# Evidence for a TDE origin of the radio transient Cygnus A-2

M. N. de Vries1 , M. W. Wise2,1, P. E. J. Nulsen3,4, A. Siemiginowska3, A.
Rowlinson1,5 and C. S. Reynolds6
1 Astronomical Institute "Anton Pannekoek", University of Amsterdam, Science
Park 904, 1098 XH Amsterdam, The Netherlands
2 SRON Netherlands Institute for Space Research, Sorbonnelaan 2, 3584 CA,
Utrecht, The Netherlands
3 Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA
02138
4 ICRAR, University of Western Australia, 35 Stirling Hwy, Crawley, WA 6009,
Australia
5 ASTRON, Netherlands Institute for Radio Astronomy, Postbus 2, 7990 AA,
Dwingeloo, The Netherlands
6 Institute of Astronomy, University of Cambridge, Cambridge, CB3 0HA, UK
E-mail<EMAIL_ADDRESS>
(Accepted XXX. Received YYY; in original form ZZZ)

###### Abstract

In 2015, a radio transient named Cygnus A-2 was discovered in Cygnus A with
the Very Large Array. Because of its radio brightness ($\nu F_{\nu}\approx
6\times 10^{39}$ erg s-1), this transient likely represents a secondary black
hole in orbit around the AGN. Using Chandra ACIS observations from 2015 to
2017, we have looked for an X-ray counterpart to Cygnus A-2. The separation of
0.42 arcsec means that Cygnus A-2 can not be spatially resolved, but by
comparing the data with simulated marx data, we put an upper limit to the 2-10
keV X-ray luminosity of Cygnus A-2 of $1\times 10^{43}$ erg s-1. Using the
Fundamental Plane for accreting black holes, we find that our upper limit to
the X-ray flux of Cygnus A-2 in 2015-2017 disfavours the interpretation of
Cygnus A-2 as a steadily accreting black hole. We suggest instead that Cygnus
A-2 is the radio afterglow of a tidal disruption event (TDE), and that a peak
in the 2-10 keV luminosity of the nuclear region in 2013, when it was observed
by Swift and NuSTAR, is X-ray emission from the TDE. A TDE could naturally
explain the X-ray light curve of the nuclear region, as well as the appearance
of a short-lived, fast, and ionized outflow previously detected in the 2013
NuSTAR spectrum. Both the radio and X-ray luminosities fall in between typical
luminosities for ’thermal’ and ’jetted’ TDE types, suggesting that Cygnus A-2
would be unlike previously seen TDE’s.

###### keywords:

X-rays:galaxies - galaxies:individual:Cygnus A

††pubyear: 2017††pagerange: Evidence for a TDE origin of the radio transient
Cygnus A-2–Evidence for a TDE origin of the radio transient Cygnus A-2

##  1 Introduction

The central engine of the radio-bright galaxy Cygnus A is generally understood
to be a heavily obscured, broad-line Active Galactic Nucleus (AGN) (Antonucci
et al., 1994; Ueno et al., 1994; Ogle et al., 1997). Because of the heavy
obscuration by the giant elliptical host galaxy, the AGN is not directly
visible at optical, UV and soft X-ray wavelengths (Young et al., 2002;
Canalizo et al., 2003). In contrast to the extreme radio power of the galaxy,
the AGN itself is only moderately luminous with a bolometric luminosity
$L_{\rm Bol}=10^{45}$ erg s-1 (Privon et al., 2012).

In July 2015, Perley et al. (2017) discovered a transient point source in
Cygnus A with the Karl G. Jansky Very Large Array (VLA). The transient, named
Cygnus A-2, is located 0.42 arcsec (460 pc) southwest of the primary AGN.
Follow-up observations in 2016 with VLA and the Very Long Baseline Array
(VLBA) confirmed the presence of the source, and the flux and spectral shape
showed no obvious variability within that year. The transient was not observed
in previous VLA observations, most recently in 1997, and therefore appeared
sometime between 1997 and 2015.

The radio luminosity $\nu F_{\nu}\approx 6\times 10^{39}$ erg s-1 makes Cygnus
A-2 a rather bright radio transient. The high luminosity puts a strong
constraint on the origin of Cygnus A-2. Perley et al. (2017) investigated
whether Cygnus A-2 could be the radio afterglow of a supernova, although a
supernova with such a high radio luminosity would be a rare and unlikely
event. The favoured explanation is that Cygnus A-2 is a secondary black hole,
orbiting the primary AGN. The black hole could have brightened due to a steady
increase in accreting material in the past 20 years, or through the sudden
disruption of a star by the black hole, known as a tidal disruption event
(TDE).

A point source coinciding with the location of Cygnus A-2 was observed in the
infrared with the Keck II AO system in 2003, in the $J$, $H$ and $K^{\prime}$
bands (Canalizo et al., 2003). The authors determined that this same point
source is also present in Hubble Space Telescope (HST) observations from 1996
and 1997. Based on the SED and the total luminosity, the most likely
interpretation for this point source is that it is a tidally stripped galaxy
core, that is in the process of merging with the giant elliptical galaxy. This
supports the secondary black hole hypothesis put forth by Perley et al.
(2017). Alternatively, the point source as seen by Keck and HST could
represent the light from the secondary black hole itself.

Additionally, between 1 and 3 arcsec northwest and southeast of the AGN, a
bipolar region with narrow emission lines has been observed in optical
observations with the HSTS (Tadhunter et al., 1994; Jackson et al., 1998). The
regions have an approximately paraboloidical shape and are oriented around the
jet axis, suggesting that they scatter the light of the obscured AGN into our
line of sight.

The nuclear region of Cygnus A has been studied at X-ray wavelengths as well,
although these observations are more limited in their angular resolution. In
Chandra ACIS observations, the AGN is moderately piled up with the standard
3.2s frame time. One 0.4s frame time observation from May 2000 has previously
been used by Young et al. (2002) to study the region. At energies below 2 keV,
the same bipolar emission regions are observed as with HST, while at energies
above 2 keV, the AGN itself becomes visible.

In 2013, the Nuclear Spectroscopic Telescope Array (NuSTAR; Harrison et al.,
2013), provided a new view of the AGN of Cygnus A at energies up to 70 keV.
Reynolds et al. (2015) have compared this observation with an XMM-Newton
observation from 2005. The two observations differ in two notable ways.
Firstly, the 2-10 keV X-ray luminosity appears to have doubled between 2005
and 2013. Secondly, subtle redshifted emission and blueshifted absorption
features were detected around the iron K$\alpha$ line at 6 keV in the NuSTAR
spectrum. These features are well fit by a fast, highly ionized wind with a
high column density. This wind would presumably have started up in the 7 years
between the two observations. We have summarized the observed properties of
the X-ray emission of the AGN as measured by Chandra, XMM-Newton, and NuSTAR
in Table 1.

Table 1: Overview of previously measured X-ray properties of the AGN, measured
by 3 different X-ray instruments.

Date | Ref | Instrument | $N_{H}$ | $L_{2-10\rm keV}$ | $\Gamma$
---|---|---|---|---|---
|  |  |  $10^{23}$ cm-2 | erg s-1 |
2000 05 | 1 |  Chandra ACIS | $2.0_{-0.1}^{+0.2}$ | $1.9\times 10^{44}$ | $1.52_{-0.12}^{+0.12}$
2005 10 | 2 | XMM-Newton | $3.4_{-0.3}^{+0.3}$ | $2.0\times 10^{44}$ | $1.43_{-0.11}^{+0.11}$
2013 02 | 2 | NuSTAR | $1.7_{-0.1}^{+0.1}$ | $4.1\times 10^{44}$ | $1.47_{-0.06}^{+0.13}$

References \- 1) Young et al. (2002), 2) Reynolds et al. (2015)

In this paper, we have searched for evidence of X-ray emission from Cygnus
A-2, with the aim of shedding more light on the nature of this transient. Of
particular interest are Chandra ACIS observations from 2000, 2005 and 2015 to
2017: firstly because its angular resolution of 0.5 arcsec is only slightly
larger than the 0.42 arcsec separation between the AGN and Cygnus A-2, and
secondly because the 2015-2017 observations are from the same epoch as the
original discovery of Cygnus A-2 with the VLA. We compare our results with
XMM-Newton and NuSTAR observations, described in Reynolds et al. (2015), as
well as archival observations from the the X-ray Telescope (XRT) on board the
Neil Gehrels Swift Observatory (hereafter referred to as Swift, Gehrels et
al., 2004; Burrows et al., 2005).

We give an overview of the Chandra observations in section 2. In section 3, we
image the soft X-ray emission and hard X-ray point source, compare the Chandra
image data with marx simulations, and use the image and the simulated data to
look for an X-ray counterpart to Cygnus A-2. In section 4, we perform an X-ray
spectral analysis of the AGN with the Chandra data, including modeling the
pileup. We compare the 2-10 keV luminosities with Swift XRT, XMM-Newton,
NuSTAR, EXOSAT, and ASCA observations to construct a light curve of the AGN
between 2000 and 2017. We also look for signatures of the fast, ionized wind
in the Chandra data. We discuss the results of the image and spectral analysis
in section 5, and conclude in section 6.

