# Digging a little deeper: characterising three new extreme ULX candidates

T. P. Roberts1, D. J. Walton2, A. D. A. Mackenzie1, M. Heida3, S. Scaringi1
1Centre for Extragalactic Astronomy & Dept of Physics, Durham University,
South Road, Durham DH1 3LE, UK
2Centre for Astrophysics Research, University of Hertfordshire, College Lane,
Hatfield AL10 9AB, UK
3European Southern Observatory, Karl-Schwarzschild-Str 2, 85748 Garching bei
München, Germany E-mail<EMAIL_ADDRESS>
(Accepted 2023 July 31. Received 2023 July 31; in original form 2023 June 2)

###### Abstract

A prime motivation for compiling catalogues of any celestial X-ray source is
to increase our numbers of rare sub-classes. In this work we take a recent
multi-mission catalogue of ultraluminous X-ray sources (ULXs) and look for
hitherto poorly-studied ULX candidates that are luminous ($L_{\rm X}\geq
10^{40}\rm~{}erg~{}s^{-1}$), bright ($f_{\rm X}\geq 5\times
10^{-13}\rm~{}erg~{}cm^{-2}~{}s^{-1}$) and have archival XMM-Newton data. We
speculate that this luminosity regime may be ideal for identifying new
pulsating ULXs (PULXs), given that the majority of known PULXs reach similar
high luminosities. We find three sources that match our criteria, and study
them using archival data. We find 4XMM J165251.5-591503 to possess a bright
and variable Galactic optical/IR counterpart, and so conclude it is very
likely to be a foreground interloper. 4XMM J091948.8-121429 does appear an
excellent ULX candidate associated with the dwarf irregular galaxy PGC 26378,
but has only one detection to date with low data quality. The best dataset
belongs to 4XMM J112054.3+531040 which we find to be a moderately variable,
spectrally hard ($\Gamma\approx 1.4$) X-ray source located in a spiral arm of
NGC 3631. Its spectral hardness is similar to known PULXs, but no pulsations
are detected by accelerated pulsation searches in the available data. We
discuss whether other missions provide objects for similar studies, and
compare this method to others suggested for identifying good PULX candidates.

###### keywords:

X-rays: binaries

††pubyear: 2023††pagerange: Digging a little deeper: characterising three new
extreme ULX candidates–Digging a little deeper: characterising three new
extreme ULX candidates

##  1 Introduction

Ultraluminous X-ray sources (ULXs; see Kaaret et al. 2017) remain a compelling
class of sources to study, despite more than two decades elapsing since the
realisation that new and exciting astrophysics were required to explain their
extraordinary X-ray luminosities of more than $10^{39}\rm~{}erg~{}s^{-1}$
(e.g. King et al. 2001). In fact, our understanding has evolved substantially
from the original focus on ULXs as intermediate-mass black hole candidates
(IMBHs; Colbert & Mushotzky 1999) to the detection of pulsations in some
objects (Pulsating ULXs, or PULXs, e.g. Bachetti et al. 2014). The pulsations
reveal the presence of a neutron star (NS) and hence very extreme accretion
rates, that can reach apparent factors $\sim 500$ above Eddington (Israel et
al., 2017a; Fürst et al., 2017). The observed phenomenology of ULXs is also
suggestive of super-Eddington accretion, with the observed X-ray spectra
(Gladstone et al., 2009; Bachetti et al., 2013), the correlated spectral and
temporal variability behaviour (Sutton et al., 2013b), the detection of fast
outflows (Pinto et al., 2016) and the presence of large bubble nebulae (Pakull
& Mirioni, 2002) strongly supporting this interpretation; this makes ULXs
important to study in the context of the rapid formation of the earliest
supermassive black holes (e.g. Bañados et al. 2018). ULXs may also have links
with other exotic phenomena, for example they may constitute an evolutionary
phase in the binary stellar systems that ultimately merge and are detected as
gravitational wave sources (Mondal et al., 2020a) and may be the systems
responsible for Fast Radio Bursts (Sridhar et al., 2021).

The requirement for novel accretion physics is particularly pertinent for
explaining ULXs that appear with luminosities in the $10^{40}-10^{41}~{}\rm
erg~{}s^{-1}$ regime, sometimes described as extreme ULXs, or eULXs
(Gladstone, 2013). This is a distinct, separate class from the yet more
luminous and rarer hyperluminous X-ray sources (HLXs) that appear above
$10^{41}~{}\rm erg~{}s^{-1}$ and remain the best candidates to host IMBHs, the
archetype being ESO 243-49 HLX-1 (Farrell et al., 2009). Given their extreme
luminosities, eULXs are relatively well-studied and provide many of the
archetypes for ULX behaviour that drive our understanding of it (e.g. Ho IX
X-1, Ho II X-1, NGC 5408 X-1, NGC 1313 X-1 etc; see Kaaret et al. 2017 and
references therein). Data from such objects have driven many of the
breakthroughs in understanding ULXs, from the curvature in their spectra above
2 keV (e.g. Ho IX X-1, Gladstone et al. 2009), to the detection of absorption
lines from outflowing gas travelling at $v\approx 0.2c$ (e.g. NGC 1313 X-1,
Pinto et al. 2016) and the detection of pulsations indicative of NSs (e.g. M82
X-2, Bachetti et al. 2014). Indeed, the majority of known PULXs reach this
regime at their brightest, these being M82 X-2; NGC 1313 X-2 (Sathyaprakash et
al., 2019); NGC 7793 P13 (Fürst et al., 2016); and NGC 5907 ULX, which peaks
in the HLX regime (Israel et al., 2017a). These luminosities are indicative of
NSs with accretion rates at least $50-100$ times their Eddington limit.

Many of the current key questions for ULXs relate to PULXs. The demographics
of ULXs remain uncertain in terms of the proportion of the overall population
that host a NS rather than a BH, with some suggestions that NS may dominate
(e.g., Pintore et al. 2017; Koliopanos et al. 2017; Middleton & King 2017;
Walton et al. 2018). The astrophysics of super-Eddington accretion onto NSs
also remains a matter for debate, with the magnetic field strength and
configuration (dipole/quadrupole) and the extent to which classical super-
critical accretion models apply, in which a geometrically thick inner disc
forms and a massive radiation-pressure driven wind is ejected from its
surface, all key areas of uncertainty (e.g., Kluzniak & Lasota 2015; Mushtukov
et al. 2015; Dall’Osso et al. 2015; Mushtukov et al. 2019). A key to
progressing all these issues will be to find more PULXs, that will add to our
population statistics and provide new observations that will help constrain
our models of accretion on to neutron stars. In this paper we examine whether
the observational quirk that most detected PULXs reach luminosities above
$10^{40}\rm~{}erg~{}s^{-1}$ can be leveraged to find new PULXs, basing our
search around the recent large multi-mission ULX catalogue of Walton et al.
(2022) (hereafter W22). The paper is arranged as follows. We discuss the
selection of targets in Section 2, and the reduction of the X-ray data for our
chosen targets in Section 3. The results are laid out in Section 4, and
discussed in Section 5, before the paper is concluded.

##  2 Source selection

Figure 1: The selection of interesting sources. The high flux, high luminosity
region used to select sources is delineated by a dashed red line. Source
positions in this parameter space are marked by a black cross, with size
matched to the $1\sigma$ uncertainties on these quantities (with a minimum
cross size adopted for display purposes for those objects with extremely well-
constrained values). Three sources are highlighted for appearing multiple
times in the region of interest: they are: red circles – M82 X-1; blue squares
– NGC 1313 X-1; green diamonds – NGC 5907 ULX. The diagonal tracks are a
trivial result of the scaling of flux by distance squared to give luminosity.

The selection of interesting targets began with our recent multi-mission ULX
catalogue, W22, and a simple observation: that 4 out of 6 known extragalactic
PULXs have been seen to exceed a luminosity of $10^{40}\rm~{}erg~{}s^{-1}$.
This compares to 1 in 4 ULX detections exceeding this threshold from 4XMM-DR10
and 2SXPS, and 1 in 6 from CSC2.0, in the W22 catalogue. Even more starkly, an
integration in the ULX regime, both above and below
$10^{40}\rm~{}erg~{}s^{-1}$, of the X-ray luminosity function of X-ray
binaries in star forming galaxies from Mineo et al. (2012) shows that only 1
in 9 ULXs should appear above this threshold luminosity. However, a bias to
high luminosity ULXs in pulsation detections should perhaps be expected, given
those detections require photon-rich data, and that is more immediately
forthcoming from higher luminosity sources at a given distance and exposure
length. Nevertheless, this preponderance presents an interesting basis from
which to search for new PULXs. We therefore filtered W22 to select ULXs with
both a luminosity between $10^{40}$ and $10^{41}\rm~{}erg~{}s^{-1}$, i.e. in
the eULX range, and an observed flux sufficiently high that a pulsation
detection could be possible given a moderately deep observation, which we set
at $5\times 10^{-13}\rm~{}erg~{}cm^{-2}~{}s^{-1}$111PULX detections tend to
come from data with $\gtrsim 10000$ pn counts (G. Israel, priv. comm.); at a
minimum flux of $5\times 10^{-13}\rm~{}erg~{}cm^{-2}~{}s^{-1}$ and a hard,
PULX-like spectrum (e.g. power-law continuum with $\Gamma\sim 1.5$ and column
$N_{\rm H}\sim 2\times 10^{21}\rm~{}cm^{-2}$) this can be obtained in $\sim
100$ ks, i.e. within a single XMM-Newton orbit, even if we allow for some data
loss to background flares (see Section 3). We note that such datasets are rare
in the archives for all but a handful of well-studied ULXs; here we focus on
analysing the currently available data, with a view to proposing for the
necessary observations if any interesting sources are identified.. We also
limit our analysis to XMM-Newton data, given that the pn is the only detector
currently operating in the 0.5-10 keV band with the combination of effective
area and readout time that regularly permits the detection of ULX pulsations
(we discuss what similar selection criteria reveal for Swift and Chandra in
Section 5).

