# Discovery of a young, highly scattered pulsar PSR J1032$-$5804 with the
Australian SKA Pathfinder

Ziteng Wang International Centre for Radio Astronomy Research, Curtin
University, Bentley, WA 6102, Australia  David L. Kaplan Center for
Gravitation, Cosmology, and Astrophysics, Department of Physics, University of
Wisconsin-Milwaukee, P.O. Box 413, Milwaukee, WI 53201, USA  Rahul Sengar
Center for Gravitation, Cosmology, and Astrophysics, Department of Physics,
University of Wisconsin-Milwaukee, P.O. Box 413, Milwaukee, WI 53201, USA
Emil Lenc ATNF, CSIRO Space and Astronomy, PO Box 76, Epping, New South Wales
1710, Australia  Andrew Zic ATNF, CSIRO Space and Astronomy, PO Box 76,
Epping, New South Wales 1710, Australia  Akash Anumarlapudi Center for
Gravitation, Cosmology, and Astrophysics, Department of Physics, University of
Wisconsin-Milwaukee, P.O. Box 413, Milwaukee, WI 53201, USA  B. M. Gaensler
Dunlap Institute for Astronomy and Astrophysics, University of Toronto, 50 St.
George St., Toronto, ON M5S 3H4, Canada  David A. Dunlap Department of
Astronomy and Astrophysics, University of Toronto, 50 St. George St., Toronto,
ON M5S 3H4, Canada  Division of Physical and Biological Sciences, University
of California Santa Cruz, 1156 High Street, Santa Cruz, CA 95064, USA  Natasha
Hurley-Walker International Centre for Radio Astronomy Research, Curtin
University, Bentley, WA 6102, Australia  Tara Murphy Sydney Institute for
Astronomy, School of Physics, University of Sydney, Sydney, New South Wales
2006, Australia.  ARC Centre of Excellence for Gravitational Wave Discovery
(OzGrav), Hawthorn, Victoria, Australia  Yuanming Wang Centre for Astrophysics
and Supercomputing, Swinburne University of Technology, Hawthorn, VIC 3122,
Australia  ARC Centre of Excellence for Gravitational Wave Discovery (OzGrav),
Hawthorn, Victoria, Australia

(Received XXX; Revised YYY; Accepted ZZZ)

###### Abstract

We report the discovery of a young, highly scattered pulsar in a search for
highly circularly polarized radio sources as part of the Australian Square
Kilometre Array Pathfinder (ASKAP) Variables and Slow Transients (VAST)
survey. In follow-up observations with Murriyang/Parkes, we identified PSR
J1032$-$5804 and measured a period of 78.7 ms, dispersion measure (DM) of
$819\pm 4$ pc cm-3, rotation measure of $-2000\pm 1\,$rad m-2, and a
characteristic age of 34.6 kyr. We found a pulse scattering timescale at 3 GHz
of $\sim$22 ms, implying a timescale at 1 GHz of $\sim$3845 ms, which is the
third most scattered pulsar known and explains its non-detection in previous
pulsar surveys. We discuss the identification of a possible pulsar wind nebula
and supernova remnant in the pulsar’s local environment by analyzing the
pulsar spectral energy distribution and the surrounding extended emission from
multiwavelength images. Our result highlights the possibility of identifying
extremely scattered pulsars from radio continuum images. Ongoing and future
large-scale radio continuum surveys will offer us an unprecedented opportunity
to find more extreme pulsars (e.g., highly scattered, highly intermittent,
highly accelerated), which will enhance our understanding of the
characteristics of pulsars and the interstellar medium.

Neutron stars (1108) — Galactic radio sources (571) — Radio pulsars (1353) —
Interstellar scattering (854)

††journal: ApJ††facilities: ASKAP, IRSA, Parkes, Swift(XRT), WISE
(https://www.ipac.caltech.edu/doi/irsa/10.26131/IRSA153), ATCA,
VST.††software: APTB (Taylor et al., 2023), astropy (Astropy Collaboration et
al., 2013, 2018), PINT (Luo et al., 2021), PSRCHIVE (Hotan et al., 2004),
PsrPopPy (Bates et al., 2014), , Pulsar Survey Scraper (Kaplan, 2022), PyGEDM
(Price et al., 2021), reproject (Robitaille et al., 2020), swarp (Bertin et
al., 2002).