Throughout this paper, we have adopted a standard cosmology with $H_{0}$= 69.3
km s-1 Mpc-1, $\Omega_{M}$ = 0.288, and $\Omega_{\Lambda}=0.712$ (Hinshaw et
al., 2013). We use a redshift value of z=0.0561 (Stockton et al., 1994). Using
this cosmology, the linear scale is 66 kpc per arcminute and the luminosity
distance $D_{L}=253.2$ Mpc for Cygnus A. To facilitate comparison, X-ray
luminosities cited from previous work, have been re-calculated for this
luminosity distance.

##  2 Observations

Table 2: Overview of Chandra ACIS observations with the AGN close to the aimpoint. ObsIDs 360 and 1707 were taken with the ACIS-S array, all others with ACIS-I. The spectra and images of ObsIDs between dashed lines are considered to be within the same time period and are analysed together. ObsID 1707 is marked with an asterisk to indicate that it is the only short (0.4s) frame time observation. Date | Observation ID | Exposure
---|---|---
(UTC) |  | (ks)
2000-05-21T03:13 | 360 | 34.7
2000-05-26T12:28 | 1707* | 9.2
2005-02-15T15:26 | 6225 | 24.3
2005-02-16T13:01 | 5831 | 50.8
2005-02-19T05:10 | 6226 | 23.7
2005-02-21T03:06 | 6250 | 7.0
2005-02-22T11:59 | 5830 | 23.2
2005-02-23T11:52 | 6229 | 22.8
2005-02-25T04:27 | 6228 | 16.0
2005-09-07T04:48 | 6252 | 29.7
2015-10-28T11:49 | 17508 | 14.9
2015-11-01T16:48 | 18688 | 34.6
2016-06-13T21:02 | 18871 | 21.8
2016-06-18T17:52 | 17133 | 30.2
2016-06-26T16:13 | 17510 | 37.3
2016-07-10T22:52 | 17509 | 51.2
2016-08-15T22:10 | 17513 | 49.1
2016-09-15T05:46 | 17512 | 66.9
2016-11-12T12:56 | 17507 | 32.4
2016-12-13T10:56 | 17514 | 49.4
2017-01-20T18:09 | 17135 | 19.8
2017-01-26T00:42 | 17136 | 22.2
2017-01-28T14:24 | 19996 | 28.6
2017-02-12T05:40 | 19989 | 41.5
2017-05-10T02:01 | 17511 | 15.9
2017-05-13T21:25 | 20077 | 27.7
2017-05-20T23:24 | 17134 | 29.4
2017-05-21T17:12 | 20079 | 23.8
| Total | 837

More than 2.2 Ms of Chandra ACIS data is currently publicly available on the
Chandra Data Archive. However, a significant fraction of this data is pointed
at some of the extended features in the system, such as the eastern and
western hot spots, the merger region, and the northwestern subcluster CygNW.

To minimize the size of the PSF, we have selected only those observations
pointed at the AGN. This leaves us with a total of 873ks of data. Of those
873ks, 43.9ks were taken in May 2000, the first year of Chandra operations.
ObsID 1707 is of particular note, because it is the only one with a short
frame time of 0.4s, specifically chosen to avoid pileup in the AGN. A second
set of observations were taken in 2005, totaling 197.5ks. Finally, a large set
of observations of were taken between October 2015 and May 2017, totaling
595.6ks. We show a list of all the observations in Table 2.

Each of these datasets has been reprocessed using CIAO 4.9 and CALDB 4.7.4
(Fruscione et al., 2006). Chandra’s pointing inaccuracy means that there can
be an offset of up to an arcsec from the real coordinates. Therefore, an
astrometric correction is necessary to compare the same region between Chandra
datasets. We have followed procedure of Snios et al. (2018), briefly outlined
here. ObsID 5831 was chosen as the reference observation, because of the long
exposure time and the high number of events. We calculated the coordinates of
the center of mass within a 5” x 5” square, centered on the AGN. We then
reprojected these coordinates to the astrometric position of the nucleus,
$\alpha_{\rm nuc}=$ 19:59:28.35648, $\delta_{\rm nuc}=$ +40:44:02.0963 (Gordon
et al., 2016) with wcs_update. We then cut out a 160” x 120” rectangular
region of the central AGN of CygA. The event lists of the other ObsIDs were
reprojected onto the sky frame of ObsID 5831. A 0.5 - 7.0 keV image of the
reprojected events was then cross-correlated with that of ObsID 5831, and then
fitted with a Lorentzian function, to determine the coordinate offset. This
coordinate shift was then applied to the event list and the aspect solution
file with wcs_update.

After the astrometric correction, we applied the following CIAO processing
tools. For each ObsID, a new badpix file was built with acis_build_badpix. We
applied this badpix file, and the latest gain and CTI corrections with
acis_process_events. We created a new level 2 event file by filtering for good
grades (0,2,3,4,6). After that, we filtered for GTIs with the deflare
procedure.

##  3 Source imaging and the PSF

###  3.1 Imaging

Figure 1: 12.5" x 12.5" images showing the central region flux over time. The
image has been binned at 0.2 ACIS pixel size in both dimensions, and smoothed
by a 0.5” FWHM Gaussian. The astrometric positions of the AGN and Cygnus A-2
are respectively indicated by a cross and an X.

We imaged the central region of Cygnus A in 3 different energy bands: the soft
(0.5-1.275 keV), intermediate (1.275-2.2 keV) and hard (2.2-8.0 keV) bands,
chosen after Young et al. (2002). The ACIS blank-sky backgrounds were used as
backgrounds for these images. These backgrounds are imported from CALDB with
the acis_bkgrnd_lookup, and scaled to the event files by using the counts
between 10.0 - 12.0 keV. The event files and backgrounds were then reprojected
to the common tangent point of ObsID 360.

For each ObsID, we extracted a spectrum from a region with a radius of 6
arcsec, centered on the source. We then fit a model to them to obtain energy
weightings for the exposure maps. These fits are not meant to find the
physical characteristics of the source, but only to find a model curve that
approximates the spectral shape, to obtain a rough energy weighting for the
exposure-corrrected images. To the 0.5-2.2 keV band, we fit a power law
multiplied by the galactic absorption component, which we froze at $3.1\times
10^{21}$ $N_{\rm H}$ cm-2 (Dickey & Lockman, 1990). To the 2.2-8.0 keV band,
we fit the same model, but we leave the absorption component as a free
parameter, as the hard X-rays come from the highly absorbed central source
(Young et al., 2002).

These model curves were used to obtain spectral weightings, and we used these
to create instrument maps and exposure maps with the tools mkinstmap and
mkexpmap. The exposure maps were then reprojected to the tangent point of
ObsID 360.

We binned each each event file and blank-sky background into the 3 energy
bands, for each of the 3 time bins of 2000, 2005, and 2015-2017. We then
sliced a 12.5 x 12.5” image of the central region for each ObsID, spatially
binned at 0.2 native pixel resolution. We used dmregrid to bin the exposure
maps to the same resolution. We subtracted the backgrounds from the data and
divided by the exposure map to obtain images of the central region. The images
are shown in Fig. 1.

The nucleus, visible in the 2.2-8.0 keV band, has an irregular, non-pointlike
shape in the 2000 and 2005 observations. These asymmetries are the strongest
in the 2005 observations, and they show up in all of the the individual ObsIDs
from 2005, indicating they are not astrometry related. Further inspection of
these observations shows that they were carried out with a large SIM_Z offset,
about 10 mm larger than the nominal value. At an off-nominal offset, the
curved detector focal place intersects the focal surface of the mirrors
differently, causing a different defocus. We believe this to be responsible
for the irregular PSF shape in the 2000 and 2005 observations.

###  3.2 Simulations and the pileup fraction

Figure 2: Top: Surface brightness profile of the composite 2015-2017 2.2-8.0
keV data in blue, the background in yellow, and the simulated PSF (green) and
piled simulated PSF (red) from the marx simulations. Middle: Residual of the
data divided by the piled PSF. Bottom: The ratio between the unpiled and piled
PSF.

We have used the simulation tool marx (Davis et al., 2012) to simulate the
spatial and spectral distributions of events for each observation. The purpose
was to determine the size of the region in which pileup affects the spectrum
and to be able to compare the image to data, to look for evidence of any hard
X-ray emission that is more extended than the the point source.

As discussed in Section 3.1, the 2000 and 2005 observations show an unusual
PSF shape, with wings to the north, south, east and west. We have not been
succesful in reproducing this irregular PSF shape with marx. In this section
we therefore focus on the 2015-2017 observations, totaling around 595.6 ks of
data. As these observations were taken shortly after the discovery of Cygnus
A-2, these are the most likely to show any X-ray emission from the transient.

