# New candidates for magnetar counterparts from a deep search with the Hubble
Space Telescope

A. A. Chrimes,1 A. J. Levan1,2, A. S. Fruchter3, P. J. Groot1,4,5, C.
Kouveliotou6,7, J. D. Lyman2,N. R. Tanvir8 and K. Wiersema9
1Department of Astrophysics/IMAPP, Radboud University, P.O. Box 9010, 6500 GL,
The Netherlands
2Department of Physics, University of Warwick, Gibbet Hill Road, Coventry, UK
3Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD
21218, USA
4Inter-University Institute for Data Intensive Astronomy, Department of
Astronomy, University of Cape Town, Private Bag X3, Rondebosch 7701, South
Africa
5South African Astronomical Observatory, P.O. Box 9, 7935 Observatory, South
Africa
6Department of Physics, The George Washington University, Corcoran Hall, 725
21st St NW, Washington, DC 20052, USA
7GWU/Astronomy, Physics and Statistics Institute of Sciences (APSIS)
8School of Physics and Astronomy, University of Leicester, University Road,
Leicester, LE1 7RH, UK
9Physics Department, Lancaster University, Lancaster, LA1 4YB, UK
E-mail<EMAIL_ADDRESS>
(Accepted XXX. Received YYY; in original form ZZZ)

###### Abstract

We report the discovery of six new magnetar counterpart candidates from deep
near-infrared Hubble Space Telescope imaging. The new candidates are among a
sample of nineteen magnetars for which we present HST data obtained between
2018–2020. We confirm the variability of previously established near-infrared
counterparts, and newly identify candidates for PSR J1622-4950, Swift
J1822.3-1606, CXOU J171405.7-381031, Swift J1833-0832, Swift J1834.9-0846 and
AX J1818.8-1559 based on their proximity to X-ray localisations. The new
candidates are compared with the existing counterpart population in terms of
their colours, magnitudes, and near-infrared to X-ray spectral indices. We
find two candidates for AX J1818 which are both consistent with previously
established counterparts. The other new candidates are likely to be chance
alignments, or otherwise have a different origin for their near-infrared
emission not previously seen in magnetar counterparts. Further observations
and studies of these candidates are needed to firmly establish their nature.

###### keywords:

stars: magnetars

††pubyear: 2022††pagerange: New candidates for magnetar counterparts from a
deep search with the Hubble Space Telescope–New candidates for magnetar
counterparts from a deep search with the Hubble Space Telescope

##  1 Introduction

Magnetars are neutron stars with extremely high magnetic field strengths
($B\sim 10^{14}$ G) and are of interest in a wide range of astrophysical
research areas (see Kaspi & Beloborodov, 2017, for a review). They provide
natural laboratories to test quantum mechanics and general relativity at the
extremes, have the potential to reveal much about the formation of neutron
stars in general, and have been invoked as the central engines in transients
ranging from gamma-ray bursts to superluminous supernovae (e.g. Gompertz et
al., 2014; Metzger et al., 2015; Metzger et al., 2017) and fast blue optical
transients (Prentice et al., 2018; Mohan et al., 2020). Recently, they have
also been suggested as promising candidates for the origin of extragalactic
fast radio bursts (FRBs), a theory backed up by the detection of low-
luminosity FRB-like bursts from Galactic magnetar SGR 1935$+$2154 (CHIME/FRB
Collaboration et al., 2020; Bochenek et al., 2020).

A more direct way to study magnetars is to measure the multi-wavelength
emission from Galactic sources, of which $\sim$30 are known (Olausen & Kaspi,
2014)111http://www.physics.mcgill.ca/~pulsar/magnetar/main. Magnetar emission
is distinct from the magnetic dipole braking radiation seen from pulsars - the
persistent magnetospheric emission is likely driven by the direct decay of the
intense magnetic field (Thompson et al., 2002), with bursts and flares driven
by magnetic reconnections (akin to solar flares, Lyutikov, 2003), starquakes
(Thompson & Duncan, 1995; Beloborodov & Thompson, 2007) or other
electrodynamic processes (Heyl & Hernquist, 2005). Galactic magnetars are
typically discovered through $\gamma$-ray/hard X-ray flares, with confirmation
following the detection of a coincident persistent X-ray source (or in some
cases a radio source, Kaspi & Beloborodov, 2017). A population of magnetars
has now been identified outside the Milky Way, through the detection of giant
flares (Burns et al., 2021).

Other than at ${\gamma}$-ray, X-ray and radio wavelengths, a few magnetars
have also been observed in the optical and infrared (e.g. Hulleman et al.,
2004; Kosugi et al., 2005; Camilo et al., 2007; Testa et al., 2008; Dhillon et
al., 2011; Tendulkar et al., 2012). Given their locations in the Galactic
plane, high dust extinctions have restricted these observations, but
optical/near-infrared (NIR) variability has been noted in a handful of cases.
Sometimes this variability is correlated with X-ray activity (Tam et al.,
2004; Ertan et al., 2006; Tam et al., 2008), which can be explained through
the presence of a debris disc, formed through supernova fallback, and heated
by emission from the magnetar (Wang et al., 2006; Ertan & Çalışkan, 2006;
Özsükan et al., 2014; Tong et al., 2016). Magnetospheric models for the origin
of the NIR counterpart also predict a correlation with X-ray emission
(Beloborodov & Thompson, 2007). However, the NIR and X-rays do not always vary
synchronously (Camilo et al., 2007; Testa et al., 2008; Lyman et al., 2021).
The aforementioned variability has been reported for a handful of sources over
month to year time-scales, but short time-scale (${\sim}$seconds) pulsations
have also been seen (Kern & Martin, 2002; Dhillon et al., 2011).

Studies thus far have been limited by to the small optical/NIR counterpart
population size, which has made it difficult to determine whether all
magnetars have similar emission properties at these wavelengths. In this
paper, we present Hubble Space Telescope (HST) imaging of 19 Galactic
magnetars. We perform photometry on previously suggested counterparts and 6
newly identified candidates reported here for the first time. We compare the
magnitudes of the previously known sources to this latest epoch of
observations, confirming or establishing NIR variability, and compare the
properties of the new candidate counterparts to the existing population.

This paper is structured as follows. We describe the details of the
observations and counterpart candidate identification in Section 2, perform
photometry in Section 3, and plot the sources on colour-magnitude diagrams in
Section 4. The variability and spectral indices of the candidates are
discussed in Sections 5 and 6, followed by conclusions in Section 7.
Throughout, magnitudes are reported in the Vega system; appropriate
conversions from AB magnitudes (Oke & Gunn, 1983) have been applied where
necessary (either following Blanton & Roweis, 2007, or with
stsynphot222https://github.com/spacetelescope/stsynphot_refactor for HST
filters). The additions to HST Vega magnitudes to obtain AB magnitudes are
0.9204 (F125W), 1.0973 (F140W) and 1.2741 (F160W).

