This document summarizes a study that uses multi-epoch mid-infrared data from the Spitzer Extended Deep Survey to identify active galactic nuclei (AGN) through their variability over timescales of months to years. Around 1% of galaxies showed significant mid-IR variability, with 80% likely to be AGN. The morphologies of variable AGN host galaxies were compared to a control sample, finding that obscured AGN hosts show more weakly disturbed morphologies than strongly disturbed or normal galaxies. This suggests mid-IR variability selects obscured or "Compton-thick" AGN, revealing information about their host galaxy morphologies.

1. MNRAS 476, 1111–1119 (2018) doi:10.1093/mnras/sty164
Advance Access publication 2018 January 19
Morphologies of mid-IR variability-selected AGN host galaxies
Mugdha Polimera,1‹
Vicki Sarajedini,1‹
Matthew L. N. Ashby,2
S. P. Willner2
and Giovanni G. Fazio2
1Department of Astronomy, University of Florida, Gainesville, FL 32611, USA
2Harvard–Smithsonian Center for Astrophysics, 60 Garden St, Cambridge MA 20138, USA
Accepted 2018 January 16. Received 2018 January 16; in original form 2017 September 18
ABSTRACT
We use multi-epoch 3.6 and 4.5 µm data from the Spitzer Extended Deep Survey (SEDS) to
probe the AGN population among galaxies to redshifts ∼3 via their mid-IR variability. About
1 per cent of all galaxies in our survey contain varying nuclei, 80 per cent of which are likely
to be AGN. Twenty-three per cent of mid-IR variables are also X-ray sources. The mid-IR
variables have a slightly greater fraction of weakly disturbed morphologies compared to a
control sample of normal galaxies. The increased fraction of weakly distorted hosts becomes
more significant when we remove the X-ray emitting AGN, while the frequency of strongly
disturbed hosts remains similar to the control galaxy sample. These results suggest that mid-IR
variability identifies a unique population of obscured, Compton-thick AGN revealing elevated
levels of weak distortion among their host galaxies.
Key words: galaxies: active – galaxies: evolution – infrared: galaxies.
1 INTRODUCTION
Active galactic nuclei (AGN) are galaxies which accrete signifi-
cant amounts of material on to their central super massive black
holes (SMBHs) and have long been one of the most interesting
phenomena in extragalactic astronomy. Questions relating to their
formation, structure, and SMBH accretion have been contemplated
since theories explaining the powering mechanism of AGN were
developed (Lynden-Bell 1969). AGN may represent an evolution-
ary phase for many galaxies and could have a significant impact
on their star formation. To understand the role played by AGN in
the evolution of galaxies, it is necessary to identify them in galaxy
surveys out to redshifts of ∼3 where significant AGN fuelling and
bulge growth occur.
Historically, AGN have been identified using several meth-
ods such as colour selection (Stern et al. 2005; Kochanek et al.
2012), spectroscopic signatures (Morse, Raymond & Wilson 1996;
Veilleux 2002), and variability (Sarajedini, Koo & Klesman 2009;
MacLeod et al. 2010). Studies using optical data found that identi-
fication is biased against more obscured or faint sources (Richards
et al. 2002). To address these issues, other studies have used X-ray
selection (Alexander et al. 2003) and mid-IR colour selection (Lacy
et al. 2004; Stern et al. 2005; Park et al. 2008), but they each have
their own biases. For instance, the X-ray selection is biased against
heavily obscured AGN, while colour-selection is biased against
AGN that are masked by the intrinsic luminosity of the host galaxy
(Kocevski et al. 2015, hereafter K15).
E-mail: mugdhapolimera@ufl.edu (MP); vicki@astro.ufl.edu (VS)
AGN have long been identified as variable sources with the
variability most likely originating from instabilities in the ac-
cretion disc or temperature fluctuations (e.g. Ruan et al. 2014).
For sources obscured by dust in the vicinity of the AGN, per-
haps in the form of a dusty torus as envisioned in the uni-
fied model, the variable UV photons may then be reprocessed
and produce variability in the mid-IR. Thus, mid-IR variabil-
ity may be more sensitive than other selection techniques to
obscured, Compton-thick AGN. Recent results from the NOAO
Deep Wide Field Survey and Spitzer Deep Wide Field Survey
(Kozłowski et al. 2010, 2016) have revealed that as many as
1.1 per cent of galaxies are significant variables in the Spitzer
bands at 3.6 and 4.5 µm. Their study covered a 9 deg2
field with short (∼90 s) exposures in five epochs spanning
∼10 yr. The mid-IR variable light curves had lower amplitudes
at short time-scales compared to optical AGN which can be inter-
preted as the accretion disc or dust torus smoothing out the short
time-scale variations.
