# A Near-Infrared look at AGN Feedback in Bulgeless Galaxies

Thomas Bohn University of California, Riverside, Department of Physics &
Astronomy
900 University Ave., Riverside, CA 92521  Gabriela Canalizo University of
California, Riverside, Department of Physics & Astronomy
900 University Ave., Riverside, CA 92521  Shobita Satyapal George Mason
University, Department of Physics & Astronomy
MS3F3, 4400 University Drive, Fairfax, VA 22030  Laura V. Sales University of
California, Riverside, Department of Physics & Astronomy
900 University Ave., Riverside, CA 92521

(Accepted April 26, 2022)

###### Abstract

While it is generally believed that supermassive black holes (SMBH) lie in
most galaxies with bulges, few SMBHs have been confirmed in bulgeless
galaxies. Identifying such a population could provide important insights to
the BH seed population and secular BH growth. To this end, we obtained near-
infrared spectroscopic observations of a sample of low-redshift bulgeless
galaxies with mid-infrared colors suggestive of AGN. We find additional
evidence of AGN activity (such as coronal lines and broad permitted lines) in
69$\%$ (9/13) of the sample, demonstrating that mid-infrared selection is a
powerful tool to detect AGN. More than half of the galaxies with confirmed AGN
activity show fast outflows in [O III] in the optical and/or [Si VI] in the
NIR, with the latter generally having much faster velocities that are also
correlated to their spatial extent. We are also able to obtain virial BH
masses for some targets and find they fall within the scatter of other late-
type galaxies in the $M_{\rm{BH}}$-$M_{\rm{stellar}}$ relation. The fact that
they lack a significant bulge component indicates that secular processes,
likely independent of major mergers, grew these BHs to supermassive sizes.
Finally, we analyze the rotational gas kinematics and find two notable
exceptions: two AGN hosts with outflows that appear to be rotating faster than
expected. There is an indication that these two galaxies have stellar masses
significantly lower than expected from their dark matter halo masses. This,
combined with the observed AGN activity and strong gas outflows may be
evidence of the effects of AGN feedback.

galaxies: active — galaxies: bulges — galaxies: evolution — galaxies: Seyfert
— infrared: galaxies

††journal: ApJ††software: BADASS (Sexton et al., 2020)
https://github.com/remingtonsexton/BADASS2), pPXF (Cappellari & Emsellem,
2004; Cappellari, 2017), PyRAF (PyRAF is a product of the Space Telescope
Science Institute, which is operated by AURA for NASA), REDSPEC
(https://www2.keck.hawaii.edu/inst/nirspec/redspec.html)

##  1 Introduction

The relations between the properties of galaxies and their SMBHs have become a
vital part of understanding galaxy evolution. Well-known correlations such as
the $M_{\rm{BH}}$-$\sigma$ (eg., Ferrarese & Merritt, 2000; Gebhardt et al.,
2000; McConnell & Ma, 2013; Sexton et al., 2019) and the $M_{\rm{BH}}$ \-
$M_{\rm{bulge}}$, (eg., Marconi & Hunt, 2003; Häring & Rix, 2004) have shown
that SMBHs and their host galaxies likely co-evolve with each other. In the
larger mass regime, galaxy mergers are often regarded as the driving mechanism
behind this co-evolution. This is because galaxy mergers are able to disrupt
the angular momentum of the baryonic matter rotating in the disk. This
redistribution culminates not only in a galactic bulge forming but can also
result in gas being funneled toward the central BH. It is through these
processes that BHs are believed to reach supermassive sizes.

This paradigm of BH growth accompanying bulge growth raises an important
question regarding galaxies that have not had merger events in their history.
While simulations have shown that galaxies can regrow their disks after a
merger event (eg., Hopkins et al., 2009), a small bulge component can still
form after a minor merger. Thus, it is likely that a galaxy with no bulge has
had a merger-free history. These systems are of particular interest since
their BHs have grown through secular processes. As such, their number density
and occupation fraction can provide important constraints on the BH seed
population. Indeed, a number of studies have investigated BHs residing in
bulgeless host galaxies. Simmons et al. (2017) report BH mass estimates for a
large sample of Type 1 targets and find they fall within the scatter of the
$M_{\rm{BH}}$ \- $M_{\rm{stellar}}$ relation. Likewise, Bohn et al. (2020)
come to a similar conclusion for a Type 2 AGN through the use of near-infrared
(NIR) observations. Adding to this fact that some simulations suggest mergers
do not induce a significant amount of SMBH growth (Martin et al., 2018;
McAlpine et al., 2020), secular processes may play a more significant role in
BH growth than originally thought.

The addition of SMBHs in bulgeless galaxies necessitates a closer look at
these systems. Understanding the dynamics between these BHs and their hosts is
crucial to putting constraints on secular growth processes and BH-galaxy co-
evolution. An important aspect of this co-evolution is the impact of AGN
feedback. Outflows from AGN are believed to regulate and suppress star
formation, leading their hosts to the well-defined red sequence (King &
Pounds, 2015; Rupke et al., 2017). However, only a limited number of AGN-
driven outflows have been observed in bulgeless galaxies (Smethurst et al.,
2019, 2021). In order to place more stringent constraints and assess the
impact of secularly grown BHs, a larger sample size is needed.

A central issue when identifying AGN in bulgeless galaxies is confirming the
true morphology of the host. While estimates to $M_{\rm{BH}}$ may be
relatively easy to obtain in Type 1 AGN through the use of emission from the
broad-line region and the virial method, the reliability of bulge-disk
decompositions could be compromised due to the bright AGN being in our direct
line of sight. Consequently, a small bulge component could be hidden. Type 2
AGN benefit from more robust bulge-disk decompositions but the lack of broad
emission lines, particularly in optical wavelengths, makes it difficult to
obtain robust $M_{\rm{BH}}$ estimates. An added limitation is that bulgeless
galaxies can have high levels of dust obscuration, making AGN identification
difficult and thus optical selection incomplete (Satyapal et al., 2014).

A number of methods have been suggested to identify and confirm the presence
of obscured AGN, including spectropolarimetry (Antonucci & Miller, 1985;
Zakamska et al., 2005) and infrared observations (eg., Veilleux et al., 1997;
Satyapal et al., 2007, 2008, 2014; Lamperti et al., 2017; Cann et al., 2020),
where extinction is less severe in the latter. The NIR spectral region hosts a
number of emission lines used for AGN analysis. Below z $\sim$ 0.3, these
include coronal lines (CLs), forbidden transitions from highly ionized ($>$100
eV) species that are highly indicative of AGN activity, and H I recombination
lines that can trace the broad-line gas. Additionally, due to the
characteristically redder mid-infrared (MIR) colors of obscured AGN (Stern et
al., 2012), MIR color cuts can be used to separate optically hidden AGN from
star forming galaxies. Indeed, the Wide-field Infrared Survey Explorer (WISE;
Wright et al. 2010) and Spitzer Space Telescope have been used to separate AGN
from star-forming galaxies, as shown by the AGN demarcation box in Jarrett et
al. (2011). Recent follow-up work has indicated that this color-cut could
identify a new group of obscured AGN that would complement existing optical
data and provide a more representative picture of the AGN population (Satyapal
et al., 2014, hereafter S14). However, confirmation that these galaxies do
indeed host AGN is needed since contamination from star formation cannot be
dismissed.

To this end, in this article we aim to confirm the presence of AGN activity in
the sample of MIR-selected bulgeless galaxies presented in S14. In Section 2,
we provide details of the sample, observations, and data reduction. Fitting of
the spectra and calculations of the extinction levels and star-formation rates
(SFRs) are covered in Section 3. In Section 4, we use a number of AGN
indicators, including CLs, broad-line emission, and AGN diagnostic diagrams,
to confirm the presence of AGN activity. Section 5 analyzes outflow kinematics
and energies. We report virial BH mass estimates in Section 6 and compare
these to known scaling relations. Lastly, in Section 7, we analyze rotational
gas velocities and discuss the affects of AGN feedback in our sample. We adopt
a standard $\Lambda$CDM cosmology with $H_{0}$ = 70 km s-1 Mpc-1, $\Omega_{M}$
= 0.3, and $\Omega_{\Lambda}$ = 0.7.

##  2 Data and Observations

Figure 1: (left) BPT diagram with diagnostic lines from Kewley et al. (2001)
and Kauffmann et al. (2003). The full bulgeless sample from Simard et al.
(2011) are represented as contours (1$\sigma$, 2$\sigma$, and 3$\sigma$
levels). Galaxies covered in this study are represented as stars, with those
confirmed as AGN with at least one indicator are shown as blue stars (see
Section 4). Targets whose emission is dominated by stellar processes are shown
red stars. (right) WISE color diagram with the AGN demarcation box from
Jarrett et al. (2011). Emission line fluxes are provided in Table A1.

###  2.1 Sample Selection

Our sample of bulgeless galaxies come from those presented in S14. To
summarize their selection process, they drew from Simard et al. (2011), where
bulge-disk decompositions were performed on SDSS imaging. To obtain a
bulgeless subsample, S14 selected galaxies with a bulge-to-total light ratio
of 0.00 in both $r$ and $g$-bands. SDSS spectroscopy was also required for
proper redshift estimates, which resulted in a bulgeless sample of
$\sim$18,000 galaxies (see Figure 1). They subsequently cross-matched this
bulgeless subsample with the WISE all-sky data release
catalog111https://wise2.ipac.caltech.edu/docs/release/allsky/ in order to
obtain $W1$ (3.4 $\mu$m), $W2$ (4.6 $\mu$m), and $W3$ (12 $\mu$m) bands.
Utilizing the AGN demarcation zone as defined in Jarrett et al. (2011), they
then formed a sample of 30 AGN candidates, all of which have $W1$ – $W2$ $>$
0.7. These candidates form the basis of our sample. In total, we obtained NIR
spectroscopy of 13 of these 30 targets during our assigned telescope time, and
these 13 targets span the full range of WISE colors presented in S14. In
Figure 1, we plot these targets on the Baldwin, Phillips $\&$ Terlevich (BPT;
Baldwin et al., 1981) diagram and the WISE color-cut diagram as presented in
Jarrett et al. (2011). Hereafter, targets with at least one AGN indicator will
be represented as a blue symbol while those whose emission is dominated by
stellar processes will be shown as red symbols (see Section 4 for details).
The redshift range of our sample is from 0.05 to 0.24, with a median of 0.117.
The stellar masses range from 10.0 - 11.1 M⊙ and were obtained from Chang et
al. (2015), who performed SED fitting on optical and IR data. Comparing to the
bulgeless sample as a whole, our galaxies tend to be on the higher mass end.

###  2.2 Observations and Data Reduction

Our Keck NIR spectroscopy was obtained throughout the 2018 and 2019 semesters
using two instruments: NIRSPEC (McLean et al., 1998) and NIRES (Wilson et al.,
2004). NIRSPEC is a NIR echelle spectrograph on Keck II with a wavelength
coverage of 0.9 — 5.5 $\mu$m. The NIRSPEC-7 filter was used in low-resolution
mode ($42^{\prime\prime}\times 0.76^{\prime\prime}$ slit) and the cross-
dispersion angle was set to 35.38∘. This resulted in a wavelength coverage of
1.98 — 2.40 $\mu$m. An average spectral resolution of 197 km s-1 ($R$
$\approx$ 1500) was measured at 2.20 $\mu$m. All NIRSPEC observations were
done on 2018-03-05 under mostly clear conditions and the seeing was typically
$\sim$0.6′′.

NIRES is a NIR echelette spectrograph with a 18${}^{\prime\prime}\times
0.55^{\prime\prime}$ slit and wavelength coverage of 0.94 — 2.45 $\mu$m, split
into five orders. There is a small gap in coverage between 1.85 and 1.88
$\mu$m, but this is a region of low atmospheric transmission. The average
spectral resolution of the five orders ranges between 85 — 95 km s-1 (R
$\approx$ 3300). The majority of observations were done under mostly clear
conditions ($\sim$0.5” seeing); only J0122+0100 and J0333+0107 were observed
under poor weather.

Individual exposures for all sets of observations were four minutes each and
were done using the standard ABBA nodding. A telluric standard star, typically
of A0 spectral class with measured magnitudes in $J$, $H$, and $K$-bands, was
observed either directly before or after the target galaxy to correct for
atmospheric absorption features. Typical airmass differences with the target
were below 0.10. Details of the observations are summarized in Table 1 and
PanSTARR (Chambers et al., 2016) images of our sample are shown in Figure 2.
For J1036+0221 we provide HST imaging. Slit positions and contours showing the
isophotes are also provided.

