# X-ray Emission of Ultraviolet Variable Active Galactic Nuclei Candidates

Erik J. Wasleske Department of Physics and Astronomy, Washington State
University, Pullman, WA 99163, USA  Vivienne F. Baldassare Department of
Physics and Astronomy, Washington State University, Pullman, WA 99163, USA

###### Abstract

We analyze the X-ray properties for a sample of 23 high probability AGN
candidates with ultraviolet variability identified in Wasleske et al. (2022).
Using data from the Chandra X-ray Observatory and the XMM-Newton Observatory,
we find 11/23 nuclei are X-ray detected. We use SED modeling to compute star
formation rates and show that the X-ray luminosities are typically in excess
of the X-ray emission expected from star formation by at least an order of
magnitude. Interestingly, this sample shows a diversity of optical
spectroscopic properties. We explore possible reasons for why some objects
lack optical spectroscopic signatures of black hole activity while still being
UV variable and X-ray bright. We find that host galaxy stellar emission and
obscuration from gas and dust are all potential factors. We study where this
sample falls on relationships such as $\alpha_{\rm OX}-L_{2500}$ and
$L_{X}-L_{IR}$ and find that some of the sample falls outside the typical
scatter for these relations, indicating they differ from the standard quasar
population. With the diversity of optical spectroscopic signatures and varying
impacts of dust and stellar emissions on our sample, these results emphasizes
the strength of variability in selecting the most complete set of AGN,
regardless of other host galaxy properties.

##  1 Introduction

It has been well established that black holes are ubiquitous in the centers of
massive galaxies (Magorrian et al., 1998). Studies in the growth and evolution
of supermassive black holes (SMBHs) have lead to open questions about the
occupation and active fractions of black holes (BHs). A complete census of
active galactic nuclei (AGN) is important for constraining the occupation
fraction and for studying BH growth throughout time. However, this is
difficult to obtain due to selection biases in each wavelength regime across
the electromagnetic spectrum, as well as observational limitations. Gas, dust,
star formation, and host galaxy dilution each have varying effects on masking
the activity of the central black hole. This paper is focused on the power of
variability selection of AGN for taking a complete AGN census.

The effects of obscuration can be seen across the spectrum of AGN radiation.
Absorbing dust emits in the infrared, and can mask ultraviolet to infrared
emission while, alongside gas, attenuating X-rays (Hickox & Alexander, 2018).
The lack of luminous X-ray emission in active galaxies that were bright at
other wavelengths, such as the infrared, has been shown to be an indicator of
heavy obscuration (Donley et al., 2012; Stern, 2015; Lambrides et al., 2020;
Carroll et al., 2021).

The infrared regime has been explored using photometry in bands spanning 1 -
1000 $\mu$m. Galaxy dust, star formation, and AGN can all dominate the
infrared regime. This dust can be heated by either AGN radiation or by star
formation, making it difficult differentiate between the two mechanisms by the
galaxies’ infrared colors (Landt et al., 2008; Kirkpatrick et al., 2015;
Hainline et al., 2016). Pfeifle et al. (2022) derived expressions to relate
column density to infrared line ratios. They find that obscured AGN have
redder mid-infrared colors than unobscured systems. Additionally, they found a
deficiency of X-ray emission and redder colors for those objects whose host
galaxies dominate the 12$\mu$m emission.

Optical spectroscopic studies have been done to collect large population of
active galaxies within the local universe (Ho et al., 1997; Reines et al.,
2013). These selection techniques use line ratios and broad emission
thresholds. The broad line emission can be obscured by torus. Studies have
show that the majority of AGN lack broad line emission, ie. are type II AGN
(Villarroel & Korn, 2014). The narrow line emission can be effected by
dilution from star formation within the host galaxy.

These issues are ever so prominent in identifying active dwarf galaxies
($M_{*}<1\times 10^{10}M_{\odot}$) whose broad emission lines are fainter and
less broad can often be confused with the signatures of supernovae
(Filippenko, 1997; Pritchard et al., 2012; Baldassare et al., 2016). Active
low-mass galaxies serve as observation tools to constrain the seeding
mechanisms of these BH in the early universe (Volonteri et al., 2008;
Volonteri, 2010; Natarajan, 2014). Populations of active dwarf galaxies have
been established using spectroscopic broad and narrow lines (Greene & Ho,
2004; Dong et al., 2012; Reines et al., 2013; Moran et al., 2014; Molina et
al., 2021), variability (Baldassare et al., 2018, 2020), X-ray (Greene & Ho,
2007; Desroches et al., 2009; Lemons et al., 2015; Plotkin et al., 2016) and
radio emission (Reines et al., 2020). These multi-wavelength views of active
galaxies enables the study of different components of the AGN, but each
wavelength regime comes with its own issues and biases. Between decoupling
other astrophysical processes from black hole activity (ie. star-formation,
illuminated gas and dust) and other technical limitations there is a
significant barrier to collecting a complete and accurate sample of AGN.
Volume limits create a specific redshift range we can search for active
galaxies, with more luminous, less elusive quasars being the only type we are
able to systematically search for at the deepest redshifts.

Though X-rays are not immune from obscuration effects, X-ray observations have
been well utilized to identify and study the properties of active galaxies
(ie. see Brandt & Hasinger (2005) and references therein). Sufficiently bright
X-ray emission is often used to confirm the presence of AGN in systems lacking
other AGN indicators (e.g., Birchall et al. 2020; Agostino et al. 2022;
Messick et al. 2023 (submitted)).

Agostino et al. (2022) studied local type 2 AGN selected by X-ray emission who
lacked apparent optical emission lines. Even with 25% of their sample spectra
was absorption-line dominated, they found measurable [O III] emission in their
total sample. [O III] emits far from the torus of the AGN and can serve as an
indicator of AGN power. They found a correlation with the specific star
formation rate (SFR) and the [O III] luminosity of these X-ray AGN. Agostino
et al. (2022) claims that less-luminous [O III] galaxies contribute to the
scatter of their [O III] to x-ray luminosity relation. This scatter is
proposed to be from gas content differences of the narrow line region. They
are distinguished only by existing at the low-luminous
($\text{log}\>L_{X}<42$) end of the broad X-ray to [O III] uni-modal relation.
This separation of less-luminous to luminous [O III] emitters is due to the
specific star-formation rate. The amount of available molecular gas within the
host galaxies drives certain processes, as star-formation is dependent on gas,
with the photoionization of this gas from the AGN creating its spectroscopic
signatures.