An interesting and unsolved question concerning AGN is
how accretion is initiated on to the central SMBH. Hopkins,
Kocevski & Bundy (2014) suggested that AGN accretion can be
triggered by mergers. However, surveys to quantify merger signa-
tures in AGN samples have yielded mixed results. Kocevski et al.
(2012) showed that host galaxies of a sample of X-ray detected
AGN are no more likely to show morphological disturbances than
a mass-matched sample of control galaxies. In a follow-up study,
K15 found that the more obscured X-ray detected AGN have higher
probability of merger signatures than the unobscured ones suggest-
ing that dust may hide the AGN shortly after the fuelling is triggered
by a merger.
C 2018 The Author(s)
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2. 1112 M. Polimera et al.
Here, we address the issue of obscuration and its impact on de-
tecting merger-triggered accretion by identifying AGN in deep ex-
tragalactic surveys by their variability in the mid-IR. The data used
in our study are part of the Spitzer Extended Deep Survey (SEDS;
Ashby et al. 2013) and the Spitzer-Cosmic Assembly Near-infrared
Deep Extragalactic Legacy Survey (S-CANDELS; Ashby et al.
2015), two Exploration programmes completed during Spitzer’s
warm mission. The multi-epoch, deep images allow us to probe
variability on time-scales from months to several years using 3.6
and 4.5 µm images of five extragalactic fields covering ∼0.9 deg2
of the sky. Our survey extends ∼3 mag deeper than the SDWFS
field from Kozłowski et al. (2016) and in some regions includes a
larger number of epochs for variability analysis. We perform mor-
phological classification for the subset of variables that lie within
the near-IR CANDELS survey (Grogin et al. 2011; Koekemoer et al.
2011) to look for evidence of merger-triggered accretion among the
AGN host galaxies.
In this paper, Section 2 describes the data sample, Section 3 out-
lines the steps to identify variable galaxies, Section 4 describes the
selection of the control sample for morphology classification. The
classification process is described in Section 5. Section 6 discusses
the results and the following section lists our conclusions.
2 DATA DESCRIPTION
The Spitzer IRAC data used for this study are fully described
by Ashby et al. (2013, 2015). The survey covered the 30 × 30
arcmin2
Extended GOODS-South (a.k.a. the GEMS field, here-
after ECDFS), 30 × 30 arcmin2
Extended GOODS-North (HDFN),
50 × 50 arcmin2
UKIDSS Ultra-Deep Survey (UDS), a 10 × 60
arcmin2
region within the Extended Groth Strip (EGS), and a
10 × 60 arcmin2
strip within the UltraVista deep survey of the
larger COSMOS field. Three epochs of SEDS observations, each
consisting of up to 4 h integration time per pointing, were obtained
for these fields in 2010 and 2011. However, all of the fields had
previous Spitzer observations, some dating back to 2003, providing
a total of four to 10 epochs of observations separated by several
months to years. Table 1 lists all epochs of data obtained for each
SEDS field used in this study.
The spectral energy distributions of AGN have a minimum at
a rest wavelength of 1 µm (Elvis et al. 2009; Assef et al. 2010)
with bluer light originating from the accretion disc and redder light
coming from hot dust in the vicinity of the AGN (Urry & Padovani
1995; Asmus et al. 2014; Vazquez et al. 2015). The Spitzer images
from our survey probe from just near the AGN minimum at z ∼ 3
into the dust-dominated regime at lower redshifts.
Because our goal is to identify variability in the mid-IR, we
make use of images produced from the individual epochs for each
field. Identical reduction procedures were applied to all data to
ensure a uniform data quality throughout the survey. Each individual
epoch consists of the combined images, or mosaics, which were re-
sampled to 0.6 arcsec. per pixel resolution and locked to the same
world coordinate system. In this way, any particular (x, y) pixel
coordinate corresponds to the same RA and Dec. in every epoch.
We used SEXTRACTOR (Bertin & Arnouts 1996) to identify ex-
tended and point-like sources in each epoch of every field in our
survey. Photometry was measured in both the 3.6 and 4.5 µm im-
ages using apertures ranging from 2.4 to 12 arcsec in diameter. A
very low detection threshold (1σ) was adopted to improve source
completeness in the individual epochs. Sources found in each epoch
were matched by RA and DEC to within 0.5 pixels of a source in
the SEDS catalogues (Ashby et al. 2013). This eliminated spuri-
ous detections found in the individual epochs due to bad pixels
around bright sources or near the noisy edges of the mosaic. The
photometry from each epoch was zero-point corrected to match the
photometry in the SEDS catalogues. To determine the offsets, we
used sources in the bright-to-mid-range between 18th and 21st mag-
nitude which consisted of ∼1800 to ∼14000 sources depending on
the image size of the epoch. Offsets were found up to ±0.03 mag
but were generally closer to ±0.01 mag. These offsets were applied
to each epoch independently, ensuring photometric consistency in
each epoch. Based on the PSF for unresolved sources in the Spitzer
images, we chose the 3.6 arcsec diameter aperture for our variabil-
ity analysis. This aperture is large enough to include nuclear light
from a varying active nucleus while excluding light from the non-
varying, outer portions of the host galaxy and provides maximum
sensitivity to flux variations originating from the AGN.