We show the flux-luminosity parameter space for the XMM-Newton detections in
W22 in Fig. 1, with the region of interest delineated. The fluxes used are
taken directly from the 4XMM-DR10 EP_8_FLUX column, which is the flux in the
broad 0.2-12 keV band (cf. Webb et al. 2020) , with the luminosities
calculated directly from these fluxes using the distances assumed in W22. Note
there are many other ULX detections at similar fluxes but lower luminosities,
which will be the subject of future work. There is also one detection at high
flux in the HLX regime; this object will be included in a new study of HLXs
(Mackenzie et al., in prep.). In total, 49 detections of of 15 ULXs are within
the interesting parameter space; we list these objects in Table 1. Three
objects dominate the detections by number, and are highlighted in the figure:
M82 X-1 (10 detections), NGC 1313 X-1 (16) and NGC 5907 ULX1 (7). These are
amongst the best-studied ULXs (for example references, see Table 1), and
indeed the majority of these objects (12/15) are already well-studied in the
literature. However, three of the eULXs – 4XMM J091948.8-121429, 4XMM
J112054.3+531040 and 4XMM J165251.5-591503 – have not been examined in detail
before (with 4XMM J112054.3+531040 the only to have been previously-
catalogued). These three sources are the subject of the remainder of this
work.

Table 1: ULXs detected with high flux and high luminosity by XMM-Newton in W22

Source ID | Host galaxy |  $d$ a |  $L_{\rm X,peak}$ b | # detns c | Other name d | References d
---|---|---|---|---|---|---
(4XMM J…) |  | (Mpc) | ($\times 10^{40}\rm~{}erg~{}s^{-1}$) |  |  |
022233.4+422027 | NGC 891 | 9.1 | $2.40\pm 0.01$ | 1(6) | NGC 891 ULX1 |  Earley et al. (2021), Hodges-Kluck et al. (2012),
|  |  |  |  |  | Wang et al. (2016)
022727.5+333443 | NGC 925 | 8.7 |  $4.5\pm 0.3$ (S) | 1(1) | NGC 925 ULX-1 |  Salvaggio et al. (2022), Pintore et al. (2018),
|  |  |  |  |  | Swartz et al. (2011)
031819.9-662910 | NGC 1313 | 4.2 |  $2.8\pm 0.2$ (S) | 16(29) | NGC 1313 X-1 |  Pinto et al. (2020), Bachetti et al. (2013),
|  |  |  |  |  |  Feng & Kaaret (2006), Colbert & Ptak (2002)
034615.8+681113 | IC 342 | 3.4 | $1.71\pm 0.01$ | 1(6) | IC 342 X-2 |  Rana et al. (2015), Mak et al. (2011),
|  |  |  |  |  |  Roberts et al. (2008), Fabbiano & Trinchieri (1987)
072647.8+854550 | NGC 2276 | 39.3 |  $9.9\pm 1.5$ (S) | 1(1) | NGC 2276 3c |  Mezcua et al. (2015), Sutton et al. (2012),
|  |  |  |  |  | Liu (2011)
091948.8-121429 | PGC 26378 | 26.5 | $6.6\pm 2.2$ | 1(1) | - | -
095550.4+694045 | NGC 3034 | 3.5 | $8.50\pm 0.02$ | 10(10) | M82 X-1 |  Brightman et al. (2020), Pasham et al. (2014),
|  |  |  |  |  |  Kaaret et al. (2006), Matsumoto et al. (2001)
112015.7+133514 | NGC 3628 | 10.5 |  $3.1\pm 0.2$ (S) | 1(1) | NGC 3628 X-1 |  Heil et al. (2009), Stobbart et al. (2006),
|  |  |  |  |  | Strickland et al. (2001)
112054.3+531040 | NGC 3631 | 20.1 |  $4.4\pm 1.3$ (S) | 2(4) | - |  Kovlakas et al. (2020), Liu (2011)
131519.5+420301 | NGC 5055 | 9.0 |  $6.7\pm 1.2$ (S) | 2(2) | NGC 5055 X-1 |  Mondal et al. (2020b), Berghea et al. (2008),
|  |  |  |  |  | Roberts & Warwick (2000)
143242.2-440939 | NGC 5643 | 16.1 |  $6.0\pm 1.8$ (S) | 3(3) | NGC 5643 X-1 |  Kosec et al. (2021), Krivonos & Sazonov (2016),
|  |  |  |  |  |  Pintore et al. (2016), Guainazzi et al. (2004)
151558.6+561810 | NGC 5907 | 17.1 |  $11.6\pm 3.2$ (S) | 7(10) | NGC 5907 ULX1 |  Fürst et al. (2023), Israel et al. (2017a),
|  |  |  |  |  |  Walton et al. (2016), Sutton et al. (2013a)
165251.5-591503 | NGC 6221 | 11.9 | $3.1\pm 0.3$ | 1(1) | - | -
230457.6+122028 | NGC 7479 | 36.8 | $9.2\pm 0.4$ | 1(3) | NGC 7479 ULX-1 |  Earnshaw et al. (2018), Sutton et al. (2012)
|  |  |  |  |  | Walton et al. (2011)
235751.0-323726 | NGC 7793 | 3.6 |  $1.5\pm 0.1$ (S) | 1(9) | NGC 7793 P13 |  Fürst et al. (2021), Israel et al. (2017b),
|  |  |  |  |  |  Motch et al. (2014), Read & Pietsch (1999)

Notes: a distances are as per adopted by W22. b Peak luminosity detected from
the ULX, taken from W22. If this is from a Swift XRT detection we add an (S)
to the column; no parentheses indicates an XMM-Newton detection as there were
no peak luminosities observed by Chandra . c Number of times detected in the
high flux, high luminosity regime. Total number of XMM-Newton detections in
W22 are given in parentheses. d Some examples of nomenclature and prior
literature for the ULXs are given, but neither is intended as an exhaustive
list.

##  3 Data reduction

Table 2: Summary of datasets used in this work

ULX | Mission | ObsID | Date | Exposure a | Count rate b
---|---|---|---|---|---
(4XMM J) |  |  | (YYYY-MM-DD) | (ks) | (ct s-1)
091948.8-121429 | XMM-Newton | 0694440301 | 2012-06-07 | 3.0/7.4/7.1 | 0.12 c
112054.3+531040 | Chandra | 3951 | 2003-07-05 | 89.1 | $48\times 10^{-3}$
| Swift | $00034428001\rightarrow 00034428026^{d}$ | 2016-03-15 $\rightarrow$ 2016-10-26 | 42.0 | $(6-23)\times 10^{-3}$
| XMM-Newton | 0762610401 | 2016-04-18 | 6.2/8.5/8.5 | 0.17
| XMM-Newton | 0762610701 | 2016-04-20 | 6.2/8.5/8.5 | 0.18
| XMM-Newton | 0762610801 | 2016-04-22 | 6.2/8.5/8.5 | 0.17
| XMM-Newton | 0762610501 | 2016-05-15 | 18.5/22.4/22.4 | 0.29
| Swift | $00093203001\rightarrow 00093203005$ | 2017-09-18 $\rightarrow$ 2017-10-13 | 3.2 | $<23\times 10^{-3}$
165251.5-591503 e | XMM-Newton | 0405380201 | 2007-02-16 | 8.7/16.6/16.5 |  $<2.9\times 10^{-3}$ f
| XMM-Newton | 0405380901 | 2007-03-25 | 6.2/7.3/7.5 | 0.13 g
| Swift | $00081199002\rightarrow 00081199004$ | 2016-05-24 $\rightarrow$ 2016-05-26 | 6.9 | $<8\times 10^{-3}$

Notes: a Detector live time for central chip of Chandra and XMM-Newton, or sum
of exposures for Swift. For XMM-Newton this is shown as pn/MOS1/MOS2, and
quoted post-filtering for good time intervals (see text). b This is shown for
Swift as either the range of count rates measured in individual observations
(top line), or the upper limit for a sequence with no $3\sigma$ detections
(lower lines). Note two instances of higher $3\sigma$ upper limits – up to
$<31\times 10^{-3}\rm~{}ct~{}s^{-1}$ – were present in observations in the top
line. The XMM-Newton count rates are combined across all three EPIC detectors
unless otherwise noted, and corrected to the equivalent on-axis count rate. c
pn-only count rate.d There were no observations numbered 00034428006 or
00034428011. e The position of 4XMM J165251.5-591503 was covered by a third
observation, 0690580101, but the position of the ULX candidate was at the edge
of the field-of-view and no detection of it was present from this dataset in
4XMM-DR10. We therefore do not analyse this data. f $3\sigma$ upper limit for
aperture photometry for combined MOS1 and MOS2 data. g Combined MOS1 and MOS2
count rate.

