# A Multiwavelength Study of Active Galactic Nuclei in Post-Merger Remnants

Wenhao Li  Dept. of Physics and Astronomy, The University of Alabama,
Tuscaloosa, AL 35487, USA  Preethi Nair  Dept. of Physics and Astronomy, The
University of Alabama, Tuscaloosa, AL 35487, USA  Jimmy Irwin  Dept. of
Physics and Astronomy, The University of Alabama, Tuscaloosa, AL 35487, USA
Sara Ellison  Dept. of Physics and Astronomy, The University of Victoria,
Victoria, BC V8P 5C2, Canada  Shobita Satyapal  Dept of Physics and Astronomy,
George Mason University, Fairfax, VA 22030, USA  Niv Drory  Dept of Astronomy,
The University of Texas at Austin, Austin, TX 78712, USA  Amy Jones  Space
Telescope Science Institute, Baltimore, MD 21218, USA  William Keel  Dept. of
Physics and Astronomy, The University of Alabama, Tuscaloosa, AL 35487, USA
Karen Masters  Department of Physics and Astronomy, Haverford College,
Haverford, PA 19041, USA  David Stark  Space Telescope Science Institute,
Baltimore, MD 21218, USA  Russell Ryan  Space Telescope Science Institute,
Baltimore, MD 21218, USA  Kavya Mukundan  Dept. of Physics and Astronomy, The
University of Alabama, Tuscaloosa, AL 35487, USA

(Received October 04, 2022; Revised December 29, 2022; Accepted January 05,
2023)

###### Abstract

We investigate the role of galaxy mergers in triggering active galactic nuclei
(AGN) in the nearby universe. Our analysis is based on a sample of 79 post-
merger remnant galaxies with deep X-ray observations from Chandra/XMM-Newton
capable of detecting a low-luminosity AGN of $\geq 10^{40.5}$ erg s-1. This
sample is derived from a visually classified, volume-limited sample of 807
post-mergers identified in the Sloan Digital Sky Survey Data Release 14 with
log M∗/M${}_{\odot}\geq 10.5$ and $0.02\leq$z$\leq 0.06$. We find that the
X-ray AGN fraction in this sample is $55.7\%\pm 5.6\%$ compared to $23.6\%\pm
2.8\%$ for a mass- and redshift-matched noninteracting control sample. The
multiwavelength AGN fraction (identified as an AGN in one of X-ray, IR, radio
or optical diagnostics) for post-mergers is $76.6\%\pm 4.8\%$ compared to
$39.1\%\pm 3.2\%$ for controls. Thus post-mergers exhibit a high overall AGN
fraction with an excess between 2 - 4 depending on the AGN diagnostics used.
In addition, we find most optical, IR, and radio AGN are also identified as
X-ray AGN while a large fraction of X-ray AGN are not identified in any other
diagnostic. This highlights the importance of deep X-ray imaging to identify
AGN. We find that the X-ray AGN fraction of post-mergers is independent of the
stellar mass above log M∗/M${}_{\odot}\geq 10.5$ unlike the trend seen in
control galaxies. Overall, our results show that post-merger galaxies are a
good tracer of the merger–AGN connection and strongly support the theoretical
expectations that mergers trigger AGN.

Galaxy evolution — Galaxy interactions — Galaxy mergers — Active galactic
nuclei

††journal: ApJ

##  1 Introduction

It is well known that most massive galaxies host a supermassive black hole
(SMBH) in their centers (Gebhardt et al., 2000; Hickox et al., 2009; McConnell
et al., 2012; Kormendy & Ho, 2013). When material is accreted onto a SMBH, it
triggers an active galactic nucleus (AGN), which can ionize the gas and/or
push gas out of the galaxy (i.e., AGN “feedback”) stopping star-formation. AGN
are expected to play a role in regulating the star formation and mass growth
of galaxies (Bower et al., 2006; Croton et al., 2006; Hopkins et al., 2008;
Schaye et al., 2015; Pillepich et al., 2019).

Theoretically, mergers of galaxies are expected to trigger AGN (Hopkins et
al., 2005; Springel et al., 2005; Somerville et al., 2008; Choi et al., 2012;
Steinborn et al., 2018). The current simplest picture of how bulge-
dominated/elliptical galaxies form is: (1) Gas rich, star-forming galaxies
merge triggering gas inflows and enhanced star formation in the center. These
systems may be observed as (ultra)luminous infrared galaxies (LIRGS). (2)
Optical/IR quasars with high Eddington ratios are triggered when gas is
accreted onto the SMBHs. (3) The AGN or stellar-driven winds quench star
formation by heating and expelling gas, creating post-merger remnants (or
bulge-dominated galaxies) with colors that span a range from the blue cloud to
the red sequence on the color magnitude diagram. AGN activity declines in this
phase until finally (4) a red and dead spheroid is formed, which may exhibit
intermittent radio AGN activity (Hickox et al., 2009).

Unfortunately, observational support for this scenario is in dispute with some
studies finding strong support for mergers triggering AGN while others find no
evidence. Numerous studies have found a higher optical/mid-IR AGN fraction in
galaxy mergers compared to noninteracting galaxies in the local universe. For
example, Ellison et al. (2011) found an optical AGN enhancement of $\sim$2.5
times in Sloan Digital Sky Survey (SDSS) very close pairs ($<$10 kpc) at
$0.01<z<0.2$ compared to isolated control galaxies. They also found an
increasing optical AGN fraction with decreasing projected separation. Many
other low-redshift ($z<0.2$) studies with similar approaches have also found
that AGN are more likely to appear in galaxy mergers than isolated galaxies
both in the optical (Keel et al., 1985; Alonso et al., 2007; Woods & Geller,
2007; Ellison et al., 2013) and in the mid-IR (Satyapal et al., 2014; Weston
et al., 2017; Goulding et al., 2018; Gao et al., 2020). This suggests a
connection between AGN and mergers.

Comparatively few studies have probed the X-ray AGN fraction in mergers
relative to isolated galaxies in the nearby universe. The recent study
presented by Secrest et al. (2020) found no statistically significant
enhancement of X-ray-selected AGN with L $\sim$ 1041.5 erg s-1 in SDSS post-
merger galaxies relative to noninteracting galaxies at $0.01<z<0.2$. However,
they did find an enhancement of mid-IR AGN for the same sample with an AGN
excess $\sim 17$ when compared to a noninteracting control sample.

X-ray studies at higher redshifts provide conflicting results. Silverman et
al. (2011) have found an excess of X-ray AGN with L $>$ 1042 erg s-1 in
kinematic close pairs compared to isolated galaxies at $0.25<z<1$. A similar
X-ray AGN excess in similar luminosity range (L $\geq$ 1042 erg s-1) was also
found in late-stage mergers relative to isolated galaxies by Lackner et al.
(2014) at $0.25<z<1$. However, Shah et al. (2020) found a lack of enhancement
of X-ray AGN with L $\geq$ 1042 erg s-1 in galaxy pairs at $0.5<z<3.0$ from
the Cosmological Evolution Survey and the Cosmic Assembly Near-infrared Deep
Extragalactic Legacy Survey.

An alternate approach is to look at the merger frequency in AGN host galaxies
compared to non-AGN host galaxies. Ellison et al. (2019) have found an
interacting fraction in both optical-selected and mid-IR-selected AGN host
galaxies, which is a factor of 2 higher than that in non-AGN control galaxies.
Their results strongly suggest that AGN are related to galaxy mergers. Similar
results were also found in studies of optical AGN host galaxies at $0.1<z<0.4$
(Bennert et al., 2008; Letawe et al., 2010; Bessiere et al., 2012; Hong et
al., 2015) and mid-IR AGN at $0.4<z<1$ (Urrutia et al., 2008), suggesting a
merger–AGN connection.

Studies of the merger rate in X-ray-selected AGN host galaxies provide
conflicting results. Koss et al. (2010) have found a high merger rate (18% vs
1%) in the Swift Burst Alert Telescope AGN sample (L $\geq$ 1042 erg s-1)
compared to non-AGN host galaxies at $z<0.05$, suggesting mergers are the
dominant mechanism triggering luminous AGN. Studies of X-ray-selected and
optical-selected luminous AGN (L $\geq$ 1042 erg s-1) also found a higher
merger rate compared to non-AGN host galaxies at $z<0.2$ (Koss et al., 2012;
Cotini et al., 2013). On the contrary, Gabor et al. (2009) analyzed the
morphology of X-ray-selected AGN host galaxies with L $\geq$ 1042 erg s-1 at
$0.3<z<1.0$ and found no difference between the asymmetry of AGN host galaxies
and non-AGN control galaxies. Numerous similar studies of the morphology of
X-ray luminous AGN host galaxies (L $\geq$ 1042 erg s-1) have not found strong
levels of merger signatures at $z<1$ (Grogin et al., 2005; Cisternas et al.,
2011, 2013; Villforth et al., 2014; Ellison et al., 2019) and at higher
redshifts $z\sim 2$ (Kocevski et al., 2012), which suggest that mergers are
not the primary mechanism triggering AGN.

Figure 1: SDSS montage of 10 random post-mergers with tidal tails, shells, or
debris structures. The size of each stamp is $\sim 50^{\prime\prime}$ on a
side.

Figure 2: SDSS montage of 10 noninteracting control galaxies. The control
galaxies have a wider range of morphology. Each control galaxy corresponds to
one post-mergers in the same order as in Figure 1. The size of each stamp is
$\sim 50^{\prime\prime}$ on a side.

There are many potential causes for these discrepant results. According to
simulations, AGN luminosities and lifetimes are variable at different merger
stages. AGN in mergers are in a lower-luminosity phase ($L_{bol}<10^{42}$ erg
s-1) for a longer duration ($\sim 1-2$ Gyr, Hopkins et al., 2008; Blecha et
al., 2018) compared to the luminous AGN phase ($L_{bol}>10^{42}$ erg s-1) of
$\sim 1-10$ Myr (Conselice, 2006; Martini, 2004; Hopkins & Hernquist, 2009).
Therefore, studies that do not probe low-luminosity AGN (LLAGN) cannot provide
a complete census of the merger-triggered AGN population. The sporadic nature
of the luminous AGN phase will also naturally lead to an underestimate in the
fraction of mergers that have experienced an AGN. Most previous studies have
mainly focused on the luminous AGN phase. Many have relied on single-wave-band
AGN diagnostics (such as optical, X-ray, or IR) which provide an incomplete
census of AGN. For example, optical AGN diagnostics can suffer from
significant contamination. As galaxy mergers can trigger both star formation
and AGN, the emission from faint AGN can be overpowered by star formation. In
addition, the source of Low-Ionization Nuclear Emission-line Regions (LINERs)
and composite emission is also uncertain. X-ray AGN emission can also be
contaminated by emission from X-ray binaries or hot gas. Dust obscuration can
also lead to an underestimate of the AGN fraction. Lastly, many previous works
have relied on incomplete/impure samples of mergers at a range of merger
stages, which can obfuscate correlations between mergers and AGN.

To probe the merger–AGN connection, we need to identify LLAGN in a merger
stage where the lifetimes of the merger signatures are comparable to the LLAGN
lifetimes. Post-merger galaxies are the ideal sample to investigate this
correlation. They are the end products of major mergers observed during or
after coalescence, from just before the ultraluminous infrared galaxy (ULIRG)
phase through to the remnant phase when the AGN fades and shells and tidal
tails are apparent (see Figure 1). These tidal structures have lifetimes
comparable to the lifetimes of LLAGN ($\sim$ 1 Gyr, Barnes, 1992; Conselice,
2006; Lotz et al., 2008; Ji et al., 2014). Hence, they are the ideal targets
to look for LLAGN.

Unfortunately, identifying AGN in post-merger systems using optical
diagnostics (i.e., Baldwin–Phillips–Telervich (BPT) diagrams, Baldwin et al.
(1981)) alone is challenging. While LINER- and composite-like emission ratios
can be caused by AGN, they can also be produced by post-AGB stars or shocks
(Singh et al., 2013; Davies et al., 2017). As post-merger galaxies are shocked
systems, they exhibit LINER-like emission line ratios and cannot be confirmed
as AGN by optical diagnostics alone. Therefore, multiwavelength diagnostics
are required in order to confirm their AGN nature.

In this paper, we use these different selection techniques to identify AGN in
our post-merger galaxies, which should enable a more comprehensive study of
the merger–AGN connection. This paper is arranged as follows. In Section 2, we
describe our high-mass post-merger subsample, the available multiwavelength
data, and the analysis techniques we used for reducing X-ray observations. In
Section 3, we describe the results of the multiwavelength AGN fraction in
high-mass post-merger galaxies and control galaxies. In Section 4, we compare
our results to previous studies and explain the reasons of the discrepancy. In
Section 5, we summarize the main conclusions in this work.

##  2 Sample and Analysis Techniques

###  2.1 High-mass Post-merger Subsample

The post-merger sample is derived from a parent catalog of 113,693 galaxies
with 0.02 $\leq$ z $\leq$ 0.06 and 9 $\leq$ log M∗/M${}_{\odot}\leq$ 12 from
the SDSS Data Release 14 (York et al., 2000) main sample. Nair (2023, in
preparation; hereafter N23) visually classified the SDSS images of this 113k
sample following the prescription described in Nair & Abraham (2010) to
identify bars, rings, spiral arms, interacting galaxies, close pairs, dual
nuclei, merger remnants, etc. N23 identifies $\sim$ 1,200 post-merger remnant
galaxies. The work of this paper focuses on the high-mass (log
M∗/M${}_{\odot}\geq$ 10.5) subsample of 807 post-merger galaxies. Example
images of post-merger galaxies are shown in Figure 1.

To investigate the X-ray AGN nature of post-merger galaxies, we used new,
deep, Chandra observations (proposal ID: 19700403 by PI Nair) for a sample of
12 objects. Eleven of these objects are in our high-mass subsample. The
observations were designed to be deep enough to detect a source down to
luminosity of $10^{40}$ erg s-1, a threshold chosen as the luminosity from
contaminants such as X-ray binaries (XRBs), which are expected to be lower
than this threshold for our sample (see Section 3). To complement data in the
archive, the sample was chosen to not be Seyfert galaxies as classified by the
[O III]/H$\beta$ vs [N II]/H$\alpha$ optical BPT diagnostic using the Kewley
et al. (2001) and Schawinski et al. (2007) demarcation lines and to have
z$<$0.04 to keep exposure times reasonable per target.

