# Radio Transients and Variables in the Tenth Deeper, Wider, Faster Observing
Run

D. Dobie,1,2 J. Pritchard,3,2,4 Y. Wang (王远明),3,2,4 L. W. Graham,1 J.
Freeburn,1,2 H. Qiu (邱昊),5 T. R. White,3 A. O’Brien,6 E. Lenc,4 J. K.
Leung,3,2,4 C. Lynch,7,8 Tara Murphy,3,2 A. J. Stewart,3 Z. Wang (王子腾),3,2,4
A. Zic,9,4 T. M. C. Abbott,10 C. Cai (蔡策),11,12 J. Cooke,1,2 M. Dobiecki,1 S.
Goode,1,2 S. Jia (贾淑梅)11, C. Li (李承奎)11, A. Möller,1,2, S. Webb,1,2 J. Zhang
(张洁莱),1,2 S. N. Zhang(张双南)11,12
1 Centre for Astrophysics and Supercomputing, Swinburne University of
Technology, Hawthorn, Victoria, Australia
2 ARC Centre of Excellence for Gravitational Wave Discovery (OzGrav),
Hawthorn, Victoria, Australia
3 Sydney Institute for Astronomy, School of Physics, University of Sydney, NSW
2006, Australia
4 Australia Telescope National Facility, CSIRO, Space and Astronomy, PO Box
76, Epping, NSW 1710, Australia
5 SKA Observatory, Jodrell Bank, Lower Withington, Macclesfield, SK11 9FT, UK
6 Department of Physics, University of Wisconsin-Milwaukee, P.O. Box 413,
Milwaukee, WI 53201, USA
7 International Centre for Radio Astronomy Research, Curtin University, Perth,
WA 6845, Australia
8 ARC Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO-3D)
9 School of Mathematical and Physical Sciences, and Research Centre in
Astronomy, Astrophysics and Astrophotonics, Macquarie University, NSW 2109,
Australia
10 Cerro Tololo Inter-American Observatory, NSF’s National Optical-Infrared
Astronomy Research Laboratory, Casilla 603, La Serena, Chile
11 Key Laboratory of Particle Astrophysics, Institute of High Energy Physics,
Chinese Academy of Sciences, 19B Yuquan Road, Beijing 100049, China
12 University of Chinese Academy of Sciences, Chinese Academy of Sciences,
Beijing 100049, China E-mail<EMAIL_ADDRESS>
(Accepted XXX. Received YYY; in original form ZZZ)

###### Abstract

The Deeper, Wider, Faster (DWF) program coordinates observations with
telescopes across the electromagnetic spectrum, searching for transients on
timescales of milliseconds to days. The tenth DWF observing run was carried
out in near real-time during September 2021 and consisted of six consecutive
days of observations of the NGC 6744 galaxy group and a field containing the
repeating fast radio burst FRB 190711 with the Australian Square Kilometre
Array Pathfinder, the Dark Energy Camera, the Hard X-ray Modulation Telescope
and the Parkes 64m “Murriyang” radio telescope. In this work we present the
results of an image-domain search for transient, variable and circularly
polarised sources carried out with ASKAP using data from the observing run,
along with test observations prior to the run and follow-up observations
carried out during and after the run. We identified eight variable radio
sources, consisting of one pulsar, six stellar systems (five of which exhibit
circularly polarised emission) and one previously uncatalogued source. Of
particular interest is the detection of pulses from the ultra-cool dwarf SCR
J1845–6357 with a period of $14.2\pm 0.3$ h, in good agreement with the known
optical rotation period, making this the slowest rotating radio-loud ultra-
cool dwarf discovered.

###### keywords:

radio continuum: stars – radio continuum: transients – stars: low-mass –
stars: flare – polarization

††pubyear: 2022††pagerange: Radio Transients and Variables in the Tenth
Deeper, Wider, Faster Observing Run–A

##  1 Introduction

The Deeper, Wider, Faster program (DWF; Andreoni & Cooke, 2019) coordinates
simultaneous observations between telescopes across the entire electromagnetic
spectrum to study astrophysical transients on timescales of milliseconds to
days. The tenth DWF observing run took place from 2021 September 5–10 and
consisted of simultaneous observations with the Australian Square Kilometre
Array Pathfinder (ASKAP; Hotan et al., 2021), the Parkes 64m “Murriyang”
radio-telescope, the Dark Energy Camera (DECam) and the Hard X-ray Modulation
Telescope (HXMT) carried out on a daily cadence. We observed fields containing
the NGC 6744 galaxy group and the repeating fast radio burst FRB 190711, for
approximately 1.5 and 3 h per night respectively.

ASKAP has been used in previous DWF runs (Cooke et al. in prep.), but only to
search for Fast Radio Bursts (FRBs) in high time resolution data. However,
ASKAP has previously been used for similar multi-wavelength studies, for
example a targeted campaign of Proxima Centauri (Zic et al., 2020) and co-
observing with the Transiting Exoplanet Survey Satellite (Rigney et al.,
2022). The tenth DWF observing run is the first time that ASKAP
interferometric visibilities have been recorded as part of DWF observing,
enabling image-domain searches for transients on timescales of minutes to
days.

Past widefield searches for transient and variable sources at gigahertz
frequencies have generally observed on timescales of weeks to years (e.g.
Mooley et al., 2013; Mooley et al., 2016; Law et al., 2018; Anderson et al.,
2020; Dobie et al., 2022), while those using faster cadences tend to consist
of narrow-field observations targeting known sources (e.g. Bell et al., 2011;
Bower & Saul, 2011; Driessen et al., 2022). The $30\,\deg^{2}$ field-of-view
provided by ASKAP has allowed us to perform a widefield search on a high
cadence and hence, the observations presented in this work provide a window
into a previously unexplored part of the radio transient parameter space.

The cadence of these observations means that our search was not sensitive to
the majority of extragalactic radio transients, which only exhibit intrinsic
variability on day–week timescales during the very early-time rise in their
light curves. Some may produce shorter-lived emission (e.g. reverse shocks
from gamma-ray bursts Laskar et al., 2013; Lloyd-Ronning, 2018), but those
compose a small subset of already rare events. Instead, our observations are
most sensitive to variability on timescales of minutes to days, such as the
refractive scintillation of extragalactic sources. This variability is
characterised by quasi-random oscillations on timescales of days with an
amplitude of tens of percent (Walker, 1998). The properties of this
variability can be used to study both the objects producing the emission (e.g.
Ross et al., 2022) and the properties of the intervening material (e.g. Wang
et al., 2021a).

Variants of neutron star and systems containing them, such as pulsars,
magnetars and X-ray binaries (XRBs), are known to produce variable radio
emission on timescales of seconds to days. The emission from all of these
systems is generally coherent, and can also be highly circularly polarised.
Their variability can be extrinsic (e.g. the scintillation of any compact
source), or intrinsic, such as pulsar mode changes (Hobbs et al., 2016),
magnetar outbursts (Rea & Esposito, 2011) and XRB flares (Fender et al.,
2009). The origin of Galactic Centre Radio Transients (Hyman et al., 2002,
2005, 2009) is as yet unknown, but may also be related to neutron stars.
Recent work has also discovered a number of similar radio variables in or near
the Galactic plane that are comparable to the aforementioned classes, but do
not their standard paradigm (Wang et al., 2021b; Hurley-Walker et al., 2022;
Wang et al., 2022). However, the primary goal of the DWF program is the multi-
wavelength detection of an extragalactic FRB, and the fields observed in this
work were chosen to minimise both the potential Galactic contribution to the
FRB dispersion measure, and extinction at optical wavelengths. Hence, we
expect the detection rates of these neutron star related objects, which are
predominantly situated in the Galactic plane, to be low.

