# A Hubble Space Telescope Imaging Survey of Low-Redshift Swift-BAT Active
Galaxies111Based on observations made with the NASA/ESA Hubble Space
Telescope, obtained at the Space Telescope Science Institute, which is
operated by the Association of Universities for Research in Astronomy, Inc.,
under NASA contract NAS5-26555. These observations are associated with program
#15444.

Minjin Kim  Department of Astronomy and Atmospheric Sciences, Kyungpook
National University, Daegu 702-701, Korea<EMAIL_ADDRESS>Aaron J.
Barth  Department of Physics and Astronomy, 4129 Frederick Reines Hall,
University of California, Irvine, CA 92697-4575, USA  Luis C. Ho  Kavli
Institute for Astronomy and Astrophysics, Peking University, Beijing 100871,
China<EMAIL_ADDRESS>Department of Astronomy, School of Physics, Peking
University, Beijing 100871, China  Suyeon Son  Department of Astronomy and
Atmospheric Sciences, Kyungpook National University, Daegu 702-701, Korea;
<EMAIL_ADDRESS>
###### Abstract

We present initial results from a Hubble Space Telescope snapshot imaging
survey of the host galaxies of Swift-BAT active galactic nuclei (AGN) at
$z<0.1$. The hard X-ray selection makes this sample sample relatively unbiased
in terms of obscuration compared to optical AGN selection methods. The high-
resolution images of 154 target AGN enable us to investigate the detailed
photometric structure of the host galaxies, such as the Hubble type and
merging features. We find that 48% and 44% of the sample is hosted by early-
type and late-type galaxies, respectively. The host galaxies of the remaining
8% of the sample are classified as peculiar galaxies because they are heavily
disturbed. Only a minor fraction of host galaxies (18%$-$25%) exhibit merging
features (e.g., tidal tails, shells, or major disturbance). The merging
fraction increases strongly as a function of bolometric AGN luminosity,
revealing that merging plays an important role in triggering luminous AGN in
this sample. However, the merging fraction is weakly correlated with the
Eddington ratio, suggesting that merging does not necessarily lead to an
enhanced Eddington ratio. Type 1 and type 2 AGN are almost indistinguishable
in terms of their Hubble type distribution and merging fraction. However, the
merging fraction of type 2 AGN peaks at a lower bolometric luminosity compared
with those of type 1 AGN. This result may imply that the triggering mechanism
and evolutionary stages of type 1 and type 2 AGN are not identical.

galaxies: active — galaxies: bulges — galaxies: fundamental parameters —
galaxies: photometry — quasars: general

##  1 Introduction

In massive galaxies that exhibit bulges, supermassive black holes (SMBHs) are
ubiquitous. The strong correlations between SMBH mass and the physical
properties (e.g., luminosity, velocity dispersion, and stellar mass) of the
spheroidal component of the host galaxy imply a causal connection between a
SMBH and its host galaxy in terms of their formation and evolution (Magorrian
et al. 1998; Gebhardt et al. 2000; Ferrarese & Merritt 2000; Kormendy & Ho
2013). According to theoretical studies, active galactic nuclei (AGN) that
originate from accreting SMBH play an important role in regulating BH growth
and star formation, which, in turn, can produce the strong correlations
between SMBHs and the properties of their host galaxies (Fabian 1999; Di
Matteo et al. 2005; Hopkins et al. 2005). In this model, SMBH growth and star
formation occur primarily during the AGN phase, which can be triggered by gas-
rich mergers or interactions with companion galaxies (Sanders et al. 1988;
Hopkins et al. 2008). Therefore, identifying the merging features of AGN hosts
is vital to understand the galaxy$-$host connection.

According to the AGN unification model, the accretion disk and broad-line
region are directly observed in type 1 AGN, while those central structures are
visually obscured by the sub-parsec dusty torus in type 2 AGN (Antonucci 1993;
Urry & Padovani 1995). On the contrary, if an AGN is mainly triggered by gas-
rich merging, then the gas and dust content in the central regions of the host
can be enhanced during the early stages of the merger (Blecha et al. 2018). A
late stage then occurs, in which the AGN-driven outflow can expel the
surrounding gas and dust so that the AGN is eventually observed to be type 1
(Sanders et al. 1988; Ishibashi & Fabian 2016). Therefore, the nucleus can be
naturally obscured due to the dense material in the host galaxy on spatial
scales larger than the dusty torus. According to this evolutionary sequence,
the host galaxies of type 2 AGN are more likely to be disturbed than those of
type 1 AGN, or might show an association with earlier merger stages. On the
other hand, Elitzur et al. (2014) argued that type 1 AGN can evolve to
intermediate-type (1.8-1.9), and finally to type 2 AGN as luminosity
decreases. In this light, investigating the physical properties of host
galaxies is crucial not only to determine the AGN triggering mechanism but
also to test AGN unification models. Host galaxy properties have been used to
test unified models for many AGN samples (e.g., Simcoe et al. 1997). Several
studies have found that the merging fraction for obscured AGN is higher than
that for unobscured AGN (e.g., Urrutia et al. 2008; Glikman et al. 2015;
Donley et al. 2018). Additionally, Compton-thick AGN appear to be
preferentially hosted by merging galaxies (Kocevski et al. 2015; Ricci et al.
2017b; Koss et al. 2018). Koss et al. (2011), however, argued that the
properties of the host galaxies of type 1 and type 2 AGN are
indistinguishable.

Numerous studies have investigated the properties of host galaxies of nearby
and distant AGN. One of the primary goals of those studies is to identify the
merging features in the AGN hosts as a possible origin of AGN triggering.
Several studies have claimed that nearby AGN are preferentially hosted by
galaxies that exhibit merging features compared with normal galaxies (Koss et
al. 2011; Hong et al. 2015; Goulding et al. 2018; Ellison et al. 2019; Marian
et al. 2020). In addition, luminous AGN are more likely to be associated with
merging or interaction than less luminous AGN (e.g., Treister et al. 2012; Kim
et al. 2017). However, some observational studies have found that there is no
evidence of an excess of merging fraction in various types of luminous AGN
(e.g., Dunlop et al. 2003; Cisternas et al. 2011; Böhm et al. 2013; Villforth
et al. 2014, 2017). For example, Zhao et al. (2019) argued that only a minor
fraction Type 2 quasar hosts (34%) are mergers, suggesting that major merging
plays only a limited role in triggering AGN. For narrow-line Seyfert 1 (NLS1)
galaxies, the fraction of barred hosts is significantly higher than the bar
fraction of ordinary Type 1 AGN, implying that this subclass is predominantly
triggered by internal secular evolution rather than by merging (Crenshaw et
al. 2003; Deo et al. 2006; Sani et al. 2010; Orban de Xivry et al. 2011; Kim
et al. 2017).

Figure 1:  Redshift and bolometric luminosity distributions of the parent
sample of Swift-BAT AGN (small gray dots). The Type 1 AGN observed for this
HST program are denoted by blue stars and blue histograms, while Type 2
objects are given by red circles and red histograms. Bolometric luminosity is
estimated from the intrinsic X-ray luminosity (Ricci et al. 2017) assuming a
bolometric correction of 8.

Finally, the photometric properties of host galaxies have been widely used to
explore the coevolution between SMBHs and host galaxies. The stellar
populations of AGN host galaxies can provide a useful constraint on the SMBH-
galaxy connection (e.g., Sánchez et al. 2004; Canalizo & Stockton 2013;
Matsuoka et al. 2014; Kim & Ho 2019; Zhao et al. 2019). Some studies have
shown that host galaxies of type 1 AGN tend to be bluer or overluminous
compared with inactive galaxies due to the former’s young stellar population
(e.g., Sánchez et al. 2004; Kim & Ho 2019). However, other investigations have
found no sign of young stellar populations in AGN hosts (e.g., Nolan et al.
2001; Bettoni et al. 2015). Additionally, the spheroid luminosity of type 1
AGN hosts has also been used to investigate the relation between BH mass
($M_{\rm BH}$) and bulge luminosity ($L_{\rm bul}$) (e.g., Kim et al. 2008;
Greene et al. 2010; Park et al. 2015; Kim & Ho 2019; Li et al. 2021).

The aforementioned studies have employed widely different sample selection
methods and datasets with diverse properties in terms of wavelength or filter
bands, spatial resolution, and depth, and these differences may be largely
responsible for the sometimes divergent conclusions reached in different
investigations. Thus, despite the large observational effort invested into AGN
host galaxy studies over many years, further work based on large, uniformly
selected samples with high-quality imaging data can still provide new
insights. Indeed, there have been several attempts to conduct imaging surveys
of nearby Seyferts using HST (e.g., Nelson et al. 1996; Malkan et al. 1998;
Schade et al. 2000). Those surveys used early HST images with a relatively
narrow field of view that did not always cover the full host galaxy (the Wide
Field Planetary Camera 1 and 2), and early snapshot programs with these
cameras obtained relatively shallow depth. Images of Type 1 AGN are often
saturated due to the bright nuclei, which makes it difficult to obtain a
robust decomposition to determine bulge properties accurately. Furthermore,
some of these studies (e.g., Malkan et al., 1998) observed samples selected
from highly heterogeneous criteria based on AGN catalogs available at the
time.

To overcome these limitations, we have used HST to conduct an imaging survey
of nearby AGN at $z<0.1$ selected from the Swift-BAT AGN catalog. Swift-BAT
AGN are identified from hard X-ray data that, compared with optical and
infrared data, is less affected by extinction and contamination from star
formation. Therefore, hard X-ray data provides a relatively uniform and
homogeneous sample in terms of obscuration, with the exception of very highly
obscured (Compton-thick) AGN. The deep and coherent high-resolution imaging
dataset from HST allows us to robustly investigate the structural properties
of the host galaxies for a large and uniformly selected sample. Moreover, the
Swift-BAT AGN sample has the benefit of extensive multiwavelength measurements
(e.g., BH mass, bolometric luminosity, Eddington ratio, hydrogen column
density, and optical classification) that have been carried out in numerous
studies (Koss et al. 2017; Oh et al. 2017; Ricci et al. 2017a). Hence, our
imaging survey is an excellent complement to the existing body of data for
this benchmark AGN sample, providing an excellent dataset to study the
detailed properties of nearby AGN hosts and to investigate the relationships
between AGN and host properties while minimizing sample selection biases.

Figure 2:  The distributions of BH mass and Eddington ratio of the sample.
$M_{\rm BH}$ is measured using the virial method, the $M_{\rm
BH}-\sigma_{\star}$ relation, or the $M_{\rm BH}-M_{\star}$ relation.

This paper presents a description of the morphological properties of the host
galaxies of these low-$z$ Swift-BAT AGN using newly acquired HST $I$-band
images for 154 objects. Our primary goal is to explore the connection between
the physical properties of AGN and those of their hosts. Section 2 describes
the sample selection, our imaging data, and the physical properties of the
sample. Section 3 presents visual morphological classifications. We discuss
the correlation between the morphological structures of the hosts and the
properties of the AGN in Section 4. A summary is given in Section 5. This work
adopts the following cosmological parameters: $H_{0}=100h=67.8$ km s-1 Mpc-1,
$\Omega_{m}=0.308$, and $\Omega_{\Lambda}=0.692$ (Planck Collaboration et al.
2016).

##  2 Sample and Data

###  2.1 Sample Selection

In 2017, the Space Telescope Science Institute announced a special mid-cycle
call proposals for “gap-filler” snapshot surveys to be conducted using the
Advanced Camera for Surveys (ACS) Wide-Field Camera (WFC). The programmatic
goal for this call was to provide large, full-sky catalogs of snapshot targets
that would be used to fill HST scheduling gaps, at lower priority than
standard general observer and snapshot programs. This survey (HST program
15444) was selected as one of three gap-filler programs in the 2017 call. The
proposal call dictated that the total duration of snapshot visits should be
$\lesssim 26$ minutes, which is sufficient to allow for two full-frame ACS/WFC
exposures with a total on-source exposure time of $\sim 700$ s after
acquisition and other overheads.

Our sample is drawn from the 70-month Swift-BAT X-ray source catalog
(Baumgartner et al. 2013). Since our primary science goals involve
morphological studies of AGN host galaxies, we focus on low-redshift objects,
and we selected Swift-BAT AGN at $z<0.1$. After cross-matching this catalog
with the HST archive, we excluded objects already having images in an $I$-band
equivalent filter (in most cases F814W) with the WF/PC2, ACS, or WFC3 cameras,
to avoid duplications. The remaining set of 543 objects provides an ideal gap-
filler sample with a large number of targets widely distributed over the full
sky. No cuts to the sample were made based on Galactic latitude or foreground
extinction, because HST $I$-band imaging could in principle provide new
morphological classifications and host galaxy structural information even for
targets in fields with moderate to high extinction that otherwise might not be
observed in other surveys. Figure 1 shows the distribution of redshifts and
bolometric luminosities for the parent Swift-BAT sample and for the set of 543
targets making up the sample for program 15444.

Figure 3:  Representative examples of various morphologiccal types: (a)
elliptical, (b) Sa spiral, (c) barred SBb spiral, and (d) peculiar. All images
are displayed on an asinh stretch.

###  2.2 Observations

Observations for Program 15444 began in 2018 March and are ongoing (at a low
rate) during the first half of 2021. This paper includes data taken through
2021 June. We used ACS/WFC with the F814W filter, which is approximately
equivalent to the $I$ band, to maximize the brightness contrast between the
host galaxy and the active nucleus. Suffering less dust attenuation than
filters at shorter wavelengths, F814W also allows us to better probe the
photometric substructures of the hosts. We obtained two dithered exposures per
target with integration times of 337 s, the minimum time required to avoid
buffer dump overheads. The AGN was centered on the WFC1 detector. For Type 1
(unobscured) AGN, a nuclear point source is generally expected to be present
at optical wavelengths (Nelson et al., 1996). Accordingly, we took an
additional 5 s exposure with the WFC1-B512 subarray to obtain an unsaturated
image of the nuclear point source and its immediate surroundings for objects
listed as Type 1 AGN by Baumgartner et al. (2013) or Koss et al. (2017). Of
the 157 AGN targeted for observations, useful data were obtained for 154
sources (Table 1), while three observations were lost due to guide star
acquisition failures. For other targets, delayed guide star acquisition led to
slightly shorter exposure times than the planned $2\times 337$ s (SWIFT
J0533.9$-$1318, SWIFT J0747.5+6057, and SWIFT J0753.1+4559). The set of 154
successfully observed targets includes 75 Type 1 and 79 Type 2 AGN.

Figure 4:  The distributions of bolometric luminosity ($L_{{\rm bol}}$) and
Eddington ratio ($L_{{\rm bol}}$/$L_{{\rm Edd}}$) for different morphological
classifications. The red, blue, and black histograms denote early-type
galaxies (E/S0), late-type galaxies with spiral arms (SA/SB), and peculiar
galaxies, respectively.

###  2.3 Data Reduction

For the long exposures, we adope the standard reduction provided by the
pipeline, including bias and dark subtraction, flat-field correction, and
correction for charge-transfer efficiency. The cosmic ray rejection was
performed when combining the two dithered images is imperfect. Therefore, we
additionally applied the LACosmic algorithm (van Dokkum 2001) to the
individual images to improve the cosmic ray rejection. We used the PyRAF task
TweakReg to determine a robust shift between the dithered images. The final
combined images, generated with AstroDrizzle, have a pixel scale of
$\sim$0$.\mkern-4.0mu^{\prime\prime}$05 and a field-of-view of $\sim
202$′′$\times 202$′′. We measured the variance of the sky values after masking
all objects to determine the depth of the images, which on average we estimate
to be $\sim 23.6$ mag arcsec-1 ($1\,\sigma$).

The short-exposure sub-array images for the type 1 objects exhibit horizontal
bands introduced by bias striping noise (Grogin et al. 2010, 2011), which were
removed separately with the acs_destripe_plus task. The saturated pixels in
the combined long-exposure image were replaced with the same pixels in the
short, unsaturated image. The short and long exposures were aligned using the
position of the nucleus. The central position of the nucleus for the long
exposures was determined after masking the saturated pixels.