##  2 Observations and Counterpart identification

###  2.1 HST observations

Details of the 19 datasets used in this work are listed in Table 1, along with
abbreviated magnetar names which we use throughout. All except CXOU J1647 have
F125W ($\sim$J-band) and F160W ($\sim$H-band) imaging, CXOU J1647 has just
F140W. All observations were taken with WFC3/IR. There are 20 datasets listed,
but guide star acquisition failed for SGR 1806. The previously unpublished
images, obtained from the archive, were corrected for charge transfer
efficiency (CTE) and reduced with standard drizzlepac procedures (with default
settings, Hoffmann et al., 2021). The native pixel scale was maintained, i.e.
pixfrac$=$1 and final scale 0.1265 arcsec pixel-1. Another source with recent
HST observations is SGR 1935. We have not included it here as the data is
already published and discussed in detail by Levan et al. (2018) and Lyman et
al. (2021).

Table 1: Details of the HST data. Shortened magnetar names (without brackets)
are used throughout the paper. The data is primarily from programmes 15348 and
16019 (PI: Levan). The listed exposure times are repeated, once in F160W and
once in F125W in each case, with the exception of CXOU J1647 (prog. 14805),
for which an F140W exposure was performed twice. WFC3 was used for all
observations.

Magnetar |  Prog. |  Date |  Exp [s]
---|---|---|---
4U 0142($+$61) |  15348 |  2018 Jan 01 |  598
SGR 0418($+$5729) |  16019 |  2020 Jan 29 |  898
SGR 0501($+$4516) |  16019 |  2020 Aug 04 |  598
1E 1547(.0-5408) |  15348 |  2018 Sep 03 |  898
PSR J1622(-4950) |  16019 |  2020 Sep 04 |  898
SGR 1627(-41) |  16019 |  2020 Sep 08 |  898
1RXS J1708(49.0-400910) |  15348 |  2018 Oct 05 |  898
CXOU J1714(05.7-381031) |  15348 |  2018 Apr 13 |  898
SGR 1745(-2900) |  15348 |  2018 Apr 09 |  898
SGR 1806(-20) ${\dagger}$ |  15348 |  2018 Jun 18 |  598
XTE J1810(-197) |  15348 |  2018 Aug 03 |  898
Swift J1822(.3-1606) |  15348 |  2018 Jul 05 |  598
SGR 1833(-0832) |  15348 |  2018 Jul 18 |  898
Swift J1834(.9-0846) |  16019 |  2020 Mar 16 |  898
3XMM J1852(46.6$+$003317) |  15348 |  2018 Jun 14 |  898
SGR 1900($+$14) |  16019 |  2020 Aug 26 |  898
1E 2259($+$586) |  15348 |  2018 Aug 16 |  598
SGR 0755(-2933) |  16019 |  2020 Sep 10 |  898
AX J1818(.8-1559) |  15348 |  2018 Aug 02 |  898
CXOU J1647(10.2-455216) |  14805 |  2018 May 23 |  2688

${\dagger}$ \- guide star not acquired, images unusable

###  2.2 Counterpart localisation with Chandra

Figure 1: F160W HST imaging of the 19 magnetars (with the exception of CXOU J1647 which has F140W imaging). The cutouts are 8${\times}$8 arcsec. Error circles which have been refined through relative alignment (e.g. CXO with HST ) are drawn as solid lines. Error circles based on absolute astrometry are dashed (if this uncertainty is lower than from relative astrometry, we only show the absolute localisation). In each case the error circle radii are adjusted to enclose $\sim$95 per cent of the probability. If sources are detected (or have previously been detected) in the error circle, the most likely counterpart position(s) is indicated by red pointers. This location is used to measure a limit in the case of non-detections. If there is no previously reported counterpart, the aperture is placed at the centre the X-ray error circle. There are three candidates for 1RXSJ 1708, including one outside the error circle which we measure for comparison with Durant & van Kerkwijk (2006a). AXJ 1818 has two candidates. The error circle for 3XMM J1852 is larger than the cutout. For SGRs 0755 and 1745, the error circle is drawn in white for contrast. The corresponding photometry is listed in Table 3. Table 2: Magnetar positions reported in the literature, and details of the CXO-HST alignment described in the text. Where the number of tie sources, $N_{\rm tie}$, is listed as X$/$Y, the first number is the objects matched between CXO and the intermediate, and the second between the intermediate and HST. Refined 2$\sigma$ uncertainty radii from relative astrometry are listed in the final column, these are used if they provide an improvement over the absolute astrometry, and 2 or more tie objects were available. Where we have been unable to precisely align a CXO X-ray localisation on the HST images, we have re-calculated the absolute astrometric uncertainty in these cases using the net source counts from wavdetect and following Evans et al. (2010). These uncertainties are denoted with a $\dagger$ symbol. Magnetar | Localisation/identification | RA | Dec | Unc. (enc.) | CXO | $N_{\rm tie}$ | Intermediate | 2${\sigma}$ unc.
---|---|---|---|---|---|---|---|---
| reference | (as reported) | (as reported) | [arcsec] | Obs ID |  |  | [arcsec]
4U 0142 | Juett et al. (2002) | 01h46m22.41s | +61d45m03.2s | 0.60 (95)$\dagger$ | 723 | 1 / 61 | Gaia | -
SGR 0418 | Van der Horst et al. (2010) | 04h18m33.867s | +57d32m22.91s | 0.35 (95) | 10168 | 0 | Gaia | -
SGR 0501 | Göǧüş et al. (2010b) | 05h01m06.76s | +45d16m33.92s | 0.11 (67) | 9131 | 0 | Gaia | -
1E 1547 | Deller et al. (2012) | 15h50m54.12s | -54d18m24.1s | (0.6$\times$2)$\times$10-3 (67) | radio | - | - | -
PSR J1622 | Anderson et al. (2012) | 16h22m44.89s | -49d50m52.7s | 0.58 (95)$\dagger$ | 10929 | 2 | None | 0.210
SGR 1627 | Wachter et al. (2004) | 16h35m51.844s | -47d35m23.31s | 0.74 (95)$\dagger$ | 1981 | 3 | None | 0.272
1RXS J1708 | Israel et al. (2003) | 17h08m46.87s | -40d08m52.4s | 0.7 (95)$\dagger$ | 1936 | 2 | None | 0.502
CXOU J1714 | Halpern & Gotthelf (2010) | 17h14m05.74s | -38d10m30.9s | 0.44 (95)$\dagger$ | 6692 | 2 | None | 0.238
SGR J1745 | Shannon & Johnston (2013) | 17h45m40.16s | -29d00m29.8s | (9$\times$22)$\times$10-3 (67) | radio | - | - | -
XTE J1810 | Helfand et al. (2007) | 18h09m51.087s | -19d43m51.93s | 4$\times$10-3 (67) | radio | - | - | -
Swift J1822 | Scholz et al. (2012) | 18h22m18.06s | -16d04m25.5s | 0.58 (95)$\dagger$ | 15992 | 0 | Gaia | -
SGR 1833 | Göǧüş et al. (2010a) | 18h33m44.37s | -08d31m07.5s | 0.41 (95)$\dagger$ | 11114 | 2 / 85 | Gaia | 0.588
3XMM J1852 | Zhou et al. (2014) | 18h52m46.67s | +00d33m17.8s | 2.4 (67) | no CXO | - | - | -
SGR 1900 | Frail et al. (1999) | 19h07m14.33s | +09d19m20.1s | 0.4 (95)$\dagger$ | 6731 | 2 / 42 | Pan-STARRS | 0.494
1E 2259 | Hulleman et al. (2001) | 23h01m08.295s | +58d52m44.45s | 0.38 (95)$\dagger$ | 6730 | 2 / 101 | Gaia | 0.41
SGR 0755 | Doroshenko et al. (2021) | 07h55m42.48s | -29d33m49.2s | 2.0 (97) | 22454 | 1 / 116 | Gaia | -
Swift J1834 | Kargaltsev et al. (2012) | 18h34m52.118s | -08d45m56.02s | 0.5 (95)$\dagger$ | 14329 | 0 | Gaia | -
AXJ1818 | Mereghetti et al. (2012) | 18h18m51.38s | -15d59m22.62s | 0.51 (95)$\dagger$ | 7617 | 1/148 | Gaia | -
CXOU J1647 | Muno et al. (2006) | 16h47m10.20s | -45d52m16.90s | 0.41 (95)$\dagger$ | 19136 | 2 / 188 | Gaia | 0.198

