V., Silk J., Haas M., 2014, ApJ, 796, 113
  * Eisenhauer et al. (2003) Eisenhauer F., et al., 2003, in Iye M., Moorwood A. F. M., eds, Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series Vol. 4841, Instrument Design and Performance for Optical/Infrared Ground-based Telescopes. pp 1548–1561 (arXiv:astro-ph/0306191), doi:10.1117/12.459468
  * Ellison et al. (2021) Ellison S. L., et al., 2021, MNRAS, 505, L46
  * Fabian (2012) Fabian A. C., 2012, ARA&A, 50, 455
  * Fiore et al. (2017) Fiore F., et al., 2017, A&A, 601, A143
  * Fluetsch et al. (2019) Fluetsch A., et al., 2019, MNRAS, 483, 4586
  * Förster Schreiber & Wuyts (2020) Förster Schreiber N. M., Wuyts S., 2020, ARA&A, 58, 661
  * Förster Schreiber et al. (2018) Förster Schreiber N. M., et al., 2018, ApJS, 238, 21
  * Fujimoto et al. (2018) Fujimoto S., et al., 2018, ApJ, 861, 7
  * Gabor & Bournaud (2014) Gabor J. M., Bournaud F., 2014, MNRAS, 441, 1615
  * Gaibler et al. (2012) Gaibler V., Khochfar S., Krause M., Silk J., 2012, MNRAS, 425, 438
  * Gallagher et al. (2019) Gallagher R., Maiolino R., Belfiore F., Drory N., Riffel R., Riffel R. A., 2019, MNRAS, 485, 3409
  * Gatkine et al. (2022) Gatkine P., Veilleux S., Perley D., Durbak J., Dichiara S., Cenko S. B., Troja E., 2022, ApJ, 926, 63
  * Gebhardt et al. (2000) Gebhardt K., et al., 2000, ApJ, 539, L13
  * Georgakakis & Nandra (2011) Georgakakis A., Nandra K., 2011, MNRAS, 414, 992
  * George et al. (2019) George K., et al., 2019, MNRAS, 487, 3102
  * Greene et al. (2011) Greene J. E., Zakamska N. L., Ho L. C., Barth A. J., 2011, ApJ, 732, 9
  * Guillard et al. (2015) Guillard P., Boulanger F., Lehnert M. D., Pineau des Forêts G., Combes F., Falgarone E., Bernard-Salas J., 2015, A&A, 574, A32
  * Gültekin et al. (2009) Gültekin K., et al., 2009, ApJ, 698, 198
  * Hao et al. (2011) Hao C.-N., Kennicutt R. C., Johnson B. D., Calzetti D., Dale D. A., Moustakas J., 2011, ApJ, 741, 124
  * Harrison et al. (2014) Harrison C. M., Alexander D. M., Mullaney J. R., Swinbank A. M., 2014, MNRAS, 441, 3306
  * Harrison et al. (2018) Harrison C. M., Costa T., Tadhunter C. N., Flütsch A., Kakkad D., Perna M., Vietri G., 2018, Nature Astronomy, 2, 198
  * Hirschmann et al. (2014) Hirschmann M., Dolag K., Saro A., Bachmann L., Borgani S., Burkert A., 2014, MNRAS, 442, 2304
  * Hodge et al. (2016) Hodge J. A., et al., 2016, ApJ, 833, 103
  * Hopkins & Beacom (2006) Hopkins A. M., Beacom J. F., 2006, ApJ, 651, 142
  * Husemann et al. (2016) Husemann B., Scharwächter J., Bennert V. N., Mainieri V., Woo J. H., Kakkad D., 2016, A&A, 594, A44
  * Husemann et al. (2017) Husemann B., Davis T. A., Jahnke K., Dannerbauer H., Urrutia T., Hodge J., 2017, MNRAS, 470, 1570
  * Ishibashi & Fabian (2012) Ishibashi W., Fabian A. C., 2012, MNRAS, 427, 2998
  * Jahnke et al. (2004) Jahnke K., Wisotzki L., Sánchez S. F., Christensen L., Becker T., Kelz A., Roth M. M., 2004, Astronomische Nachrichten, 325, 128
  * Jarvis et al. (2020) Jarvis M. E., et al., 2020, MNRAS, 498, 1560
  * Kakkad et al. (2016) Kakkad D., et al., 2016, A&A, 592, A148