The primary focus of this work were the datasets in which the catalogued ULX
detections were made. These XMM-Newton observations, alongside complementary
data from Chandra and Swift where analysed, are listed in Table 2. This also
provides an indication of the amount of useful exposure per observation, and
the count rate detected from each ULX during the observations.

The XMM-Newton data were reduced using the science analysis system
(SAS)222https://www.cosmos.esa.int/web/xmm-newton/sas version 20.0.0, with our
procedures based largely on the associated analysis
threads333https://www.cosmos.esa.int/web/xmm-newton/sas-threads. All XMM-
Newton data in Table 2 was taken in full-frame mode in all detectors. We began
by reprocessing the data using up-to-date calibration files, and then checked
the high energy (10-12 keV) light curve for each full dataset to determine
whether background flare filtering was necessary. This was not necessary for
any of the datasets for 4XMM J112054.3+531040 where the full-field count rates
were always below the suggested nominal cut-off rates for filtering
($0.35\rm~{}ct~{}s^{-1}$ for the MOS detectors and $0.4\rm~{}ct~{}s^{-1}$ for
the pn), with the exception of small number of 100 s pn bins which only
marginally exceeded the threshold and so were retained. In contrast, both
datasets for 4XMM J165251.5-591503 required flare filtering, with the standard
thresholds used for observation 0405380201 resulting in the loss of $\sim
10\%$ of the MOS exposure length, and $\sim 50\%$ of that from the pn. The
flaring was much more extreme for 0405380901, where standard filters would
have resulted in very little exposure surviving; we therefore adopted much
higher threshold for both MOS ($2\rm~{}ct~{}s^{-1}$) and pn
($10\rm~{}ct~{}s^{-1}$), resulting in the loss of $\sim 35\%$ of the original
MOS data, and up to $\sim 75\%$ of the pn exposure. The single exposure
covering 4XMM J091948.8-121429 was also badly affected by flaring. After the
application of the nominal cut-offs, only $\sim 30\%$ of the MOS exposure was
retained, and $<20\%$ of that from the pn.

A barycentric correction was applied to the event lists. Light curves and
spectra were extracted for 4XMM J112054.3+531040 from a 20-arcsecond radius
circular aperture centred on the source, with background data extracted from a
nearby circular region on the same chip (and at as similar a distance from the
readout nodes as possible in pn data) with radius 40 arcseconds. 4XMM
J165251.5-591503 was 11-12 arcminutes off-axis in each dataset and so larger
apertures were used, of 30 arcsecond radius for the source, and 60 arcseconds
for the background aperture. Similar large apertures were also used for 4XMM
J091948.8-121429 which was even further off-axis. All light curves were
extracted in the 0.2-10 keV band using events flagged as good (the
#xmmea$\\_$em and #xmmea$\\_$ep selection criteria for the MOS and pn
respectively). We also selected on event pattern, with a threshold of $\leq 4$
for pn data (single and double events) and $\leq 12$ for MOS (which also
includes triples and quadruples). We used epiclccorr to subtract background
counts and correct the light curves for instrumental effects such as
vignetting and deadtime, and where we co-added light curves over the three
different detectors we ensured the light curves had the exact same start and
stop times (taken from the pn data). Spectra were extracted using the same
patterns and flags as the light curves, excepting that the more stringent FLAG
$=0$ was used for the pn. Response matrices (rmf files) and ancillary response
files (arf) were produced for each spectrum, with the latter incorporating a
correction such the spectra better align with NuSTAR calibration. Finally, the
spectra were binned to a minimum of 25 counts per bin and with an oversampling
factor limited to three times the intrinsic energy resolution of the detector
across all photon energies.

The Swift data utilised in the analysis of 4XMM J112054.3+531040 were all
obtained directly from online tools associated with the 2SXPS
catalogue444https://www.swift.ac.uk/2SXPS/ (Evans et al., 2020). The stacked
spectrum, composed of all XRT data for the ULX, was obtained directly from the
2SXPS interface, which also provided appropriate background data and response
(rmf and arf) files. The spectral data were binned to 20 counts per bin before
fitting. The Swift data points contributing to the full light curve were
extracted on the basis of one point per observation, with the data either
displayed as a detection (with corresponding $1\sigma$ error) where the count
rate exceeded three times the error, or as a $3\sigma$ upper limit in other
cases.

We also include the analysis of an archival Chandra dataset for 4XMM
J112054.3+531040. We reduced this data using the Chandra interactive analysis
of observations software package,
ciao555https://cxc.harvard.edu/ciao/index.html version 4.14, and version 4.9.8
of the Chandra calibration database. Our reduction again relied heavily on the
provided science threads666https://cxc.harvard.edu/ciao/threads/index.html.
The data was reprocessed and data products for the ULX were extracted from an
8-pixel ($\sim 4$ arcsecond) radius aperture centred on the source. Given the
proximity of a second, much fainter source (about 7 arcseconds to the south-
west) we chose to use a separate background region rather than an annulus,
which we set as a 20-pixel circular aperture to the north-west of the ULX. We
then extracted the source and background spectra, and corresponding response
files, using the specextract tool, and grouped the output spectrum to a
minimum of 20 counts per bin before analysis. The events file was barycentre-
corrected and then background-subtracted light curves were extracted using the
same regions and the dmextract tool. Finally, we attempted to produce an
improved position for 4XMM J112054.3+531040 by correcting the astrometry of
the Chandra data to corresponding optical counterparts in the Gaia DR2
catalogue (see Section 4.2.3 for more details).

##  4 Results

###  4.1 4XMM J091948.8-121429

Figure 2: The environment of 4XMM J091948.8-121429 shown as a 3-colour
PanSTARRs image. The red, green and blue colours represent light observed in
the $i$, $r$ and $g$ filters respectively. The data in each filter is is
convolved with a 2-pixel ($\equiv 0.5$ arcsecond) Gaussian kernel for display
purposes. A circle of radius 6.25 arcseconds marks the $3\sigma$ error in the
position of the ULX as determined in 4XMM-DR10, and the field of view is
$2\times 2$ arcminutes2. The PanSTARRs data was obtained from
http://ps1images.stsci.edu/cgi-bin/ps1cutouts.

This candidate ULX is associated with the dwarf galaxy PGC 26378 (also known
as DDO 060 or MCG -02-24-011), at a distance of 26.5 Mpc (W22). It appears co-
located with a knot of emission about 30 arcseconds north of the nominal
centre of the host galaxy, as shown in Fig. 2. It is only detected by XMM-
Newton and inspection of the reduced data of the single observation covering
its position reveals it to lie at the very edge of the pn field of view, at
$\sim 16$ arcminutes off-axis. It was not detected in either MOS image given
that the ’good’ event flags filter used to clean the data reject events so far
off-axis. Hence, only 3 ks of pn data for this source were available for
analysis, from which we had $<100$ source counts777Given the low detected
count rate and severe flaring, taking a higher threshold for the background
filtering resulted in background domination at high and low energies, e.g.
below 0.5 and above 4 keV for the 10 count s-1 GTI filter used for 4XMM
J165251.5-591503. The resulting spectral constraints were no better than those
from the method detailed in the text.. Strong constraints on the source
properties and behaviour are therefore not possible without obtaining further
data.

However, we were able to obtain some provisional constraints on the ULX
properties by analysing its pn spectrum. In particular, we extracted the
spectrum and then binned it only on the oversampling parameter, such that we
did not oversample the energy resolution (precisely as per other XMM-Newton
spectra analysed in this work); only we did not specify any minimum number of
counts per bin. This spectrum was then fitted in xspec888Version 12.12.1,
available as part of the heasoft package from
https://heasarc.gsfc.nasa.gov/docs/software/heasoft/. Throughout this work we
adopt the convention of quoting 90% errors on spectral fitting results. using
Cash statistics. We report the results for two simple models – an absorbed
power-law continuum, and an absorbed multi-colour disc blackbody spectrum – in
Table 3. The fits assumed a Galactic foreground column of $4.85\times
10^{20}\rm~{}cm^{-2}$, interpolated from Dickey & Lockman (1990) using the
colden interface999https://cxc.harvard.edu/toolkit/colden.jsp. Here and
throughout this paper we use the tbabs model for absorption (Wilms et al.,
2000). We find the spectrum to be relatively hard ($\Gamma\sim 1.6$ or
$kT_{\rm in}\sim 1.9$ keV), albeit with a very wide range of possible photon
indexes or disc temperatures, and with a relatively low intrinsic absorption
for a ULX ($\lesssim 6\times 10^{20}\rm~{}cm^{-2}$). The estimated flux is
$\sim 4\times 10^{-13}\rm~{}erg~{}cm^{-2}~{}s^{-1}$, again with a wide
uncertainty range, which equates to a 0.3-10 keV luminosity of $\sim 3\times
10^{40}\rm~{}erg~{}s^{-1}$ at the distance of PGC 26378.