Lambrides et al. (2020) also investigated this broad X-ray to [O III]
relationship for a population of obscured AGN, finding that the type 2 AGN are
below the relation of Yan et al. (2011) set for unambiguous AGN. These objects
have low observed X-ray emission per their amount of [O III] emission due not
from any intrinsic factors, but from heavy obscuration. Comparison of AGN
candidates with varying spectroscopic classes can make indications on the
molecular gas contained in the host galaxy.

Correlations of the X-ray to the mid-infrared (MIR) show a near linear
relation for nearby AGN with low-luminosities, whose dispersions are
attributed to the geometry of the dust, star-formation and variability of the
AGN (Lutz et al., 2004; Gandhi et al., 2009). This relationship has been use
to convert between X-ray and MIR luminosities regardless of the nature of the
AGN, as both uncontaminated MIR and X-ray emission are a proxy for the AGN’s
intrinsic power (Asmus et al., 2015).

Wasleske et al. (2022) identified 48 AGN candidates by their high variability
in the near ultraviolet (NUV) band. They selected these candidates from 2000
galaxies from the NASA Sloan Atlas that lay within the sky covered by the
GALEX Time-Domain Survey (Gezari et al., 2013). The 48 AGN candidates had a
variety of optical spectroscopic properties, with some lacking optical
spectroscopic AGN signatures entirely. In this paper, we search for nuclear
X-ray emission from these UV-variable sources to search for additional
evidence of the presence of AGN. Furthermore, we compare their X-ray
luminosities to various empirical relations to search for differences between
spectral classes. This analysis is compared to that analysis work of Wasleske
et al. (2022), which used optical spectroscopy, mid-infrared colors, and low-
resolution spectral energy distributions. In the analysis of the optical
spectra of these variable galaxies, Wasleske et al. (2022) found examples of
their variable population having signatures of AGN, star formation,
composites, and even absorption-line dominated systems.

This study compares the variable AGN population to known X-ray relations of
AGN emission to investigate the underlying physics of their emission
signatures. Our goal is to measure X-ray emission from variable AGN candidates
and use the multi-wavelength galaxy properties to determine whether dust,
obscuration, and star-formation impact the optical spectral signatures.

This work is structured as follows: In Section 2, we discuss our sample and
the data available in the Chandra X-ray Observatory (CXO) and XMM-Newton (XMM)
archives. In Section 3, we discuss the data reduction and the construction of
spectral energy distribution (SED) models. In Section 4, we report our results
from the X-ray emission and SED modeling. In Section 5, we discuss the
implications of these results in relationship to literary observational
relations, associating optical, IR, and X-ray.

##  2 Data

###  2.1 Sample Selection

Our sample is comprised of all objects from Wasleske et al. (2022) that had
available X-ray data within the CXO or XMM archives. Wasleske et al. (2022)
identified 48 high-probability AGN candidates from their near-ultraviolet
variability in the GALEX Time-Domain Survey (TDS; Gezari et al. 2013). The
parent population for this variability study was taken from the NASA Sloan
Atlas (NSA), which combines imaging products from SDSS and GALEX to construct
a catalog of roughly 641,500 galaxies with redshifts and other derived
quantities (Blanton & Moustakas, 2009; Maller et al., 2009; Zhu et al., 2010).
There were $\sim 2,000$ galaxies in the region covered by GALEX TDS which were
analyzed for their NUV variability. The 48 high-probability candidates were
selected for significant variability in their light curve over the 3 year
baseline of the TDS. The pointing of the TDS covered six of the Pan-STARRS1
Medium Deep Survey fields, four of which are in the northern sky. The NUV
filter covers a range from 1750-2800Å.

Of the 48 AGN candidates, 23 unique objects had coverage with either CXO or
XMM Archive. The description of these data products is given below.

###  2.2 Chandra X-ray Observatory

We searched for 48 AGN candidates from Wasleske et al. (2022) in the CXO
Archive. To establish whether objects were observed with Chandra, we searched
for each object in the Chandra Archive with the default search radius of 10
arc-minutes. We then examined each observation to determine whether the object
was contained within the field. We found a total of 13 objects covered by
Chandra ACIS observations, with some objects having repeat observations.
Reduction of these observation products is described in 3.1. NSA 64129 is the
only galaxy that was not analyzed. It is 9.07 arc-minutes from the nearest
observation’s center, and inspection of that observation’s image shows that
the galaxy straddles the edge of the CCD, thus we removed it from the CXO
sample. NSA 64129 however lays within the XMM source catalog, as discussed in
Section 2.3. Cross-check of the Chandra Source Catalog, CSC 2.0, (Evans et
al., 2020) was done to ensure that the appropriate data products were
collected from the archive for the remaining 12 objects.

Our sample of 12 objects having CXO observations have an array of optical
spectroscopic signatures that were analyzed in Wasleske et al. (2022). From
the BPT diagram (Baldwin et al., 1981), two objects are classified as AGN, one
as starburst, one as a Composite galaxy. Three of the objects are dominated by
absorption features while the rest either have no available SDSS spectrum or
spectrum too noisy to preform the fitting routine.

###  2.3 XMM-Newton Observatory

We searched the XMM-Newton Serendipitous source catalog (Webb, N. A. et al.,
2020) for matches to our 48 AGN candidates from Wasleske et al. (2022). Beyond
collected detections, we searched for upper limits of the remaining galaxies
within XMM’s coverage.