###  2.4 Physical Properties of AGN

To investigate the connection between AGN and their host galaxies, we
assembled the optical spectral properties of the sample from the literature to
estimate physical properties such as BH mass, accretion rate, and bolometric
luminosity. For type 1 AGN, we use the virial method ($M_{\rm BH}\propto
Rv^{2}/G$) to estimate BH mass by combining the size ($R_{\rm BLR}$) and
velocity dispersion ($v$) of the broad-line region (BLR). The BLR size can be
estimated through reverberation mapping experiments (Blandford & McKee 1982)
and from single-epoch optical spectroscopy using the empirical relation
between $R_{\rm BLR}$ and AGN luminosity (Kaspi et al. 2000; Bentz et al.
2013). The intrinsic scatter of the BLR size-luminosity relation (Du et al.
2018; Fonseca Alvarez et al. 2020) introduces significant systematic
uncertainty into the BH masses derived from single-epoch spectra. For single-
epoch mass estimates, the assumption of a single virial scaling factor
contributes additional error to the mass estimates, since the true virial
factor for a given AGN will depend on the geometry and kinematics of the BLR.
While the mean virial factor has been determined by assuming that AGN follow
the same $M_{\rm BH}-\sigma_{\star}$ relation as the inactive galaxies, its
calibration appears to be sensitive morphologies of galaxies and types of AGNs
(e.g., Ho & Kim, 2014). Here, we recalculate the BH masses rather than using
the values from Koss et al. (2017). We adopt the virial mass estimator based
on H$\beta$ and 5100 Å AGN continuuum luminosity as calibrated by Ho & Kim
(2015) for all bulge types, using spectral measurements from Koss et al.
(2017) of 56 type 1 AGN. We use the scaling relations of Greene & Ho (2005) to
convert H$\alpha$ and H$\beta$ luminosities to 5100 Å AGN luminosity, and we
scale broad H$\alpha$ line widths and broad H$\beta$ line widths.

Figure 5:  Example images of subgroups based on the various merging
properties: (a) minor merger with tidal tail and single nucleus; (b) minor
merger with shell and single nucleus; (c) major merger with tidal tail and
double nuclei in separate hosts; and (d) major merger with tidal tail and
double nuclei in a single host. In panel (d), a close-up of the central region
is shown in the inset.  Figure 6:  Example images of different subgroups based
on their merging stages: (a) accompanying a galaxy with no (or weak) sign of
interaction (m1); (b) merging galaxy without the major disturbance of the host
(m2); (c) major disturbance but the companion galaxy is not yet merged (m3);
(d) merging host with two galaxies sharing a common envelope (m4).

For the Type 1 AGN lacking useful measurements of broad emission lines but
that do have available stellar velocity dispersion ($\sigma_{\star}$)
measurements, and for Type 2 objects having $\sigma_{\star}$ available, we
compute $M_{\rm BH}$ using the $M_{\rm BH}-\sigma_{\star}$ relation from
Kormendy & Ho (2013)222We use the $M_{\rm BH}-\sigma_{\star}$ relation for
classical bulges and elliptical galaxies: $\log(M_{\rm
BH}/M_{\odot})=8.49+4.38\log(\sigma_{*}/200\,{\rm km~{}s^{-1}})$..

For the remaining 63 objects without broad-line measurements or information on
$\sigma_{\star}$, we estimate $M_{\rm BH}$ from the total stellar mass of the
host galaxy ($M_{\star}$). Although the $M_{\rm BH}-M_{\star}$ relation is not
as tight as the $M_{\rm BH}-\sigma_{\star}$ relation, it can still yield
approximate BH masses. The $M_{\rm BH}-M_{\star}$ relation is sensitive to the
host galaxy morphological type. For the sake of simplicity, we adopt the
$M_{\rm BH}-M_{\star}$ relation for all galaxy types, which has an uncertainty
of $\sim 0.8$ dex (Greene et al. 2020)333We use the $M_{\rm BH}-M_{\star}$
relation for all galaxy types: $\log(M_{\rm
BH}/M_{\odot})=7.43+1.61\log({M_{\star}}/{3\times 10^{10}M_{\odot}})$.. We
obtain the integrated F814W-band flux of the host galaxy through elliptical
isophotal fitting of the observed images using the IRAF task ellipse, after
masking blended nearby galaxies and foreground stars using SExtractor (Bertin
& Arnouts 1996). For type 1 AGN, the nucleus is subtracted prior to isophotal
fitting using the point-spread function generated from isolated stars in the
science images (S. Son et al., in preparation). The $I$-band flux is corrected
for Galactic extinction (Schlafly & Finkbeiner 2011), and a $k$-correction is
applied according to the method described by Chilingarian et al. (2010) using
host galaxy $V-I_{\rm C}$ colors assigned based on the morphological
classification (Section 4.1; Fukugita et al. 1995). Along with the mass-to-
light ratio inferred from the $V-I_{\rm C}$ color (Into & Portinari 2013), the
integrated $I$-band luminosity then gives $M_{\star}$.

Note that assigning a fixed color based on galaxy morphology likely
overestimates the true stellar mass if AGN host galaxies preferentially
contain a younger stellar population (Sánchez et al. 2004; Zhao et al. 2019),
especially in systems with higher Eddington ratio (Kim & Ho 2019). However,
apart from later-type spirals with pseudo bulges (Zhao et al. 2021), the
effect of young stars may not be substantial in the $I$ band. Pseudo bulges
contribute $\lesssim 20\%$ to the total light in disk galaxies (e.g., Gao et
al. 2019). This, in conjunction with the fact that our sample has relatively
low Eddington ratios (median $\langle\log L_{\rm bol}$/$L_{\rm
Edd}\rangle=-1.5$), leads us to suspect that the systematic uncertainty due to
mass-to-light ratio should be small compared with the intrinsic scatter in the
$M_{\rm BH}-M_{\star}$ relation.

We use the intrinsic hard X-ray ($14-195$ keV) luminosity derived from
spectral fitting of the Swift-BAT data by Ricci et al. (2017a) to estimate the
bolometric luminosity using a conversion factor of 8 (Koss et al. 2017; Ricci
et al. 2017a)444X-ray measurements are unavailable for SWIFT J1737.7$-$5956A..
The AGN bolomteric luminosities range from $L_{\rm
bol}=10^{43.2}-10^{45.7}\,{\rm erg~{}s^{-1}}$, and, for Eddington luminosity
$L_{\rm Edd}=1.26\times 10^{38}(M_{\rm BH}/M_{\odot})\,{\rm erg~{}s^{-1}}$,
the Eddington ratios span $L_{{\rm bol}}$/$L_{{\rm Edd}}$ $=0.00018-18.2$.
Finally, we take the column density of neutral hydrogen ($N_{\rm H}$) deduced
from spectral analysis of the X-ray data, as assembled by Ricci et al.
(2017a). A lower limit of $N_{\rm H}\approx 10^{20}$ cm-2 yields negligible
obscuration along the line of sight. The distributions of BH mass and
Eddington ratio are displayed in Figure 2. The comparison reveals that the BH
masses of type 2 AGN are systematically higher than those of type 1 by $\sim
0.16$ dex. However, given the uncertainties of BH mass measurements ($0.3-0.8$
dex) and the different methods applied for the two populations, it is unclear
if this represents a genuine difference between the type 1 and type 2
subsamples.

Finally, we also estimate the axis ratio ($b/a$, where $b$ is the semi-minor
axis and $a$ is the semi-major axis) of the host galaxy using the results from
the elliptical isophotal analysis.

##  3 Analysis and Results

###  3.1 Morphological Classification

All the targets are classified into approximate morphological types, based on
visual inspection independently conducted by three of the authors (MK, AB,
LH). We assign the morphologies into four basic Hubble types: elliptical (E),
lenticular (S0), spiral (S), and peculiar. The disk galaxies are additionally
scrutinized for the possible presence of a bar (SA/SB) and the relative
prominence of their bulge and disk (Sa: bulge-dominated; Sb: intermediate
bulge; Sc: disk-dominated). Where disagreement arises among the three
classifiers, they reinspect the images until they reach convergence. The
classifications of the sample are summarized in Table 2. The sample is roughly
evenly divided between early-type hosts (74 or 48% E/S0) and late-type hosts
(67 or 44% spirals), with peculiar morphologies accounting for the minority
(13 or 8%). Representative examples of each Hubble type are given in Figure 3.

Figure 4 shows the distributions of Hubble type as a function of bolometric
luminosity and Eddington ratio. The ellipticals and peculiar galaxies appear
to be found preferentially in more luminous AGN. However, this trend is less
significant in Eddington ratio. We also find that there is no substantial
difference in the Hubble type distribution of type 1 versus type 2 AGN.

Figure 7:  Dependence of the merging fraction on bolometric luminosity, for
hosts with (a) a tidal tail or shell; (b) a major or minor merger; (c) tidal
features that belong to merging stages “m2”, “m3”, or “m4” (black histograms)
and those in the latest merging stages (“m4”; red histogram); (d) fraction of
hosts having double nuclei (“d” or “dd”). Each panel shows separate
distributions for all AGN, type 1 AGN, and type 2 AGN.  Figure 8:  Dependence
of the merging fraction on Eddington ratio, for hosts with (a) a tidal tail or
shell; (b) a major or minor merger; (c) tidal features that belong to merging
stages “m2”, “m3”, or “m4” (black histograms) and those in the latest merging
stages (“m4”; red histogram); (d) fraction of hosts having double nuclei (“d”
or “dd”). Each panel shows separate distributions for all AGN, type 1 AGN, and
type 2 AGN.

###  3.2 Signatures of Dynamical Perturbations

In addition to conventional morphological classification, we systematically
search for the presence of irregular, asymmetric, features that are indicative
of dynamical perturbations such as tidal interactions and galaxy-galaxy
mergers. As with the main morphological classification, three co-authors
visually examine the HST images based on four independent criteria. First, we
divide the hosts into three groups depending on the presence of a tidal tail
or shell. Second, hosts showing clear signs of interactions are identified, as
either a “major merger” for the hosts that exhibit interacting companions of
comparable brightness, or “minor merger” for those containing an apparent
companion of significantly lower brightness. Third, by analogy with a similar
classification scheme employed for luminous infrared galaxies (Haan et al.
2011; Stierwalt et al. 2013), we distinguish four merging stages: “m1” for
hosts having a companion galaxy with no obvious signs of interaction; “m2” for
hosts with signs of interaction, such as tidal tail or shell, but no major
disturbances; “m3” for hosts with major disturbances but a companion galaxy
that has not yet merged; “and m4” for hosts with two galaxies sharing a common
envelope. And fourth, the hosts are split into three subgroups according to
the presence of a double nucleus: “s” for hosts with a single nucleus; “d” for
hosts with double nuclei residing in a single host; and “dd” for hosts with
double nuclei in separate hosts.

The classifications based on the merging properties are listed in Table 2.
Example images of different subtypes are displayed in Figure 5, and Figure 6
shows cutout images of hosts in different merging stages. We find 38 objects
that are accompanied by tidal tails (27 objects) or shells (11 objects). Based
on signs of interactions, 38 objects are classified as merging galaxies, among
them 18 major mergers and 20 minor mergers. Intermediate and late merging
stages (i.e. “m2”, “m3”, or “m4”) can be assigned to 28 objects. Note that
this number of objects is slightly smaller than the values from other merging
indicators (38) because the merging stage is defined only if the body of the
companion galaxy is clearly seen in the science images. For example, a stellar
stream or faint shell is not considered as a companion galaxy in this
classification. Finally, only three objects appear to have double nuclei in a
single host (i.e. “d”), while four objects have double nuclei in separate
hosts (i.e. “dd”). We will discuss the physical connection between merging
features and AGN properties in Section 5.2. The merging fraction as a function
of different physical properties of AGN is summarized in Table 3.

##  4 Discussion

###  4.1 Type 1 vs. Type 2

Because our sample is identified from Swift-BAT hard X-ray data and targets
were selected for observation based on HST scheduling criteria unrelated to
any galaxy properties other than location on the sky, selection biases
resulting from X-ray obscuration or other AGN properties are minimized.
Therefore, it should be possible to obtain a statistically meaningful
comparison of the host properties of type 1 and type 2 AGN in this survey
sample. We find that there is no significant difference in Hubble type between
the hosts of the two types of AGN. Approximately $52,41$, and $7\%$ of the
type 1 targets and $44,46,$ and 10% of type 2 targets are hosted by early-
type, late-type, and peculiar galaxies, respectively. However, for the low-
luminosity AGN ($L_{{\rm bol}}$$\leq 10^{44.5}$ erg s-1), the early-type
fraction for type 2 ($\sim 48\%$) is marginally higher than that for type 1
($\sim 37\%$). In other words, out of 35 early-type hosts for type 2 AGN,
about half (18) contain low-luminosity AGN. On the contrary, out of 39 early-
type hosts for type 1 AGN, only 18% (7) contain low-luminosity AGN. However,
this luminosity dependence is not clearly detected in late-type hosts. We also
confirm this trend using the Kolmogorov-Smirnov test to examine the
distribution of bolometric luminosity of early-type hosts, finding that the
null hypothesis that the two subsamples (type 1 and type 2) are drawn from the
same population can be rejected with a confidence level of 99.9%.

It is worthwhile to note that the mean $M_{\rm BH}$ for type 2 AGN
($10^{8.20\pm 0.58}$$M_{\odot}$) is marginally higher than that for type 1 AGN
($10^{8.04\pm 0.78}$$M_{\odot}$) by $\sim 0.2$ dex. Therefore, the different
levels of luminosity dependence of Hubble type between type 1 and type 2 AGN
could originate from bias in the $M_{\rm BH}$ because galaxy morphology is a
strong function of the stellar mass of the host. To test this hypothesis, we
perform the same experiment using the subsample with $M_{\rm BH}$ ranging from
$10^{7.5}$$M_{\odot}$to $10^{9.5}$$M_{\odot}$, where the $M_{\rm BH}$
distributions of type 1 and type 2 AGN are similar. We again find that there
are different levels of luminosity dependence between type 1 and type 2 AGN,
indicating that such variation is not due to $M_{\rm BH}$ bias.

The merging properties in the host can also provide insight into the physical
connection between type 1 and type 2 AGN. In this study, we consider hosts in
relatively late stages (i.e. “m2”, “m3”, or “m4” in merging stages) as merging
hosts. The merging fractions for both types of AGN are nearly identical (16%
and 20% for type 1 and type 2, respectively). This is somewhat inconsistent
with previous studies of nearby obscured AGN, which claimed that obscured AGN
are more preferentially found in merging galaxies compared with unobscured AGN
(e.g., Donley et al. 2018; Ellison et al. 2019). This discrepancy could be due
to the fact that IR-selected obscured AGN have higher merging fractions
compared with optical and X-ray selected AGN.

We again divide the sample into two subgroups according to bolomteric
luminosity. For the low-luminosity AGN ($L_{{\rm bol}}$$\leq 10^{44.5}$ erg
s-1), the merging fraction for type 2 ($11^{+5.5}_{-4.4}$%555Note that the
error estimation in each bin is conducted using Jeffrey’s confidence interval,
which is known to be robust for a small sample size.) is marginally higher
than that for type 1 ($0^{+5.0}$%). This luminosity dependence of the merging
fraction is also seen in Figure 7. This trend is commonly detected in various
merging features (e.g., the existence of a tidal tail or shell, major or minor
merging, and the presence of double nuclei; Figure 7). More interestingly,
this discrepancy between type 1 and type 2 AGN disappears in the parameter
space of Eddington ratio (Figure 8). Therefore, bolometric luminosity appears
to be a main driver to determine the role merging plays in type 1 compared
with type 2 AGN.

In addition, the merging fraction of type 1 AGN peaks at a higher bolometric
luminosity compared with that of type 2 AGN. Taken at face value, this
indicates either (1) the AGN triggering mechanism is not only dependent upon
bolometric luminosity, but also differentiates somewhat between type 1 and
type 2 AGN, or (2) the types are in different evolutionary stages, in the
sense that type 2 precedes type 1.