Table 1 shows the number of sources found in each epoch of
each observing field and the median depth of the observation. The
differences in the numbers of sources are a reflection of the areas
observed. Our analysis includes only those sources detected in both
bands in three or more epochs in each field, which amounts to about
30 per cent of all sources detected. Thus, the total number of sources
used in our variability analysis is 87670.
3 VARIABILITY SELECTION
For each source in the catalogue detected in both bands with at least
three epochs of data, we calculated the standard deviation v[X] as
a function of the apparent magnitude as done by Kozłowski et al.
(2010),
v[X] =
1
N − 1
N
j=1
(m[X]j − m[X] )2
1
2
, (1)
where N is the number of epochs for an observed source, m[X]j is
the magnitude of the source in the jth epoch, X is the 3.6 or 4.5 µm
band, and m[X] is the average magnitude of the source in band X.
Fig. 1 shows the v[3.6] values for all galaxies in the COSMOS
field as a function of magnitude. Because the vast majority of galax-
ies in our survey are expected to be non-varying, the spread in the
v[X] values represents the photometric noise which increases as a
function of magnitude. We quantify this noise term by first calculat-
ing the median v[X] value, vm[X], in various magnitude bins along
the x-axis. The width of the bins used for this calculation ranged
from 1 mag at the bright end to 0.5 mag at the faint end to ensure
an adequate number of sources per bin. The vm[X] values were then
fitted with a line to produce a smooth distribution (red line in Fig. 1).
Next, we calculate the dispersion, σ[X], as the standard deviation
of v[X] values from vm[X] in each magnitude bin. These values
were also fitted to produce a smooth distribution of σ[X] values as a
function of magnitude (black line in Fig. 1). Making use of both the
3.6 and 4.5 µm data available for each source, we calculate the joint
significance parameter, which quantifies the degree of variability of
the source in both bands as
σ12 =
v[3.6] − vm[3.6]
σ[3.6]
2
+
v[4.5] − vm[4.5]
σ[4.5]
2 1
2
(2)
where σ12 is essentially the significance level of the variability in
each band added in quadrature. Fig. 2 shows the joint significance
values for all sources with the thresholds of 3 and 4σ indicated.
To quantify the coupling of variances in both the bands, we
calculate a variability covariance C and Pearson’s correlation factor
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3. Morphologies of mid-IR AGN host galaxies 1113
Table 1. Photometric depth of data.
Field PIDa Date Source count Median magnitudeb Number of Number of Number of
yyyy-mm-dd [3.6] [4.5] [3.6] (AB) [4.5] (AB) detected sources analysed sourcesc variable sourcesd
COSMOS 61043 2010/01/30 20334 19776 23.282 22.225 40635 13673 (34%) 107 (0.8%)
61043 2010/06/18 20857 19633 23.235 23.245
61043 2011/01/31 20049 19341 21.689 21.739
80057 2012/02/11 5812 5249 23.307 23.219
80057 2012/07/03 5674 5804 22.761 23.128
ECDFS 194 2004/02/08 4058 3229 22.874 22.191 76792 18936 (25%) 163 (0.9%)
194 2004/08/13 4399 3125 22.579 22.379
20708 2005/08/23 23417 17413 22.562 22.218
20708 2006/02/09 22203 18161 22.527 22.174
60022 2010/09/24 31680 28366 23.510 23.060
60022 2011/03/28 30676 28557 23.247 23.340
60022 2011/10/15 31648 28831 23.354 23.308
70204 2011/03/21 2838 2778 23.407 23.597
80217 2011/09/27 2085 2012 23.232 23.372
EGS 0008 2003/12/25 30070 25195 23.000 22.928 75217 21471 (29%) 305 (1.4%)
0008 2004/07/01 29476 24459 22.923 23.000
0008 2006/03/28 5845 4537 22.741 22.214
41023 2008/01/25 10798 8266 22.319 21.966
41023 2008/07/23 11181 8821 22.512 21.944
61042 2010/02/06 27856 25803 22.957 22.972
61042 2010/08/05 29047 26028 22.883 23.078
61042 2011/02/10 28085 26155 23.084 22.999
80216 2011/08/19 5181 4626 23.464 23.043
80216 2012/02/23 5711 5213 23.553 22.817
80216 2012/08/31 5004 4658 23.403 22.853
HDFN 00169 2004/05/16 4402 3177 22.640 22.480 57354 12450 (22%) 112 (0.9%)
00169 2004/11/17 4114 3413 22.806 22.393
00169 2005/11/25 1144 1026 22.485 22.597
20218 2005/12/09 4820 2759 22.127 21.805
20218 2006/06/02 3785 3208 22.395 21.932
61040 2010/05/27 23750 22815 22.951 22.893
61040 2011/02/28 24324 20984 22.734 23.142
61040 2011/06/02 24706 22772 22.853 22.914
UDS 40021 2008/01/28 32351 26772 23.132 22.766 67181 21140 (31%) 186 (0.9%)
61041 2009/09/21 32469 29639 22.984 23.373
61041 2010/02/25 31945 30597 23.207 21.539
61041 2010/09/23 32907 29842 23.180 23.294
80218 2012/03/11 4807 4459 22.565 23.422
80218 2012/10/13 4752 4160 21.668 23.162
80218 2013/03/16 3610 3402 23.216 22.790
aSpitzer program identification number; bThe number of sources meeting our criteria of detection in both bands with at least 3 epochs and the percentage of
total detected sources this represents; cThe number of variable sources in the field and the percentage of analysed sources this represents; dMedian magnitude
of sources detected in this field.