Based on the images of the source, it is apparent that the soft X-rays
primarily come from an extended region, while the hard X-rays primarily come
from the point source. If pileup was not a factor, the hard X-rays could be
simulated as a point source and the soft X-rays could be ignored. However,
because of pileup, both the spatial and spectral distribution of the source
emission affect the spectrum extracted from a region. Thus the soft X-ray
photons coming from the extended region need to be taken into account when
simulating the source. We therefore performed two separate simulations for
each ObsID. The soft, extended emission between 0.5 and 2.2 keV was simulated
by using the exposure-corrected image of the source (SourceType=IMAGE), and an
extracted spectrum, both obtained from ObsID 1707 and filtered for counts
between 0.5 and 2.2 keV. Marx matches the brightness distribution of the
simulated source to the input image, so that the simulated source has the same
shape, and the same spectral distribution. The 2.2-8.0 keV emission was
simulated as a point source (SourceType=POINT). The input spectrum was again
obtained from ObsID 1707, filtered for counts between 2.2 and 8.0 keV.

Other parameters relevant for the simulation, like the aspect solution file,
the exposure time, detector type, and SIM offsets, were all used in the
simulation by reading the header of each event file. The AspectBlur parameter,
which blurs the PSF by a fraction of an arcsecond to account for the
uncertainty in the determination of the aspect solution, was set to 0.20
arcsec. This is the recommended value for ACIS-I.

After both simulations were performed for a given ObsID, the simulations were
combined with the tool marxcat. We then applied the pileup tool marxpileup to
the combined simulation and binned images of the same size as the data, a 12.5
x 12.5” image at 0.2 native pixel resolution. Finally, we filtered each
simulated observation for events between 2.2 and 8.0 keV, and summed all the
images of individual observations to obtain the combined 2.2-8.0 keV simulated
data of the 2015-2017 observations. Because the source is embedded in the
intracluster medium (ICM), there are a significant number of background
counts, especially at radii beyond 3 arcsec. Therefore, we modeled the
background as a linear function $bkg(r)=a*r+b$ that is fit to the data - model
residual.

The results of our comparison between data and the simulation are shown in
Fig. 2. We note that, to achieve the best match between the data and the
simulation, we iterated over the SourceFlux parameter, which renormalizes the
total flux of the model. Because the soft X-ray emission is a few kiloparsec
in size, we do not expect that it varied significantly between 2000 and 2015,
and so we leave this input spectrum as it is. However, the AGN itself could
well have changed in brightness. We iterated several times to find the best
match between the piled PSF and the image data, and ultimately found the best
match by setting the SourceFlux to about 90% of that of the input spectrum of
ObsID 1707. In section 4.1, we compare this estimate against the luminosities
from the spectral analysis.

In the bottom panel of Fig. 2, we have compared the PSF and the piled PSF to
determine the radius within which pileup is significant, approximately 1.3-1.5
arcsec. Furthermore, we determine that the piled PSF contains 78% of the
counts of the unpiled PSF, yielding a pileup fraction of 22%. This provides us
with an estimate of the pileup fraction to compare against in section 4.1.

###  3.3 Searching for an X-ray counterpart to Cygnus A-2

Figure 3: Top: Counts per pixel profiles of the 2015-2017 data, divided in NW,
NE, SW, and SE quadrants. The dashed red line indicates the location of Cygnus
A-2, at 0.42 arcsec, in the SW quarter. Bottom: as above, but for the image
simulated with marx. Figure 4: Left: residual of the 2.2-8.0 keV image divided
by the simulated image. Right: residual of the 2.2-8.0 keV image divided by
the simulated image with an additional point source, with 5% the flux of the
AGN point source, at the location of Cygnus A-2. Both images have been
smoothed by a 0.5 arcsec Gaussian. The white crosses indicate the astrometric
locations of Cyg A and Cyg A-2, the red circle indicates a radius of 3 arcsec.

We have used the 2015-2017 data to search for evidence of Cygnus A-2. In the
2000 and 2005 observations, the irregular shape of the PSF makes this
comparison more difficult, as we were not able to reproduce the shape in the
Marx simulations. The 2015-2017 data is the most obvious place to look for
Cygnus A-2 in either case, because it is the time period closest to detection.
If Cygnus A-2 is emitting X-rays, it would elongate the circular shape of the
point source. We therefore look for hints of an elongated point source, by
comparing the 2.2-8.0 keV image data from section 3.1 with the simulated image
from section 3.2.

In the 2015-2017 image, we determined the center coordinate by calculating the
center of mass of the image. We then divided the image into quadrants NW, NE,
SW, and SE, using the center of mass as the center point. The transient is
located at 0.42 arcsec southwest of the center, and would thus be expected to
show most clearly in the SW quadrant. We calculated the SB profile for each of
the quadrants. We did the same for the simulated and piled PSF in order to
understand the order of magnitude of asymmetries in the PSF versus the image.
We show the SB profiles of the quadrants of both the image and the PSF in
Figure 3.

While the SE quadrant has the highest surface brightness at 0.42 arcsec, the
SW has the same surface brightness to within just a few percent. In the
simulated PSF, we see similar kinds of deviation, although slightly smaller
than in the data. Around 0.4 arcsec, the differences are of order 1-2%. It is
likely that at least some of these differences are caused by the fact that the
center of the source is not perfectly in the center of a single subpixel,
which means the different quadrants are not perfect quarters of the circle. In
the range from 0.2 to 0.6 arcsec, the total counts difference between the SW
and NE quadrants in the data is about 5%. We therefore expect the maximum
observed 2.2-8.0 keV flux to be not more than 5% of that of the AGN.

As support for this estimate, we revisited the marx simulations of section
3.2. We created a new simulated PSF by adding a secondary point source at the
location of Cygnus A-2 to the PSF simulations, and scaled the input spectrum
of that point source to 5% of the primary point source spectrum. We then
created two residual images: the first one by dividing the 2015-2017 2.2-8.0
keV data by the original simulated PSF, and the second one by dividing the
data by the simulated PSF with the transient added. The left and right panels
of Fig. 4 shows these two residual images. The left panel shows a similar
structure to the surface brightness profiles in Fig. 2: a decent match up to a
radius of 2.5-3 arcsec. At larger radii, the background dominates. The
residual appears to be roughly radially symmetric. The right panel of Fig. 2
shows the data divided by the PSF with the transient added. In this residual,
there is a visible deficit at the location of the secondary point source,
particularly noticeable towards the southwest. We conclude that a source with
a flux more than 5% would have been visible in the comparison between the data
and the PSF.

##  4 Spectral analysis

###  4.1 Chandra observations

(a) 2000 SF

(b) 2000 NF

(c) 2005

(d) 2015-2017

Figure 5: The spectral fits to the 2000 short and normal frame time, 2005 and
2015-2017 observations. Only energies above the red line at 3 keV are included
in the fit Table 3: Results of our fits to the the 2000, 2005, and 2015-2017
Chandra ACIS spectra with the source model described in the text. Parameters
directly obtained from the fit are shown with the 90% confidence interval.

Year |  $\alpha$ a |  $f_{\rm pileup}$ b |  $N_{\rm H}$ c | $\Gamma$ | $L_{2-10\rm keV}$ |  $\mu_{\rm iron-K\alpha}$ d | EWiron-Kα e |  $\tau_{edge}$ f | $\chi^{2}$
---|---|---|---|---|---|---|---|---|---
|  |  | ($10^{22}$ cm-2) |  | ($10^{44}$ erg s-1) | (keV) | (eV) |  |
2000 | $0.55\pm 0.05$ | 0.19 | $19.2\pm 4.3$ | $1.42\pm 0.12$ | $2.0\pm 0.2$ | $6.40\pm 0.01$ | 219 | $0.32\pm 0.15$ | $330/320$
2005 | 0.55 h | 0.19 | $19.1\pm 3.9$ | $1.30\pm 0.04$ | $2.2\pm 0.2$ | $6.43\pm 0.01$ | 149 | $0.40\pm 0.23$ | $335/321$
2015-2017 | 0.55 h | 0.17 | $20.7\pm 3.3$ | $1.23\pm 0.04$ | $1.9\pm 0.2$ | $6.44\pm 0.01$ | 150 | $0.35\pm 0.10$ | $412/383$

a The grade migration parameter.
b The fraction of piled events.
c The column density to the nucleus.
d The median rest-frame energy of the iron-K$\alpha$ line.
e The equivalent width of the iron-K$\alpha$ line.
f The optical depth of the absorption edge at rest-frame energy 7.2 keV.
h This parameter was fixed, see text for details.

We have defined a circular extraction region with a radius of 3 arcsec,
centered on the AGN. As a local background, we used an annulus around the
source between 6 and 10 arcsec. The source and background regions, as well as
the response files, were extracted from each ObsID with the CIAO tool
specextract. All observations in 2005 and between 2015 and 2017 were combined
with combine_spectra. The 2005 and 2015-2017 observations were all taken with
the ACIS-I detector, and thus we did not have to worry about different
detector types. After extracting, we fit the spectra with the CIAO fitting and
modeling tool Sherpa (Freeman et al., 2001).