Table 3: Single component spectral model fits for 4XMM J091948.8-121429

$n_{\rm H}~{}^{a}$ | $\Gamma/kT_{\rm in}~{}^{b}$ | $f_{\rm X}~{}^{c}$ | C-stat/dof$~{}^{d}$
---|---|---|---
power-law continuum |
$0.30^{+0.34}_{-0.25}$ | $1.6^{+0.8}_{-0.6}$ | $4.1^{+2.5}_{-1.6}$ | 29.7/37
multi-colour disc blackbody |
$<0.35$ | $1.9^{+4.8}_{-0.8}$ | $3.7^{+1.3}_{-1.4}$ | 31.2/37

Notes: a Absorption in excess of foreground Galactic ($\times
10^{21}\rm~{}cm^{-2}$). b Photon index for power-law, or inner-disc
temperature (in keV) for disc blackbody. c Observed 0.3-10 keV flux, corrected
for foreground Galactic absorption ($\times
10^{-13}\rm~{}erg~{}cm^{-2}~{}s^{-1}$).d C-statistic value and number of
degrees of freedom for fit.

###  4.2 4XMM J112054.3+531040

This ULX candidate has the richest dataset of the three we examine in the
section, with data from all three missions covered by the W22 catalogue. We
separate out the more detailed analysis this facilitates into three sections
below.

####  4.2.1 X-ray spectra

The spectra for 4XMM J112054.3+531040 were all extracted and binned as
detailed in Section 3. After background subtraction they had sufficient counts
to permit fitting using the $\chi^{2}$ statistic. In this analysis the XMM-
Newton and Swift data were fitted in the 0.3-10 keV band, and the Chandra data
were fitted in the narrower 0.5-8 keV regime commensurate with its more
limited spectral response. As an initial step the data were all fitted
separately with simple power-law continuum and multi-colour disc blackbody
models. For each spectrum we included a foreground absorption component set to
$1.02\times 10^{20}\rm~{}cm^{-2}$, derived from colden as above. We also
included a constant component for each XMM-Newton observation to model slight
calibration differences between the detectors; in practise differences in this
component between detectors never exceeded $15\%$ for any individual
observation. The results of these fits are displayed in Table 4. It is
immediately obvious that this ULX is relatively hard, with a photon index
$\Gamma$ that does not deviate substantially from $1.4$, and with moderate
absorption beyond our own Galaxy (and so likely to be intrinsic to the ULX or
its host galaxy) of $\lesssim 10^{21}\rm~{}cm^{-2}$; the equivalent parameters
for the disc blackbody model are $kT_{\rm in}\sim 2$ keV and negligible column
in excess of Galactic. The power-law provides a statistically-acceptable fit
to all spectra; however this is not the case for all disc-blackbody fits, with
XMM-Newton observations 0762610801 and 0762610501 not providing acceptable
fits (null hypothesis probability $<5\%$). We also show a flux for each
observation, which is the observed flux corrected only for foreground Galactic
absorption, as calculated using the cflux convolution model in xspec. The ULX
does appear to vary in flux, albeit only by a factor $\sim 2$ between
different observations.

Table 4: Single component spectral model fits

ObsID | $n_{\rm H}~{}^{a}$ | $\Gamma/kT_{\rm in}~{}^{b}$ | $f_{\rm X}~{}^{c}$ |  $\chi^{2}$/dof$~{}^{d}$
---|---|---|---|---
power-law continuum |  |
3951 | $1.24^{+0.38}_{-0.36}$ | $1.38\pm 0.08$ | $5.5\pm 0.3$ | 130/144
Swift stack | $<1.62$ | $1.21^{+0.26}_{-0.17}$ | $5.4^{+0.8}_{-0.9}$ | 19/16
0762610401 | $1.30^{+0.84}_{-0.72}$ | $1.57^{+0.19}_{-0.17}$ | $3.6^{+0.4}_{-0.5}$ | 34/27
0762610701 | $<1.22$ | $1.23^{+0.16}_{-0.15}$ | $4.4^{+0.6}_{-0.5}$ | 16/29
0762610801 | $<1.13$ | $1.46^{+0.17}_{-0.15}$ | $3.5^{+0.6}_{-0.4}$ | 36/29
0762610501 | $0.83^{+0.23}_{-0.21}$ | $1.45\pm 0.06$ | $6.5^{+0.3}_{-0.5}$ | 128/127
multi-colour disc blackbody |  |
3951 | $<0.14$ | $1.90^{+0.14}_{-0.12}$ | $4.6\pm 0.2$ | 139/144
Swift stack | $<0.58$ | $2.09^{+0.62}_{-0.4}$ | $4.4\pm 0.7^{e}$ | 17/16
0762610401 | $<0.38$ | $1.52^{+0.22}_{-0.19}$ | $3.0\pm 0.4$ | 34/27
0762610701 | $0^{f}$ | $2.16^{+0.41}_{-0.3}$ | $3.7\pm 0.5$ | 21/30
0762610801 | $0^{f}$ | $1.62^{+0.24}_{-0.2}$ | $3.0\pm 0.4$ | 50/30
0762610501 | $<2.7\times 10^{-2}$ | $1.87^{+0.11}_{-0.10}$ | $5.8\pm 0.3$ | 194/127

Notes: a Absorption in excess of foreground Galactic ($\times
10^{21}\rm~{}cm^{-2}$). b Inner disc temperature in keV. c Observed 0.3-10 keV
flux, corrected for foreground Galactic absorption ($\times
10^{-13}\rm~{}erg~{}cm^{-2}~{}s^{-1}$). d $\chi^{2}$ value and number of
degrees of freedom for fit. e Absorption fixed at 0 in order to obtain error
range.

Figure 3: Unfolded two-component spectral fits for 4XMM J112054.3+531040.
(Top) Chandra spectrum, with data points shown as crosses (in blue). The best
fitting model is the solid line, and the hot and cool disc components are
shown as dotted and dashed lines respectively. (Middle) Combined spectral data
from XMM-Newton observations 07262610401, 0762610701 & 0762610801\. Model
components are indicated as per the top panel (with the slight offsets from
the different constants in the modelling). Data from the pn is shown as simple
crosses (in black), MOS1 is highlighted by a circle (red) and MOS 2 by a
square (green). (Bottom) Data from XMM-Newton observation 0762610501,
displayed similarly to the middle panel.

Given the similarity of the spectral parameters across all of the X-ray
observations, we attempted to fit all the spectra simultaneously with the same
power-law model, allowing only the relative constant differences between the
XMM-Newton detectors to vary. This did not produce a good fit to the data when
the normalisation of the power-law continua were all constrained to the same
value ($\chi^{2}=681.5$ for 391 degrees of freedom). However, permitting the
normalisations to vary (and so the flux of the source to vary between epochs)
produced a substantial improvement of $\Delta\chi^{2}=278$ for 5 fewer degrees
of freedom, and a statistically-acceptable fit to the data. Further unfreezing
of fit parameters did not result in large statistical improvements – a small
but not very significant improvement of $\Delta\chi^{2}=22$ for 5 fewer
degrees of freedom resulted from thawing the photon index, and minimal
improvement resulting from thawing the absorption component
($\Delta\chi^{2}=6$ for 5 fewer degrees of freedom). We therefore conclude
that there is no strong evidence for variability in either the absorption
component or the spectral shape throughout the observations. We present the
best-fitting power-law and disc-blackbody parameters where absorption and
photon index/inner-disc temperature are constrained to the same values across
all spectra in Table 5. Note that the disc-blackbody model is not
statistically acceptable, as a result of the two individual spectra noted
above; it also does not require any absorption above Galactic foreground in
its best fit.

Table 5: Single component fits for 4XMM J112054.3+531040 with parameters
constrained to the same value across all spectra

$n_{\rm H}~{}^{a}$ | $\Gamma/kT_{\rm in}~{}^{b}$ |  $\chi^{2}$dof$~{}^{c}$
---|---|---
power-law continuum
$0.92\pm 0.15$ | $1.42\pm 0.04$ | 403.6/386
multi-colour disc blackbody
$0^{f}$ | $1.86\pm 0.07$ | 470.8/387

Notes: a Absorption in excess of foreground Galactic ($\times
10^{21}\rm~{}cm^{-2}$). b Photon index for power-law, or inner-disc
temperature (in keV) for disc blackbody. c $\chi^{2}$ value and number of
degrees of freedom for fit. f Value fixed to zero as model does not require
any additional absorption.

We also consider two-component fits to the spectra, composed of two thermal
components, consistent with modelling of good quality 0.3-10 keV ULX spectra
(e.g. Stobbart et al. 2006; Koliopanos et al. 2017). In order that we can
potentially place meaningful constraints we must use only the best quality
examples of the spectra of 4XMM J112054.3+531040 , which means the Chandra
spectrum and the 0762610501 XMM-Newton spectrum (both of which have in excess
of 100 bins). In addition, we note that the other three XMM-Newton spectra
have similar levels of flux and spectral parameters (Table 4), and were
obtained within a 5-day window in 2016 (Table 2). We therefore consider them
suitable for combining to a single spectrum per XMM-Newton detector, and to do
so used the SAS tool epicspeccombine to combine the data across the three
observations, before binning as previously described. This had similar
spectral quality to the other two datasets and so we used it in the two-
component spectral fitting.