The 4XMM-DR9 catalog is based off a set of 11,204 EPIC observations that
contain a detection, spanning 19 years. Data processing for this catalog was
based on Science Analysis Software (SAS) version 18 to produce calibrated
event lists for each observation. The process of converting the raw
observation data event files from the EPIC instruments into event lists by the
pipeline is the same as described in Watson et al. (2009). The 4XMM-DR9
updates to the 2XMM (Watson et al., 2009) and 3XMM (Rosen et al., 2016)
catalogs are the inclusion of source spectra, light curves, source detection,
and event corrections using Timing mode and pn small window data. This catalog
contains 550,000 unique sources, building upon earlier iterations with an
improved source detection and provides an ideal easy access to data products
from the XMM Newton archive. Webb, N. A. et al. (2020) discusses the
properties of the catalog, finding a Gaussian distribution of fluxes for all
sources detected. The minimum flux value for the 0.2 - 12 keV broadband is
$1.44\times 10^{-19}$erg/cm2/s, for source 4XMM J174538.0-285950.

This catalog contains fluxes in 9 X-ray bands for each object that span
different pieces of $0.2-12\rm{keV}$ energy range. Analysis of the selected
sources is described in Section 3.2. Of the 48 variable AGN candidates, seven
were found in the source catalog. Selection and analysis of these sources is
discussed in Section 3.2.

Using the FLIX server111http://flix.irap.omp.eu/, we compute X-ray upper
limits for an additional 14 of the AGN candidates from Wasleske et al. (2022),
given in Table 1. These 14 objects were within fields observed by XMM, but the
separation between the nearest detected source within the catalog to each of
these candidates was within the range of 50 - 207 arcsec. Seven of these
objects were also found in the CXO Archive. We compute upper limits using the
pn band 8 (0.2 -12.0 keV) flux from the observation with the minimum Axis
Offset value for each of these 14 candidates.

###  2.4 Ancillary Data

Photometry was collected from surveys across the electromagnetic spectrum to
be used for input values of the SED models. Along with the photometric X-ray
values pulled from our analysis, we use the median GALEX photometric values
from Wasleske et al. (2022) for each variable galaxy, data from SDSS DR16
(Ahumada et al., 2020), the United Kingdom Infrared Telescope (UKIRT; Lawrence
et al. (2007)), Wide-field Infrared Survey Explorer (WISE; Wright et al.
(2010)), unblurred and unofficial coadds of the WISE imaging (unWISE; Lang
(2014)), and the Two Micron All-Sky Survey (2MASS; Skrutskie et al. (2006)).

The compilation of these values serve as the input of the SED analysis using
X-CIGALE V2022.0 (Yang et al., 2022), discussed in Section 3.3.

X-ray Sample
NSA ID z $\log(\text{M}_{*}/\text{M}_{\odot})$ BPT Class CXO XMM Counts
$n_{H}$ $L_{0.5-7.0\rm{keV}}$ $n_{H}$ $L_{0.5-7.0\rm{keV}}$
[$10^{22}\text{cm}^{-2}$] [erg/s] [$10^{22}\text{cm}^{-2}$] [erg/s] 28616
0.0991 10.89 AGN – – – $0.106$ $2.8^{+0.1}_{-0.09}\times 10^{43}$ 28810 0.1394
11.24 None $\leq 15\pm 4$ – $<8.6\times 10^{41}$ – $<7.7\times 10^{41}$ 64129
0.0783 10.53 AGN – – – $0.096$ $5.0^{+0.5}_{-0.5}\times 10^{41}$ 64145 0.1030
10.59 Absorption $1397\pm 37$ $2.230$ $(3.6\pm 0.7)\times 10^{42}$ $0.045$
$(1.2\pm 0.3)\times 10^{42}$ 64258 0.1084 10.74 Starburst $\leq 8\pm 2$ –
$<7.3\times 10^{39}$ – $<2.1\times 10^{41}$ 64266 0.0805 10.68 None $\leq
12\pm 4$ – $<6.5\times 10^{39}$ – $<1.5\times 10^{41}$ 64272 0.1329 10.89 AGN
$554\pm 24$ – $(4.6\pm 0.3)\times 10^{42}$ $0.107$ $(9.7\pm 0.2)\times
10^{42}$ 64286 0.0234 10.67 AGN $97\pm 10$ $1.667$ $2.7^{+3.4}_{-0.7}\times
10^{41}$ $0.036$ $(5.3\pm 0.2)\times 10^{41}$ 205160 0.1396 10.52 None – – – –
$<1.3\times 10^{42}$ 208465 0.0765 11.61 Absorption – – – $0.055$ $(2.4\pm
0.03)\times 10^{43}$ 208625 0.0732 10.85 Absorption $503\pm 22$ –
$1.4^{+0.6}_{-0.7}\times 10^{42}$ – $<1.4\times 10^{41}$ 208662 0.1122 10.98
Composite $455\pm 21$ $2.49$ $8.4^{+10.1}_{-7.0}\times 10^{40}$ – $<1.2\times
10^{42}$ 208702 0.0448 9.61 Composite – – – – $<9.9\times 10^{40}$ 259478
0.0784 10.84 Composite – – – – $<1.7\times 10^{41}$ 259789 0.1063 10.76 None
$10038\pm 100$ $0.292$ $4.9^{+3.1}_{-2.5}\times 10^{40}$ – – 259880 0.0762
10.65 Absorption – – – – $<1.3\times 10^{41}$ 259895 0.0834 10.11 AGN – – –
$0.226$ $(2.4\pm 0.2)\times 10^{42}$ 259919 0.0781 10.52 Absorption – – – –
$<1.2\times 10^{41}$ 260221 0.0742 10.73 Absorption – – – – $<2.1\times
10^{41}$ 260241 0.0743 10.51 None – – – – $<1.5\times 10^{41}$ 613397 0.1274
11.54 Absorption $\leq 9\pm 3$ – $<3.3\times 10^{41}$ – – 631480 0.0442 7.74
None $\leq 5\pm 3$ – $<9.8\times 10^{38}$ – $<3.6\times 10^{40}$ 631492 0.0119
6.89 None $25\pm 5$ – $7.8^{+10.8}_{-6.7}\times 10^{37}$ – $<8.0\times
10^{39}$

Table 1:  Our sample from Wasleske et al. (2022) of UV variable AGN candidates
found in X-ray surveys. Counts for CXO detections are calculated by their
$0.5-7.0\rm{keV}$ count rate multiplied by the exposure time, with Poissonian
errors given. Their BPT classifications are given as “BPT Class”, with some
spectrum dominated by absorption lines. Those galaxies with a BPT Class of
’None’ do not have available spectra that can be properly fitted and analyzed.
Intrinsic absorption $n_{H}$ values given for detections in CXO and XMM, based
on the methods described in Section 3.1 and 3.2.