Chandra X-ray Observatory (CXO) observations provide the best localisation
available for 15 of the 19 magnetars. We download the CXO event files for each
source, obtained via the CXO data centre with the Obs IDs as listed in Table
2. Observations are variously with ACIS and HRC. We measure the source
positions in these images using the CIAO source detection algorithm wavdetect.
Standard ciao (v4.13, with caldb v4.9.3) procedures were used, including
reprocessing, PSF map creation and energy filtering to the range 0.5-7 keV
(HRC) or 0.5-8 kev (ACIS). Point sources 5 ${\sigma}$ above the background
level are extracted.

As a first step, we attempt to find sources in common between the X-ray and
HST images, and compute the offsets in RA and Dec required to map one set of
coordinates to the other (astrometrically ‘tying’ the images). In this way, we
are removing the absolute uncertainty of the world coordinate system (WCS)
calibrations and are limited only by the relative uncertainty in the
transformation. Ideally we would find sources in common directly between CXO
and HST, which was only possible in 4 cases. The source centroids were
measured in each image’s own coordinate system, and the mean RA and Dec
offsets needed to map CXO coordinates on to the HST frame were computed. These
were applied to the CXO coordinates, and the RMS difference between the
transformed CXO and HST source positions measured. This is added in quadrature
to the centroid uncertainty, calculated as FWHM/(2.35 SNR), where FWHM is the
full width at half maximum and SNR is the signal to noise ratio. This yields
the smallest possible (sub-arcsecond) positional uncertainties. We note that
the resulting refined error circle for CXOU J1647 is slightly offset from the
source identified as the counterpart by Testa et al. (2008). However, as there
are no other objects in the unrefined or refined error circle, we adopt this
source as the likely counterpart.

For the remaining 11 sources with HST and CXO observations, there are $<2$
sources in common that are not a counterpart candidate, precluding a direct
tie between HST and CXO (without relying on a single tie object). We instead
try to tie the images via an intermediate step. The intermediate image should
have an area comparable to CXO images, so that common sources can be found
within the CXO field of view, but deep enough for sources in common with HST
to be identified. Intermediate catalogues searched include Gaia (EDR3, Gaia
Collaboration et al., 2021), 2MASS (Skrutskie et al., 2006) and Pan-STARRS
(Chambers et al., 2016). If there were insufficient matches in these surveys,
we also searched the ESO and Gemini archives for imaging of the fields. In
each case, where Gaia offered enough suitable intermediate tie objects, no
improvement could be gained by moving to a different survey. The uncertainty
in the CXO \- intermediate alignment is calculated in the same way as for the
CXO \- HST direct alignments, by computing the RA and Dec shifts required and
the RMS of this translation. For the intermediate - HST alignment, there are
tens to hundreds of matches, so in principle rotation and scaling could also
be left as free parameters. This is equivalent to improving the absolute
astrometry of the HST frame. The intermediate (Gaia) - HST RMS values, using
simple RA and Dec shifts, are typically $\sim$20 mas (e.g. for 1E 2259, 25
mas). This compares well to the RMS values obtained from the FITS headers of
HST advanced data product images (for 1E 2259, 23 mas in RA and 26 mas in
Dec), whose astrometric solutions are now calibrated against Gaia (DR1 or DR2)
by the automated pipeline. In any case, the CXO \- intermediate step dominates
the uncertainty in the transformation. Using 1E 2259 as an example again, the
CXO \- Gaia RMS is 0.2 arcsec, so any further refinement of the HST \-
intermediate step will be of little benefit.

Details of the image alignment and tying are given in Table 2. Other datasets
are available to act as intermediates for for 4U 0142 and SGR 0501, but these
counterparts are already well established and unambiguously identified. The
refined 2${\sigma}$ error radii have three components if an intermediate is
used - the two tie steps and the centroid error. Error circles from relative
astrometry are drawn as solid circles in Figure 1, with candidate counterparts
(or their expected location in the case of non-detections) indicated by red
pointers.

Where a HST \- CXO alignment was not possible even via an intermediate, error
circles are placed on the HST images at the coordinates reported by the
references in Table 2. The absolute astrometric accuracy of CXO is variously
reported in these references as $\sim$0.6-0.8 arcsec (90 per
cent)333https://cxc.harvard.edu/cal/ASPECT/444https://cxc.harvard.edu/ciao/ahelp/coords.html,
but the precise value depends on the source location in the image and net
counts. We re-calculate the uncertainty in the absolute astrometry of these
sources by taking the net counts from wavdetect and applying the (off-axis
angle and source counts dependent) absolute accuracy calculations of Evans et
al. (2010). Since many of these sources are bright, and the off-axis angles
are exclusively $\sim$0 (they are the targets), the absolute astrometric
uncertainties are typically smaller than previously reported. The sources for
which we have performed this calculation are noted in Table 2. If these
uncertainties are smaller than those arising from relative alignment, we use
the absolute astrometry instead. In one instance an accurately calculated
value is already reported (SGR 0418), and in another, the absolute astrometry
of the CXO localisation was improved by alignment with 2MASS (SGR 0501).