Given the similarities of the individual datasets discussed above we also
adopted a simultaneous fitting process for the three higher quality spectra.
An initial fit held all values (other than the corrections for relative EPIC
detector calibrations) fixed across the three spectra, and a statistically-
poor fit resulted $\chi^{2}=652$ for 377 degrees of freedom). Thawing the
normalisations of the hot and cool disk blackbody components both resulted in
significant improvements to the fits, with $\Delta\chi^{2}=247$ and 27 (for 2
fewer degrees of freedom) for the hot and cool components respectively when
applied consecutively. However, thawing the disc temperatures and the
absorption did not result in any further, additional improvements to the fits
($\Delta\chi^{2}\leq 5$ for 2 degrees of freedom), so we keep those values the
same across all 3 datasets. The resulting fit is shown in Table 6, where we
also show the intrinsic fluxes of each disc blackbody component (as calculated
using cflux). The absorption and disc component temperatures are within the
range of values observed from bright ULXs (cf. Koliopanos et al. 2017; Walton
et al. 2018), albeit towards the harder end of the range. The ratio between
the flux in either component is rather high, and interestingly may vary
between the Chandra observation in 2003 and the XMM-Newton observations in
2016, with $f_{\rm X,2}/f_{\rm X,1}=10\pm 4$ in the earlier epoch, and
$(6-7)\pm 3$ in the latter (note these are $90\%$ and not $1\sigma$ errors).
We illustrate these fits in Fig 3, where we show the unfolded spectra and both
underlying model components.

Table 6: Two component spectral fits for 4XMM J112054.3+531040

ObsID | $n_{\rm H}~{}^{a}$ | $kT_{\rm in,1}~{}^{b}$ | $kT_{\rm in,2}~{}^{b}$ | $f_{\rm X,1}~{}^{c}$ | $f_{\rm X,2}~{}^{c}$ |  $\chi^{2}$/dof d
---|---|---|---|---|---|---
3951 |  |  |  | $0.5\pm 0.2$ | $4.8\pm 0.2$ |
Combined ($401+701+801$) | $0.29^{+0.29}_{-0.24}$ | $0.48^{+0.17}_{-0.11}$ | $2.69^{+0.54}_{-0.3}$ | $0.5^{+0.2}_{-0.1}$ | $3.2^{+0.2}_{-0.3}$ | 377.8/373
0762610501 |  |  |  | $0.8^{+0.3}_{-0.2}$ | $5.5\pm 0.4$ |

Notes: Where a value is shown solely in the middle row, it is the result of a
simultaneous fit to all 3 datasets. a Absorption in excess of foreground
Galactic ($\times 10^{21}\rm~{}cm^{-2}$). b Inner-disc temperature (in keV)
for disc blackbody components. c Intrinsic flux of component in 0.3-10 keV
band ($\times 10^{-13}\rm~{}erg~{}cm^{-2}~{}s^{-1}$); this value is
extrapolated beyond the fitted energy range for the Chandra data. d $\chi^{2}$
value and number of degrees of freedom for fit.

####  4.2.2 X-ray variability

We have composed a long-term light curve for 4XMM J112054.3+531040 from the
archival XMM-Newton, Chandra and Swift data, which we display in Fig 4. The
XMM-Newton and Chandra fluxes were taken directly from the individual power-
law spectral fits and converted to a luminosity for a distance of 20.1 Mpc;
the Swift fluxes were calculated based on a conversion factor of
$1\rm~{}ct~{}s^{-1}\equiv 5.65\times 10^{-11}\rm~{}erg~{}cm^{-2}~{}s^{-1}$,
derived from the best fit spectral model in the
pimms101010https://cxc.harvard.edu/toolkit/pimms.jsp calculator. The light
curve shows that 4XMM J112054.3+531040 is moderately variable on timescales of
days (up to factors of $\sim 5$ in Swift data), but has remained luminous in
all observations to date with $L_{\rm X}$ (0.3-10 keV) persistently
$>10^{40}\rm~{}erg~{}s^{-1}$. However, coverage is limited, with most
observations in a short window in 2016 as the XMM-Newton and Swift
observations were a follow-up programme for a supernova, AT2016bau (see Arbour
2016; Granata et al. 2016). The supernova lies $\sim 45$ arcseconds from the
ULX, in the direction of the centre of the host galaxy (cf. Figure 7), and
remained undetected in the XMM-Newton and Swift data. We note the only period
of observations without a detection were the five follow-up observations with
Swift in late 2017. These observations were short and so do not provide
stringent individual limits, however combining their data provides a $3\sigma$
upper limit on the luminosity of $<2.05\times 10^{40}\rm~{}erg~{}s^{-1}$ for
that period, similar to the lowest detected luminosities from a year earlier.

Figure 4: Long-term light curve for 4XMM J112054.3+531040 from all missions.
The Chandra observation is shown as a (green) square, XMM-Newton observations
are (red) circles, Swift $3\sigma$ detections are black crosses and $3\sigma$
upper limits from Swift are (blue) downwards arrows. Note the x-axis is broken
for display purposes, given the long (13-year) gap between the Chandra and
subsequent observations.

We also investigated the intra-observational variability in the XMM-Newton and
Chandra data. In Fig 5 we show summed EPIC light curves for all four XMM-
Newton observations. In each case we limit the light curves to the pn start
and stop times to ensure simultaneity across the three EPIC detectors, and bin
the data to 500 s intervals. Visual inspection of Fig 5 hints that the data
might vary in excess of that expected from white noise processes, and this is
confirmed by calculating the excess variance ($\sigma_{\rm XS}$; see Vaughan
et al. 2003) for each dataset, which in each case is in the range $4-9\%$. We
performed the same analysis on the Chandra dataset, binned to 1000 s given its
lower count rate, and found a similar $\sigma_{\rm XS}=7\%$; we show this
light curve in Fig. 6. This demonstrates that 4XMM J112054.3+531040 is
consistently varying on timescales as short as $<10$ minutes.

Figure 5: Combined EPIC light curves for 4XMM J112054.3+531040 from each
individual exposure, displayed with 500 s binning. Note the x-axis is broken
for display purposes. Figure 6: Chandra ACIS-S light curve for 4XMM
J112054.3+531040 shown with 1000 s binning.

In order to investigate variability at the shortest accessible timescales we
used the the stingray packages (Huppenkothen et al., 2019; Bachetti et al.,
2022), as scripted up in the hendrics tools111111Version 7.0, see
https://hendrics.stingray.science/en/stable/index.html.. We worked on the XMM-
Newton EPIC-pn data as its 73.4 ms frame time means it is the only data for
4XMM J112054.3+531040 with the time resolution adequate to access the $\sim 1$
Hz pulsations seen in PULXs. We extracted pn event files from the source
apertures for each XMM-Newton observation, and performed barycentric
corrections on each event list. We first used these events files to create
power spectra for each observation. Each power spectrum was subject to
geometric rebinning over a variety of factors in the range 0.01 – 0.3 before
inspection; however, there was no power above the white noise level in any of
the power spectra, which were sensitive to power in the $\sim 10^{-3}-6$ Hz
range. (We note this is consistent with the excess variance results above,
which are based on variability over longer timescales than probed by the power
spectra.) We then performed accelerated pulsation searches, using the hendrics
implementation of the Ransom et al. (2002) algorithm. Although each search
found candidate pulsations, these were statistically weak (highest powers in
the range 30 – 40), and were generally not recovered by $Z^{2}_{N}$ searches
focussing on a narrow range around the candidate frequency, so we do not
regard any as real pulsation candidates. This $Z^{2}_{N}$ test was used to
place limits on the amplitude of possible pulsations in the data; for the
shorter ($\sim 6$ ks in the pn) observations the $3\sigma$ upper limit on the
possible pulsation amplitude at frequencies $\gtrsim 1$ Hz was $\sim 45\%$,
and for the longer ($18$ ks, 0762610501 dataset) a more stringent limit on the
pulsation amplitude of $\sim 20\%$ at similar frequencies was calculated.

####  4.2.3 Optical follow-up

An accurate position for 4XMM J112054.3+531040 was obtained from the Chandra
data by considering matches between X-ray source detections on the S3 chip and
optical sources from Gaia DR2, as per the relevant science
thread121212https://cxc.cfa.harvard.edu/ciao/threads/reproject_aspect/. The
best solution was obtained from the raw data; any attempts to correct the
astrometry algorithmically induced false matches within the body of NGC 3631,
which resulted in no good matches in the field and an overall matching error
$>0.6$ arcseconds. If we used the raw data we instead found three excellent
matches and a statistical error of $0.14$ arcseconds on the field astrometry.
Using this astrometric solution we find a J2000 position for the eULX of
$11~{}20~{}54.306,+53~{}10~{}40.68$ $\pm 0.02$ arcseconds (X-ray centroid
error) $\pm 0.14$ arcseconds (astrometric uncertainty).

We then investigated the environment and possible counterparts of 4XMM
J112054.3+531040 using HST data. Specifically, the eULX position was covered
by three HST images. A pair of WFC3 UVIS images, in the F555W and F814W
filters, each of $\sim 750$ s exposure (datasets ID9610010 & ID9610020), were
taken in October 2016 and aimed at SN AT2016bau, as per most of the X-ray
data; and a deeper $\sim 2300$ s ACS WFC image was taken in April 2019, also
in the F814W filter (dataset JDXK07010). We display the latter, with the ULX
position highlighted in a zoom of its projected immediate vicinity, in Fig 7.
4XMM J112054.3+531040 clearly lies in a spiral arm to the west of the nucleus
of NGC 3631, and is associated with some structure within the arm, consistent
with it being a bona fide eULX rather than a background AGN.