##  3 Analysis

We present an examination of the reduction and compilation of X-ray data to
measure broadband photometric luminosities. We also discuss the process and
the choices made for the SED modeling.

###  3.1 CIAO Reduction

The Chandra Interactive Analysis of Observations (CIAO, version 4.14 222see
https://cxc.cfa.harvard.edu/ciao/ for user guides of this software package)
data reduction software was used to reduce and analyze the observations. For
each observation file, we first reprocessed the observation files using the
chandra_repro script to apply the latest calibrations, which creates a new
level 2 event file and a bad pixel file from the background cleaning of the
original event file. Preliminary sources within the level 2 event file are
then identified using CIAO WAVDETECT function. WAVDETECT does this through
correlating potential pixel sources to Ricker wavelet functions, removing
highly correlated values as assumed sources. After this is completed, we
filter the event file to the 0.5-10.0 keV range.

We used CIAO’s SRCFLUX software to carry out the aperture photometry. SRCFLUX
is a software that calculates net count rates and fluxes with uncertainties
while accounting for contributions of the point spread function to both source
and background apertures. We use a $2.0"$ source aperture in unison with a
source-less background annulus of size $20.00"$ for its inner and $30.00"$ for
its outer radius. Our source aperture is set by the spatial resolution of the
CXO.

The spectral model we used within the SRCFLUX333SRCFLUX references its models
from Xspec, see https://heasarc.gsfc.nasa.gov/xanadu/xspec/manual for user
manual function for all CXO objects is xsphabs.abs1 * xspowerlaw.pow1 where
xspowerlaw is a simple photon power law where we defined its index as
$\Gamma=1.8$. This model accounts only for galactic absorption, not the host
galaxy of each for these sources. We set the absorption parameter to
abs1.nH=%GAL% so that National Radio Astronomy Observatory values for galactic
column density $n_{H}$ are collected.

Assuming this absorbed power law spectrum we then collect count and flux
estimates for broad (0.5 - 7.0 keV), soft (0.5 - 1.2), medium (1.2 - 2.0 keV),
and custom 2.0 - 10.0 keV bands. Once these estimated values are collected, we
follow the method of Baldassare et al. (2017) to measure the intrinsic
absorption. Using the Portable Interactive Multi-Mission Simulator (PIMMS)
toolkit444https://heasarc.gsfc.nasa.gov/docs/software/tools/pimms.html, we
started with our custom 2.0 - 10.0 keV band’s count rate to calculate the
expected count rate for the 0.5 - 2.0 keV band, assuming a photon index of
$\Gamma=1.8$. If this expected value was higher than the observed rate from
the CIAO reduction, an intrinsic $n_{H}$ was calculated. This was the case for
four of the objects detected in CXO, with the intrinsic $n_{H}$ value given in
Table 1.

From these fluxes, we calculate the luminosities using the distances given in
the NSA.

The bottom panel of Figure 6 shows the source and background apertures over
each event file used in the data reduction. For NSA 64286, as the object was
collected near the edge of the ACIS chip, the background annulus apertures was
centered at RA = 150.500°, DEC = 3.077°, 2.1’ away from the objects position
and the source aperture. Analogous optical Legacy Imaging cutouts are given in
the top panel of Figure 6.

Figure 1: _Top:_ Legacy Survey images of the galaxies from our sample with
X-ray detections in either CXO and XMM. _Bottom:_ X-ray images for each galaxy
with an X-ray detection. The teal scale-bar is 20” on each panel. For objects
detected with XMM (i.e. NSA 28616, 64129, 208465, and 259895), the XMM EPIC-
RGB cutout is shown 666collected from http://xmm-catalog.irap.omp.eu/. For
objects with detected in CXO, the circular source aperture and annulus
background aperture from the CIAO data reduction are given in green. For those
detected in both CXO and XMM, the CXO image is displayed.

###  3.2 XMM Source catalog objects

Sources from the XMM-Newton Serendipitous Source catalog were cross matched to
the AGN candidates via closest 2-D sky separation. This list was then filtered
down to more probable comparison if the sources were within a 10” radius of
the objects position. This separation threshold filtered the list down to
seven probable sources, three of which overlap with our CXO sample. Figure 2
shows the positions of the source compared to the position given in the NSA
catalog. The 6” resolution of XMM instrument is given by the black circles on
each panel of Figure 2. This demonstrates the accuracy of the 2-D position
cross matching used to select these sources. We collect the
$0.2-12~{}\rm{keV}$ fluxes for these seven sources.

Once these sources were identified, we used the Spectrum Fitting tool777 see
’Fit Spectrum’ option of http://xmm-catalog.irap.omp.eu/ for Source and
respective Detection IDs. for these source to fit the broadband 0.2-12.0 keV
spectrum. This fitting gave a total absorption estimate for the spectrum.
Since we know the Galactic absorption for each position, we can then compute
intrinsic absorption of each object. These values are given for the XMM source
detections in Table 1.

The $0.5-7.0~{}\rm{keV}$ broadband luminosity for these X-ray analogous
sources and the FLIX upper limits are given in Table 1. The PIMMS toolkit was
used to convert the broadband luminosity $0.2-12~{}\rm{keV}$ to the broad
$0.5-7.0~{}\rm{keV}$ CXO band for ease of comparison.

Figure 2: X-ray source and object positions for sources found in the XMM-
Newton catalog. Faint red circles show the object position, while the blue ”X”
represents the X-ray source position. The solid black circle represents the 6”
FWHM point-spread function of XMM. The 10” threshold circle is given in dashed
grey.