Some stars can produce bursts or flares (see Güdel, 2002, for an overview)
that are often coherent, last seconds–minutes, and can also be highly
circularly polarised (Dulk, 1985). Variable quiescent emission has also been
observed from stellar systems, has been hypothesised to originate from the
combined contribution of multiple small flares (Forbrich et al., 2011), but
has also been demonstrated to be caused by rotational modulation in some
instances (e.g. Leto et al., 2006). While the underlying distribution of stars
is Galactic, the distribution of those detectable in this survey is
sensitivity limited and we therefore we don’t expect the high Galactic
latitude of these observations to impact our ability to detect them.

In this work, we present a search for transient and variable sources in the
ASKAP observations carried out during the tenth DWF run. This work is focused
on “slow” (timescales longer than minutes) radio variability and hence we do
not discuss the search for FRBs with ASKAP or Parkes, nor the optical
transient search carried out with DECam. We have carried out two radio
variability studies – the first using each day’s observations; and the second
on 15-minute images created from each observation. We have also searched for
circularly polarised sources, as a substantial fraction of the variable radio
emission these observations are sensitive to is expected to be circularly
polarised.

Field | SBID | Start Time | Duration | $\sigma_{\rm RMS}$
---|---|---|---|---
|  | (UTC) | (hh:mm:ss) | ($\mu$Jy)
FRB190711 | 31377 | 2021-08-28 15:45:15 | 03:22:50 | 72
FRB190711 | 31495 | 2021-08-31 07:39:48 | 03:21:01 | 119
FRB190711 | 31585 | 2021-09-02 07:03:48 | 03:21:21 | 65
FRB190711 | 31652 | 2021-09-03 10:48:04 | 03:23:22 | 59
FRB190711 | 31701 | 2021-09-04 06:25:30 | 00:48:24 | 131
FRB190711 | 31702 | 2021-09-04 07:19:58 | 03:21:12 | 64
FRB190711 | 31751 | 2021-09-05 06:22:03 | 03:21:28 | 65
FRB190711 | 31822 | 2021-09-06 06:21:53 | 03:21:20 | 65
FRB190711 | 31883 | 2021-09-07 06:25:26 | 03:21:21 | 67
FRB190711 | 31945 | 2021-09-08 06:22:00 | 03:21:27 | 72
FRB190711 | 32016 | 2021-09-09 06:26:48 | 03:23:24 | 67
FRB190711 | 32036 | 2021-09-10 06:22:01 | 03:23:37 | 66
NGC6744 | 31349 | 2021-08-27 16:37:24 | 01:21:05 | 87
NGC6744 | 31584 | 2021-09-02 05:41:31 | 01:22:15 | 107
NGC6744 | 31640 | 2021-09-03 05:15:00 | 01:22:28 | 107
NGC6744 | 31651 | 2021-09-03 09:22:47 | 01:25:15 | 92
NGC6744 | 31700 | 2021-09-04 05:21:59 | 01:03:30 | 125
NGC6744 | 31750 | 2021-09-05 04:59:58 | 01:22:00 | 110
NGC6744 | 31821 | 2021-09-06 04:59:57 | 01:21:53 | 108
NGC6744 | 31882 | 2021-09-07 05:02:47 | 01:22:37 | 112
NGC6744 | 31944 | 2021-09-08 05:00:03 | 01:21:53 | 119
NGC6744 | 32015 | 2021-09-09 05:00:03 | 01:26:43 | 114
NGC6744 | 32018 | 2021-09-09 12:09:26 | 07:01:07 | 45
NGC6744 | 32035 | 2021-09-10 05:00:01 | 01:21:58 | 115
NGC6744 | 32039 | 2021-09-10 12:08:40 | 07:01:19 | 42
NGC6744 | 32235 | 2021-09-19 05:20:01 | 10:01:01 | 38
Table 1: Details of the ASKAP observations carried out as part of the tenth
DWF observing run, including the median image noise, $\sigma_{\rm RMS}$. We
also provide the scheduling block (SBID) which can be used to access the data
via the ASKAP Science Data Archive.

##  2 Searching for Transients and Variables with ASKAP

###  2.1 Observations

All ASKAP observations were carried out with the closepack36 beam footprint
(see Fig. 20 of Hotan et al., 2021) centered on 19:08:00.000,$-$64:30:00.00
and 22:00:20.447,$-$79:55:21.84 for the NGC 6744 and FRB 190711 fields,
respectively, and a central frequency of 943 MHz with 288 MHz of bandwidth.

We carried out nightly observations of both fields from 2021 September 5 to
10, targeting the NGC 6744 field for approximately 80 minutes per night, and
the FRB 190711 field for 3 hours and 20 minutes per night. ASKAP was on-field
for the entirety of the run, but also carried out a number of observations of
both fields in the week prior to the run to test both the operation and
scheduling of the telescope. Additionally, we carried out three target-of-
opportunity observations of the NGC 6744 field in response to our discovery of
radio emission from SCR J1845–6357 (see Section 4.1), which we also include in
this analysis. A summary of the observations reported in this paper can be
found in Table 1.

Each observation was calibrated and imaged using the default ASKAPsoft
pipeline (Whiting et al., 2017), which produces calibrated visibilities, full-
polarisation images and noise maps, as well as Stokes I source catalogues for
each observation.

Name | Right Ascension | Declination | $\eta$ | $V$ | Polarisation | Fast Imaging | Gaia parallax | Optical period
---|---|---|---|---|---|---|---|---
| (hh:mm:ss) | (dd:mm:ss) |  |  |  |  | (mas) | (days)
SCR J1845–6357 | 18:45:13.73 | -63:57:34.9 | 96 | 1.0 | Yes | Yes | $249.7\pm 0.1$ | $0.588\pm 0.008$
UCAC 053-023945 | 21:07:28.58 | -79:26:27.3 | 3.4 | 0.55 | Yes | No | $14.44\pm 0.02$ | $17.16\pm 0.2$
Gaia 6438561254116213632 | 19:04:03.68 | -64:00:12.1 | 5.9 | 30 | Yes | Yes | $2.27\pm 0.05$ | –
UCAC 048-020372 | 22:01:25.30 | -80:34:35.6 | 4.27 | 1.3 | Yes | No | $13.32\pm 0.03$ | $9.5\pm 1.4$
V* CF Oct | 20:49:37.54 | -80:08:00.6 | 79 | 0.42 | No | No | $4.45\pm 0.06$ | 19.90–20.45
ASKAP J212525.4-813829 | 21:25:25.35 | -81:38:28.7 | 3.5 | 0.17 | No | Yes | – | –
PSR J1933–6210 | 19:33:32.39 | -62:11:46.9 | 83 | 0.64 | No | Yes | – | –
CD–64 1208 | 18:45:37.12 | -64:51:49.3 | 170 | 0.40 | Yes | Yes | $35.2\pm 0.2$ | $0.354\pm 0.004$
Table 2: Properties of the eight variable sources discovered in this work.
$\eta$ and $V$ are the variability metrics calculated by the VAST pipeline
(see Section 2.2 for details). “Polarisation” denotes sources that were found
by the circular polarisation search (Section 2.3) and “Fast Imaging” denotes
sources that were found by the fast-imaging search (Section 2.4). Optical
periods are measured using TESS observations (Section 3.2.2) except for CD–64
1208 where we report the measurement from García-Alvarez et al. (2011) and V*
CF Oct where we report the period range measured by Borisova et al. (2012).