Fig 7 shows two relatively bright sources within the $3\sigma$ uncertainty
region, and a third just outside. The central source appears potentially
extended towards the south-east, so may be an amalgamation of two (or more)
objects. The Hubble source catalog131313https://catalogs.mast.stsci.edu/hsc/
provides magnitudes in both filters from the 2016 WFC3 UVIS observation; both
objects within the error region have near-identical magnitudes of $m_{\rm
F555W}=23.86/23.87$ and $m_{\rm F814W}=23.68/23.66$, for the central and
north-western objects respectively, and hence both have a colour $m_{\rm
F555W}-m_{\rm F814W}\approx 0.2$. The object to the east of the error region
is very slightly brighter, with $m_{\rm F555W}=23.36$, $m_{\rm F814W}=23.51$
and so a colour of $m_{\rm F555W}-m_{\rm F814W}=-0.15$. After correcting for
minimal foreground extinction from within our own Galaxy, absolute magnitudes
of $M_{\rm F555W}\approx-7.7$ and $M_{\rm F814W}\approx-7.5$ can be calculated
for the two most likely counterparts. This combination of absolute magnitude
and slightly red colour is not a good match for any type of supergiant star,
but may perhaps instead be indicative of young stellar clusters in NGC 3631,
with the possibility of some reddening due to local dust extinction in the
spiral arm. It is also likely that the observed magnitudes of these
counterparts rule out a background AGN, given these typically have $f_{\rm
X}/f_{\rm opt}\sim 0.1-10$ (e.g., Aird et al. 2010), whereas $f_{\rm X}/f_{\rm
opt}>220$ for this eULX.

Figure 7: HST ACS WFC image of NGC 3631 in the F814W filter (main image, using
a heat colour map). The image is aligned such that North is up, and East to
the left. The location of 4XMM J112054.3+531040 is within the small white box,
and the region within the box is shown in detail in the insetted zoom, which
has size $4\times 4$ arcseconds2 and is displayed as a greyscale image. The
position of the eULX is highlighted by the red circle, which is equivalent to
the $3\sigma$ error region for the eULX position. The position of SN2016bau is
highlighted by the white star.

###  4.3 4XMM J165251.5-591503

The position of 4XMM J165251.5-591503 has been covered by 3 XMM-Newton
observations, but only one (ObsID 0405380901) provided a reasonably high
source count rate and this observation was heavily affected by flaring (cf.
Table 2 and Section 3). Worse still, the source lay at the very edge of the pn
detector where a sizeable fraction of the source extraction aperture lay
outside the field-of-view; we therefore concentrated our analysis on the MOS
detections of this source, where the flare contamination was also less
pronounced than for the pn. Spectra were extracted and fitted with simple
single component models, similarly to the previous sources. We report the
results of this analysis in Table 7. In this case the foreground column was
higher, at $1.53\times 10^{21}\rm~{}cm^{-2}$. We find the source to display a
relatively soft spectrum, with $\Gamma\sim 2.5$ for a power-law continuum, or
$kT_{\rm in}\sim 0.65$ keV for a multi-colour disc blackbody model. The latter
shows no evidence for absorption above the Galactic line-of-sight. Both models
provide formally acceptable fits to the data, although the $\chi^{2}$ is
better for the power-law model. The source flux (corrected for Galactic
absorption) is the highest for any of our three new eULX candidates at $\sim
10^{-12}\rm~{}erg~{}cm^{-2}~{}s^{-1}$. However, this is not a persistent flux;
we note that the upper limit on the count rate from a second observation
(taken roughly 5 weeks prior to the dataset fitted above) was a factor $\sim
45$ lower, so this object is strongly X-ray variable on a timescale of weeks.

This variability is corroborated by Swift data; the position of 4XMM
J165251.5-591503 is covered by three Swift observations (as listed in Table 2,
the target for which was NGC 6221), taken over 3 days in 2016 and totalling
6.9 ks of exposure. No source is detected at the ULX position in 2SXPS
analysis of this data. We have therefore performed aperture photometry at the
position of the source and find a combined $3\sigma$ upper limit on the flux
as $\lesssim 2\times 10^{-13}\rm~{}erg~{}cm^{-2}~{}s^{-1}$ (converting the
upper limits on the count rate to flux in pimms using the power-law spectrum
in Table 7). Although not as constraining as the second XMM-Newton
observation, this again highlights that this object is variable and, nine
years after the original detection, it had a factor $\geq 5$ lower flux
compared to the earlier epoch.

Table 7: Single component fits for 4XMM J165251.5-591503

$n_{\rm H}~{}^{a}$ | $\Gamma/kT_{\rm in}~{}^{b}$ | $f_{\rm X}~{}^{c}$ |  $\chi^{2}$dof$~{}^{d}$
---|---|---|---
power-law continuum |
$2.0_{-1.2}^{+1.5}$ | $2.5_{-0.4}^{+0.5}$ | $1.1_{-0.2}^{+0.3}$ | 54.4/50
multi-colour disc blackbody |
$0^{f}$ | $0.65_{-0.1}^{+0.13}$ | $0.9_{-0.2}^{+0.1}$ | 66.2/51

Notes: a Absorption in excess of foreground Galactic ($\times
10^{21}\rm~{}cm^{-2}$). b Photon index for power-law, or inner-disc
temperature (in keV) for disc blackbody. c Observed 0.3-10 keV flux, corrected
for foreground Galactic absorption ($\times
10^{-12}\rm~{}erg~{}cm^{-2}~{}s^{-1}$). d $\chi^{2}$ value and number of
degrees of freedom for fit. f Value fixed to zero as model does not require
any additional absorption.

The high foreground column is indicative that the line-of-sight to this eULX
candidate lies close to the Galactic plane. In fact, its Galactic coordinates
are $l_{\rm II}=329.72,b_{\rm II}=-9.60$, which lies both close to the
Galactic plane, and near to the direction of the Galactic centre. This,
combined with the soft spectrum, lead to a suspicion that this could be a
foreground Galactic source. We therefore conducted a more extensive check for
multi-wavelength counterparts and found that 4XMM J165251.5-591503 has a
bright IR counterpart, detected within $\sim 1$ arcsecond of the eULX
candidate position, with $m_{\rm K}=13.01\pm 0.03$ in the 2MASS all-sky point
source catalogue (Cutri et al., 2003). Given this strongly suggests a Galactic
counterpart we also checked Gaia-DR3 (Gaia Collaboration et al., 2022), and
found the counterpart with $m_{g,\rm mean}=15.6$ and a parallax of $0.41\pm
0.03$ milli-arcseconds. The presence of a parallax means that this counterpart
is clearly Galactic, and the measured value places it at a distance of $2.4\pm
0.2$ kpc. The apparent magnitude of the counterpart then converts to a mean
absolute magnitude of $M_{g}\approx 3.2$, correcting for foreground extinction
of $A_{g}=0.5$ (Schlafly & Finkbeiner 2011, via the NASA/IPAC extragalactic
database141414https://ned.ipac.caltech.edu), and the 0.3-10 keV X-ray
luminosity is $L_{\rm X}\approx 7\times 10^{32}\rm~{}erg~{}s^{-1}$.

To investigate its nature further we extracted a TESS light curve at its
position. TESS observed the target during Sector 12 (2019-May-21 to
2019-Jun-19) at 30 minute cadence. We extracted its light curve by defining
target and background apertures around the target and show the resulting light
curve in Fig 8. The counterpart displays a clear $\sim 2$ day modulation, on
top of a possible longer term variation. Given the Gaia distance and colour,
the position in the Gaia calibrated colour-magnitude diagram places this
system as a K-type star, with its absolute magnitude suggesting an evolved
type. It may therefore be possible that the 2-day modulation is related to the
orbital period of a binary, with the X-ray emission potentially originating in
colliding winds. Alternatively the optical variability could be related to a
super-orbital modulation caused by a precessing tilted disk as observed in
several cataclysmic variables (see e.g. Iłkiewicz et al. 2021); however it is
unclear what the origin of the X-ray emission might be in this scenario. A
third possible scenario is unrelated to the possible binary nature of the
stellar system; this may simply be a stellar flare. At close to
$10^{33}\rm~{}erg~{}s^{-1}$ this would be at the upper end of known flare
luminosities (cf. Table 4 of Güdel 2004), and the ratio of quiescent to flare
luminosity would also be rather extreme for a late stellar type (Pye et al.,
2015), but this is a plausible nature given its soft X-ray spectrum. It is
even possible that this optical counterpart is entirely unrelated to the X-ray
emission, which still might be originating in a bona fide ULX in NGC 6221. The
nature of this source therefore remains to be confirmed and will require
follow-up observations to resolve.

Figure 8: Light curve of the candidate counterpart to 4XMM J165251.5-591503
obtained with 30 minute cadence during Sector 12 of the TESS mission.