r as
C =
1
N − 1
(m[3.6]j − m[3.6] )(m[4.5]j − m[4.5] )) (3)
r =
C
v[3.6]v[4.5]
. (4)
Fig. 3 is a histogram of the correlation factors for all 3 and 4σ
variables. The correlation factor r is constrained in the closed inter-
val [−1, 1], where −1 shows absolute anti-correlation between the
variability in the two bands and +1 shows complete correlation.
To ensure a robust selection of true variables above the photomet-
ric noise and with highly correlated light curves, we set the criteria
for variable galaxies as σ12 ≥ 3 and r ≥ 0.8. The selected galaxies
were examined by eye, of which 16 per cent were classified as spu-
rious detections due to artefacts like diffraction spikes from nearby
foreground stars or close proximity of a source to the edge. Since
variability could not be accurately determined for these sources,
they were removed from the survey. Fig. 4 shows the distribution
of [3.6] mag of all detected sources and all the variability-selected
sources in all five fields. The variables span the entire magnitude
range of the galaxy survey and extend about 3 mag deeper than the
mid-IR variability survey in the SDWFS (Kozłowski et al. 2010,
2016).
The results of this analysis are summarized in the last column
of Table 1. The number of variables in each field are as fol-
lows: 107 (0.8 per cent) in COSMOS, 163 (0.9 per cent) in ECDFS,
305 (1.4 per cent) in EGS, 112 (0.9 per cent) in HDFN, and 186
(0.9 per cent) in UDS. This gives us a total of 873 variables or
∼1.0 per cent of analysed sources in our survey which is in agree-
ment with the result from Kozłowski et al. (2010) where the AGN
fraction was found to be ∼1.1 per cent.
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4. 1114 M. Polimera et al.
Figure 1. Standard deviation (equation 1) versus magnitude in the 3.6 µm
band of the COSMOS field. The blue dots represent all the sources, the red
line represents a fit to the vm [3.6] median values, and the black line repre-
sents the 1σ dispersion above the median line. This plot is representative of
the other fields in our survey.
Figure 2. Joint significance (equation 2) versus magnitude in the 3.6 µm
band for all sources in all five fields. The red and black dashed lines represent
the 3 and 4σ thresholds.
Although our aim is to identify AGN, other sources such as su-
pernovae can be detected as variable objects. An optical variability
survey by Falocco et al. (2015) identified 0.06 per cent of sources as
SNe among ∼33 300 sources with their SNe selection criteria being
r ≥ 23 and Nepoch ≥ 6. Given this statistic, the number of SNe in
our galaxy survey of ∼87 000 sources should be about 52, which is
∼6 per cent of the variability-selected sources. However, the spec-
tral energy distribution models of SNe from Smitka (2016) show
that the luminosity of the SNe dips in the mid-IR, suggesting that
the fraction of SNe among our mid-IR variability-selected galaxies
has an upper limit of 6 per cent and is likely to be even lower than
the percentage based on the Falocco et al. (2015) statistics.
We estimate the number of spurious detections in our survey
using the average number of sources with σ12 ≥ 3 but having
correlation factor values r < 0.8. These are sources which have
uncorrelated light curves and are unlikely to be true variables. The
average number of sources found per bin having r < 0.8 is 84
Figure 3. Histogram of the correlation factor r (equation 4) for all sources
with cut-offs as σ12 ≥ 3 (blue) and σ12 ≥ 4 (green). The red and black
dashed lines represent the average r number of objects per bin at r < 0.8 for
the 3 and 4σ sources, respectively.