Two sources have non-CXO localisations plotted in Fig. 1. These are an XMM
position for 3XMM J1852 and a Swift/XRT position of SGR 0755 - which we plot
instead of the later CXO localisation, since this XRT position was associated
with the BAT SGR discovery burst. While 3XMM J1852 has CXO observations, they
are exclusively in continuous clocking mode, so they cannot be used for
imaging. The magnetar is also in the field of view of Kes 79 supernova remnant
observations, but is not detected in these images.

When placing positions from absolute astrometry on our HST images , we must
also consider that the HST image WCS solutions also have an uncertainty. This
is quantified by the RA and Dec RMS values after source alignment with Gaia as
performed by the HST pipeline, of order tens of mas. Assuming the CXO
uncertainty is Gaussian, we convert the reported error radius to a 67 per cent
radius if it is not already. We add this in quadrature to the HST-Gaia RMS and
X-ray centroid uncertainty. In this way we can derive an approximate 2
${\sigma}$ positional uncertainty for the X-ray source in the HST frame. These
error circles are drawn with dashed lines in Figure 1. Measured proper motions
for magnetars are at the mas yr-1 level, such that temporal separations
between the CXO and HST epochs should only produce small spatial offsets
compared to the localisation uncertainty.

###  2.3 Radio localisations

The final three sources in our sample have precise radio localisations. The
position of 1E 1547 was measured using very long baseline interferometry
observations (Deller et al., 2012). An ellipsoidal uncertainty region of
(0.6${\times}$2.0) mas (1 ${\sigma}$) is reported. To place this on the HST
frames, however, the uncertainty in the VLBA and HST absolute astrometry must
be considered. The quoted VLBA positional error includes both statistical and
systematic uncertainties, while the HST frames have been aligned with the Gaia
reference frame, with an RMS uncertainty in the HST absolute astrometry of 14
mas (from the RMS$\\_$RA and RMS$\\_$DEC header entries). The total
uncertainty on the magnetar position in the HST frame is, therefore, dominated
by the HST-Gaia alignment.

Since SGR 1745 lies near the Galactic centre, the extremely high extinction
along this sightline means that the chance of any sources seen in the crowded
field being associated (rather than foreground objects) is very low.
Nevertheless, we can measure a limit at the position on the HST image. As with
1E 1547, we assume the uncertainty on this precise ATCA localisation in the
HST frame is dominated by the HST WCS solution (Shannon & Johnston, 2013). The
final magnetar in this sample where we use a radio-localisation is XTE J1810.
Helfand et al. (2007) report an absolute astrometric uncertainty of 4 mas, so
the HST-Gaia WCS solution again dominates.

###  2.4 Identification through variability

Some NIR counterparts have been identified due to their variability. In these
cases, the variable source association is favoured (over non-variable sources
in the X-ray error circle) either because the NIR variability correlates with
X-ray behaviour, or the expectation that variable NIR sources are sufficiently
rare that finding such a source in the error circle by chance is extremely
unlikely (although such arguments are as yet poorly quantified).

The source associated with SGR 1900 has $H=21.17\pm 0.04$ and $K_{p}=20.63\pm
0.02$ (with 0.5 and 0.1 errors on the zero points), and was suggested as the
counterpart due to variability (Tendulkar et al., 2012). The two clear sources
within/on the edge of the error circle in the HST imaging presented in Figure
1 are labelled as sources 3 and 6 by Tendulkar et al. (2012) (and Testa et
al., 2008). The suggested variable counterpart, source 7, and another object,
source 10, are not readily visible in the HST images, nor are they visible in
images re-drizzled onto a 0.065 arcsec pixel-1 grid. To investigate whether
proximity to the bright star 3 is obscuring sources 7 and 10 at this
resolution, we subtract the PSF of this star in Figure 2. To do this, we
subtract a rotated image cutout centred on star 3, to sample the precise PSF
at this location. There is slight excess in the residual image between stars 3
and 6, $\sim$0.2 arcsec from the centre of star 3, at approximate location of
stars 7 and 10 in the Keck/NIRC2 LGS-AO observations of Tendulkar et al.
(2012). The reported proper motion of 2.1$\pm$0.6 mas yr-1 for the magnetar
corresponds to only $\sim$0.3 pixels of movement over 10 years at this pixel
scale. We conclude that we are not resolving these sources from star 3. The
high flux ratio (a magnitude $\sim$18 source only 0.2 arcsec from magnitude
$\sim$21 sources) makes robust recovery of the suggested counterpart extremely
challenging, so we consequently adopt the range of previously reported $H$ and
$K$-band photometry for the suggested variable counterpart (Testa et al.,
2008; Tendulkar et al., 2012).

Figure 2: Left: a 2.2$\times$2.2 arcsec cutout of the re-drizzled F160W image
(pixel scale 0.065 arcsec pixel-1) centered around the target star (T)
coincident with SGR 1900 (star 3 of Tendulkar et al., 2012, other sources also
follow this labelling). The approximate location of star 7, the SGR 1900
counterpart candidate, is marked by a cross. Right: the target cutout rotated
by 180 degrees, subtracted from the original cutout. There is a slight excess
at the location of sources 7 and 10 in the residual image (mirrored in x and y
by an equal deficit since we subtracted a rotated image).

Tendulkar et al. (2012) also identify a candidate counterpart to SGR 1806
thanks to its variability, measuring $K\sim 21.75\pm 0.75$ (this approximate
uncertainty reflects the source variability), in agreement with Kosugi et al.
(2005) who find $K=21.9$. We adopt these values since the HST images for this
target are unusable following a guide star acquisition failure.

There have been unambiguous localisation (both in previous works and here) of
magnetar counterparts known to be variable, for example 1E 2259 and 4U 0142
(Tam et al., 2004; Hulleman et al., 2004; Tendulkar et al., 2013). Since they
are clearly localised with CXO independent of variability arguments, this
demonstrates that at least some magnetar counterparts are variable and
supports associations based on variability.