We crossmatched our high-mass (log M∗/M${}_{\odot}\geq$ 10.5) post-merger
sample with the Chandra and XMM-Newton archive. Given the large imaging field,
we used a search radius of $10^{\prime}$ in Chandra and $18^{\prime}$ in XMM-
Newton observations to allow a search for both targeted and serendipitous
observations for our galaxies. We also restricted our matches to be within
$10^{\prime}$ of the focal point (off-axis angle) of Chandra observations and
$18^{\prime}$ of the XMM-Newton observations to allow robust point-spread
function (PSF) corrections. There are 36 post-mergers that were observed in
Chandra, and 47 were observed in XMM. We also crossmatched the post-merger
sample with the CSC 2.0 catalog (Evans et al., 2010) and the 4XMM-DR11 source
catalog (Webb et al., 2020) to ensure no X-ray source is missed. For each
observation, we calculated the detection limit in photon counts by using the
$3\sigma$ Poisson upper limit for (assumed) zero background count (Gehrels,
1986). We converted the detection limit from counts to fluxes and luminosities
using the WebPIMMS111 https://heasarc.gsfc.nasa.gov/cgi-
bin/Tools/w3pimms/w3pimms.pl by assuming a simple power-law model with
$\Gamma=1.9$ and Galactic absorption assuming the HI4PI survey map (HI4PI
Collaboration et al., 2016).

In order to search for the very faint AGN, we further selected observations
that were deep enough to detect a source with L $\geq 10^{40.5}$ erg s-1.
(Very few of the archived sources had detection limits down to $10^{40}$ erg
s-1). There are 26 Chandra-observed sources and 41 XMM-observed sources that
satisfy this detection threshold. An additional Chandra post-merger galaxy has
shallower Chandra observations but has a point-source detection. Hence, we
still included it in our sample. Of the 27 Chandra-observed post-mergers, 12
were serendipitously observed in the field of view while the remaining 15 were
targeted X-ray observations. Of the 15, 10 were targeted because they were AGN
preselected in either hard X-ray, radio, IR, or optical. The remaining 5 were
targeted for other reasons not directly related to their potential AGN nature.
For the 41 XMM-observed sources, 28 were serendipitously observed while the
other 13 post-mergers were targeted. Of the 13, 10 were targeted because they
were preselected as AGN in other wavebands. This yields a sample of 38
Chandra-observed galaxies and 41 unique XMM-observed galaxies. In total, there
are 79 high-mass post-merger galaxies with deep observations or a source
detection in either Chandra or XMM. A summary of the targets is shown in Table
1 for Chandra data and Table 2 for XMM, which also include details on the
X-ray observations. The serendipitously observed galaxies are marked with a
following the SDSS object ID. Galaxies with b marked in Table 1 are the (non-
Seyfert) post-mergers observed as part of our Chandra proposal.

Optical data for the 79 post-mergers are available from the value-added
catalog compiled by the Max Planck Institute for Astrophysics and the John
Hopkins University (MPA-JHU, Brinchmann et al., 2004; Kauffmann et al., 2003a;
Tremonti et al., 2004). The MPA-JHU catalog contains optical emission line
fluxes, equivalent widths measurements, and spectral indexes from SDSS single-
fiber spectra, which are used to identify AGN in this work. This catalog also
provides derived stellar masses and star formation rate (SFR) measured within
the 3$"$ SDSS fiber (fiber value) and those measured for the entire galaxy
(total value).

We crossmatched these 79 X-ray-observed post-mergers with value-added catalogs
from infrared and radio. Infrared measurements were obtained by crossmatching
with the All-sky Wide-field Infrared Survey Explorer (ALLWISE) catalog (Cutri
& et al., 2014), which contains photometric measurements for over 700,000,000
objects detected in the all-sky imaging of the Wide-field Infrared Survey
Explorer (WISE; Wright et al., 2010). This catalog provides magnitudes
measured with profile-fitting photometry in four different filters centered at
3.4, 4.6, 12, and 22 $\mu$m (denoted as W1, W2, W3, and W4). By using a search
radius of $5^{\prime\prime}$, we found counterparts for all 79 post-mergers.
Radio data were obtained from the Very Large Array (VLA) Faint Images of the
Radio Sky at Twenty cm (FIRST) catalog (Becker et al., 1994), which contains
radio flux densities for sources detected by the VLA over 10,000 square
degrees of the north and south sky in the FIRST (Becker et al., 1995)) survey.
Using a search radius of $30^{\prime\prime}$, 77 out of these 79 post-mergers
had counterparts in the VLA FIRST catalog. The remaining two galaxies do not
have FIRST radio observation and are excluded from the multiwavelength AGN
analysis.

In summary, out of 79 high-mass X-ray observed post-mergers, 77 have
multiwavelength observations in all four wavebands: optical, X-ray, infrared,
and radio band. We will discuss AGN identification in Section 3.

Table 1: Chandra-observed post-merger galaxies

SDSS ObjID | R.A. | Dec. | z | log$\frac{M_{*}}{M_{\odot}}$ | ObsID | Exp. | Sep. | $\Gamma$ | log$\frac{L_{X}}{ergs^{-1}}$ | log$\frac{L_{XRB}}{ergs^{-1}}$ | log$\frac{L_{gas}}{ergs^{-1}}$ | BPT
---|---|---|---|---|---|---|---|---|---|---|---|---
| J2000 | J2000 |  |  |  | ksec | arcmin |  |  |  |  |
1237651272966275163 | 143.96 | 61.35 | 0.039 | 10.9 | 2033 | 49.3 | 0.59 | 0.44 | 41.6 | 39.9 | 39.4 | L
1237651539262701677a | 242.84 | 52.45 | 0.029 | 10.6 | 6859 | 14.8 | 2.58 | - |  $<$39.9 | 39.0 | 36.6 | N
1237651539792953375 | 222.33 | 63.27 | 0.042 | 11.3 | 12797 | 28.7 | 0.29 | 1.97 | 40.6 | 39.4 | 37.4 | S
1237652600101142677b | 319.27 | -6.72 | 0.029 | 11.1 | 20435 | 12.9 | 0.44 | 1.92 | 41.0 | 39.3 | 38.5 | C
1237654030867562543a | 176.39 | 3.23 | 0.020 | 10.8 | 17029 | 4.9 | 9.38 | 1.9 | 40.4 | 40.3 | 39.8 | C
1237654400765395076a | 177.62 | 65.74 | 0.055 | 10.9 | 10355 | 7.8 | 1.75 | 1.9 | 40.9 | 39.4 | 38.5 | S
1237654602104569933a | 159.88 | 5.10 | 0.027 | 10.7 | 15117 | 13.6 | 4.12 | 1.9 | 40.1 | 39.8 | 39.5 | C
1237654881271414816 | 209.28 | 5.25 | 0.040 | 10.8 | 14932 | 46.5 | 0.19 | 1.9 | 40.2 | 40.0 | 39.6 | C
1237655349431959652 | 246.76 | 43.47 | 0.047 | 11.0 | 10273 | 14.8 | 1.68 | 1.9 | 40.7 | 39.2 | 36.9 | L
1237655465922658349 | 215.65 | 59.93 | 0.029 | 10.8 | 14933 | 29.0 | 0.18 | 1.89 | 40.7 | 39.1 | 38.2 | C
1237655468597575708a | 225.33 | 1.63 | 0.035 | 11.1 | 5907 | 48.4 | 5.76 | 1.01 | 41.7 | 40.4 | 38.5 | C
1237656496713105500a | 333.63 | 13.77 | 0.024 | 10.6 | 5635 | 27.0 | 3.52 | - |  $<$39.5 | 38.7 | 36.7 | N
1237657629513809952b | 135.75 | 40.43 | 0.029 | 10.6 | 20430 | 11.9 | 0.43 | - |  $<$40.0 | 39.2 | 38.7 | C
1237658205567320143 | 130.93 | 35.82 | 0.054 | 11.1 | 18143 | 22.7 | 0.27 | 1.17 | 43.4 | 39.6 | 39.1 | S
1237658423556964512a | 167.20 | 7.00 | 0.041 | 10.9 | 12749 | 19.3 | 1.33 | - |  $<$40.1 | 39.3 | 38.1 | N
1237658612519141389a | 173.70 | 49.07 | 0.033 | 11.4 | 6946 | 47.3 | 1.86 | 1.9 | 39.8 | 39.3 | 36.9 | N
1237658800968761369b | 202.31 | 53.08 | 0.029 | 11.2 | 20436 | 12.9 | 0.28 | - |  $<$40.0 | 39.1 | 37.5 | L
1237659897784566134b | 264.68 | 57.23 | 0.030 | 10.8 | 20432 | 12.9 | 0.32 | - |  $<$40.0 | 39.0 | 37.4 | N
1237661354316726385 | 179.77 | 58.34 | 0.054 | 11.4 | 17116 | 93.8 | 0.33 | 1.16 | 42.0 | 39.4 | 37.3 | L
1237661387602853939 | 206.17 | 55.88 | 0.037 | 10.9 | 18177 | 59.9 | 0.13 | 1.17 | 41.7 | 39.8 | 39.4 | S
1237662194528026666b | 189.59 | 42.20 | 0.029 | 10.7 | 20431 | 11.9 | 0.26 | 1.64 | 41.4 | 39.0 | 37.0 | L
1237662199356325991b | 225.46 | 9.72 | 0.034 | 10.7 | 20427 | 16.9 | 0.35 | - |  $<$40.0 | 39.1 | 36.8 | N
1237662224616128524a | 218.32 | 34.73 | 0.034 | 10.9 | 19668 | 24.7 | 8.06 | 1.78 | 41.7 | 39.9 | 38.1 | L
1237662236393406478a | 186.64 | 9.03 | 0.025 | 11.0 | 2982 | 37.9 | 2.60 | 1.9 | 39.7 | 39.1 | 36.3 | L
1237662335719309348b | 241.66 | 30.09 | 0.022 | 11.0 | 20434 | 7.0 | 0.37 | - |  $<$40.0 | 39.6 | 38.6 | C
1237662666963025994 | 247.47 | 24.44 | 0.038 | 10.7 | 18169 | 9.1 | 0.18 | 1.52 | 42.3 | 39.7 | 39.3 | C
1237663480337072277 | 343.77 | 0.97 | 0.053 | 10.8 | 8173 | 15.9 | 0.29 | 1.9 | 40.8 | 39.3 | 38.7 | N
1237663783674314797 | 31.56 | -0.29 | 0.043 | 11.3 | 19560 | 48.6 | 0.36 | 1.57 | 43.0 | 39.8 | 39.3 | L
1237665331471515679 | 208.07 | 31.44 | 0.045 | 11.2 | 12712 | 67.8 | 0.28 | 1.07 | 42.9 | 39.7 | 39.0 | L
1237665372796223576a | 239.14 | 20.05 | 0.032 | 11.1 | 21400 | 17.8 | 5.77 | - |  $<$40.0 | 39.2 | 36.7 | N
1237665532798763287b | 244.66 | 15.55 | 0.030 | 11.3 | 20437 | 12.9 | 0.41 | - |  $<$40.0 | 39.3 | 37.2 | L
1237665564998762503b | 219.84 | 19.99 | 0.030 | 11.0 | 20433 | 12.9 | 0.34 | - |  $<$40.0 | 39.0 | 37.7 | C
1237665566615666691 | 234.72 | 17.02 | 0.030 | 11.0 | 18080 | 9.8 | 0.16 | 1.01 | 41.4 | 39.1 | 37.9 | S
1237667212121604127b | 138.57 | 22.27 | 0.027 | 10.6 | 20429 | 11.4 | 0.30 | - |  $<$40.0 | 38.7 | 37.1 | N
1237667430091194665 | 134.65 | 18.37 | 0.060 | 11.1 | 14970 | 19.8 | 0.16 | 1.9 | 40.7 | 39.7 | 39.0 | S
1237667430630228069b | 139.56 | 20.36 | 0.031 | 10.5 | 20428 | 13.8 | 0.42 | 1.9 | 40.4 | 38.9 | 37.5 | L
1237667536920707358 | 121.19 | 10.77 | 0.035 | 10.8 | 22089 | 10.0 | 0.28 | 0.43 | 43.2 | 39.6 | 38.8 | S
1237667915416731720a | 176.22 | 19.77 | 0.027 | 10.7 | 17201 | 61.3 | 3.94 | 1.9 | 41.2 | 39.0 | 38.3 | C

Note. — (1) SDSS object IDs. IDs marked with a were serendipitously observed
in the field of view. IDs marked with b were the objects observed as part of
our Chandra proposal (ID: 19700403). Columns (2) and (3) are the RA and DEC
J2000 epoch coordinates, respectively. (4) Spectroscopic redshifts. (5)
Stellar mass in log M∗/M⊙. (6) Chandra observation IDs. (7) Exposure time in
ksec. (8) Off-axis angle in arcminutes. (9) Photon index $\Gamma$. For sources
with counts $>50$, the spectra were fit with XSPEC and the best-fit $\Gamma$
is reported. For sources with counts $<50$, a $\Gamma=1.9$ is used, which is
typical for low-luminosity AGN. See Section 2.3 for details. (10) 2 - 10 keV
luminosity calculated by XSPEC or WebPIMMS. Upper limits are shown for
nondetections. (11) The expected 2 - 10 keV luminosity from low-mass and high-
mass X-ray binaries calculated by using the Lehmer et al. (2010) empirical
relation. (12) The expected 0.5 - 2 keV luminosity from hot gas calculated
using the Mineo et al. (2012) relation. (13) Optical AGN BPT classification: S
for Seyferts. L for LINERs. C for composites. N for objects not classified on
the BPT due to a low S/N. There are no high-mass post-mergers classified as
star forming by the BPT diagnostic.