Table 1: Observation Log Galaxy | Date | Instrument | Redshift | Scale | Exp. TimeaaExposures were typically done in ABBA nodding. | Slit PA | Aperture | Airmass
---|---|---|---|---|---|---|---|---
(SDSS Name) | (YYYY-mm-dd) |  |  | (kpc/arcsec) |  | (degrees) | (arcsec) |
J012218.11+010025.76 | 2018-09-20 | NIRES | 0.05546 | 1.08 | 4 x 240sbbFour exposures were taken for both the east and west targets. | 100, 183 | 1.92 | 1.25
J033331.86+010716.92 | 2018-10-24 | NIRES | 0.17755 | 3.00 | 2 x 240s | 0 | 1.49 | 1.15
J075039.97+292845.75 | 2018-03-05 | NIRSPEC | 0.14701 | 2.57 | 12 x 240s | 68 | 1.46 | 1.11
J085153.64+392611.76ccJ0851 and J1228 were also observed with NIRSPEC. | 2019-03-25 | NIRES | 0.12958 | 2.31 | 5 x 240s | 94 | 1.33 | 1.07
— | 2018-03-05 | NIRSPEC | — | — | 8 x 240s | 46 | 1.34 | 1.06
J085236.35+292853.20 | 2019-03-25 | NIRES | 0.07866 | 1.49 | 8 x 240s | 162 | 1.34 | 1.04
J092907.78+002637.29 | 2019-03-25 | NIRES | 0.11732 | 2.12 | 8 x 240s | 56.5 | 1.51 | 1.09
J103222.94+361727.91 | 2019-03-25 | NIRES | 0.23578 | 3.74 | 4 x 240s | 131 | 1.18 | 1.05
J103631.88+022144.10 | 2018-03-05 | NIRSPEC | 0.05026 | 0.98 | 4 x 240s | 42.5 | 1.68 | 1.05
J122809.19+581431.40ccJ0851 and J1228 were also observed with NIRSPEC. | 2019-01-24 | NIRES | 0.10982 | 2.00 | 12 x 240s | 333 | 1.34 | 1.28
— | 2018-03-05 | NIRSPEC | — | — | 8 x 240s | 333 | 1.34 | 1.27
J123304.57+002347.11 | 2019-03-25 | NIRES | 0.06917 | 1.32 | 8 x 240s | 75.5 | 1.33 | 1.06
J132647.54+101436.53 | 2018-03-05 | NIRSPEC | 0.08943 | 1.67 | 6 x 240s | 161.5 | 1.57 | 1.02
J133341.72+653619.16 | 2019-03-25 | NIRES | 0.15756 | 2.72 | 4 x 240sddFour exposures were taken for each position angle. | 123, 44 | 1.34 | 1.43
J155409.08+145703.59 | 2019-03-25 | NIRES | 0.13666 | 2.42 | 8 x 240s | 121 | 1.33 | 1.02

A similar reduction process was performed for both the NIRSPEC and NIRES data.
However, the differences in the two instruments necessitated slight
modifications in the two pipelines used. The first algorithm provided flat
fielding and a robust background subtraction by using techniques described in
Kelson (2003) and Becker et al. (2009). In short, this routine maps the 2D
science frame and models the sky background before rectification, thus
reducing the possibility of artifacts appearing due to the binning of sharp
features. The sky subtraction attained with this procedure is excellent,
despite the strong OH lines present in the NIR; the procedure is also quite
insensitive to cosmic rays and hot pixels, and is reliable regardless of
skyline intensity.

Rectification, telluric correction, wavelength calibration, and extraction
were all done with a slightly modified version of
REDSPEC.222https://www2.keck.hawaii.edu/inst/nirspec/redspec.html Telluric
correction was done by dividing by the spectrum of the telluric standard star
and multiplying by a blackbody curve of the same temperature. Strong OH
skylines were used for wavelength calibration and the 1D spectra were then
median combined. Flux calibration of individual exposures was done using the
telluric star and the Spitzer Science Center unit
converter333https://irsa.ipac.caltech.edu/data/SPITZER/docs/dataanalysistools/tools/pet/magtojy/index.html
to convert the magnitude of the star to the associated flux in that band. In
addition to correcting for Galactic reddening, a small corrective factor
($<$5%) was introduced due to the differences between the center NIR bands and
that of the wavelength coverage.

##  3 Analysis

###  3.1 Spectral Fitting

####  3.1.1 NIR Fitting

Figure 2: PanSTARRS (and HST for J1036+0221) image cut-outs of our sample. The
galaxy short-name and 5” scale are listed at the top. The blue lines indicate
the placement of the slit. For galaxies where we see gas rotation, we place
arrows pointing in the direction from blueshifted to redshifted velocities
(see Fig. 6). Lastly, the white contours show the isophotes of each target.

We fit all NIR spectra using emcee, an affine invariant Markov Chain Monte
Carlo (MCMC) ensemble sampler (Foreman-Mackey et al., 2013). A narrow Gaussian
component, along with a low order ($\leq$ 7) Legendre polynomial for the
continuum, were fit simultaneously for each emission line. We determined
whether a second Gaussian component was needed to fit the emission lines using
the following F-test: F = $(\sigma_{single})^{2}/(\sigma_{double})^{2}$, where
$\sigma$ is the standard deviation of the residuals using either single or
double Gaussian components. If F $>$ 2.0, then adding an extra component is
justifiable and we added a component that is constrained to be broader and
lower in amplitude than the first component to avoid degeneracies. Both the
narrow and broad components were treated as free Gaussians with amplitude,
full-width half-maximum (FWHM), and velocity offset from rest-frame wavelength
as free variables. The fluxes of all NIR emission lines detected at $>$
3$\sigma$ level are listed in Table A1 of Appendix A.

Various absorption features were also fit in a similar fashion. The fitting
was done simultaneously with that of emission lines in order to keep the
continuum level consistent across all measurements. Although we ran the F-test
as defined above, only one gaussian was needed for all the absorption fits.

####  3.1.2 SDSS Fitting

As noted in Section 2.1, SDSS spectra are available for our entire sample and
these provide full wavelength coverage from 4000 Å to 9000 Å. The SDSS spectra
were fit using Bayesian AGN Decomposition Analysis for SDSS Spectra
(BADASS,444https://github.com/remingtonsexton/BADASS2 Sexton et al., 2020), a
spectral analysis tool that provides comprehensive fits to SDSS spectra.
Through BADASS, we fit absorption features using the penalized Pixel Fitting
(pPXF555https://www-astro.physics.ox.ac.uk/~mxc/software/; Cappellari &
Emsellem, 2004) with stellar templates from The Indo-US Library of Coudé Feed
Stellar Spectra (Valdes et al., 2004). We also included a power-law function
to simulate the AGN continuum. However since our sample does not have Type 1
Seyferts, we did not fit for FeII emission. All components were fit
simultaneously, allowing for a detailed and robust analysis of the spectrum.
Notable emission line fluxes are listed in Table A1.

A key feature of BADASS is that it allows the user to test for the presence of
outflows in the form of broad components of emission lines by setting various
constraints on parameters such as amplitude, line width, and velocity offset.
[O III] $\lambda$5007 is often used as a tracer of ionized gas outflows in the
optical since it is isolated (i.e., no risk of blending with broad-lines) and
in a region free of significant stellar absorption. Evidence of outflow
activity is generally believed to manifest itself as a broad flux excess,
typically seen as an asymmetric wing that is blue-shifted relative to the
rest-wavelength emission (Woo et al., 2016; Manzano-King et al., 2019). In
addition to velocity shifts, widths of a few hundred to thousands of km s-1
have been reported in optical and NIR data (eg., Rodríguez-Ardila et al.,
2006; Müller-Sánchez et al., 2011; Harrison et al., 2014; McElroy et al.,
2015). These fast outflows can be seen on kiloparsec (kpc) scales (eg., Cresci
et al., 2015; Rupke et al., 2017; Müller-Sánchez et al., 2018b; Liu et al.,
2020) and could potentially be key contributors to suppressing star formation
(Fabian, 2012; King & Pounds, 2015; Costa et al., 2020). If the outflows are
driven by the AGN, then this BH feedback may lead to well-known scaling
relations, such as the $M_{\rm{BH}}$-$\sigma$. In addition, CL emission has
often been observed with strong outflows (Müller-Sánchez et al., 2011; Bohn et
al., 2021), making outflow detections a unique point of interest when
searching for and confirming AGN activity using CLs.

Through SDSS spectral fitting of [O III], we detect strong outflows in four
galaxies: J0852+2928, J0929+0026, J1233+0023, and J1333+6536 at a $>$ 95$\%$
confidence based on the F-test model comparison included in the code. We also
require the amplitude of the outflow component to be greater than 3$\sigma$ of
the noise level and FWHM to be 1$\sigma$ greater than the core component. This
confidence cut and parameter requirements result in a stringent selection
criteria. In the successful cases, the outflow parameters determined in [O
III] are used to constrain the outflow components found in other strong
emission lines (H$\alpha$, H$\beta$, etc.). These constraints include a fixed
amplitude ratio ($A_{outflow}/A_{core}$), FWHM, and velocity offset. This is
done since blending, particularly between H$\alpha$ and [N II], can be
problematic in identifying and fitting outflow components. We have listed
fluxes to the outflow components in Table A1.

A non-outflow detection worthy of note is J1036+0221 since it does show a high
confidence, $\sim$90$\%$. However, it is likely undergoing a merger event and
a number of mechanisms could be causing the broader [O III] profile, such as
superposition of two nuclei or tidal disruptions caused by the merger. Due to
these uncertainties, we do not include J1036+0221 in our outflow analysis.

We do not detect outflows in the rest of our sample, where they all have low
confidence levels ($<$ 65$\%$). However, this does not rule out the presence
of outflows in these galaxies. As Sexton et al. (2020) points out, signal-to-
noise (S/N) can play an important role in detecting outflows. Additionally,
spatial and spectral resolution can affect detection, as shown in Manzano-King
et al. (2019), where nine outflows are detected in Keck LRIS but only two of
these are detected in SDSS. Kadir et al. (in prep.) also find that high
extinction can inhibit outflow detection. Indeed, galaxies in our sample where
we do see outflows tend to have lower levels of extinction (see Tables 2 and
3). Thus the detection rate of outflows in our sample should be taken as a
lower limit.

Table 2: Summary of Galaxy Properties

Galaxy | W1-W2 | log(MBH) | E(B-V) | SFR | CL? | Outflow? | Overmass. | BPT | OVT ’92 | AGN
---|---|---|---|---|---|---|---|---|---|---
|  | ($M_{\odot}$) |  | ($M_{\odot}$ yr-1) |  |  | DMH? | AGN? | AGN? | Evidence?
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | (10) | (11)
J0122ne | — | — | 0.00 |  $<$0.40 | — | — | — | — | ✓ | ✓
J0122se | 1.60 | — | 0.80${}^{+0.11}_{-0.11}$ |  $<$3.47 | ✓aaNIR CLs detected in Satyapal et al. (2017). | — | — | — | — | ✓
J0122w | — | — | 1.82${}^{+0.07}_{-0.07}$ |  $<$8.57 | — | — | — | — | — | —
J0333 | 0.87 | — | 1.38${}^{+0.28}_{-0.31}$ | 4.00${}^{+2.16}_{-1.50}$ | — | — | — | — | — | —
J0750 | 1.00 | — | 1.27${}^{+0.49}_{-0.57}$ | 3.28${}^{+3.59}_{-1.91}$ | — | — | — | — | — | —
J0851 | 0.71 | 6.78$\pm$0.14 | 0.66${}^{+0.36}_{-0.40}$ | 0.36${}^{+0.32}_{-0.19}$ | — | — | — | — | ✓ | ✓
J0852 | 0.76 | — | 0.00 |  $<$0.18 | ✓ | ✓ | ✓ | ✓ | ✓ | ✓
J0929 | 0.85 | — | 1.28${}^{+0.08}_{-0.08}$ | — | ✓* | ✓ | — | ✓ | ✓ | ✓
J1032 | 0.74 | — | 0.80${}^{+0.25}_{-0.27}$ | 2.74${}^{+1.33}_{-0.96}$ | — | — | — | — | — | —
J1036 | 1.30 | — | 2.17${}^{+0.13}_{-0.13}$ |  $<$6.53 | ✓aaNIR CLs detected in Satyapal et al. (2017). | — | — | — | ✓ | ✓
J1228 | 0.72 | 6.80$\pm$0.32 | 2.50${}^{+1.25}_{-2.12}$ |  $<$3.19 | — | — | — | ✓ | ✓ | ✓
J1233 | 0.98 | — | 0.81${}^{+0.30}_{-0.34}$ |  $<$0.46 | ✓ | ✓ | ✓ | — | — | ✓
J1326 | 0.73 | — | 2.88${}^{+1.08}_{-1.67}$ |  $<$2.04 | — | — | — | — | — | —
J1333 | 0.73 | — | 0.18${}^{+0.33}_{-0.18}$ | — | ✓* | ✓ | — | ✓ | ✓ | ✓
J1554 | 1.14 | — | 1.59${}^{+0.47}_{-0.55}$ | 1.18${}^{+1.69}_{-0.78}$ | ✓ | ✓ | — | — | — | ✓

Note. — Columns: (1) Galaxy name. (2) WISE W1-W2 magnitude. (3) BH mass as
determined in Section 4.2 and 6. (4) Extinction based on the
H$\alpha$/H$\beta$ Balmer decrement. (5) Star-formation rate based on [O II]
(Kewley et al., 2004). We omit values if [Ne V] is detected and place upper
limits if the presence of [Ne V] cannot be determined. (6) Presence of NIR
CLs. An asterisk (*) signifies optical CLs are detected. (7) Evidence of
outflows. (8) Evidence of an overmassive DMH. (9) Galaxy falls within the AGN
region of the BPT diagram. (10) Galaxy falls within the AGN region of at least
one of the diagnostic diagrams in Osterbrock et al. (1992). (11) Any
indication of AGN activity.

###  3.2 Extinction

To quantify the extinction, we used the intrinsic line ratio of
H$\alpha$/H$\beta$ = 3.1, typically used for AGN (eg., Veilleux & Osterbrock,
1987; Osterbrock et al., 1992), and a Cardelli reddening law (Cardelli et al.,
1989) with an extinction factor of $R_{V}$ = 3.1. We used the narrow-line flux
measurements from the SDSS data (see Section 3.1.2), where we have decomposed
the H$\alpha$ and H$\beta$ emission into narrow and broad (outflow)
components. For galaxies where no broad component is detected, we used the
full emission line to obtain a flux. The value of E(B-V) for each galaxy is
listed in Table 2. Note that two galaxies, J0122+0100 (Northeast region) and
J0852+2928, have Balmer decrements below the intrinsic ratio so we did not
apply any extinction correction to them. For the rest of this article, we use
extinction corrected flux values unless otherwise specified.

###  3.3 Star-formation Rates

We estimated the SFRs of our sample through the use of the [O II]
$\lambda$3727 doublet indicator presented in Kewley et al. (2004). We list
these measurements in Table 2. While [O II] is useful for calculating SFRs,
complications can arise if an AGN is present and can ionize the [O II] gas in
the extended emission line regions. This is mainly seen in cases where AGN
ionization reaches beyond the NLR. In order to identify whether an AGN could
be ionizing [O II], the CL [Ne V] $\lambda$3426 is often used (Maddox, 2018).
As such, the presence of [Ne V] would indicate contamination of the [O II]
emission from the AGN and thus it cannot be used as a SF indicator.

We find [Ne V] emission in two targets, J0929 and J1333, and thus omit their
values from Table 2. For targets where we cannot confirm the absence of [Ne V]
(mainly due to the wavelength coverage of SDSS), we report their SFRs as upper
limits.