###  2.5 New counterpart candidates

Using the localisations and imaging described above, we identify counterpart
candidates for six magnetars for the first time. These are PSR J1622, Swift
J1822, CXOU J1714, Swift J1833, Swift J1834 and AX J1818 (two candidates).
This has increased the sample of Galactic magnetar NIR counterparts (confirmed
or otherwise) by $\sim$50 per cent (Olausen & Kaspi, 2014). Additionally, SGR
1627 has previous imaging, but the source we deem to be the most likely
counterpart has not been measured, as it was too faint for reliable photometry
in previous imaging (Wachter et al., 2004). We therefore report photometry for
this candidate for the first time.

Figure 3: Colour-magnitude diagrams of the fields of the 13 magnetars with
dual-band imaging and a detection. The source photometry was extracted in both
filters simultaneously using DOLPHOT. The density of field objects in this
parameter space is indicated by the blue shading, targets in the error circles
in Figure 1 are shown as orange points (errorbars are typically too small to
be visible). Unusually red colours, outside the cloud of stellar sources,
might indicate a non-stellar origin (e.g. a debris disc), however this is not
necessarily the case: the spectral energy distribution of 4U 0142 suggests the
existence of a debris disc, but it does not appear particularly anomalous in
this parameter space. The probability of finding a source in the error circle,
of the counterpart brightness or brighter, is given by Pchance (the brightest
counterpart candidate is used where there are several). The 3XMM J1852 source
is simply the reddest object in the large error circle, and is not a robust
counterpart candidate.

##  3 Photometry

###  3.1 Manual photometry

We initially perform manual photometry on counterparts or candidates
identified in the 2${\sigma}$ error circles as shown in Figure 1 and listed in
Table 3. Aperture photometry is carried out with the photutils python package
(v1.2.0, Bradley et al., 2021). The aperture radius used is typically 0.4
arsec, but is reduced to as low as 0.1 arcsec if there are immediately
neighbouring sources, to reduce flux contamination. The tabulated WFC3 IR
encircled energy corrections are
applied555https://www.stsci.edu/hst/instrumentation/wfc3/data-
analysis/photometric-calibration/ir-encircled-energy. Because many of these
fields are crowded, rather than using an annulus, we estimate the background
by placing apertures on ‘blank’ areas of sky (judged by eye) around the image.
The background level is extracted by constructing a pixel value distribution
from these apertures and using the sigma clipped median.

To verify this method, we also calculate the background with the photutils
function background2D in less crowded fields. In these cases we get similar
results. For example, for the NIR counterpart of 4U 0142, the difference in
photometry between aperture background and background2D estimators produce
results that differ by much less than the total photometric uncertainty (a
0.008 difference with an error of 0.02). The photometry for the counterparts
and candidates is listed in Table 3, with multiple rows where there is more
than one candidate. If the flux at the magnetar location fails to reach
3${\sigma}$ significance, a 3${\sigma}$ limit is listed instead.

###  3.2 Automated photometry

In addition to the aperture photometry, we also perform automated source
detection and photometry for all sources in the HST images. There are two
reasons for this, (i) to verify the manual measurements and (ii) to obtain
magnitudes and colours for every source in the field. This way, we can see if
the counterpart candidates stand out as having unusual magnitudes or colours,
or find sources that do. DOLPHOT is used (v2.0, Dolphin,
2000)666http://americano.dolphinsim.com/dolphot/, running on the F160W and
F125W bands simultaneously, with the point spread functions of Anderson
(2016). Drizzled F160W images are used as the reference, but photometry is
performed on the undrizzled flt frames. We retain sources with a SNR of at
least 3 in each filter, and reject those with an ellipticity greater than 0.2,
helping to remove diffraction spikes and some galaxies. Differences between
these measurements and the manual photometry are typically small, but can
arise because DOLPHOT accounts for source blending and the PSF, which can have
a significant impact on HST photometry in crowded fields (Sodemann & Thomsen,
1998).

Table 3: The HST photometry for candidates in the error circles in Figure 1,
supplemented by $H$ (or if unavailable, $K$) band data from the literature,
where we cannot reliably measure at previously suggested counterpart location.
Non-HST data is used for SGR 1900 and SGR 1806 ($H$ and $K$-band, Tendulkar et
al., 2012), and SGR 0755 ($H$-band, 2MASS). Otherwise, even if we do not
detect a previously suggested counterpart, we use the HST photometry as
measured below. AXJ 1818 and 1RXSJ 1708 have multiple candidates, the first
two for 1RXSJ 1708 follow the same labelling as Israel et al. (2003) and
Durant & van Kerkwijk (2006a). Quiescent unabsorbed X-ray fluxes (2-10 kev)
are also listed with the reference for the original measurement. Several
unabsorbed fluxes were calculated from different energy ranges by Olausen &
Kaspi (2014) and they are provided below where the original reference did not
give this measurement. In the final column we give the NIR to X-ray power law
index.