Table 2: XMM-observed post-merger galaxies

SDSS ObjID | R.A. | Dec. | z | log$\frac{M_{*}}{M_{\odot}}$ | ObsID | Exp. | Sep. | log$\frac{L_{X}}{ergs^{-1}}$ | log$\frac{L_{XRB}}{ergs^{-1}}$ | log$\frac{L_{gas}}{ergs^{-1}}$ | BPT
---|---|---|---|---|---|---|---|---|---|---|---
| J2000 | J2000 |  |  |  | ksec | arcmin |  |  |  |
1237649963529535543 | 51.36 | -6.14 | 0.034 | 10.9 | 0760230401 | 21.9 | 1.70 | 42.4 | 40.3 | 39.9 | S
1237651534946959533 | 130.40 | 54.91 | 0.045 | 10.7 | 0403190901 | 13.5 | 1.68 | 42.7 | 39.7 | 38.8 | S
1237651735777509473a | 226.99 | 1.23 | 0.035 | 10.9 | 0402781001 | 19.7 | 4.28 | 40.9 | 40.3 | 39.9 | C
1237652900758880309 | 24.98 | -9.24 | 0.042 | 11.6 | - | - | - | 40.5 | 40.6 | 38.0 | L
1237652901297061972a | 27.88 | -8.78 | 0.036 | 11.2 | 0761730401 | 37.3 | 9.64 |  $<$39.4 | 40.2 | 39.3 | N
1237652942625767592 | 330.42 | 11.85 | 0.030 | 11.3 | 0762630201 | 21.9 | 1.75 | 40.3 | 40.3 | 39.0 | L
1237653438155128872 | 346.18 | -8.68 | 0.047 | 11.4 | 0790640101 | 53.6 | 1.71 | 44.1 | 40.6 | 40.0 | S
1237653616933535826a | 158.19 | 58.86 | 0.046 | 11.5 | 0142970101 | 25.5 | 9.54 |  $<$39.8 | 40.5 | 37.8 | L
1237654382515060810a | 138.35 | 52.98 | 0.025 | 11.1 | - | - | - | 40.6 | 40.1 | 37.6 | L
1237655370892247130a | 154.65 | 59.66 | 0.044 | 10.7 | 0406630201 | 41.4 | 11.22 |  $<$39.1 | 40.0 | 39.5 | C
1237655373573062713a | 247.43 | 40.81 | 0.029 | 11.6 | 0203710201 | 26.3 | 1.07 | 41.6 | 40.5 | 38.0 | L
1237657857145962520 | 176.84 | 52.44 | 0.049 | 10.7 | 0504101401 | 30.3 | 1.71 | 41.5 | 40.2 | 39.8 | S
1237657857145962550a | 176.92 | 52.44 | 0.048 | 10.8 | 0504101401 | 30.3 | 4.01 | 41.0 | 39.9 | 39.0 | C
1237658297922945185a | 157.49 | 5.48 | 0.056 | 10.6 | 0148560501 | 103.8 | 9.09 |  $<$38.9 | 39.6 | 37.4 | N
1237658299534802987 | 160.29 | 6.82 | 0.033 | 10.6 | 0782530701 | 9.9 | 1.69 | 40.4 | 39.6 | 38.6 | C
1237658304352944175a | 160.60 | 58.45 | 0.045 | 10.6 | - | - | - | 40.7 | 39.6 | 37.5 | L
1237658304355172477a | 170.13 | 59.87 | 0.054 | 10.9 | 0502780201 | 21.2 | 14.70 |  $<$39.5 | 39.9 | 37.4 | N
1237660613973049348 | 168.45 | 9.58 | 0.029 | 10.9 | 0601780201 | 15.1 | 1.68 | 42.8 | 40.1 | 39.6 | S
1237661416605679815a | 224.94 | 49.50 | 0.027 | 10.6 | 0401270301 | 23.1 | 3.95 |  $<$38.9 | 39.7 | 38.9 | N
1237661949739663472 | 235.86 | 7.91 | 0.036 | 10.8 | 0822391101 | 16.2 | 1.69 | 42.2 | 40.1 | 39.6 | C
1237662236394258511a | 188.68 | 9.00 | 0.043 | 10.6 | 0722960101 | 52.9 | 6.96 | 40.7 | 40.2 | 39.9 | C
1237662340012507431a | 239.43 | 27.46 | 0.032 | 10.8 | - | - | - | 40.5 | 39.8 | 38.9 | C
1237664092903047228a | 138.74 | 29.73 | 0.021 | 10.9 | 0673150401 | 42.4 | 13.55 | 40.7 | 39.9 | 38.8 | C
1237664106852319509a | 149.77 | 13.02 | 0.037 | 10.7 | 0504100201 | 21.9 | 1.68 | 41.6 | 39.8 | 38.8 | S
1237664106852450313a | 149.98 | 13.04 | 0.035 | 10.8 | 0504100201 | 21.9 | 10.56 | 43.3 | 40.8 | 40.5 | C
1237664667902345246a | 166.34 | 38.02 | 0.030 | 10.7 | - | - | - | 40.0 | 39.7 | 37.3 | L
1237664880485728337a | 139.28 | 29.37 | 0.035 | 10.7 | 0673150301 | 31.9 | 9.32 | 41.2 | 40.0 | 39.5 | S
1237665025440677967a | 181.45 | 35.17 | 0.054 | 10.6 | - | - | - | 43.6 | 40.1 | 39.7 | C
1237665532247670906a | 211.42 | 25.23 | 0.030 | 10.8 | - | - | - | 42.0 | 39.8 | 38.0 | S
1237666299481817317a | 50.18 | -1.04 | 0.021 | 11.1 | 0810600201 | 43.0 | 1.86 | 40.0 | 40.0 | 37.8 | L
1237667107428565094a | 130.67 | 19.65 | 0.055 | 11.2 | - | - | - | 40.7 | 40.2 | 38.5 | N
1237667210529275951 | 184.58 | 29.25 | 0.048 | 10.7 | 0762630301 | 21.9 | 1.70 | 41.0 | 39.7 | 38.4 | S
1237667211597119522a | 169.09 | 29.25 | 0.045 | 11.4 | - | - | - | 41.1 | 40.4 | 38.0 | L
1237667255624990807 | 181.18 | 31.17 | 0.025 | 10.8 | 0601780601 | 39.5 | 1.69 | 41.9 | 40.0 | 39.3 | S
1237667735572381852 | 159.96 | 20.84 | 0.046 | 11.2 | 0059800101 | 14.9 | 1.66 | 40.9 | 40.1 | 37.8 | L
1237668298739351591a | 181.04 | 20.40 | 0.024 | 11.2 | 0112270601 | 12.4 | 9.71 | 41.2 | 40.2 | 37.6 | L
1237671140947591227 | 180.24 | 6.80 | 0.036 | 10.7 | 0312191701 | 12.9 | 1.76 | 42.4 | 39.7 | - | S
1237671932283256842a | 164.93 | 10.07 | 0.035 | 10.9 | 0802200801 | 35.9 | 7.93 | 40.8 | 39.9 | 37.7 | N
1237671932820259064a | 165.31 | 10.48 | 0.042 | 10.9 | - | - | - | 40.3 | 39.9 | 38.6 | N
1237673808121495726a | 128.93 | 21.59 | 0.042 | 10.6 | 0803953001 | 38.8 | 14.55 |  $<$39.1 | 39.9 | 39.4 | C
1237674462024106294a | 136.01 | 1.45 | 0.053 | 11.0 | 0725310131 | 12.5 | 11.45 | 41.3 | 40.2 | 39.5 | C

Note. — (1) SDSS object IDs. Galaxies with a marked are the serendipitous
galaxies in XMM observations. (2) and (3) J2000 epoch. (4) Spectroscopic
redshifts. (5) Stellar mass in log M∗/M⊙. (6) XMM observation IDs. If a source
is not detected in a single archived image but is detected in the 4XMM-DR11
catalog, then their observation IDs and exposure time are not shown in the
table. (7) Exposure time in ksec. (8) Off-axis angle in arcmin. (9) 2 - 10 keV
luminosity in log unit estimated by WebPIMMS with a fix $\Gamma=1.9$. If a
source is not detected in a single archived image but is detected in the 4XMM-
DR11 catalog, the luminosity reported in the catalog is shown here. (10) 2 -
10 keV luminosity contributed from X-ray binaries in log unit calculated by
using the Lehmer et al. (2010) relation. (11) 0.5 - 2 keV luminosity form hot
gas in log unit calculated by using the Mineo et al. (2012) relation. (12) BPT
classification: S for Seyferts. L for LINERs. C for composites. N for not on
BPT due to a low S/N. There are no post-mergers classified as star forming by
BPT.

Figure 3: The top and middle panels show the stellar mass and redshift
normalized distribution of the 79 post-merger galaxies (red) and the 233
control galaxies (black dashed). The bottom panel shows the stellar mass and
redshift distribution in the 2D parameter space of post-mergers and control
galaxies.

###  2.2 Noninteracting Control Sample

For the 79 X-ray observed post-mergers, we built a control sample by searching
for noninteracting galaxies with similar redshift and stellar mass from the
$\sim$ 113,000 N23 parent sample. For each of the post-mergers, we required
its control galaxies to have a redshift within $\Delta$z $\pm 0.005$ and
stellar mass within $\Delta$log M∗/M${}_{\odot}\pm 0.1$. We found $\sim$
19,000 noninteracting control galaxies. We crossmatched this control sample
with the Chandra and XMM archive and calculated the detection limit in
luminosity with the same procedure as we did for the post-mergers. We
identified 245 Chandra-observed control galaxies and 177 XMM-observed control
galaxies for a total of 422 unique control galaxies that were deep enough to
detect a source with L $\geq 10^{40.5}$ erg s-1. We then required the same
number of X-ray-observed control galaxies matched for each of the 79 post-
mergers within the $\Delta$z and $\Delta$log M∗/M⊙ range to avoid any biases.
We found 77 out of 79 post-mergers that have three unique X-ray-observed
noninteracting control galaxies matched. For the remaining two post-mergers,
one has only two unique control galaxies and for the other (one of the most
massive galaxy in our sample; log M∗/M${}_{\odot}=11.6$) we were not able to
find any control galaxies with X-ray observations. Including this object in
our post-merger sample did not affect our results so we choose to keep it in
the sample. In total, there are 233 unique noninteracting control galaxies
with deep X-ray observations in either Chandra or XMM. Out of the 233
controls, 129 are observed in Chandra and the other 104 are observed in XMM.
Out of the 129 Chandra-observed control galaxies, 21 were targeted objects and
108 were serendipitously observed in the field of view. Out of the 104 XMM-
observed galaxies, 12 were targeted and 92 were serendipitous. These 233
control galaxies also have been observed with WISE and VLA FIRST. Their
optical emission line fluxes, equivalent widths, and spectral indexes are
provided by the MPA-JHU catalog. Figure 2 shows example images of control
galaxies. Figure 3 shows the normalized histogram distribution of stellar
masses and redshifts of post-merger galaxies and control galaxies as well as
the distribution in the 2D parameter space.

###  2.3 X-ray Data Reduction

We downloaded the raw data from the Chandra and XMM archives and reduced all
X-ray data in a consistent manner using version 4.10 of the CIAO package with
version 4.7.8 of the CALDB calibration files, XSPEC version 12.11.1c, and
WebPIMMS version 4.11b.

For Chandra sources, the data-reduction process is as follows. We reproduced
the Chandra event-2 file in CIAO by running chandra_repro and used a $90\%$
enclosed counts fraction (ECF) aperture to account for PSF correction by
running psfsize_srcs in CIAO. To estimate the background, a nearby region
$\sim$ 10 times larger was chosen without any sources. For XMM sources, we
used wavdetect in CIAO to determine the source regions, which also accounts
for PSF correction.

To identify X-ray detections in Chandra and XMM, we required a S/N $>5$
detection threshold for point sources with X-ray photon counts $>25$. For
point sources with X-ray photon counts $<25$, we used small number statistics
and required the source flux to be greater than the $3\sigma$ Poisson upper
limit of the background (Gehrels, 1986).

For Chandra detections with X-ray counts $>50$, we extracted their X-ray
spectra by using specextract and calculated their X-ray luminosities by
modeling an absorbed power-law spectrum using XSPEC. For Chandra detections
with X-ray counts $<50$ and all XMM detections, their X-ray luminosities are
calculated by applying a power-law model of a fixed photon index $\Gamma=1.9$
with Galactic absorption using WebPIMMS (Constantin et al., 2009; Ishibashi &
Courvoisier, 2010).

For the 79 post-mergers, a total of 60 X-ray point sources were detected: 26
X-ray point sources were detected out of 38 (68.4%) Chandra observations while
34 sources were detected out of 41 (82.9%) XMM observations. For the 233
control galaxies, a total of 62 X-ray point sources were detected: 33 point
sources were detected out of 129 (25.6%) Chandra observations, while 29
galaxies were detected out of 104 (or 27.9%) XMM observations. Figure 4 shows
the luminosity distribution of X-ray detections in (left) post-mergers and
(right) control galaxies. The Chandra detections are shown in blue while the
XMM detections are shown in red. It should be noted that the Chandra
observations are well resolved (1$"$), and hence the luminosity corresponds to
the central, nuclear luminosity of the galaxy. The XMM observations are not as
well resolved, and the luminosity plotted in Figure 4 is for the entire
galaxy. However, as can be seen in Figure 4, the luminosity distribution of
the XMM detections is consistent with the Chandra detections, which suggests a
similar origin. To investigate this further, we will compare the X-ray AGN
fractions in the Chandra vs XMM observations separately. In the next section,
we determine how many of the X-ray detections are classified as AGN by
comparing the observed X-ray luminosities to the luminosities expected from
X-ray binaries and/or hot gas.

Figure 4: Distributions of the 2 - 10 keV luminosities of X-ray detections in
(left) post-mergers and (right) control galaxies. Chandra detections are shown
in blue, and XMM detections are shown in red. The bin size is 0.5 dex. The
vertical line is the detection threshold at L = $10^{40.5}$ erg s-1. Both the
Chandra- and XMM-detected sources span the same range in luminosity, and they
also peak at low luminosities around $10^{41}$ erg s-1 in both post-mergers
and control galaxies.

##  3 Multiwavelength AGN Diagnostics

###  3.1 X-ray AGN Diagnostics

We consider X-ray detections with luminosities higher than those contributed
from XRBs and hot gas as X-ray AGN. X-ray hot gas mostly contributes to soft
X-ray emission between 0.5 – 2 keV with negligible contribution beyond 2 keV
while XRBs and AGN are the main sources of X-ray emission beyond 2 keV (see
Fabbiano, 1989 and Fabbiano, 2006 and references therein). To identify the
source of the X-ray emission, we use the following empirical scaling relation
from Lehmer et al. (2010) to determine the expected X-ray contribution from
high-mass and low-mass X-ray binaries (HMXB & LMXB):

$L_{XRB}=\alpha M_{\ast}+\beta SFR,$ (1)

where $\alpha=(9.05\pm 0.37)\times 10^{28}$ erg $s^{-1}M_{\odot}^{-1}$ and
$\beta=(1.62\pm 0.22)\times 10^{39}$ erg $s^{-1}(M_{\odot}yr^{-1})^{-1}$. The
X-ray emission from hot gas is calculated using the relation from Mineo et al.
(2012):

$L_{Gas}=(8.3\pm 0.1)\times 10^{38}\times SFR$ (2)

with a dispersion of 0.34 dex. For sources detected in resolved Chandra
imaging (PSF FWHM $\sim 0.5^{\prime\prime}$), their X-ray luminosities are
calculated within the $90\%$ ECF aperture, with an average radius of $\sim
1^{\prime\prime}$. Most Chandra-observed sources have a $90\%$ ECF aperture
$<3^{\prime\prime}$. We use the stellar masses and SFRs within the
$3^{\prime\prime}$ SDSS fiber to estimate the luminosities from X-ray binaries
(XRBs) and hot gas in the very center of the galaxies. In addition, two
Chandra sources in post-mergers and four Chandra sources in the controls have
a $90\%$ ECF aperture $>3^{\prime\prime}$. For these sources, we use the total
stellar masses and SFRs of the entire galaxy to estimate the luminosities from
XRBs and hot gas. For XMM detections, which are unresolved with a PSF FWHM
$\sim 6^{\prime\prime}$, we use the total stellar mass and total SFR to
estimate the luminosities from XRBs and hot gas in the entire galaxy.