###  2.2 VAST pipeline

We carried out a search for variable sources with the Variables And Slow
Transients (VAST) pipeline111https://vast-survey.org/vast-pipeline/ (Murphy et
al., 2021; Pintaldi et al., 2022), using the Stokes I images, noise maps and
source catalogues produced by ASKAPsoft. As in Dobie et al. (2022) we
performed source association with a de Ruiter radius of 5.68 (Scheers, 2011)
and used the equations of Condon (1997) to recalculate the source fitting
uncertainty estimates.

We applied the following cuts to minimise the number of image artefacts
contaminating our sample:

  * •

a ratio of integrated to peak flux density $<1.5$;

  * •

no relations, i.e. it is not associated with any other source222See
https://vast-survey.org/vast-pipeline/design/association/##relations;

  * •

distance to nearest source $>1\,$′;

  * •

signal-to-noise ratio $>5$.

We note that while these cuts potentially exclude real variable sources, in
the absence of dedicated artefact detection algorithms (which are currently
under development) they are necessary in order to remove the substantial
number of artefacts that are associated with bright sources in our data.

For sources detected in at least two observations, we carried out a standard
$\eta$–$V$ variability search where

$V=\frac{1}{\overline{S}}\sqrt{\frac{N}{N-1}\left(\overline{S^{2}}-\overline{S}^{2}\right)},$
(1)

is the flux density variability relative to the weighted mean and

$\eta=\frac{N}{N-1}\left(\overline{wS^{2}}-\frac{\overline{wS}^{2}}{\overline{w}}\right),$
(2)

quantifies the statistical significance of that variability. In both the above
equations $N$ is the number of datapoints, $S$ is the flux density, $w$ is the
inverse uncertainty and overbars denote the mean of a quantity. These
statistics were originally defined by Swinbank et al. (2015) and a full
description of the search technique we used can be found in Dobie et al.
(2022). We then manually inspected all candidates, removing all of those that
were likely imaging artefacts or were quasi-random, low-amplitude ($V\lesssim
0.3$) oscillations around a mean flux density (as expected from refractive
scintillation). All sources with a single detection were also manually
inspected. From 2021-09-07 onwards this search was carried out the morning
after each observation, with a list of candidates compiled before the next
day’s observations began. This is the first time an image domain radio
transient search has been carried out in near-real-time, and ensured that we
were able to trigger multi-wavelength follow-up observations of any candidates
as necessary.

Eight sources passed our vetting process333PSR J1933–6210 does not pass the
criteria in the final pipeline run due to a spurious single-epoch noise spike
offset from the source by 0.43′. Gaia 6438561254116213632 does not pass the
criteria in the final run due to a faint source offset by 0.43′ detected in
the 3 deep epochs. However, both passed our selection criteria in earlier
pipeline runs and hence we include them in this work.. Crossmatching with
SIMBAD, NED and the TESS Input Catalogue, we find that six are coincident with
known stellar systems, one is coincident with a known pulsar and the remaining
variable has no known multi-wavelength counterparts. These sources and their
variability metrics are listed in Table 2 and discussed in detail in Section
4.

###  2.3 Polarisation Search

We performed a circular polarisation search to identify sources with a high
fractional circular polarisation $f_{p}=|S_{V}|/S_{I}$ using a similar
technique to that presented by Pritchard et al. (2021). This search does not
directly probe variability but, as we note in Section 1, the variable sources
that these observations are predominantly sensitive to can often produce
circularly polarised emission. Hence, this search serves as a way to detect
variable sources of interest that may have been missed by our other searches
(e.g. highly polarised pulses that are detected at low significance).

We first extracted Gaussian source components from the Stokes V images using
the selavy (Whiting & Humphreys, 2012) source finder package, using the same,
standard selavy settings as used in ASKAPsoft for the Stokes I images. We ran
source extraction twice, with the second pass running over the inverted
images, to extract sources with both positive and negative Stokes V emission.
We then generated associations between the Stokes I and V components by
performing a many-to-many crossmatch within a search radius of
$6\text{\,}\arcsec$. Many-to-many association allows for all permutations of
I-V matches between multi-component sources, ensuring no candidates are missed
due to incorrect association with near neighbours or selavy artefacts.

We then crossmatched the resulting list of I-V associations across each epoch,
and required that candidates contained at least one epoch with $f_{p}>0.06$ in
order to remove I-V associations attributed to polarisation leakage (which can
be as high as $\sim 2$ per cent; Pritchard et al., 2021). This resulted in a
final set of 51 candidates in the FRB190711 field and 74 candidates in the
NGC6744 field. We manually inspected each candidate to identify associations
to imaging artefacts caused by bright or extended sources and associations to
spurious noise peaks in Stokes V, and identified five sources coincident with
stars (see Table 2.

###  2.4 Fast-imaging Search

We carried out a search for rapid variable sources on 15-minute timescales
with the VAST fast-imaging pipeline (Wang Y. et al. in prep) using the self-
calibrated visibilities produced by ASKAPsoft.

We processed each of the 36 beams separately, and all imaging was carried out
using CASA. For each beam, we made an independent sky model image using multi-
scale multi-frequency synthesis with two Taylor terms from the self-calibrated
visibilities from the full observation. We performed a deep clean (10 000
iterations) using Briggs weighting with robustness of 0.5 to provide a
compromise between resolution and sensitivity, and achieved a mean residual
RMS noise of $\sim$70 $\mu$Jy beam-1 for the FRB190711 fields444Excluding
SB31701 which is too short to conduct a fast-imaging search because each
source would have 3 measurements at most. and a mean residual RMS noise of
$\sim$100 $\mu$Jy beam-1 for the NGC6744 fields. We then converted each sky
model image to model visibilities, and subtracted the model visibilties from
the calibrated visibilities. These model-subtracted visibilities were imaged
at 15-min timesteps using the same weighting parameters, generating a series
of short 15-min images for variability analysis.

For each beam, we generated a source catalog from the independent sky model
restored image using Aegean (Hancock et al., 2012, 2018) using a $6\sigma$
detection threshold. For each source in the sky model, we converted the global
coordinate to the pixel position in each image, and at each position measured

  * •

the deep flux density $S_{\mathrm{d}}$ on the sky model restored image;

  * •

the residual flux density $S_{\mathrm{r}}$ on the sky model residual image;
and

  * •

the peak flux density $S_{i,\mathrm{s}}$ on the $i$-th short 15-min image.