##  5 Discussion

###  5.1 Have we found any good PULX candidates?

In this paper we have identified and studied three new extreme ULX candidates,
selected on the basis of at least one high flux ($>5\times
10^{-13}\rm~{}erg~{}cm^{-2}~{}s^{-1}$) and high luminosity ($L_{\rm
X}>10^{40}\rm~{}erg~{}s^{-1}$) XMM-Newton detection in the ULX catalogue of
W22, with a view to identifying good PULX candidates. So, what have we learnt?

The first object, 4XMM J091948.8-121429, has insufficient data to determine
whether it is a good candidate to be a PULX. Its host is relatively distant at
26.5 Mpc, and its only detection has it 16 arcminutes off-axis in 3 ks of
cleaned pn data, so $<100$ counts were obtained from the source. This was
however sufficient to determine the object appears likely to be within its
host given its association with structure in PGC 26378, and that its spectrum
is likely to be moderately hard (although this is poorly constrained). It is
pertinent to note that the host galaxy is a dwarf irregular system; several
such systems are known to host eULXs, including some of the best studied local
objects (e.g. NGC 5408, Holmberg II). Indeed some of these objects are
particularly interesting as local analogues for processes at high redshift,
e.g. I Zw 18 (Kaaret & Feng, 2013) and Haro II (Prestwich et al., 2015). So,
4XMM J091948.8-121429 is at least a good candidate for a bona fide eULX, but
further observations are required to reveal the details of this interesting
object.

4XMM J112054.3+531040, in contrast, has a reasonable set of data already
available, largely thanks to follow-up of a supernova that detonated in the
host galaxy, NGC 3631, in 2016. This includes over 40 ks of Swift snapshots,
four short XMM-Newton observations, and a much earlier (2003) and deeper
Chandra observation. These reveal a source that varies in flux by a factor
$\sim 2-3$ on timescales from days to years, and that has demonstrable
variability on timescales as short as tens of minutes. Its spectrum is
generally hard for a ULX, represented by a power-law with $\Gamma\sim 1.4$,
however it can also be satisfactorily described by a two component model with
both components being thermal in nature, with the form and its
parameterisation within the known range of spectra for ULXs. Combining Chandra
astrometry with HST imaging reveals possible counterparts to the ULX within a
spiral arm of the host, that have colour and magnitude similar to young
stellar clusters, but far too high an X-ray/optical flux ratio for a
background AGN. It therefore is a good eULX detection, and its hardness marks
it out as good PULX candidate given that PULXs tend to have harder-than-
average X-ray spectra amongst ULXs, generally due to the dominance of a hard
and variable spectral component in the 0.3-10 keV range (Walton et al., 2018;
Gúrpide et al., 2021). We do not detect pulsations in any individual XMM-
Newton observation, with only one relatively stringent limit of $\lesssim
20\%$ at frequencies $>1$ Hz. Even then, we note that pulsations are a
transient phenomenon in PULXs and are not seen in all epochs; and indeed the
pulsed fraction itself varies in the 0.3-10 keV band, with it dropping below
the best limit seen for 4XMM J112054.3+531040 in several observations of NGC
7793 P13 (Fürst et al., 2021), or never exceeding 10% in the faintest of the
detected pulsations from NGC 1313 X-2 (Sathyaprakash et al., 2019). It is
therefore still eminently possible that further observations of 4XMM
J112054.3+531040 could reveal pulsations, and we regard it as a good candidate
PULX.

The final object, 4XMM J165251.5-591503, has been shown to likely be a
foreground object within our own Galaxy, although its precise nature is not
clear. The fact it was not removed from W22 during the composition of that
catalogue shows a potential weakness of its selection/rejection criteria – a
lack of detailed consideration of Galactic contaminants. Although stars are
rejected if spatially coincident with candidate ULXs, this is limited to those
in the Tycho 2 catalogue (Høg et al., 2000) and those that are picked up via
the Simbad interface151515http://simbad.cds.unistra.fr/simbad/. This example
shows that more filtering is required to pick up Galactic objects, for example
looking for counterparts with measured parallax at low Galactic latitudes. The
4XMM-DR9 ULX catalogue of Bernadich et al. (2022) performs better than W22 in
this regard by searching catalogues including Gaia DR2 for optical point
source counterparts to its ULX candidates, and then using the X-ray/optical
flux ratios to exclude stars and other objects. The even more recent catalogue
of Tranin et al. (2023) uses an automated probabilistic classification of
X-ray sources to produce a catalogue with a claimed contamination of only 2%.
Such stratagems will help to improve future generations of ULX catalogues.

###  5.2 Are there alternative targets for study from Chandra or Swift ?

In total, our selection strategy revealed three previously unstudied eULXs
from a sample of 15 in W22 that had relatively high flux and high luminosity
detections in XMM-Newton data. The focus on XMM-Newton was specifically so
that we could select pre-existing data where pulsation searches were possible
at frequencies similar to those of the pulsations of known PULXs, which is
currently only possible below 10 keV using pn data. It is interesting to ask
whether the other mission catalogues analysed in W22 revealed broadly similar
eULX candidates; although they might not have XMM-Newton data suitable for
sensitive pulsation analysis currently available, they would potentially be
excellent targets for future observations. We therefore repeated the selection
of eULX candidates using the same two simple flux and luminosity criteria, but
using the ULX catalogues in W22 derived from Swift (2SXPS) and Chandra
(CSC2.0).

Figure 9: Re-creation of Fig 1, but instead for the CSC2.0 (left) and 2SXPS
(right) ULX candidates from W22. Any of the 15 sources detected by XMM-Newton
within the region of interest (delineated by the red, dotted line) also
detected in the same region of parameter space by Chandra or Swift are
highlighted by a green square. Any of these objects detected but not in the
region of interest are highlighted instead by blue squares. The CSC2.0 fluxes
and luminosities are all increased by a factor 1.3 to account for its smaller
bandpass; the 2SXPS data panel uses the peak values for each individual source
(i.e. the highest flux/luminosity combination) from any individual Swift
observation.

The results are shown in Fig 9. To create this figure we needed to correct the
CSC2.0 data for its narrower (0.5-7 keV) bandpass. For a variety of spectral
shapes representative of most ULXs (power-law continua in the range
$\Gamma\sim 1.5-2.5$ and absorption column $\sim 1-3\times
10^{21}\rm~{}cm^{-2}$) the correction factor is generally in the range
$1.1-1.3$; we used the optimistic upper value of 1.3 to correct the Chandra
fluxes and luminosities for each detection of each ULX in the left-hand panel.
In the right-hand panel we show the Swift data, and have chosen to display the
peak flux/luminosity combination for each source (observation-level data is
not present for 2SXPS sources in W22, although it is easily recoverable from
2SXPS itself). Clearly the numbers of sources chosen from each detector as
inhabiting the demarcated parameter space vary greatly. There are only 7
CSC2.0 detections within the selection region (including one very marginal
case, even after the generous correction factor). The 5 brightest (in flux)
are all already in our XMM-Newton selection - three separate detections of
4XMM J095550.4+694045 (M82 X-1), and one each of 4XMM J022727.5+333443 (NGC
925 X-1) and 4XMM J131519.5+420301 (NGC 5055 X-1). The two fainter sources are
not in the current list, and so present new targets. The 2SXPS data, on the
other hand, presents far more potential targets than the XMM-Newton selection
- a total of 75 eULX candidates with peak flux and luminosity in the correct
region of parameter space. Ten of these were in the XMM-Newton selection
presented in Section 2; those missing include two of the sources presented in
this paper (4XMM J091948.8-121429 and 4XMM J165251.5-591503 respectively), M82
X-1 which will have been excluded by W22 for being too close the the nucleus
of M82 for Swift to resolve it from any putative nuclear activity, 4XMM
J151558.6+561810 (NGC 5907 ULX1) whose luminosity peaked in the HLX regime
during Swift observations, and 4XMM J230457.6+122028 (NGC 7479 ULX-1) where
the flux was marginally below the cut-off. Note, however, that if we had
chosen instead to use the average Swift flux and luminosity per source, we
would have obtained a similar outcome to the original XMM-Newton selection –
15 sources (albeit the overlap with the XMM-Newton selection was only 7
objects, with the other 8 all new potential targets). The analysis of data
from these new eULX candidates is left to future work.

The lack of Chandra sources is puzzling, but may be due to a combination of
several factors. These include the narrower bandpass (although an attempt was
made to correct for this in the figure); the smaller point spread function,
which will be much better at removing contaminants (local diffuse emission
and/or other point sources) than is possible for XMM-Newton or Swift; and
perhaps most importantly the removal of sources from W22 that are quality
flagged, which will have removed objects at relatively high fluxes due to the
presence of readout streaks and/or pile-up. The much larger potential target
list revealed by Swift is likely a consequence of two factors. First, Swift
has covered a larger sky area than either other mission (e.g. $\sim
3800\rm~{}deg^{2}$ in 2SXPS, Evans et al. 2020, compared to $\sim
1200\rm~{}deg^{2}$ in 4XMM-DR10 which is marginally larger than the area
covered by 4XMM-DR9 reported in Webb et al. 2020), and so has better coverage
of galaxies at moderate distances ($<30$ Mpc) for which the detection of eULX
candidates is possible, even for short Swift snapshots. Second, it takes many
more observations of individual sources, on average, than the other missions.
Hence, for ULXs which are generally a variable population, it has more chances
to catch a source in the correct luminosity range. The combination of these
two factors bodes well for the detection of eULXs by the eROSITA all-sky
survey, which will combine multiple visits to the position of each ULX
candidate with full sky coverage and sensitivity per visit similar to the
Swift snapshots.