Figure 5 shows the measured 2 - 10 keV X-ray luminosities for our sources vs
the luminosities expected from HMXBs and LMXBs using the Lehmer et al. (2010)
relation for (left) post-mergers and (right) control galaxies. The diagonal
line shows the $1:1$ relation, and the blue shaded region is the 1-$\sigma$
scatter of the relation. We defined sources above the 1-$\sigma$ scatter of
the Lehmer et al. (2010) relation as X-ray AGN. More or less stringent cuts do
not affect our final conclusions but do impact statistics. Figure 6, shows the
measured 0.5 - 2 keV luminosities of post-mergers (left) and control galaxies
(right) vs the estimated luminosity from X-ray hot gas using the scaling
relation in Mineo et al. (2012). All of our sources have X-ray luminosities
higher than that expected from hot gas (on average $\sim$3 orders of magnitude
higher). The three Chandra post-merger sources with luminosities close to the
1:1 line also have 2 - 10 keV luminosities consistent with XRBs and are ruled
out as AGN. Out of the 79 X-ray observed post-mergers, 60 are detected, and 49
out of the 60 detections have luminosities higher than those predicted for
X-ray binaries (see Figure 5) and hot gas (see Figure 6), which indicates
their X-ray emission is dominated by the AGN. In the control sample of 233
noninteracting galaxies, there are 62 detections, out of which 61 have X-ray
luminosities dominated by AGN.

Figure 5: 2 - 10 keV X-ray luminosities vs luminosities estimated from HMXB &
LMXB by the Lehmer et al. (2010) relation for (left) post-mergers and (right)
control galaxies. Chandra detections are shown in blue while XMM detections
are shown in red. Targeted sources are shown as crosses and serendipitous
sources are shown as circles. The black diagonal line is the $1:1$ relation,
with the 1-$\sigma$ scatter of 0.34 dex shown as blue shaded region. We
identify detections above the shaded region as X-ray AGN. In post-mergers, 23
AGN are identified in Chandra and 26 AGN are identified in XMM. In control
sample, 33 AGN are identified in Chandra, while 28 AGN are identified in XMM.

Figure 6: 0.5 - 2 keV X-ray luminosities vs estimated luminosity from X-ray
hot gas using the Mineo et al. (2012) relation for (left) post-mergers and
(right) control galaxies. The symbols and legends are the same as in Figure 5.
The black diagonal line is the $1:1$ relation, with the 1-$\sigma$ scatter of
0.34 dex shown as blue shaded region. All the detections have luminosities (3
orders of magnitudes on average) greater than those estimated from hot gas.
The three Chandra post-mergers with luminosities close to the 1:1 line have 2
- 10 keV luminosities consistent with XRBs.

####  3.1.1 X-ray AGN Frequency in Post-merger Remnants

We define the AGN fraction as the number of galaxies hosting an X-ray AGN with
L $\geq 10^{40.5}$ erg s-1. Any galaxies with a detected X-ray AGN with
luminosity $<10^{40.5}$ erg s-1 are not included as not all of our data are
deep enough to detect fainter sources. Thus our X-ray AGN fractions are lower
limits.

Out of the 38 Chandra-observed post-mergers, 26 are point-source detections.
Of the 26 Chandra nuclear detections, 23 have X-ray luminosities higher than
that expected from XRBs and hot gas. Hence, they are classified as X-ray AGN.
Out of these 23 AGN, 20 have L $\geq 10^{40.5}$ erg s-1. This yields an X-ray
AGN fraction of $52.6\%\pm 8.1\%$222The errors are calculated as
$\sqrt{f(1-f)/N}$, where f is the AGN fraction and N is the total number of
galaxies. in the Chandra-observed sample. Another three Chandra detections are
within the 1-$\sigma$ scatter shaded region and have X-ray luminosities
consistent with those of X-ray binaries. Hence, they are not identified as
X-ray AGN in our analysis.

Out of 41 XMM-observed post-mergers, 34 have been detected. Out of the 34
detections, 26 are classified as X-ray AGN, and 24 of the 26 AGN have L $\geq
10^{40.5}$ erg s-1. This implies an X-ray AGN fraction of $58.5\%\pm 7.7\%$.
The other 8 have luminosities consistent with X-ray binaries and are not
classified as X-ray AGN. The XMM AGN fraction in post-mergers is consistent
with the Chandra AGN fraction. We take this as confirmation that we can
combine the Chandra and XMM samples despite the different imaging resolutions.
In total, 44 unique X-ray AGN with L $\geq 10^{40.5}$ erg s-1 are identified
in the entire X-ray observed post-merger sample of 79 galaxies, with a
fraction of $55.7\%\pm 5.6\%$. It should be noted that this is a lower limit
on the X-ray AGN fraction. If we include those AGN with detected luminosities
$<10^{40.5}$ erg s-1, there will be 49 X-ray AGN identified in 79 post-
mergers, with an AGN fraction of $62.0\%\pm 5.5\%$.

####  3.1.2 X-ray AGN Frequency in the Control Sample

For control galaxies, out of the 129 Chandra-observed controls, all 33 X-ray
detections (blue points in Figure 5 (right) and Figure 6 (right)) are
identified as X-ray AGN, and 29 out of the 33 AGN have L $\geq 10^{40.5}$ erg
s-1. This is an X-ray AGN fraction of $22.5\%\pm 3.7\%$. For the 104 XMM-
observed controls, 28 of the 29 X-ray detections are identified as AGN, and 26
out of the 28 AGN have L $\geq 10^{40.5}$ erg s-1, which implies an X-ray AGN
fraction of $25.0\%\pm 4.2\%$. Again, the XMM AGN fraction is consistent with
the Chandra AGN fraction for control galaxies. Combining the two samples,
there are 55 unique X-ray AGN with L $\geq 10^{40.5}$ erg s-1 identified in
the entire X-ray-observed control sample of 233 galaxies. The X-ray AGN
fraction in the control sample is $23.6\%\pm 2.8\%$. Including lower-
luminosity AGN, there are 61 X-ray AGN in 233 control galaxies, with an AGN
fraction of $26.2\%\pm 2.9\%$.

The X-ray AGN frequency in high-mass post-mergers ($55.7\%\pm 5.6\%$) is
$\sim$ 2.4 times higher than that in control galaxies ($23.6\%\pm 2.8\%$).
This high X-ray AGN excess suggests a strong correlation between galaxy
mergers and AGN. The significance of this result can be quantified by a
hypergeometric test (urn problem). A hypergeometric test describes the
probability of ‘k’ successes (the number of AGN) in ‘n’ draws (sample size of
post-mergers with Chandra observations) from ‘N’ objects (total number of
post-mergers) containing ‘K’ successes (total number of AGN). In particular:

${P(X=k)={N\choose k}\times{N-K\choose n-k}/{N\choose n}}$ (3)

where ${n}\choose{k}$ = n!/(k! $\times$ (n-k)!) is the binomial coefficient.
Assuming a null hypothesis that post-mergers and control galaxies have the
same AGN fraction of 23.6%, the probability that we randomly draw 79 post-
mergers from a volume-limited sample of 807 and obtain an AGN fraction of
55.7% is less than 1 in $10^{10}$. Thus, we can rule out at $>6.5\sigma$
confidence that mergers and control galaxies have similar AGN fractions.
Applying a Fisher exact test for the association between post-mergers and
X-ray AGN, the probability (p-value) that we observe this excess by chance is
only $10^{-7}$. Hence, we find that post-mergers and AGN are strongly
correlated.

It should be noted that some of the post-merger and control galaxies were
targeted because they were identified as AGN with some other diagnostic. If we
restrict our analysis to only the serendipitously observed galaxies, then the
X-ray AGN fraction in post-merger galaxies reduces slightly to $45.0\%\pm
7.9\%$, which is consistent with our previous measurement ($55.7\%\pm 5.6\%$).
The AGN fraction in the serendipitously observed control galaxy sample also
decreases down to $17.0\%\pm 2.7\%$. The AGN excess in post-merger galaxies is
then $\sim$ 2.6 times that in control galaxies, consistent with the full
sample. Hence we will use the full 79 galaxy post-merger sample and its
control going forward.

####  3.1.3 Stacking the X-ray Nondetections

Out of the 38 Chandra-observed post-mergers, 26 have point-source detections
and 12 have no individual detections. By stacking the Chandra images of the 12
nondetections, we detected a point source in the center of the stacked image
in the soft band (0.5 - 2 keV) and hard band (2 - 8 keV), respectively. The
source counts are extracted from an aperture of $\sim 3^{\prime\prime}$ radius
after subtracting the average background. The average flux is calculated in
WebPIMMS by using a power-law spectrum with a fixed photon index $\Gamma=1.9$
and a fixed Galactic absorption column density $n_{H}=10^{20}cm^{-2}$. The
median luminosity distance of the 12 nondetections is used to convert flux to
luminosity. The stacked source has an average luminosity of log $L=39.7$ erg
s-1 with S/N=6 at 0.5 - 2 keV band and log $L=39.5$ erg s-1 with S/N=3 at 2 -
8 keV band.

As hot gas and X-ray binaries can produce X-ray emission in addition to AGN,
we need to estimate their contribution to this faint source to determine if
the emission is due to AGN, hot gas, or X-ray binaries. To estimate the
contribution of hot gas, we calculated the count ratio between the 0.5 - 2 keV
band and 2 - 8 keV band of the stacked image. For post-mergers, this ratio is
$2.5^{+3.3}_{-2.0}$. Then we compared it to the expected count ratio of a
typical hot gas model assuming an APEC spectrum with 0.768 keV (log T = 6.95)
and with the median Galactic absorption column density of the stacked post-
mergers in WebPIMMS, which results in a count ratio of $26^{+0.8}_{-0.1}$. The
count ratio of the stacked source is much lower than that of the hot gas
model. This suggests that hot gas does not contribute much to the X-ray
emission of the stacked source. We used the median star formation rate of the
stacked sample to estimate the X-ray luminosity from hot gas at 0.5 - 2 keV by
using the Mineo et al. (2012) relation (equation 2). We found that hot gas
contributes $<3\%$ of the X-ray emission of the stacked source.

To estimate the contribution of XRBs in the 2 - 8 keV band, we applied the
Lehmer et al. (2010) relation with the average stellar mass and SFR of the 12
nondetections. We calculated the X-ray luminosity from XRBs to be log $L=39.2$
erg s-1. The 2 - 8 keV luminosity of the stacked source is within the
1-$\sigma$ scatter of the luminosity from XRBs. Hence, the X-ray emission in
the stacked source of post-mergers is more consistent with XRBs rather than
AGN or hot gas.

In the stacking analysis of the Chandra-observed control sample, we exclude
the observations with targets close to the gaps between the telescope chips or
with a bright source nearby. By stacking the 83 Chandra nondetections in the
control sample, we detected a source of log $L=39.8$ with S/N=17 at 0.5 - 2
keV and log $L=39.4$ erg s-1 with S/N=8 at 2 - 8 keV. The count ratio between
the 0.5 - 2 keV band and 2 - 8 keV band of the stacked controls is $3.2\pm
0.3$. This is much lower than the expected count ratio ($75^{+1.5}_{-1.4}$) of
a 0.768 keV hot gas model with the median Galactic absorption column density
of the stacked controls. Similarly, we find that hot gas contributes $<1\%$ of
the soft-band emission and the X-ray luminosity at the hard band is within the
1-$\sigma$ scatter of the luminosity of XRBs (log $L=39.7$ erg s-1). Thus,
XRBs are the likely source of the X-ray emission in stacked nondetections.
However, we still cannot rule out the existence of faint AGN whose luminosity
is comparable to XRBs.

We also stacked the XMM nondetections in post-mergers and control galaxies and
also found a source in the stacked images in both cases. For both the stacked
objects, we found that the X-ray emission is most likely due to XRBs not AGN
or hot gas.

Figure 7: The [O III]$\lambda 5007$/H$\beta$ vs [N II]$\lambda 6584$/H$\alpha$
BPT diagram for (left) 79 post-mergers and (right) 233 control galaxies. The
grey points are all SDSS galaxies with log M∗/M${}_{\odot}\geq 10.5$ drawn
from the parent sample. Galaxies are classified into Seyferts (red), LINERs
(brown), composites (green), and star forming (blue). We consider galaxies
above the Kewley et al. (2001) solid curve (Seyferts + LINERs) as optical AGN.
Seyferts and LINERs are distinguished using the Schawinski et al. (2007)
empirical (dotted) line. Objects between the Stasinska et al. (2006) dashed
and the Kewley et al. (2001) solid lines are composites and those below the
Stasinska et al. (2006) line are star forming. The Kauffmann et al. (2003a)
empirical curve (dot dashed) is also shown for reference. In 79 post-mergers,
there are 16 Seyferts, 24 LINERs, 26 composites, and 13 unclassified. All
post-mergers including X-ray non-AGN lie above the Stasinska et al. (2006)
curve, which indicates that they are AGN candidates. In 233 control galaxies,
there are 14 Seyferts, 50 LINERs, 61 composites, 10 star forming and 98
unclassified.

###  3.2 Optical AGN Diagnostics and Frequency

To identify optical AGN, we use the emission line ratios [O III]$\lambda
5007$/H$\beta$ vs [N II]$\lambda 6584$/H$\alpha$ to construct a BPT diagram
(Baldwin et al., 1981). Fluxes of emission lines are obtained from the MPA-JHU
catalog. We place a S/N $\geq$ 3 cut for these four emission lines. By using
the Schawinski et al. (2007) empirical relation, the Kewley et al. (2001), and
the Stasinska et al. (2006) theoretical relations, galaxies are classified
into Seyferts (red, Figure 7), LINERs (brown), composites (green), and star
forming (blue) on the BPT diagram. Out of the 79 X-ray observed post-mergers,
66 have S/N $>3$ for all the four lines and are shown in Figure 7. The
remaining 13 galaxies are unclassified due to a low S/N. These 79 galaxies are
classified into 16 Seyferts (20.3%$\pm$4.5%), 24 LINERs (30.4%$\pm$5.2%), 26
composites (32.9%$\pm$5.3%), and 13 unclassified (16.5%$\pm$4.2%). No galaxy
in our high-mass post-merger sample is classified as star forming. (Most
galaxies with masses $>10^{10.5}M_{\odot}$ including controls are not
classified as star forming.) Out of 233 control galaxies, 135 are above the
S/N cuts and are classified into 14 Seyferts (6.0%$\pm$1.6%), 50 LINERs
(21.5%$\pm$2.7%), 61 composites (26.2%$\pm$2.9%), and 10 star forming
(4.3%)$\pm$1.3%, as shown in Figure 7 right. The other 98 (42.1%$\pm$3.2%)
remain unclassified due to a low S/N.