##  1 Introduction

When radio pulses from pulsars traverse the turbulent interstellar medium,
multi-path propagation leads to temporal and spatial scattering, which in turn
smears out the pulse profile. Despite extensive pulsar searching surveys
spanning decades (e.g., Lyne et al., 1998; Manchester et al., 2001; Lorimer &
Kramer, 2004; Keith et al., 2010; Stovall et al., 2014; Keane et al., 2018),
some highly scattered pulsars remain challenging to detect with traditional
time-domain techniques. These pulsars are especially hard to detect at
frequencies $\lesssim 1\,$GHz where the majority of pulsar surveys take place.
The periodic signal is difficult (or impossible) to detect when the observed
pulse profile width is comparable to the pulsar spin period. For a Kolmogorov
distribution of interstellar medium inhomogeneities, the scattering timescale
$\tau$ scales with frequency $\nu$ as $\tau\propto\nu^{-4.4}$ (e.g., Romani et
al., 1986). Most of the pulsar searching surveys are not sensitive to highly
scattered pulsars as they are performed at a relatively low frequency, such as
the High Time Resolution Universe Pulsar Survey (Keith et al., 2010) at
$\sim$1.4 GHz, the Green Bank Northern Celestial Cap Pulsar Survey (Stovall et
al., 2014) at 350 MHz, and the MPIfR-MeerKAT Galactic Plane survey (MMGPS;
Padmanabh et al., 2023) currently at $\sim 1.4\,$GHz (from 856 MHz to 1712
MHz).

As a concrete example, the most scattered pulsar found to date, PSR
J1813$-$1749 (catalog PSR J1813-1749), was first identified as a pulsar
candidate as a TeV source (Aharonian et al., 2005, 2006), an X-ray source
(Brogan et al., 2005; Ubertini et al., 2005), and a supernova remnant
association (Brogan et al., 2005). Gotthelf & Halpern (2009) measured the
pulse period $P=44.7\,$ms in X-rays, while no radio pulsations were detected
with the Green Bank Telescope (GBT) at 1.4 GHz and 2 GHz (Halpern et al.,
2012) or the Effelsberg Telescope at 1.4 GHz (Dzib et al., 2018), though radio
interferometric observations did detect a variable point source at the pulsar
position (Dzib et al., 2010, 2018). Radio pulsations were finally detected
with the GBT at frequencies of 4.4–10.2 GHz (Camilo et al., 2021). The pulsar
was detected with a high scattering timescale $\tau\approx 0.25\,$s at 2 GHz,
which explains the non-detection in the previous pulsar searches.

The special properties of pulsars can help in identifying pulsar candidates in
radio continuum images (e.g., Sett et al., 2023). Pulsars typically have
steeper spectra than most other radio source types, with spectral indices
$\alpha<-1$, where $S_{\nu}\approx\nu^{\alpha}$ (e.g., Bates et al., 2013;
Posselt et al., 2023). Selecting steep-spectrum radio sources has long been
used to find new pulsar candidates, and has successfully identified new
pulsars including the first detected millisecond pulsar (Backer et al., 1982).

Pulsars are also one of a few astronomical sources measured to be strongly
polarized (e.g., Lorimer & Kramer, 2004; Johnston & Kerr, 2018), and in
particular circularly polarized. This means searches in circular polarisation
are another method that can be used to find them in the image domain (e.g.,
Gaensler et al., 1998). For example, Lenc et al. (2018) conducted an all-sky
circular polarization survey at 200 MHz with the Murchison Widefield Array
(MWA; Bowman et al., 2013) and identified 33 known pulsars. Pritchard et al.
(2021) performed a circular polarization survey with the Australian Square
Kilometre Array Pathfinder (ASKAP; Johnston et al., 2008; Hotan et al., 2021)
on the Rapid ASKAP Continuum Survey (RACS; McConnell et al., 2020) data and
identified 37 known pulsars. In a similar search, Kaplan et al. (2019)
serendipitously discovered a new millisecond pulsar, PSR J1431–6328, by
identifying circularly polarized sources with the ASKAP data. Recently, Sobey
et al. (2022) discovered two new pulsars, PSR J1049+5822 and PSR J1602+3901,
with the Low-Frequency Array (LOFAR) Two-metre Sky Survey (LoTSS) as part of
the Targeted search using LoTSS images for polarized pulsars (TULIPP) survey.