Figure 9:  Double nuclei embedded in the host of (a) SWIFT J0234.6$-$0848 and
(b) SWIFT J1848.0$-$7832\. A close-up view of the central region is shown in
the inset.  Figure 10:  The distributions of the column density of neutral
hydrogen ($N_{\rm H}$) derived from X-ray observations (Ricci et al. 2017) for
different morphological classifications. The red, blue, and black histograms
denote early-type galaxies (E/S0), late-type galaxies with spiral arms
(SA/SB), and peculiar galaxies, respectively.  Figure 11:  Distribution of
host galaxt axis ratio ($b/a$) versus column density of neutral hydrogen
($N_{\rm H}$) derived from X-ray observations (Ricci et al. 2017) for type 1
AGN (blue stars and blue histograms) and type 2 (red circles and red
histograms) AGN.  Figure 12:  Dependence of the merging fraction on X-ray
absorbing column density $N_{\rm H}$, for hosts with (a) a tidal tail or
shell; (b) a major or minor merger; (c) tidal features that belong to merging
stages “m2”, “m3”, or “m4” (black histograms) and those in the latest merging
stages (“m4”; red histogram); (d) fraction of hosts having double nuclei (“d”
or “dd”). Each panel shows separate distributions for all AGN, type 1 AGN, and
type 2 AGN. As described in the text, the fraction of galaxies found to
contain double nuclei in this sample should be considered a lower limit,
because the $I$-band imaging is not sufficient to identify some heavily
obscured nuclei.

###  4.2 Triggering Mechanism of AGN

The relative importance of internal (secular) and external (merger-driven)
triggering of AGN is still not fully understood. While internal secular
evolution in the host is thought to be responsible for enhancing the gas
inflow toward a SMBH, for some AGN at least, galaxy merging is still regarded
as a primary mechanism that triggers luminous AGN (e.g., Hong et al. 2015; Kim
et al. 2017; Marian et al. 2020). The proximity of the target galaxies and
deep HST images with high spatial resolution make our dataset useful to
identify merging features. In this study, we compare visually identified
merging features and physical properties of AGN to investigate the role
merging plays in triggering AGN in the Swift-BAT sample.

We use four criteria to identify the merging features; merging fraction and
its trend are in very good agreement with one another (Figs. 7 and 8). While
these visual classifications are somewhat subjective and cannot capture the
full complexity of galaxy mergers, we use these classifications as a simple
proxy for the merger stage. Out of 154 targets, 28 ($\sim 18\%$) are
classified as mergers (i.e., “m2”, “m3”, or “m4” in the merging stage). This
is in good agreement with the result ($\sim 18\%$) derived using the SDSS
images from a similar sample (Koss et al., 2011). Zhao et al. (2021) reached a
similar conclusion from HST images of Palomar-Green QSOs at $z<0.5$; they
found that only 17% of the sample exhibits signs of interactions. However, our
estimation of merging fraction is significantly lower than that for nearby
luminous AGN (Hong et al. 2015; Gao et al. 2020; Marian et al. 2020). More
strikingly, the merging fraction for less luminous AGN in our sample ($L_{{\rm
bol}}$$\leq 10^{44.5}$ erg s-1) is dramatically lower than that for more
luminous AGN ($L_{{\rm bol}}$$>10^{44.5}$ erg s-1; $7.0^{+4.1}_{-2.6}$% versus
$25^{+4.6}_{-4.12}$%). Previous studies have shown that the merging fraction
can be as high as $\sim 40-45$% for relatively nearby luminous AGN ($L_{{\rm
bol}}$ $>10^{45}$ erg s-1). For example, Hong et al. (2015) claimed that the
merger fraction of luminous AGN at $z<0.3$ is $\sim 44$%. Marian et al. (2020)
analyzed ground-based optical images of luminous AGN at $z<0.2$ and reached a
similar conclusion (merging fraction of $\sim 41$%). Gao et al. (2020) also
showed that the merging fraction of less luminous AGN at $z<0.1$ ($L_{{\rm
bol}}$ $<10^{45}$ erg s-1) is as low as $\sim 20$% and that for more luminous
AGN at $z<0.6$ can be as high as $\sim 40$%. Using more distant AGN ($z\sim
0.7$) but with moderate luminosity ($10^{42.5}<$ $L_{{\rm bol}}$ $<10^{45.5}$
erg s-1), Villforth et al. (2014) found a merging fraction of $\sim 17$%. For
our sample, the merging fraction for $L_{{\rm bol}}$$\leq 10^{45}$ erg s-1 is
$\sim 17$%, and that for $L_{{\rm bol}}$ $>10^{45}$ erg s-1 is $\sim 23$%.
Therefore, our findings are in broad agreement with those of previous studies.
However, the merging fraction for luminous AGN appears to be systematically
lower than those from the literature. This discrepancy could be due to the
fact that our $z<0.1$ sample lacks highly luminous AGN ($L_{{\rm bol}}$
$>10^{45.5}$ erg s-1) that are better represented in more distant AGN samples.

As shown in Figure 7, the merging fraction dramatically increases as AGN
luminosity increases. This trend is in good agreement with those of previous
studies based on nearby and distant AGN (Treister et al. 2012; Kim et al.
2017; Ellison et al. 2019), suggesting that the luminous AGN are more likely
to be triggered by merging. To the contrary, this tendency is not clearly
observed in the comparison between the merging fraction and Eddington ratio
(Figure 8). Taken at face value, the merging fraction also marginally
increases as Eddington ratio increases. The merging fraction appears to peak
at around $\log$ $L_{{\rm bol}}$/$L_{{\rm Edd}}$$\sim-1.5$. This trend is more
prominent for type 1 AGN although the significance of this finding should be
further explored using larger sample sizes. It may also be related to the fact
that NLS1, which tend to have large Eddington ratio, are preferentially found
in non-merger barred hosts, revealing that lower mass BH can be efficiently
fueled at a high rate through secular processes (Crenshaw et al. 2003; Orban
de Xivry et al. 2011; Kim et al. 2017). Nevertheless, this finding suggests
that merging may not be necessary to enhance the Eddington ratio (see also
Weigel et al. 2018).

Using near-infrared ($K-$band) images obtained with adaptive optics for Swift-
BAT AGN, Koss et al. (2018) claimed that luminous obscured AGN have an excess
of late-stage mergers with double nuclei with a close separation ($d\leq
3$kpc) compared to unobscured AGN and inactive galaxies. Due to the high
spatial resolution of the HST images, our dataset is suitable to test this
finding independently, even though the obscuration tends to be more severe in
$I-$ band compared with $K-$band. In this study, we find only three objects
(SWIFT J0234.6$-$0848, SWIFT J1845.4+7211, and SWIFT J1848.0$-$7832; Figure 9)
that have double nuclei in a single merged host (i.e., “d” in the number of
nuclei). The separations between the two nuclei are
3$.\mkern-4.0mu^{\prime\prime}$7 (2.6 kpc), 1$.\mkern-4.0mu^{\prime\prime}$6
(1.5 kpc), and 3$.\mkern-4.0mu^{\prime\prime}$1 (4.5 kpc) for SWIFT
J0234.6$-$0848, SWIFT J1845.4+7211, and SWIFT J1848.0$-$7832, respectively.
Thus, two objects from our survey (SWIFT J0234.6$-$0848 and SWIFT
J1845.4+7211) satisfy the criteria ($d\leq 3$ kpc) for close-separation double
nuclei from Koss et al. (2018). For comparison, two objects (SWIFT
J0804.6+1045 and SWIFT J1845.4+7211) classified as close nuclei in Koss et al.
(2018) are also observed in this study. While SWIFT J1845.4+7211 is classified
as “d” based on the nuclear structure visible in the HST F814W data, SWIFT
J0804.6+1045 appears to have a single nucleus in the F814W image. This
indicates that $I$-band images will miss some double nuclei that can be
identified in longer-wavelength imaging at comparable resolution, as would be
expected for gas-rich mergers with highly obscured central regions.

Based on ground-based imaging surveys of nearby Swift-BAT AGN, several studies
have independently examined the merging fraction using different methods
(e.g., Koss et al., 2010, 2012; Cotini et al., 2013). For example, Koss et al.
(2010) found that the fractions of disturbed host galaxies and of close pairs
within 30 kpc in nearby sources ($z<0.05$) are $\sim 18$% and $\sim 24$%,
respectively. The merging fraction coincides with our finding. The fraction of
close pairs from this study ($\sim 33$%) is marginally higher than that from
Koss et al. (2010), although we do not impose any constraint on the distance
to the companion, and the imaging quality of the two studies in terms of the
depth and spatial resolution is not identical. Cotini et al. (2013) analyzed
ground-based images of nearby sources ($z<0.03$) to identify interacting
systems through quantitative methods (Conselice, 2003; Lotz et al., 2004).
They found that the merging fraction is $20^{+7}_{-5}$%, again in good
agreement with this study. Finally, Koss et al. (2012) used optical
spectroscopy and X-ray data to identify dual AGNs from the nearby Swift-BAT
AGN ($z<0.05$), and found that $\sim 10$% of the sample contains dual AGN.
They also found that the fraction of dual AGN increases with increasing AGN
luminosity, supporting the idea that merging plays an important role in
luminous AGN.

###  4.3 Connection between the Obscuration and Merging Properties

As discussed in Section 5.1 and claimed in previous studies, there are
marginal differences in the host properties between type 1 and type 2 AGN.
Observational studies have found that significant obscuration can originate
from dense material on larger scales in the host galaxy (e.g., Simcoe et al.
1997; Malkan et al. 1998; Malizia et al. 2020). In addition, theoretical and
observational studies have suggested that the central BH can be heavily
obscured during mergers (Sanders et al. 1988; Blecha et al. 2018). The hard
X-ray selection makes the Swift-BAT sample particularly useful for exploring
whether there is any connection between the degree of obscuration and the host
galaxy morphological type or inclination. Here, we compare the hydrogen column
density ($N_{\rm H}$) as a proxy of obscuration with the host properties of
our sample.

Figure 10 shows the distributions of column density for different
morphologies. Based on the Kolmogorov–Smirnov test, there is no significant
difference in $N_{\rm H}$ distributions between Hubble types. More
surprisingly, the majority of highly obscured AGN ($\log N_{\rm H}>10^{23}$
cm-1) are hosted by early-type galaxies. In addition, we compare the axis
ratio with the hydrogen column density (Figure 11), and find there is no
casual correlation between the two, and there is little difference in the axis
ratio distributions between type 1 and type 2 AGN. These findings might
indicate that the obscuration material is not physically related to the host
galaxy, but rather to the nuclear torus.

We also compare the merging properties with $N_{\rm H}$ (Figure 12). As type 1
AGN tend to have a smaller $N_{\rm H}$ than type 2 by nature, it is not
adequate to directly compare trends of type 1 and those of type 2 AGN.
However, it is intriguing that the merging fractions appear to peak at $\log
N_{\rm H}\sim 10^{20}$ cm-1 and $\log N_{\rm H}\sim 10^{22-23}$ cm-1. However,
it is difficult to understand the origin of this bimodality; it might imply
that the obscuration is somehow related to the various types of merging
properties (e.g., gas contents, orbital motion, mass ratio, and merging
stages). Contrary to our findings, previous observational studies claimed that
obscured AGN, as opposed to unobscured AGN, are more likely to be hosted by
galaxies that exhibit merging features (e.g., Urrutia et al. 2008; Kocevski et
al. 2015). However, because previous studies primarily relied on red AGN
selected from optical and IR bands (Glikman et al. 2015) or distant X-ray
selected AGN ($z>1$; Kocevski et al. 2015), the samples could be biased toward
either luminous AGN or high$-z$ environments, where merging plays a more
important role in BH growth than at the present epoch.

##  5 Summary

Through an intensive imaging survey of Swift-BAT AGN at $z<0.1$ using the HST,
we obtained coherent, deep $I-$band images for 154 targets. We conducted a
visual classification of the host galaxies based on Hubble type and merging
features. We also assembled AGN properties (BH mass, bolometric luminosity,
Eddington ratio, and neutral hydrogen column density) of the sample from the
literature, and compare them with the morphological properties of the hosts.
From this program, we obtain the following results:

  * •

Out of 154 targets, 74, 67, and 13 hosts are classified as early-type (E/S0),
late-type (SA/SB) and peculiar galaxies, respectively.

  * •

Using merger indicators including tidal tails and shells, we find 18%$-$25% of
the sample is hosted by the merging galaxies, which is broadly consistent with
the findings of previous studies. However, the merging fraction substantially
is larger for high-luminosity AGN ($L_{{\rm bol}}$ $>10^{44.5}$) compared with
less luminous AGN $L_{{\rm bol}}$ $\leq 10^{44.5}$ (25% versus 7%,
respectively). It suggests that the merging plays a more important role in
triggering luminous AGN in the Swift-BAT sample.

  * •

To test AGN unification models, we compare the host morphologies of Type 1 and
2 AGN. We find there is a negligible difference in terms of Hubble type and
merging fraction between these hosts. The merging fraction for Type 2 AGN,
however, peaks at a marginally lower AGN luminosity than that of Type 1 AGN,
implying that the triggering mechanism and/or evolutionary stage for Type 1
and Type 2 may differ somewhat.

  * •

Finally, we compare the neutral hydrogen column density and axis ratio to host
properties to investigate the origin of the obscuration. Although we did not
identify any clear trend as a result of this comparison, we find that merging
fractions appear to reach their maximum at $\log N_{\rm H}\sim 10^{20}$ cm-1
and $\log N_{\rm H}\sim 10^{22-23}$. Although this bimodality has yet to be
confirmed with a larger sample size, it could suggest that the physical origin
of obscuration is complex.

The dataset presented in this paper will have broad applications for
addressing other questions related to the physical connection between SMBHs
and ther host galaxies. For example, we are currently performing two-
dimensional imaging decomposition, and examining the $M_{\rm BH}-L_{\rm{bul}}$
relation for type 1 AGN. Our sample can also be combined with existing
archival HST data of other Swift-BAT AGN, which will enable us to investigate
the host galaxy statistical properties with a larger sample size. Finally, our
extensive imaging survey can be used to carry out detailed host-galaxy studies
of individual targets of interest among the nearby AGN population (e.g.,
Maksym et al., 2020).

We are grateful to the anonymous referee for the constructive comments. We are
grateful to STScI for supporting the gap-filler snapshot programs, and we
thank Amber Armstrong and Norman Grogin for their assistance in preparing the
Phase II program for this survey. LCH was supported by the National Science
Foundation of China (11721303, 11991052, 12011540375) and the National Key R&D
Program of China (2016YFA0400702). This work was supported by a National
Research Foundation of Korea (NRF) grant (No. 2020R1A2C4001753) funded by the
Korean government (MSIT) and under the framework of international cooperation
program managed by the National Research Foundation of Korea
(NRF-2020K2A9A2A06026245).