Considering only Seyferts as true AGN, the optical AGN fraction in post-
mergers (20.3%$\pm$4.5%) is 3.4 times higher than in control galaxies
(6.0%$\pm$1.6%). Considering Seyfert+LINERs, the optical AGN fraction in post-
mergers (50.6%$\pm$5.6%) is 1.8 times higher than that in control galaxies
(27.5%$\pm$2.9%). Including composites, the AGN excess in post-mergers
relative to controls is 1.6. The Seyfert-only excess is more consistent with
the X-ray measured AGN excess in post-mergers. Contamination by non-AGN
sources (post-AGB stars, shocks) in optically identified LINERs and composites
likely causes an underestimate in the measurement of optical AGN excess. This
is also true using other optical AGN diagnostics as shown in the Appendix.

Some studies (Cid Fernandes et al., 2011; Stasinska et al., 2006) have applied
an equivalent width cut on H$\alpha$ (EW$>$3Å) to remove potential
contaminants. If we apply the same cut (EW(H$\alpha$)$>$3Å), we find a Seyfert
fraction of 20.3%$\pm$4.5% in post-mergers and 5.2%$\pm$1.4% in control
galaxies. The Seyferts + LINERs fraction is 34.2%$\pm$5.3% in post-mergers and
9.0%$\pm$1.9% in control galaxies. We find a consistent optical AGN excess of
3.8 in post-mergers relative to controls when considering either Seyferts or
Seyferts+LINERs with the equivalent width cut (See Table 3). However, the
equivalent width cut preferentially removes X-ray-identified low-luminosity
AGN.

To investigate this further, we look at the X-ray properties of Seyferts,
LINERs, and composites. In Figure 7, galaxies with an X-ray-identified AGN are
shown as circles for Chandra and crosses for XMM. X-ray non-AGN are shown as
filled squares. Remarkably, all post-merger galaxies classified as Seyferts
are also identified as X-ray AGN. This high X-ray AGN fraction in Seyferts
compared to that in other BPT classes is consistent with a previous study by
Constantin et al. (2009). Out of the 24 post-merger LINERs, 11 (or 45.8% $\pm$
10.2%) are identified as X-ray AGN. Out of the 26 composite optical AGN, 14
(or 53.8% $\pm$ 9.8%) are identified as X-ray AGN, a similar fraction as
LINERs. Similar trends are seen for controls. Out of the 14 control Seyferts,
10 (or 71.4% $\pm$ 12.1%) are identified as X-ray AGN. Out of the 50 control
LINERs, 17 (or 34.0% $\pm$ 6.7%) are identified as X-ray AGN. Out of 61
composites, 17 (or 27.9% $\pm$ 5.7%) are also identified as X-ray AGN. As
expected, the X-ray AGN fraction in control galaxies is lower for Seyferts,
LINERs, and composites in comparison to post-merger galaxies. While a
significant fraction of optical LINERs and composites are clearly X-ray AGN,
many are not, suggesting contamination by shocks or post-AGB stars (Binette et
al., 1994; Dopita & Sutherland, 1996; Yan & Blanton, 2012; Singh et al.,
2013). Applying an equivalent width cut on H$\alpha$ does not significantly
alter these results. We investigate the multiwavelength AGN properties in more
detail in Section 4.

Figure 8: W1 - W2 vs W2 - W3 in Vega magnitudes for (left) 79 post-mergers and
(right) 233 control galaxies. W1, W2, and W3 are the magnitudes of filters
centered at 3.4, 4.6, and 12$\mu$m in the WISE survey. The dashed line is the
AGN selection criterion adopted from Assef et al. (2013). Galaxies above the
dashed line are classified as WISE infrared AGN. Galaxies with X-ray AGN
identified in Chandra are shown as blue circles, while AGN identified in XMM
are shown as red crosses. Galaxies not hosting an X-ray AGN are shown as black
squares. The sizes of the symbols are related to their X-ray luminosities (for
AGN). The relative sizes of the minimal and maximum luminosities are shown in
the legend. Out of the 18 WISE AGN identified in post-mergers, 17 are also
identified as AGN in X-rays, and they tend to have higher X-ray luminosities
than non-WISE AGN. In the control sample, 8 WISE AGN are identified, and all
eight are also identified as X-ray AGN.

###  3.3 WISE AGN Diagnostics and Frequency

In the infrared, we use the WISE color diagnostics to identify AGN. Figure 8
shows the WISE color W1–W2 vs W2–W3 diagram for the (left) 79 post-mergers and
(right) 233 control galaxies. Galaxies with an AGN detected in X-rays are
color coded into blue circles for Chandra and red crosses for XMM. The sizes
of the data points indicate their X-ray luminosities. By using the WISE AGN
criteria: W1 - W2 $>0.5$ from Assef et al. (2013), we identify 18 WISE AGN out
of 79 post-merger galaxies, which implies an infrared AGN fraction of
$22.8\%\pm 4.7\%$. Remarkably, 17 out of the 18 WISE AGN are also identified
as AGN in X-rays and they are more luminous in X-rays than other X-ray AGN
that are not identified as WISE AGN. This is consistent with previous works
that show that infrared color diagnostics have a selection bias towards the
most luminous AGN (Mateos et al., 2013; Yan et al., 2013; Rovilos et al.,
2014).

In the control samples, 8 WISE AGN are identified out of the 233 X-ray
observed control galaxies, with an infrared AGN fraction of $3.4\%\pm 1.2\%$.
All of the 8 AGN are also identified as X-ray AGN. The infrared AGN excess of
post-mergers is $\sim$ 6.7 relative to noninteracting control galaxies, which
strongly suggests mergers trigger AGN. This is consistent with many previous
works finding a high infrared AGN excess in post-mergers and galaxy pairs
relative to noninteracting galaxies (Ellison et al., 2013; Satyapal et al.,
2014; Weston et al., 2017; Goulding et al., 2018; Gao et al., 2020).

Figure 9: The $D_{n}(4000)$ strength vs 1.4 GHz radio luminosity per stellar
mass (left panel) and the H$\alpha$ luminosity in solar unit vs 1.4 GHz radio
luminosity (right panel) for 77 post-mergers (top) and 233 control galaxies
(bottom). The curve on the $D_{n}(4000)$ vs $L_{1.4GHz}/M_{\ast}$ plane is
adopted from Best et al. (2005). For $L_{1.4GHz}/M_{\ast}<12.2$, a straight-
line cut is adopted from Kauffmann et al. (2008) with the equation
$D_{n}(4000)=1.45-0.55\times$ (log $(L_{1.4GHz}/M_{\ast})-12.2)$. The straight
line on the $L_{H\alpha}/L_{Sun}$ vs $L_{1.4GHz}$ plane is adopted from Best &
Heckman (2012) with the equation log $(L_{H\alpha}/L_{Sun})=1.12\times$ (log
$L_{1.4GHz}-17.5)$. Galaxies with X-ray AGN identified in Chandra are shown as
blue circles, while AGN identified in XMM are shown as red crosses. Galaxies
not hosting X-ray AGN are shown as squares. In this work, galaxies classified
by either one of these two planes are considered to be radio AGN (shown in
green). There are four radio AGN classified in post-mergers. Three out of
these four are also identified in X-rays. There are 16 radio AGN identified in
control galaxies, and 13 out of 16 are also X-ray AGN.

###  3.4 Radio AGN Diagnostics and Frequency

There are 77 post-mergers out of the 79 that have been observed by the VLA
FIRST survey. Out of the 77, 49 have radio detections showing the presence of
a radio core in the center of the galaxies. Radio lobes have also been found
in some sources, indicating AGN. However, both AGN and star formation can
produce core radio emission. In order to exclude galaxies with radio emission
dominated by star formation, we apply two methods to identify radio AGN. The
first method is to compare the strength of the $D_{n}(4000)$ break in the
optical spectra to the 1.4 GHz radio luminosity per stellar mass (see Figure 9
left). The demarcation curve between radio-loud AGN and normal star-forming
galaxies was developed by Best et al. (2005) and modified by Kauffmann et al.
(2008). It is 0.225 higher in $D_{n}(4000)$ than the track produced by a
galaxy with an exponentially declining star formation rate of 3 Gyr e-folding
time. Radio AGN are expected to have radio luminosities higher than normal
star-forming galaxies (to the right of the curve). The second method is to
compare the H$\alpha$ luminosity in solar unit to the 1.4 GHz radio luminosity
(see Figure 9 right). Galaxies to the right of the straight line show a radio
luminosity excess relative to star-forming galaxies, and hence they are
identified as radio-loud AGN. Figure 9 shows these two planes for the 77 post-
merger galaxies in the upper panel and 233 control galaxies in the lower
panel. The 1.4 GHz radio luminosities are obtained from the VLA FIRST catalog,
while the strength of $D_{n}(4000)$ and H$\alpha$ luminosities are obtained or
derived from the MPA-JHU catalog. Galaxies located either above the division
line on the ‘$D_{n}(4000)$ vs $L_{1.4GHz}/M_{\ast}$’ plane or below the
division line on the $L_{H\alpha}/L_{Sun}$ vs $L_{1.4GHz}$ plane are
classified as radio AGN, which are shown in green in Figure 9. Out of the 77
post-mergers, 4 are classified as radio-loud AGN, with a radio AGN fraction of
$5.2\%\pm 2.5\%$.

In the control sample, all the 233 control galaxies are observed by the VLA
FIRST survey, out of which, 56 have radio detections showing a radio core. By
using the same identification method, 16 radio AGN are identified from the 233
X-ray observed control sample, which yields a radio AGN fraction of $6.9\%\pm
1.7\%$. The AGN fraction in post-mergers and in control galaxies are
comparable to each other. Thus, there is no enhancement in the radio AGN
fraction in post-mergers relative to control galaxies. This suggests that
mergers may have no role in triggering radio AGN. It is interesting to note
that the radio AGN fraction obtained is similar to that in higher-redshift
studies such as Hickox et al. (2009). Unlike that study, we find most of our
radio AGN in both post-merger and control galaxies are identified as X-ray
AGN. We discuss this further in Section 4.

Figure 10: Venn diagrams for multiwavelength AGN. The upper panel shows the
AGN identified in X-rays, infrared, radio, and optical (Seyferts only) for
(left) the 77 post-mergers and (right) the 233 control galaxies. The lower
panel shows the same four wavelength bands but considers both Seyferts and
LINERs as optical AGN. X-ray AGN are shaded in blue. Radio AGN are shaded in
yellow, while infrared AGN are in red and optical AGN are in green. The
multiwavelength AGN fraction are shown above the diagram. The AGN excess in
post-mergers relative to control galaxies is $\sim 2.2$ when considering
Seyferts only as optical AGN, and $\sim 2.3$ including LINERs as optical AGN.
Table 3: Dependence of AGN fraction and excess on AGN diagnostics

| AGN in post-mergers | AGN in control galaxies | AGN Excess
---|---|---|---
Chandra | 20 / 38 ($52.6\%\pm 8.1\%$) | 29 / 129 ($22.5\%\pm 3.7\%$) | $2.3\pm 0.5$
XMM | 24 / 41 ($58.5\%\pm 7.7\%$) | 26 / 104 ($25.0\%\pm 4.2\%$) | $2.3\pm 0.5$
Chandra+XMM | 44 / 79 ($55.7\%\pm 5.6\%$) | 55 / 233 ($23.6\%\pm 2.8\%$) | $2.4\pm 0.4$
WISE infrared | 18 / 79 ($22.8\%\pm 4.7\%$) |  8 / 233 ($~{}3.4\%\pm 1.2\%$) | $6.7\pm 2.7$
FIRST radio |  4 / 77 ($~{}~{}5.2\%\pm 2.5\%$) | 16 / 233 ($~{}6.9\%\pm 1.7\%$) | $0.8\pm 0.4$
Optical (BPT, Seyfert) | 16 / 79 ($20.3\%\pm 4.5\%$) | 14 / 233 ($~{}6.0\%\pm 1.6\%$) | $3.4\pm 1.2$
Optical (BPT, Seyfert, EWH$\alpha>3$Å) | 16 / 79 ($20.3\%\pm 4.5\%$) | 12 / 233 ($~{}5.2\%\pm 1.4\%$) | $3.9\pm 1.4$
Optical (BPT, Seyfert+LINER) | 40 / 79 ($50.6\%\pm 5.6\%$) | 64 / 233 ($27.5\%\pm 2.9\%$) | $1.8\pm 0.3$
Optical (BPT, Seyfert+LINER, EWH$\alpha>3$Å) | 27 / 79 ($34.2\%\pm 5.3\%$) | 21 / 233 ($~{}9.0\%\pm 1.9\%$) | $3.8\pm 1.0$
Optical (BPT, S+L+composite) | 66 / 79 ($83.5\%\pm 4.2\%$) | 125 / 233 ($53.6\%\pm 3.3\%$) | $1.6\pm 0.1$
Optical (BPT, S+L+composite, EWH$\alpha>3$Å) | 52 / 79 ($65.8\%\pm 5.3\%$) | 55 / 233 ($23.6\%\pm 2.8\%$) | $2.8\pm 0.4$
Optical (WHaN, strong AGN) | 45 / 79 ($57.0\%\pm 5.6\%$) | 34 / 233 ($14.6\%\pm 2.3\%$) | $3.9\pm 0.7$
Optical (WHaN, strong+weak AGN) | 51 / 79 ($64.6\%\pm 5.4\%$) | 53 / 233 ($22.7\%\pm 2.7\%$) | $2.8\pm 0.4$
X-ray, WISE, radio | 45 / 77 ($58.4\%\pm 5.6\%$) | 58 / 233 ($24.9\%\pm 2.8\%$) | $2.3\pm 0.3$
WISE, radio, optical (S+L, EWH$\alpha>3$Å) | 33 / 77 ($42.9\%\pm 5.6\%$) | 39 / 233 ($16.7\%\pm 2.4\%$) | $2.6\pm 0.5$
X-ray, WISE, radio, optical (Seyferts,EWH$\alpha>3$Å) | 45 / 77 ($58.4\%\pm 5.6\%$) | 61 / 233 ($26.2\%\pm 2.9\%$) | $2.2\pm 0.3$
X-ray, WISE, radio, optical (S+L,EWH$\alpha>3$Å) | 49 / 77 ($63.6\%\pm 5.5\%$) | 65 / 233 ($27.9\%\pm 2.9\%$) | $2.3\pm 0.3$
X-ray, WISE, radio, optical (S+L+composite,EWH$\alpha>3$Å) | 59 / 77 ($76.6\%\pm 4.8\%$) | 91 / 233 ($39.1\%\pm 3.2\%$) | $2.0\pm 0.2$
X-ray, WISE, radio, optical (WhaN) | 60 / 77 ($77.9\%\pm 4.7\%$) | 99 / 233 ($42.5\%\pm 3.2\%$) | $1.8\pm 0.2$

Note. — The table lists the number of AGN and the AGN fraction in post-mergers
and control galaxies and the AGN excess in different wavelength bands. The AGN
excess is defined as the AGN fraction in post-mergers relative to that in
control galaxies. When calculating the AGN fraction for a specific wavelength
band or telescope, only the galaxies with existing observations are taken into
account. The WHaN AGN fraction (Cid Fernandes et al., 2011), described in the
Appendix, is also shown in this table.