The $i$-th data point of the intra-observation light curve is then given by

$S_{i}=S_{i,\mathrm{s}}+S_{\mathrm{d}}-S_{\mathrm{r}}$ (3)

We then carried out a variability analysis, using the modulation index $m$ to
characterize the magnitude of variability, and reduced chi-squared $\chi^{2}$
to measure its statistical significance (See Section 3.2 of Wang et al.,
2021a). We selected candidates with a reduced chi-squared
$\chi^{2}>2.0\sigma_{\chi^{2}}$ (where $\sigma_{\chi^{2}}$ is the standard
deviation measured by fitting a Gaussian function to the distributions of
reduced chi-squared in logarithmic space) and a modulation index $m>5\%$ (for
ruling out potential bright sources of which high chi-square value are
dominated by high self-noises; see Kulkarni, 1989). We also ruled out
potential extended sources with a ratio of integrated to peak flux density
$>1.5$, and sources more than one full-width half maximum (FWHM; $\sim
0.8\,\deg$) from the beam centre. We manually inspected each candidate,
including comparing its light curve with the light curve of the same source as
observed by neighbouring beams to rule out the variability being caused by
instrumental effects. This search ultimately revealed five variable sources as
described in Table 2.

Energy range (keV) | Upper limit (erg cm-2 s-1)
---|---
| FRB190711 | NGC 6744
1–10 | $8.9\times 10^{-10}$ | $5.6\times 10^{-10}$
10–30 | $1.0\times 10^{-9}$ | $9.9\times 10^{-10}$
28-250 | $1.4\times 10^{-9}$ | $1.5\times 10^{-9}$
Table 3: Constraints (calculated as $3\sigma$ upper limits) on transient X-ray
emission in the FRB190711 and NGC 6744 fields during our observations. The
sensitivity of each detector is time variable and these constraints correspond
to a typical period during our observations.

##  3 Multi-wavelength Observations

###  3.1 Simultaneous

####  3.1.1 Dark Energy Camera

We carried out simultaneous observations of both fields with the Dark Energy
Camera (DECam; Flaugher et al., 2015), with a 3 $\deg^{2}$ footprint ($\sim
2.5\deg^{2}$ effective field-of-view accounting for chip gaps) centered on
19:07:58.52 $-$64:30:00.4 and 21:57:20.87 $-$80:17:00.8 for the NGC 6744 and
FRB 190711 fields respectively. We used the standard DWF observing strategy of
20 s $g$-band exposures with a typical readout of 30 s. We achieved a typical
depth of 22.8 mag and a typical seeing of 1.6″. An overview of the typical
data reduction process can be found in Webb et al. (2021) and Andreoni et al.
(2020). An optical transient search was carried out in real-time, but
discussion of it is beyond the scope of this work, and will instead be
presented in a future manuscript.

####  3.1.2 Hard X-ray Modulation Telescope

The Hard X-ray Modulation Telescope (HXMT; Zhang et al., 2020) consists of
three separate instruments – the High Energy X-ray Telescope (HE; 27–250 keV;
Liu et al., 2020), the Medium Energy X-ray Telescope (ME; 10–35 keV; Cao et
al., 2020) and the Low Energy X-ray Telescope (LE; 1–10 keV; Chen et al.,
2020). The instruments are co-aligned and were centered on 19:08:00
$-$64:30:00 and 21:57:40.8 $-$80:21:36 for the NGC 6744 and FRB 190711 fields
respectively. The effective fields of view are $1.1\times 5.7$ deg2 (HE),
$1\times 4$ deg2 (ME) and $1.6\times 6$ deg2 (LE) although the sensitivity
across the field is not uniform. Observations were carried out simultaneously
with ASKAP, although we note that only Gaia 6438561254116213632 and UCAC
048-020372 were within the HXMT field of view.

We do not detect any transient emission across either field in any instrument
using the search technique described by Guidorzi et al. (2020b, a). While the
sensitivity of the telescope is not static, we place constraints on transient
X-ray emission in the field by estimating a typical upper limit for each field
and detector across the whole observing run. Table 3 shows these constraints
as 3$\sigma$ upper limits.

###  3.2 Archival

####  3.2.1 Gaia

To determine precise distances for the sources we have identified in the three
searches, we crossmatched the seven non-pulsar sources with the Gaia Data
Release 3 catalogue (DR3; Gaia Collaboration et al., 2016, 2022). We searched
for all catalogued sources within 10″of the radio source and then calculated
the proper motion corrected positions at 2021-09-05. Six sources had Gaia
counterparts with proper motion corrected positions in agreement with the
radio position to within uncertainties. We list the parallax of each source in
Table 2.

####  3.2.2 Transiting Exoplanet Survey Satellite

We used data from the Transiting Exoplanet Survey Satellite (TESS) to search
for optical periodicity from the six stellar sources. Two sources (V* CF Oct,
UCAC 053-023945) have light curves accessible via the MAST archive, while
CD–64 1208 is not within the footprint of any TESS observations. The remaining
three sources with optical counterparts are within the TESS footprint, but do
not have pre-existing light curves. Gaia 6438561254116213632 is too close to
TYC 9078–815–1 to have reliable photometry, but for the other two sources (SCR
J1845–6357 and UCAC 048-020372) we manually extract light curves from the TESS
Full-Frame-Images using the standard lightkurve method of threshold masking
and background subtraction555https://docs.lightkurve.org/tutorials/2-creating-
light-curves/2-1-cutting-out-tpfs.html at the Gaia proper-motion corrected
position at the time of observation.

Qualitatively, all five sources with TESS light curves exhibit clear optical
periodicity. We generated a Lomb-Scargle periodogram of each light curve and
report the period (Table 2) corresponding to the peak power and the associated
uncertainty using the FWHM of the peak. For sources that were observed in
multiple TESS sectors we performed the aforementioned calculations on a
sector-by-sector basis and then combined the resulting estimate of the period.

Figure 1: ASKAP light curves of the 8 variable sources found in this work.
After manually inspecting the images of all 8 variables, we have determined
that the non-detections of SCR J1845–6357 and ASKAP J212525.4-813829 and one
non-detection of UCAC 053-023945053 are sub-threshold detections and we
therefore show the forced fit flux measurements as calculated by the VAST
pipeline as measurements with open markers. Non-detections of other sources
are shown as $3\sigma$ upper limits, also with open markers.

##  4 Radio sources of interest

We found eight variable radio sources in total, with all passing the VAST
pipeline variability criteria and five passing the fast-imaging variability
criteria. In addition, our polarisation search revealed that five of the
variables exhibit circularly polarised emission, while there are no further
circularly polarised sources in the field. Seven radio sources are associated
with known objects – six stars and one pulsar. While the purpose of the DWF
program is to have simultaneous multi-wavelength observations of the sky, the
size mismatch between the DECam and ASKAP fields of view means that UCAC
048-020372 is the only variable radio source with simultaneous DECam
observations. Gaia 6438561254116213632 is within the DECam field of view, but
lies in a chip gap.