##  4 Evidence of AGN Activity

###  4.1 Coronal Line Detections

Figure 3: Zoom-in plots of [Si VI] emission and the surrounding region. The
best-fit line from emcee is plotted in red and the dash-dot green and blue
lines denote the rest-frame location of H2 1.957 $\mu$m and [Si VI],
respectively. Grey lines and shaded yellow regions signify the location of
skylines and telluric absorption that are in close proximity to [Si VI].

An effective method of identifying AGN activity is through the detection of
CLs. This is because CLs have higher ionization potentials than what is
typically produced by stellar processes. A total of seven out of the 13
bulgeless galaxies in our sample (54%) show CLs. We detect [Si VI] 1.9630
$\mu$m in the NIR spectra of five targets in our sample (see Figure 3 and
Table 2; fluxes listed in Table A1). In addition, Satyapal et al. (2017)
report the detection of [Si VI] in J0122+0100(SE) and [Si X] 1.4305 $\mu$m in
J1036+0221. They used a wider slit with a different placement for
J0122+0100(SE), which may explain why we did not observe [Si VI] in our NIRES
spectrum. We fit their [Si VI] emission line and include it in the following
analysis. For J1036+0221, we do not detect [Si X] since it is outside our
selected wavelength coverage for NIRSPEC. Additional details on these two
targets are included in Appendix B. While we include the detection of CLs in
these targets in our overall statistics, we only investigate the kinematics
and other properties of the CLs observed in our NIRSPEC and NIRES spectra.

Inspection of the SDSS spectra reveals optical CL emission in only two
targets, J0929+0026 and J1333+6536; these are marked with an asterisk in Table
2. We detect [Ne V] $\lambda$3426 in both of these galaxies, in addition to
[Si VI] mentioned above. Environmental effects have been shown to inhibit
optical CL detection. As suggested by comparisons between NIR and optical
spectra of Sy1 and Sy2, and the reduced strength of CLs in the latter (Nagao
et al., 2000; Gelbord et al., 2009), the dusty torus likely lowers the
detection frequency of such lines. This, along with the high extinction levels
seen in our sample, could explain the low detection rate of optical CLs in our
sample.

Figure 4: [Si VI] flux vs W2 (4.6 $\mu$m) flux. [Si VI] detections are
represented as blue stars. Note that we include the [Si VI] detection from
S14. Crosses represent targets with no [Si VI] emission detected. The arrows
indicate these are 3$\sigma$ upper limit fluxes to [Si VI]. Blue symbols
represent galaxies with AGN activity while red represents galaxies with
stellar emission dominating the spectra. The solid line is the best-fit line
to the data found in Müller-Sánchez et al. (2018a).

It is not surprising that [Si VI] is the only prominent NIR CL we detect. It
has a lower ionization potential (IP = 167 eV) than other CLs and benefits
from being located in a region free of stellar absorption. Indeed, other
studies find [Si VI] to be the most common CL, with Rodríguez-Ardila et al.
(2011) finding it in 56$\%$ of their sample and Lamperti et al. (2017) finding
it in 33$\%$ of theirs.

The 54% CL detection rate in our sample should be regarded as a lower limit,
as there are several factors that can affect the detectability of CLs. For
instance, faint lines can be easily diluted by the underlying continuum and/or
they can fall below detection limits. To obtain estimates for the expected
flux values for the [Si VI] lines that we do not detect, we make use of the
relation reported by Cann et al. (2021) between WISE W2 (4.6 $\mu$m) flux and
[Si VI] flux. We plot this relation in Figure 4. Upper limit fluxes to the
non-[Si VI] detections were calculated by integrating over a Gaussian with a
width equaling the resolution element and the amplitude equaling the 1$\sigma$
noise level where [Si VI] should appear. This value was multiplied by three to
obtain the 3$\sigma$ upper limit that is plotted. We include the AGN sample
(black dots) from Müller-Sánchez et al. (2018a), from which the plotted line
of best fit is derived in order to show the scatter in the relation. Figure 4
shows that the majority of our non-detections (crosses) are indeed the targets
with the lowest expected fluxes.

Figure 5: AGN diagnostic plots derived by Osterbrock et al. (1992), where we
include their sample. We plot our sample as blue and red stars, where blue
represents galaxies with clear signatures of AGN activity and red represents
galaxies whose emission is dominated by stellar processes. Fluxes to emission
lines are listed in A1.

It is worthwhile to note the [Si VI] emission in J1233+0023. It has the lowest
luminosity and spatial extent of [Si VI] in our sample. As such, this faint
emission is susceptible to dilution from other sources of emission. Indeed, we
see no trace of [Si VI] emission if we use the extraction aperture listed in
Table 1. Only when a smaller aperture that sampled the very center was used
could we confirm the presence of [Si VI]. Although this is the sole case in
our sample, caution should be taken when using large apertures.

The majority of our non-detections lie below and to the left of the [Si VI]
measurements, suggesting that deeper observations are likely required to
detect any emission (see Figure 4). Inspection of the SFRs (see Section 3.3)
shows that galaxies with no [Si VI] emission have SFRs about an order of
magnitude higher than those with [Si VI] emission. Visual inspection of some
of these targets show that they are likely involved in an on-going merger
event. In such an event, tidal forces could funnel gas towards the central
regions and fuel star formation. Although these results are not indicative of
starburst activity, they do suggest an increase of SF that could increase the
continuum level and make weak emission lines, such as CLs, more difficult to
detect.

###  4.2 NIR Broad Emission from Broad-Line Region

The NIR spectral region includes several important recombination lines,
including Pa$\alpha$ and Pa$\beta$. Like H$\alpha$ and H$\beta$, these Paschen
lines can be used to trace the broad-line gas from an AGN. They also benefit
from being less affected by dust obscuration. As such, the ‘hidden’ broad-line
(HBL) region can arise in cases where broad emission is present in the NIR but
obscured in the optical, betraying the presence of an AGN.

Inspection of the NIR spectra reveals hidden broad-line emission (Pa$\alpha$)
in two of our targets, J0851+3926 (see also Bohn et al., 2020) and J1228+5814.
Our detection rate (15$\%$) is similar to that of other studies such as
Lamperti et al. (2017), who find HBLs in 10$\%$ of their Sy2 sample, and
Veilleux et al. (1997) who find HBLs in 27$\%$ of theirs.

Observations for both of our targets with HBL were conducted on two separate
nights, approximately one year apart. While broad emission is certainly
indicative of AGN activity, Baldassare et al. (2016) and other follow-up
studies of AGN candidates with broad emission have shown that supernovae (SNe)
and other stellar activity can produce similar broad profiles. Type II SNe
(Pritchard et al., 2012) and luminous blue variables (Smith et al., 2011) are
known to produce broad recombination lines up to thousands of km s-1. If the
broad Pa$\alpha$ observed were powered by SNe, the broad emission would have
persisted for more than a year, and this in turn would indicate that the SNe
would likely be Type II-P. Using this time scale, we would expect to see other
NIR SN features such as O I, Mg I, and Ca I (e.g., Rho et al., 2018). However,
we do not see any of these features in either of our NIR observations.
Additionally, we would expect the line profiles to change significantly over
this time (Rho et al., 2018) but our width measurements are consistent with
each other: 1490 and 1360 km s-1 for J0851+3926, and 1640 and 1840 km s-1 for
J1228+5814.

Another potential origin of a broad-line could be powerful outflows driven by
star formation. Broad, symmetric components to emission lines are observed in
some starburst galaxies (Martin, 1998; Westmoquette et al., 2008; Manzano-King
et al., 2019). However, these galaxies show broad emission in other lines,
particularly in [O III]$\lambda 5007$. As mentioned in Section 3.1.2, we
utilized BADASS to check for the presence of any outflow component in the
optical spectra. All reasonable criteria came back negative for outflows in
these two targets, thus it is unlikely that outflows are affecting the broad-
line emission. We conclude that the most likely origin of the observed broad
Pa$\alpha$ is the broad-line region of an AGN, providing strong evidence that
these two targets have AGN activity.

###  4.3 NIR Diagnostic Diagrams

Optical line ratios, such as the BPT diagram shown in Figure 1, indicate AGN
activity in only four of the 13 targets in our sample. With the inclusion of
NIR data, we can use additional AGN diagnostics that are more insensitive to
dust obscuration. Osterbrock et al. (1992) use H$\alpha$, [S II]
$\lambda\lambda$6718+6732, [O II] $\lambda\lambda$7320+7330, and [S III]
$\lambda\lambda$9069+9531 fluxes to detect AGN activity. We plot these line
ratio diagrams in Figure 5, where we include the AGN and star-forming samples
from Osterbrock et al. (1992). We overplot narrow-line fluxes of our sample
(star symbols) and exclude the galaxies with no measurable [O II] or [S III]
emission. In cases where [S III] $\lambda$9531 is measurable but [S III]
$\lambda$9069 is not, we use the intrinsic flux ratio of [S III]
$\lambda$9531/$\lambda$9069 = 2.6 to obtain flux values for the latter.
Lastly, for J0122+0100, SDSS provides three sets of spectra: one for the west
galaxy and two for the east galaxy, a north and south component separated by
about 2”. We include all three of these in Figure 5.

Most galaxies with CLs and HBLs fall within the scatter of the other AGN. As
for the rest of the sample, the line ratios of J1036+0221 and J0122+0100(ne)
place them within the AGN region of Figure 5. J0122+0100(w+se) do not fall
consistently in the same region but they generally do not fall within the
scatter of the star-forming galaxies. In addition to the NIR line ratios
presented here, Satyapal et al. (2017) report Chandra and XMM-Newton X-ray
observations for J1036+0221 and J0122+0100(w+se). The observed luminosities of
all three sources are significantly higher ($>$7.5 times greater) than the
luminosities expected from X-ray binaries. This, along with CLs detected by
Satyapal et al. (2017), indicate the presence of AGN in these galaxies.

Table 3: Outflow and [Si VI] Properties

Galaxy |  $[\rm{O\;III}]$ $v\rm{{}_{50}}$ |  $[\rm{Si\;VI}]$ $v\rm{{}_{50}}$ |  $[\rm{O\;III}]$ $W\rm{{}_{80}}$ ($v\rm{{}_{out}}$) |  $[\rm{Si\;VI}]$ $W\rm{{}_{80}}$ ($v\rm{{}_{out}}$) |  $[\rm{Si\;VI}]$ Radius | log($L_{[\rm{SiVI}]}$) | log($L\rm{{}_{AGN}}$)
---|---|---|---|---|---|---|---
| (km s-1) | (km s-1) | (km s-1) | (km s-1) | (kpc) | ($\rm{erg\;s^{-1}}$) | ($\rm{erg\;s^{-1}}$)
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8)
SDSS J0852+2928 | -260$\pm$20 | -250$\pm$30 | 1120$\pm$40 (820$\pm$40) | 2130$\pm$220 (1315$\pm$140) | 0.8 | 39.97${}^{+0.06}_{-0.08}$ | 42.81${}^{+0.09}_{-0.12}$
SDDS J0929+0026 | -40$\pm$5 | -510$\pm$40 | 700$\pm$20 (390$\pm$15) | 2510$\pm$440 (1765$\pm$260) | 1.4 | 41.07${}^{+0.10}_{-0.12}$ | 44.65${}^{+0.06}_{-0.07}$
SDSS J1233+0023 | -120$\pm$20 | -70$\pm$5 | 510$\pm$60 (375$\pm$50) | 310$\pm$70 (225$\pm$40) | 0.3 | 38.19${}^{+0.07}_{-0.09}$ | 42.78${}^{+0.16}_{-0.25}$
SDSS J1333+6536 | -110$\pm$15 | -40$\pm$5 | 470$\pm$50 (345$\pm$40) | 490$\pm$50 (285$\pm$30) | 0.4 | 39.98${}^{+0.04}_{-0.04}$ | 43.19${}^{+0.16}_{-0.27}$
SDSS J1554+1457 | — | -20$\pm$15 | — | 1720$\pm$210 (880$\pm$120) | 1.2 | 39.99${}^{+0.07}_{-0.08}$ | 42.96${}^{+0.26}_{-0.35}$

Note. — Columns: (1) Galaxy name. (2) Velocity offset of the [O III]
$\lambda$5007 outflow component from the core component. (3) Velocity offset
of [Si VI] from rest-wavelength. (4) $W\rm{{}_{80}}$ values of the [O III]
$\lambda$5007 outflow component. In parentheses are $v\rm{{}_{out}}$ values as
defined in Equation 1. (5) Same as the previous column but for [Si VI]. (6)
Spatial extension of [Si VI]. (7) Extinction-corrected [Si VI] luminosities.
(8) Extinction-corrected AGN luminosities.

While no single line ratio can confidently separate AGN from stellar
ionization, our bulgeless sample shows optical and NIR line ratios that, when
considered collectively, strongly suggest the presence of AGN. This lack of
strong stellar activity not only supports ionization from the AGN, but also
indicates the outflows detected (discussed in Section 5) are of AGN origin.

###  4.4 Summary of AGN Indicators

In the sections above, we discussed confirming AGN in our sample using a
variety of methods, including CL detections, broad-line emission, and AGN
diagnostic diagrams. Of our sample, we report CL detection in 54$\%$, hidden
broad-lines in 15$\%$, and NIR AGN line ratios in 54$\%$. Collectively, this
results in 69$\%$ (9/13) unique targets with at least one indication of AGN
activity. Indeed, our results show that MIR color are an effective tool to
select AGN, with over half of the confirmations coming from galaxies that
would not have been classified as AGN from optical studies. For those targets
for which we find no clear indication of AGN, we find they have generally
twice the extinction levels and an order of magnitude higher SFRs than those
for which we find evidence of AGN in the NIR. If these galaxies do indeed have
an AGN, then they are likely heavily obscured or the emission from stellar
processes is dominating the optical and NIR spectra. For the rest of the
article, we will refer to galaxies with confirmed signatures of AGN activity
as ‘AGN Confirmed’ and those without as ‘SF Dominated’.

##  5 Outflows

In Section 3.1, we reported the detection of fast outflows in [O III] in four
of the galaxies in our sample and in Section 4.1 we identified an additional
target with an outflow in [Si VI]. Thus, five out of the nine (54%) AGN-
confirmed galaxies show fast outflows, whereas none of the SF-dominated
galaxies do. This is consistent with other studies that find a higher
incidence of outflows in AGN hosts as compared to star forming galaxies (e.g.
Cicone et al., 2014; Harrison et al., 2016; Concas et al., 2017; Leung et al.,
2019; Lutz et al., 2020; Avery et al., 2021, W. Matzko et al. in preparation).