##  4 Discussion

###  4.1 Multiwavelength AGN Fraction

In the previous section, we investigated the merger–AGN relation in post-
merger galaxies and controls individually in the X-rays, optical, mid-
infrared, and radio. We found a significant AGN excess in post-mergers
compared to control galaxies in the X-ray, infrared, and optical bands. In
this section, we will discuss the multiwave-band AGN fraction by combing all
four AGN identification methods. We identify a galaxy as an AGN if it is
detected as an AGN in at least one diagnostic. We will first calculate the
multiwave-band AGN fraction by considering only Seyferts as optical AGN. Then
we will include LINERs. We will also apply the equivalent width cut on
H$\alpha$ to be $>$ 3Å.

Figure 10 shows Venn diagrams of AGN identified in all four wavebands: X-rays
(blue), mid-IR (red), radio (yellow), and optical (green) for post-mergers
(left) and their control galaxies (right). The top panels consider Seyferts
only as optical AGN while the bottom panel considers both Seyferts and LINERs
as optical AGN. Note that only 77 of the 79 post-mergers are shown in these
diagram as two post-mergers do not have FIRST radio observations. The upper
panels in Figure 10 show that 45 of the 77 post-mergers ($58.4\%\pm 5.6\%$)
are identified as AGN in at least one band (X-rays, IR, radio and optical)
while 61 of the 233 control galaxies ($26.2\%\pm 2.9\%$) are identified as
AGN. Nearly all WISE mid-IR and FIRST radio AGN are also X-ray AGN no matter
if they are post-mergers or control galaxies. This is also true for a large
fraction of optically identified AGN. Thus the overall multiwavelength AGN
fraction is dominated by the X-ray-detected sample. The multiwavelength AGN
fraction in post-merger galaxies is $\sim 2.2$ times higher than in
noninteracting control galaxies. By applying a hypergeometric test, we can
rule out that post-mergers and control galaxies have similar AGN fractions at
$>6.5\sigma$ confidence level. Applying a Fisher exact test, we find post-
mergers and AGN are strongly correlated with a p-value of $10^{-7}$.

The bottom Venn diagrams in Figure 10 show the multiwavelength AGN (including
LINERs as optical AGN) identified in post-mergers and control galaxies. There
are 49 AGN out of 77 post-mergers identified in at least one band. The
multiwavelength AGN fraction including optical LINERs in the post-merger
sample is $63.6\%\pm 5.5\%$. In the control sample, 65 AGN out of 233 control
galaxies are identified in at least one band, which is shown as the last Venn
diagram in Figure 10. This implies an AGN fraction of $27.9\%\pm 2.9\%$ in
control galaxies. The AGN excess in post-mergers is $\sim 2.3$ relative to
control galaxies. By applying a similar hypergeometric test, we can rule out
that post-mergers and control galaxies have similar AGN fractions at
$>6.5\sigma$ confidence level. A Fisher exact test shows that mergers and AGN
are strongly related with a p-value = $10^{-8}$ for the null hypothesis.

We find that a large fraction of AGN are identified mainly in X-rays ($\sim
80\%$ in both post-mergers and control galaxies). In fact, $\sim$ 40% of AGN
are only identified in deep X-ray imaging for both post-mergers and control
galaxies. If we consider AGN classified in WISE, radio, and optical, the
multiwavelength AGN fraction is $42.9\%\pm 5.6\%$ in post-mergers and
$16.7\%\pm 2.4\%$ in control galaxies. Although it still implies a similar AGN
excess (2.6), the multiwavelength AGN fraction is lower without X-ray AGN.
Hence, deep X-ray observations are crucial to probe the complete demographics
of AGN and the merger–AGN relation.

Table 3 summarizes the AGN fractions and excesses obtained using different AGN
selection techniques for both post-mergers and their controls. In every
wavelength range, except radio, post-mergers have a higher AGN fraction
compared to control galaxies. However, the exact values of the AGN fraction
and excess obtained differ based on the diagnostic.

Figure 11: X-ray AGN fraction in 79 post-mergers (red) and 233 control
galaxies (black) as a function of the X-ray luminosity threshold. The numbers
of X-ray AGN above each luminosity threshold are shown next to the data
points. The red dashed line shows the X-ray AGN excess as a function of the
X-ray luminosity threshold.

Figure 12: X-ray AGN fraction (blue circles), optical AGN fraction (green
circles), and IR AGN fraction (red circles) in post-mergers and control
galaxies (black triangles) as a function of the stellar mass, color, and
environment density. Here we only consider X-ray AGN with luminosities
$>=10^{40.5}$ erg s-1. In the optical, we consider Seyferts + LINERs with
EW(H$\alpha$)$>$3Å as AGN. We also show the Seyferts + LINERs without the
equivalent width cut with dashed lines. The numbers of galaxies per bin are
shown near the points. There is an increasing trend of the X-ray AGN fraction
in control galaxies as a function of the stellar mass while the X-ray AGN
fraction in post-mergers stays roughly the same. The optical and IR AGN
fractions do not show a dependence on the stellar mass in neither post-mergers
nor controls. There is a decreasing trend of the X-ray and IR AGN fractions as
a function of the color in post-mergers while the AGN fraction in control
galaxies does not show a dependence on color. The AGN fraction stays roughly
consistent in different environment densities in both post-mergers and control
galaxies in all three wavebands.

Our multiwavelength AGN excess in optical and WISE diagnostics is consistent
with that of many previous works (Ellison et al., 2011, 2013; Satyapal et al.,
2014; Weston et al., 2017; Goulding et al., 2018; Gao et al., 2020). However,
our X-ray analysis is not consistent with a similar work. Secrest et al.
(2020) investigated the AGN fraction in 43 post-mergers by using XMM-Newton
observations. They found that $4.7^{+9.3}_{-3.8}\%$ (2/43) of their post-
mergers host an X-ray AGN while $2.1^{+1.5}_{-1.0}\%$ (9/430) of
noninteracting galaxies have X-ray AGN detections, with an excess of $\sim
2.22^{+4.44}_{-2.22}$ which though comparable to our measured excess was not
statistically significant. Compared to their work, we find both a higher X-ray
AGN fraction in post-mergers ($55.7\%\pm 5.6\%$) and control galaxies
($23.6\%\pm 2.8\%$) and a significant AGN excess in post-mergers. As can be
seen in Figure 5, most of the X-ray AGN in both our post-merger sample and
control sample have luminosities $<10^{43}$ erg s-1, with a median value of
log L = $41.6$ in post-mergers and log L = $41.4$ in control galaxies. The
Secrest et al. (2020) sample, while not having a single detection threshold,
was restricted to objects with luminosities between $10^{41}-10^{43}$ erg s-1,
with a median luminosity of $\sim 10^{41.5}$ erg s-1. If we restrict our
sample to the same luminosity range, we obtain an X-ray AGN fraction of
$29.1\%\pm 5.1\%$ in post-mergers and $13.5\%\pm 1.7\%$ in control galaxies
leading to an AGN excess of $2.2\pm 0.5$. We attribute the lower X-ray AGN
fraction in Secrest et al. (2020) to (a) their sample not having uniform
depth, (b) a smaller sample size spanning a wider range in merger stages, and
(c) having contamination from noninteracting galaxies (like outer ring
galaxies) in their post-merger sample.

Figure 11 shows the X-ray AGN fraction (solid line) and AGN excess (dashed
line) versus the threshold X-ray luminosity for post-mergers (red lines) and
control galaxies (black line). We find that the AGN fraction obtained
decreases with increasing X-ray-detection threshold, as expected. However, the
AGN excess stays in the range of 2 - 3 for any X-ray threshold luminosity
chosen. There are indications that the AGN excess in post-mergers may increase
at higher luminosities. However, we do not have the statistics to confirm
this. This is consistent with some previous studies that found that major
mergers tend to trigger the most luminous AGN more frequently than normal
galaxies (Treister et al., 2012; Glikman et al., 2015; Hong et al., 2015;
Dietrich et al., 2018; Goulding et al., 2018; Weigel et al., 2018; McAlpine et
al., 2020). However, there are other studies finding no trend between mergers
and luminous AGN (Villforth et al., 2014; Marian et al., 2019).

Overall, unlike many previous studies mainly focusing on luminous AGN (e.g.,
Silverman et al., 2011; Lackner et al., 2014; Weston et al., 2017; Goulding et
al., 2018), our sample probes AGN with a wider range of X-ray luminosities
from $10^{44}$ erg s-1 down to $10^{40.5}$ erg s-1. By specifically including
LLAGN, we are able to have a more complete census of the AGN population.

###  4.2 Dependence of the AGN Fraction on Galaxy Properties

In addition to AGN selection techniques, sample selection could play a role in
understanding the merger–AGN connection. In Figure 12, we investigate the
X-ray AGN fraction (top), optical AGN fraction (middle), and WISE IR AGN
fraction (bottom) as a function of the stellar mass (left), g - r color
(middle), and environment density (right) of the post-mergers and control
galaxies. Again, we only consider X-ray AGN with luminosities $>=10^{40.5}$
erg s-1. We find that the X-ray AGN fraction in the 79 post-mergers is $\sim
56\%$ and nearly independent of the stellar mass given our measurement errors
(blue, solid line), while in the 233 galaxy control sample (black, solid
line), the X-ray AGN fraction increases with the stellar mass. This suggests
that X-ray LLAGN in post-merger galaxies are a better tracer of the
supermassive black hole (SMBH) occupation fraction compared to normal,
noninteracting galaxies.

In Figure 12 (left, middle row), we consider Seyferts and LINERs with
EW(H$\alpha$) $>$ 3Å as AGN (solid lines). We also show the Seyferts + LINERs
without the equivalent width cut (dotted lines) for comparison. The optical
AGN fraction does not depend on the stellar mass in neither post-mergers nor
the control sample. Removing the equivalent width cut in H$\alpha$ leads to a
dependence of the AGN fraction on the stellar mass such that the AGN fractions
are higher in more massive galaxies. This is likely due to increased
contamination by non-AGN LINERs at higher masses. The IR AGN fraction is also
consistent with having no dependence on the stellar mass for post-mergers
given the error bars.

The middle column in Figure 12 shows the dependence of the AGN fraction on the
galaxy color. We find a clear trend of decreasing X-ray AGN fraction from blue
to red (g - r) colors for post-mergers. Bluer post-mergers tend to have a very
high X-ray AGN fraction ($\sim 90\%$) than redder post-mergers ($\sim 30\%$).
Our control galaxy sample shows no such trend in the X-rays. This trend with
the color could be related to the gas content in these merger systems.

The optical AGN fraction shows no clear dependence on the galaxy color given
the error bars although post-mergers with intermediate colors (g-r = 0.6-0.8)
may have a slightly higher optical AGN fraction.

The IR AGN fraction in post-mergers shows a similar dependence on the color as
the X-ray AGN fraction such that bluer post-merger galaxies have a higher IR
AGN fraction compared to redder galaxies. This is consistent with Hickox et
al. (2009) finding that AGN identified in the mid-IR tend to be located in
blue star-forming galaxies. The control sample shows a slight IR AGN excess
for intermediate colors.

Figure 13: The (g - r) color vs stellar mass diagram (left) and the specific
SFR vs stellar mass diagram (right) of AGN in post-mergers on the upper panel
and control galaxies on the lower panel. AGN identified in X-rays are shown as
blue crosses; in optical as green, open circles; in WISE mid-IR as red, open
boxes; and in radio as filled, orange stars. The grey contours show the N23
SDSS sample of 113K galaxies. The outermost grey contours include 99% of all
galaxies in the N23 sample from SDSS DR14. The (g - r) color vs stellar mass
diagram is divided into red-sequence, green-valley, and blue-cloud regions by
dashed lines. The specific SFR vs stellar mass diagram is divided into active
star-forming, transition, and quiescent regions. The black dashed lines are
drawn by eye. Optical and X-ray sources span the entire range of galaxy
properties. Radio AGN are in the red-sequence/quiescent region while IR AGN
are in the blue-cloud/active SF region and green-valley/transition region.

When constructing the control sample, we only controlled for the stellar mass
and redshift. However, the environment of galaxies can affect the gas content
and triggering of an AGN (Kim et al., 2020). Figure 12 (right) shows the
dependence of the X-ray AGN fraction on the environment density in post-
mergers and the control sample. The environment density for our galaxies is
obtained from Baldry et al. (2006). We find that the X-ray AGN fraction in
both post-merger and control galaxies is nearly independent of the
environment. The optical and IR AGN fractions also show no dependence (or a
very mild dependence) on the galaxy environment within errors. It should be
noted that our sample does not probe the most massive clusters. Hence, we
cannot rule out a dependence of the AGN fraction on the environment in the
densest regions.

The color and stellar mass of our sample are key factors in determining the
AGN fraction in both post-mergers and controls. Figure 13 shows the (g - r)
color vs stellar mass diagram on the left and the specific SFR vs stellar mass
diagram on the right for AGN identified in post-mergers (top) and controls
(bottom). The gray contours are for the entire N23 SDSS 113K galaxy sample.
X-ray-identified AGN are shown as blue crosses, optical AGN are shown as green
open circles, IR AGN are shown as red open squares, and radio AGN are shown as
yellow stars. The dashed lines in each plot show the demarcation between
passive/red-sequence, green-valley, and star-forming/blue-cloud galaxies. We
find that X-ray AGN are distributed throughout the color–mass and sSFR–mass
space for both post-mergers and controls. The same is true for optical AGN. IR
AGN are more likely to be located in star-forming/blue-cloud or green-valley
galaxies. On the contrary, AGN identified in the radio tend to appear in the
passive/red-sequence regions. This is consistent with Hickox et al. (2009) and
numerous studies (Magliocchetti, 2022 and references therein) which claim that
radio AGN are more likely in massive, red galaxies where they are important in
maintaining quenching. The mechanisms triggering radio AGN are expected to be
related to the stellar mass of the galaxy (Magliocchetti, 2022) and not
external triggers.