As previously mentioned, ObsID 1707 is unique because it is the only short
frame time observation of the AGN, and therefore is not piled up. For ease of
reference, we will refer to ObsID 1707 as the 2000 SF (short frame time)
observation, and to ObsID 360 as the 2000 NF (normal frame time) observation.
As our analysis in section 3.2 has shown, there is moderate to strong pileup
in this source which needs to be accounted for in the spectra of the normal
frame time observations. To this end, we have used the pileup model jdpileup
(Davis, 2001).

Several parameters are used in jdpileup to parametrize the amount of pileup in
the spectrum. The most important of these are 1) $n$, describing the number of
3x3 islands in which pileup is applicable, 2) $f$, the fraction of the total
flux of the spectrum that is inside the pileup region, and 3) $\alpha$, a
parametrization of grade migration, where if $N$ photons are piled together,
the chance that they are registered as a single photon with their combined
energy is given as $\alpha^{N-1}$.

The PSF simulations from the previous section have shown that pileup
significantly affects the data up to about 1.3 arcsec radius. We estimate the
parameter $f$ from the 2.2-8.0 keV flux image of the 2000 SF observation. We
calculate the flux ratio of the flux within the estimated pileup radius of 1.3
arcsec, and 3 arcsec, the total size of the extraction region. From the image
we measure $f=0.93$. Although the PSF is a bit more extended in 2005 compared
to 2000, we assume this will not significantly alter the value of $f$ and we
have chosen to leave this parameter fixed.

The parameter $n$ represents the number of 3x3 pixel islands in the
observation where pileup is significant. After the example in Davis (2001), we
have counted the number of full pixels in a 1.3 arcsec circle and divided this
number by 9. We count 14 pixels, and therefore we set $n=1.55$.

Next, we consider the spectral model. Previous modeling of the AGN by Young et
al. (2002) and Reynolds et al. (2015) shows that the AGN spectrum is a heavily
absorbed power law. Because of the heavy absorption, there are virtually no
counts coming from the AGN below 2 keV. On top of the power law, there is a
fluorescent iron-K$\alpha$ emission line in the spectrum, around 6.4 keV rest-
frame energy. This line can be modeled either with a Gaussian, or with a more
detailed Compton-thick reflection model. While the reflection model is the
more physical of the two, it is difficult to fit this to the Chandra data,
where we are restricted to the 0.5-7.0 keV energy range, below most of the
Compton reflection features. In fact, Reynolds et al. (2015) have attempted to
fit the reflection model to the XMM-Newton data and find that the reflection
model does not significantly improve the fit over a Gaussian emission line. We
therefore use a Gaussian to describe the fluorescent emission line. Beyond the
iron-K$\alpha$ line, Young et al. (2002) note the presence of an absorption
edge at a rest-frame energy of around 7.2 keV, or 6.8 keV observed energy. We
therefore include this component in our model, and we have fixed the treshold
energy of the absorption edge to 6.8 keV.

The presence of pileup in the spectrum means that we must consider the full
Chandra ACIS energy range, and not just photons above 2 keV, where the AGN is
bright. This is because the soft X-ray photons will affect higher energies by
becoming piled. This presents a problem, as the soft X-ray photons come from
an extended region rather than the AGN. Therefore, the parameters of the
pileup model are not necessarily valid. We have attempted to circumvent this
problem by including the model components of the soft X-ray emission in the
total model, but not fitting the data below 3 keV. The soft X-ray emission is
modeled as a second, unabsorbed power law as well as 3 fluorescent emission
lines, modeled with Gaussians (see Young et al., 2002). Given that this model
is not fit to the data, we do not consider the fit values that we obtain for
the soft X-ray model components as physically accurate. Rather, the soft X-ray
model components exist purely to model how the soft X-ray band of the spectrum
affects the shape of the spectrum in the hard X-ray band due to pileup. During
the fitting process, we have tweaked the parameters of the soft X-ray model
components, in particular the amplitude of the emission lines, such that they
do not deviate too far from the soft X-ray data.

Lastly, we take into account the contribution of the thermal ICM. We have
modeled the ICM with a thermal APEC model, absorbed by the galactic
absorption. We fit this model to the background annulus between 0.5 and 4 keV.
At energies beyond 4 keV, the PSF of the AGN is so wide that the hard X-ray
photons from the AGN significantly contribute to the background annulus. For
each time period, we determine the abundance and temperature with a fit to the
background annulus. We then freeze the temperature and abundance in the fit to
the source spectrum, allowing only the normalization to vary. The temperature
and abundance are slightly different between 2000 and the later time periods.
This can be explained by the fact that the 2000 observations were taken with
ACIS-S and the later observations with ACIS-I. The changes are of order 5-10%,
and the ICM temperature and abundance for all spectra are around $kT=3.5$ keV
and $Z=0.55$ Z ⊙.

The final model is then as follows: ABS1 * (ICM + POW1 + 3*emLINES + ABS2 *
EDGE * (POW2 + emLINE)). This model is used as input to the jdpileup model for
all spectra except the 2000 SF observation. The galactic absorption is set to
$3.1\times 10^{21}$ cm-2 (Dickey & Lockman, 1990). The FWHM of each emission
line is set to 0.07 keV, roughly the expected FWHM of Chandra. We took the
energies of the soft X-ray emission lines from Young et al. (2002), and left
the energy of the iron-K$\alpha$ emission line as a free parameter. We have
also linked the photon index of POW1 to the photon index of POW2, which is
what is expected if the soft X-ray emission is scattered AGN light.

We have fit the 2000 SF and 2000 NF spectra simultaneously. Because these were
taken days apart, we have assumed that parameters such as the photon index and
the absorbing column have stayed the same in this time period. Simultaneously
fitting the same model to these two spectra helps to further constrain the
pileup model. The 2005 and 2015-2017 spectra were fit separately, giving us 4
spectra and 3 time periods in total.

Our best fits to the spectra are shown in Fig. 5, and the results of those
fits are given in Table LABEL:AGN:tab:hardemission. During the fitting process
we noticed that the grade migration parameter $\alpha$, when left as a free
parameter, takes on a value of 1 when fitting the 2005 and 2015-2017 spectra.
Because more grade migration hardens the spectrum, it is likely that there is
some degeneracy between $\alpha$ and the photon index $\Gamma$, which makes it
difficult to find the appropriate value of $\alpha$. In the 2000 spectra this
degeneracy is easier to break, because the SF and NF spectra are fit
simultaneously. We therefore fixed the grade migration parameter in these
observations to 0.55, the value found from the fit to the 2000 observations.

Furthermore, there seems to be no significant change in the spectra between
the three different time periods. The photon index is lower in the 2005 and
2015-2017 observations, but given the degeneracy between $\alpha$ and
$\Gamma$, it is unclear whether this is a real trend. The photon indices we
find are also broadly consistent with the photon index $\Gamma=1.43\pm 0.11$
that Reynolds et al. (2015) find for the XMM-Newton data, using the ICM +
cABS(PL + emLINE) model. The photon index is found to be higher, around
$1.60$, in the NuSTAR data, but this is somewhat model dependent. In
particular, adding reflection and wind model components changes the way the
region around the iron-K$\alpha$ line and beyond is modeled, and this can
shift the photon index of the entire spectrum.

One particular challenge of pileup models is that it can be difficult to
distinguish between a source with a high flux/high pile-up fraction, and low
flux/low pile-up fraction. For each of the fits, we have calculated the pileup
fraction in Sherpa with the command print(get_pileup_model()). The pileup
fraction for all observations is between 0.17 and 0.19, comparable to the
pileup fraction of 0.22 found in Section 3.2. Additionally, the luminosity in
2015-2017 is about 95% of the 2000 luminosity, consistent with the 90%
estimate we used to simulate the data with marx.

We have used the Sherpa tool sample_flux to estimate the 90% confidence
interval on the AGN luminosity. We find that for all time periods, the error
is on the order 10%.

The XMM-Newton data has significantly higher absorbing column ($3.0\times
10^{23}$ cm-2 ) than the Chandra observations from 2005. Because these
observations were taken close together in time, we would expect the absorbing
column to be roughly the same value. We tried to re-fit the 2005 Chandra
spectrum by fixing the absorbing column to the XMM-Newton value, but were
unable to find a good fit with this constraint. Most of Chandra exposures in
2005 were taken in February, with only ObsID 6252 being taken later, in
September. This is also the ObsID that is closest in time to the XMM-Newton
observation date in October. To see whether the absorbing column changed
between February and September, we fit the spectral model to ObsID 6252
separately to look for signs of a higher absorbing column. However, we find a
value that is consistent with that of the total 2005 spectrum, $N_{H}=(17.6\pm
2.2)\times 10^{22}$ cm-2. We therefore find no indication in the Chandra data
that the absorbing column increased towards the XMM-Newton observation date.