Magnetar | F160W | F125W | Pchance | Unabsorbed FX [2-10 keV] | X-ray reference | NIR to X-ray
---|---|---|---|---|---|---
| (Vega) | (Vega) |  | [10-12erg s-1 cm-2] |  | PL Index
4U 0142 | 20.80$\pm$0.01 | 21.72$\pm$0.01 | 0.000 | 67.9 | Rea et al. (2007b) | 0.98$\pm$0.01
SGR 0418 |  $>$25.12 |  $>$26.08 | - | 0.0020${}^{+0.0014}_{-0.0010}$ | Rea et al. (2013) |  $>$0.26
SGR 0501 | 22.56${}^{+0.06}_{-0.07}$ | 23.33$\pm$0.07 | 0.002 | 1.7 | Camero et al. (2014) | 0.75$\pm$0.02
1E 1547 |  $>$20.22 |  $>$22.45 | - | 0.54 | Bernardini et al. (2011) |  $>$0.38
PSR J1622 | 22.39$\pm 0.05$ | 23.95$\pm 0.08$ | 0.043 | 0.045${}^{+0.063}_{-0.028}$ | Anderson et al. (2012) | 0.33$\pm$0.11
SGR 1627 | 20.48$\pm$0.01 | 21.97$\pm 0.01$ | 0.032 | 0.25${}^{+0.17}_{-0.10}$ | An et al. (2012) | 0.32$\pm$0.06
1RXS J1708 (A) | 18.77${\pm}$0.01 | 20.61${\pm}$0.01 | 0.036 | 24.3 | Rea et al. (2007a) | 0.66$\pm$0.01
1RXS J1708 (B) | 20.58${\pm}$0.01 | 22.37$\pm$0.02 | 0.104 | - | - | 0.97$\pm$0.02
1RXS J1708 (C) | 21.80${\pm}$0.08 | 23.71${}^{+0.14}_{-0.16}$ | 0.164 | - | - | 0.85$\pm$0.01
CXOU J1714 | 17.45$\pm$0.01 | 19.01$\pm$0.01 | 0.005 | 2.68$\pm$0.09 | Sato et al. (2010) | 0.28$\pm$0.01
SGR J1745 |  $>$15.97 |  $>$18.98 | - |  $<$0.013 | Mori et al. (2013) | -
SGR 1806 $[1]$ | 21.75$\pm$0.75 | - | - | 18$\pm$1 | Esposito et al. (2007) | 0.99$\pm$0.05
XTE J1810 |  $>$24.79 |  $>$25.58 | - | 0.029 | Gotthelf et al. (2004) |  $>$0.53
Swift J1822 | 19.76$\pm$0.01 | 21.04$\pm 0.02$ | 0.146 |  $<$0.0013 | Scholz et al. (2012) |  $<$-0.34
AXJ1818 (A) | 21.38${}^{+0.14}_{-0.16}$ | 22.80${}^{+0.14}_{-0.16}$ | 0.242 | 1.68${}^{+0.15}_{-0.16}$ | Mereghetti et al. (2012) | 0.63$\pm$0.02
AXJ1818 (B) | 20.40$\pm 0.06$ | 21.87${}^{+0.06}_{-0.07}$ | 0.182 | - | - | 0.53$\pm$0.02
3XMM J1852${\dagger}$ | 18.85$\pm$0.01 | 21.97$\pm$0.02 | 0.948 |  $<$0.001 | Rea et al. (2014) |  $<$-0.47
SGR 1900 $[2]$ | 21.17$\pm$0.50 | - | - | 4.8$\pm$0.2 | Mereghetti et al. (2006) | 0.74$\pm$0.04
IE 2259 | 22.52$\pm 0.04$ | 23.61${\pm}$0.05 | 0.016 | 14.1$\pm$0.3 | Zhu et al. (2008) | 0.99$\pm$0.01
SGR 0755$[3]$ | 9.52$\pm$0.01 | 9.69$\pm$0.01 | 0.000 |  $<$5.5${\ddagger}$ | Archibald et al. (2016) |  $<$-0.31
Swift J1834 | 21.74$\pm 0.02$ | 23.21$\pm 0.03$ | 0.050 |  $<$0.004 | Younes et al. (2012) |  $<$-0.01
SGR 1833 | 21.56$\pm 0.03$ | 22.93$\pm 0.02$ | 0.031 |  $<$0.2 | Esposito et al. (2011) |  $<$0.41
CXOU J1647 | 22.20${}^{+0.09}_{-0.10}$ (F140W) | - | 0.095 | 0.25$\pm$0.04 | An et al. (2013) | 0.48$\pm$0.03

${\dagger}$ \- Reddest source in error circle, not a robust counterpart
association. ${\ddagger}$ \- 0.5–10 keV
$[1]$ \- $K$-band photometry from Tendulkar et al. (2012), $[2]$ \- $H$-band
from Tendulkar et al. (2012), includes zero-point uncertainty, see Section 2.4
$[3]$ \- HMXB (Doroshenko et al., 2021), listed $H$ and $J$-band photometry
from 2MASS.

##  4 Colour-magnitude diagrams

In Figure 3 we show colour-magnitude diagrams for the fields where at least
one candidate counterpart is detected in the error circle. For each field, the
probability of finding an object of magnitude $m$ or brighter in the error
circle area is evaluated and shown (for the brightest, lowest probability
source if there are multiple candidates) in Figure 3. This is given by

$P_{\rm chance}=1-{\rm exp}(-{\pi}r^{2}/{\Sigma}),$ (1)

where ${\Sigma}$ is the surface density of sources with F160W magnitude $m$ or
brighter, averaged over the HST frame, and $r$ is the 2${\sigma}$ uncertainty
radius.

Searching for unusually red magnetar counterparts is well established,
following the discovery that some do have such colours (Wang & Chakrabarty,
2002; Israel et al., 2003; Wachter et al., 2004; Durant et al., 2011). An
infrared excess was confirmed in magnetar 4U 0142, possibly due to a debris
disc (Wang et al., 2006). In other magnetars the red colour may be
magnetospheric (Thompson & Duncan, 1996). In either case, these sources are
non-stellar in colour, appearing distinct from the cloud of other objects. In
Figure 3, most of the counterparts and candidates are not obviously distinct.
Even some previously established counterparts are not clearly separated in
this $J$-$H$ versus $H$ parameter space (e.g. 4U 0142, Wang et al., 2006). The
magnetars which do have unusual sources in their error circle are CXOU J1714
(off the main sequence), 1RXS 1708 (source A of Israel et al., 2003), 1E 2259
(previously noted as perhaps being magnetospheric in origin, Hulleman et al.,
2001), SGR 0755 and 3XMM J1852.

The latter two deserve special attention. For 3XMM J1852 the XMM error circle
is nearly 5 arcsec in diameter. There is one exceptionally red source in the
error circle, which we adopt as the potential counterpart going forward, with
the caveat that there is no way to firmly establish this association with
existing datasets.

SGR 0755 has a Swift/XRT localisation (indicated on Figure 1 as this was
associated with the BAT discovery burst), and further X-ray observations
including a CXO localisation (Doroshenko et al., 2021), which is also aligned
with the bright star. The Swift/XRT error circle is slightly offset from the
centre of the bright star, which cannot be explained by the Gaia proper motion
of $\sim$4 mas yr-1, given that the gap between Swift and HST observations is
only 4 years. In any case, the probability of chance alignment is negligible,
and subsequent X-ray observations have also suggested association with the
$H{\sim}9$ Be-star, which has been identified as a high-mass X-ray binary
(HMXB, Doroshenko et al., 2021). The source is too bright for HST photometry,
so the adopted magnitudes are from 2MASS. The SGR classification was initially
due to the Swift/BAT detection of a magnetar-like burst. The HMXB was seen in
subsequent Swift/XRT and CXO observations, but is not the sole X-ray source in
the ${\sim}$3 arcmin BAT error circle, leaving open the possibility of a
chance alignment. The 90 percent uncertainty radius on this localisation of
${\sim}$3 arcmin is larger than the ${\sim}$2 arcmin HST field of view.
Although we identify several sources red-wards of the main sequence, there are
too many to suggest counterpart candidates (and the magnetar, if not in the
HMXB itself, could still lie outside of the field of view).

Figure 4: The seven magnetars for which we identify (or place limits on) a
previously known NIR counterpart (excluding SGR 1935, see Lyman et al., 2021,
for a discussion of the variability of this source). Shown are the F160W
measurements (this work, note that CXOU J1647 has F140W observations instead),
compared with $H$-band, or if unavailable, $K$-band data from previous
studies.