Figure 14: X-ray luminosity versus (left) stellar mass, (middle) SDSS (g - r)
color, and (right) environment density for post-mergers (red filled circles)
and control galaxies (black filled triangles). Each plot is divided into three
bins. Each box shows the first quartile to the third quartile range of the
data in that bin, with a line at the median and a solid symbol at the mean.
The whiskers extend from the box by 1.5x the interquartile range. Outliers are
shown as open symbols. There is no dependence of the mean or median X-ray
luminosity of post-mergers or controls on the stellar mass, color, or
environment.

###  4.3 Dependence of the AGN Luminosities on Galaxy Properties

Figure 14 shows the distribution of the X-ray luminosities of AGN in post-
mergers (red circles) and controls (black triangles) in bins of the (left)
stellar mass, (middle) color, and (right) environment density. We find no
dependence of the AGN luminosity on the stellar mass of the galaxy for both
post-mergers and controls. The median X-ray luminosities in both post-mergers
and their noninteracting controls are similar. This suggests that while
mergers help trigger more AGN, the AGN properties might not depend on the
triggering mechanism. There is a large scatter in X-ray luminosities. However,
this could be driven by our smaller AGN sample for both post-mergers and
control galaxies at large masses.

The X-ray AGN luminosity of post-mergers also shows no dependence on the
galaxy color within errors although there are mild hints that it may increase
with blue colors. The control galaxies show no dependence of the AGN
luminosity on the galaxy color. Lastly, neither post-mergers nor controls show
any dependence of the X-ray luminosity on the environment within our
measurement errors. It should be noted that we cannot rule out the presence of
strong dust obscuration, which could lead to an underestimate in the measured
X-ray luminosities of our sources. This will be investigated in future work
with NuSTAR (Harrison et al., 2013) observations.

##  5 Summary

In this paper, we investigate the relationship between mergers and AGN in the
nearby universe with 79 post-merger remnant galaxies and 233 control galaxies
with X-ray imaging from Chandra or XMM. We find that the X-ray AGN fraction in
post-merger galaxies is $\sim 55.7\%\pm 5.6\%$, and it is $\sim$2.4 times
higher than that in a mass- and redshift-matched control sample. The
significance of this results is $>$6.5$\sigma$. The AGN fraction and excess
obtained are sensitive to the AGN selection technique used. An AGN excess is
seen using X-rays, optical, and mid-infrared AGN diagnostics but not in the
radio. We find that the X-ray AGN fraction of post-merger remnants is
independent of the stellar mass and galaxy environment but strongly depends on
the galaxy color so that blue galaxies have higher X-ray AGN fractions. On the
other hand, the X-ray AGN fraction in noninteracting control galaxies has a
strong dependence on the galaxy mass, increasing with the stellar mass, but
shows no dependence on the galaxy color or environment given our measurement
errors. These trends strongly depend on the AGN wavelength diagnostics used.
We find that probing low-luminosity AGN with deep X-ray observations provides
a better constraint on the overall AGN fractions. Our work shows that deep
X-ray data are essential to understanding the merger–AGN connection. We will
be extending this work to lower-mass galaxies with $9<$log
M∗/M${}_{\odot}<10.5$ and investigating quenching signatures in these merger
remnants in future papers.

## Acknowledgement

Support for this work was provided by the National Aeronautics and Space
Administration through Chandra Award Number 19700403 issued by the Chandra
X-ray Center, which is operated by the Smithsonian Astrophysical Observatory
for and on behalf of the National Aeronautics Space Administration under
contract NAS8-03060. The scientific results reported in this article are based
on observations made by the Chandra X-ray Observatory, data obtained from the
Chandra Data Archive and the Chandra Source Catalog 2.0, and software provided
by the Chandra X-ray Center (CXC) in the application packages CIAO.

This work was also based on observations obtained with XMM-Newton, an ESA
science mission with instruments and contributions directly funded by ESA
Member States and NASA. This research has made use of data obtained from the
4XMM XMM-Newton Serendipitous Source Catalog compiled by the 10 institutes of
the XMM-Newton Survey Science Centre selected by ESA.

Coauthor Preethi Nair would also like to acknowledge support by the National
Science Foundation under Grant No. 1616547. The NSF grant enabled the visual
classification of the parent sample of galaxies used in this analysis. Any
opinions, findings, and conclusions or recommendations expressed in this
material are those of the author(s) and do not necessarily reflect the views
of the National Science Foundation.

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. This research has
made use of ALLWISE catalog from the NASA/IPAC Infrared Science Archive
(IRSA), which is funded by the National Aeronautics and Space Administration
and operated by the California Institute of Technology.

This publication makes use of the VLA FIRST catalog provided by the National
Radio Astronomy Observatory, which is a facility of the National Science
Foundation operated under cooperative agreement by Associated Universities,
Inc.

This publication makes use of data from the Sloan Digital Sky Survey. Funding
for the Sloan Digital Sky Survey has been provided by the Alfred P. Sloan
Foundation, the U.S. Department of Energy Office of Science, and the
Participating Institutions. SDSS acknowledges support and resources from the
Center for High Performance Computing at the University of Utah. The SDSS
website is www.sdss.org.

##  Appendix A Other optical diagnostics

Figure 15: The [O III]/H$\beta$ vs [N II]/H$\alpha$, [O III]/H$\beta$ vs [S
II]/H$\alpha$ and [O III]/H$\beta$ vs [O I]/H$\alpha$ BPT diagrams for post-
mergers in the upper panel and control galaxies in the lower panel. The grey
points at the background are the general galaxies with log
M∗/M${}_{\odot}>10.5$ in SDSS DR14. Galaxies with an X-ray AGN identified in
Chandra are shown with circles. AGN identified in XMM are shown with crosses.
Galaxies are classified as Seyferts (red), LINERs (brown), composites (green),
and star forming (blue) by the Stasinska et al. (2006) dashed curve and the
Kewley et al. (2006) solid lines. The Kauffmann et al. (2003b) curve is also
plotted for comparison.

The optical AGN diagnostic used in this work is introduced in Section 3, which
is the [O III]$\lambda 5007$/H$\beta$ vs [N II]$\lambda 6584$/H$\alpha$ BPT
diagram. We have found that all BPT Seyferts and 45.8% of LINERs in post-
mergers are identified as X-ray AGN by either Chandra or XMM. Here we compare
our single BPT diagnostic to other optical AGN diagnostics. Figure 15 shows
the combined BPT diagnostics (Kewley et al., 2006) for post-mergers in the
upper panel and control galaxies in the lower panel. We applied a cut of S/N
$>3$ on all six emission lines ([O III]$\lambda 5007$, H$\beta$, [N
II]$\lambda 6584$, H$\alpha$, [S II]$\lambda 6717,6731$, and [O I]$\lambda
6300$). Galaxies below the Stasinska et al. (2006) dashed curve on the
[NII]/H$\alpha$ diagram and below the Kewley et al. (2006) solid curves on [S
II]/H$\alpha$ and [O I]/H$\alpha$ diagrams are classified as star forming
(blue). Galaxies between the dashed curve and the Kewley et al. (2001) solid
curve on [NII]/H$\alpha$ diagram are classified as composites (green).
Galaxies above either one of the solid curves on these three diagrams are
classified as optical AGN (Seyferts + LINERs). Seyferts (red) are classified
as above either one of the division straight lines on [S II]/H$\alpha$ or [O
I]/H$\alpha$ diagrams. The 79 post-mergers are classified into 21 Seyferts, 19
LINERs, 16 composites, and no star forming. The remaining 23 galaxies are
unclassified due to a low S/N. Using the combined BPT diagnostics, the optical
AGN (Seyferts + LINERs) fraction in post-mergers is $50.6\%\pm 5.6\%$. The 233
control galaxies are classified into 15 Seyferts, 29 LINERs, 21 composites,
and 8 star forming. The remaining 160 galaxies have low S/N and are not
classified by the BPT diagnostic. The optical AGN fraction in the control
sample is $18.9\%\pm 2.6\%$, which implies an optical AGN excess of $\sim 2.7$
in post-mergers relative to control galaxies. Applying the equivalent width
cut of EWH$\alpha>3$Å , we obtained an optical AGN of $41.8\%\pm 5.5\%$ in
post-mergers and $12.0\%\pm 2.1\%$ in control galaxies. This implies an AGN
excess of 3.5$\pm$0.8. The AGN excess obtained with this method is higher than
that obtained from the single [N II] BPT method. However, this method results
in a large unclassified fraction in the sample compared to the single BPT
method as we placed S/N cuts on two additional emission lines.

Figure 16: The H$\alpha$ equivalent width vs [N II]/H$\alpha$ diagrams for
post-mergers on the left and control galaxies on the right. The grey points at
the background are the general galaxies with log M∗/M${}_{\odot}>10.5$ in SDSS
DR14. Galaxies with an X-ray AGN identified in Chandra are shown with circles.
AGN identified in XMM are shown with crosses. Galaxies are classified into
Seyferts (red), weak AGN (brown), retired galaxies (green), star-forming
galaxies (blue), and passive galaxies (black).

Another optical AGN diagnostic is the WHaN diagram (Cid Fernandes et al.,
2011), which uses the H$\alpha$ equivalent width vs [N II]/H$\alpha$ emission
line ratio. We applied a cut of S/N $>3$ on H$\alpha$ and [N II]. Pure star-
forming galaxies (blue) are classified with log ([N II]/H$\alpha)<-0.4$ and
W(H$\alpha$) $>$ 3Å. Strong AGN (i.e., Seyferts; red) are classified with log
([N II]/H$\alpha)>-0.4$ and W(H$\alpha$) $>$ 6Å. Weak AGN (brown) are
classified with log ([N II]/H$\alpha)>-0.4$ and W(H$\alpha$) between 3 and 6Å.
Retired galaxies (green) are classified with W(H$\alpha$) $<$ 3Å. Passive
galaxies (black) are classified with W(H$\alpha$) and W([N II]) $<$ 0.5Å.
LINERs in this method are defined as the combination of weak AGN and retired
galaxies. Figure 16 shows the WHaN diagnostic for post-mergers (left) and
control galaxies (right). The 79 post-mergers are classified into 45 strong
AGN, 6 weak AGN, 20 retired galaxies, 1 passive galaxy and 1 star-forming
galaxy. The remaining 6 galaxies have a low S/N and are unclassified. The
optical AGN (strong + weak AGN) fraction in post-mergers with this method is
$64.6\%\pm 5.4\%$. The 233 control galaxies are classified into 34 strong AGN,
19 weak AGN, 87 retired galaxies, 11 star-forming galaxies, and 10 passive
galaxies. The remaining 72 galaxies are unclassified due to a low S/N. The
optical AGN fraction in the control sample is $22.7\%\pm 2.7\%$. The optical
AGN excess is $\sim 2.8$ in post-mergers relative to control galaxies. This is
consistent with the optical BPT AGN excess in post-mergers relative to control
galaxies. In addition, the number of multiwavelength AGN is consistent no
matter which optical diagnostic is used. However, 38.2% of the strong AGN
classified by the WHaN diagram in post-mergers are X-ray non-AGN, unlike in
the [N II]/H$\alpha$ single BPT where all Seyfert post-mergers were X-ray
detected. This suggests that the WHaN diagram may misclassify some non-AGN
host galaxies as strong AGN.

In summary, we find a strong excess of AGN in post-mergers compared to control
galaxies in all optical AGN diagnostics.