## References

  * Antonucci (1993) Antonucci, R. 1993, ARA&A, 31, 473
  * Baumgartner et al. (2013) Baumgartner, W. H., Tueller, J., Markwardt, C. B., et al. 2013, ApJS, 207, 19
  * Bentz et al. (2013) Bentz, M. C., Denney, K. D., Grier, C. J., et al. 2013, ApJ, 767, 149
  * Bertin & Arnouts (1996) Bertin, E., & Arnouts, S. 1996, A&AS, 117, 393
  * Bettoni et al. (2015) Bettoni, D., Falomo, R., Kotilainen, J. K., Karhunen, K., & Uslenghi, M. 2015, MNRAS, 454, 4103
  * Blandford & McKee (1982) Blandford, R. D., & McKee, C. F. 1982, ApJ, 255, 419
  * Blecha et al. (2018) Blecha, L., Snyder, G. F., Satyapal, S., & Ellison, S. L. 2018, MNRAS, 478, 3056
  * Böhm et al. (2013) Böhm, A., Wisotzki, L., Bell, E. F., et al. 2013, A&A, 549, A46
  * Canalizo & Stockton (2013) Canalizo, G., & Stockton, A. 2013, ApJ, 772, 132
  * Chilingarian et al. (2010) Chilingarian, I. V., Melchior, A.-L., & Zolotukhin, I. Y. 2010, MNRAS, 405, 1409
  * Cisternas et al. (2011) Cisternas, M., Jahnke, K., Inskip, K. J., et al. 2011, ApJ, 726, 57
  * Conselice (2003) Conselice, C. J. 2003, ApJS, 147, 1
  * Cotini et al. (2013) Cotini, S., Ripamonti, E., Caccianiga, A., et al. 2013, MNRAS, 431, 2661
  * Crenshaw et al. (2003) Crenshaw, D. M., Kraemer, S. B., & Gabel, J. R. 2003, AJ, 126, 1690
  * Deo et al. (2006) Deo, R. P., Crenshaw, D. M., & Kraemer, S. B. 2006, AJ, 132, 321
  * Di Matteo et al. (2005) Di Matteo, T., Springel, V., & Hernquist, L. 2005, Natur, 433, 604
  * Donley et al. (2018) Donley, J. L., Kartaltepe, J., Kocevski, D., et al. 2018, ApJ, 853, 63
  * Du et al. (2018) Du, P., Zhang, Z.-X., Wang, K., et al. 2018, ApJ, 856, 6
  * Dunlop et al. (2003) Dunlop, J. S., McLure, R. J., Kukula, M. J., et al. 2003, MNRAS, 340, 1095
  * Elitzur et al. (2014) Elitzur, M., Ho, L. C., & Trump, J. R. 2014, MNRAS, 438, 3340
  * Ellison et al. (2019) Ellison, S. L., Viswanathan, A., Patton, D. R., et al. 2019, MNRAS, 487, 2491
  * Fabian (1999) Fabian, A. C. 1999, MNRAS, 308, L39
  * Ferrarese & Merritt (2000) Ferrarese, L., & Merritt, D. 2000, ApJL, 539, L9
  * Fonseca Alvarez et al. (2020) Fonseca Alvarez, G., Trump, J. R., Homayouni, Y., et al. 2020, ApJ, 899, 73
  * Fukugita et al. (1995) Fukugita, M., Shimasaku, K., & Ichikawa, T. 1995, PASP, 107, 945
  * Gao et al. (2020) Gao, F., Wang, L., Pearson, W. J., et al. 2020, A&A, 637, A94
  * Gao et al. (2019) Gao, H., Ho, L. C., Barth, A. J., & Li, Z.-Y. 2019, ApJS, 244, 34
  * Gebhardt et al. (2000) Gebhardt, K., Bender, R., Bower, G., et al. 2000, ApJL, 539, L13
  * Glikman et al. (2015) Glikman, E., Simmons, B., Mailly, M., et al. 2015, ApJ, 806, 218
  * Goulding et al. (2018) Goulding, A. D., Greene, J. E., Bezanson, R., et al. 2018, PASJ, 70, S37
  * Greene & Ho (2005) Greene, J. E., & Ho, L. C. 2005, ApJ, 630, 122
  * Greene et al. (2020) Greene, J. E., Strader, J., & Ho, L. C. 2020, ARA&A, 58, 257
  * Greene et al. (2010) Greene, J. E., Peng, C. Y., Kim, M., et al. 2010, ApJ, 721, 26
  * Grogin et al. (2010) Grogin, N. A., Lim, P. L., Maybhate, A., Hook, R. N., & Loose, M. 2010, in Hubble after SM4. Preparing JWST, 54
  * Grogin et al. (2011) Grogin, N. A., Lim, P. L., Maybhate, A., Hook, R. N., & Loose, M. 2011, Post-SM4 ACS/WFC Bias Striping: Characterization and Mitigation, Instrument Science Report ACS 2011-05
  * Haan et al. (2011) Haan, S., Surace, J. A., Armus, L., et al. 2011, AJ, 141, 100
  * Ho & Kim (2014) Ho, L. C., & Kim, M. 2014, ApJ, 789, 17
  * Ho & Kim (2015) —. 2015, ApJ, 809, 123
  * Hong et al. (2015) Hong, J., Im, M., Kim, M., & Ho, L. C. 2015, ApJ, 804, 34
  * Hopkins et al. (2005) Hopkins, P. F., Hernquist, L., Cox, T. J., et al. 2005, ApJ, 630, 705
  * Hopkins et al. (2008) Hopkins, P. F., Hernquist, L., Cox, T. J., & Kereš, D. 2008, ApJS, 175, 356
  * Into & Portinari (2013) Into, T., & Portinari, L. 2013, MNRAS, 430, 2715
  * Ishibashi & Fabian (2016) Ishibashi, W., & Fabian, A. C. 2016, MNRAS, 463, 1291
  * Kaspi et al. (2000) Kaspi, S., Smith, P. S., Netzer, H., et al. 2000, ApJ, 533, 631
  * Kim & Ho (2019) Kim, M., & Ho, L. C. 2019, ApJ, 876, 35
  * Kim et al. (2017) Kim, M., Ho, L. C., Peng, C. Y., Barth, A. J., & Im, M. 2017, ApJS, 232, 21
  * Kim et al. (2008) Kim, M., Ho, L. C., Peng, C. Y., et al. 2008, ApJ, 687, 767
  * Kocevski et al. (2015) Kocevski, D. D., Brightman, M., Nandra, K., et al. 2015, ApJ, 814, 104
  * Kormendy & Ho (2013) Kormendy, J., & Ho, L. C. 2013, ARA&A, 51, 511
  * Koss et al. (2012) Koss, M., Mushotzky, R., Treister, E., et al. 2012, ApJL, 746, L22
  * Koss et al. (2010) Koss, M., Mushotzky, R., Veilleux, S., & Winter, L. 2010, ApJL, 716, L125
  * Koss et al. (2011) Koss, M., Mushotzky, R., Veilleux, S., et al. 2011, ApJ, 739, 57
  * Koss et al. (2017) Koss, M., Trakhtenbrot, B., Ricci, C., et al. 2017, ApJ, 850, 74
  * Koss et al. (2018) Koss, M. J., Blecha, L., Bernhard, P., et al. 2018, Natur, 563, 214
  * Li et al. (2021) Li, J. I. H., Shen, Y., Ho, L. C., et al. 2021, ApJ, 906, 103
  * Lotz et al. (2004) Lotz, J. M., Primack, J., & Madau, P. 2004, AJ, 128, 163
  * Magorrian et al. (1998) Magorrian, J., Tremaine, S., Richstone, D., et al. 1998, AJ, 115, 2285
  * Maksym et al. (2020) Maksym, W. P., Schmidt, J., Keel, W. C., et al. 2020, ApJL, 902, L18
  * Malizia et al. (2020) Malizia, A., Bassani, L., Stephen, J. B., Bazzano, A., & Ubertini, P. 2020, A&A, 639, A5
  * Malkan et al. (1998) Malkan, M. A., Gorjian, V., & Tam, R. 1998, ApJS, 117, 25
  * Marian et al. (2020) Marian, V., Jahnke, K., Andika, I., et al. 2020, ApJ, 904, 79
  * Matsuoka et al. (2014) Matsuoka, Y., Strauss, M. A., Price, III, T. N., & DiDonato, M. S. 2014, ApJ, 780, 162
  * Nelson et al. (1996) Nelson, C. H., MacKenty, J. W., Simkin, S. M., & Griffiths, R. E. 1996, ApJ, 466, 713
  * Nolan et al. (2001) Nolan, L. A., Dunlop, J. S., Kukula, M. J., et al. 2001, MNRAS, 323, 308
  * Oh et al. (2017) Oh, K., Schawinski, K., Koss, M., et al. 2017, MNRAS, 464, 1466
  * Orban de Xivry et al. (2011) Orban de Xivry, G., Davies, R., Schartmann, M., et al. 2011, MNRAS, 417, 2721
  * Park et al. (2015) Park, D., Woo, J.-H., Bennert, V. N., et al. 2015, ApJ, 799, 164
  * Planck Collaboration et al. (2016) Planck Collaboration, Ade, P. A. R., Aghanim, N., et al. 2016, A&A, 594, A13
  * Ricci et al. (2017a) Ricci, C., Trakhtenbrot, B., Koss, M. J., et al. 2017a, ApJS, 233, 17
  * Ricci et al. (2017b) Ricci, C., Bauer, F. E., Treister, E., et al. 2017b, MNRAS, 468, 1273
  * Sánchez et al. (2004) Sánchez, S. F., Jahnke, K., Wisotzki, L., et al. 2004, ApJ, 614, 586
  * Sanders et al. (1988) Sanders, D. B., Soifer, B. T., Elias, J. H., et al. 1988, ApJ, 325, 74
  * Sani et al. (2010) Sani, E., Lutz, D., Risaliti, G., et al. 2010, MNRAS, 403, 1246
  * Schade et al. (2000) Schade, D. J., Boyle, B. J., & Letawsky, M. 2000, MNRAS, 315, 498
  * Schlafly & Finkbeiner (2011) Schlafly, E. F., & Finkbeiner, D. P. 2011, ApJ, 737, 103
  * Simcoe et al. (1997) Simcoe, R., McLeod, K. K., Schachter, J., & Elvis, M. 1997, ApJ, 489, 615
  * Stierwalt et al. (2013) Stierwalt, S., Armus, L., Surace, J. A., et al. 2013, ApJS, 206, 1
  * Treister et al. (2012) Treister, E., Schawinski, K., Urry, C. M., & Simmons, B. D. 2012, ApJL, 758, L39
  * Urrutia et al. (2008) Urrutia, T., Lacy, M., & Becker, R. H. 2008, ApJ, 674, 80
  * Urry & Padovani (1995) Urry, C. M., & Padovani, P. 1995, PASP, 107, 803
  * van Dokkum (2001) van Dokkum, P. G. 2001, PASP, 113, 1420
  * Villforth et al. (2014) Villforth, C., Hamann, F., Rosario, D. J., et al. 2014, MNRAS, 439, 3342
  * Villforth et al. (2017) Villforth, C., Hamilton, T., Pawlik, M. M., et al. 2017, MNRAS, 466, 812
  * Weigel et al. (2018) Weigel, A. K., Schawinski, K., Treister, E., Trakhtenbrot, B., & Sanders, D. B. 2018, MNRAS, 476, 2308
  * Zhao et al. (2019) Zhao, D., Ho, L. C., Zhao, Y., Shangguan, J., & Kim, M. 2019, ApJ, 877, 52
  * Zhao et al. (2021) Zhao, Y., Ho, L. C., Shangguan, J., et al. 2021, ApJ, 911, 94

Fig. Set13. Images

Figure 13: HST F814W-band images of the target galaxies. Images for the entire
sample are available in the online figure set.