In this section, we report an observed strong correlation between the
detection of outflows and that of CLs. We also present the outflow kinematics
and estimated energies, and provide supporting evidence that outflows in
bulgeless galaxies may be intrinsically different than those in galaxies with
merger dominated histories.

###  5.1 Outflows and Coronal Lines

CLs are often associated with outflows, where the blue-shifted emission
profiles of CLs have been attributed to outflow kinematics (Rodríguez-Ardila
et al., 2006; Müller-Sánchez et al., 2011). Indeed, Liu et al. (2020) and Bohn
et al. (2021) find that the galaxies with the strongest and fastest outflows
have the strongest and most numerous CL detections. Here, we report similar
findings, where all the galaxies with detectable outflows also have CLs. We
note that while J1554+1457 has NIR CL emission with a fast outflow, it does
not show any evidence of an outflow in its optical spectrum. A possible reason
for this is the high level of extinction, E(B-V) = 1.59, that could be
inhibiting the detection of a small outflow component in the SDSS spectra.

A number of scenarios could give rise to the connection between outflows and
CLs that we observe. One such case is if the AGN is responsible for both
producing the outflow and ionizing the CL gas: CL emission requires a highly
energetic radiative source, and this source in turn could drive a highly
energetic outflow. Other scenarios are more causal. Relativistic outflowing
winds have been known to produce strong shocks in the interstellar medium
(ISM) surrounding the AGN (Fabian, 2012; King & Pounds, 2015; Harrison et al.,
2018). These shocks can heat gas, which in turn can provide at least some of
the necessary ionization for CL emission. Although photoionization is believed
to be the main mechanism to produce CL emission, some studies have shown that
the addition of energy input from shocks can help the observed line ratios
better replicate those predicted by ionization models (Rodríguez-Ardila et
al., 2006; Müller-Sánchez et al., 2011). Lastly, the outflowing winds may be
simply removing the obscuring medium, allowing for a more clear view of the CL
region.

###  5.2 Kinematics of Outflows and Coronal Lines

Due to the connection between CLs and outflows, CLs have been used to trace
the kinematics of outflows (Rodríguez-Ardila et al., 2006; Müller-Sánchez et
al., 2011). In Table 3, we list gas kinematics measured from the [O III] and
[Si VI] lines. To calculate the velocity of an outflow, we can utilize two
values: $v_{50}$ and $W\rm{{}_{80}}$ (Harrison et al., 2014). Here, $v_{50}$
is the velocity offset of the outflow component from the core component while
$W\rm{{}_{80}}$ is the width containing 80$\%$ of the line flux. For a single
Gaussian profile, $W\rm{{}_{80}}$ = 1.09$\times$FWHM. In the cases where only
one [Si VI] component was fit, we use the full emission profile and set
$v_{50}$ to be the offset from rest-wavelength. Using these parameters, we can
define the outflow velocity as follows

$v_{\rm{out}}=-v_{50}+\frac{\rm{W_{80}}}{2}$ (1)

A general trend seen here is the outflow velocities associated with CLs (mean
$\sim$890 km s-1) tend to be higher than those seen in the narrow-line region
(mean $\sim$480 km s-1). Since the CL region is believed to lie closer to the
SMBH, this trend would suggest a decelerating outflow. Here, a high velocity
wind would originate near the AGN and would slow down as it encounters the
surrounding ISM.

We additionally report the spatial extent of [Si VI] emission and bolometric
AGN luminosities in Table 3. We derived the AGN luminositites from the
measured [O III] $\lambda$5007 flux. Empirical bolometric correlation factors
from Lamastra et al. (2009) were used: $L\rm{{}_{AGN}}$ = 87
$L_{[\rm{O\;III}]}$ for 38 $<$ log($L_{[\rm{O\;III}]}$) $<$ 40 and
$L\rm{{}_{AGN}}$ = 142 $L_{[\rm{O\;III}]}$ for 40 $<$ log($L_{[\rm{O\;III}]}$)
$<$ 42\. We find stronger [Si VI] emission in galaxies with more luminous AGN,
further suggesting that the AGN is the ionizing source for the CL emission in
this sample. Due to the strong correlation between CLs and outflows, this
would also indicate that the AGN are also responsible for driving the
outflows. Although we do not find a strong correlation between outflow
velocities and AGN luminosity (Pearson coefficient = -0.37), we do see a
correlation with the spatial extent of [Si VI] and outflow speed as calculated
through [Si VI] (Pearson coefficient = 0.86). A likely cause of this is that
the faster and more energetic outflows are less inhibited by the ISM and can
more easily clear out the surrounding gas. Alternatively, the faster, more
extended outflows could be expanding into regions that are less dense or
obscured.

###  5.3 Outflow Energies

The energies of the outflows can be calculated assuming a time averaged, thin-
shell, free wind model (Shih & Rupke, 2010). However, the outflows in the SDSS
data are not spatially resolved and thus some simplifying assumptions need to
be made on the size of the outflows. From Rupke et al. (2005), the outflow
energies can be calculated using the following simplified equation:

$\frac{dE}{dt}=\frac{1}{2}(v_{50}^{2}+3\sigma^{2})\frac{dM}{dt}$ (2)

where $\sigma$ = $W_{80}$/2.563. The outflow mass rate, $dM/dt$, can be
expressed as:

$\frac{dM}{dt}=\frac{M_{out}v_{out}}{R_{out}}$ (3)

where $M_{out}$ is the total mass of the outflowing gas and $R_{out}$ is the
upper limit on the radius of the outflow. From Osterbrock & Ferland (2006),
$M_{out}$ can be calculated from:

$\frac{M_{out}}{M_{\odot}}=4.48\bigg{(}\frac{L_{H\alpha}}{10^{35}\;\rm{erg}\;s^{-1}}\bigg{)}\bigg{(}\frac{<n_{e}>}{1000\;\rm{cm}^{-3}}\bigg{)}^{-1}$
(4)

where we assume Case B recombination with $T$ = 104 K. Here, $L_{H\alpha}$ is
the extinction corrected luminosity of the outflow component of H$\alpha$ and
$n_{e}$ is the electron density, which we estimated using the [S II]
$\lambda$6716/$\lambda$6731 relation (Sanders et al., 2016). The uncertainties
in $n_{e}$ are relatively large, and are incorporated into the errors listed
in Table 4. Lastly, upper limits to $R_{out}$ were calculated using the
$R_{out}$ \- $L_{[OIII]}$ relation derived in Kang & Woo (2018). We multiply
these values by a factor of 2 to account for the far side of the outflow that
is blocked by the galaxy. Lower limits for the mass and energy rates of the
outflows are listed in Table 4.

Table 4: Energetics of the Outflows

Galaxy | log($M_{out}$) | log($dM/dt$) | log($dE/dt$)
---|---|---|---
| ($M_{\odot}$) | ($M_{\odot}$ yr-1) | (erg s-1)
J0852+2928 | 5.7$\pm$0.21 |  $>$-0.6 |  $>$40.8
J0929+0026 | 7.6$\pm$0.25 |  $>$0.6 |  $>$41.4
J1223+0023 | 6.1$\pm$0.24 |  $>$-0.5 |  $>$40.2
J1333+6536 | 4.3$\pm$0.19 |  $>$-2.4 |  $>$38.2

Note. — Columns: (1) Galaxy name. (2) Total mass of the outflow. (3) Mass
outflow rate. (4) Kinetic energy outflow rate.

Comparing the mass and mass outflow rates of our galaxies to those of the
disk-dominated sample from Smethurst et al. (2019), we find that the outflows
presented here have comparable values. Smethurst et al. (2019) find that the
outflow rates of disk-dominated galaxies are lower than those measured in
galaxies with merger dominated histories. They attribute this discrepancy to
differences in black hole spin and accretion geometries that are a result of
accretion by secular processes. As such, this would suggest that outflows in
bulgeless galaxies may be intrinsically different than those found in galaxies
that have had a significant merger history.

##  6 Scaling Relations

Since two of our targets show broad emission from the BLR, we can estimate
their BH masses through the virial relation:

$M_{\rm{BH}}=\mathnormal{f}\frac{V^{2}R}{G}$ (5)

where $\mathnormal{f}$ is the virial coefficient; $V$ is the velocity of the
broad-line gas; $R$ is the distance from the broad emission gas to the central
continuum source which can be estimated using relations derived from
reverberation mapping; and $G$ is the gravitational constant. The FWHM of the
broad emission line can be used for the value of $V$, and the value of $R$ is
estimated empirically using the optical luminosity of the AGN as a proxy
(Kaspi et al., 2005; Bentz et al., 2013).

The BH mass was obtained following the estimators presented by Kim et al.
(2018), where they adopted the virial factor log $\mathnormal{f}$ = 0.05 $\pm$
0.12 derived by Woo et al. (2015). From Kim et al. (2018), their Equation 10,

$\frac{M}{M_{\odot}}=10^{7.07\pm
0.04}\left(\frac{L_{\rm{Pa}\alpha}}{10^{42}\;\rm{erg}\;\rm{s}^{-1}}\right)^{0.49\pm
0.06}\left(\frac{\rm{FWHM}_{\rm{Pa}\alpha}}{10^{3}\;\rm{km}\;\rm{s}^{-1}}\right)^{2}$
(6)

where the FWHM of broad Pa$\alpha$ is the analog to the velocity in the virial
mass estimator and $L_{\rm{Pa}\alpha}$ of the broad component is the analog to
the distance to the BLR. From Equation (6), our NIRSPEC and NIRES measurements
give a BH mass of log($M_{\rm{BH}}/M_{\odot}$) = 6.59$\pm$0.32 and
6.78$\pm$0.14 for J0851+3926, and 6.83$\pm$0.27 and 6.80$\pm$0.32 for
J1228+5814. The listed uncertainties come from the random error estimates in
the fitting process. Accounting for systematic uncertainties, virial BH mass
estimates typically have errors of 0.3 - 0.5 dex (eg., Shen, 2013; Reines &
Volonteri, 2015). For a detailed description on virial mass uncertainties, see
Sexton et al. (2019).

Bohn et al. (2020) compiled a sample of galaxies with secure BH mass estimates
and obtained $M_{\rm{BH}}$–$M_{\rm{bulge}}$ and
$M_{\rm{BH}}$–$M_{\rm{stellar}}$ relations. They found that bulgeless and/or
disk dominated galaxies fall closer to the $M_{\rm{BH}}$–$M_{\rm{stellar}}$
relation, despite it having more scatter than the $M_{\rm{bulge}}$ relation.
Moreover, they also found that bulgeless galaxies best correlate with late-
type galaxies in the $M_{\rm{BH}}$–$M_{\rm{stellar}}$ relation. Indeed, with
an estimated $M_{\rm{stellar}}$ = 10.61 (Chang et al., 2015), J0851+3926 only
lies 0.37 dex below the late-type relation. Similarly, J1228+5814 lies 0.41
dex below the same relation. Thus, it appears that these two bulgeless
galaxies, which have presumably grown in the absence of major mergers, have
managed to grow their SMBH enough to remain within the scatter of the
$M_{\rm{BH}}$–$M_{\rm{stellar}}$ relation.

An important question for AGN hosts lacking a substancial bulge is what
mechanism initiated the in-fall of gas towards the center to turn the AGN on.
Close inspection of J0851+3926 reveals a faint tail leading to a small galaxy
(see Figure 2). We obtained spectra of this target with the goal of estimating
a redshift, however the spectra is featureless in all five orders of NIRES.
While it is uncertain whether this is a true interacting companion,
2-dimensional surface brightness decompostions show that J0851+3926 has
undisturbed disk. Thus, it is unlikely that this event is a major merger.
Interestingly, as we will discuss in Section 7, counter-rotation is seen
within the central kpc (see Figure 6). This could have been a product of an
interaction with the aforementioned companion. Alternatively, a galactic bar
could be present that is altering the angular momentum of the gas (Piner et
al., 1995; Sheth et al., 2002; Wang et al., 2012). Follow-up, high resolution
imaging will be needed to resolve the true nature of the central region.

Imaging of J1228+5814 shows two bright sources in the central region. Two-
dimensional surface brightness decompositions confirm this; adding a second
disk component greatly reduces the residuals of the fit. Some possible
explanations of this include an off-centered AGN or an on-going merger event.
Inspection of our spectroscopic data also show two sources. Only the southern
one shows broad emission while the northern source only shows absorption
features. There is no significant redshift difference between the absorption
features in the two sources. If a merger event is indeed occurring, this could
provide the in-fall of gas needed to start the gas accretion that is fueling
the current AGN episode. However, the lack of a substantial bulge still
indicates a relatively mergerless past, where mergers could not have
contributed significantly to the growth of the SMBH.

Figure 6: Velocity curves, corrected for inclination, showing the gas
kinematics of the galaxies in our sample that show extended emission lines.
The black dotted line represents velocities expected from an NFW model,
assuming a concentration parameter of 10. The shaded blue/red regions
represent the concentration parameter varying from 8 to 15. Here, blue
identifies targets with confirmed AGN and red identifies targets dominated by
stellar emission. Images from SDSS and inclination values are also included.
Notice that J0851+3926 might show signs of a counter-rotating bar, as
discussed in Appendix B and presented in detail in (Bohn et al., 2020).

In conclusion, both targets fall within the scatter of other late-type
galaxies and the $M_{\rm{BH}}$ we measure are some of the highest reported for
bulgeless galaxies in the literature. Although follow-up observations are
needed to ascertain the triggering mechanism of the AGN, it is certainly
intriguing how these BHs grew to supermassive sizes through secular processes
in the absence of major mergers that would have also built up a significant
bulge component.

##  7 Probing Dark Matter via Rotation Curves

Spatially extended emission is detected in a number of galaxies, enabling us
to perform analysis on the kinematics of the gas (see Figure 6). We describe
in Appendix C the procedure used to extract rotation velocities for seven
targets where this was possible. The rotation curves of these galaxies showing
measurable extended gas emission are shown in Figure 6.