###  3.3 Spectral Energy Distribution Modeling

Using X-CIGALE V2022.0 (Yang et al., 2022), we fit spectral energy
distribution (SED) models to estimate emission mechanisms for all 23 objects.
The photometric values, including those for the GALEX NUV band, are equivalent
to those used in the Wasleske et al. (2022) SED decomposition, with the
addition of the X-ray values collected above. X-ray boxcars for the ranges of
$0.5-7.0\rm{keV}$ and $0.2-12.0\rm{keV}$ were used for CXO and XMM sources
respectively. We followed the SED-fitting methodology of Burke et al. (2021)
to set the specific models and parameter ranges for our SED models. Burke et
al. (2021) SED analysis focused on modeling galaxies whose SEDs were not
dominated by the central AGN, which is well-aligned with the sample and
science goals presented here. We detail this work below.

To model the AGN emission, we use the SKIRTOR (Stalevski et al., 2012, 2016)
model, for its two-phase clumpy model of the radiative transfer of the AGN’s
dusty torus. We let the AGN fraction vary from 0.0 to 0.9, and the polar
extinction $E(B-V)$ maximum value be $0.175$. Viewing angle was let to vary
between 10°and 60°.

The star formation history was done using a delayed exponential model. This
model used parameters of e-folding times ranging from 100 - 5000 Myr and age
of main stellar population of 1000, 2000, or 5000 Myr. We used the initial
stellar mass function from Chabrier (2003), the stellar population models of
Bruzual & Charlot (2003), and nebular emission model of Inoue (2011). Dust
emission was modeled by Draine et al. (2013), with extinction reddening from
Calzetti et al. (2000) template. Example SED models are given in the Appendix.

##  4 Results

We present the results of the data reduction processes stated above.

###  4.1 X-ray Properties

Broad band 0.5-7.0 keV X-ray luminosities are given in Table 1 for the 23
objects covered by CXO and/or XMM. X-ray luminosities range from
$L_{0.5-7.0\rm{keV}}=7.8\times 10^{37}$ to $2.8\times 10^{43}$
$\rm{erg~{}s^{-1}}$. Of the 23 galaxies with X-ray coverage in either CXO or
XMM, 11 are detected in X-ray. Figure 3 plots the relationship of stellar mass
to $0.5-7.0~{}\rm{keV}$ luminosity for both XMM and CXO sources.

Through the CXO data reduction for 12 objects, we found X-ray luminosities
ranging from $L_{0.5-7.0\rm{keV}}=7.8\times 10^{37}$ to $4.6\times 10^{42}$
$\rm{erg~{}s^{-1}}$. There were two dwarf galaxies with CXO coverage - NSA
631492 and 631480. The stellar mass range of objects from the CXO Archive is
$\log(\text{M}_{*}/\text{M}_{\odot})=6.89$ to $11.54$.

Upper limits were found for NSA 28810, 64258, 64266, 613397, and 631480 within
CXO observations. Their values range from $9.8\times 10^{38}$
$\rm{erg~{}s^{-1}}$ for NSA 631480 to $8.6\times 10^{41}$ $\rm{erg~{}s^{-1}}$
for NSA 28810.

The X-ray luminosities for the XMM source catalog objects are generally higher
than for those observed with CXO. The X-ray luminosities range is
$L_{0.5-7.0\rm{keV}}=5.3\times 10^{41}$ to $2.8\times 10^{43}$
$\rm{erg~{}s^{-1}}$. The catalog sources are all massive galaxies, with
stellar mass range of $\log(\text{M}_{*}/\text{M}_{\odot})=10.53$ to $11.61$.

Upper limits from XMM observations were found for NSA 28810, 64258, 64266,
205160, 208625, 208662, 208702, 259478, 259880, 259919, 260221, 260241,
631480, and 631492. Their values range from $8.0\times 10^{39}$ to $1.3\times
10^{42}$ $\rm{erg~{}s^{-1}}$. We note these provide loose constraints on the
luminosity of the objects as these limits are derived from flux upper limits
of the observations themselves.

NSA 631492 has the lowest luminosity of our whole X-ray population, at
$L_{0.5-7.0\rm{keV}}=7.8\times 10^{37}$ $\rm{erg~{}s^{-1}}$. It is also worth
noting that NSA 631492 is the least massive object in this study, at
$\log(\text{M}_{*}/\text{M}_{\odot})=6.89$ and it lacks an optical spectrum
from SDSS. In contrast, the most massive galaxy, NSA 208465, with a stellar
mass of $\log(\text{M}_{*}/\text{M}_{\odot})=11.61$, is the second most
luminous within our population. Its optical spectrum is dominated by
absorption lines.

We find that three of the seven X-ray sources within CXO are moderately
obscured, with intrinsic $n_{H}$ on the order of $10^{22}\text{cm}^{-2}$.
Comparatively, all the XMM sources are below this threshold of obscuration,
pointing to the bias of the XMM source catalog towards bright AGN.

Figure 3 shows the stellar masses versus the $L_{0.5-7.0\rm{keV}}$ for each
target. We observe a general trend that an increase in host stellar mass leads
to an increase in X-ray luminosity. Objects with both CXO and XMM luminosities
are marked on the plot. These cases are discussed further in Section 4.2.

Figure 3: Galaxy mass versus X-ray luminosity for each source and upper limit.
Diamonds represent those values collected from CXO, with ’X’s representing
XMM. We color coordinated points from XMM and CXO to which represent one
singular object. Unfilled points represent those objects with values taken
from only that one survey.

###  4.2 Objects detected with CXO and XMM

As seen in Table 1, NSA 64145, NSA 64272, and NSA 64286 have both bright X-ray
emission within archival CXO data and an associated source within the XMM
Source Catalog. Thus, we can evaluate whether these sources have persistent or
variable/transient X-ray emission. We present the GALEX near-UV light curves
for these three objects from Wasleske et al. (2022) in Figure 4.

Figure 4: _Top:_ GALEX NUV light curve of NSA 64145 from Wasleske et al.
(2022). _Middle:_ GALEX NUV light curve of NSA 64272. _Bottom:_ GALEX NUV
light curve of NSA 64286. Each of these light curves so significant
($>0.2\textit{mag}$) variability across roughly three years. NSA 64272 and
64286 show significant change in mean magnitude in a one of their observation
windows, for a duration of about a month. Thus, we investigate the possibility
of a TDE in Section 4.2.