  * Kakkad et al. (2017) Kakkad D., et al., 2017, MNRAS, 468, 4205
  * Kakkad et al. (2020) Kakkad D., et al., 2020, A&A, 642, A147
  * Kakkad et al. (2022) Kakkad D., et al., 2022, MNRAS, 511, 2105
  * Kalfountzou et al. (2017) Kalfountzou E., et al., 2017, MNRAS, 471, 28
  * Kauffmann et al. (2003) Kauffmann G., et al., 2003, MNRAS, 346, 1055
  * Kennicutt (1998) Kennicutt Jr. R. C., 1998, ARA&A, 36, 189
  * Kewley et al. (2013) Kewley L. J., Dopita M. A., Leitherer C., Davé R., Yuan T., Allen M., Groves B., Sutherland R., 2013, ApJ, 774, 100
  * Kim et al. (2022) Kim C., et al., 2022, arXiv e-prints, p. arXiv:2202.10044
  * Kormendy & Richstone (1995) Kormendy J., Richstone D., 1995, ARA&A, 33, 581
  * Koss et al. (2021) Koss M. J., et al., 2021, ApJS, 252, 29
  * LaMassa et al. (2016) LaMassa S. M., et al., 2016, ApJ, 817, 172
  * Lamperti et al. (2021) Lamperti I., et al., 2021, A&A, 654, A90
  * Lang et al. (2019) Lang P., et al., 2019, ApJ, 879, 54
  * Liu et al. (2016) Liu Z., et al., 2016, MNRAS, 459, 1602
  * Luo et al. (2017) Luo B., et al., 2017, ApJS, 228, 2
  * Luo et al. (2019) Luo R., Woo J.-H., Shin J., Kang D., Bae H.-J., Karouzos M., 2019, ApJ, 874, 99
  * Mainieri et al. (2011) Mainieri V., et al., 2011, A&A, 535, A80
  * Mainieri et al. (2021) Mainieri V., et al., 2021, The Messenger, 182, 45
  * Maiolino et al. (2017) Maiolino R., et al., 2017, Nature, 544, 202
  * Man et al. (2019) Man A. W. S., Lehnert M. D., Vernet J. D. R., De Breuck C., Falkendal T., 2019, A&A, 624, A81
  * Menzel et al. (2016) Menzel M. L., et al., 2016, MNRAS, 457, 110
  * Michiyama et al. (2020) Michiyama T., Iono D., Nakanishi K., Ueda J., Saito T., Yamashita T., Bolatto A., Yun M., 2020, ApJ, 895, 85
  * Nesvadba et al. (2020) Nesvadba N. P. H., Bicknell G. V., Mukherjee D., Wagner A. Y., 2020, A&A, 639, L13
  * Osterbrock & Ferland (2006) Osterbrock D. E., Ferland G. J., 2006, Astrophysics of gaseous nebulae and active galactic nuclei
  * Perna et al. (2015) Perna M., et al., 2015, A&A, 574, A82
  * Perna et al. (2020) Perna M., et al., 2020, A&A, 643, A139
  * Perna et al. (2021) Perna M., et al., 2021, A&A, 646, A101
  * Pillepich et al. (2018) Pillepich A., et al., 2018, MNRAS, 473, 4077
  * Puglisi et al. (2021) Puglisi A., et al., 2021, Nature Astronomy, 5, 319
  * Ramos Almeida et al. (2021) Ramos Almeida C., et al., 2021, arXiv e-prints, p. arXiv:2111.13578
  * Rauch et al. (2013) Rauch M., Becker G. D., Haehnelt M. G., Carswell R. F., Gauthier J. R., 2013, MNRAS, 431, L68
  * Richstone et al. (1998) Richstone D., et al., 1998, Nature, 385, A14
  * Rieke et al. (2015) Rieke G. H., et al., 2015, PASP, 127, 584
  * Rojas et al. (2020) Rojas A. F., et al., 2020, MNRAS, 491, 5867
  * Roos et al. (2015) Roos O., Juneau S., Bournaud F., Gabor J. M., 2015, ApJ, 800, 19
  * Rosario et al. (2018) Rosario D. J., et al., 2018, MNRAS, 473, 5658
  * Salomé et al. (2015) Salomé Q., Salomé P., Combes F., 2015, A&A, 574, A34
  * Schawinski et al. (2015) Schawinski K., Koss M., Berney S., Sartori L. F., 2015, MNRAS, 451, 2517
  * Schaye et al. (2015) Schaye J., et al., 2015, MNRAS, 446, 521