##  5 Variability

In Section 2.4, we discussed the variability of sources in previous
observations as an extra tool for identifying counterparts. Counterpart
variability is also interesting in its own right, as it can provide clues to
the nature of the emission. In Figure 4 we show the F160W measurements from
this paper, compared to previous measurements of the counterpart ($H$ or
$K$-band), where a detection has previously been made (following references in
the McGill catalogue, Olausen & Kaspi, 2014). We also compare with the
candidate detection for CXOU J1647 by Testa et al. (2018), who find $J=23.5\pm
0.2$, $H=21.0\pm 0.1$ and $K=20.4\pm 0.1$. There are cases where we have
detected sources below previously established limits, but these are not
constraining in terms of variability and so are not shown. Where there is only
$K$-band data to compare, it is difficult to establish if there is
variability, or simply a red $H$-$K$ colour (not unusual for magnetars).

Four have previous $\sim H$-band observations, and a long baseline between
observations (4U 0142, previous observed from 2004–2006, 1RXSJ 1708,
previously observed 2006, XTEJ 1810, previously observed 2007–2008 and CXOU
J1647, previously observed 2013). For 1RXSJ 1708, the second (fainter) source
is added from just outside the error circle (labelled star B, Durant & van
Kerkwijk, 2006a). The $H$-band magnitudes of stars A (the brightest object)
and B are reported by Durant & van Kerkwijk (2006a) to be 18.82$\pm$0.06 and
20.29$\pm$0.13. We report magnitudes of 18.77$\pm$0.01 and 20.58$\pm$0.01,
respectively. The star A measurements are therefore consistent, while star B
has a ${\sim}$2.2$\sigma$ difference. Given the proximity of star A to star B,
and the difference between the $H$ and F160W filters, this is unlikely to be a
reliable variability measurement. None the less, Durant & van Kerkwijk (2006a)
claim the potentially variable star B as the more likely counterpart based on
its anomalous $JHK$ colours.

Figure 5: The cumulative distribution of NIR to X-ray power law indices (Table
3). Sources for which we report a counterpart candidate for the first time are
labelled in bold/red, limits are indicated on the corresponding histogram
step. Photon index upper limits are due to X-ray upper limits, and lower
limits are NIR non-detections. Only SGR 1745 (not plotted) lacks a quiescent
detection in both the NIR and X-ray and therefore has an unconstrained
$\Gamma$. The new candidates have lower indices than previously established
counterparts, with the exception of AX J1818.

4U 0142 is consistent with previously noted variability (Hulleman et al.,
2004; Durant & van Kerkwijk, 2006b), and there are significant differences
between our measurements of SGR 0501 and 1E 2259, although these are also in
different bands. CXOU J1647 appears to have faded by $\sim$1 magnitude, but
the most striking change is in XTEJ 1810 which has dropped ${\sim}$2.5
magnitudes (a factor of ${\sim}$10 in flux). This is much more than the
previously reported $H$-band variability of this source ($\sim$1 magnitude,
Testa et al., 2008). If the NIR emission is thermal in nature (flux $\propto
T^{4}$), as in the case of blackbody emission from a debris disc, this
corresponds to cooling by a factor of $\sim$2 over a 10 year time-scale.

Variability of NIR emission can equally be explained if we invoke a surviving
binary companion as the origin of the emission. The variability of stars in
the NIR is poorly understood (e.g. Levesque & Massey, 2020), but such a
scenario would predict a lack of correlation in the variability seen for
different spectral bands in some magnetars. Roughly equal-mass binaries would
be likely to place OB-stars as the companions, which can have prominent
variability in the NIR (Bonanos et al., 2009; Roquette et al., 2020). Another
possibility, given the young age estimates for magnetars, are pre-main
sequence companions. These could feasibly remain pre-main sequence for longer
than the lifetime of a massive star magnetar progenitor, and are known to be
variable in the NIR (e.g. Carpenter et al., 2001; Eiroa et al., 2002; Alves de
Oliveira & Casali, 2008). We will investigate these possibilities further in a
separate paper (Chrimes et al., in prep).

##  6 NIR – X-ray spectral indicies

Another measurement we can make for the sample, placing the new candidate
counterparts in context, is the NIR to X-ray spectral index. We fit a power
law (PL) between the unabsorbed quiescent X-ray flux, adjusted so that all
measurements are in the $\sim$2-10 keV range (taken from Olausen & Kaspi,
2014, where necessary), and F160W (or nearest available band, see Table 3).
The corresponding frequencies used are 9$\times$1017 Hz and 2$\times$1014 Hz,
with $\nu F_{\nu}\propto\nu^{1-\beta}$ and $\beta=1-\Gamma$. The uncertainties
are not quantified for all of the X-ray flux estimates, where they are not, a
10 per cent uncertainty is assumed, with the caveat that this may be an
underestimate.

We first note that the six sources reported here for the first time have
typical apparent magnitudes compared the existing population, with
$17.5<H<22.5$ (see Table 3). Most notable is SGR 0755, which is by far the
brightest source at $H\sim 10$. However, there is ambiguity as to whether this
Be-star HMXB is associated with SGR 0755, in which case the accretor would be
the magnetar, or whether this is an unrelated HMXB which happened to lie in
the 3 arcmin error region of the Swift/BAT discovery burst (Doroshenko et al.,
2021).

Figure 5 shows the cumulative distribution of PL indices $\Gamma$. Previously
established counterparts - those for which a single source has previously been
noted due to unambiguous localisation or variability - include 4U 0142, SGR
1900, SGR 1806, 1E 2259, SGR 0501, CXOU J1647 and XTE 1810. There is a clear
delineation between these known counterparts and the new candidates - all
known sources lie at the upper end of the distribution. The lowest (CXOU
J1647) has $\Gamma=0.43$, the only new candidates to lie above this are for AX
J1818.

To measure these indices, we have used unabsorbed X-ray fluxes and observed
NIR fluxes, uncorrected for extinction. Magnetars with previously established
NIR counterparts have relatively low extinction estimates (e.g. A${}_{\rm
v}\sim$3.5 for 4U 0142, Wang et al., 2006). The neutral hydrogen column
density assumed to calculate the unabsorbed quiescent X-ray flux of 4U 0142 is
$10^{22}$ cm-2 (Rea et al., 2007b). This corresponds to an extinction of
A${}_{\rm V}\sim 5$ according to the A${}_{\rm V}-$NH relation inferred from
X-ray scattering halos and supernova remnants (Predehl & Schmitt, 1995). The
unabsorbed X-ray estimate is therefore broadly consistent with a small NIR
extinction correction of $\sim 0.6$ magnitudes, given A${}_{\rm v}\sim$3.5, a
Fitzpatrick extinction curve (Fitzpatrick, 1999) and R${}_{\rm v}=3.1$. This
further implies that the power law of index of $\sim$1 for 4U 0142 is close to
the intrinsic, unattenuated value. Similar arguments can be made for other
established counterparts, such as 1E 2259 and SGR 0501.