(red dashed line in Fig. 3). Extrapolating this line to sources with
r > 0.8 implies that about 15 per cent of the variables meeting
our variability criteria are spurious. This is much smaller than the
number of spurious sources found by Kozłowski et al. (2016). They
found 34 to 47 per cent false positives among variables identified
with the same criteria we use (σ12 > 3 and r > 0.8) among variables
having four to five epochs of data. Our estimated percentage of false
positives combined with the percentage of sources which may be
SNe results in ∼20 per cent of our variables being spurious or non-
AGN in nature. Therefore, we estimate ∼80 per cent of the mid-IR
variability-selected sources are likely due to the presence of an
AGN. It can be seen that the false positive rate cited by Kozłowski
et al. (2016) is much higher than our estimated rate. But, the rate
drops significantly in Kozłowski et al. (2016) when they consider
presumably brighter sources with magnitudes measurable in all
four Spitzer bands. These have only a 6 to 7 per cent false positive
rate. Therefore, we could say that since our false positive rate falls
between that of their two photometry groups, this may indicate that
the parameters used for photometry of sources in our survey result
in a sample somewhere between these two photometry groups.
4 COMPARISON TO MULTIWAVELENGTH
DATA
Smaller regions within the SEDS fields have extremely large
amounts of multiwavelength data from X-ray to radio wavelengths.
For the purposes of our study, we focus on the sub-regions of the
fields with deep, HST imaging and well-sampled spectral energy
distributions for determining masses, redshifts, and morphological
classification of the host galaxies. The Rainbow data base (P´erez-
Gonz´alez et al. 2008)1
is a thorough compilation of photometry and
spectroscopy for several extragalactic fields which includes portions
of the SEDS fields. Multiwavelength photometry is used to deter-
mine photometric redshifts as well as stellar mass. We searched for
sources in the Rainbow data base within 1 arcsec of sources included
in our survey. We cross-referenced both the mid-IR variability-
selected sources and the non-varying sources and identified 7146
1 Website: http://rainbow.fis.ucm.es
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5. Morphologies of mid-IR AGN host galaxies 1115
Figure 4. Histogram of magnitudes of all sources (blue line) and the
variability-selected AGN (green) in all five fields. Variable numbers have
been multiplied by 100 to be compared with all sources.
sources in COSMOS (28 of which were mid-IR variables), 1992 in
ECDFS (13 variables), 5574 in EGS (18 variables), 2054 in HDFN
(20 variables), and 5173 in the UDS (25 variables). We further re-
quired that the Rainbow sources are within the CANDELS F160W
field of view. This is necessary for the morphology classification
process (see Section 5). This reduced the number of sources in the
ECDFS field to 6, EGS to 17, and HDFN to 19, with the number
of sources in the other fields remaining the same. Thus, a total of
95 mid-IR variables were found in the Rainbow data base within
the CANDELS field of view, representing 11 per cent of all mid-IR
variable sources. A visual inspection of the spectral energy distri-
bution fits to model templates indicate that the variable sources are
well fitted by the templates and should yield accurate redshifts and
masses for the galaxies.
To produce a control sample for our morphological study of AGN
host galaxies, we require a randomly selected sample of galaxies
that are non-varying and therefore not likely to be AGN but whose
physical parameters are similar to the AGN host galaxy parame-
ters. In particular we use galaxy mass, luminosity, and redshift to
constrain the control galaxy population.
For each field, we used the upper and lower limits of the mass,
redshift, and magnitude ranges to search for sources to constitute our
control sample. From the pool of candidates, we chose three random,
non-varying galaxies per variable source whose masses fall within
the range Mvar/2 < Mcontrol < 2 ∗ Mvar, where Mvar is the mass of the
AGN host galaxy displaying variability. Of the 285 control galaxies
initially selected from the Rainbow data base, 55 were discarded
since they were not within the CANDELS image field of view.
Fig. 5 shows the mass versus redshift for all mid-IR sources in our
survey with available data in the Rainbow data base (grey points),
mid-IR-selected variables (red points), and control galaxies (blue
triangles). The distributions of the control and variable samples are
well matched in the redshift range between z = 0.25 and 3 and in
the mass range between log(mass [M ]) = 8.5 and 11.5. This is
further displayed in the histograms of these galaxy samples shown
in Figs 6 and 7. The sharp decline in AGN at redshifts beyond z =
3 may be due to the combination of several effects. At these high
redshifts, we probe the part of the AGN SED that becomes more
strongly dominated by the host galaxy, making us less sensitive to
the AGN variability. Additionally, the decrease in surface brightness
at high redshift leads to greater incompleteness in the Rainbow data
Figure 5. Redshifts versus masses of the galaxies (for which data were
available from the RAINBOW data base) in our survey (grey dots), the mid-
IR-selected AGN host galaxies (red circles), and the control sample galaxies
(blue triangles). Note: The three outlier points lie outside the CANDELS
fields and thus have no control galaxies nearby.