We find consistent and persistent broadband X-ray emission for NSA 64145, NSA
64272, and NSA 64286. For NSA 64145, the CXO observations for CXO were taken
in June 2013 and the XMM observations were taken between December 2004 and May
2006. Thus, NSA 64145 demonstrates persistent X-ray emission over near decade-
long timescale. NSA 64286 also has consistent X-ray luminosity between its XMM
and CXO observations, taken in May 2015 and March 2019 respectively. For NSA
64272, both its CXO and XMM X-ray luminosities are roughly consistent,within a
half dex of each other. The XMM source catalog used observations from December
2003, May 2006, and May 2007. The CXO observation for this object was taken in
January of 2007.

We consider the X-ray emission from the three sources above to be most likely
due to an AGN as opposed to a variable source such as a tidal disruption event
(TDE). TDEs would not be visible in the optical spectrum beyond a time scale
of months to a year. Faint and fast TDEs are seen to peak within a month and
decline in a shorter time (Charalampopoulos et al., 2022). Optical and X-ray
emission from TDEs is typically seen over a months-long timescale (Rees, 1988;
Komossa et al., 2008; Strubbe & Quataert, 2009; Wang et al., 2012; Cao et al.,
2018) (see Gezari (2021) for review and reference therein).

Objects NSA 28810, 64258, 64266, 208662, 631480 and 631492 each have analogous
XMM upper limits paired with their CXO detection or upper limit. In these
cases, if the object is detected by CXO, the CXO X-ray luminosity is less than
the XMM upper limit.

Interestingly, NSA 208625 has a CXO detection at a higher value than its XMM
upper limit. All archival CXO observations of this object were taken between
August and October of 2005. XMM observed this field on December 26th, 2015.
The UV light curve, constructed with data collected between May 4th, 2009 and
March 14th, 2011, shows stochastic variability rather than a burst-like light
curve. A possible scenario for this object is a TDE that occurred prior to the
CXO observations and faded by the time of the XMM observations. The
intermediate UV variability could be from residual accretion following the
TDE. Alternately, this object could be a changing state AGN. Further study of
object is needed to confirm either scenario.

##  5 Discussion

We compare X-ray luminosities to different host galaxy properties estimated by
the SED modeling. We show that the X-ray luminosities are higher than would be
expected based on star formation rates. We compare these objects against known
relationships for lumionus quasars, and search for reasons why these UV
variable, X-ray bright AGN candidates can lack optical signatures of BH
activity.

###  5.1 Origin of X-ray Emission

We can compare X-ray emission to the star formation rates (SFR) as estimated
by the SED models as an additional confirmation of the presence of an AGN.
Ranalli, P. et al. (2003) developed a relation between SFR and hard X-ray
luminosity for normal (non-AGN) galaxies. This relation reflects the expected
X-ray emission from X-ray binaries and supernova remnants. An excess of X-ray
emission for a galaxy’s SFR can indicate the presence of an AGN in a galaxy.
This relationship was used by Agostino et al. (2021) to identify AGN
candidates.

We plot the estimated SFR from SED modeling versus the $L_{0.5-10\rm{keV}}$
for our sample in Figure 5. Almost every galaxy in our sample is shown to have
excess X-ray emission compared to the Ranalli, P. et al. (2003) relation for
non-AGN objects. The notable exception is NSA 631492, which is the lowest
mass, lowest X-ray luminosity object in the sample.

Agostino et al. (2022) finds that LINER type galaxies have excess X-ray
emission across broad 0.5-10 keV for their SFR compared to normal non-AGN
galaxies. They separate their X-ray AGN candidates as those having X-ray
luminosities more than 0.6 dex above the X-ray luminosity predicted from their
SFR. All but NSA 631492 lay within Agostino et al. (2022) criteria for X-ray
AGN.

Figure 5: SFR versus 0.5-10 keV X-ray luminosity. The SFRs are the Bayesian
SFRs estimated from our SED modeling. The relation between SFR and X-ray
luminosity for normal galaxies is defined by Ranalli, P. et al. (2003).
Agostino & Salim (2019) adapted this relation for 0.5-10 keV X-ray
luminosities. The dashed red line shows this adaptation, with the shaded red
region quoting the intrinsic scatter of $0.3$dex ($1\sigma$) found by Ranalli,
P. et al. (2003). The grey shaded region reflects the selection criteria for
X-ray AGN from Agostino et al. (2021, 2022), where AGN candidates are chosen
to have an X-ray excess of $\geq 0.6$dex compared to the Ranalli, P. et al.
(2003) relation. Green dots, purple diamonds and orange triangles represent
BPT AGN, star-forming, or composite classifications on the BPT diagram
(Baldwin et al., 1981) respectively. These values are taken from Wasleske et
al. (2022). Blue crosses represent absorption line dominated spectrum. Black
squares represent those galaxies whose either did not have optical spectrum or
spectrum that could not be fit.

Even the galaxies with SF, composite and absorption line dominated optical
spectrum in our sample have X-rays in excess of the SFR predictions. The
galaxies with optical spectroscopic AGN signatures have a higher excess of
X-ray emission compared to the spectroscopic star-forming and composite
galaxies. Our results are similar to those of Agostino & Salim (2019), who
found that some of their X-ray AGN candidates did fall within the star forming
region of the BPT diagram. Agostino et al. (2022) also finds that one-quarter
of their X-ray AGN sample have apparent pure absorption-dominated spectra.
However, it is possible that higher resolution optical spectra (compared to
SDSS spectroscopy) or more robust optical spectroscopic modeling would reveal
some AGN signatures.

All of the X-ray detected objects besides NSA 631492 are likely AGN based on
having UV variability and X-ray emission in excess of SFR-based expectations.
This includes all 5 BPT AGN, 1/3 BPT composite, 3/7 absorption line systems,
and 1/7 of the galaxies with with no optical spectroscopy. For the non-
detected objects, the upper limits are generally not constraining enough to
rule out the possible presence of an AGN.

These results demonstrate variability selection is as effective as X-ray
selection at identifying AGN in objects lacking optical spectroscopic
signatures.