Figure 2: Intra-observation light curve of SCR J1845–6357, using 15-minute
samples created as part of the VAST fast-imaging search (Section 2.4). We have
excluded the first and last observations which were carried out long
before/after the other observations. The shaded region denotes the duration of
the simultaneous Swift observation, in which no X-ray or UV emission was
detected. Figure 3: Intra-observation light curves of SCR J1845–6357 from the
five epochs where we detected a pulse, phased to the 14.1 hr optical period
measured using TESS data.

###  4.1 SCR J1845–6357

SCR J1845–6357 is an M8.5-dwarf/T6-dwarf binary system (Kasper et al., 2007)
with a parallax of $249.7\pm 0.1$ mas and a proper motion of 2.6 ″per year
(Gaia Collaboration et al., 2016, 2022). It was first noted as a source of
interest through the VAST pipeline search using data up to and including the
first epoch of the observing run (SB31700) and was later also detected by both
the polarisation and fast-imaging searches. The radio light curve (Figure 1)
is characterised by a series of marginal detections of $\sim 0.5\,$mJy with
four observations showing an increased flux density of either $\sim 3$ mJy or
$\sim 1$ mJy. Based on the first two detections of $\sim 3$ mJy, we triggered
additional ASKAP observations on 2021-09-09 (SB32018), 2021-09-10 (SB32039)
and 2021-09-19 (SB32235) to characterise the observed behaviour.

Figure 2 shows the intra-observation light curve, from which we conclude that
the variability stems from multiple pulses, each lasting $\sim 2$ h. The radio
emission is highly ($\sim$90%) circularly polarised during the pulses, but we
do not detect any polarised emission from the source in its quiescent state.
We detected a fifth pulse in the final epoch that is not visible in the full
light curve (Figure 1) because of the long integration time, which averages it
out across five times the pulse duration.

SCR J1845–6357 is known to be variable at X-ray wavelengths, and
$L_{X}=8\times 10^{27}$ erg s-1 flares have previously been detected from it
(Robrade et al., 2010). We obtained a 3.5 ks exposure with Swift (ToO request
#16280) from 2021-09-10 15:13:02 to 2021-09-10 19:53:53 to search for
contemporaneous radio–X-ray flares. We detected 19 photons spatially
coincident with SCR J1845–6357 over the full observation, but we were unable
to obtain a spectra. The count rate is consistent with the quiescent flux
observed by Robrade et al. (2010). No emission was detected with the UV
instrument (UVOT). Noting that this observation overlaps with the fourth pulse
detected with ASKAP (see Fig. 2), we conclude that the X-ray and radio
activity are not coupled.

SCR J1845–6357 was observed with TESS during Sector 13 and we measure an
optical period of $14.1\pm 0.2\,$h after manually extracting the light curve
at the proper-motion corrected source location. We also performed a
periodicity search on the intra-observation light curve (see Appendix A) and
measure a radio period of $14.2\pm 0.3$ h666This measurement is also in good
agreement with preliminary analysis of follow-up observations conducted with
the Australia Telescope Compact Array (ATCA) that will be presented in a
separate manuscript..

Figure 3 shows the intra-observation light curves for the five epochs with
detected pulses folded to the TESS period, showing that the pulses are all
aligned to the same rotational phase, and suggesting that the variability at
each wavelength shares a common origin. While SCR J1845–6357 is known to have
a binary companion, the orbital separation is approximately 4 AU (Kasper et
al., 2007). The corresponding orbital period is therefore on the order of
decades and hence we rule out the periodicity originating from the binary
orbit. We also rule out the radio variability originating from an interaction
between the two stars for similar reasons. The periodic signal in the TESS
light curve is quasi-sinusoidal and consistent with the signature of spots on
a rotating star. The radio light curve is also consistent with pulses from a
rotating star (e.g. comparable to UV Ceti; Zic et al., 2019a; Bastian et al.,
2022). We cannot conclusively rule out the pulses being produced by the
interaction between the star and an exoplanet (or an undetected low-mass
stellar companion) as this scenario would produce periodic, circularly
polarised radio pulses similar to what we observe (e.g. Zarka, 2007). However,
this and other similarly exotic scenarios are unlikely given the behaviour of
the star at optical wavelengths.

We conclude that the observed radio variability stems from rotational
modulation, making this the slowest rotating radio-pulsing ultra-cool dwarf
discovered to-date. It is also one of only a small number of ultra-cool dwarfs
detected at sub-gigahertz frequencies (Zic et al., 2019a; Vedantham et al.,
2020). Further analysis of this source, including the results of our ongoing
monitoring campaign, will be presented in a future manuscript.

###  4.2 UCAC 048-020372

UCAC 048-020372 is a known cool dwarf (likely M5V; Stassun et al., 2019) with
a parallax of $13.32\pm 0.03$ mas (Gaia Collaboration et al., 2021). We
measure an optical period of $9.5\pm 1.4$ days after combining data from TESS
sectors 13 and 27. It is the only object in our sample that was covered by
simultaneous DECam observations.

UCAC 048-020372 is detected in a single ASKAP observation (SB31751;
2021-09-05) with a flux density of $330\pm 50\,\mu$Jy. We also measure a
fractional circular polarisation of $\sim 60$%. The intra-observation light
curve for that epoch shows no significant variability, suggesting that the
outburst lasted longer than the observation duration of approximately 200
minutes. It is not detected in the intra-observation imaging of any other
epoch.

Figure 4 shows the DECam light curve across the six nights of the run, showing
that the source exhibits minimal variability on the observed timescales. We
see a small ($\Delta m\approx 0.1$) flare on 2021-09-07 at 08:00 UTC, and
marginal evidence for smaller flares on 2021-09-09 and 2021-09-10, but no
unusual behaviour during the period surrounding the radio detection. Further
radio observations are required to determine whether the radio emission is due
to rotational modulation, as our observations sample less than two rotations
of the star.

Figure 4: Optical light curves of UCAC 048-020372 (blue circles) and an
unrelated reference source in the field (grey crosses) across the six nights
of the observing run. Observations were carried out with the Dark Energy
Camera using the $g$ band filter and there were simultaneous ASKAP
observations on all nights. The radio emission from UCAC 048-020372 was
detected on the first night of DECam observing (2021-09-05). We find strong
evidence that UCAC 048-020372 is variable at optical wavelengths, but rule out
any correlation with the observed radio variability.

###  4.3 V* CF Oct

V* CF Oct is a likely RS CVn star (e.g. Pollard et al., 1989; Borisova et al.,
2012) with a parallax of $4.45\pm 0.06$ mas (Gaia Collaboration et al., 2021).
Borisova et al. (2012) found a rotational period of 19.90–20.45 days, with the
large range caused by differential rotation on the stellar surface. The star
is known to be active at radio wavelengths. Slee et al. (1987a); Slee et al.
(1987b) reported the detection of circularly polarised bursts at 8.4 GHz
reaching tens of mJy. It has also been detected with a flux density of 2 mJy
at 843 MHz (Vaughan & Large, 1987), broadly consistent with our measurements.
The source exhibits significant radio inter-observation variability
($\eta=78.5$, $V=0.42$), but does not appear variable on 15-minute timescales
except for a slight rise across the final observation. We also do not detect
any circularly polarised emission, despite it being it being common in radio-
loud RS CVn systems (García-Sánchez et al., 2003).