We mainly plot Pa$\alpha$ but also report [S III] 0.953 $\mu$m and He I 1.083
$\mu$m if detectable. Also note that two observed velocity profiles are
plotted for J0851+3926. This is because we observed this target on two
separate occasions with the slits positioned perpendicular to each other (see
Figure 2). Plotted error bars include spectral and fitting errors as well as
the uncertainties in the ellipticity and the value of q.

The shaded regions of Figure 6 represent velocity curves assuming a Navarro-
Frenk-White (NFW) dark matter density profile (Navarro et al., 1996) and using
abundance matching from Moster et al. (2013) to calculate the corresponding
halo mass starting from the stellar masses of our targets. We assume a
concentration parameter $c=10$ (dotted black line in Figure 6), but vary c
between 8 – 15 to illustrate the uncertainty in this parameter (shaded areas).
Our stellar mass, M⋆, estimates come from Chang et al. (2015), who performed
SED fitting on optical and IR data. These values are also consistent with the
MPA/JHU catalog666https://wwwmpa.mpa-garching.mpg.de/SDSS/. The halo mass and
other associated values are listed in Table 5.

Table 5: Gas Rotation and Galaxy Parameters

Galaxy | log(M⋆) | log(MDM) | Inc. Angle | Outflow |  $>$ NFW Velocities
---|---|---|---|---|---
| (M⊙) | (M⊙) |  |  |
(1) | (2) | (3) | (4) | (5) | (6)
SDSS J0333+0107 | 10.67${}^{+0.10}_{-0.08}$ | 12.23${}^{+0.30}_{-0.17}$ | 58∘ | — | —
SDSS J0851+3926 | 10.61${}^{+0.10}_{-0.09}$ | 12.13${}^{+0.26}_{-0.17}$ | 53∘ | — | —
SDSS J0852+2928 | 10.22${}^{+0.09}_{-0.09}$ | 11.69${}^{+0.11}_{-0.11}$ | 48∘ | ✓ | ✓
SDDS J0929+0026 | 11.13${}^{+0.02}_{-0.09}$ | 13.40${}^{+0.17}_{-0.33}$ | 63∘ | ✓ | —
SDSS J1032+3617 | 10.83${}^{+0.09}_{-0.10}$ | 12.56${}^{+0.32}_{-0.29}$ | 22∘ | — | —
SDSS J1233+0023 | 10.01${}^{+0.10}_{-0.08}$ | 11.54${}^{+0.12}_{-0.10}$ | 55∘ | ✓ | ✓
SDSS J1333+6536 | 10.93${}^{+0.08}_{-0.09}$ | 12.84${}^{+0.31}_{-0.30}$ | 27∘ | ✓ | —

Note. — Columns: (1) Galaxy name. (2) Total stellar mass of the galaxy as
determined in Chang et al. (2015). (3) Dark matter halo mass estimates as
calculated through abundance matching. (4) Inclination angle of the galaxy (5)
Presence of an outflow. (6) Observed rotational gas velocities are greater
than NFW curve.

We find that, in general, our rotation curves are consistent with the
estimates from NFW halos with masses estimated from abundance matching
following Moster et al. (2013). However, two galaxies, J0852+2928 and
J1233+0023, are worth highlighting since they have observed velocities that
are significantly greater than those predicted by the NFW curve. They are both
isolated and thus disruptions from a merger event are unlikely.

A more compelling, albeit speculative, interpretation is that these two
galaxies inhabit a dark matter halo (DMH) that is more massive than estimates
from abundance matching using their stellar mass. This would then indicate
that some feedback process could have suppressed star formation, leading to
the lower stellar galaxy mass. Since AGN-driven outflows are detected in both
of these targets, winds could have expelled gas from the central regions and
help lower star formation as a result of AGN feedback.

To quantify the discrepancy between the measured stellar mass and expected DMH
mass of these two targets, we plot the $M_{\rm{stellar}}$–$M_{\rm{H}}$
relation in Figure 7 as derived in Moster et al. (2013). Here, we plot the
stellar mass of our sample (as derived in Chang et al., 2015) against the DMH
mass as calculated from the observed velocities in our data. Due to their high
observed velocities, the estimated DMH mass of the two targets places them
about 0.7 and 1.1 dex below the relation, outside the general scatter of the
other targets.

Figure 7: Total stellar mass vs. halo mass relation as calculated in Moster et
al. (2013) through abundance matching. The colored contours represent one,
two, and three sigma errors of the relation. Plotted as diamonds are the
measured stellar mass and expected DMH mass of our sample. Blue represents
galaxies with confirmed AGN while red represents targets whose emission is
dominated by stellar processes.

When comparing these two with the other five targets, we see no distinguishing
characteristics that would cause their stellar masses to be significantly
underestimated. If the AGN is the source of regulating star formation, then
this could lead to an intriguing and unique method of analyzing the effects of
AGN feedback through rotation curves. However, further investigation with a
larger sample and follow-up high-resolution IFS data will be needed to
properly analyze the impact of AGN feedback on rotational velocities and
assess the timescales on which AGN outflows affect star-formation in the local
ISM.

As for the two targets with detected outflows but that do not show evidence of
residing in a overmassive DMH (J0929+0026 and J1333+6536), a number of
circumstances could explain why we do not see fast velocities. There is
evidence of dust obscuration in J0929+0026 and a galactic bar in J1333+6536
that could be affecting the velocity profiles (see Appendix B.4 for further
details). Thus, it is difficult to judge what effect, if any, the outflows may
be having on the mass distribution of these galaxies.

##  8 Conclusion

In this article, we presented Keck NIR spectroscopy of a sample of candidate
AGN hosted in bulgeless galaxies. These galaxies were selected through MIR
selection techniques and many are not classified as AGN by optical surveys. As
such, we analyzed optical and NIR spectra to confirm AGN activity, and we also
examined other characteristics that may be indicative of AGN feedback. The
main results are as follows:

• We report evidence of AGN activity in 9/13 (69$\%$) galaxies through NIR CL
emission, broad emission, and Osterbrock et al. (1992) NIR line ratios.

• We detect strong [Si VI] 1.9630 $\mu$m in five galaxies. Due to the high IP
of [Si VI] (167 eV), this strongly suggests AGN activity. Two of these targets
also have [Ne V] $\lambda$3426 optical CL emission. Including detections of CL
in two other targets of our sample by Satyapal et al. (2017), our total CL
detection rate is 54% (7/13). Most of our non-detections of CLs can be
explained by emission lines falling in telluric absorption, high extinction,
or requiring deeper observations.

• We detect signatures of outflows in five of our targets, all of which have
NIR CL detections suggesting a strong correlation between the two. The outflow
velocities measured through [Si VI] (mean $\sim$890 km s-1) tend to be faster
than those measured through [O III] (mean $\sim$480 km s-1), which is
consistent with a decelerating outflow. In addition, we see a trend between
AGN luminosity and [Si VI] luminosity which suggests that CL emission, and
thus most likely the outflows, are of AGN origin.

• We observe a significant correlation between the spatial extent of the [Si
VI] emission and the velocity of the outflowing coronal gas, with the fastest
outflows (W80 $\sim$2000 km s-1) extending to over $\sim$1 kpc from the center
of the galaxy, while the slower outflows (W80 $\sim$400 km s-1) tend to be
confined to within a few hundred pc.

• Estimates to the mass and energies of the outflows in our sample are similar
to those of disk-dominated galaxies with AGN-driven outflows, but are less
than those of bulge-dominated galaxies. Our results are in agreement with
those of (Smethurst et al., 2021), suggesting that merger-free galaxies may
have outflows that are intrinsically different from those of galaxies with
significant merger histories.

• We report virial estimates to BH masses in two galaxies of our sample. Both
of these targets show broad Pa$\alpha$ with no clear indication of broad-lines
in their optical spectra. Their BH mass estimates,
log($M_{\rm{BH}}/M_{\odot}$) = 6.78 and 6.80, respectively, place them both
well within the scatter of other late-type galaxies in the
$M_{\rm{BH}}$–$M_{\rm{stellar}}$ relation. More importantly, the lack of a
strong bulge component indicates that secular processes, likely independent of
major mergers, grew these BHs to supermassive sizes.

• Inspection of rotation curves reveals two targets with observed velocities
significantly greater than those predicted by the NFW curve. This would
suggest an unusually massive DMH compared to their observed stellar mass. In
such interpretation, some feedback process could have quenched star formation,
leading to a smaller stellar mass. Since outflows likely originating from the
AGN are detected in both these galaxies, AGN feedback regulating star
formation is certainly an intriguing possibility.

ACKNOWLEDGMENTS

We thank Lisa Prato and Remington Sexton for their assistance with their
codes, REDSPEC and BADASS, and George Becker for assisting with the NIR
reduction pipeline.

We thank Dr. Percy Gomez, Dr. Gregg Doppmann, and Dr. Josh Walawender for
supporting our Keck observations. Partial support for this project was
provided by the National Science Foundation, under grant No. AST 1817233. We
also thank Dr. Randy Campbell and the support provided by the Keck Visiting
Scholars Program.

LVS acknowledges financial support from NSF AST 1817233 and NSF CAREER 1945310
grants.

Some of the data presented herein were obtained at the W. M. Keck Observatory,
which is operated as a scientific partnership among the California Institute
of Technology, the University of California and the National Aeronautics and
Space Administration. Use of this observatory was made possible by the
generous financial support of the W. M. Keck Foundation.

The authors wish to recognize and acknowledge the very significant cultural
role and reverence that the summit of Mauna Kea has always had within the
indigenous Hawaiian community. We are most fortunate to have the opportunity
to conduct observations from this mountain.

Funding for the SDSSI/II has been provided by the Alfred P. Sloan Foundation,
the Participating Institutions, the National Science Foundation, the U.S.
Department of Energy, the National Aeronautics and Space Administration, the
Japanese Monbukagakusho, the Max Planck Society, and the Higher Education
Funding Council for England. The SDSS Website is http://www.sdss.org/. SDSS is
managed by the Astrophysical Research Consortium for the Participating
Institutions. The Participating Institutions are the American Museum of
Natural History, Astrophysical Institute Potsdam, University of Basel,
University of Cambridge, Case Western Reserve University, University of
Chicago, Drexel University, Fermilab, The Institute for Advanced Study, the
Japan Participation Group, Johns Hopkins University, The Joint Institute for
Nuclear Astrophysics, the Kavli Institute for Particle Astrophysics and
Cosmology, the Korean Scientist Group, the Chinese Academy of Sciences
(LAMOST), Los Alamos National Laboratory, the Max Planck Institute for
Astronomy (MPIA), the Max Planck Institute for Astrophysics (MPA), New Mexico
State University, Ohio State University, University of Pittsburgh, University
of Portsmouth, Princeton University, the United States Naval Observatory, and
the University of Washington.

This publication makes use of data products from the Wide-field Infrared
Survey Explorer, which is a joint project of the University of California, Los
Angeles, and the Jet Propulsion Laboratory/California Institute of Technology,
funded by the National Aeronautics and Space Administration.

The Pan-STARRS1 Surveys (PS1) and the PS1 public science archive have been
made possible through contributions by the Institute for Astronomy, the
University of Hawaii, the Pan-STARRS Project Office, the Max-Planck Society
and its participating institutes, the Max Planck Institute for Astronomy,
Heidelberg and the Max Planck Institute for Extraterrestrial Physics,
Garching, The Johns Hopkins University, Durham University, the University of
Edinburgh, the Queen’s University Belfast, the Harvard-Smithsonian Center for
Astrophysics, the Las Cumbres Observatory Global Telescope Network
Incorporated, the National Central University of Taiwan, the Space Telescope
Science Institute, the National Aeronautics and Space Administration under
Grant No. NNX08AR22G issued through the Planetary Science Division of the NASA
Science Mission Directorate, the National Science Foundation Grant No.
AST-1238877, the University of Maryland, Eotvos Lorand University (ELTE), the
Los Alamos National Laboratory, and the Gordon and Betty Moore Foundation.

##  Appendix A NIR Line Fluxes

In this section, we list fluxes of the NIR emission lines detected at the
3$\sigma$ level or greater for each target. Note that fluxes are omitted if
the emission has insufficient signal-to-noise, fall in heavy telluric
absorption, or are outside the wavelength coverage. All fluxes are in units of
10-17 erg s-1.