###  5.2 Diversity of Optical Spectroscopic Properties

Through our X-ray analysis, we establish that almost all of the UV-variability
selected, X-ray detected objects are bonafide AGN. In this section, we discuss
possible explanations for diversity in optical spectroscopic signatures.

####  5.2.1 Stellar populations

Here, we investigate the AGN power versus the emission from stars, as
estimated by our SED modeling. We note that all of the objects in our sample
preferred an AGN to be included in the best-fit SED. For galaxies without
optical spectroscopic AGN signatures, it is possible that host galaxy stellar
light is diluting the AGN emission. Stellar and AGN emission can also both
heat dust. In Figure 6, we show the best fit stellar luminosity versus AGN
luminosity from SED modeling. For the full sample, the stellar population is
brighter than the AGN. However, the stellar population is more dominant for
the absorption line-dominated systems than for the AGN or composite objects.
This is notable as the X-ray emission from the absorption line systems is
comparable to the BPT AGN, suggesting it is not simply a question of AGN
power. This suggests that host galaxy stellar populations or heating of dust
by stellar emission could be diluting the AGN signatures for these objects.

Figure 6: Scatter plot of AGN to stellar luminosity measured from SED
modeling. The thick red dash-dot is the unity line. The other faded red curves
are 0.5 dex deviations from unity. Points for NSA 631492 and 631480 are left
off as they exist in the far left, less luminous regime, compared to the rest
of the sample. Marker shapes and colors are the same as those defined for
Figure 5.

####  5.2.2 Disk - Corona Relation

Just et al. (2007) investigated the correlation of the X-ray-to-optical slope
$\alpha_{\text{OX}}$ to monochromatic luminosity density
$l_{2500\textrm{\AA}}$ for luminous Quasars in the Sloan Digital Sky Survey.
They found a clear dependence of $\alpha_{\text{OX}}$ on this UV luminosity
and no significant change in the $\alpha_{\text{OX}}$ over the redshift range
of $1.5\leq z\leq 4.5$. We explore whether our sample also follows the
$\alpha_{\text{OX}}$ relation in Figure 7. Points are identified by their
location on the BPT diagram. Residuals to the Just et al. (2007) relation are
given in the bottom panel.

Figure 7: Comparison of $\alpha_{\text{OX}}$ to monochromatic luminosity at
2500Å. The relation derived for quasars from Just et al. (2007) is plotted as
the grey line. Residuals from the Just et al. (2007) relation are given in the
bottom panel. The BPT AGN have the tightest fit to this relation. Marker
shapes and colors are the same as those defined for Figure 5.

Inspection of Figure 7 shows that the sub-population with optical
spectroscopic AGN signatures best agree with the Just et al. (2007) relation,
whereas the BPT composite and star forming galaxies, absorption line systems,
and those with no optical spectroscopy deviate more significantly from this
relation.

As hard X-rays of AGN come from the innermost region of the accretion disk,
deviations below the relationship from Just et al. (2007) suggest the presence
of obscuring material. This obscuring material can not only effect these
potential type-II AGNs, but also low-luminosity type-I’s. This obscuring gas
could be highly ionized, having no significant dust grains due to the heating
from the accretion outflow. High resolution spectroscopy of less luminous
sources, such as NSA 631492 and 631480, would help decipher between this
objects being a type-II or a low luminosity type-I AGN. We investigate the
effects of dust further in Section 5.2.3.

The deviation from $\alpha_{\text{OX}}$ for these non-spectroscopic AGNs could
also suggest a low ionization parameter, $\xi$, of its accretion disk.

We note that some objects with absorption features in their optical spectrum
have a closer correspondence than other non-BPT AGN. With optical absorption
features suggesting a predominantly older stellar population, the bright X-ray
emission of these sources paired with their UV variability support the need
for additional multi-wavelength observations for these objects to fully
understand the processes at work.

####  5.2.3 Dust Obscuration

We investigate the potential effect of dust obscuration from the host galaxy
on the spectroscopic signatures of our sample. Narrow emission lines are known
to to be attenuated by dust (see Hickox & Alexander (2018) and references
therein). Rigby et al. (2006) find that dust obscuration from the host galaxy
is a likely cause of optically-dull emission line ratios.

For our sample, we find that the dust-to-AGN luminosity plot of Figure 8
separates these objects similarly to the distinction of Figure 6, as the
absorption line dominated and non-BPT AGN have higher dust luminosities than
the rest of the sample. However, there is less of a spread in dust
lumionsities than is seen for stellar luminosities.

Figure 8: Plot of AGN to dust luminosity for our sample. Line are defined the
same as those in Figure 6. Again, points for NSA 631492 and 631480 are left
off as they exist in the far left, less luminous regime, compared to the rest
of the sample. Marker shapes and colors are the same as those defined for
Figure 5.

####  5.2.4 Excess Mid-Infrared Luminosity

Previous works have used the relationship between mid-IR and X-ray luminosity
to explore the accretion physics and dust structure of luminous AGN. Gandhi et
al. (2009) established a tight linear relation between mid-IR and X-ray
luminosity for local Seyfert galaxies. Rigby et al. (2006) investigates the
mid-IR emission of their sample, finding that their optically dull X-ray AGN
have mid-IR emission similar to Seyfert galaxies. Normal AGN optical/UV
continua is needed for Seyferts to produce their mid-IR luminosity, thus this
rules out a lacking optical/UV continuum as the reason for their optical
dullness.

We use the luminosity at $6\mu$m to investigate the mid-IR regime of their
spectrum. This should also help separate the effects of dust from host galaxy
and torus components, as mid-IR emission from AGN is produced by torus dust
being heated by UV photons.

We investigate the scaling between mid-IR luminosity at $6\mu$m to
obscuration-corrected X-ray luminosity, as discussed in Chen et al. (2017).
This relation is constructed from a Levenberg-Marquardt minimized $\chi^{2}$
fitting to AGN populations from the Boötes, XMM-COSMOS, XRT-SDSS, and XXL-N
samples assuming a bi-linear, broken power law fit. We note that the ”breaking
luminosity” of this relation is at $L_{6\mu m}=44.79$ erg s-1, which is
brighter than our most luminous object at $6\mu$m.