The radio light curve morphology is of particular interest, with no clear
trend in the first four measurements followed by a smooth, quasi-parabolic,
decline and rise (which we henceforth refer to as “the dip”). We are unable to
conclusively determine the origin of this variability with existing
observations. However, there are a number of plausible scenarios which could
explain the observed behaviour.

The dip is not consistent with a simple sinusoid at the optical rotation
period (and is instead better fit by a period of $\sim 12$ d), but we cannot
rule out the variability being caused by some form of rotational modulation.
For example, if the star has a large number of magnetically active regions
distributed unevenly across the surface, the observed light curve may be
explained by a particularly under-active region rotating in and out of view
(e.g. Pakhomov & Gorynya, 2015a).

While V* CF Oct has a binary companion, the system is known to be non-
eclipsing (Pollard et al., 1989), and hence we rule out an eclipse as the
origin of the dip. The dip may originate from some form of orbital interaction
(e.g. direct orbital modulation, or simply decreased emission near apoapsis),
although we note that RS CVn are typically tidally locked (Pakhomov & Gorynya,
2015b) and hence a simple explanation along these lines is disfavoured for
similar reasons as above.

Ultimately, further interpretation of this source is limited by our relatively
short observing campaign which does not cover a single rotational/orbital
period. A dedicated observing campaign spanning at least a month will shed
light on the cause of this intriguing variability, while Very Long Baseline
Interferometry would be useful in determining whether the radio emission
originates from one star in the system or the binary separation region.

Figure 5: Intra-observation light curve of PSR J1933–6210 from SB32018 using
15-minute samples generated as part of the VAST fast-imaging search (see
Section 2.4). The observed variability is likely caused by diffractive
scintillation.

###  4.4 PSR J1933–6210

PSR J1933–6210 is a millisecond binary pulsar with a spin period of $\sim
3.54$ ms and a dispersion measure of 11.52 pc cm-3 (Jacoby et al., 2007;
Graikou et al., 2017). It was noted as a source of interest in the VAST
pipeline search and we measure significant variability in the full light
curve, with $\eta=83.4$ and $V=0.64$. PSR J1933–6210 has been observed to
exhibit variability due to diffractive scintillation at 1.3 GHz with a
timescale of $\sim 2$ h (Graikou et al., 2017), longer than most of our
observations of this field. Figure 5 shows the intra-observation light curve
of this source from SB32018 where we measure flux densities spanning 0.5–4 mJy
across 7 h of observation with a characteristic timescale broadly in agreement
with that reported by Graikou et al. (2017). PSR J1933–6210 exhibits similar
variability in the two other long observations (SB32039 and SB32235), albeit
with a lower average flux density. We therefore conclude that the observed
variability is solely due to diffractive scintillation.

Figure 6: Dynamic spectra of CD–64 1208 showing the detection of four
circularly polarised bursts on 2021-09-19. Top: Stokes I. Bottom: Stokes V.

###  4.5 CD–64 1208

CD–64 1208 is a K5Ve star (Torres et al., 2006) with a parallax of $35.2\pm
0.2$ mas (Gaia Collaboration et al., 2021) and a rotation period of $8.5\pm
0.1$ h (García-Alvarez et al., 2011).

The star was first noted as a source of interest in the VAST pipeline search
where we measure $\eta=169$ and $V=0.4$. The first 13 epochs of the inter-
observation light curve (Fig. 1) show a small degree of variability,
consistent with slow variations in the flux of quiescent emission. It exhibits
no clear variability in the intra-observation light curves except for the
final epoch (SB32235) where we detect a highly circularly polarised ($\sim
100\%$) quadruple outburst spanning approximately 3 h. This part of the
rotational phase is covered by multiple other epochs and we find no evidence
for comparable behaviour in any of them.

To study the structure of these bursts in more detail we created dynamic
spectra for all Stokes parameters. We phase rotated the model-subtracted
visibilities (generated during the fast-imaging search; see Section 2.4) from
the beam center to the coordinates of CD–64 1208. To minimize the influence of
poorly-modelled diffuse emission on the dynamic spectra, we vector-averaged
visibilities for each instrumental polarization only across baselines longer
than 200 m. We combined the complex visibilities for each instrumental
polarization to produce dynamic spectra for full Stokes parameters.

Figure 6 shows the resulting Stokes I and V dynamic spectra (we do not show
Stokes Q or U as the source is not detected). We find that the bursts show
frequency structure, with the first burst being band-limited between 850–1050
MHz and the final two having a low-frequency cutoff of $\sim 900\,$MHz. The
second burst exhibits a frequency drift of approximately $-1.1\,$MHz/s,
similar to that observed in pulses from UV Ceti, TVLM 513–46, and 2M 0746+20
(Lynch et al., 2015; Zic et al., 2019b). However, in those instances the
pulses and drift were attributed to rotationally modulated auroral emission
produced by the electron cyclotron maser instability (ECMI; Treumann, 2006),
with pulses detected at the same rotational phase over multiple stellar
rotations. In the case of CD–64 1208 we have comprehensive coverage of the
full stellar rotation period and only detect the four pulses in SB32235, with
a 9 day gap separating the previous observation at the same rotational phase
in SB32039. Hence, if this variability is rotationally modulated the local
plasma conditions must have only become favourable for ECMI to operate in the
previous 9 days. Alternatively, the four bursts may be driven by stochastic
stellar magnetic activity (e.g. Villadsen & Hallinan, 2019). Further
monitoring will distinguish between these competing scenarios.

Figure 7: Intra-observation light curve of Gaia 6438561254116213632 from
SB31750 using 1-minute samples, showing that the radio emission originates
from a flare lasting approximately 10 minutes.

###  4.6 Gaia 6438561254116213632

This source has only previously been catalogued by Gaia, likely due to its
proximity to TYC 9078–815–1, a 10th magnitude star only 4 ″away. It has a
parallax of $2.27\pm 0.05$ mas, and is classified as a likely cataclysmic
variable with 84% confidence in Gaia DR3.

Gaia 6438561254116213632 is only detected in a single ASKAP observation
(SB31750; 2021-09-05) where we measure a peak flux density of $510\pm
60\,\mu$Jy with a fractional circular polarisation of 98%. The intra-
observation light curve for that epoch shows a single integration detection of
$1.6\pm 0.1$ mJy. We created a higher time resolution light curve following
the same procedure used to generate the dynamic spectra of CD–64 1208 (Section
4.5). To achieve a good signal-to-noise we then averaged across all sub-bands
and every six integrations, resulting in a temporal resolution of 1 minute.

The resulting light curve (Fig. 7) shows a single burst lasting approximately
10 minutes. Accounting for the possibility of beamed emission, we infer a peak
radio luminosity of $\sim 1\times 10^{18}$ erg s-1 Hz-1, consistent with other
detections of stars with ASKAP (Pritchard et al., in prep.).

###  4.7 ASKAP J212525.4-813829

ASKAP J212525.4-813829 is a previously uncatalogued radio source that exhibits
a gradual rise across the course of the observing period (Fig. 1), with
$\eta=3.5$, $V=0.17$. The source shows negligible intra-observation
variability except for SB31702 where it increases from a typical flux density
of $\sim 0.5$ mJy (ranging from 0.3–0.9 mJy) to $2.0\pm 0.3$ mJy in the final
30 minutes of the observation.