Finally, pulsars can show flux density variability due to, for example, pulse
nulling (e.g., Backer, 1970), pulse intermittency (e.g., Kramer et al., 2006),
interstellar scintillation (e.g., Rickett, 1970), and/or eclipsing by the
companion (e.g., Broderick et al., 2016). Finding highly variable sources is
another way to select pulsar candidates, but additional criteria (e.g., radio
spectrum, polarization, multi-wavelength counterparts association) are often
applied to make the sample size manageable. For example, Wang et al. (2022)
identified 27 highly variable point sources towards the Magellanic Clouds with
ASKAP, including a new pulsar. The new pulsar was the only source that was
circularly polarized but which did not have a multi-wavelength counterpart.
Dai et al. (2016) discussed the prospect of identifying pulsars in variance
images. These image domain techniques can help us discover pulsars located in
previously poorly explored parameter spaces, such as pulsars with high
dispersion measure (DM), extreme nulling behaviors, and/or highly scattered
pulses.

In this paper, we present the discovery of a young, highly scattered pulsar
with the circular polarization search technique based on the data from two
ASKAP projects: the Variable and Slow Transients (VAST; Murphy et al., 2013,
2021) survey and the Evolutionary Map of the Universe (EMU; Norris et al.,
2011, 2021) survey. We confirmed the nature of the source in a dedicated
search with the Parkes radio telescope, Murriyang. In Section 2, we summarise
the discovery observations for the new pulsar. Analysis of archival
observations and follow-up observations are discussed in Section 3. In Section
4, we discuss the properties and the local environment of the pulsar. We also
discuss the prospects for identifying new pulsars, especially highly scattered
ones, through image domain techniques. Conclusions of this work are presented
in Section 5

##  2 Source Discovery

###  2.1 ASKAP Discovery

As part of the VAST survey, we have been conducting ASKAP observations of the
southern Galactic plane. VAST observed 41 Galactic fields covering
$|b|<6\arcdeg$ and $\delta<-10\arcdeg$ totaling $1260\,{\rm deg}^{2}$,
repeating each field, on average, every two weeks 111ASKAP uses dynamic
scheduling so we cannot give an exact cadence since 2022 November. Each
observation had $\sim$12 mins integration at a central frequency of 888 MHz
with a bandwidth of 288 MHz, achieving a typical sensitivity of 0.4 mJy beam-1
for the fields covering the Galactic plane. All four instrumental polarization
products (XX, XY, YX, and YY) were recorded to allow images to be made in four
Stokes parameters (I, Q, U, and V). The data were processed offline using the
ASKAPSoft pipeline (Cornwell et al., 2011), from which we can get Stokes I/V
images and catalogs. PKS B1934–638 (catalog PKS B1934-638) was used for the
flux scale and bandpass calibration, and self-calibration was applied to
correct for phase variations during the observation. A detailed description of
data reduction is given by Murphy et al. (2021).

We conducted a search for highly circularly polarized sources in the VAST
Galactic plane observations to identify interesting sources (also see
Pritchard et al., 2021; Rose et al., 2023, for the results of other circular
polarization searches with ASKAP data). Most of the detected sources were
matched to known pulsars or stellar objects. We selected VAST J103250.4–580434
for further investigation because no clear multi-wavelength association was
found. VAST J103250.4–580434 was first detected in a VAST observation on 2022
November 19 (Schedule Block 45739) with a Stokes I peak flux density of
$4.16\pm 0.52$ mJy beam-1, and a fractional circular polarization of $-28.5\pm
5.0\%$: a higher magnitude than average for pulsars, but consistent with the
population (Anumarlapudi et al., 2023). The broader search results will be
presented in future work.

###  2.2 Murriyang Discovery

Motivated by the detection of circular polarization and lack of
multiwavelength association, we conducted a follow-up observation of VAST
J103250.4–580434 with the 64-m Parkes telescope, Murriyang, on 2023 February
24 (project code PX103) with the Ultra-Wideband Low (UWL) receiver (Hobbs et
al., 2020), which provides a wide frequency coverage spanning 704 to 4032 MHz
and has been pivotal in confirming pulsar candidates that are scarcely
detectable below 1.4 GHz (Sengar et al., 2023). The data were recorded in
1-bit pulsar searching mode (total intensity) with the MEDUSA backend. The
observation was 2500 seconds with a 32 $\mu$s time resolution and 62.5 kHz
frequency resolution (2048 channels per 128 MHz subband).