Table 1: The sample

Source Name | Alt. Name | R.A. | Dec. | $A_{V}$ | $z$ | Type | Obs. Date | log $L_{\rm bol}$ | log $M_{\rm BH}$ | M | log $\lambda$ | $b/a$ | log $N_{\rm H}$
---|---|---|---|---|---|---|---|---|---|---|---|---|---
|  | (deg.) | (deg.) | (mag) |  |  |  | (erg s-1) | ($M_{\odot}$) |  |  |  | (cm-2)
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | (10) | (11) | (12) | (13) | (14)
SWIFT J0001.0$-$0708 |  | 0.2032 | -7.1532 | 0.087 | 0.0375 | 1 | 2018-12-05 | 44.50 | 7.12 | H$\alpha$ | -0.72 | 0.63 | $22.19^{+0.07}_{-0.08}$
SWIFT J0001.6$-$7701 | Fairall 1203 | 0.4419 | -76.9540 | 0.160 | 0.0585 | 1 | 2018-12-23 | 44.82 | 8.75 | $M_{*}$ | -2.03 | 0.90 | $20.00^{+0.00}_{-0.00}$
SWIFT J0003.3+2737 |  | 0.8643 | 27.6548 | 0.164 | 0.0397 | 2 | 2019-01-22 | 44.57 | 7.85 | $\sigma_{*}$ | -1.38 | 0.37 | $22.86^{+0.12}_{-0.08}$
SWIFT J0005.0+7021 |  | 1.0082 | 70.3217 | 2.313 | 0.0964 | 1 | 2018-12-02 | 45.33 | 8.20 | $M_{*}$ | -0.97 | 0.87 | $22.61^{+0.07}_{-0.05}$
SWIFT J0006.2+2012 | Mrk 335 | 1.5813 | 20.2029 | 0.096 | 0.0259 | 1 | 2018-05-20 | 44.30 | 7.34 | H$\alpha$ | -1.14 | 0.87 | $20.48^{+0.03}_{-0.22}$
SWIFT J0036.3+4540 |  | 9.0874 | 45.6650 | 0.181 | 0.0476 | 1 | 2019-01-12 | 44.80 | 8.54 | $M_{*}$ | -1.84 | 0.52 | $20.00^{+0.00}_{-0.00}$
SWIFT J0100.9$-$4750 | ESO 195-IG 021 NED03 | 15.1457 | -47.8676 | 0.037 | 0.0484 | 2 | 2018-03-31 | 44.84 | 8.42 | $\sigma_{*}$ | -1.68 | 0.39 | $22.57^{+0.03}_{-0.04}$
SWIFT J0123.9$-$5846 | Fairall 9 | 20.9408 | -58.8057 | 0.071 | 0.0460 | 1 | 2018-12-25 | 45.32 | 8.38 | H$\alpha$ | -1.16 | 0.85 | $20.00^{+0.00}_{-0.00}$
SWIFT J0128.4+1631 | CGCG 459-058 | 22.1017 | 16.4593 | 0.199 | 0.0387 | 1 | 2019-01-22 | 44.57 | 6.51 | H$\alpha$ | -0.04 | 0.49 | $23.30^{+0.18}_{-0.04}$
SWIFT J0134.1$-$3625 | NGC 612 | 23.4906 | -36.4933 | 0.055 | 0.0298 | 2 | 2018-12-25 | 45.23 | 8.99 | $\sigma_{*}$ | -1.86 | 0.86 | $23.97^{+0.11}_{-0.07}$
SWIFT J0157.2+4715 |  | 29.2956 | 47.2666 | 0.409 | 0.0478 | 1 | 2019-01-13 | 44.84 | 7.85 | H$\alpha$ | -1.11 | 0.82 | $20.00^{+0.00}_{-0.00}$
SWIFT J0202.4+6824A |  | 30.5720 | 68.3620 | 3.094 | 0.0119 | 2 | 2019-01-20 | 43.38 | 8.94 | $M_{*}$ | -3.66 | 0.81 | $22.23^{+0.35}_{-0.45}$
SWIFT J0202.4+6824B |  | 30.3850 | 68.4061 | 3.085 | 0.0152 | 2 | 2019-01-20 | 43.50 | 9.04 | $M_{*}$ | -3.64 | 0.86 | $22.10^{+0.13}_{-0.69}$
SWIFT J0206.2$-$0019 | Mrk 1018 | 31.5666 | -0.2914 | 0.075 | 0.0430 | 1 | 2019-01-11 | 45.01 | 8.00 | H$\alpha$ | -1.09 | 0.64 | $20.00^{+0.00}_{-0.00}$
SWIFT J0234.6$-$0848 | NGC 985 | 38.6574 | -8.7876 | 0.090 | 0.0430 | 1 | 2019-01-16 | 45.02 | 8.43 | H$\alpha$ | -1.51 | 0.93 | $20.92^{+0.09}_{-0.06}$
SWIFT J0243.9+5324 | 2MFGC 02171 | 41.0125 | 53.4745 | 1.040 | 0.0364 | 2 | 2019-01-12 | 44.29 | 7.83 | $M_{*}$ | -1.64 | 0.25 | $22.72^{+0.17}_{-0.12}$
SWIFT J0333.3+3720 |  | 53.3282 | 37.3030 | 1.465 | 0.0547 | 1 | 2019-01-11 | 45.14 | 8.15 | H$\alpha$ | -1.11 | 0.80 | $21.36^{+0.16}_{-0.20}$
SWIFT J0347.0$-$3027 |  | 56.7729 | -30.3972 | 0.030 | 0.0950 | 1 | 2018-12-21 | 45.18 | 7.76 | $M_{*}$ | -0.68 | 0.72 | $20.00^{+0.00}_{-0.00}$
SWIFT J0356.9$-$4041 |  | 59.2356 | -40.6960 | 0.023 | 0.0747 | 2 | 2018-12-19 | 45.22 | 8.74 | $M_{*}$ | -1.62 | 0.86 | $22.66^{+0.03}_{-0.04}$
SWIFT J0405.3$-$3707 | ESO 359- G 019 | 61.2570 | -37.1875 | 0.016 | 0.0552 | 1 | 2019-01-13 | 44.77 | 8.18 | $M_{*}$ | -1.51 | 0.61 | $20.00^{+0.00}_{-0.00}$
SWIFT J0429.6$-$2114 |  | 67.4095 | -21.1622 | 0.067 | 0.0700 | 1 | 2018-11-26 | 45.00 | 8.72 | H$\alpha$ | -1.82 | 0.70 | $20.00^{+0.00}_{-0.00}$
SWIFT J0443.9+2856 |  | 70.9450 | 28.9718 | 2.028 | 0.0217 | 1 | 2018-11-13 | 44.48 | 8.08 | $M_{*}$ | -1.70 | 0.82 | $22.34^{+0.03}_{-0.03}$
SWIFT J0446.4+1828 | UGC 3157 | 71.6240 | 18.4609 | 1.646 | 0.0158 | 1 | 2019-01-21 | 43.91 | 6.69 | H$\alpha$ | -0.88 | 0.80 | $23.78^{+0.21}_{-0.19}$
SWIFT J0456.3$-$7532 | ESO 033- G 002 | 73.9957 | -75.5412 | 0.400 | 0.0181 | 2 | 2018-12-14 | 44.13 | 8.44 | $M_{*}$ | -2.41 | 0.92 | $22.51^{+0.40}_{-0.31}$
SWIFT J0504.6$-$7345 |  | 76.1425 | -73.8242 | 0.335 | 0.0451 | 2 | 2020-10-02 | 44.52 | 8.58 | $M_{*}$ | -2.16 | 0.40 | $21.91^{+0.14}_{-0.14}$
SWIFT J0510.7+1629 | IRAS 05078+1626 | 77.6896 | 16.4989 | 0.820 | 0.0173 | 1 | 2019-01-19 | 44.72 | 7.64 | H$\alpha$ | -1.02 | 0.66 | $21.08^{+0.07}_{-0.10}$
SWIFT J0516.2$-$0009 | Ark 120 | 79.0476 | -0.1498 | 0.349 | 0.0325 | 1 | 2018-11-28 | 45.11 | 8.68 | H$\alpha$ | -1.67 | 0.82 | $20.00^{+0.00}_{-0.00}$
SWIFT J0526.2$-$2118 | ESO 553- G 043 | 81.6135 | -21.2866 | 0.116 | 0.0277 | 2 | 2019-01-22 | 44.30 | 8.05 | $\sigma_{*}$ | -1.85 | 0.85 | $23.30^{+0.07}_{-0.07}$
SWIFT J0528.1$-$3933 |  | 82.0086 | -39.5791 | 0.073 | 0.0369 | 2 | 2020-05-31 | 44.37 | 8.20 | $M_{*}$ | -1.93 | 0.49 | $21.68^{+0.22}_{-0.28}$
SWIFT J0533.9$-$1318 |  | 83.4589 | -13.3553 | 0.371 | 0.0290 | 2 | 2019-10-23 | 44.52 | 8.51 | $M_{*}$ | -2.09 | 0.71 | $23.76^{+0.19}_{-0.33}$
SWIFT J0544.4$-$4328 |  | 86.0000 | -43.4240 | 0.132 | 0.0446 | 2 | 2021-04-07 | 44.45 | 7.40 | $M_{*}$ | -1.05 | 0.46 | $22.81^{+0.14}_{-0.19}$
SWIFT J0552.5+5929 |  | 88.1169 | 59.4756 | 0.511 | 0.0585 | 1 | 2018-11-19 | 44.96 | 8.35 | $M_{*}$ | -1.49 | 0.82 | $20.00^{+0.00}_{-0.00}$
SWIFT J0623.9$-$6058 | ESO 121-IG 028 | 95.9400 | -60.9790 | 0.158 | 0.0405 | 2 | 2018-12-14 | 44.98 | 9.04 | $M_{*}$ | -2.16 | 0.87 | $23.31^{+0.05}_{-0.04}$
SWIFT J0641.3+3257 |  | 100.3252 | 32.8254 | 0.414 | 0.0486 | 2 | 2018-12-22 | 45.15 | 8.12 | $\sigma_{*}$ | -1.07 | 0.96 | $23.12^{+0.05}_{-0.06}$
SWIFT J0645.9+5303 |  | 101.6108 | 53.0758 | 0.207 | 0.0359 | 2 | 2020-04-14 | 44.41 | 8.06 | $M_{*}$ | -1.75 | 0.96 | $22.34^{+0.16}_{-0.15}$
SWIFT J0707.1+6433 |  | 106.8047 | 64.5997 | 0.104 | 0.0797 | 1 | 2019-01-16 | 45.10 | 8.56 | $M_{*}$ | -1.56 | 0.90 | $20.00^{+0.00}_{-0.00}$
SWIFT J0709.0$-$4642 |  | 107.1803 | -46.7137 | 0.298 | 0.0468 | 2 | 2018-12-22 | 44.74 | 8.25 | $\sigma_{*}$ | -1.61 | 0.66 | $22.40^{+0.16}_{-0.12}$
SWIFT J0736.9+5846 | Mrk 9 | 114.2374 | 58.7704 | 0.160 | 0.0399 | 1 | 2019-01-11 | 44.40 | 7.84 | H$\alpha$ | -1.54 | 0.97 | $20.46^{+0.28}_{-0.31}$
SWIFT J0743.0+6513 | Mrk 78 | 115.6739 | 65.1771 | 0.097 | 0.0366 | 2 | 2019-01-06 | 44.49 | 8.27 | $M_{*}$ | -1.88 | 0.58 | $24.15^{+0.11}_{-0.13}$
SWIFT J0743.3$-$2546 |  | 115.8114 | -25.7639 | 1.969 | 0.0238 | 1 | 2018-12-17 | 44.30 | 7.39 | H$\alpha$ | -1.19 | 0.96 | $20.95^{+0.25}_{-1.65}$
SWIFT J0747.5+6057 | Mrk 10 | 116.8714 | 60.9335 | 0.128 | 0.0294 | 1 | 2019-01-10 | 44.36 | 7.54 | H$\alpha$ | -1.28 | 0.45 | $20.53^{+0.22}_{-0.12}$
SWIFT J0747.6$-$7326 |  | 116.9098 | -73.4314 | 1.128 | 0.0359 | 2 | 2019-12-27 | 44.61 | 8.84 | $M_{*}$ | -2.33 | 0.99 | $23.56^{+0.19}_{-0.16}$
SWIFT J0753.1+4559 | B3 0749+460A | 118.1842 | 45.9493 | 0.226 | 0.0516 | 1 | 2019-01-08 | 44.83 | 8.38 | H$\alpha$ | -1.65 | 0.94 | $20.00^{+0.00}_{-0.00}$
SWIFT J0756.3$-$4137 |  | 119.0817 | -41.6284 | 2.116 | 0.0210 | 2 | 2019-01-16 | 43.90 | 6.94 | H$\alpha$ | -1.14 | 0.56 | $21.77^{+0.07}_{-0.07}$
SWIFT J0759.8$-$3844 |  | 119.9242 | -38.7322 | 2.225 | 0.0402 | 1 | 2019-02-03 | 45.15 | 8.52 | H$\alpha$ | -1.47 | 0.73 | $20.00^{+0.00}_{-0.00}$
SWIFT J0800.1+2638 | IC 0486 | 120.0874 | 26.6135 | 0.111 | 0.0266 | 1 | 2018-12-29 | 44.59 | 7.06 | H$\alpha$ | -0.57 | 0.75 | $22.06^{+0.12}_{-0.11}$
SWIFT J0801.9$-$4946 |  | 120.4915 | -49.7784 | 0.709 | 0.0405 | 1 | 2020-05-11 | 44.80 | 9.23 | $M_{*}$ | -2.53 | 0.36 | $21.18^{+0.14}_{-0.18}$
SWIFT J0804.6+1045 | MCG +02-21-013 | 121.1933 | 10.7767 | 0.073 | 0.0349 | 2 | 2018-12-28 | 44.55 | 8.21 | $\sigma_{*}$ | -1.76 | 0.41 | $23.02^{+0.15}_{-0.22}$
SWIFT J0805.1$-$0110 |  | 121.2208 | -1.1466 | 0.071 | 0.0915 | 2 | 2021-03-26 | 45.39 | 8.45 | $\sigma_{*}$ | -1.16 | 0.47 | $23.46^{+0.16}_{-0.31}$
SWIFT J0807.9+3859 | Mrk 622 | 121.9210 | 39.0042 | 0.138 | 0.0232 | 2 | 2018-05-25 | 44.32 | 6.74 | H$\alpha$ | -0.52 | 0.95 | $24.10^{+1.90}_{-0.43}$
SWIFT J0819.2$-$2259 |  | 124.7410 | -22.8770 | 0.335 | 0.0346 | 1 | 2020-05-03 | 44.39 | 8.31 | $M_{*}$ | -2.02 | 0.75 | $20.00^{+0.00}_{-0.00}$
SWIFT J0823.4$-$0457 | Fairall 272 | 125.7546 | -4.9349 | 0.125 | 0.0222 | 2 | 2018-04-08 | 44.66 | 8.14 | $\sigma_{*}$ | -1.58 | 0.48 | $23.53^{+0.05}_{-0.04}$
SWIFT J0840.2+2947 | 4C +29.30 | 130.0099 | 29.8174 | 0.153 | 0.0647 | 2 | 2019-01-21 | 45.28 | 8.77 | $\sigma_{*}$ | -1.59 | 0.85 | $23.80^{+0.11}_{-0.10}$
SWIFT J0855.6+6425 | MCG +11-11-032 | 133.8023 | 64.3959 | 0.279 | 0.0362 | 2 | 2019-01-05 | 44.66 | 8.35 | $\sigma_{*}$ | -1.79 | 0.42 | $23.31^{+0.13}_{-0.13}$
SWIFT J0902.7$-$4814 |  | 135.6555 | -48.2261 | 4.222 | 0.0391 | 1 | 2020-07-31 | 44.90 | 5.54 | $M_{*}$ | 1.26 | 0.77 | $22.15^{+0.13}_{-0.22}$
SWIFT J0923.7+2255 | MCG +04-22-042 | 140.9292 | 22.9090 | 0.120 | 0.0333 | 1 | 2019-01-11 | 44.87 | 7.54 | H$\alpha$ | -0.77 | 0.57 | $20.00^{+0.00}_{-0.00}$
SWIFT J0924.2$-$3141 |  | 140.9739 | -31.6919 | 0.408 | 0.0426 | 2 | 2020-04-27 | 45.00 | 8.05 | $M_{*}$ | -1.15 | 0.75 | $24.42^{+0.09}_{-0.07}$
SWIFT J0925.2$-$8423 |  | 141.5735 | -84.3593 | 0.540 | 0.0629 | 1 | 2018-12-28 | 44.85 | 7.81 | $M_{*}$ | -1.06 | 0.78 | $22.40^{+0.08}_{-0.12}$
SWIFT J0936.2$-$6553 |  | 144.0260 | -65.8093 | 0.640 | 0.0393 | 2 | 2018-12-25 | 44.50 | 7.97 | $M_{*}$ | -1.57 | 0.59 | $22.60^{+0.35}_{-2.60}$
SWIFT J0942.2+2344 | CGCG 122-055 | 145.5200 | 23.6853 | 0.069 | 0.0217 | 1 | 2019-01-19 | 43.98 | 7.35 | H$\alpha$ | -1.47 | 0.77 | $20.78^{+0.33}_{-1.22}$
SWIFT J0947.6$-$3057 | MCG -05-23-016 | 146.9173 | -30.9489 | 0.295 | 0.0083 | 1 | 2019-01-23 | 44.40 | 6.62 | H$\alpha$ | -0.32 | 0.45 | $22.18^{+0.03}_{-0.04}$
SWIFT J1020.5$-$0237B |  | 154.9941 | -2.5767 | 0.112 | 0.0595 | 1 | 2019-01-19 | 44.60 | 8.58 | H$\beta$ | -2.08 | 0.94 | $20.00^{+0.00}_{-0.00}$
SWIFT J1021.7$-$0327 | ARK 241 | 155.4177 | -3.4539 | 0.123 | 0.0410 | 1 | 2019-01-17 | 44.72 | 8.15 | $M_{*}$ | -1.53 | 0.89 | $20.00^{+0.00}_{-0.00}$
SWIFT J1029.8$-$3821 | ESO 317- G 038 | 157.4400 | -38.3486 | 0.199 | 0.0151 | 2 | 2021-05-11 | 43.65 | 7.41 | $\sigma_{*}$ | -1.86 | 0.35 | $23.41^{+0.42}_{-0.30}$
SWIFT J1031.9$-$1418 |  | 157.9763 | -14.2809 | 0.183 | 0.0851 | 1 | 2019-10-30 | 45.67 | 8.73 | H$\alpha$ | -1.16 | 0.93 | $20.00^{+0.00}_{-0.00}$
SWIFT J1032.7$-$2835 | ESO 436- G 034 | 158.1855 | -28.6101 | 0.170 | 0.0121 | 2 | 2021-03-12 | 43.60 | 8.07 | $\sigma_{*}$ | -2.57 | 0.27 | $22.85^{+0.21}_{-0.14}$
SWIFT J1033.6+7303 | CGCG 333-038 | 158.5981 | 73.0140 | 0.343 | 0.0224 | 1 | 2021-03-12 | 44.06 | 8.01 | $M_{*}$ | -2.05 | 0.53 | $22.62^{+0.17}_{-0.21}$
SWIFT J1038.8$-$4942 |  | 159.6883 | -49.7816 | 1.360 | 0.0602 | 1 | 2021-03-12 | 45.15 | 8.56 | H$\beta$ | -1.51 | 0.80 | $22.73^{+0.05}_{-0.05}$
SWIFT J1040.7$-$4619 |  | 160.0939 | -46.4238 | 0.424 | 0.0238 | 2 | 2019-01-16 | 44.21 | 8.52 | $\sigma_{*}$ | -2.41 | 0.60 | $22.60^{+0.03}_{-0.02}$
SWIFT J1042.4+0046 |  | 160.5349 | 0.7017 | 0.153 | 0.0952 | 2 | 2021-03-12 | 45.30 | 7.89 | $M_{*}$ | -0.69 | 0.33 | $22.20^{+0.14}_{-0.12}$
SWIFT J1043.4+1105 | SDSS J104326.47+110524.2 | 160.8603 | 11.0901 | 0.075 | 0.0480 | 1 | 2021-03-12 | 44.73 | 8.29 | H$\alpha$ | -1.66 | 0.85 | $20.00^{+0.00}_{-0.00}$
SWIFT J1059.8+6507 |  | 164.9315 | 65.0684 | 0.070 | 0.0835 | 2 | 2018-07-30 | 45.16 | 8.45 | $\sigma_{*}$ | -1.39 | 0.79 | $22.53^{+0.10}_{-0.10}$
SWIFT J1132.9+1019A | IC 2921 | 173.2053 | 10.2965 | 0.090 | 0.0440 | 1 | 2019-01-22 | 44.72 | 7.84 | H$\alpha$ | -1.22 | 0.41 | $21.52^{+0.23}_{-0.22}$
SWIFT J1136.7$-$6007 |  | 174.1752 | -60.0519 | 2.599 | 0.0142 | 2 | 2019-01-25 | 43.87 | 7.92 | $M_{*}$ | -2.15 | 0.48 | $22.43^{+0.15}_{-0.20}$
SWIFT J1139.1+5913 | SBS 1136+594 | 174.7870 | 59.1990 | 0.041 | 0.0616 | 1 | 2018-03-28 | 45.14 | 8.21 | H$\alpha$ | -1.17 | 0.53 | $20.00^{+0.00}_{-0.00}$