Figure 6. Normalized histogram showing the masses of all galaxies (for
which data were available from the RAINBOW data base) in our survey
(blue line), the mid-IR-selected AGN host galaxies (green shaded), and the
control sample galaxies (red lines).
base. We also find few AGN hosts among the low-mass tail of the
galaxy distribution. Since AGN are generally more common among
massive galaxies, it is not too surprising that we find very few among
the lowest mass galaxies.
5 MORPHOLOGY CLASSIFICATION
The aim of our morphology study is to look for evidence of mergers
or interactions by examining the physical features of the AGN host
galaxies. If AGN accretion is indeed triggered by mergers or in-
teractions, we should observe a higher fraction of morphologically
disturbed galaxies among our variability-selected sample compared
to the control sample. We visually classify 30 × 30 pixel (0.9 × 0.9
arcsec2
) thumbnails of the AGN hosts extracted from the F160W
(1600nm) images, available in the CANDELS (Grogin et al. 2011)
Public Access data base. The classification was done using the
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6. 1116 M. Polimera et al.
Figure 7. Normalized histogram showing the redshift distribution of all
galaxies (for which data were available from the RAINBOW data base)
in our survey (blue line), the mid-IR-selected AGN host galaxies (green
shaded), and the control sample galaxies (red lines).
criteria described in more detail in Kocevski et al. (2012). First,
the general morphology was classified as disc, spheroid, irregular,
or point-like. Secondly, the degree of disturbance was classified as
Merger/Interacting (highly disturbed with multiple nuclei or two
distinct galaxies with interacting features such as tidal arms), Dis-
torted/Asymmetric (single asymmetric or distorted galaxies with
no visible interacting companion), Close Pair (near-neighbour pair
with both the galaxies in a single frame), Double Nuclei (multi-
ple nuclei in a single system) or Undisturbed (none of the above).
Fig. 8 shows representative galaxies from our survey in the various
morphological classes.
We performed a blind inspection, which means that the images
of the variable and control galaxies within each field were mixed to
avoid any biases during the classification process of the galaxies.
The classification was performed by two of the authors of this
paper individually (M. Polimera and V. Sarajedini), and the results
were merged. For ∼30 per cent of the galaxies, each reviewer had
classified them differently and these galaxies were reinspected until
a consensus could be reached on the proper classification.
We chose to employ this type of visual inspection to resolve the
subtle, low surface brightness features which are easy to miss using
modern automated classification techniques. However, we hope to
use these classifications as training sets for a machine-learning-
based classifier in the future.
6 RESULTS
Figs 9 and 10 show the visual morphology classification results
tabulated in Table 2. The 1σ error bars are calculated as confidence
intervals for a binomial population as
Error = z1−α/2
p(1 − p)
n
, (5)
where p is the fraction of variable galaxies in the each disturbance
category and n is the total number of galaxies (e.g. Cameron 2011).
We estimate the 1σ error where the confidence level is c = 0.683,
so the variate value from the standard normal distribution z1−α/2 =
1 (α = 1 − c).
Fig. 9 shows no significant differences between the AGN host
galaxy classifications and those for the control sample in terms of
Figure 8. Sample galaxies belonging to each of the classification groups
employed in our analysis. The size of each thumbnail is 30 × 30 pixels or
0.9 × 0.9 arcsec2.
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7. Morphologies of mid-IR AGN host galaxies 1117
Figure 9. Fraction of variable galaxies (blue diamonds) and control galaxies
(red squares) in each of the major morphology classes.
Figure 10. Fraction of variable galaxies (blue diamonds) and control galax-
ies (red squares) in different disturbance classes.
galaxy classified as disc, spheroidal, irregular, or point-like. We also
find no difference in the percentage of galaxies in a close pair. We
find a similar fraction of AGN hosts in galaxies with a discernible
disc (40 ± 10 per cent) as did Kocevski et al. (2012) for an X-ray-
selected sample (51.4 ± 5.8 per cent). About 30 ± 10 per cent of the
mid-IR variables are found in pure elliptical (spheroidal) hosts. This
is also quite similar to that found by Kocevski et al. (2012) for
X-ray-selected AGN hosts (27.8 ± 5 per cent).
In Fig. 10, we compare the percentage of galaxies displaying
signs of mergers/interactions and distortion/asymmetry using the
same symbols as Fig. 9. We find that AGN hosts and control galax-
ies have the same fraction of merger/interaction hosts within the
uncertainties (19 ± 5 to 23 ± 3 per cent). However, AGN hosts
have a slightly higher tendency to reside in galaxies that are either
distorted or asymmetric (42 ± 5 per cent) compared to the control
galaxy population (32 ± 3 per cent). This result is significant at the
1.7σ level. Dividing our sample into high- and low-mass hosts and
control galaxies also produced similar results.