The intrinsic luminosity that we find from simultaneously fitting the 2000 SF
and 2000 NF spectra is $L_{2-10\rm keV}=2.0\times 10^{44}$ erg s-1. This is
consistent with the value of $L_{2-10\rm keV}=1.9\times 10^{44}$ erg s-1 that
Young et al. (2002) find, using the 2000 SF observation. Furthermore, the 2005
Chandra luminosity is consistent with the XMM-Newton luminosity.

###  4.2 Swift XRT observations

Table 4: The Swift XRT observations of the field of Cygnus A, in Photon Counting Mode. ObsIDs between dashed lines were combined. Date | Observation ID | Exposure | Distance from centre
---|---|---|---
(UTC) |  | (ks) | (arcsec)
2006-01-23T05:08 | 00035024002 | 5.1 | 103
2007-03-06T04:26 | 00036397001 | 9.0 | 98
2007-03-08T00:57 | 00036397002 | 12.4 | 84
2008-08-23T15:08 | 00036397003 | 5.6 | 118
2008-08-27T04:19 | 00036397004 | 3.7 | 139
2013-02-17T20:08 | 00080235002 | 2.0 | 118
2013-02-27T23:58 | 00082067001 | 1.9 | 399
2013-03-01T16:01 | 00080235003 | 1.9 | 95

To be able to study the long-term behaviour of the nuclear region, we have
searched for other X-ray observations of Cygnus A between 2000 and 2015. Swift
XRT has observed Cygnus A eight times between January 2006 and March 2013. Two
observations, on the 17th of February and 1st of March 2013, correspond
exactly to NuSTAR observation dates. The full observation log is given in
Table 4.

For each of these observations, obtained in Photon Counting Mode, we have
created a spectrum and associated response files. This was done using HEASoft
version 6.24, and the associated CALDB for Swift. Because the FWHM of the XRT
PSF is 18 arcsec, the AGN is not clearly resolved inside the larger Cygnus A
X-ray environment. Therefore, any spectrum extracted from the Cygnus A region
is significantly contaminated by emission from the surrounding ICM, which is
relatively hot and bright. This is in principle no different from NuSTAR, but
there are additional problems for Swift XRT: the count rate of the
observations, around 0.56 counts/sec, is above the approximate pileup treshold
count rate of 0.5 counts s-1
111http://www.swift.ac.uk/analysis/xrt/pileup.php. The data is therefore
likely piled up. Additionally, Swift is more sensitive to soft X-ray photons
than NuSTAR, which means the contribution of the ICM to the spectrum is
stronger.

While the Swift software has tools to correct for pileup by excising the
center pixels of the observation, these tools assume that the extracted region
is a point source on a constant background. Because of the ICM that the AGN is
embedded in, this is not the case here and therefore any pile-up correction
will be inaccurate.

To minimize ICM contamination, we chose a relatively small extraction circle
of 18 arcsec, centered on the brightest pixel of each ObsID. We combined the
spectra from 2 ObsIDs in March 2007, 2 in August 2008, and 3 in February/March
2013. Together with the 2006 data point, this makes 4 data points in total.

All of the Swift spectra have a strong peak in the soft X-ray band, between
0.5 and 4 keV, and a peak in the hard X-ray band, between 4 and 10 keV. We
interpreted the soft X-ray peak to be the ICM and have therefore excluded
energies below 4 keV, where the ICM is the brightest. We fit an observed power
law to the spectrum between 4-10 keV and use that to determine the observed
luminosity. We note that, given the presence of pile-up, and the potentially
still significant presence of contaminating ICM, we do not regard the obtained
fit values for the photon index and the absorbing column as physically
accurate. Instead, the model serves as a way to determine the observed, rather
than the intrinsic, luminosity from the spectra.

After obtaining the observed luminosities, we estimated the intrinsic
luminosities by applying a few different corrections. Firstly, we applied a
pileup correction. Because the count rate is slightly above the pileup count
rate treshold, we assume a small pileup fraction of 10%. This rough estimate
is based on the fact that the count rate in our Swift spectra, 0.56 counts
s-1, is roughly 10% higher than the pileup treshold count rate, 0.5 counts
s-1. Secondly, we estimated the ICM contribution by fitting an absorbed
thermal model to the spectra between 0.5-2.0 keV, and calculating the
luminosity of this thermal model between 4-10 keV. The estimated 4-10 keV ICM
luminosity within the extraction region is $\sim 2.5\times 10^{43}$ erg s-1.
We subtracted this from the pileup-corrected observed luminosity. Thirdly, we
increased the luminosity by 5% to account for the difference between the 2-10
keV and 4-10 keV band. Finally, we de-absorbed the luminosities, by assuming a
photon index $\Gamma=1.4$. In the 2006 and 2013 observations, we assumed the
absorbing column to be the same as in the 2005 Chandra and 2013 NuSTAR
observations respectively. In the 2007 and 2008 observations, we assumed a
range in absorbing column between $1-3\times 10^{23}$ cm-2, which adds an
uncertainty of 40% to the calculated intrinsic luminosity.

###  4.3 X-ray observations before 2000

To measure the long-term X-ray behaviour of Cygnus A, we searched the
literature for X-ray observations before 2000. Cygnus A has been observed by
several X-ray telescopes before Chandra, although in these observations, the
AGN was not spatially resolved from the ICM. Given the lower spatial and
spectral resolution of these instruments, and the relative brightness of the
ICM, the measured intrinsic AGN luminosities are a lot more uncertain.

Cygnus A was observed with the European X-ray Observatory Satellite (EXOSAT)
in 1985 (Arnaud et al., 1987). A fit to the data with a thermal component and
an absorbed power law yielded an intrinsic 2-10 keV luminosity of $2.8\times
10^{44}$ erg s-1, while the thermal component has a luminosity of $3.4\times
10^{44}$ erg s-1.

In 1991, Cygnus A was observed with the Ginga satellite (Ueno et al., 1994).
Like with the EXOSAT observations, the authors find that the best description
of the data is provided by a model consisting of 1) a thermal and 2) an
absorbed power law component. The intrinsic luminosity was found to be much
higher than during the EXOSAT observation, about $5.5\times 10^{44}$ erg s-1,
and a thermal luminosity of $5.8\times 10^{44}$ erg s-1. However, the Large
Area Counter instrument on board Ginga that was used to observe Cygnus A has a
PSF with a FWHM of $1\degree.1\times 2\degree.0$ (Turner et al., 1989). With
such a large field of view, it measures the spectrum of the entire cluster,
and can not be used to make a reliable measurement of the AGN luminosity. We
therefore do not include the Ginga luminosity in our light curve.

Finally, Cygnus A was observed by the Advanced Satellite for Cosmology and
Astrophysics (ASCA) in May and October 1993. The data were analysed by
Sambruna et al. (1999). Fitting a thermal model plus absorbed power law to
these data, they found that the nuclear flux increased by a factor of more
than 3 in 5 months, while the absorbing column increased from $1.1\times
10^{23}$ cm-2 to $1.5\times 10^{23}$ cm-2. Because we were unable to reproduce
the conversion from observed to intrinsic luminosity listed in that paper, we
retrieved the archival data from the HEASARC data archive and re-analysed the
spectra. We selected the pre-extracted spectrum of the entire field that is
included in the standard data products, and used the spectra of the Solid
State Imager (SIS) instrument in Bright mode.

Comparing ASCA observations, we find that the 2-10 keV count rate is about 10%
higher in October than in May. We freeze the photon index to 1.8, the value
found by Sambruna et al. (1999), and leave the other parameters free. We fit
the spectra between 3 and 9 keV and find intrinsic luminosities for the non-
thermal component of $3.1\times 10^{44}$ erg s-1 and $3.0\times 10^{44}$ erg
s-1 for May and October, respectively. Interestingly, the absorbing column is
also much higher than what was found by Sambruna et al. (1999), $2.6\times
10^{23}$ cm-2 and $3.1\times 10^{23}$ cm-2 respectively. This is likely
because we used 3 keV instead of 4 keV as a lower limit, which allows for a
better restriction of the absorbing column.

###  4.4 The AGN light curve

Figure 6: The intrinsic 2-10 keV luminosity of the AGN of Cygnus A over time,
as measured by EXOSAT, ASCA, Chandra, XMM-Newton, NuSTAR and Swift. The dashed
line indicates the date of first discovery of Cygnus A-2 with the VLA.

We have combined all the available luminosity data on the AGN of Cygnus A into
a single light curve in Fig. 6. Shown are the Chandra data from section 4.1,
the Swift data from section 4.2, the EXOSAT and ASCA data from section 4.3,
and the XMM-Newton and NuSTAR data from Reynolds et al. (2015).