SWIFT J1143.7+7942 | UGC 06728 | 176.3168 | 79.6815 | 0.278 | 0.0063 | 1 | 2020-03-02 | 43.28 | 6.01 | H$\alpha$ | -0.83 | 0.78 | $20.00^{+0.00}_{-0.00}$
SWIFT J1148.3+0901 |  | 176.9795 | 9.0413 | 0.074 | 0.0693 | 1 | 2019-01-10 | 45.02 | 8.63 | H$\alpha$ | -1.71 | 0.62 | $20.00^{+0.00}_{-0.00}$
SWIFT J1200.2$-$5350 |  | 180.6985 | -53.8355 | 0.562 | 0.0277 | 2 | 2020-09-02 | 44.81 | 7.98 | $\sigma_{*}$ | -1.27 | 0.52 | $22.46^{+0.02}_{-0.03}$
SWIFT J1211.3$-$3935 |  | 182.8095 | -39.5574 | 0.233 | 0.0609 | 2 | 2019-01-11 | 45.16 | 8.57 | $\sigma_{*}$ | -1.51 | 0.49 | $22.19^{+0.06}_{-0.08}$
SWIFT J1213.1+3239A | CGCG 187-022 | 183.2888 | 32.5964 | 0.034 | 0.0248 | 2 | 2018-12-17 | 44.18 | 7.75 | $\sigma_{*}$ | -1.67 | 0.45 | $23.74^{+0.29}_{-0.46}$
SWIFT J1217.2$-$2611 | ESO 505-IG 030 | 184.2380 | -26.2093 | 0.224 | 0.0393 | 2 | 2020-04-24 | 44.60 | 7.79 | $M_{*}$ | -1.29 | 0.26 | $23.28^{+0.06}_{-0.20}$
SWIFT J1248.2$-$5828 |  | 191.9910 | -58.5001 | 1.649 | 0.0279 | 2 | 2020-07-15 | 44.08 | 8.03 | $M_{*}$ | -2.05 | 0.34 | $22.46^{+0.23}_{-0.20}$
SWIFT J1306.4$-$4025B |  | 196.8004 | -40.4076 | 0.280 | 0.0159 | 2 | 2019-01-13 | 43.79 | 7.68 | $M_{*}$ | -1.99 | 0.61 | $20.00^{+0.00}_{-0.00}$
SWIFT J1315.8+4420 | UGC 08327 NED02 | 198.8220 | 44.4071 | 0.052 | 0.0355 | 2 | 2018-04-23 | 44.63 | 8.67 | $\sigma_{*}$ | -2.14 | 0.69 | $22.88^{+0.07}_{-0.05}$
SWIFT J1316.9$-$7155 |  | 199.2262 | -71.9242 | 0.699 | 0.0703 | 1 | 2018-12-26 | 45.16 | 9.03 | H$\beta$ | -1.97 | 0.86 | $20.00^{+0.00}_{-0.00}$
SWIFT J1322.2$-$1641 | MCG -03-34-064 | 200.6019 | -16.7286 | 0.215 | 0.0168 | 1 | 2019-01-18 | 44.32 | 7.14 | H$\alpha$ | -0.92 | 0.69 | $23.80^{+0.02}_{-0.02}$
SWIFT J1332.0$-$7754 |  | 203.1692 | -77.8446 | 0.577 | 0.0098 | 2 | 2020-03-30 | 43.60 | 8.78 | $M_{*}$ | -3.28 | 0.52 | $23.80^{+0.12}_{-0.08}$
SWIFT J1333.5$-$3401 | ESO 383-18 | 203.3587 | -34.0148 | 0.163 | 0.0128 | 2 | 2020-04-13 | 43.85 | 6.94 | $M_{*}$ | -1.19 | 0.41 | $23.31^{+0.03}_{-0.02}$
SWIFT J1336.0+0304 | NGC 5231 | 203.9510 | 2.9990 | 0.066 | 0.0216 | 2 | 2019-01-13 | 44.06 | 7.95 | $\sigma_{*}$ | -1.99 | 0.72 | $22.34^{+0.04}_{-0.02}$
SWIFT J1338.2+0433 | NGC 5252 | 204.5665 | 4.5426 | 0.095 | 0.0229 | 2 | 2018-06-18 | 45.00 | 8.87 | $\sigma_{*}$ | -1.97 | 0.56 | $22.43^{+0.02}_{-0.02}$
SWIFT J1341.5+6742 | NGC 5283 | 205.2740 | 67.6723 | 0.052 | 0.0103 | 2 | 2019-10-26 | 43.23 | 8.87 | $\sigma_{*}$ | -3.74 | 0.85 | $23.15^{+0.08}_{-0.10}$
SWIFT J1345.5+4139 | NGC 5290 | 206.3299 | 41.7126 | 0.019 | 0.0085 | 2 | 2018-07-19 | 43.36 | 7.76 | $\sigma_{*}$ | -2.50 | 0.46 | $21.96^{+0.08}_{-0.06}$
SWIFT J1349.7+0209 | UM 614 | 207.4701 | 2.0791 | 0.077 | 0.0331 | 1 | 2019-01-03 | 44.51 | 7.50 | H$\alpha$ | -1.09 | 0.49 | $21.18^{+0.10}_{-0.07}$
SWIFT J1354.5+1326 |  | 208.6211 | 13.4659 | 0.077 | 0.0633 | 2 | 2019-01-15 | 44.89 | 7.74 | $M_{*}$ | -0.95 | 0.38 | $23.34^{+0.12}_{-0.09}$
SWIFT J1416.9$-$1158 |  | 214.2084 | -11.9829 | 0.183 | 0.0992 | 1 | 2018-08-15 | 45.53 | 9.05 | H$\beta$ | -1.62 | 0.79 | $20.00^{+0.00}_{-0.00}$
SWIFT J1421.4+4747 | SBS 1419+480 | 215.3742 | 47.7902 | 0.048 | 0.0727 | 1 | 2018-08-16 | 45.27 | 8.54 | H$\alpha$ | -1.37 | 0.58 | $20.00^{+0.00}_{-0.00}$
SWIFT J1424.2+2435 | NGC 5610 | 216.0954 | 24.6144 | 0.060 | 0.0169 | 2 | 2018-12-18 | 43.99 | 7.81 | $\sigma_{*}$ | -1.92 | 0.40 | $22.56^{+0.06}_{-0.10}$
SWIFT J1431.2+2816 |  | 217.7700 | 28.2873 | 0.057 | 0.0461 | 1 | 2019-01-16 | 44.52 | 8.93 | $M_{*}$ | -2.51 | 0.73 | $20.00^{+0.00}_{-0.00}$
SWIFT J1457.8$-$4308 | IC 4518A | 224.4216 | -43.1321 | 0.429 | 0.0158 | 2 | 2020-06-14 | 44.18 | 6.89 | $M_{*}$ | -0.81 | 0.34 | $23.36^{+0.09}_{-0.08}$
SWIFT J1506.7+0353B |  | 226.6840 | 3.8620 | 0.132 | 0.0373 | 2 | 2019-01-11 | 44.62 | 7.49 | $\sigma_{*}$ | -0.97 | 0.88 | $22.18^{+0.07}_{-0.08}$
SWIFT J1513.8$-$8125 |  | 228.6751 | -81.3939 | 0.744 | 0.0687 | 1 | 2020-07-02 | 45.40 | 8.71 | H$\alpha$ | -1.41 | 0.58 | $20.00^{+0.00}_{-0.00}$
SWIFT J1546.3+6928 |  | 236.6014 | 69.4861 | 0.114 | 0.0378 | 2 | 2021-03-19 | 44.62 | 9.18 | $\sigma_{*}$ | -2.66 | 0.27 | $23.49^{+0.24}_{-0.18}$
SWIFT J1548.5$-$1344 | NGC 5995 | 237.1040 | -13.7578 | 0.439 | 0.0244 | 1 | 2019-01-18 | 44.68 | 7.01 | H$\alpha$ | -0.43 | 0.82 | $21.97^{+0.06}_{-0.07}$
SWIFT J1605.9$-$7250 |  | 241.3470 | -72.8990 | 0.257 | 0.0900 | 2 | 2020-07-08 | 45.66 | 9.42 | $M_{*}$ | -1.86 | 0.61 | $23.18^{+0.10}_{-0.10}$
SWIFT J1643.2+7036 | NGC 6232 | 250.8343 | 70.6325 | 0.121 | 0.0149 | 2 | 2021-05-06 | 44.15 | 7.43 | $\sigma_{*}$ | -1.38 | 0.85 | $24.35^{+0.43}_{-0.19}$
SWIFT J1648.0$-$3037 |  | 252.0635 | -30.5845 | 0.935 | 0.0310 | 1 | 2018-05-27 | 44.89 | 7.67 | $M_{*}$ | -0.88 | 0.58 | $21.40^{+0.29}_{-0.50}$
SWIFT J1652.3+5554 |  | 253.0780 | 55.9055 | 0.053 | 0.0291 | 2 | 2018-08-24 | 44.37 | 8.74 | $M_{*}$ | -2.47 | 0.36 | $22.70^{+0.08}_{-0.07}$
SWIFT J1731.3+1442 |  | 262.8058 | 14.7155 | 0.264 | 0.0826 | 1 | 2021-06-07 | 45.16 | 9.00 | $M_{*}$ | -1.94 | 0.77 | $20.00^{+0.00}_{-0.00}$
SWIFT J1737.7$-$5956A |  | 264.4128 | -59.9407 | 0.205 | 0.0171 | 2 | 2020-09-02 |  $\cdots$ | 8.41 | $M_{*}$ |  $\cdots$ | 0.81 | $-9.00^{+0.00}_{-0.00}$
SWIFT J1741.9$-$1211 | 2E 1739.1-1210 | 265.4802 | -12.1991 | 1.591 | 0.0369 | 1 | 2020-08-01 | 45.07 | 8.04 | H$\alpha$ | -1.07 | 0.46 | $21.40^{+0.08}_{-0.08}$
SWIFT J1747.7$-$2253 |  | 266.8739 | -22.8791 | 2.794 | 0.0467 | 1 | 2018-08-19 | 44.93 | 8.99 | H$\alpha$ | -2.16 | 0.91 | $22.41^{+0.28}_{-0.37}$
SWIFT J1747.8+6837A | Mrk 507 | 267.1599 | 68.7044 | 0.106 | 0.0551 | 1 | 2018-11-14 | 44.35 | 7.21 | H$\alpha$ | -0.96 | 0.64 | $20.00^{+0.00}_{-0.00}$
SWIFT J1747.8+6837B | VII Zw 742 | 266.7493 | 68.6102 | 0.103 | 0.0630 | 1 | 2020-03-15 | 44.59 | 7.20 | H$\alpha$ | -0.71 | 0.86 | $20.00^{+0.00}_{-0.00}$
SWIFT J1748.8$-$3257 |  | 267.2297 | -32.9145 | 4.482 | 0.0200 | 1 | 2018-07-06 | 44.43 | 7.67 | H$\alpha$ | -1.34 | 0.61 | $21.38^{+0.07}_{-0.02}$
SWIFT J1800.3+6637 |  | 270.0304 | 66.6151 | 0.124 | 0.0265 | 2 | 2018-08-19 | 44.55 | 8.88 | $M_{*}$ | -2.43 | 0.62 | $24.02^{+0.23}_{-0.16}$
SWIFT J1807.9+1124 |  | 271.9580 | 11.3470 | 0.365 | 0.0787 | 1 | 2021-06-04 | 45.45 | 8.82 | H$\alpha$ | -1.47 | 0.73 | $21.54^{+0.06}_{-0.09}$
SWIFT J1824.2+1845 |  | 276.0451 | 18.7691 | 0.572 | 0.0661 | 1 | 2021-06-13 | 45.16 | 7.88 | H$\alpha$ | -0.82 | 0.86 | $22.43^{+0.13}_{-0.12}$
SWIFT J1824.3$-$5624 | IC 4709 | 276.0808 | -56.3692 | 0.242 | 0.0167 | 2 | 2021-05-28 | 44.36 | 8.08 | $M_{*}$ | -1.82 | 0.32 | $23.15^{+0.05}_{-0.07}$
SWIFT J1826.8+3254 |  | 276.6350 | 32.8583 | 0.294 | 0.0221 | 2 | 2018-08-11 | 44.22 | 7.72 | $\sigma_{*}$ | -1.60 | 0.31 | $22.98^{+0.11}_{-0.10}$
SWIFT J1830.8+0928 |  | 277.7110 | 9.4783 | 0.670 | 0.0191 | 2 | 2020-06-01 | 43.40 | 8.39 | $\sigma_{*}$ | -3.09 | 0.80 | $23.18^{+0.22}_{-0.28}$
SWIFT J1844.5$-$6221 | Fairall 51 | 281.2249 | -62.3648 | 0.297 | 0.0139 | 1 | 2018-07-25 | 44.15 | 7.20 | H$\alpha$ | -1.15 | 0.35 | $20.00^{+0.00}_{-0.00}$
SWIFT J1845.4+7211 |  | 281.3593 | 72.1838 | 0.167 | 0.0463 | 2 | 2018-10-02 | 44.64 | 7.86 | $M_{*}$ | -1.32 | 0.37 | $22.46^{+0.07}_{-0.10}$
SWIFT J1848.0$-$7832 |  | 281.7618 | -78.5304 | 0.306 | 0.0743 | 1 | 2019-01-11 | 45.24 | 7.73 | $M_{*}$ | -0.59 | 0.62 | $20.00^{+0.00}_{-0.00}$
SWIFT J1856.2$-$7829 |  | 284.2823 | -78.4725 | 0.427 | 0.0420 | 1 | 2020-07-06 | 44.88 | 8.76 | $M_{*}$ | -1.98 | 0.55 | $22.15^{+0.11}_{-0.11}$
SWIFT J1903.9+3349 | UGC 11397 | 285.9548 | 33.8447 | 0.248 | 0.0152 | 2 | 2019-10-15 | 43.89 | 8.24 | $M_{*}$ | -2.45 | 0.60 | $22.87^{+0.11}_{-0.15}$
SWIFT J1905.4+4231 |  | 286.3581 | 42.4610 | 0.198 | 0.0279 | 1 | 2018-09-24 | 44.16 | 8.03 | $M_{*}$ | -1.97 | 0.55 | $20.76^{+0.42}_{-0.30}$
SWIFT J1940.4$-$3015 | IGR J19405-3016 | 295.0629 | -30.2644 | 0.281 | 0.0525 | 1 | 2020-07-09 | 45.03 | 8.37 | H$\alpha$ | -1.44 | 0.76 | $20.52^{+0.08}_{-0.11}$
SWIFT J1947.3+4447 |  | 296.8307 | 44.8284 | 0.535 | 0.0528 | 2 | 2018-12-05 | 45.12 | 9.01 | $\sigma_{*}$ | -1.99 | 0.75 | $22.84^{+0.03}_{-0.02}$
SWIFT J1952.4+0237 | 3C 403 | 298.0660 | 2.5070 | 0.520 | 0.0584 | 2 | 2020-07-19 | 45.47 | 9.15 | $\sigma_{*}$ | -1.78 | 0.87 | $23.69^{+0.13}_{-0.04}$
SWIFT J2006.5+5619 |  | 301.6389 | 56.3435 | 1.013 | 0.0423 | 2 | 2019-01-11 | 44.66 | 7.82 | $M_{*}$ | -1.26 | 0.22 | $23.48^{+0.09}_{-0.10}$
SWIFT J2010.7+4801 |  | 302.5725 | 48.0059 | 1.106 | 0.0254 | 2 | 2018-12-05 | 44.18 | 9.48 | $\sigma_{*}$ | -3.40 | 0.59 | $23.00^{+0.17}_{-0.43}$
SWIFT J2018.4$-$5539 | PKS 2014-55 | 304.5050 | -55.6590 | 0.184 | 0.0607 | 2 | 2020-07-10 | 45.39 | 8.50 | $M_{*}$ | -1.21 | 0.63 | $23.45^{+0.10}_{-0.08}$
SWIFT J2018.8+4041 |  | 304.6613 | 40.6834 | 9.336 | 0.0144 | 2 | 2019-01-17 | 44.01 | 7.85 | $M_{*}$ | -1.94 | 0.87 | $22.78^{+0.04}_{-0.06}$
SWIFT J2021.9+4400 |  | 305.4544 | 44.0110 | 3.620 | 0.0175 | 2 | 2018-12-05 | 43.85 | 7.52 | $M_{*}$ | -1.77 | 0.52 | $23.02^{+0.34}_{-0.24}$
SWIFT J2027.1$-$0220 |  | 306.7328 | -2.2775 | 0.254 | 0.0291 | 2 | 2018-07-26 | 44.53 | 7.83 | $M_{*}$ | -1.40 | 0.94 | $23.82^{+0.15}_{-0.11}$
SWIFT J2035.2+2604 |  | 308.7735 | 26.0583 | 0.746 | 0.0478 | 1 | 2018-09-30 | 44.67 | 7.53 | H$\alpha$ | -0.96 | 0.26 | $21.30^{+0.34}_{-0.29}$
SWIFT J2040.2$-$5126 | ESO 234-IG 063 | 310.0656 | -51.4297 | 0.077 | 0.0541 | 2 | 2021-05-22 | 44.91 | 8.11 | $\sigma_{*}$ | -1.30 | 0.73 | $23.41^{+0.20}_{-0.18}$
SWIFT J2044.0+2832 | RX J2044.0+2833 | 311.0188 | 28.5534 | 0.941 | 0.0489 | 1 | 2018-10-04 | 44.93 | 8.23 | H$\alpha$ | -1.40 | 0.64 | $21.15^{+0.12}_{-0.09}$
SWIFT J2052.0$-$5704 | IC 5063 | 313.0098 | -57.0688 | 0.169 | 0.0115 | 2 | 2019-11-25 | 44.31 | 8.17 | $M_{*}$ | -1.96 | 0.83 | $23.56^{+0.07}_{-0.01}$
SWIFT J2109.1$-$0942 |  | 317.2915 | -9.6707 | 0.584 | 0.0268 | 1 | 2018-09-18 | 44.40 | 7.52 | H$\alpha$ | -1.22 | 0.87 | $21.20^{+0.32}_{-0.50}$
SWIFT J2114.4+8206 |  | 318.5049 | 82.0801 | 0.419 | 0.0833 | 1 | 2018-04-02 | 45.68 | 9.02 | H$\alpha$ | -1.44 | 0.82 | $20.00^{+0.00}_{-0.00}$
SWIFT J2118.9+3336 |  | 319.8714 | 33.5491 | 0.589 | 0.0509 | 1 | 2019-01-03 | 44.77 | 8.11 | H$\alpha$ | -1.44 | 0.74 | $21.57^{+0.17}_{-0.17}$
SWIFT J2124.6+5057 | 4C 50.55 | 321.1643 | 50.9735 | 6.665 | 0.0151 | 1 | 2018-12-13 | 44.95 | 6.69 | H$\alpha$ | 0.16 | 0.70 | $23.02^{+0.08}_{-0.14}$
SWIFT J2127.4+5654 |  | 321.9391 | 56.9430 | 3.523 | 0.0147 | 1 | 2018-08-19 | 44.15 | 6.60 | $M_{*}$ | -0.55 | 0.83 | $20.00^{+0.00}_{-0.00}$
SWIFT J2156.1+4728 |  | 323.9750 | 47.4727 | 1.741 | 0.0253 | 1 | 2018-12-06 | 44.39 | 7.47 | H$\alpha$ | -1.18 | 0.34 | $21.28^{+0.24}_{-0.10}$
SWIFT J2201.9$-$3152 | NGC 7172 | 330.5080 | -31.8698 | 0.073 | 0.0083 | 2 | 2020-09-15 | 44.22 | 8.45 | $\sigma_{*}$ | -2.33 | 0.70 | $22.91^{+0.01}_{-0.01}$
SWIFT J2204.7+0337 |  | 331.0799 | 3.5639 | 0.126 | 0.0611 | 2 | 2020-07-19 | 45.10 | 8.25 | $M_{*}$ | -1.25 | 0.96 | $22.83^{+0.15}_{-0.14}$
SWIFT J2214.2$-$2557 |  | 333.5382 | -25.9636 | 0.065 | 0.0519 | 2 | 2020-09-16 | 44.89 | 8.17 | $\sigma_{*}$ | -1.38 | 0.83 | $23.48^{+0.23}_{-0.12}$
SWIFT J2219.7+2614 |  | 334.9573 | 26.2244 | 0.297 | 0.0877 | 1 | 2019-01-20 | 45.41 | 9.01 | H$\alpha$ | -1.70 | 0.67 | $21.52^{+0.06}_{-0.04}$
SWIFT J2237.0+2543 |  | 339.1370 | 25.7632 | 0.143 | 0.0246 | 2 | 2018-04-27 | 44.07 | 8.43 | $M_{*}$ | -2.46 | 0.91 | $23.02^{+0.18}_{-0.09}$
SWIFT J2246.0+3941 | 3C 452 | 341.4532 | 39.6877 | 0.381 | 0.0811 | 1 | 2018-12-08 | 45.66 | 6.58 | H$\alpha$ | 0.98 | 0.70 | $23.76^{+0.07}_{-0.08}$
SWIFT J2320.8+6434 |  | 350.1526 | 64.5125 | 4.592 | 0.0717 | 2 | 2019-10-23 | 45.03 | 7.65 | $M_{*}$ | -0.72 | 0.57 | $22.04^{+0.41}_{-0.19}$
SWIFT J2330.5+7124 | IGR J23308+7120 | 352.6571 | 71.3796 | 1.791 | 0.0369 | 2 | 2018-12-15 | 44.40 | 8.55 | $M_{*}$ | -2.25 | 0.95 | $22.95^{+0.06}_{-0.06}$
SWIFT J2359.3$-$6058 |  | 359.7682 | -60.9165 | 0.037 | 0.0963 | 2 | 2020-01-14 | 45.40 | 8.92 | $M_{*}$ | -1.62 | 0.57 | $23.16^{+0.02}_{-0.02}$