  * Scholtz et al. (2020) Scholtz J., et al., 2020, MNRAS, 492, 3194
  * Scholtz et al. (2021) Scholtz J., et al., 2021, MNRAS, 505, 5469
  * Schutte & Reines (2022) Schutte Z., Reines A. E., 2022, Nature, 601, 329
  * Shin et al. (2019) Shin J., Woo J.-H., Chung A., Baek J., Cho K., Kang D., Bae H.-J., 2019, ApJ, 881, 147
  * Shivaei et al. (2016) Shivaei I., et al., 2016, ApJ, 820, L23
  * Silk (2013) Silk J., 2013, ApJ, 772, 112
  * Silk & Rees (1998) Silk J., Rees M. J., 1998, A&A, 331, L1
  * Soltan (1982) Soltan A., 1982, MNRAS, 200, 115
  * Springel (2005) Springel V., 2005, MNRAS, 364, 1105
  * Steinborn et al. (2015) Steinborn L. K., Dolag K., Hirschmann M., Prieto M. A., Remus R.-S., 2015, MNRAS, 448, 1504
  * Tozzi et al. (2021) Tozzi G., et al., 2021, A&A, 648, A99
  * Trakhtenbrot et al. (2017) Trakhtenbrot B., Lira P., Netzer H., Cicone C., Maiolino R., Shemmer O., 2017, ApJ, 836, 8
  * Veilleux & Osterbrock (1987) Veilleux S., Osterbrock D. E., 1987, ApJS, 63, 295
  * Venturi et al. (2018) Venturi G., et al., 2018, A&A, 619, A74
  * Vietri et al. (2018) Vietri G., et al., 2018, A&A, 617, A81
  * Vietri et al. (2020) Vietri G., et al., 2020, A&A, 644, A175
  * Vietri et al. (2022) Vietri G., et al., 2022, A&A, 659, A129
  * Vogelsberger et al. (2014) Vogelsberger M., et al., 2014, MNRAS, 444, 1518
  * Ward et al. (2022) Ward S. R., Harrison C. M., Costa T., Mainieri V., 2022, MNRAS, 514, 2936
  * White & Rees (1978) White S. D. M., Rees M. J., 1978, MNRAS, 183, 341
  * Xie & Ho (2019) Xie Y., Ho L. C., 2019, ApJ, 884, 136
  * Yu & Tremaine (2002) Yu Q., Tremaine S., 2002, MNRAS, 335, 965
  * Zubovas & Bourne (2017) Zubovas K., Bourne M. A., 2017, MNRAS, 468, 4956
  * Zubovas et al. (2013a) Zubovas K., Nayakshin S., Sazonov S., Sunyaev R., 2013a, MNRAS, 431, 793
  * Zubovas et al. (2013b) Zubovas K., Nayakshin S., King A., Wilkinson M., 2013b, MNRAS, 433, 3079
  * van der Wel et al. (2014) van der Wel A., et al., 2014, ApJ, 788, 28

##  Appendix A Line fitting results using different methods

Table 3: H$\alpha$ line fitting parameters for the M2 model. The line fitting for J1441+0454 remained unconstrained and hence, not reported in this table. Target | $\lambda_{\rm range}$ | Aperture | FWHM | $L_{\rm H\alpha}$
---|---|---|---|---
|  |  | $v_{1}$ | $v_{2}$ | $v_{\rm BLR}$ | $L_{1}$ | $L_{2}$ | $L_{\rm BLR}$
| Å | arcsec | km/s | km/s | km/s | erg/s | erg/s | erg/s
X_N_160_22 | 6200–6900 | 0.9 | 287$\pm$53 | 2211$\pm$278 | 6807$\pm$260 | 42.68$\pm$0.13 | 43.84$\pm$2.90 | 44.28$\pm$0.01
X_N_81_44 | 6200–6900 | 0.9 | 990$\pm$82 | 2929$\pm$95 | 8250$\pm$313 | 43.27$\pm$0.06 | 44.02$\pm$0.14 | 44.16$\pm$0.02
X_N_53_3 | 6200–6900 | 0.8 | 345$\pm$213 | – | 4577$\pm$187 | 42.04$\pm$0.22 | – | 43.70$\pm$0.01
X_N_66_23 | 6200–6900 | 0.9 | – | – | 5640$\pm$182 | – | – | 43.72$\pm$0.01
X_N_35_20 | 6200–6900 | 0.5 | 532$\pm$63 | – | 6549$\pm$972 | 41.97$\pm$0.06 | – | 42.68$\pm$0.05
X_N_12_26 | 6200-6900 | 1.0 | 544$\pm$32 | – | 4615$\pm$100 | 42.80$\pm$0.04 | – | 43.95$\pm$0.01
X_N_44_64 | 6200–6900 | 0.5 | 411$\pm$17 | – | 7688$\pm$560 | 42.37$\pm$0.02 | – | 43.03$\pm$0.02