Although extinction is generally low at NIR wavelengths, magnetar sight-lines
are frequently in the plane of the Galaxy where even NIR extinctions can be
large. However, this cannot reconcile the lower PL indices of the new
counterparts with previously established ones: correcting for NIR extinction
would only increase the NIR flux and decrease the indices, pushing them
further from the existing population. Assuming that intrinsic indices of
$0.5-1$ are typical, this suggests that the new candidates reported here are
either chance alignments or are fundamentally different in nature to the other
counterparts. This could include, for instance, bound companion stars, a
possibility which we will explore in a subsequent paper (Chrimes et al., in
prep).

A possible exception is AX J1818, for which the two candidates in the error
circle both have $\Gamma$ values similar to known counterparts. The likely
explanation is that one of the sources is the genuine counterpart, and the
other is a brighter, bluer object at a larger distance with more extinction,
such that it appears to have a similar magnitude and colour. There is a
similar situation for 1RXS J1708, which has three similar (in terms of
$\Gamma$) candidates in the error circle. To determine whether this is a
likely scenario by chance, we consider both the magnitude and colour of the AX
J1818 candidates. We first note that the Pchance values (based on F160W
magnitudes only) are high for these sources, at 0.32 and 0.24. Secondly, in
terms of F125W-F160W colours, the AX J1818 values of $\sim$1.45 are typical
for the field: 17 per cent of sources in the HST images have redder colours,
and 83 per cent are bluer. Therefore, it is not improbable to find chance
alignments within the error circle which happen to have a similar appearance
to genuine counterparts.

Although not part of this HST sample, we also calculate the NIR – X-ray
spectral index for the possible Galactic FRB source SGR 1935. Using a
quiescent X-ray flux level of $\sim 5\times 10^{-11}$ erg s-1 cm-2, and HST
measurement of m${}_{\rm F140W}\sim 25$ (Lyman et al., 2021), we find that
this object has $\Gamma\sim 1.2$. Although this is the highest value in the
population, the steep, positive slope is similar to other established
counterparts.

At the extreme low end of the PL index distribution are SGR 0755, possibly an
unrelated HMXB as discussed, and 3XMM J1852, for which we simply selected the
reddest source in the large error circle. If NIR - X-ray spectral indices of
$0.5-1$ are typical of genuine magnetar counterparts, this suggests that
simply searching for anomalously red objects may be not a reliable method of
identification.

Going forwards, spectral energy distributions constructed from photometry will
be needed, if not spectra, to reliably separate magnetar counterparts from
other sources in the field. This can also be seen in Figure 3, where the
counterparts do not always stand out from other sources. Counterpart spectral
energy distributions should be constructed using data taken as close to
simultaneously as possible, given that these sources can be highly variable,
as demonstrated by Figure 4.

##  7 Conclusions

In this paper, we have measured the magnitudes and colours of Galactic
magnetar counterpart candidates in deep HST imaging, adding a later epoch for
several sources, and confirming their variability on 5-10 year time-scales. We
identify six new NIR counterpart candidates for SGR J1622-4950, Swift
J1822.3-1606, CXOU J171405.7-381031, Swift J1833-0832, Swift J1834.9-0846 and
AX J1818.8-1559. This represents a substantial $\sim$50 per cent increase in
the NIR counterpart sample size. Placing these new candidates in the context
of the wider population, we find that they have typical apparent magnitudes
but lower NIR - X-ray indices, with the exception of the AX J1818 candidates.
This implies either that the new candidates are chance alignments, or that the
emission mechanisms are distinct from previously established counterparts. To
make further progress in identifying and understanding these counterparts,
more data points are needed across the optical/NIR, since two-band colours are
not necessarily enough to distinguish them from other sources. It is important
for such observations to be taken as close together in time as possible, as
magnetar counterparts can be highly variable over time-scales of months and
years, and the inferred properties could vary substantially if different
epochs are combined.

## Acknowledgements

AAC is supported by the Radboud Excellence Initiative. AJL has received
funding from the European Research Council (ERC) under the European Union’s
Seventh Framework Programme (FP7-2007-2013) (Grant agreement No. 725246). PJG
acknowledges support from the NRF SARChI program under grant number 111692.
JDL acknowledges support from a UK Research and Innovation Fellowship
(MR/T020784/1). CK and ASF acknowledge support for this research, provided by
NASA through a grant from the Space Telescope Science Institute, which is
operated by the Association of Universities for Research in Astronomy, Inc.

Support for this research was provided by NASA through a grant from the Space
Telescope Science Institute, which is operated by the Association of
Universities for Research in Astronomy, Inc. Observations analysed in this
work were taken by the NASA/ESA Hubble Space Telescope under programs 14805,
15348 and 16019.

This work has made use of ipython (Perez & Granger, 2007), numpy (Harris et
al., 2020), scipy (Virtanen et al., 2020); matplotlib (Hunter,
2007),astropy,777https://www.astropy.org a community-developed core Python
package for Astronomy (Astropy Collaboration et al., 2013; Price-Whelan et
al., 2018) and photutils, an Astropy package for detection and photometry of
astronomical sources (Bradley et al., 2021). We have also made use Seaborn
packages (Waskom, 2021).

This research has made use of the SVO Filter Profile Service
(http://svo2.cab.inta-csic.es/theory/fps/) supported from the Spanish MINECO
through grant AYA2017-84089 (Rodrigo et al., 2012; Rodrigo & Solano, 2020).

This research has made use of software provided by the Chandra X-ray Center
(CXC) in the application of the CIAO package.

This publication makes use of data products from the Two Micron All Sky
Survey, which is a joint project of the University of Massachusetts and the
Infrared Processing and Analysis Center/California Institute of Technology,
funded by the National Aeronautics and Space Administration and the National
Science 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.

Finally, we thank the anonymous referee for their constructive comments
regarding the astrometry and clarity of this manuscript.

## Data Availability

Based on observations made with the NASA/ESA Hubble Space Telescope, obtained
from the data archive at the Space Telescope Science Institute. STScI is
operated by the Association of Universities for Research in Astronomy, Inc.
under NASA contract NAS 5-26555. These observations are associated with
programs 14805, 15348 and 16019 (Levan). The scientific results reported in
this article are based on data obtained from the Chandra Data Archive.

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