We note that the errors on the luminosities are, in some cases, rather
uncertain. No errors on the luminosity are reported for the EXOSAT data point
in Arnaud et al. (1987), nor for the XMM-Newton and NuSTAR data points in
Reynolds et al. (2015). For EXOSAT, we based our uncertainty estimate on the
uncertainty in the absorbing column, as well as adding 25% systematic
uncertainty because of the fact that the AGN is not resolved within the larger
environment, and the limitations of the simple two-component model that is fit
to this data. For the ASCA data, which we have re-analysed in this work, we
used the sample_flux tool in Sherpa to obtain 90% confidence intervals. For
the Chandra data, we similarly used sample_flux to estimate the 90% confidence
interval. For the XMM-Newton and NuSTAR data, we based our estimate on
uncertainty in the the absorbing column as well as a 5% systematic error. For
Swift XRT, we based our estimate on the uncertainty in the absorbing column
and a 25% systematic error. The systematic error in the case of Swift is large
because of the assumptions we had to make when converting observed luminosity
to intrinsic luminosity.

Although there are some hints that the average luminosity was higher before
2000, this increase is not significant because of the large error bars on the
EXOSAT and ASCA luminosities. All data points are consistent with a luminosity
of $2\times 10^{44}$ erg s-1, except for in 2013, when a statistically
significant higher luminosity was observed by both NuSTAR and Swift. We
discuss potential reasons for this increase in sections 5.1 and 5.3.

###  4.5 Wind signatures in the Chandra data

Figure 7: The Chandra ACIS 2005 and 2015-2017 ratio spectra. The horizontal
axis shows the Cygnus A rest-frame energy. The data have been divided by a
piled, absorbed powerlaw, leaving the iron K line and the absorption edge at
7.2 keV.

Reynolds et al. (2015) previously detected a fast and ionized wind in the 2013
NuSTAR spectrum. The presence of this wind was deduced from a P Cygni-like
spectroscopic feature around the iron-K$\alpha$ line: a redshifted emission
component that moves the centroid of the iron-K$\alpha$ line to lower
energies, and a blueshifted absorption component of the power law continuum.
The 2005 XMM-Newton spectrum showed no evidence of such an outflow, leading to
the conclusion that the wind appeared somewhere between 2005 and 2013.

To compare the the spectral features around the iron-K$\alpha$ line between
the 2005 and 2015-2017 Chandra observations, we have made ratio plots by
dividing the data by the piled up power law model. These are shown in Fig. 7.
Since the fluorescent iron K$\alpha$ line and the absorption edge are not
included in the model used for the divisor, their structure can be seen in the
ratio spectra. A visual comparison between the two spectra shows that the
centre of the iron K line has not redshifted. In fact, as Table
LABEL:AGN:tab:hardemission shows, it appears that the line centroid has
slightly blueshifted between 2000, 2005, and 2015-2017. During the XMM-Newton
observation in 2005, the line centroid was at $6.39\pm 0.01$ keV, lower than
the 2005 Chandra value of $6.43\pm 0.01$ keV .

We think that the most likely explanation for the shift is uncertainties in
the gain calibration, and the different chips that were used during each
epoch. In the 2000 observations, the AGN was on the S3 chip. In the 2005
observations, the AGN was on I1, with the exception of ObsID 6252, where it
was on I3. In all the 2015-2017 observations, the AGN was on I3. According to
the Chandra Calibration Status Report from July 2017, the average uncertainty
in detector gain is $0.3\%$. The uncertainty in gain calibration is lowest for
the back-illuminated chips, but it can be up to $0.6\%$ on front-illuminated
chips at higher focal plane temperatures and at high values of CHIPY. The 2005
observations were all taken at the standard focal plane temperature of
$-119.7\degree$, but some of the 2015-2017 observations had higher
temperatures, of up to $-115\degree$. Additionally, the nucleus is positioned
at high CHIPY values on most observations. We believe that these factors,
combined with the $0.01$ keV uncertainty from the fit, can account for the
$0.4-0.6\%$ shift between 2000 and the later observations.

However, in all Chandra observations the line centroid is significantly higher
than during the NuSTAR observation, $\mu_{NuSTAR}=6.34_{-0.04}^{+0.03}$.
Therefore, based on the centroid of the iron-K$\alpha$ line, there is no
evidence for a redshifted wind component in the Chandra spectra.

The absorption edge can clearly be seen in both the 2005 and 2015-2017
spectra. Reynolds et al. (2015) speculate that the absorption edge could be
the result of iron-K$\alpha$ absorption in an ionized wind. The fact that the
ionized wind is not seen in the XMM-Newton data could then be explained by the
fact that the absorbing column was significantly higher during that
observation, in October 2005. As discussed in section 4.1, the Chandra
observations from 2005 show no evidence of a higher absorbing column. Fitting
the spectral model to individual ObsID 6252, from September 2005 does not
return a higher absorbing column than the average 2005 value. Therefore, if
the absorbing column was higher during the XMM-Newton observation, it must
have increased from roughly $2-3\times 10^{23}$ cm-2 in the month between the
observations. This would be a relatively rapid change, especially considering
the absorbing column is around the same value in all Chandra and NuSTAR
observations.

Furthermore, supposing that the fast wind was present in all the Chandra data,
and is simply related to the amount of absorbing material in our line of
sight, it is puzzling why the centre of the iron-K$\alpha$ emission line seen
with Chandra is inconsistent with that of NuSTAR. This alone seems to be the
strongest evidence that the fast wind is not present in either 2005 or in
2015-2017. However, this still leaves the exact nature of the absorption edge
as an open question.

##  5 Discussion

###  5.1 AGN variability in Cygnus A

AGN are known to be variable on a multitude of timescales, ranging from hours
to years (e.g. Mushotzky et al., 1993; Markowitz et al., 2003; González-Martín
& Vaughan, 2012). In the light curve in Fig. 6, we observe that the X-ray
luminosity doubled between 2005 and 2013, and then halved again between 2013
and 2015. In this section, we discuss whether the rise and fall in luminosity
can be explained by intrinsic variability of the AGN.

Although most observations have roughly the same duration, on the order of
kiloseconds, for the Chandra 2015-2017 observations we combined observations
over a significantly longer time span. To verify that we are not missing
significant variability within that time period, we looked at the 2-10 keV
count rates of all the ObsIDs that make up the combined 2015-2017 observation.
The count rate is steady with variations of order 10% around the mean. From
these observations, there is therefore no evidence that the AGN is highly
variable on the timescale of weeks and months. To explain the increased
luminosity seen by NuSTAR we would therefore need to turn to long-term
variability.

An extensive study of long-term AGN variability in the 2-10 keV band was
carried out by Sobolewska & Papadakis (2009). In the 10 AGN that were studied,
a change in luminosity by a factor of 2 seems to certainly be within the
realms of possibility. However, this also depends strongly on the properties
of the AGN itself. Stochastic modeling of AGN variability shows that the
characteristic decay timescale is larger if the black hole mass is larger
(Kelly et al., 2011). For the AGN of Cygnus A, with a black hole mass
$M_{BH}=2.5\times 10^{9}$ M⊙ (Tadhunter et al., 2003), this timescale is on
the order of $\sim 50-1000$ days. This means that it could take years for the
AGN luminosity to decay back to its mean value. The time between the NuSTAR
and earliest Chandra observations is more than 2.5 years, so in principle this
could have been enough time for the AGN to settle back to its mean luminosity.

Soldi et al. (2014) carried out a long-term AGN variability study with the
Swift Burst Alert Telescope (BAT). For this study, 66 month lightcurves
(December 2004- May 2010) in the 15-100 keV band were used. The sample
includes Cygnus A. The variability is parametrized as $S_{V}$, the sample
standard deviation expressed as a percentage of the mean. For Cygnus A,
$S_{V}=31_{-5}^{+4}$%, compared to the average $\langle S_{V}\rangle=24\pm 1$
for the full sample of 11 radio-loud galaxies.

However, how $S_{V,14-100keV}$ translates to variability between 2-10 keV is
not directly obvious. At energies above 10 keV, reflection contributes to the
total emission, as evidenced by the Compton hump in the NuSTAR spectrum around
20-30 keV (Reynolds et al., 2015). The reflection component is expected to be
constant because any variability will be smeared out by the light travel time
towards the reflector (Sobolewska & Papadakis, 2009; Bianchi et al., 2009).
Because the reflection component decreases in strength towards lower energies,
the variability at 15-100 keV should be lower than at 2-10 keV.

The observations of Cygnus A before 2000, with EXOSAT and ASCA show
luminosities that are consistent with what we have measured with more recent
missions. However, as mentioned before, the relatively low spatial and
spectral resolutions make it more difficult to accurately separate the thermal
from the non-thermal emission. Fitting a single thermal model to the entire
cluster emission would likely leave a hard residual in the spectrum of gas
that is hotter than the mean. This hot emission might have been attributed to
the AGN, leading to higher measured luminosities. Additionally, the absorbing
column is not always well-constrained. This means the luminosities measured
with these missions are uncertain and that they are consistent with both the
idea of a relatively steady AGN, or an AGN doubling or perhaps even tripling
its luminosity within a few years.

Given the stochastic nature of AGN variability and the long-term studies of
AGN variability at X-ray wavelengths mentioned above, we can not rule out that
the 2013 peak in the Cygnus A light curve is simply the nucleus going through
a temporary high-accretion phase.