The source is located close to the known variable star V* FT Oct, but based on
the light curve morphology and the 6.1″offset between the radio and proper-
motion corrected optical positions, it is likely unrelated. However, the
proximity to such a bright optical/infra-red source means that we are unable
to place any constraints on this source using archival multi-wavelength data.

We can use the NE2001 model of galactic electron density (Cordes & Lazio,
2002) and the equations of Walker (1998) to determine the expected properties
of scintillation-induced variability for extragalactic compact sources. We
estimate a characteristic timescale of $\sim 17$ days and a characteristic
amplitude of $\sim 20\%$ along the line of sight to ASKAP J212525.4-813829 at
943 MHz, in good agreement with the observed radio light curve. We note that
while there is clear correlation in flux density between consecutive
observations, this is not unexpected if the variability is due to refractive
scintillation, since the observing cadence is much less than the scintillation
timescale. We therefore propose that this source is likely a scintillating
extragalactic source rather than an intrinsically variable source.

Figure 8: Radio light curve of UCAC 053-023945053 folded to the optical period
of 17.2 h. The horizontal errorbars denote the duration of the observation,
and non-detections are shown as $3\sigma$ upper limits. The marginal detection
in SB32036 is denoted by an open marker.

###  4.8 UCAC 053-023945053

UCAC 053-023945053 is a known cool dwarf (likely M4V; Stassun et al., 2019)
with a parallax of $14.44\pm 0.02$ mas (Gaia Collaboration et al., 2021). We
measure an optical period of $17.16\pm 0.20$ days after combining data from
TESS sectors 13 and 27.

UCAC 053-023945 was initially found by the VAST pipeline search and has
variability metrics of $\eta=3.77$ and $V=0.55$. The light curve (Fig. 1) is
characterised by four $\sim 0.3$ mJy detections, and a fifth marginal
detection with similar flux density. Each detection is consistent with a
polarisation fraction of $\sim 70\%$, although the detection of Stokes V
emission in SB31377 and SB31751 is marginal. The source is not detected in any
intra-observation image due to insufficient sensitivity, ruling out this
variability originating from short-timescale flares. Figure 8 shows the inter-
observation light curve folded to the optical period, and we note that the
detections occur in two groups separated by $140\deg$ of rotational phase.

Each of the eleven observations of this source covers a rotational phase that
overlaps with at least two other observations (i.e. there are 11 unique pairs
of overlapping observations). There are four intervals of rotational phase
covered by three observations. To assess the significance of the grouping of
the detections we assume that the detections are unrelated to the rotation of
the star, and hence would be distributed randomly in rotational phase. There
are ${11\choose 5}=462$ ways to distribute five detections between our eleven
observations. Of these, 104 (23%) have at least three detections that overlap
in phase space, 65 (14%) have all five detections overlapping with at least
one other detection, and 52 (11%) arranged into exactly one group of two
overlapping detections and one group of three overlapping detections. We
therefore conclude that the probability of a similar scenario occurring by
chance is greater than $11\%$. Hence, the observed clustering is not
statistically significant, but does warrant further investigation.

If the grouping of the detections is real, one possible explanation for the
observed behaviour is that the detections originate from two independent
active regions on the star – one which has persisted throughout the
observation period, and another that arose partway some time after 2021-09-01.
On the other hand, the comparable polarisation fraction of all five detections
perhaps suggests a single origin, independent of the star’s rotation. However,
we were unable to find a period that aligns all five detections and does not
also align them with constraining non-detections. Given the relatively low
significance of each detection, the observed variability could also be
explained by low level quiescent variability either associated with the
rotation of the star, or intrinsic to it. Ultimately, we are unable to
definitively determine the origin of the variability from these observations
alone.

##  5 Discussion and Summary

We have carried out a search for transient, variable and circularly polarised
radio sources using daily observations of two fields with ASKAP. We used a
three-pronged approach consisting of a standard variability search of the
default images produced by the telescope’s data reduction pipeline (see
Section 2.2), an examination of all sources detected in the Stokes V images
(see Section 2.3), and a “fast-imaging” approach which involved splitting each
observation into 15-minute sub-integrations (see Section 2.4).

We found eight sources of interest in total – all eight in the standard
variability search and five in each of the polarisation and fast-imaging
searches as shown in Table 2. Of these, six are intrinsically variable
emission from stellar systems, one is a pulsar exhibiting diffractive
scintillation and one is likely an extragalactic source exhibiting refractive
scintillation. Three of the stellar systems are known M-dwarfs, one is a
K-dwarf, one is an RS CVn while the spectral type of the sixth is unknown. Of
particular interest is the detection of circularly polarised bursts from three
of the stars (SCR J1845–6357, Gaia 6438561254116213632and CD–64 1208) lasting
minutes–hours. We have determined that the variable emission from SCR
J1845–6357 originates from the rotation of the star, but the mechanism by
which the other five stellar systems are variable remains unclear.

Our approach demonstrates the utility of using a variety of techniques when
searching for and classifying sources of interest in an untargeted widefield
search. For example, determining that the emission from SCR J1845–6357 was
periodic required the results of the fast-imaging search even though it was
initially detected by the standard variability search. Similarly, if our
observing cadence had been different UCAC 053-023945 may not have been found
in the standard variability search (e.g. all observations made detections with
similar flux densities) although it would have been detected by the
polarisation search.

These observations probe a new part of the gigahertz-frequency transient
parameter space – previous widefield searches have generally had an observing
cadence of months–days, while searches with a comparable cadence have lacked
areal coverage. Our combination of widefield coverage and high cadence makes
this survey sensitive to variability on timescales of days while also
producing a reasonably large event rate. Furthermore, the high cadence was
also vital for inferring source properties from the observed light curves. For
example, the daily cadence enabled us to measure the period of the pulses from
SCR J1845–6357 to a precision of less than one hour, and in turn allowed us to
conclusively link the observed variability to the rotation of the star.

While seven of the eight sources have been previously catalogued by surveys at
other wavelengths, this is the first time variable radio emission has been
detected from most of them. More importantly, only SCR J1845–6357 (producing
large X-ray flares) and V* CF Oct(producing radio flares) were known to be
particularly interesting prior to this search – the other five known objects
show no remarkable features that would motivate further dedicated study of
them. The widefield nature of these observations means that our search is not
biased by selection effects such as those encountered by targeted searches for
radio variability from known objects. This work, and other widefield searches,
therefore present a unique opportunity to study topics such as the link
between stellar radio variability and activity at other wavelengths.

ASKAP is uniquely placed to carry out searches for bright short-timescale
transients like those presented in this work as it is the only widefield
gigahertz-frequency interferometer currently operating. Similar searches can
be carried out with MeerKAT, but will be hindered by the comparably small
field of view. The relatively large number of variable sources we have
detected motivates a dedicated observing campaign independent of the planned
VAST survey (which will not achieve comparable sensitivity or cadence).
However, any such survey should target the Galactic plane to increase the
prospects of detecting emission from GCRTs, magnetars and pulsars. We note
that the planned DSA-2000 (Hallinan et al., 2019) will be well-placed to carry
out similar searches.