Note. — Col. (1): Object name. Col. (2): Alternative name. Col. (3): Right
Ascension in J2000 coordinates. Col. (4): Declination in J2000 coordinates.
Col. (5): Galactic extinction in the V band. Col. (6): Redshift. Col. (7): AGN
type determined based on the optical spectrum. Col. (8): Observation date.
Col. (9): Bolometric luminosity inferred from the intrinsic X-ray luminosity,
assuming a bolometric correction of 8 (Ricci et al. 2017). Col. (10): Black
hole mass. Col. (11): Method to estimate the black hole mass: H$\alpha$:
virial method with the broad H$\alpha$; H$\beta$: virial method with the broad
H$\beta$; $\sigma_{*}$: $M_{\rm BH}-\sigma_{*}$ relation; $M_{*}$: $M_{\rm
BH}-M_{*}$ relation. Col. (12): Eddington ratio ($\lambda=L_{\rm bol}/L_{\rm
Edd}$). Col. (13): Axis ratio. Col. (14): Column density of neutral hydrogen
derived from the hard X-ray spectrum (Ricci et al. 2017).

Table 2: Morphology of Host Galaxies

Source Name | Morp.(1) | Morp.(2) | T/S | Major/Minor | Merging Stage | Nucleus
---|---|---|---|---|---|---
(1) | (2) | (3) | (4) | (5) | (6) | (7)
SWIFT J0001.0$-$0708 | S0 | Sb |  $\cdots$ |  $\cdots$ | m1 | s
SWIFT J0001.6$-$7701 | SB | Sc | T | Minor | m2 | s
SWIFT J0003.3+2737 | SA | Sa | T | Minor | m2 | s
SWIFT J0005.0+7021 | E/S0 |  $\cdots$ | S |  $\cdots$ |  $\cdots$ | s
SWIFT J0006.2+2012 | E |  $\cdots$ |  $\cdots$ | Minor | m1 | s
SWIFT J0036.3+4540 | SA | Sc |  $\cdots$ |  $\cdots$ | m1 | s
SWIFT J0100.9$-$4750 | SA | Sa | T | Major | m3 | s
SWIFT J0123.9$-$5846 | SB | Sb | S | Minor | m2 | s
SWIFT J0128.4+1631 | SB | Sc |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0134.1$-$3625 | E |  $\cdots$ |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0157.2+4715 | SB | Sc | T | Minor | m2 | s
SWIFT J0202.4+6824A | SB | Sb |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0202.4+6824B | SB | Sb |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0206.2$-$0019 | pec. |  $\cdots$ | T | Major | m4 | s
SWIFT J0234.6$-$0848 | pec. |  $\cdots$ | T | Major | m4 | d
SWIFT J0243.9+5324 | SB | Sb |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0333.3+3720 | S0 | Sa | S | Minor | m1 | s
SWIFT J0347.0$-$3027 | S0 | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0356.9$-$4041 | E/S0 | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0405.3$-$3707 | E/S0 | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0429.6$-$2114 | pec. |  $\cdots$ | T | Major | m4 | s
SWIFT J0443.9+2856 | SB | Sb |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0446.4+1828 | SB | Sb |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0456.3$-$7532 | SB0 | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0504.6$-$7345 | SA | Sb |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0510.7+1629 | E/S0 |  $\cdots$ |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0516.2$-$0009 | SA | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0526.2$-$2118 | SB0 | Sa | S | Minor |  $\cdots$ | s
SWIFT J0528.1$-$3933 | SB | Sa | T | Major | m2 | dd
SWIFT J0533.9$-$1318 | S0 | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0544.4$-$4328 | E |  $\cdots$ | T | Minor | m2 | s
SWIFT J0552.5+5929 | pec. |  $\cdots$ | T | Major | m4 | s
SWIFT J0623.9$-$6058 | SB | Sa | T | Minor | m1 | s
SWIFT J0641.3+3257 | S0 | Sa | T | Major | m1 | s
SWIFT J0645.9+5303 | SA | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0707.1+6433 | E/S0 | Sa | S | Minor | m1 | s
SWIFT J0709.0$-$4642 | E |  $\cdots$ | S | Minor | m1 | s
SWIFT J0736.9+5846 | SB | Sc |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0743.0+6513 | E/S0 | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0743.3$-$2546 | SB | Sc |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0747.5+6057 | SB | Sb |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0747.6$-$7326 | S0 | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0753.1+4559 | E |  $\cdots$ |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0756.3$-$4137 | E |  $\cdots$ |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0759.8$-$3844 | E |  $\cdots$ |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0800.1+2638 | SB | Sb |  $\cdots$ |  $\cdots$ | m1 | s
SWIFT J0801.9$-$4946 | SA | Sc |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0804.6+1045 | pec. |  $\cdots$ | T | Major | m4 | s
SWIFT J0805.1$-$0110 | SA | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0807.9+3859 | SB | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0819.2$-$2259 | SB | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0823.4$-$0457 | SA | Sa |  $\cdots$ |  $\cdots$ | m1 | s
SWIFT J0840.2+2947 | E/S0 | Sa | S | Minor | m2 | s
SWIFT J0855.6+6425 | SA | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0902.7$-$4814 | E |  $\cdots$ |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0923.7+2255 | SB | Sb |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0924.2$-$3141 | E |  $\cdots$ |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0925.2$-$8423 | E |  $\cdots$ | T | Minor | m2 | s
SWIFT J0936.2$-$6553 | SB0 | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0942.2+2344 | SB0 | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J0947.6$-$3057 | SB0 | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1020.5$-$0237B | SB | Sb |  $\cdots$ |  $\cdots$ | m1 | s
SWIFT J1021.7$-$0327 | E |  $\cdots$ |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1029.8$-$3821 | SA | Sa |  $\cdots$ |  $\cdots$ | m1 | s
SWIFT J1031.9$-$1418 | E |  $\cdots$ |  $\cdots$ |  $\cdots$ | m1 | s
SWIFT J1032.7$-$2835 | S0 | Sb |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1033.6+7303 | E/S0 | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1038.8$-$4942 | E |  $\cdots$ |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1040.7$-$4619 | S0 | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1042.4+0046 | SA | Sb |  $\cdots$ |  $\cdots$ | m1 | s
SWIFT J1043.4+1105 | E |  $\cdots$ |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1059.8+6507 | pec. |  $\cdots$ | T | Minor | m3 | s
SWIFT J1132.9+1019A | SB | Sc |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1136.7$-$6007 | S0 | Sb |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1139.1+5913 | E/S0 |  $\cdots$ | S | Minor | m2 | s
SWIFT J1143.7+7942 | SB0 | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1148.3+0901 | SB0 | Sa |  $\cdots$ |  $\cdots$ | m1 | s
SWIFT J1200.2$-$5350 | pec. |  $\cdots$ | S |  $\cdots$ | m4 | s
SWIFT J1211.3$-$3935 | SB | Sb |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1213.1+3239A | S0 | Sb |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1217.2$-$2611 | SB | Sb | T | Major | m2 | s
SWIFT J1248.2$-$5828 | S0 | Sb | T | Major | m2 | s
SWIFT J1306.4$-$4025B | SB0 | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1315.8+4420 | pec. |  $\cdots$ | T | Major | m3 | s
SWIFT J1316.9$-$7155 | E |  $\cdots$ |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1322.2$-$1641 | SB | Sb |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1332.0$-$7754 | SA | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1333.5$-$3401 | SA | Sc |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1336.0+0304 | SA | Sb |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1338.2+0433 | S0 | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1341.5+6742 | SB0 | Sa |  $\cdots$ |  $\cdots$ | m1 | s
SWIFT J1345.5+4139 | SA | Sc |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1349.7+0209 | S0 | Sa |  $\cdots$ |  $\cdots$ | m1 | s
SWIFT J1354.5+1326 | SA | Sb | T | Major | m3 | s
SWIFT J1416.9$-$1158 | E |  $\cdots$ |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1421.4+4747 | E/S0 | Sa |  $\cdots$ | Minor | m1 | s
SWIFT J1424.2+2435 | SB | Sb |  $\cdots$ | Minor |  $\cdots$ | s
SWIFT J1431.2+2816 | SB | Sc |  $\cdots$ |  $\cdots$ | m1 | s
SWIFT J1457.8$-$4308 | pec. |  $\cdots$ | T | Major | m3 | dd
SWIFT J1506.7+0353B | SB0 | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1513.8$-$8125 | S0 | Sa | T | Major | m3 | dd
SWIFT J1546.3+6928 | SB0 | Sb |  $\cdots$ |  $\cdots$ | m1 | s
SWIFT J1548.5$-$1344 | SB | Sc |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1605.9$-$7250 | SA | Sb |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1643.2+7036 | SB | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1648.0$-$3037 | E |  $\cdots$ |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1652.3+5554 | SB | Sc |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1731.3+1442 | SA | Sa | T |  $\cdots$ |  $\cdots$ | s
SWIFT J1737.7$-$5956A | SA | Sb |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1741.9$-$1211 | SB | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1747.7$-$2253 | E |  $\cdots$ |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1747.8+6837A | SB | Sb |  $\cdots$ |  $\cdots$ | m1 | s
SWIFT J1747.8+6837B | E |  $\cdots$ | T | Major | m3 | dd
SWIFT J1748.8$-$3257 | E/S0 |  $\cdots$ |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1800.3+6637 | SB | Sb |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1807.9+1124 | E |  $\cdots$ |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1824.2+1845 | SA | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1824.3$-$5624 | SA | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1826.8+3254 | S0 | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1830.8+0928 | SB0 | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1844.5$-$6221 | SB | Sb |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1845.4+7211 | pec. |  $\cdots$ | T | Major | m4 | d
SWIFT J1848.0$-$7832 | pec. |  $\cdots$ | T | Major | m4 | d
SWIFT J1856.2$-$7829 | S0 | Sb |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1903.9+3349 | SB | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1905.4+4231 | SB | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1940.4$-$3015 | SB | Sc |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1947.3+4447 | SA | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J1952.4+0237 | E |  $\cdots$ |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J2006.5+5619 | SA | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J2010.7+4801 | SB0 | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J2018.4$-$5539 | E/S0 |  $\cdots$ |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J2018.8+4041 | SA | Sc |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J2021.9+4400 | SB0 | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J2027.1$-$0220 | S0 | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J2035.2+2604 | SA | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J2040.2$-$5126 | pec. |  $\cdots$ | T | Major | m4 | s
SWIFT J2044.0+2832 | SB | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J2052.0$-$5704 | E |  $\cdots$ |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J2109.1$-$0942 | SB | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J2114.4+8206 | E |  $\cdots$ |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J2118.9+3336 | E |  $\cdots$ | S | Minor | m1 | s
SWIFT J2124.6+5057 | E |  $\cdots$ |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J2127.4+5654 | E |  $\cdots$ |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J2156.1+4728 | SA | Sc |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J2201.9$-$3152 | E/S0 |  $\cdots$ |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J2204.7+0337 | pec. |  $\cdots$ | T | Minor | m4 | s
SWIFT J2214.2$-$2557 | SB | Sb |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J2219.7+2614 | E |  $\cdots$ | S | Minor | m1 | s
SWIFT J2237.0+2543 | SB | Sb |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J2246.0+3941 | E |  $\cdots$ |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J2320.8+6434 | E |  $\cdots$ |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J2330.5+7124 | SB | Sa |  $\cdots$ |  $\cdots$ |  $\cdots$ | s
SWIFT J2359.3$-$6058 | E |  $\cdots$ |  $\cdots$ |  $\cdots$ |  $\cdots$ | s

Note. — Col. (1): Object name. Col. (2): Morphological classification:
E;E/S0;S0;SB0;SA;SB;peculiar. Col. (3): Morphological classification based on
the bulge dominance: Sa/Sb/Sc. Col. (4): Presence of perturbed structure: “T”
= tidal tail; “S” = shell structure. Col. (5): Merging feature: “Major” =
major merger; “Minor” = minor merger. Col. (6): Merging stage: “m1” = a
companion galaxy with very faint (or no) sign of interaction; “m2” = a sign of
interaction (tail and shell) but no major disturbance in the host galaxy; “m3”
= major disturbance in the host galaxy but the companion galaxy is not yet
merged. “m4” = two galaxies share the common envelope (latest stage of the
merger). Col. (7): Number of nuclei: “s” = single nucleus; “d” = double nuclei
in a single host; “dd” = double nuclei in separate hosts.