###  5.2 The X-ray luminosity upper limit of Cygnus A-2

In section 3.3 we have estimated an upper limit to the X-ray luminosity of
Cygnus A-2, by looking for coincident excess emission in the 2015-2017 Chandra
observations. The observed 2-10 keV luminosity of the primary AGN in the
2015-2017 Chandra observation is $\sim 8\times 10^{43}$ erg s-1, which gives
an upper limit to the observed luminosity of Cygnus A-2 of $\sim 4\times
10^{42}$ erg s-1. How this translates to intrinsic luminosity depends on the
absorbing column and spectral shape of Cygnus A-2. If we assume the spectrum
to be an absorbed power law and take the absorbing column to Cygnus A as an
upper limit, our upper limit estimate of the 2-10 keV intrinsic luminosity is
$\sim 1\times 10^{43}$ erg s-1.

One of the scenarios that Perley et al. (2017) proposed is that Cygnus A-2 is
a steadily accreting secondary AGN. If the radio emission comes from accretion
mechanisms, it implies a highly variable AGN, because of the non-detection of
Cygnus A-2 in earlier radio observations. Based on the luminosity of the
infrared point source that coincides with Cygnus A-2 (Canalizo et al., 2003),
this black hole would be accreting at far below the Eddington limit. This
means it is expected to lie on the Fundamental Plane for sub-Eddington
accreting black holes, given in Plotkin et al. (2012) as

$\log{L_{\rm X}}=(1.45\pm 0.04)\log{L_{\rm R}}-(0.88\pm 0.06)\log{M_{\rm
BH}}-6.07\pm 1.10.$ (1)

In Eq. 1, $L_{\rm X}$ is the X-ray luminosity between 0.5 and 10 keV, $L_{\rm
R}=(\nu L_{\nu})_{\rm 5GHz}$ the radio luminosity, and $M_{\rm BH}$ the mass
of the black hole in solar mass. If we assume a spectrum with a photon index
of $\Gamma=1.4$, similar to the primary AGN, $L_{0.5-10}\sim 1.2\times
10^{43}$ erg s-1.

Although no 5GHz observations of Cygnus A-2 were reported on by Perley et al.
(2017) we assume $F_{\rm 5GHz}=3.5$ mJy by extrapolating the optically thin
spectral model in their Fig. 2. This results in a radio luminosity
$L_{R}=1.3\times 10^{39}$ erg s-1, and a lower limit to the black hole mass of
$4\times 10^{8}$ M⊙.

Perley et al. (2017) have previously noted two constraints to the upper limit
of the Cygnus A-2 black hole mass: firstly, no dynamical disturbances are
observed from IR spectroscopy at the location of Cygnus A-2, implying a mass
significantly lower than the mass of the primary black hole ($\sim 2.5\times
10^{9}$ M⊙, Tadhunter et al., 2003).

The intrinsic scatter of the FP is given in Plotkin et al. (2012) as
$\sigma_{\rm int}=0.07\pm 0.05$ dex. This means the lower limit that we find
can potentially be a little bit lower, but not by a significant amount, and is
likely to be at least $10^{8}M_{\odot}$. This is a significant fraction of the
black hole mass of the primary AGN. Additionally, the $L_{\rm R}-M_{\rm BH}$
relationship Franceschini et al. (1998), and the pre-flare upper limits to the
radio flux density imply a black hole mass $M_{\rm BH}\sim 10^{8}M_{\odot}$,
which is inconsistent with our lower limit of $4\times 10^{8}$ M⊙.

Lastly, an estimate for the black hole mass can be obtained from the infared
luminosity of Cygnus A-2 during the 2003 Keck observation (Canalizo et al.,
2003). This is done by using the scaling relationship between the black hole
mass, the 1µm luminosity, and the width of the Paschen-$\beta$ broad emission
line (Landt et al., 2013, equation 2). Although neither of these values is
reported in the paper, the $\nu L\nu$ luminosity at 2µm is given as $1.7\times
10^{41}$ erg s-1. Using this as an upper limit, and assuming a broad Pa$\beta$
line with a FWHM of 7500 km s-1, implies a black hole mass of $3.2\times
10^{7}$ M⊙, an order of magnitude lower than we get from the X-ray estimate.
However, it is unclear how long-term AGN variability plays into this scenario.
It is possible that in 2003, Cygnus A-2 was still in the process of becoming
’active’ and thus had not yet reached its full potential infrared luminosity.

Although none of the above arguments give us hard limits, the result is that
the range of possible black hole masses for Cygnus A-2 is very narrow: it
would require the X-ray luminosity to be at the upper limit, or for Cygnus A-2
to have an absorbing column significantly higher than $2\times 10^{23}$ cm-2,
for the black hole mass to be at the lower end of the fundamental plane due to
intrinsic scatter, and for the $L_{\rm Radio}-M_{\rm BH}$ correlation to be
off by a factor of a few. Therefore, although Perley et al. (2017) favoured
the explanation of Cygnus A-2 as an accreting black hole, the lack of X-ray
flux seems to argue against this idea. We therefore turn to the alternative
scenario of Cygnus A-2 as a TDE, which we discuss in the following section.

###  5.3 Cygnus A-2 as a TDE

As an alternative to a steady accretion scenario, Cygnus A-2 could have
suddenly increased in brightness through a TDE. This would more naturally
explain the absence of detectable X-ray emission in the 2015-2017 Chandra
observations: not all TDE’s emit X-ray radiation, and when they do the X-ray
emission typically fades on a scale of weeks to months (e.g. Auchettl et al.,
2017). While the TDE rate in an average galaxy is estimated to be on the order
of $10^{-4}$ \- $10^{-5}$ yrs-1, analytical modeling shows that supermassive
black hole binary systems may perturb stellar orbits around them enough to
yield a significantly higher disruption rate, of up to $10^{-1}$ yrs-1 (Liu &
Chen, 2013). The recent discovery of a TDE in an ultra-luminous infrared
galaxy by Tadhunter et al. (2017) gives some observational evidence that this
may be the case. However, it is unclear whether the separation between the
primary AGN and Cygnus A-2, a projected offset of 460 pc, is close enough to
result in a significant perturbation of the stellar orbits.

Furthermore, we suggest that the peak in 2-10 keV X-ray luminosity in 2013
might be emission from that TDE. The $\sim 2.5$ years between NuSTAR and
Chandra observations would have been more than enough for the X-ray emission
to fade. Radio emission in TDE’s has been observed for $\sim 2-3$ years after
the disruption (e.g Bright et al., 2018), so an initial disruption in late
2012 or 2013 would be consistent with both X-ray and radio observations.

The difference in 2-10 keV luminosity in the Cygnus A light curve between 2013
and earlier observations is around $\sim 1-2\times 10^{44}$ erg s-1, but these
intrinsic luminosities were calculated by using the absorbing column of the
primary AGN, $N_{\rm H}\approx 20\times 10^{22}$ cm-2. If Cygnus A-2 were
instead responsible for the increase in X-ray luminosity, the intrinsic
luminosity would likely be lower, because the absorbing column would be a lot
lower. The sample of TDE’s studied in Auchettl et al. (2017) all have
absorbing columns which are, although enhanced compared to their Galactic
columns, not larger than $\sim 10^{22}$ cm-2. Based on a range of reasonable
absorbing column values, we therefore estimate the intrinsic luminosity to be
$\sim(0.5-1)\times 10^{44}$ erg s-1.

Most X-ray emitting TDE’s radiate the majority of their energy away through
soft, thermal X-ray emission from an optically thick disk, below 2 keV. The
exception is the rare class of jetted TDE’s, such as Sw J1644+57 (Burrows et
al., 2011; Zauderer et al., 2013) and Sw J2058+05 (Pasham et al., 2015). In
jetted TDE’s, the non-thermal X-ray emission in the 2-10 keV band can reach
peak luminosities of $10^{47}$ erg s-1. Assuming the standard TDE light curve
evolution of $t^{-5/3}$, 2-10 keV luminosities of order $10^{44}$ erg s-1
could be reached after hundreds of days. If the TDE had ever reached a peak
luminosity of $10^{47}$ erg s-1, it would have been brighter than the rest of
the galaxy by orders of magnitude, and it seems unlikely that it would not
have been noticed by Swift BAT, which continuously monitors the full sky.
However, the high luminosities in jetted TDE events are a result of the jet’s
direct orientation toward our line of sight. A slightly different viewing
angle could potentially have lead to a lower X-ray peak luminosity more
comparable to the X-ray luminosity of the primary AGN.

Alternatively, it has previously been shown in the literature that some
thermal TDE’s also have a non-thermal emission component in the 2-10 keV band,
as in the TDE XMMSL1 J0740-85 (Kawamuro et al., 2016; Saxton et al., 2017).
This power-law component is thought to be from the hot corona which
Comptonizes the thermal optically thick disk emission. In XMMSL1 J0740-85, the
2-10 keV luminosity is $\sim 5\times 10^{42}$ erg s-1, which is about an order
of magnitude lower than what would be required in Cygnus A-2. The TDE in
Cygnus A-2 would therefore have to rather bright for a thermal TDE, and it
might fall in what Auchettl et al. (2017) identified as the ’reprocessing
valley’: an observed luminosity gap between the thermal and jetted TDE events.
For TDE’s of such brightness, any X-rays are expected to be reprocessed into
UV and optical wavelengths before escaping the source.