Additionally, Fiore et al. (2009) and Gandhi et al. (2009) have established an
intrinsic mid-IR to X-ray relationships. Gandhi et al. (2009) used high
resolution photometry of local Seyfert galaxies to find that they follow the
same correlation of Compton-thick AGN. The work of Fiore et al. (2009)
searched for highly obscured, Compton-thick AGN to estimate the missing
fraction of AGN that should be observed in these systems. In doing so, they
estimate unobscured X-ray luminosities for source that they originally detect
in the mid-IR.

We plot this relation against our variable X-ray AGN candidates in Figure 9.
The luminosity at $6\mu$m is estimated from our SED models. We find some of
the BPT AGN and absorption line dominated systems to be generally consistent
with the X-ray to mid-IR relation. This suggests that at least some of the
optically dull AGN in our sample have typical AGN optical/UV continuum and
torus dust emission.

On the other hand, some of the objects in our sample do have excess mid-IR
emission compared to their X-ray luminosity. These include four spectroscopic
AGN, two of the absorption line systems, composite objects and some objects
without optical spectroscopy. These objects could have excess dust near the
nucleus, potentially explaining the optical dullness in some cases. As mid-IR
emission can be an indirect tracer of AGN power (Lansbury et al., 2015), this
can point to the effect of obscuration within these systems. X-ray absorption
causes a steeper slope in the fitting, thus causing some of our spectroscopic
AGN to fall below these literary relations.

Figure 9: Plot of 2-10 keV luminosity to luminosity at $6\mu$m. Grey line and
shaded region show the empirical relation and its uncertainty from Chen et al.
(2017). The intrinsic relationships of Fiore et al. (2009) and Gandhi et al.
(2009) are given as solid black lines, with the blue area shaded between
representing a range of possible intrinsic and unabsorbed X-ray luminosity for
given mid-IR power. Residuals relative to the Chen et al. (2017) relation are
again given on the bottom panel. Marker shapes and colors are the same as
those defined for Figure 5.

##  6 Conclusions

In this work we measured X-ray emission for 23 UV variability-selected AGN
candidates from Wasleske et al. (2022) using archival CXO and XMM
observations. We detect X-ray emission from 11 of these objects. Then, we
constructed spectral energy distribution models using X-CIGALE (Yang et al.,
2020) to measure contributions from dust, stars, and gas across the
electromagnetic spectrum. We then explored reasons as to why this sample
displays a diversity of optical spectroscopic signatures. We summarize our
main findings below.

  * •

We measure X-ray emission for 23 sources originally selected as AGN candidates
from their UV variability (Wasleske et al., 2022). 11 of the 23 are detected.

  * •

We compare our observed X-ray luminosities to those expected due to star
formation. We find that 10/11 detected galaxies have X-ray luminosities more
than 0.6 dex above the Ranalli, P. et al. (2003) $L_{X-ray}$-SFR relationship
(this is the criteria used for AGN selection in Agostino et al. 2022). This
suggests that these systems are bona fide AGN. The upper limits for the
remaining objects are not constraining enough to rule out the presence of AGN.

  * •

Three sources, NSA 64146, 64272, and 64286, have detections in both CXO and
XMM observations. We argue that the consistency of the X-ray emission over
years long timescales is more consistent with AGN rather than a TDE as the
possible cause for the X-ray emission and their significant UV variability.

  * •

One source, NSA 208625, has bright X-ray emission in CXO observations taken in
2005 and a non-detection in XMM observations taken in 2015. The source faded
by at least an order of magnitude over the decade. This could suggest a
changing state AGN or a TDE in this galaxy.

  * •

Our confirmed AGN show a diversity of optical spectroscopic properties. We use
results from SED modeling to study whether stellar or dust emission could
impact the optical spectroscopic properties. We find:

    * –

The absorption line dominated systems generally have a higher ratio of
stellar-to-AGN luminosities. This is consistent with a scenario where host
galaxy light dominates the optical spectrum.

    * –

The BPT AGN are in general good agreement with the relationship of
$\alpha_{\text{OX}}$ to luminosity at 2500Å from (Just et al., 2007). Other
objects show large deviations from this relationship, suggesting possible
physical differences from luminous quasars. Obscuring material blocking X-ray
emission from the innermost part of the AGN’s accretion disk could be
responsible for the non-spectroscopic AGN deviating from the relation.

    * –

We find excess dust luminosity in those objects in our sample lacking optical
spectroscopic signatures.

    * –

We also find excess mid-IR emission for some objects in our sample, possibly
from the heating of dust or host galaxy contamination.

Ultimately, there is no one clear scenario that explains the diversity of
optical spectroscopic properties in this sample. Dilution of AGN signatures by
star formation, galaxy-wide dust extinction, and nuclear dust extinction are
likely all at play to different degrees in different galaxies. Spatially
resolved spectroscopy and more detailed spectral fitting would help to further
understand the diversity of properties in this interesting sample.

The variability selection of candidates done in Wasleske et al. (2022) was
complemented by spectroscopic analysis, IR AGN selection and low-resolution
SED modeling without X-ray values. This work has expanded on that analysis by
including X-ray information and more detailed SED modeling. The results here
clearly demonstrate that variability is a robust AGN selection technique,
identifying objects that would not have been selected based on their optical
spectroscopic properties.

##  7 Acknowledgments

We thank Erin Kimbro for helpful comments.

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.

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##  Appendix A Example SED Models

Below we give examples of SED modeling of X-CIGALE for NSA 28616 and NSA
64129. Models for Stellar attenuated, Stellar unattenuated, Nebular, Dust, and
AGN emission are given by color yellow, blue, green, red, and orange
respectively. Total model is shown in black with model fluxes as red dots and
observed fluxes as purple circles.

Both object’s SED modeling has significant AGN contributions in the IR. The
model fro NSA 28616 shows extinction of the AGN emission at higher energies,
but the sole contribution to the X-ray portion as the total black model line
is sitting on top of the orange AGN emission line. The model for NSA 64129
shows heavy extinction in the ultraviolet.

Figure 10: SED Models of NSA 28616 (_Top_) and NSA 64129 (_Bottom_).