Table A1: NIR Line Fluxes Line | J0122ne | J0122se | J0122w | J0333 | J0750 | J0851 | J0852 | J0929
---|---|---|---|---|---|---|---|---
$\rm{H}\beta$ 4862 Å | 273 $\pm$6 | 3268 $\pm$421 | 7886 $\pm$689 | 306 $\pm$105 | 307 $\pm$162 | 144 $\pm$37 | 93 $\pm$4 | 1027 $\pm$101
Outflow Comp. | — | — | — | — | — | — | 41 $\pm$2 | 328 $\pm$35
$[\rm{O\;III}]$ 5007 Å | 581 $\pm$7 | 2848 $\pm$336 | 5771 $\pm$475 | 138 $\pm$50 | 142 $\pm$72 | 155 $\pm$39 | 338 $\pm$7 | 10320 $\pm$909
Outflow Comp. | — | — | — | — | — | — | 149 $\pm$7 | 3342 $\pm$335
$\rm{H}\alpha$ 6565 Å | 567 $\pm$9 | 10129 $\pm$ 935 | 24429 $\pm$1611 | 951 $\pm$210 | 951 $\pm$346 | 367 $\pm$77 | 278 $\pm$6 | 3181 $\pm$219
Outflow Comp. | — | — | — | — | — | — | 149 $\pm$6 | 1009 $\pm$82
$[\rm{N\;II}]$ 6585 Å | 185 $\pm$3 | 3109 $\pm$273 | 7587 $\pm$456 | 426 $\pm$97 | 334 $\pm$124 | 204 $\pm$44 | 183 $\pm$4 | 716 $\pm$52
Outflow Comp. | — | — | — | — | — | — | 98 $\pm$2 | 228 $\pm$18
$[\rm{S\;II}]$ 6718 Å | 167 $\pm$4 | 1357 $\pm$125 | 3573 $\pm$219 | 160 $\pm$39 | 184 $\pm$70 | 93 $\pm$21 | 66 $\pm$4 | 521 $\pm$39
Outflow Comp. | — | — | — | — | — | — | 36 $\pm$2 | 167 $\pm$14
$[\rm{S\;II}]$ 6732 Å | 123 $\pm$3 | 1047 $\pm$96 | 2878 $\pm$181 | 127 $\pm$32 | 136 $\pm$53 | 70 $\pm$19 | 60 $\pm$3 | 387 $\pm$30
Outflow Comp. | — | — | — | — | — | — | 33 $\pm$2 | 124 $\pm$12
$[\rm{O\;II}]$ 7320 Å | 11 $\pm$2 | 70 $\pm$12 | 172 $\pm$19 | — | — | — | — | 48 $\pm$15
$[\rm{O\;II}]$ 7330 Å | 5 $\pm$1 | 59 $\pm$10 | 153 $\pm$18 | — | — | — | — | 54 $\pm$21
$[\rm{S\;III}]$ 0.9069 $\mu$m | 36 $\pm$4 | 119 $\pm$10 | 171 $\pm$11 | — | — | 33 $\pm$16 | 149 $\pm$35 | 152 $\pm$30
$[\rm{S\;III}]$ 0.9531 $\mu$m | 74 $\pm$8 | 361 $\pm$18 | 577 $\pm$19 | — | — | 57 $\pm$18 | 387 $\pm$23 | 550 $\pm$40
$\rm{Pa}\epsilon$ 0.9549 $\mu$m | — | 27 $\pm$3 | 51 $\pm$3 | — | — | — | — | —
$\rm{Pa}\delta$ 1.0052 $\mu$m | 9 $\pm$1 | 34 $\pm$4 | 58 $\pm$3 | — | — | — | — | —
$\rm{He\;I}$ 1.0830 $\mu$m | — | — | — | — | — | — | 135 $\pm$20 | 237 $\pm$42
$\rm{Pa}\gamma$ 1.0941 $\mu$m | — | — | — | — | — | — | 20 $\pm$2 | 62 $\pm$4
$[\rm{P\;II}]$ 1.1880 $\mu$m | — | — | 12 $\pm$2 | — | — | — | 36 $\pm$7 | —
$[\rm{Fe\;II}]$ 1.2567 $\mu$m | 12 $\pm$0.7 | 33 $\pm$2 | 58 $\pm$3 | — | — | — | 184 $\pm$12 | —
$\rm{Pa}\beta$ 1.2822 $\mu$m | — | — | — | — | — | — | — | 43 $\pm$3
$[\rm{Fe\;II}]$ 1.6435 $\mu$m | 7 $\pm$0.9 | 28 $\pm$2 | 38 $\pm$2 | — | — | — | 57 $\pm$4 | —
$\rm{Pa}\alpha$ 1.8756 $\mu$m | 89 $\pm$4 | 288 $\pm$9 | 514 $\pm$17 | 41 $\pm$3 | 69 $\pm$11 | 168 $\pm$18aaIncludes both broad and narrow component fluxes. | 87 $\pm$3 | 427 $\pm$44
$\rm{Br}\delta$ 1.9451 $\mu$m | 4 $\pm$1 | 18 $\pm$1 | 27 $\pm$2 | — | — | — | — | —
$\rm{H_{2}}$ 1.9576 $\mu$m | 3 $\pm$1 | 7 $\pm$1 | 15 $\pm$2 | — | — | — | 5 $\pm$2 | 17 $\pm$4
$[\rm{Si\;VI}]$ 1.9630 $\mu$m | — | — | — | — | — | — | 69 $\pm$9 aaIncludes both broad and narrow component fluxes. | 392 $\pm$102
$\rm{H_{2}}$ 2.0338 $\mu$m | 2 $\pm$0.5 | 4 $\pm$1 | 7 $\pm$2 | — | — | — | — | —
$\rm{He\;I}$ 2.0587 $\mu$m | 4 $\pm$1 | 18 $\pm$2 | 21 $\pm$4 | — | — | — | — | —
$\rm{H_{2}}$ 2.1218 $\mu$m | 4 $\pm$1 | 9 $\pm$1 | 17 $\pm$1 | — | — | — | 11 $\pm$2 | —
$\rm{Br}\gamma$ 2.1661 $\mu$m | 8 $\pm$1 | 31 $\pm$1 | 38 $\pm$1 | — | — | — | — | 13 $\pm$3
$\rm{H_{2}}$ 2.2235 $\mu$m | — | 3 $\pm$0.5 | 5 $\pm$1 | — | — | — | — | —
$W1$ 3.4 $\mu$m | — | 21 $\pm$0.5 | — | 2.5 $\pm$0.1 | 2 $\pm$0.1 | 3 $\pm$0.1 | 3 $\pm$0.1 | 8 $\pm$0.2
$W2$ 4.6 $\mu$m | — | 66 $\pm$1 | — | 4 $\pm$0.1 | 4$\pm$0.1 | 5 $\pm$0.2 | 5 $\pm$0.2 | 13 $\pm$0.3
$W3$ 12.0 $\mu$m | — | 1028 $\pm$14 | — | 57 $\pm$3 | 55 $\pm$3 | 44 $\pm$3 | 61 $\pm$4 | 113 $\pm$4

Table A1: continued

Line | J1032 | J1036 | J1228 | J1233 (central) | J1326 | J1333 | J1554
---|---|---|---|---|---|---|---
$\rm{H}\beta$ 4862 Å | 184 $\pm$55 | 4307 $\pm$693 | 97 $\pm$93 | 223 $\pm$78 | 90 $\pm$82 | 43 $\pm$13 | 131 $\pm$71
Outflow Comp. | — | — | — | 25 $\pm$14 | — | 5 $\pm$2 | —
$[\rm{O\;III}]$ 5007 Å | 197 $\pm$53 | 3597 $\pm$539 | 928 $\pm$831 | 405 $\pm$132 | 119 $\pm$105 | 202 $\pm$69 | 155 $\pm$79
Outflow Comp. | — | — | — | 40 $\pm$22 | — | 23 $\pm$ 10 | —
$\rm{H}\alpha$ 6565 Å | 570 $\pm$115 | 13354 $\pm$1426 | 302 $\pm$248 | 692 $\pm$163 | 277 $\pm$206 | 141 $\pm$39 | 407 $\pm$150
Outflow Comp. | — | — | — | 86 $\pm$41 | — | 21 $\pm$8 | —
$[\rm{N\;II}]$ 6585 Å | 228 $\pm$48 | 7517 $\pm$789 | 174 $\pm$145 | 419 $\pm$108 | 275 $\pm$204 | 109 $\pm$30 | 307 $\pm$113
Outflow Comp. | — | — | — | 46 $\pm$23 | — | 16 $\pm$6 | —
$[\rm{S\;II}]$ 6718 Å | 94 $\pm$25 | 2764 $\pm$311 | 88 $\pm$75 | 177 $\pm$46 | 103 $\pm$82 | 25 $\pm$8 | 89 $\pm$39
Outflow Comp. | — | — | — | 20 $\pm$9 | — | 4 $\pm$1 | —
$[\rm{S\;II}]$ 6732 Å | 68 $\pm$17 | 2160 $\pm$250 | 25 $\pm$23 | 131 $\pm$35 | 45 $\pm$39 | 25 $\pm$9 | 64 $\pm$30
Outflow Comp. | — | — | — | 15 $\pm$7 | — | 4 $\pm$1 | —
$[\rm{O\;II}]$ 7320 Å | — | 240 $\pm$68 | — | — | — | — | —
$[\rm{O\;II}]$ 7330 Å | — | 144 $\pm$69 | — | — | — | — | —
$[\rm{S\;III}]$ 0.9069 $\mu$m | 14 $\pm$6 | — | 37 $\pm$28 | 16 $\pm$5 | — | 32 $\pm$7 | 6 $\pm$2
$[\rm{S\;III}]$ 0.9531 $\mu$m | 34 $\pm$6 | — | 58 $\pm$39 | 39 $\pm$6 | — | 65 $\pm$12 | 26 $\pm$8
$\rm{Pa}\epsilon$ 0.9549 $\mu$m | — | — | — | — | — | — | —
$\rm{He\;I}$ 1.0830 $\mu$m | 32 $\pm$7 | — | 78 $\pm$40 | 12 $\pm$2 | — | 46 $\pm$6 | 22 $\pm$7
$\rm{Pa}\gamma$ 1.0941 $\mu$m | 6 $\pm$1 | — | 15 $\pm$9 | 3 $\pm$1 | — | — | —
$[\rm{P\;II}]$ 1.1880 $\mu$m | — | — | — | — | — | — | —
$[\rm{Fe\;II}]$ 1.2567 $\mu$m | — | — | — | 4 $\pm$1 | — | — | —
$\rm{Pa}\beta$ 1.2822 $\mu$m | — | — | 89 $\pm$50 | — | — | 8 $\pm$3 | 8 $\pm$3
$[\rm{Fe\;II}]$ 1.6435 $\mu$m | — | — | — | 3 $\pm$1 (2 $\pm$0.6) | — | — | —
$\rm{Pa}\alpha$ 1.8756 $\mu$m | 33 $\pm$3 | — | 125 $\pm$42aaIncludes both broad and narrow component fluxes. | 19 $\pm$2 | 72 $\pm$20 | 46 $\pm$3 | 43 $\pm$5
$\rm{Br}\delta$ 1.9451 $\mu$m | — | 345 $\pm$19 | — | — | — | — | —
$\rm{H_{2}}$ 1.9576 $\mu$m | — | 987 $\pm$56 | — | 3 $\pm$1 | 39 $\pm$14 | 7 $\pm$1 | 7 $\pm$2
$[\rm{Si\;VI}]$ 1.9630 $\mu$m | — | — | — | (2 $\pm$0.3) | — | 18 $\pm$2 | 24 $\pm$6
$\rm{H_{2}}$ 2.0338 $\mu$m | — | 398 $\pm$19 | — | — | — | — | —
$\rm{He\;I}$ 2.0587 $\mu$m | — | 393 $\pm$19 | — | — | — | — | —
$\rm{H_{2}}$ 2.1218 $\mu$m | — | 1049 $\pm$29 | — | 3 $\pm$0.6 (1 $\pm$0.3) | — | — | 4 $\pm$1
$\rm{Br}\gamma$ 2.1661 $\mu$m | — | 714 $\pm$25 | — | 2 $\pm$0.8 (2 $\pm$0.6) | — | — | —
$\rm{H_{2}}$ 2.2235 $\mu$m | — | 310 $\pm$16 | — | — | — | — | —
$W1$ 3.4 $\mu$m | 2 $\pm$0.1 | 32 $\pm$1 | 5 $\pm$0.1 | 3 $\pm$0.1 | 4 $\pm$0.1 | 5 $\pm$0.1 |
$W2$ 4.6 $\mu$m | 3 $\pm$0.1 | 80 $\pm$2 | 7 $\pm$0.2 | 5 $\pm$0.2 | 6 $\pm$0.2 | 10 $\pm$0.2 |
$W3$ 12.0 $\mu$m | 43 $\pm$3 | 1503 $\pm$31 | 28 $\pm$2 | 73 $\pm$3 | 64 $\pm$2 | 125 $\pm$4 |

Note. — All optical and NIR fluxes are in units of 10-17 erg s-1. WISE fluxes
are in units of 10-13 erg s-1. J1036 also has emission lines with the
following fluxes: $\rm{H_{2}}$ 2.0735 $\mu$m (106 $\pm$14) and $\rm{H_{2}}$
2.2477 $\mu$m (182 $\pm$15).

##  Appendix B Additional Details on Individual Objects

###  B.1 J012218.11+010025.76

J0122+0100 is a dual system that is likely undergoing a merger event. Optical
and NIR spectroscopy identify three sources, two in the east component (NE and
SE) and one in the west. The two east sources are separated about 1.9” (2.1
kpc). Optical line ratios place all three sources in the star-forming region
of the BPT diagram. NIR line ratios of the southeast and west sources, likely
the nuclei of the two galaxies, also lie within the scatter of star-forming
galaxies in the NIR diagnostic diagrams of Osterbrock et al. (1992). Indeed,
these sources show prominent H I recombination, He I, and H2 emission lines.
In Pa$\alpha$, spatially extended gas emission is seen in the East component.
It extends northwards by about 3.65” (3.9 kpc) and has receding velocities.
Due to the asymmetry of the emission, it is likely a result of the interaction
between the two galaxies.

While we do not detect any CLs in any of the three sources in our
observations, Satyapal et al. (2017) report a 4$\sigma$ detection of [Si VI]
in the southeast source based on LBT LUCI-1 spectroscopy. Close inspection of
the acquisition image reveals three sub-components in the eastern target. Due
to the smaller width of the NIRES slit (0.55”, compared to 1.0” of LUCI), we
could have missed this third component since it is not aligned with the other
two ($\sim$0.4” offset).

Chandra and XMM-Newton X-ray observations are also reported for both the east
and west sources (Satyapal et al., 2017; Pfeifle et al., 2019). The observed
X-ray luminosities are above those expected by stellar processes, such as
XRBs. Coupled with the high extinction found in these targets, these results
point to an optically obscured dual AGN system.

###  B.2 J033331.86+010716.92

J0333+0107 was observed under heavy cloud cover and only $K$-band data have
sufficient S/N for proper analysis. As such, this could severely effect the
detections of any weak CLs. The high extinction, E(B-V) = 1.38, could also
play a role in the lack of CL detections. Our slit position for this target is
misaligned $\sim$15∘ from the semi-major axis. As such, the rotational
velocities in Figure 6 could be underestimated.

###  B.3 J085153.64+392611.76

J0851+3926 is one of two galaxies for which we report a BH mass through virial
mass estimators using broad Pa$\alpha$ (see Section 4.2 and 6). Here, the
broad Pa$\alpha$ is detected while no clear indication of optical broad lines
are seen in the SDSS spectra. We can use this broad emission (or lack thereof)
to calculate estimates to extinction in the central regions. To do this, we
fit the SDSS spectrum incorporating a broad component to H$\alpha$. A check of
the F-test (F = $(\sigma_{single})^{2}/(\sigma_{double})^{2}$) results in F =
1.41, too low to justify adding the component. As such, we will consider these
measurements as upper limits. Fits to the spectra give a line ratio of
Pa$\alpha$/H$\alpha$ $\geq$ 1.44. Assuming an electron density of $n_{e}$ =
108 cm-3 and temperature $T_{e}$ = 15,000 K, we use the intrinsic line ratio
Pa$\alpha$/H$\alpha$ = 0.10 as derived in Dopita & Sutherland (2003). This
results in an E(B-V) $\geq$ 1.40, higher than the extinction measured using
the H$\alpha$/H$\beta$ Balmer decrement. This extinction is comparable to that
of other targets that do not show any CLs, suggesting that obscuration could
be inhibiting CL detection in this target.