###  5.3 Is this a good method for finding PULX candidates?

The starting point for this work was to search for new PULX candidates, using
a combination of high flux, high luminosity and existing XMM-Newton data as
the selection criteria. This has revealed one new interesting PULX candidate,
and another object requiring further observations. There are many other
potential candidates for observation revealed by Swift, and a couple more by
Chandra. However, a basic question remains - is this a good way of finding
good candidates to be PULXs? This is important to answer as it helps us to
make the best use of limited observational time on X-ray facilities.

There are a couple of alternative approaches that can be taken. Earnshaw et
al. (2018) suggested looking for ULXs that display large amplitude
variability, based in the suggestion of Tsygankov et al. (2016) that high
amplitude flux variability in M82 X-2 was due to the propeller effect
(although it is now unclear whether this is the case, or it is instead
variable due to a $\sim 60$ day super-orbital period, cf. Brightman et al.
2019). Song et al. (2020) improved upon the Earnshaw work, identifying 17 good
candidates including two known PULXs; however none of the new objects in that
sample have yet been identified as PULXs, and the premise of looking for large
amplitude variability as evidence for the propeller effect has recently been
questioned by Middleton et al. (2023) who argue this should instead lead to
increased variability in the hard spectral component of ULXs. This is
consistent with Walton et al. (2018), who show that known PULXs have a
dominant hard spectral component when pulsating, which reduces in strength
when they are not doing so.

Indeed, a second method for looking for PULXs is to compare the spectral and
timing behaviour of other ULXs to the known PULXs; Gúrpide et al. (2021)
suggest good PULX candidates on this basis, but again no pulsations have been
found from these objects yet. However, propeller-induced variability may not
be the only reason to continue to look for high amplitude variability in ULXs;
Khan et al. (2022) show that if NS-ULXs have a higher degree of geometric
beaming than BH-ULXs, then precession of the accretion discs will result in a
higher fraction of variable NS-ULXs than BH-ULXs. Therefore, high amplitude
variability may remain as a possible marker for PULX candidates even without
propeller effects.

In the absence of of any positive results, it is not clear whether any of
these suggested strategies provide a better chance of finding detectable PULXs
than the others. It is therefore prudent to continue to attempt them all if we
wish to maximise our chances of discovering more PULXs, and thereby learn more
about the physics of super-Eddington accretion in the regime of high magnetic
field compact objects.

##  6 Conclusions

We started by posing a question - can we use the fact that most of the small
number of PULXs detected to date have observed luminosities that peak in
excess $10^{40}\rm~{}erg~{}s^{-1}$ (i.e. in the eULX regime) to find more PULX
candidates? To answer this, we filtered the ULX catalogue of Walton et al.
(2022) to select objects with XMM-Newton data showing peak luminosities in
this range, concurrent with fluxes above $5\times
10^{-13}\rm~{}erg~{}cm^{-2}~{}s^{-1}$ (with the latter used to select objects
where we have a good chance of accumulating $>10^{4}$ counts in an orbit,
sufficient to detect pulsations). Most of the 15 objects selected are well-
studied ULXs; however we uncovered three ULXs that have hitherto been largely
neglected for study. The analysis of available archival data for these objects
is the subject of this paper.

We found 4XMM J165251.5-591503 to be a soft and variable X-ray source. It lies
at low Galactic latitude and is coincident with a bright optical/IR source
with measured parallax and $\sim 2$ day periodic variability, indicating it is
very likely a foreground contaminant. However, a full diagnosis of the nature
of this object requires more observations. The presence of a Galactic
contaminant highlights a weakness in the filtering of W22 for such objects.
However, this could readily be corrected by the use of Gaia data and/or the
use of statistical/multiwavelength identification techniques to better
identify foreground objects in future catalogues, as has already been done in
the work of Bernadich et al. (2022) and Tranin et al. (2023). 4XMM
J091948.8-121429 on the other hand remains an excellent eULX candidate, but
suffers from minimal archival data being available at present, so also
requires further observational study to improve our understanding of it. The
final object, 4XMM J112054.3+531040 has by far the best current archival data.
It shows moderate X-ray variability on timescales of minutes to years, an
X-ray spectrum that is hard and can be modelled similarly to other ULXs, and a
local environment in the spiral arm of its host galaxy that appears similar to
other ULX environments (including potential counterparts, which indicate an
X-ray-to-optical flux ratio that is too high for a background AGN). We are
able to perform accelerated pulsation searches on the XMM-Newton pn data for
this object, but we do not find any pulsations, with the best limits of a
pulse fraction $\lesssim 20\%$ for a pulsation at $\sim 1$ Hz. So, 4XMM
J112054.3+531040 is not at this time a confirmed PULX; it does however remain
a plausible candidate given its hard X-ray spectrum, moderate limits on the
pulsed fraction, and the fact that pulsations are transient characteristics of
PULXs. Again, further observations with the current fleet of X-ray
observatories are required to better understand the nature of this object.

Finally, we note that the selection of high luminosity, high flux ULXs
provides an interesting sample of objects that could be the subject of further
study with many future X-ray missions, both imminent and proposed (e.g. XRISM,
HEX-P, New Athena etc.), that could provide new opportunities to investigate
whether they host PULXs. We look forward to the excellent science they will
enable.

## Acknowledgements

We thank the anonymous referee for their constructive comments that have
helped improve this paper. TPR & SS were supported by the Science and
Technology Facilities Council (STFC) as part of consolidated grant
ST/T000244/1. ADAM thanks STFC for their support via an STFC studentship
(ST/T506047/1). This research has made use of data obtained with XMM-Newton,
an ESA science mission with instruments and contributions directly funded by
ESA Member States and NASA. It has made use of data obtained from the Chandra
Data Archive and the Chandra Source Catalog, and software provided by the
Chandra X-ray Center (CXC) in the application package ciao. This work made use
of data supplied by the UK Swift Science Data Centre at the University of
Leicester. It uses observations made with the NASA/ESA Hubble Space Telescope,
and obtained from the Hubble Legacy Archive, which is a collaboration between
the Space Telescope Science Institute (STScI/NASA), the Space Telescope
European Coordinating Facility (ST-ECF/ESAC/ESA) and the Canadian Astronomy
Data Centre (CADC/NRC/CSA). This paper includes data collected with the TESS
mission, obtained from the MAST data archive at the STScI. Funding for the
TESS mission is provided by the NASA Explorer Program. STScI is operated by
the Association of Universities for Research in Astronomy, Inc., under NASA
contract NAS 5-26555. The Pan-STARRS1 Surveys (PS1) and the PS1 public science
archive have been made possible through contributions by the Institute for
Astronomy, the University of Hawaii, the Pan-STARRS Project Office, the Max-
Planck Society and its participating institutes, the Max Planck Institute for
Astronomy, Heidelberg and the Max Planck Institute for Extraterrestrial
Physics, Garching, The Johns Hopkins University, Durham University, the
University of Edinburgh, the Queen’s University Belfast, the Harvard-
Smithsonian Center for Astrophysics, the Las Cumbres Observatory Global
Telescope Network Incorporated, the National Central University of Taiwan, the
Space Telescope Science Institute, the National Aeronautics and Space
Administration under Grant No. NNX08AR22G issued through the Planetary Science
Division of the NASA Science Mission Directorate, the National Science
Foundation Grant No. AST-1238877, the University of Maryland, Eotvos Lorand
University (ELTE), the Los Alamos National Laboratory, and the Gordon and
Betty Moore Foundation. This work has made use of data from the European Space
Agency (ESA) mission Gaia (https://www.cosmos.esa.int/gaia), processed by the
Gaia Data Processing and Analysis Consortium (DPAC,
https://www.cosmos.esa.int/web/gaia/dpac/consortium). Funding for the DPAC has
been provided by national institutions, in particular the institutions
participating in the Gaia Multilateral Agreement. This research has made use
of the NASA/IPAC Extragalactic Database (NED) which is operated by the Jet
Propulsion Laboratory, California Institute of Technology, under contract with
the National Aeronautics and Space Administration. It has also made use of
NASA’s Astrophysics Data System.

## Data Availability

The data used in this paper is all available from public archives, via
searches for the observation identifiers in Table 2 and/or the text, or via
searches at the positions of the three sources studied.. XMM-Newton data was
obtained from the XMM-Newton Science Archive (XSA)
(https://www.cosmos.esa.int/web/xmm-newton/xsa), and Chandra data was obtained
from the Chandra Data Archive (https://cxc.cfa.harvard.edu/cda/). The Swift
data was all obtained from 2SXPS (https://www.swift.ac.uk/2SXPS/). Pan-STARRS
imaging data was obtained from http://ps1images.stsci.edu/cgi-bin/ps1cutouts,
and HST data was obtained from MAST (https://archive.stsci.edu). The TESS data
used in the analysis of this work is available on the MAST webpage
(https://mast.stsci.edu/portal/Mashup/Clients/Mast/Portal.html). Gaia data was
obtained via the VizieR interface for astronomical catalogues
(https://vizier.cds.unistra.fr).

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