Table 3: Merging Fraction

|  | Tidal/shell |  | Major/minor |  | m2+m3+m4 |  | Double nuclei
---|---|---|---|---|---|---|---|---
Parameter | Bin | All | Type 1 | Type 2 |  | All | Type 1 | Type 2 |  | All | Type 1 | Type 2 |  | All | Type 1 | Type 2
(1) | (2) | (3) | (4) | (5) |  | (6) | (7) | (8) |  | (9) | (10) | (11) |  | (12) | (13) | (14)
log $L_{\rm bol}$ | 43.25 | $0.00^{+0.17}_{-0.00}$ | $0.00^{+0.54}_{-0.00}$ | $0.00^{+0.21}_{-0.00}$ |  | $0.00^{+0.17}_{-0.00}$ | $0.00^{+0.54}_{-0.00}$ | $0.00^{+0.21}_{-0.00}$ |  | $0.00^{+0.17}_{-0.00}$ | $0.00^{+0.54}_{-0.00}$ | $0.00^{+0.21}_{-0.00}$ |  | $0.00^{+0.17}_{-0.00}$ | $0.00^{+0.54}_{-0.00}$ | $0.00^{+0.21}_{-0.00}$
| 43.75 | $0.00^{+0.07}_{-0.00}$ | $0.00^{+0.35}_{-0.00}$ | $0.00^{+0.08}_{-0.00}$ |  | $0.08^{+0.11}_{-0.04}$ | $0.00^{+0.35}_{-0.00}$ | $0.09^{+0.12}_{-0.05}$ |  | $0.00^{+0.07}_{-0.00}$ | $0.00^{+0.35}_{-0.00}$ | $0.00^{+0.08}_{-0.00}$ |  | $0.00^{+0.07}_{-0.00}$ | $0.00^{+0.35}_{-0.00}$ | $0.00^{+0.08}_{-0.00}$
| 44.25 | $0.13^{+0.06}_{-0.04}$ | $0.00^{+0.06}_{-0.00}$ | $0.22^{+0.10}_{-0.07}$ |  | $0.15^{+0.07}_{-0.05}$ | $0.06^{+0.09}_{-0.04}$ | $0.22^{+0.10}_{-0.07}$ |  | $0.10^{+0.06}_{-0.04}$ | $0.00^{+0.06}_{-0.00}$ | $0.17^{+0.09}_{-0.06}$ |  | $0.05^{+0.05}_{-0.02}$ | $0.00^{+0.06}_{-0.00}$ | $0.09^{+0.08}_{-0.04}$
| 44.75 | $0.33^{+0.07}_{-0.06}$ | $0.21^{+0.08}_{-0.06}$ | $0.48^{+0.10}_{-0.10}$ |  | $0.31^{+0.07}_{-0.06}$ | $0.21^{+0.08}_{-0.06}$ | $0.43^{+0.10}_{-0.10}$ |  | $0.27^{+0.07}_{-0.06}$ | $0.17^{+0.08}_{-0.06}$ | $0.39^{+0.10}_{-0.09}$ |  | $0.04^{+0.04}_{-0.02}$ | $0.03^{+0.05}_{-0.02}$ | $0.04^{+0.06}_{-0.03}$
| 45.25 | $0.41^{+0.08}_{-0.08}$ | $0.52^{+0.10}_{-0.10}$ | $0.25^{+0.12}_{-0.09}$ |  | $0.38^{+0.08}_{-0.07}$ | $0.48^{+0.10}_{-0.10}$ | $0.25^{+0.12}_{-0.09}$ |  | $0.26^{+0.07}_{-0.06}$ | $0.30^{+0.10}_{-0.09}$ | $0.19^{+0.11}_{-0.08}$ |  | $0.08^{+0.05}_{-0.03}$ | $0.13^{+0.09}_{-0.05}$ | $0.00^{+0.06}_{-0.00}$
| 45.75 | $0.00^{+0.17}_{-0.00}$ | $0.00^{+0.21}_{-0.00}$ | $0.00^{+0.54}_{-0.00}$ |  | $0.00^{+0.17}_{-0.00}$ | $0.00^{+0.21}_{-0.00}$ | $0.00^{+0.54}_{-0.00}$ |  | $0.00^{+0.17}_{-0.00}$ | $0.00^{+0.21}_{-0.00}$ | $0.00^{+0.54}_{-0.00}$ |  | $0.00^{+0.17}_{-0.00}$ | $0.00^{+0.21}_{-0.00}$ | $0.00^{+0.54}_{-0.00}$
log $\lambda$ | -3.50 | $0.00^{+0.15}_{-0.00}$ | $0.00^{+0.00}_{-0.00}$ | $0.00^{+0.15}_{-0.00}$ |  | $0.00^{+0.15}_{-0.00}$ | $0.00^{+0.00}_{-0.00}$ | $0.00^{+0.15}_{-0.00}$ |  | $0.00^{+0.15}_{-0.00}$ | $0.00^{+0.00}_{-0.00}$ | $0.00^{+0.15}_{-0.00}$ |  | $0.00^{+0.15}_{-0.00}$ | $0.00^{+0.00}_{-0.00}$ | $0.00^{+0.15}_{-0.00}$
| -2.50 | $0.16^{+0.09}_{-0.06}$ | $0.14^{+0.18}_{-0.08}$ | $0.17^{+0.10}_{-0.07}$ |  | $0.16^{+0.09}_{-0.06}$ | $0.14^{+0.18}_{-0.08}$ | $0.17^{+0.10}_{-0.07}$ |  | $0.12^{+0.08}_{-0.05}$ | $0.14^{+0.18}_{-0.08}$ | $0.11^{+0.09}_{-0.05}$ |  | $0.00^{+0.04}_{-0.00}$ | $0.00^{+0.13}_{-0.00}$ | $0.00^{+0.05}_{-0.00}$
| -1.50 | $0.31^{+0.69}_{-****}$ | $0.30^{+0.07}_{-0.06}$ | $0.31^{+0.07}_{-0.06}$ |  | $0.32^{+0.68}_{-****}$ | $0.32^{+0.07}_{-0.06}$ | $0.31^{+0.07}_{-0.06}$ |  | $0.22^{+0.78}_{-****}$ | $0.19^{+0.06}_{-0.05}$ | $0.25^{+0.07}_{-0.06}$ |  | $0.04^{+0.96}_{-****}$ | $0.04^{+0.04}_{-0.02}$ | $0.04^{+0.04}_{-0.02}$
| -0.50 | $0.21^{+0.09}_{-0.07}$ | $0.17^{+0.10}_{-0.07}$ | $0.33^{+0.20}_{-0.15}$ |  | $0.17^{+0.09}_{-0.06}$ | $0.11^{+0.09}_{-0.05}$ | $0.33^{+0.20}_{-0.15}$ |  | $0.17^{+0.09}_{-0.06}$ | $0.11^{+0.09}_{-0.05}$ | $0.33^{+0.20}_{-0.15}$ |  | $0.12^{+0.08}_{-0.05}$ | $0.11^{+0.09}_{-0.05}$ | $0.17^{+0.20}_{-0.10}$
| 0.50 | $0.00^{+0.35}_{-0.00}$ | $0.00^{+0.35}_{-0.00}$ | $0.00^{+0.00}_{-0.00}$ |  | $0.00^{+0.35}_{-0.00}$ | $0.00^{+0.35}_{-0.00}$ | $0.00^{+0.00}_{-0.00}$ |  | $0.00^{+0.35}_{-0.00}$ | $0.00^{+0.35}_{-0.00}$ | $0.00^{+0.00}_{-0.00}$ |  | $0.00^{+0.35}_{-0.00}$ | $0.00^{+0.35}_{-0.00}$ | $0.00^{+0.00}_{-0.00}$
| 1.50 | $0.00^{+0.54}_{-0.00}$ | $0.00^{+0.54}_{-0.00}$ | $0.00^{+0.00}_{-0.00}$ |  | $0.00^{+0.54}_{-0.00}$ | $0.00^{+0.54}_{-0.00}$ | $0.00^{+0.00}_{-0.00}$ |  | $0.00^{+0.54}_{-0.00}$ | $0.00^{+0.54}_{-0.00}$ | $0.00^{+0.00}_{-0.00}$ |  | $0.00^{+0.54}_{-0.00}$ | $0.00^{+0.54}_{-0.00}$ | $0.00^{+0.00}_{-0.00}$
log $N_{\rm H}$ | 20.00 | $0.32^{+0.08}_{-0.07}$ | $0.33^{+0.08}_{-0.07}$ | $0.00^{+0.54}_{-0.00}$ |  | $0.35^{+0.08}_{-0.07}$ | $0.36^{+0.08}_{-0.07}$ | $0.00^{+0.54}_{-0.00}$ |  | $0.27^{+0.08}_{-0.07}$ | $0.28^{+0.08}_{-0.07}$ | $0.00^{+0.54}_{-0.00}$ |  | $0.08^{+0.06}_{-0.03}$ | $0.08^{+0.06}_{-0.03}$ | $0.00^{+0.54}_{-0.00}$
| 20.50 | $0.30^{+0.07}_{-0.06}$ | $0.31^{+0.07}_{-0.07}$ | $0.00^{+0.54}_{-0.00}$ |  | $0.33^{+0.07}_{-0.07}$ | $0.33^{+0.08}_{-0.07}$ | $0.00^{+0.54}_{-0.00}$ |  | $0.26^{+0.07}_{-0.06}$ | $0.26^{+0.07}_{-0.06}$ | $0.00^{+0.54}_{-0.00}$ |  | $0.09^{+0.05}_{-0.03}$ | $0.10^{+0.05}_{-0.04}$ | $0.00^{+0.54}_{-0.00}$
| 21.00 | $0.12^{+0.10}_{-0.06}$ | $0.12^{+0.10}_{-0.06}$ | $0.00^{+0.00}_{-0.00}$ |  | $0.12^{+0.10}_{-0.06}$ | $0.12^{+0.10}_{-0.06}$ | $0.00^{+0.00}_{-0.00}$ |  | $0.06^{+0.08}_{-0.03}$ | $0.06^{+0.08}_{-0.03}$ | $0.00^{+0.00}_{-0.00}$ |  | $0.06^{+0.08}_{-0.03}$ | $0.06^{+0.08}_{-0.03}$ | $0.00^{+0.00}_{-0.00}$
| 21.50 | $0.20^{+0.10}_{-0.07}$ | $0.19^{+0.11}_{-0.08}$ | $0.25^{+0.25}_{-0.14}$ |  | $0.20^{+0.10}_{-0.07}$ | $0.19^{+0.11}_{-0.08}$ | $0.25^{+0.25}_{-0.14}$ |  | $0.05^{+0.07}_{-0.03}$ | $0.00^{+0.06}_{-0.00}$ | $0.25^{+0.25}_{-0.14}$ |  | $0.05^{+0.07}_{-0.03}$ | $0.00^{+0.06}_{-0.00}$ | $0.25^{+0.25}_{-0.14}$
| 22.00 | $0.25^{+0.08}_{-0.07}$ | $0.21^{+0.13}_{-0.09}$ | $0.28^{+0.11}_{-0.09}$ |  | $0.22^{+0.08}_{-0.06}$ | $0.21^{+0.13}_{-0.09}$ | $0.22^{+0.11}_{-0.08}$ |  | $0.16^{+0.07}_{-0.05}$ | $0.07^{+0.10}_{-0.04}$ | $0.22^{+0.11}_{-0.08}$ |  | $0.06^{+0.06}_{-0.03}$ | $0.00^{+0.07}_{-0.00}$ | $0.11^{+0.09}_{-0.05}$
| 22.50 | $0.26^{+0.07}_{-0.06}$ | $0.17^{+0.13}_{-0.08}$ | $0.29^{+0.08}_{-0.07}$ |  | $0.24^{+0.07}_{-0.06}$ | $0.08^{+0.11}_{-0.05}$ | $0.29^{+0.08}_{-0.07}$ |  | $0.22^{+0.07}_{-0.05}$ | $0.08^{+0.11}_{-0.05}$ | $0.26^{+0.08}_{-0.07}$ |  | $0.02^{+0.03}_{-0.01}$ | $0.00^{+0.08}_{-0.00}$ | $0.03^{+0.04}_{-0.02}$
| 23.00 | $0.31^{+0.07}_{-0.06}$ | $0.20^{+0.22}_{-0.12}$ | $0.32^{+0.07}_{-0.07}$ |  | $0.31^{+0.07}_{-0.06}$ | $0.00^{+0.17}_{-0.00}$ | $0.34^{+0.07}_{-0.07}$ |  | $0.22^{+0.06}_{-0.05}$ | $0.00^{+0.17}_{-0.00}$ | $0.25^{+0.07}_{-0.06}$ |  | $0.02^{+0.03}_{-0.01}$ | $0.00^{+0.17}_{-0.00}$ | $0.02^{+0.03}_{-0.01}$
| 23.50 | $0.23^{+0.07}_{-0.06}$ | $0.00^{+0.17}_{-0.00}$ | $0.26^{+0.08}_{-0.07}$ |  | $0.23^{+0.07}_{-0.06}$ | $0.00^{+0.17}_{-0.00}$ | $0.26^{+0.08}_{-0.07}$ |  | $0.15^{+0.07}_{-0.05}$ | $0.00^{+0.17}_{-0.00}$ | $0.18^{+0.07}_{-0.06}$ |  | $0.03^{+0.04}_{-0.01}$ | $0.00^{+0.17}_{-0.00}$ | $0.03^{+0.04}_{-0.02}$
| 24.00 | $0.06^{+0.08}_{-0.03}$ | $0.00^{+0.26}_{-0.00}$ | $0.07^{+0.09}_{-0.04}$ |  | $0.06^{+0.08}_{-0.03}$ | $0.00^{+0.26}_{-0.00}$ | $0.07^{+0.09}_{-0.04}$ |  | $0.06^{+0.08}_{-0.03}$ | $0.00^{+0.26}_{-0.00}$ | $0.07^{+0.09}_{-0.04}$ |  | $0.00^{+0.05}_{-0.00}$ | $0.00^{+0.26}_{-0.00}$ | $0.00^{+0.06}_{-0.00}$
| 24.50 | $0.00^{+0.17}_{-0.00}$ | $0.00^{+0.00}_{-0.00}$ | $0.00^{+0.17}_{-0.00}$ |  | $0.00^{+0.17}_{-0.00}$ | $0.00^{+0.00}_{-0.00}$ | $0.00^{+0.17}_{-0.00}$ |  | $0.00^{+0.17}_{-0.00}$ | $0.00^{+0.00}_{-0.00}$ | $0.00^{+0.17}_{-0.00}$ |  | $0.00^{+0.17}_{-0.00}$ | $0.00^{+0.00}_{-0.00}$ | $0.00^{+0.17}_{-0.00}$

Note. — Col. (1): Parameter. Col. (2): Bin. The units for $L_{\rm bol}$ and
$N_{\rm H}$ are erg s-1 and cm-2, respectively. Col. (3): Merging fraction of
the entire sample, based on the presence of tidal tail or shell. Col. (4):
Merging fraction of type 1 AGN, based on the presence of tidal tail or shell.
Col. (5): Merging fraction of type 2 AGN, based on the presence of tidal tail
or shell. Col. (6): Merging fraction of the entire sample, based on the
presence of major/minor merging features. Col. (7): Merging fraction of type 1
AGN, based on the presence of major/minor merging features. Col. (8): Merging
fraction of type 2 AGN, based on the presence of major/minor merging features.
Col. (9): Merging fraction of the entire sample, based on the merging stage
(m2+m3+m4). Col. (10): Merging fraction of type 1 AGN, based on the merging
stage (m2+m3+m4). Col. (11): Merging fraction of type 2 AGN, based on the
merging stage (m2+m3+m4). Col. (12): Fraction of the entire sample, based on
the presence of double nuclei. Col. (13): Fraction of type 1 AGN, based on the
presence of double nuclei. Col. (14): Fraction of type 2 AGN, based on the
presence of double nuclei.