As discussed in Section 7, inspection of gas emission in J0851+3926 shows
counter-rotation within the central kpc. This asymmetry is not seen in the
slit perpendicular to this, which could indicate the presence of a bar along
the semi-major axis (Bohn et al., 2020). Analysis of SDSS imaging seems to
confirm this, but higher resolution imaging is required. Another scenario to
create the observed counter-rotation is through tidal disruptions induced by a
flyby of a companion galaxy (see SDSS postage stamp in Figure 6). However, the
spectroscopic redshift of this companion could not be obtained and its
photometric redshift does not match with J0851+3926. If the photometric
redshifts are accurate, this would indicate the companion is a background
galaxy. Surface brightness decompositions of J0851+3926 seems to confirm this,
since no significant asymmetries in the disk appear and thus it is largely
intact. Regardless of the scenario, it is likely through these processes that
gas can be funneled to the central regions to allow BH growth without the need
of major mergers or the build-up of the central bulge.

###  B.4 J092907.78+002637.29

The velocity profile of the gas in J092907.78+002637.29 is quite unique since
it is significantly asymmetric. We see receding gas that roughly matches the
NFW curve, though it is somewhat ‘core-like’. We see zero net velocity in the
gas emission on the approaching side. A number of factors could be the cause
of this, but due to the low resolution of available imaging, we can only
provide speculative scenarios. The simplest reasoning is that the rotating gas
did not fall within the slit, however this is unlikely since the slit covers
most of the semi-major axis. A more plausible scenario is that a dust plane is
obscuring the rotating gas and that we are only observing gas moving
perpendicular to us. This is consistent with the extinction seen in this
target, E(B-V) = 1.28, one of the highest of targets with rotation curves.

Considering the asymmetry in the profile, the possibility of the outflow or a
merger event altering the gas rotation cannot be dismissed. While we detect a
fast outflow in J0929+0026, the associated gas emission is blueshifted and is
inconsistent with the rotation curve. If we assume a bi-conical model (Bae &
Woo, 2016), we would also expect the receding gas to be more heavily obscured
by the galactic disk. Lastly, while surface brightness decompositions do not
show a significant merger event occurring, higher resolution imaging will be
needed to confirm if a minor merger is occurring.

###  B.5 J103631.88+022144.10

HST imaging reveals J1036+0221 is likely a merger system. Our NIR data show
rotational H2 (2.0338, 2.1218 $\mu$m), He I 2.0587 $\mu$m, and Br$\gamma$ gas
emission within the central $\sim$2 kpc that peaks $\sim$ 200 km s-1. We
suspect that this rotation is due largely to tidal disruptions of the merger.

Our NIRSPEC spectra, in which only $K$-band is observed, do not show any CLs.
However, Satyapal et al. (2017) obtained LBT LUCI-1 spectra, through which the
coverage is extended to $H$-band. They detect [Si X] 1.4305 $\mu$m at the
4$\sigma$ level. NIR line ratio diagnostics (see Section 4.3) places this
galaxy within the scatter of other AGN, further suggesting the presence of an
AGN in the nucleus. They also detect a strong X-ray source, which further
indicates AGN activity in this merger.

###  B.6 J122809.19+581431.40

SDSS imaging shows evidence of two central sources in J1228+5814. This is
confirmed with GALFIT where two exponential disks best fit the surface
brightness profile. Indeed, two sources are also seen in the 2D spectrum.
However, we only detect hidden broad Pa$\alpha$ emission in the south source
(see Section 4.2). Inspection of the north source reveals a featureless
spectrum, except for a few stellar absorption features in $H$-band. This is,
however, enough to confirm that there is no significant velocity offset
between the two sources.

It is interesting to note that we may be observing an off-nuclear BH in J1228.
The southern source is about 1.7 kpc offset from the photometric center.
Simulations have shown that off-center or “wandering” BHs can be found a few
kpc away from the center in dwarf galaxies (Bellovary et al., 2019). These
wandering BHs have also been found in observations of dwarf galaxies (Reines
et al., 2020) but are not as common in more massive galaxies, such as J1228
(log(M⋆) = 10.67). As such, J1228 could lead to an interesting study of off-
center AGN in more massive galaxies.

Along with J1326+1014, this target also has one of the highest extinction
levels in this sample, E(B-V) = 2.50. This is largely due to the weak H$\beta$
emission that indicates significant obscuration. For J1228+5814, this is
consistent with the fact that no broad H$\alpha$ emission is detected in the
SDSS spectra. This high level of obscuration is likely inhibiting CL
detection.

##  Appendix C Rotation Curves Extraction

We obtained velocities at various radii by first fitting a Gaussian along the
spatial axis of the rectified 2D spectrum to locate the center of the galaxy.
The row with the highest pixel value was taken as the center and used as the
zero-point from which we constructed velocity curves. If multiple rows in the
central region had comparable pixel values, we took the pixel pair with the
highest values as the center. Note that this method selects the photometric
peak and not necessarily the kinematic center of the galaxy.

Spectra were extracted at 0.3” intervals (based on the telescope resolution)
but since the typical seeing was worse than this, the effective extraction
intervals are closer to 0.5”. These intervals were increased if the S/N was
sufficiently low (S/N $<$ 10). Each subsequent extraction sampled a new set of
pixels out to the edge where a proper S/N of the emission line was no longer
achievable. Each extraction was fit with emcee in a similar manner as
described in Section 3.1.1. The peaks of each emission profile was compared to
the zero-point to obtain line of sight velocities. We convert these velocities
to rotational velocities using

$v_{\rm{rot}}=\frac{v_{\rm{LoS}}}{\rm{sin}^{-1}(\theta_{\rm{inc}})}$ (C1)

where $\theta_{\rm{inc}}$ is the inclination angle of the disk to the line of
sight. For an infinitely thin disk, $\theta_{\rm{inc}}$ can be calculated
using the ratio of the semi-minor axis b and semi-major axis a through the
equation $\theta_{\rm{inc}}$ = cos-1(b/a). To more accurately estimate the
inclination angle, a thickness parameter q = c/a can be introduced, where a is
the radius of a circular disc and c is its thickness. When projected on a
plane, the resulting shape is elliptical and $\theta_{\rm{inc}}$ can be
described as

$\theta_{\rm{inc}}=\sqrt{{\rm{cos}}^{-1}\bigg{(}\frac{(b/a)^{2}-q^{2}}{1-q^{2}}\bigg{)}}$
(C2)

We assume a value of q = 0.1 (Giovanelli et al., 1994) for all of our targets.
To calculate the ellipticity $\epsilon$ = (1 - (b/a)), we use the isophote
routine of the photutils package (Bradley et al., 2020).

Seven galaxies show spatially extended emission for which we could measure the
rotation curves as shown in Figure 6. We also do see some extended gas
emission in J1036+0221 and J0122+0100(w), but do not include them in this
analysis since they are likely involved in a merger event. The remaining four
targets do not show spatially extended emission lines, most likely due to the
high levels of extinction that they show.

##  Appendix D J120443.76+050543.87

We include J1204+0505 here because it was observed in a parallel campaign and
shares many similar characteristic with the bulgeless sample presented here.
It is located at a redshift of 0.1097 and has a stellar mass of 10.1 M⊙ (Chang
et al., 2015). Surface brightness decompositions from Simard et al. (2011)
show a B/T = 0.01, and supplementary fits only using an exponential disk
result in a Sérsic index of 0.71. As such, it is unlikely that there is a
significant bulge component. Although the BPT optical line ratios are not
suggestive of AGN activity, J1204+0505 does fall within the scatter of our
sample in the [S III]/H$\alpha$ vs. [S II]/H$\alpha$ diagram. It also meets
the MIR color cut of S14 ($W1$ – $W2$ = 0.84).

J1204+0505 is a unique case since it is the only galaxy where we detect [Al
IX] 2.044 $\mu$m emission and no other CL. Fitting the line with a single
Gaussian, we detect it at a 3$\sigma$ level (see Figure 8). To determine
whether noise could have recreated this line profile, we use the F-test in a
regression analysis model. Put simply, we sample a small region around the
emission line and compare the residuals of when the line is fit and when it is
not. We will call this value $F_{statistic}$ (or $F_{stat}$). Since this value
is based on residual error, we need to treat it as a random variable with some
probability. As such, we can use this to construct a probability density
function (PDF), from which we can obtain a confidence level that the emission
line is real, and not from random noise.

Figure 8: Zoom-in plot of [Al IX] 2.044 $\mu$m emission in J1204. The best-fit
line from EMCEE is plotted in red. The fit to H2 2.004 $\mu$m is also shown.
The bottom panel shows the residuals of the fit with the 1$\sigma$ error level
shown as horizontal dotted lines.

We begin by using the following equation to calculate $F_{stat}$:

$\textit{F${}_{stat}$}=\bigg{(}\frac{\frac{RSS_{1}-RSS_{2}}{k_{2}-k_{1}}}{\frac{RSS_{2}}{n-k_{2}}}\bigg{)}$
(D1)

where $RSS_{1}$ is the residual sum of squares of just a continuum fit (one
degree of freedom), $RSS_{2}$ is the residual sum of squares of a continuum
plus Gaussian fit (four degrees of freedom), and $k$ is the degrees of freedom
for each fit. Here, $n$ is the sampling size, which in this case, is the
number of wavelength channels in the selected region. From here,
($k_{2}-k_{1}$) and ($n-k_{2}$) can be used to calculate the PDF for
$F_{stat}$. We obtain a probability value of 0.97, that is, we detect the line
at a 97$\%$ confidence. While this result is suggestive that the emission line
is real, deeper follow-up observations will be needed to confirm this.