## References

  * Alonso et al. (2007) Alonso, M. S., Lambas, D. G., Tissera, P., & Coldwell, G. 2007, MNRAS, 375, 1017, doi: 10.1111/j.1365-2966.2007.11367.x
  * Assef et al. (2013) Assef, R. J., Stern, D., Kochanek, C. S., et al. 2013, ApJ, 772, 26, doi: 10.1088/0004-637X/772/1/26
  * Baldry et al. (2006) Baldry, I. K., Balogh, M. L., Bower, R. G., et al. 2006, MNRAS, 373, 469, doi: 10.1111/j.1365-2966.2006.11081.x
  * Baldwin et al. (1981) Baldwin, J. A., Phillips, M. M., & Terlevich, R. 1981, PASP, 93, 5, doi: 10.1086/130766
  * Barnes (1992) Barnes, J. E. 1992, ApJ, 393, 484, doi: 10.1086/171522
  * Becker et al. (1994) Becker, R. H., White, R. L., & Helfand, D. J. 1994, in Astronomical Society of the Pacific Conference Series, Vol. 61, Astronomical Data Analysis Software and Systems III, ed. D. R. Crabtree, R. J. Hanisch, & J. Barnes, 165
  * Becker et al. (1995) Becker, R. H., White, R. L., & Helfand, D. J. 1995, ApJ, 450, 559, doi: 10.1086/176166
  * Bennert et al. (2008) Bennert, N., Canalizo, G., Jungwiert, B., et al. 2008, ApJ, 677, 846, doi: 10.1086/529068
  * Bessiere et al. (2012) Bessiere, P. S., Tadhunter, C. N., Ramos Almeida, C., & Villar Martín, M. 2012, MNRAS, 426, 276, doi: 10.1111/j.1365-2966.2012.21701.x
  * Best & Heckman (2012) Best, P. N., & Heckman, T. M. 2012, MNRAS, 421, 1569, doi: 10.1111/j.1365-2966.2012.20414.x
  * Best et al. (2005) Best, P. N., Kauffmann, G., Heckman, T. M., & Ivezić, Ž. 2005, MNRAS, 362, 9, doi: 10.1111/j.1365-2966.2005.09283.x
  * Binette et al. (1994) Binette, L., Magris, C. G., Stasińska, G., & Bruzual, A. G. 1994, A&A, 292, 13
  * Blecha et al. (2018) Blecha, L., Snyder, G. F., Satyapal, S., & Ellison, S. L. 2018, MNRAS, 478, 3056, doi: 10.1093/mnras/sty1274
  * Bower et al. (2006) Bower, R. G., Benson, A. J., Malbon, R., et al. 2006, MNRAS, 370, 645, doi: 10.1111/j.1365-2966.2006.10519.x
  * Brinchmann et al. (2004) Brinchmann, J., Charlot, S., White, S. D. M., et al. 2004, MNRAS, 351, 1151, doi: 10.1111/j.1365-2966.2004.07881.x
  * Choi et al. (2012) Choi, E., Ostriker, J. P., Naab, T., & Johansson, P. H. 2012, ApJ, 754, 125, doi: 10.1088/0004-637X/754/2/125
  * Cid Fernandes et al. (2011) Cid Fernandes, R., Stasińska, G., Mateus, A., & Vale Asari, N. 2011, MNRAS, 413, 1687, doi: 10.1111/j.1365-2966.2011.18244.x
  * Cisternas et al. (2013) Cisternas, M., Jahnke, K., & Cosmos Collaboration. 2013, in Astronomical Society of the Pacific Conference Series, Vol. 477, Galaxy Mergers in an Evolving Universe, ed. W. H. Sun, C. K. Xu, N. Z. Scoville, & D. B. Sanders, 173
  * Cisternas et al. (2011) Cisternas, M., Jahnke, K., Inskip, K. J., et al. 2011, ApJ, 726, 57, doi: 10.1088/0004-637X/726/2/57
  * Conselice (2006) Conselice, C. J. 2006, ApJ, 638, 686, doi: 10.1086/499067
  * Constantin et al. (2009) Constantin, A., Green, P., Aldcroft, T., et al. 2009, ApJ, 705, 1336, doi: 10.1088/0004-637X/705/2/1336
  * Cotini et al. (2013) Cotini, S., Ripamonti, E., Caccianiga, A., et al. 2013, MNRAS, 431, 2661, doi: 10.1093/mnras/stt358
  * Croton et al. (2006) Croton, D. J., Springel, V., White, S. D. M., et al. 2006, MNRAS, 365, 11, doi: 10.1111/j.1365-2966.2005.09675.x
  * Cutri & et al. (2014) Cutri, R. M., & et al. 2014, VizieR Online Data Catalog, II/328
  * Davies et al. (2017) Davies, R. L., Groves, B., Kewley, L. J., et al. 2017, MNRAS, 470, 4974, doi: 10.1093/mnras/stx1559
  * Dietrich et al. (2018) Dietrich, J., Weiner, A. S., Ashby, M. L. N., et al. 2018, MNRAS, 480, 3562, doi: 10.1093/mnras/sty2056
  * Dopita & Sutherland (1996) Dopita, M. A., & Sutherland, R. S. 1996, ApJS, 102, 161, doi: 10.1086/192255
  * Ellison et al. (2013) Ellison, S. L., Mendel, J. T., Patton, D. R., & Scudder, J. M. 2013, MNRAS, 435, 3627, doi: 10.1093/mnras/stt1562
  * Ellison et al. (2011) Ellison, S. L., Patton, D. R., Mendel, J. T., & Scudder, J. M. 2011, MNRAS, 418, 2043, doi: 10.1111/j.1365-2966.2011.19624.x
  * Ellison et al. (2019) Ellison, S. L., Viswanathan, A., Patton, D. R., et al. 2019, MNRAS, 487, 2491, doi: 10.1093/mnras/stz1431
  * Evans et al. (2010) Evans, I. N., Primini, F. A., Glotfelty, K. J., et al. 2010, ApJS, 189, 37, doi: 10.1088/0067-0049/189/1/37
  * Fabbiano (1989) Fabbiano, G. 1989, ARA&A, 27, 87, doi: 10.1146/annurev.aa.27.090189.000511
  * Fabbiano (2006) —. 2006, ARA&A, 44, 323, doi: 10.1146/annurev.astro.44.051905.092519
  * Gabor et al. (2009) Gabor, J. M., Impey, C. D., Jahnke, K., et al. 2009, ApJ, 691, 705, doi: 10.1088/0004-637X/691/1/705
  * Gao et al. (2020) Gao, F., Wang, L., Pearson, W. J., et al. 2020, A&A, 637, A94, doi: 10.1051/0004-6361/201937178
  * Gebhardt et al. (2000) Gebhardt, K., Bender, R., Bower, G., et al. 2000, ApJ, 539, L13, doi: 10.1086/312840
  * Gehrels (1986) Gehrels, N. 1986, ApJ, 303, 336, doi: 10.1086/164079
  * Glikman et al. (2015) Glikman, E., Simmons, B., Mailly, M., et al. 2015, ApJ, 806, 218, doi: 10.1088/0004-637X/806/2/218
  * Goulding et al. (2018) Goulding, A. D., Greene, J. E., Bezanson, R., et al. 2018, PASJ, 70, S37, doi: 10.1093/pasj/psx135
  * Grogin et al. (2005) Grogin, N. A., Conselice, C. J., Chatzichristou, E., et al. 2005, ApJ, 627, L97, doi: 10.1086/432256
  * Harrison et al. (2013) Harrison, F. A., Craig, W. W., Christensen, F. E., et al. 2013, ApJ, 770, 103, doi: 10.1088/0004-637X/770/2/103
  * HI4PI Collaboration et al. (2016) HI4PI Collaboration, Ben Bekhti, N., Flöer, L., et al. 2016, A&A, 594, A116, doi: 10.1051/0004-6361/201629178
  * Hickox et al. (2009) Hickox, R. C., Jones, C., Forman, W. R., et al. 2009, ApJ, 696, 891, doi: 10.1088/0004-637X/696/1/891
  * Hong et al. (2015) Hong, J., Im, M., Kim, M., & Ho, L. C. 2015, ApJ, 804, 34, doi: 10.1088/0004-637X/804/1/34
  * Hopkins & Hernquist (2009) Hopkins, P. F., & Hernquist, L. 2009, ApJ, 698, 1550, doi: 10.1088/0004-637X/698/2/1550
  * Hopkins et al. (2005) Hopkins, P. F., Hernquist, L., Cox, T. J., et al. 2005, ApJ, 630, 705, doi: 10.1086/432438
  * Hopkins et al. (2008) Hopkins, P. F., Hernquist, L., Cox, T. J., & Kereš, D. 2008, ApJS, 175, 356, doi: 10.1086/524362
  * Ishibashi & Courvoisier (2010) Ishibashi, W., & Courvoisier, T. J. L. 2010, A&A, 512, A58, doi: 10.1051/0004-6361/200913587
  * Ji et al. (2014) Ji, I., Peirani, S., & Yi, S. K. 2014, A&A, 566, A97, doi: 10.1051/0004-6361/201423530
  * Kauffmann et al. (2008) Kauffmann, G., Heckman, T. M., & Best, P. N. 2008, MNRAS, 384, 953, doi: 10.1111/j.1365-2966.2007.12752.x
  * Kauffmann et al. (2003a) Kauffmann, G., Heckman, T. M., White, S. D. M., et al. 2003a, MNRAS, 341, 33, doi: 10.1046/j.1365-8711.2003.06291.x
  * Kauffmann et al. (2003b) Kauffmann, G., Heckman, T. M., Tremonti, C., et al. 2003b, MNRAS, 346, 1055, doi: 10.1111/j.1365-2966.2003.07154.x
  * Keel et al. (1985) Keel, W. C., Kennicutt, R. C., J., Hummel, E., & van der Hulst, J. M. 1985, AJ, 90, 708, doi: 10.1086/113779
  * Kewley et al. (2001) Kewley, L. J., Dopita, M. A., Sutherland, R. S., Heisler, C. A., & Trevena, J. 2001, ApJ, 556, 121, doi: 10.1086/321545
  * Kewley et al. (2006) Kewley, L. J., Groves, B., Kauffmann, G., & Heckman, T. 2006, MNRAS, 372, 961, doi: 10.1111/j.1365-2966.2006.10859.x
  * Kim et al. (2020) Kim, M., Choi, Y.-Y., & Kim, S. S. 2020, MNRAS, 491, 4045, doi: 10.1093/mnras/stz3158
  * Kocevski et al. (2012) Kocevski, D. D., Faber, S. M., Mozena, M., et al. 2012, ApJ, 744, 148, doi: 10.1088/0004-637X/744/2/148
  * Kormendy & Ho (2013) Kormendy, J., & Ho, L. C. 2013, ARA&A, 51, 511, doi: 10.1146/annurev-astro-082708-101811
  * Koss et al. (2012) Koss, M., Mushotzky, R., Treister, E., et al. 2012, ApJ, 746, L22, doi: 10.1088/2041-8205/746/2/L22
  * Koss et al. (2010) Koss, M., Mushotzky, R., Veilleux, S., & Winter, L. 2010, ApJ, 716, L125, doi: 10.1088/2041-8205/716/2/L125
  * Lackner et al. (2014) Lackner, C. N., Silverman, J. D., Salvato, M., et al. 2014, AJ, 148, 137, doi: 10.1088/0004-6256/148/6/137
  * Lehmer et al. (2010) Lehmer, B. D., Alexander, D. M., Bauer, F. E., et al. 2010, ApJ, 724, 559, doi: 10.1088/0004-637X/724/1/559
  * Letawe et al. (2010) Letawe, Y., Letawe, G., & Magain, P. 2010, MNRAS, 403, 2088, doi: 10.1111/j.1365-2966.2010.16244.x
  * Lotz et al. (2008) Lotz, J. M., Jonsson, P., Cox, T. J., & Primack, J. R. 2008, MNRAS, 391, 1137, doi: 10.1111/j.1365-2966.2008.14004.x
  * Magliocchetti (2022) Magliocchetti, M. 2022, A&A Rev., 30, 6, doi: 10.1007/s00159-022-00142-1
  * Marian et al. (2019) Marian, V., Jahnke, K., Mechtley, M., et al. 2019, ApJ, 882, 141, doi: 10.3847/1538-4357/ab385b
  * Martini (2004) Martini, P. 2004, in Coevolution of Black Holes and Galaxies, ed. L. C. Ho, 169\.  https://arxiv.org/abs/astro-ph/0304009
  * Mateos et al. (2013) Mateos, S., Alonso-Herrero, A., Carrera, F. J., et al. 2013, MNRAS, 434, 941, doi: 10.1093/mnras/stt953
  * McAlpine et al. (2020) McAlpine, S., Harrison, C. M., Rosario, D. J., et al. 2020, MNRAS, 494, 5713, doi: 10.1093/mnras/staa1123
  * McConnell et al. (2012) McConnell, N. J., Ma, C.-P., Murphy, J. D., et al. 2012, ApJ, 756, 179, doi: 10.1088/0004-637X/756/2/179
  * Mineo et al. (2012) Mineo, S., Gilfanov, M., & Sunyaev, R. 2012, MNRAS, 426, 1870, doi: 10.1111/j.1365-2966.2012.21831.x
  * Nair & Abraham (2010) Nair, P. B., & Abraham, R. G. 2010, ApJS, 186, 427, doi: 10.1088/0067-0049/186/2/427
  * Pillepich et al. (2019) Pillepich, A., Nelson, D., Springel, V., et al. 2019, MNRAS, 490, 3196, doi: 10.1093/mnras/stz2338
  * Rovilos et al. (2014) Rovilos, E., Georgantopoulos, I., Akylas, A., et al. 2014, MNRAS, 438, 494, doi: 10.1093/mnras/stt2228
  * Satyapal et al. (2014) Satyapal, S., Ellison, S. L., McAlpine, W., et al. 2014, MNRAS, 441, 1297, doi: 10.1093/mnras/stu650
  * Schawinski et al. (2007) Schawinski, K., Thomas, D., Sarzi, M., et al. 2007, MNRAS, 382, 1415, doi: 10.1111/j.1365-2966.2007.12487.x
  * Schaye et al. (2015) Schaye, J., Crain, R. A., Bower, R. G., et al. 2015, MNRAS, 446, 521, doi: 10.1093/mnras/stu2058
  * Secrest et al. (2020) Secrest, N. J., Ellison, S. L., Satyapal, S., & Blecha, L. 2020, MNRAS, 499, 2380, doi: 10.1093/mnras/staa1692
  * Shah et al. (2020) Shah, E. A., Kartaltepe, J. S., Magagnoli, C. T., et al. 2020, ApJ, 904, 107, doi: 10.3847/1538-4357/abbf59
  * Silverman et al. (2011) Silverman, J. D., Kampczyk, P., Jahnke, K., et al. 2011, ApJ, 743, 2, doi: 10.1088/0004-637X/743/1/2
  * Singh et al. (2013) Singh, R., van de Ven, G., Jahnke, K., et al. 2013, A&A, 558, A43, doi: 10.1051/0004-6361/201322062
  * Somerville et al. (2008) Somerville, R. S., Hopkins, P. F., Cox, T. J., Robertson, B. E., & Hernquist, L. 2008, MNRAS, 391, 481, doi: 10.1111/j.1365-2966.2008.13805.x
  * Springel et al. (2005) Springel, V., Di Matteo, T., & Hernquist, L. 2005, ApJ, 620, L79, doi: 10.1086/428772
  * Stasinska et al. (2006) Stasinska, G., Cid Fernandes, R., Mateus, A., Sodre, Laerte, J., & Asari, N. V. 2006, Mon. Not. Roy. Astron. Soc., 371, 972, doi: 10.1111/j.1365-2966.2006.10732.x
  * Steinborn et al. (2018) Steinborn, L. K., Hirschmann, M., Dolag, K., et al. 2018, MNRAS, 481, 341, doi: 10.1093/mnras/sty2288
  * Treister et al. (2012) Treister, E., Schawinski, K., Urry, C. M., & Simmons, B. D. 2012, ApJ, 758, L39, doi: 10.1088/2041-8205/758/2/L39
  * Tremonti et al. (2004) Tremonti, C. A., Heckman, T. M., Kauffmann, G., et al. 2004, ApJ, 613, 898, doi: 10.1086/423264
  * Urrutia et al. (2008) Urrutia, T., Lacy, M., & Becker, R. H. 2008, ApJ, 674, 80, doi: 10.1086/523959
  * Villforth et al. (2014) Villforth, C., Hamann, F., Rosario, D. J., et al. 2014, MNRAS, 439, 3342, doi: 10.1093/mnras/stu173
  * Webb et al. (2020) Webb, N. A., Coriat, M., Traulsen, I., et al. 2020, A&A, 641, A136, doi: 10.1051/0004-6361/201937353
  * Weigel et al. (2018) Weigel, A. K., Schawinski, K., Treister, E., Trakhtenbrot, B., & Sanders, D. B. 2018, MNRAS, 476, 2308, doi: 10.1093/mnras/sty383
  * Weston et al. (2017) Weston, M. E., McIntosh, D. H., Brodwin, M., et al. 2017, MNRAS, 464, 3882, doi: 10.1093/mnras/stw2620
  * Woods & Geller (2007) Woods, D. F., & Geller, M. J. 2007, AJ, 134, 527, doi: 10.1086/519381
  * 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
  * Yan et al. (2013) Yan, L., Donoso, E., Tsai, C.-W., et al. 2013, AJ, 145, 55, doi: 10.1088/0004-6256/145/3/55
  * Yan & Blanton (2012) Yan, R., & Blanton, M. R. 2012, ApJ, 747, 61, doi: 10.1088/0004-637X/747/1/61
  * York et al. (2000) York, D. G., Adelman, J., Anderson, John E., J., et al. 2000, AJ, 120, 1579, doi: 10.1086/301513