If Cygnus A-2 is a thermal TDE, we would expect there to be a thermal emission
component below 2 keV, that is more luminous than the non-thermal emission
component. NuSTAR does not observe at energies below 3 keV, leaving the 2013
Swift XRT observation as the only one that could have potentially seen 0.5-2.0
keV emission from the TDE. We therefore compared the Swift spectra from 2007
and 2013 between 0.5 and 2 keV. The 0.5-2.0 keV count rate in 2013 is roughly
13% higher compared to 2007.

We first fit an absorbed thermal model to the 2007 spectrum, which yields a
temperature of 3.1 keV and an abundance of 0.6 Z⊙. We then fit the same
thermal model plus an additional absorbed power law to the 2013 spectrum,
fixing all of the parameters of the thermal model to the 2007 values. We also
set an upper limit to the additional absorbing column of $10^{22}$ cm-2. We
find that an absorbed power law with $\Gamma=1.5$ and $N_{H}=0.74\times
10^{22}$ cm-2 gives a good fit to the data, with a reduced $\chi^{2}=19/21$.
The intrinsic 0.5-2.0 keV luminosity of the powerlaw component is $1.8\times
10^{43}$ erg s-1. These parameters are all roughly consistent with a TDE
spectrum. It is also important to note that the observed rise in 0.5-2.0 keV
could not have been caused by the primary AGN, unless the absorbing column was
significantly lower during those observations. However, from the concurrent
NuSTAR observation in 2013 we know that this is not the case, further
supporting the idea that the rise in X-ray luminosity in the Swift and NuSTAR
spectra is connected to Cygnus A-2.

Radio emission has been observed from only 6 TDE’s so far. In all of the
jetted TDE events, like the aforementioned Sw J1644+57 and Sw J2058+05, as
well as Sw J1112.2 (Brown et al., 2017), 5GHz radio luminosities of
$10^{40}-10^{42}$ erg s-1 have been observed. In these events, the radio
emission, like the X-ray emission, is thought to arise from the relativistic
jets that are oriented toward our line of sight. In 3 other thermal TDE
events, radio emission has been observed with luminosity ranges of
$10^{37}-10^{39}$ erg s-1. The origin of this emission is uncertain, although
several models exist, such as transient jets (van Velzen et al., 2016) and
non-relativistic winds (Alexander et al., 2016). The radio luminosity at 5 GHz
of Cygnus A-2 is $\approx 6\times 10^{39}$ erg s-1. It is worth noting that
the radio luminosity, like the X-ray luminosity, falls right in the middle of
a bi-modal luminosity distribution, between the jetted and thermal TDE’s. This
suggests that if Cygnus A-2 is a TDE, it is unlike previously observed TDE’s.

As we have shown in section 4.5, we see no evidence in the Chandra data for
the fast, ionized wind that NuSTAR detected in 2013. Similar types of outflow
have been detected in the TDE’s J1521+0749 (Lin et al., 2015) and ASASSN-14li
(Kara et al., 2018). They are interpreted as warm absorbers that are fast-
moving, with speeds of $\sim 0.12c$ and $\sim 0.22c$ respectively.
Additionally, both outflows were detected to be ionized, with $\log\xi\sim
2-3$ erg cm s-1. This resembles the outflow in the NuSTAR observation, with a
velocity of $\sim 0.06c$ and $\log\xi\sim 3.2$. The NuSTAR data also suggests
a second wind component with $v\sim 0.16c$, although this component is very
poorly constrained.

In ASASSN-14li, the outflow was not detected a year later, suggesting these
outflows are naturally short-lived and stop once the accretion rate drops back
below the Eddington rate. The timescale of approximately a year is consistent
with the Chandra non-detection of the wind a few years after NuSTAR.

For the outflow to exist in the first place, it must be super-Eddington.
Reynolds et al. (2015) calculated the kinetic energy flux of the wind was to
be $L_{K}>1.7\times 10^{45}$ erg s-1. This is below the bolometric luminosity
of the primary AGN. However, in a black hole a few orders of magnitudes less
massive, this kinetic energy flux well be super-Eddington.

##  6 Conclusion

The absence of X-ray emission from Cygnus A-2 exceeding 5% of the emission
from the primary AGN in 2015-2017 Chandra observations presents a new
constraint on the origin of the transient. In particular, if Cygnus A-2 is a
steadily accreting black hole, we would expect its X-ray flux to exceed this
limit, unless it is either implausibly massive, $\sim 10^{8-9}M_{\odot}$, or
if the absorbing column is significantly higher than the primary AGN at
$2\times 10^{23}$ cm-2. In the latter case, the intrinsic luminosity could be
a few times higher than the upper limit that we have set.

The lack of X-ray radiation is more naturally explained if Cygnus A-2 is the
radio afterglow of a destructive event. Perley et al. (2017) discuss the
possibility of a supernova, although the high radio luminosity, the spatial
correlation with a previously detected infrared point source, and the lack of
variability over the year that the source was monitored with the VLA are all
difficult to explain with supernova models. They therefore favor the
explanation of a TDE in an offset, secondary AGN. A TDE scenario would not
require the secondary black hole to be as massive as in a steadily accreting
black hole scenario. Although TDE’s are quite rare, 460 pc separation between
the primary AGN and Cygnus A-2 might be enough to significantly enhance the
average disruption rate of $10^{-4}$ \- $10^{-5}$ yrs-1 galaxy-1.

The X-ray light curve of the AGN of Cygnus A that we have constructed in this
work, shows that the 2-10 keV luminosity has been fairly steady since at least
2000, with the exception of 2013, when the luminosity was twice as high.
Although it is possible that the luminosity increase can be attributed to
stochastic variability that is inherent to AGN, we suggest that Cygnus A-2
might instead have been responsible for this extra X-ray emission. We
therefore investigated a TDE model for Cygnus A-2 based on the X-ray
observations. To explain the 2-10 keV emission, the TDE would either have to
be a powerful, jetted TDE or a thermal TDE with a hot corona comptonizing
thermal disk emission and re-emitting it as non-thermal power law emission.

The observed 2-10 keV luminosity increase, of $0.5-1\times 10^{44}$ erg s-1,
falls in the gap between typical luminosities for a thermal TDE with a non-
thermal component ($10^{41}-10^{43}$ erg s${-1}$) and a jetted TDE
($10^{46}-10^{48}$ erg s-1). Similarly, the radio luminosity, which at 5 GHz
is $5\times 10^{39}$ erg s-1, falls in between the $10^{37}-10^{39}$ erg s-1
luminosity range for thermal TDE’s, and the $10^{40}-10^{42}$ erg s-1
luminosity range for jetted TDE’s. Cygnus A-2 would therefore either have to
be a particularly powerful thermal TDE, or particularly faint jetted TDE,
perhaps because of a larger viewer angle towards the jet.

We have observed a small increase in 0.5-2.0 keV luminosity in the Swift XRT
spectra between 2007 and 2013. This increase could not have been caused by the
AGN itself, if the absorbing column is indeed as large as measured in 2013 by
NuSTAR. Although the Swift data is not very constraining, it suggests a
connection between the 2013 X-ray observations and Cygnus A-2. The detection
of the fast, ionized wind in the 2013 NuSTAR data, and the non-detection with
Chandra in 2015, can also be explained by a TDE, as these have been known to
launch short-lived fast ionized winds.

The sparsity of X-ray data around 2013, other than the NuSTAR and Swift
observations discussed in this paper, make a more detailed X-ray analysis
difficult. Additional observations between 2013 and 2015 could have confirmed
whether the post-2013 light curve follows a TDE-like slope. Unequivocal proof
that the X-ray emission in 2013 came from a TDE might therefore be out of
reach. However, future X-ray observations of the AGN could potentially
determine whether the X-ray luminosity rises again, or if perhaps the wind
detected by NuSTAR has reappeared. If so, then this would imply that the X-ray
luminosity peak and the fast wind, are recurring behaviour of the AGN rather
than a unique event like a TDE. Continued monitoring with the VLA and the VLBA
should be able to confirm whether Cygnus A-2 is indeed a TDE.

## Acknowledgements

Support for this work was provided by the National Aeronautics and Space
Administration through Chandra Award Number GO5-16117A issued by the Chandra
X-ray Observatory Center, which is operated by the Smithsonian Astrophysical
Observatory for and on behalf of the National Aeronautics Space Administration
under contract NAS8-03060. This work made use of data supplied by the UK Swift
Science Data Centre at the University of Leicester. This research has made use
of data, software and/or web tools obtained from the High Energy Astrophysics
Science Archive Research Center (HEASARC), a service of the Astrophysics
Science Division at NASA/GSFC and of the Smithsonian Astrophysical
Observatory’s High Energy Astrophysics Division.

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