As previously mentioned, Kocevski et al. (2012) studied 72
X-ray-selected AGN hosts in the GOODS-S field using the same
CANDELS NIR images analysed in this study. However, they found
no statistical difference between AGN hosts and the control galaxies
having strongly disturbed (merger/interaction) or weakly disturbed
(distorted/asymmetric) morphologies. One possibility they suggest
is that X-ray-selected samples of AGN still miss the most obscured
sources which could be hiding hosts displaying merger signatures.
A follow-up study by K15 explored this issue by determining the
level of obscuration in the X-ray-selected AGN using reflection-
dominated X-ray spectroscopic analysis. They found that the more
obscured X-ray detected AGN (i.e. those with the highest hydro-
gen column densities) had a higher fraction of morphologically
disturbed host galaxies than less obscured X-ray detected AGN.
Our results indicate that mid-IR variability-selected AGN sam-
ples have marginally significant levels of weakly disturbed host
galaxy morphologies. This could be interpreted as an indication that
our sample includes a significant number of obscured, Compton-
thick AGN. In order to test this hypothesis, we cross-referenced our
sample of mid-IR variables with X-ray identified AGN in the five
survey fields [COSMOS: Elvis et al. (2009); ECDFS: Alexander
et al. (2003) and Xue et al. (2011); EGS: Nandra et al. (2015);
HDFN: Alexander et al. (2003); UDS: Ueda et al. (2008)]. We ini-
tially searched for X-ray sources within 1 arcsec of the position
of each mid-IR variable and found that matched sources generally
lie within a 0.5 arcsec radius. Setting this as our matching thresh-
old, we found 22 of our mid-IR variables are also X-ray detected
AGN (23 per cent). This means that 77 per cent of our sources, or 73
mid-IR variables, are not identified in deep X-ray surveys and are
likely to be either spurious sources (expected among ∼20 per cent
of our sample) or may be highly obscured AGN whose X-ray
emission has been absorbed. If these represent the most obscured
sources, we may expect to find their morphologies to be the most
disturbed.
Table 2. Disturbance classification.
Galaxy
type
Disturbance
class COSMOS UDS EGS HDFN ECDFS Total
Variable Merg/Int 6 (21 ± 8 per cent) 5 (21 ± 8 per cent) 2 (11 ± 7 per cent) 2 (11 ± 7 per cent) 3 (50 ± 20 per cent) 18 (19 ± 4 per cent)
Dist/Asy 10 (35 ± 9 per cent) 12 (50±10 per cent) 12 (70 ± 11 per cent) 5 (26 ± 10 per cent) 1 (17 ± 15 per cent) 40 (42 ± 5 per cent)
Undisturbed 12 (42 ± 9 per cent) 8 (33 ± 9 per cent) 3 (17 ± 9 per cent) 12 (63 ± 11 per cent) 2 (33 ± 19 per cent) 37 (39 ± 5 per cent)
Total 28 25 17 19 6 95
Control Merg/Int 10 (22 ± 6 per cent) 17 (26 ± 5 per cent) 12 (25 ± 6 per cent) 11 (20 ± 5 per cent) 7 (35 ± 10 per cent) 57 (25 ± 3 per cent)
Dist/Asy 17 (37 ± 7 per cent) 22 (35 ± 6 per cent) 13 (27 ± 6 per cent) 19 (34 ± 6 per cent) 3 (15 ± 7 per cent) 74 (32 ± 3 per cent)
Undisturbed 17 (37 ± 7 per cent) 25 (39 ± 6 per cent) 22 (46 ± 7 per cent) 25 (45 ± 7 per cent) 10 (50 ± 11 per cent) 99 (43 ± 3 per cent)
Total 45 63 47 55 20 230
∗ The galaxies used to calculate these percentages are only those that are present in the RAINBOW data base for which the visual morphology classification
described in Section 5 has been performed.
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8. 1118 M. Polimera et al.
Figure 11. Fraction of mid-IR variable galaxies with an X-ray counterpart
(green diamonds) and those with no X-ray counterpart detected within 0.5
arcsec (black diamonds) in different disturbance classes.
In Fig. 11, we compare the fraction of host galaxies of different
morphological classifications for the mid-IR variables that are also
identified in X-ray surveys (green diamonds) to the mid-IR variable
sources without an X-ray counterpart (black diamonds). We see that
while the two samples have the same, low fraction of highly dis-
turbed host galaxies, a much higher fraction of mid-IR-only sources
have weakly disturbed hosts (48 ± 5 per cent) than those with X-ray
counterparts (23 ± 8 per cent). This difference is significant at the
3σ level. When we compare these percentages with those of the
most highly obscured, Compton-thick X-ray sources from K15, we
find that they agree favourably. We find that 22 ± 5 per cent of mid-
IR-only-selected AGN have highly disturbed host morphologies
compared to 21.5+4.2
−3.3 per cent of the most obscured X-ray sources
in K15. Furthermore, 40 ± 5 per cent of mid-IR-only-selected AGN
have weakly disturbed hosts compared to 43.0+4.6
−4.4 per cent in K15.