## Acknowledgements

Parts of this research were conducted by the Australian Research Council
Centre of Excellence for Gravitational Wave Discovery (OzGrav), project number
CE170100004. This work was partially supported by International Partnership
Program of Chinese Academy of Sciences (Grant No.113111KYSB20190020).

The Australian SKA Pathfinder is part of the Australia Telescope National
Facility (grid.421683.a) which is managed by CSIRO. Operation of ASKAP is
funded by the Australian Government with support from the National
Collaborative Research Infrastructure Strategy. ASKAP uses the resources of
the Pawsey Supercomputing Centre. Establishment of ASKAP, the Murchison Radio-
astronomy Observatory and the Pawsey Supercomputing Centre are initiatives of
the Australian Government, with support from the Government of Western
Australia and the Science and Industry Endowment Fund. We acknowledge the
Wajarri Yamatji people as the traditional owners of the Observatory site.

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 paper includes data collected by the TESS mission, which are publicly
available from the Mikulski Archive for Space Telescopes (MAST). Funding for
the TESS mission is provided by NASA’s Science Mission directorate.

This project used data obtained with the Dark Energy Camera (DECam), which was
constructed by the Dark Energy Survey (DES) collaboration. Funding for the DES
Projects has been provided by the US Department of Energy, the US National
Science Foundation, the Ministry of Science and Education of Spain, the
Science and Technology Facilities Council of the United Kingdom, the Higher
Education Funding Council for England, the National Center for Supercomputing
Applications at the University of Illinois at Urbana-Champaign, the Kavli
Institute for Cosmological Physics at the University of Chicago, Center for
Cosmology and Astro-Particle Physics at the Ohio State University, the
Mitchell Institute for Fundamental Physics and Astronomy at Texas A&M
University, Financiadora de Estudos e Projetos, Fundação Carlos Chagas Filho
de Amparo à Pesquisa do Estado do Rio de Janeiro, Conselho Nacional de
Desenvolvimento Científico e Tecnológico and the Ministério da Ciência,
Tecnologia e Inovação, the Deutsche Forschungsgemeinschaft and the
Collaborating Institutions in the Dark Energy Survey.

The Collaborating Institutions are Argonne National Laboratory, the University
of California at Santa Cruz, the University of Cambridge, Centro de
Investigaciones Enérgeticas, Medioambientales y Tecnológicas-Madrid, the
University of Chicago, University College London, the DES-Brazil Consortium,
the University of Edinburgh, the Eidgenössische Technische Hochschule (ETH)
Zürich, Fermi National Accelerator Laboratory, the University of Illinois at
Urbana-Champaign, the Institut de Ciències de l‘Espai (IEEC/CSIC), the
Institut de Física d‘Altes Energies, Lawrence Berkeley National Laboratory,
the Ludwig-Maximilians Universität München and the associated Excellence
Cluster Universe, the University of Michigan, NSF’s NOIRLab, the University of
Nottingham, the Ohio State University, the OzDES Membership Consortium, the
University of Pennsylvania, the University of Portsmouth, SLAC National
Accelerator Laboratory, Stanford University, the University of Sussex, and
Texas A&M University.

Based on observations at Cerro Tololo Inter-American Observatory, NSF’s
NOIRLab (NOIRLab Prop. ID 2020B-0253; PI: J. Cooke), which is managed by the
Association of Universities for Research in Astronomy (AURA) under a
cooperative agreement with the National Science Foundation.

This research has made use of the SIMBAD database, operated at CDS,
Strasbourg, France. This research has made use of NASA’s Astrophysics Data
System.

This research made use of Lightkurve, a Python package for Kepler and TESS
data analysis (Lightkurve Collaboration et al., 2018).

This research made use of matplotlib, a Python library for publication quality
graphics (Hunter, 2007), SciPy (Virtanen et al., 2020) and Astropy, a
community-developed core Python package for Astronomy (Astropy Collaboration
et al., 2013, 2018).

## Data Availability

The ASKAP data used in this work can be accessed through the CSIRO ASKAP
Science Data Archive
(CASDA777https://data.csiro.au/dap/public/casda/casdaSearch.zul) using the
SBIDs listed in Table 1. The DECam and HXMT data will be shared on reasonable
request to the corresponding author.

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##  Appendix A Measuring the period of SCR J1845–6357

To search for periodicity in the emission observed from SCR J1845–6357 we
followed the recommendations outlined by VanderPlas (2018). We used
astropy.timeseries.LombScargle to calculate the Lomb-Scargle periodogram of
the intra-observation light curve as well as the associated window transform
(Figure 9). We set samples_per_peak=10, but all other options were left
default.

Figure 9: Top: Window function of our observations of SCR J1845–6357. Bottom:
Lomb-Scargle periodogram of the intra-observation light curve of SCR
J1845–6357with the periods corresponding to prominent peaks labelled.

The window transform shows a large amount of structure, with significant peaks
at 24, 26, 30 and 34 hours. We also note the presence of a peak at 22.7 hours,
corresponding to the gap between the end of one day’s observations and the
beginning of the next. All peaks in the window function below 15 hours occur
at periods of $24/n$ for integer $n$ and are aliases of the 24 hours spike.
This level of structure is to be expected given our non-uniform observing
windows.

The periodogram power is maximum at a period of $14.2\pm 0.3$ h, but we also
find five other significant peaks at periods of $17.6\pm 0.3$, $10.5\pm 0.1$,
$9.1\pm 0.1$, $7.0\pm 0.1$ and $5.55\pm 0.04$ hours. The presence of multiple
peaks is qualitatively consistent with expectations given the highly
structuted window transform. We use the Baluev method (Baluev, 2008, ; as
implemented in astropy) to calculate the False Alarm Probability (FAP) of each
periodogram peak. We find that the 14.2 h peak has a FAP of $6.5\times
10^{-14}$, while the five other peaks have FAPs ranging from $10^{-10}$ to
$10^{-8}$. The Baluev method is known to be inaccurate for periodograms with
structured window functions, but generally overestimates the FAP and hence,
can be treated as an upper limit. We have also attempted to calculate the FAP
with a bootstrap method, but found no peaks exceeding the power of those in
the periodogram in $10^{5}$ samples, consistent with the upper limit obtained
from the Baluev method.

Figure 10: The complete intra-observation light curve of SCR J1845–6357 folded
to the six candidate periods. Only the 14.2 h light curve shows good alignment
between peaks with no constraining non-detections at the pulse phase.

There is no generalised method with which to compute the relative likelihood
of multiple peaks in the periodogram originating from a real, periodic signal
(VanderPlas, 2018). Instead, we manually inspect the intra-observation light
curves folded to the six candidate periods (Figure 10). Only the light curves
folded to 7.0 and 14.2 h show good alignment between the five detected pulses,
but the 7.0 h light curve also has multiple constraining non-detections at the
pulse phase.

We therefore conclude that the true period is $14.2\pm 0.3$ h with an
associated false alarm probability of less than $6.5\times 10^{-14}$. We also
note that while the best-fit period measured from the periodogram is $14.2$ h,
there is qualitatively better agreement between detected pulses after folding
to the known optical period of $14.1$ h as shown in Figure 3.