## References

  * Antonucci & Miller (1985) Antonucci, R. R. J., & Miller, J. S. 1985, ApJ, 297, 621, doi: 10.1086/163559
  * Avery et al. (2021) Avery, C. R., Wuyts, S., Förster Schreiber, N. M., et al. 2021, MNRAS, 503, 5134, doi: 10.1093/mnras/stab780
  * Bae & Woo (2016) Bae, H.-J., & Woo, J.-H. 2016, ApJ, 828, 97, doi: 10.3847/0004-637X/828/2/97
  * Baldassare et al. (2016) Baldassare, V. F., Reines, A. E., Gallo, E., et al. 2016, ApJ, 829, 57, doi: 10.3847/0004-637X/829/1/57
  * Baldwin et al. (1981) Baldwin, J. A., Phillips, M. M., & Terlevich, R. 1981, PASP, 93, 5, doi: 10.1086/130766
  * Becker et al. (2009) Becker, G. D., Rauch, M., & Sargent, W. L. W. 2009, ApJ, 698, 1010, doi: 10.1088/0004-637X/698/2/1010
  * Bellovary et al. (2019) Bellovary, J. M., Cleary, C. E., Munshi, F., et al. 2019, MNRAS, 482, 2913, doi: 10.1093/mnras/sty2842
  * Bentz et al. (2013) Bentz, M. C., Denney, K. D., Grier, C. J., et al. 2013, ApJ, 767, 149, doi: 10.1088/0004-637X/767/2/149
  * Bohn et al. (2020) Bohn, T., Canalizo, G., Satyapal, S., & Pfeifle, R. W. 2020, ApJ, 899, 82, doi: 10.3847/1538-4357/aba52c
  * Bohn et al. (2021) Bohn, T., Canalizo, G., Veilleux, S., & Liu, W. 2021, ApJ, 911, 70, doi: 10.3847/1538-4357/abe70c
  * Bradley et al. (2020) Bradley, L., Sipőcz, B., Robitaille, T., et al. 2020, astropy/photutils: 1.0.0, 1.0.0, Zenodo, doi: 10.5281/zenodo.4044744
  * Cann et al. (2020) Cann, J. M., Satyapal, S., Bohn, T., et al. 2020, ApJ, 895, 147, doi: 10.3847/1538-4357/ab8b64
  * Cann et al. (2021) Cann, J. M., Satyapal, S., Rothberg, B., et al. 2021, ApJ, 912, L2, doi: 10.3847/2041-8213/abf56d
  * Cappellari (2017) Cappellari, M. 2017, MNRAS, 466, 798, doi: 10.1093/mnras/stw3020
  * Cappellari & Emsellem (2004) Cappellari, M., & Emsellem, E. 2004, PASP, 116, 138, doi: 10.1086/381875
  * Cardelli et al. (1989) Cardelli, J. A., Clayton, G. C., & Mathis, J. S. 1989, ApJ, 345, 245, doi: 10.1086/167900
  * Chambers et al. (2016) Chambers, K. C., Magnier, E. A., Metcalfe, N., et al. 2016, arXiv e-prints, arXiv:1612.05560.  https://arxiv.org/abs/1612.05560
  * Chang et al. (2015) Chang, Y.-Y., van der Wel, A., da Cunha, E., & Rix, H.-W. 2015, ApJS, 219, 8, doi: 10.1088/0067-0049/219/1/8
  * Cicone et al. (2014) Cicone, C., Maiolino, R., Sturm, E., et al. 2014, A&A, 562, A21, doi: 10.1051/0004-6361/201322464
  * Concas et al. (2017) Concas, A., Popesso, P., Brusa, M., et al. 2017, A&A, 606, A36, doi: 10.1051/0004-6361/201629519
  * Costa et al. (2020) Costa, T., Pakmor, R., & Springel, V. 2020, MNRAS, 497, 5229, doi: 10.1093/mnras/staa2321
  * Cresci et al. (2015) Cresci, G., Mainieri, V., Brusa, M., et al. 2015, ApJ, 799, 82, doi: 10.1088/0004-637X/799/1/82
  * Dopita & Sutherland (2003) Dopita, M. A., & Sutherland, R. S. 2003, Astrophysics of the diffuse universe
  * Fabian (2012) Fabian, A. C. 2012, ARA&A, 50, 455, doi: 10.1146/annurev-astro-081811-125521
  * Ferrarese & Merritt (2000) Ferrarese, L., & Merritt, D. 2000, ApJ, 539, L9, doi: 10.1086/312838
  * Foreman-Mackey et al. (2013) Foreman-Mackey, D., Hogg, D. W., Lang, D., & Goodman, J. 2013, PASP, 125, 306, doi: 10.1086/670067
  * Gebhardt et al. (2000) Gebhardt, K., Bender, R., Bower, G., et al. 2000, ApJ, 539, L13, doi: 10.1086/312840
  * Gelbord et al. (2009) Gelbord, J. M., Mullaney, J. R., & Ward, M. J. 2009, MNRAS, 397, 172, doi: 10.1111/j.1365-2966.2009.14961.x
  * Giovanelli et al. (1994) Giovanelli, R., Haynes, M. P., Salzer, J. J., et al. 1994, AJ, 107, 2036, doi: 10.1086/117014
  * Häring & Rix (2004) Häring, N., & Rix, H.-W. 2004, ApJ, 604, L89, doi: 10.1086/383567
  * Harrison et al. (2014) Harrison, C. M., Alexander, D. M., Mullaney, J. R., & Swinbank, A. M. 2014, MNRAS, 441, 3306, doi: 10.1093/mnras/stu515
  * Harrison et al. (2018) Harrison, C. M., Costa, T., Tadhunter, C. N., et al. 2018, Nature Astronomy, 2, 198, doi: 10.1038/s41550-018-0403-6
  * Harrison et al. (2016) Harrison, C. M., Alexander, D. M., Mullaney, J. R., et al. 2016, MNRAS, 456, 1195, doi: 10.1093/mnras/stv2727
  * Hopkins et al. (2009) Hopkins, P. F., Cox, T. J., Younger, J. D., & Hernquist, L. 2009, ApJ, 691, 1168, doi: 10.1088/0004-637X/691/2/1168
  * Jarrett et al. (2011) Jarrett, T. H., Cohen, M., Masci, F., et al. 2011, ApJ, 735, 112, doi: 10.1088/0004-637X/735/2/112
  * Kang & Woo (2018) Kang, D., & Woo, J.-H. 2018, ApJ, 864, 124, doi: 10.3847/1538-4357/aad561
  * Kaspi et al. (2005) Kaspi, S., Maoz, D., Netzer, H., et al. 2005, ApJ, 629, 61, doi: 10.1086/431275
  * Kauffmann et al. (2003) Kauffmann, G., Heckman, T. M., Tremonti, C., et al. 2003, MNRAS, 346, 1055, doi: 10.1111/j.1365-2966.2003.07154.x
  * Kelson (2003) Kelson, D. D. 2003, PASP, 115, 688, doi: 10.1086/375502
  * Kewley et al. (2004) Kewley, L. J., Geller, M. J., & Jansen, R. A. 2004, AJ, 127, 2002, doi: 10.1086/382723
  * Kewley et al. (2001) Kewley, L. J., Heisler, C. A., Dopita, M. A., & Lumsden, S. 2001, ApJS, 132, 37, doi: 10.1086/318944
  * Kim et al. (2018) Kim, D., Im, M., Canalizo, G., et al. 2018, ApJS, 238, 37, doi: 10.3847/1538-4365/aadfd5
  * King & Pounds (2015) King, A., & Pounds, K. 2015, ARA&A, 53, 115, doi: 10.1146/annurev-astro-082214-122316
  * Lamastra et al. (2009) Lamastra, A., Bianchi, S., Matt, G., et al. 2009, A&A, 504, 73, doi: 10.1051/0004-6361/200912023
  * Lamperti et al. (2017) Lamperti, I., Koss, M., Trakhtenbrot, B., et al. 2017, MNRAS, 467, 540, doi: 10.1093/mnras/stx055
  * Leung et al. (2019) Leung, G. C. K., Coil, A. L., Aird, J., et al. 2019, ApJ, 886, 11, doi: 10.3847/1538-4357/ab4a7c
  * Liu et al. (2020) Liu, W., Veilleux, S., Canalizo, G., et al. 2020, arXiv e-prints, arXiv:2010.09008.  https://arxiv.org/abs/2010.09008
  * Lutz et al. (2020) Lutz, D., Sturm, E., Janssen, A., et al. 2020, A&A, 633, A134, doi: 10.1051/0004-6361/201936803
  * Maddox (2018) Maddox, N. 2018, MNRAS, 480, 5203, doi: 10.1093/mnras/sty2201
  * Manzano-King et al. (2019) Manzano-King, C. M., Canalizo, G., & Sales, L. V. 2019, ApJ, 884, 54, doi: 10.3847/1538-4357/ab4197
  * Marconi & Hunt (2003) Marconi, A., & Hunt, L. K. 2003, ApJ, 589, L21, doi: 10.1086/375804
  * Martin (1998) Martin, C. L. 1998, ApJ, 506, 222, doi: 10.1086/306219
  * Martin et al. (2018) Martin, G., Kaviraj, S., Volonteri, M., et al. 2018, MNRAS, 476, 2801, doi: 10.1093/mnras/sty324
  * McAlpine et al. (2020) McAlpine, S., Harrison, C. M., Rosario, D. J., et al. 2020, MNRAS, 494, 5713, doi: 10.1093/mnras/staa1123
  * McConnell & Ma (2013) McConnell, N. J., & Ma, C.-P. 2013, ApJ, 764, 184, doi: 10.1088/0004-637X/764/2/184
  * McElroy et al. (2015) McElroy, R., Croom, S. M., Pracy, M., et al. 2015, MNRAS, 446, 2186, doi: 10.1093/mnras/stu2224
  * McLean et al. (1998) McLean, I. S., Becklin, E. E., Bendiksen, O., et al. 1998, in Proc. SPIE, Vol. 3354, Infrared Astronomical Instrumentation, ed. A. M. Fowler, 566–578, doi: 10.1117/12.317283
  * Moster et al. (2013) Moster, B. P., Naab, T., & White, S. D. M. 2013, MNRAS, 428, 3121, doi: 10.1093/mnras/sts261
  * Müller-Sánchez et al. (2018a) Müller-Sánchez, F., Hicks, E. K. S., Malkan, M., et al. 2018a, ApJ, 858, 48, doi: 10.3847/1538-4357/aab9ad
  * Müller-Sánchez et al. (2018b) Müller-Sánchez, F., Nevin, R., Comerford, J. M., et al. 2018b, Nature, 556, 345, doi: 10.1038/s41586-018-0033-2
  * Müller-Sánchez et al. (2011) Müller-Sánchez, F., Prieto, M. A., Hicks, E. K. S., et al. 2011, ApJ, 739, 69, doi: 10.1088/0004-637X/739/2/69
  * Nagao et al. (2000) Nagao, T., Taniguchi, Y., & Murayama, T. 2000, AJ, 119, 2605, doi: 10.1086/301411
  * Navarro et al. (1996) Navarro, J. F., Frenk, C. S., & White, S. D. M. 1996, ApJ, 462, 563, doi: 10.1086/177173
  * Osterbrock & Ferland (2006) Osterbrock, D. E., & Ferland, G. J. 2006, Astrophysics of gaseous nebulae and active galactic nuclei
  * Osterbrock et al. (1992) Osterbrock, D. E., Tran, H. D., & Veilleux, S. 1992, ApJ, 389, 196, doi: 10.1086/171197
  * Pfeifle et al. (2019) Pfeifle, R. W., Satyapal, S., Secrest, N. J., et al. 2019, ApJ, 875, 117, doi: 10.3847/1538-4357/ab07bc
  * Piner et al. (1995) Piner, B. G., Stone, J. M., & Teuben, P. J. 1995, ApJ, 449, 508, doi: 10.1086/176075
  * Pritchard et al. (2012) Pritchard, T. A., Roming, P. W. A., Brown, P. J., et al. 2012, ApJ, 750, 128, doi: 10.1088/0004-637X/750/2/128
  * Reines et al. (2020) Reines, A. E., Condon, J. J., Darling, J., & Greene, J. E. 2020, ApJ, 888, 36, doi: 10.3847/1538-4357/ab4999
  * Reines & Volonteri (2015) Reines, A. E., & Volonteri, M. 2015, ApJ, 813, 82, doi: 10.1088/0004-637X/813/2/82
  * Rho et al. (2018) Rho, J., Geballe, T. R., Banerjee, D. P. K., et al. 2018, ApJ, 864, L20, doi: 10.3847/2041-8213/aad77f
  * Rodríguez-Ardila et al. (2011) Rodríguez-Ardila, A., Prieto, M. A., Portilla, J. G., & Tejeiro, J. M. 2011, ApJ, 743, 100, doi: 10.1088/0004-637X/743/2/100
  * Rodríguez-Ardila et al. (2006) Rodríguez-Ardila, A., Prieto, M. A., Viegas, S., & Gruenwald, R. 2006, ApJ, 653, 1098, doi: 10.1086/508864
  * Rupke et al. (2005) Rupke, D. S., Veilleux, S., & Sanders, D. B. 2005, ApJS, 160, 115, doi: 10.1086/432889
  * Rupke et al. (2017) Rupke, D. S. N., Gültekin, K., & Veilleux, S. 2017, ApJ, 850, 40, doi: 10.3847/1538-4357/aa94d1
  * Sanders et al. (2016) Sanders, R. L., Shapley, A. E., Kriek, M., et al. 2016, ApJ, 816, 23, doi: 10.3847/0004-637X/816/1/23
  * Satyapal et al. (2014) Satyapal, S., Secrest, N. J., McAlpine, W., et al. 2014, ApJ, 784, 113, doi: 10.1088/0004-637X/784/2/113
  * Satyapal et al. (2008) Satyapal, S., Vega, D., Dudik, R. P., Abel, N. P., & Heckman, T. 2008, ApJ, 677, 926, doi: 10.1086/529014
  * Satyapal et al. (2007) Satyapal, S., Vega, D., Heckman, T., O’Halloran, B., & Dudik, R. 2007, ApJ, 663, L9, doi: 10.1086/519995
  * Satyapal et al. (2017) Satyapal, S., Secrest, N. J., Ricci, C., et al. 2017, ApJ, 848, 126, doi: 10.3847/1538-4357/aa88ca
  * Sexton et al. (2019) Sexton, R. O., Canalizo, G., Hiner, K. D., et al. 2019, ApJ, 878, 101, doi: 10.3847/1538-4357/ab21d5
  * Sexton et al. (2020) Sexton, R. O., Matzko, W., Darden, N., Canalizo, G., & Gorjian, V. 2020, MNRAS, doi: 10.1093/mnras/staa3278
  * Shen (2013) Shen, Y. 2013, Bulletin of the Astronomical Society of India, 41, 61.  https://arxiv.org/abs/1302.2643
  * Sheth et al. (2002) Sheth, K., Vogel, S. N., Regan, M. W., et al. 2002, AJ, 124, 2581, doi: 10.1086/343835
  * Shih & Rupke (2010) Shih, H.-Y., & Rupke, D. S. N. 2010, ApJ, 724, 1430, doi: 10.1088/0004-637X/724/2/1430
  * Simard et al. (2011) Simard, L., Mendel, J. T., Patton, D. R., Ellison, S. L., & McConnachie, A. W. 2011, ApJS, 196, 11, doi: 10.1088/0067-0049/196/1/11
  * Simmons et al. (2017) Simmons, B. D., Smethurst, R. J., & Lintott, C. 2017, MNRAS, 470, 1559, doi: 10.1093/mnras/stx1340
  * Smethurst et al. (2019) Smethurst, R. J., Simmons, B. D., Lintott, C. J., & Shanahan, J. 2019, MNRAS, 489, 4016, doi: 10.1093/mnras/stz2443
  * Smethurst et al. (2021) Smethurst, R. J., Simmons, B. D., Coil, A., et al. 2021, MNRAS, 507, 3985, doi: 10.1093/mnras/stab2340
  * Smith et al. (2011) Smith, N., Li, W., Silverman, J. M., Ganeshalingam, M., & Filippenko, A. V. 2011, MNRAS, 415, 773, doi: 10.1111/j.1365-2966.2011.18763.x
  * Stern et al. (2012) Stern, D., Assef, R. J., Benford, D. J., et al. 2012, ApJ, 753, 30, doi: 10.1088/0004-637X/753/1/30
  * Valdes et al. (2004) Valdes, F., Gupta, R., Rose, J. A., Singh, H. P., & Bell, D. J. 2004, ApJS, 152, 251, doi: 10.1086/386343
  * Veilleux et al. (1997) Veilleux, S., Goodrich, R. W., & Hill, G. J. 1997, ApJ, 477, 631, doi: 10.1086/303735
  * Veilleux & Osterbrock (1987) Veilleux, S., & Osterbrock, D. E. 1987, ApJS, 63, 295, doi: 10.1086/191166
  * Wang et al. (2012) Wang, J., Kauffmann, G., Overzier, R., et al. 2012, MNRAS, 423, 3486, doi: 10.1111/j.1365-2966.2012.21147.x
  * Westmoquette et al. (2008) Westmoquette, M. S., Smith, L. J., & Gallagher, J. S. 2008, MNRAS, 383, 864, doi: 10.1111/j.1365-2966.2007.12628.x
  * Wilson et al. (2004) Wilson, J. C., Henderson, C. P., Herter, T. L., et al. 2004, in Proc. SPIE, Vol. 5492, Ground-based Instrumentation for Astronomy, ed. A. F. M. Moorwood & M. Iye, 1295–1305, doi: 10.1117/12.550925
  * Woo et al. (2016) Woo, J.-H., Bae, H.-J., Son, D., & Karouzos, M. 2016, ApJ, 817, 108, doi: 10.3847/0004-637X/817/2/108
  * Woo et al. (2015) Woo, J.-H., Yoon, Y., Park, S., Park, D., & Kim, S. C. 2015, ApJ, 801, 38, doi: 10.1088/0004-637X/801/1/38
  * Wright et al. (2010) Wright, E. L., Eisenhardt, P. R. M., Mainzer, A. K., et al. 2010, AJ, 140, 1868, doi: 10.1088/0004-6256/140/6/1868
  * Zakamska et al. (2005) Zakamska, N. L., Schmidt, G. D., Smith, P. S., et al. 2005, AJ, 129, 1212, doi: 10.1086/427543