This further supports the claim that AGN selected via mid-IR vari-
ability are likely to contain a larger fraction of obscured AGN, pos-
sibly more obscured than the most absorbed X-ray-selected sources,
revealing a higher fraction of asymmetric hosts and highlighting the
unique nature of this selection technique.
7 DISCUSSION
It has been speculated that mergers tidally induce non-axis-
symmetric modes in the merging galaxy and these modes sweep the
interstellar gaseous medium into a disc with a radius of a few par-
sec around the central SMBH (Shlosman, Frank & Begelman 1989;
Shlosman, Begelman & Frank 1990). The disc then is accreted on
to the SMBH. Simulations from Barnes & Hernquist (1992) have
shown that these discs are more likely to form in a major head-on
merger scenario. Given such a theory, we may expect to see the
AGN hosts displaying a higher fraction of major mergers as com-
pared to the control group. Our results, however, do not show a sig-
nificant fraction of strong interaction signatures among the mid-IR
variability-selected AGN hosts. We do find a marginally significant
increase in the presence of weak interaction signatures in the host
galaxies when compared to a control sample and the significance
increases when we remove X-ray-selected AGN and isolate mid-IR
variability-selected AGN. One explanation is that during the entire
process of a galaxy merger, the galaxies spend more time in stages
where they appear to be weakly disturbed versus having a highly
disturbed morphology. Based on recent simulations by Capelo et al.
(2015), the time a galaxy spends in the weakly disturbed phases is
about 7.9 Gyr, but the system shows a highly disturbed morphology
only for about 4.6 Gyr. This makes it less likely to ‘catch’ the galaxy
in the highly disturbed phase because their signatures dissipate too
fast and we see less dramatic distortions in the hosts.
Another possibility is that the dominant AGN triggering mecha-
nism is not major mergers but that minor mergers are more impor-
tant for AGN to begin accretion as the perturbation is sufficient for
the orbits of material in the central part of the galaxy to get ran-
domized and disturbed just enough to infall into the central SMBH
(Hernquist & Mihos 1995; Menci et al. 2014). Hernquist & Mihos
(1995) also point out that the occurrences of major mergers are
more unusual as compared to minor mergers/interactions.
Yet another possibility is that the low fraction of major merger
signatures seen in our AGN hosts is due to heavy obscuration which
would absorb the variable UV photons from the accretion disc and
weaken the mid-IR variable flux necessary for our selection method.
As shown in K15, there is a significant increase in the fraction of
AGN host galaxy morphology disturbance as a function of obscu-
ration, with the Compton-thick AGN hosts showing the highest
fraction of disturbed morphologies compared to unobscured hosts.
Our study found that the host galaxies of mid-IR variables have
the same fraction of disturbed morphologies as the most obscured
X-ray-selected sources. It is possible that higher levels of distur-
bance are hidden by extreme obscuration such that neither X-ray
nor mid-IR variability is able to detect the AGN nature of the source.
8 CONCLUSION
The results of our study are summarized as follows.
(i) 1 per cent of all galaxies with [3.6] < 24.5 are significantly
variable in the mid-IR Spitzer/IRAC mosaics with 80 per cent like-
lihood of being AGN.
(ii) The AGN host galaxies show a marginally sig-
nificant trend (1.7σ significance) towards higher fractions
of Disturbed/Asymmetric morphologies (42 ± 5 per cent) as
compared to the control sample (32 ± 3 per cent), whereas
Merger/Interaction fractions are not statistically different for the
AGN and control galaxies.
(iii) 23 per cent of mid-IR variables are also identified in X-ray
surveys. The mid-IR variables without an X-ray counterpart show a
higher fraction of weakly disturbed hosts than those also identified
with X-ray emission. This suggests that mid-IR variability selects
a unique population of obscured AGN that would likely be missed
using other selection techniques.
ACKNOWLEDGEMENTS
This work is based on observations made with the Spitzer Space
Telescope, which is operated by the Jet Propulsion Laboratory, Cal-
ifornia Institute of Technology under a contract with NASA. This
work has also made use of the Rainbow Cosmological Surveys data
base, which is operated by the Universidad Complutense de Madrid
(UCM), partnered with the University of California Observatories at
Santa Cruz (UCO/Lick,UCSC) and used observations taken by the
CANDELS Multi-Cycle Treasury Program with the NASA/ESA
HST, which is operated by the Association of Universities for Re-
search in Astronomy, Inc., under NASA contract NAS5-26555.
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9. Morphologies of mid-IR AGN host galaxies 1119
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