X_N_4_48 | 6200–6900 | 0.7 | 473$\pm$53 | – | 7596$\pm$303 | 42.79$\pm$0.06 | – | 44.18$\pm$0.01
X_N_102_35 | 6200–6900 | 0.3 | 535$\pm$151 | 3443$\pm$92 | 9070$\pm$588 | – | 43.71$\pm$0.17 | 43.67$\pm$0.02
X_N_115_23 | 6200–6900 | 0.9 | 376$\pm$52 | 1184$\pm$139 | 6862$\pm$162 | 42.85$\pm$0.11 | 43.25$\pm$0.07 | 44.16$\pm$0.01
cid_166 | 6200–6900 | 0.9 | 458$\pm$49 | 1968$\pm$260 | 6943$\pm$95 | 42.66$\pm$0.16 | 43.77$\pm$0.13 | 44.60$\pm$0.01
cid_1605 | 6200–6900 | 0.3 | 516$\pm$110 | – | 3802$\pm$80 | 41.96$\pm$0.15 | – | 43.27$\pm$0.01
cid_346 | 6200–6900 | 0.9 | 301$\pm$43 | 2884$\pm$156 | 7298$\pm$592 | 42.60$\pm$0.08 | 43.60$\pm$0.16 | 43.89$\pm$0.05
cid_1205 | 6200–6900 | 0.8 | 446$\pm$89 | – | 5023$\pm$183 | 42.04$\pm$0.12 | – | 43.46$\pm$0.01
cid_467 | 6200–6900 | 0.3 | 575$\pm$61 | – | 8750$\pm$285 | 42.37$\pm$0.05 | – | 43.86$\pm$0.01
J1333+1649 | 6350–7000 | 0.9 | 1059$\pm$415 | 4246$\pm$320 | 8839$\pm$304 | 43.87$\pm$0.16 | 45.28$\pm$3.27 | 45.30$\pm$0.03
J1549+1245 | 6200–6900 | 1.1 | 1045$\pm$35 | 4557$\pm$118 | 10495$\pm$208 | 44.23$\pm$0.02 | 41.73$\pm$3.87 | 45.50$\pm$0.01
S82X1905 | 6200–6900 | 1.0 | 920$\pm$58 | – | 5219$\pm$96 | 43.14$\pm$0.03 | – | 44.11$\pm$0.01
S82X1940 | 6200–6900 | 0.8 | 426$\pm$117 | 3001$\pm$713 | 6430$\pm$1138 | 42.78$\pm$1.45 | 43.15$\pm$4.49 | 43.69$\pm$0.28
S82X2058 | 6200-6900 | 0.9 | 481$\pm$75 | 3243$\pm$192 | 8809$\pm$455 | 42.43$\pm$0.11 | 40.88$\pm$3.82 | 43.95$\pm$0.03
Table 4: H$\alpha$ line fitting parameters for the M1 model. The emission line modelling using the M1 method for J1441+0454 and J1549+1245 remained unconstrained. Only those targets are shown for which the line fitting results were different from the ones in Table 3 i.e. for those targets where only H$\alpha$ components were sufficient to reproduce the H$\alpha$ complex. Target | $\lambda_{\rm range}$ | Aperture | FWHM | $L_{\rm H\alpha}$
---|---|---|---|---
|  |  | $v_{1}$ | $v_{2}$ | $v_{\rm BLR}$ | $L_{1}$ | $L_{2}$ | $L_{\rm BLR}$
| Å | arcsec | km/s | km/s | km/s | erg/s | erg/s | erg/s
X_N_160_22 | 6200–6900 | 0.9 | 296$\pm$44 | 2368$\pm$60 | 6742$\pm$188 | 42.68$\pm$0.07 | 43.95$\pm$0.02 | 44.28$\pm$0.01
X_N_81_44 | 6200–6900 | 0.9 | 1034$\pm$65 | 3168$\pm$104 | 8336$\pm$321 | 43.31$\pm$0.05 | 44.17$\pm$0.02 | 44.15$\pm$0.02
X_N_53_3 | 6200–6900 | 0.8 | 1527$\pm$623 | – | 4718$\pm$266 | 42.71$\pm$0.52 | – | 43.66$\pm$0.02
X_N_66_23 | 6200–6900 | 0.9 | 150$\pm$150 | – | 5638$\pm$167 | 41.44$\pm$0.33 | – | 43.72$\pm$0.01
X_N_115_23 | 6200–6900 | 0.9 | 527$\pm$27 | 3306$\pm$114 | 9339$\pm$344 | 43.10$\pm$0.02 | 43.82$\pm$0.03 | 44.10$\pm$0.02
cid_1605 | 6200–6900 | 0.3 | 1200$\pm$409 | – | 3887$\pm$217 | 42.26$\pm$0.35 | – | 43.27$\pm$0.02
J1333+1649 | 6350–7000 | 0.9 | 2354$\pm$657 | 4444$\pm$909 | 9058$\pm$492 | 44.47$\pm$0.33 | 45.38$\pm$3.01 | 45.30$\pm$0.05

Figure 12: Integrated K-band spectra of all targets for the fitting model used
in this paper.

Figure 13: Integrated K-band spectra of all targets for the fitting model used
in this paper (continued from Figure 12).

Figure 14: Same as Fig. 10