The periodic search was carried out with pulsar_miner
222https://github.com/alex88ridolfi/PULSAR_MINER(Ridolfi et al., 2021), an
automated pulsar searching pipeline based on
presto333https://github.com/scottransom/presto (Ransom, 2001). To run the
search more efficiently, we divided the data into two segments (1250 s each)
and only selected two groups of subbands (bottom band group from 832 to 1216
MHz considering the steep spectral indices for the normal pulsar population,
and high band group from 2624 to 3008 MHz considering the potential high
scattering and/or dispersion). The dispersion measure (DM) range that we
searched was 2–1500 pc cm-3 with harmonic summing of 8 and no acceleration
search applied. We only folded the candidates with a signal to noise ratio
threshold of 8. We identified a strong pulsar candidate, now called PSR
J1032$-$5804, with a period of 78.72 ms and a DM of 867.8 pc cm-3 in the high
band group data. There is no previously published pulsar at this position in
the ATNF pulsar catalog (Manchester et al., 2005), nor is there any
unpublished discovery in the Pulsar Survey Scraper444https://pulsar.cgca-
hub.org (Kaplan, 2022).

PSR J1032$-$5804 was measured to have a wide pulse profile, with a duty cycle
$\sim$30% at $\sim$2.8 GHz (using the pulse width at 50% maximum). After the
initial discovery, we also folded the data at frequencies ranging from 1216 to
1600 MHz (centered at 1408 MHz) and from 3648 to 4032 MHz (centered at 3840
MHz) respectively. We saw a clear periodic signal (25.5$\sigma$) from the data
centered at $\sim$3.8 GHz, but no signal from the data centered at $\sim$1.4
GHz.

##  3 Follow-up Observations and Source Properties

###  3.1 Timing and Polarization

All timing observations were conducted at the Murriyang radio telescope using
the UWL receiver and MEDUSA backend. Each observation was recorded in both
fold and search mode with full Stokes parameters along with a noise diode
observation. All data were coherently de-dispersed at the best DM value we
could measure at the time of the observation ($821\,$pc cm-3). The time
resolution for each observation was 128 $\mu\rm s$, with a bandwidth of 0.5
MHz per channel. Prior to the timing analysis, observations were first cleaned
using clfd555https://github.com/v-morello/clfd. We also excised each
observation affected by narrowband and impulsive radio-frequency interference
(RFI) using pazi of the PSRCHIVE package. Using the highest SNR observation we
created a standard profile using pas from the PSRCHIVE package (Hotan et al.,
2004). Note that the pulsar is not visible below 2.5 GHz, therefore the UWL
frequency band from 704–2500 MHz was removed from the analysis. All
observations of the pulsar taken on 11 epochs were frequency scrunched to one
sub-band and polarization scrunched to total intensity for timing
(polarization analysis was performed separately). We divided the data into 1
to 4 sub-integrations depending on their signal to noise ratio. To generate
the TOAs we used pat from PSRCHIVE, and employed the Fourier domain with
Markov Chain Monte Carlo (FDM) algorithm. In total 26 TOAs were obtained over
11 epochs, and each TOA had signal to noise ratio greater than 15.

We fit the TOAs derived from the Parkes/Murriyang data in PINT (Luo et al.,
2021), using only frequencies above 2.5 GHz. We were able to obtain a good
timing solution connecting back to our discovery observation, as shown in
Figure 1 and given in Table 1, without rejecting any TOAs from the solution.
We initially fit only for the rotation frequency $f$, but then added the
frequency derivative $\dot{f}$ once it was warranted by the residuals; the
position was held fixed at the position from ATCA imaging. We verified that
this solution was robust and unique using Algorithmic Pulsar Timing for
Binaries (APTB; Taylor et al., 2023), which identified the same solution as we
did by hand as the only solution. This solution has a reduced $\chi^{2}$ of
1.97, suggesting that the uncertainties may be slightly underestimated or that
there is some timing noise present. Regardless, we leave the uncertainties in
Table 1 as the unscaled values reported by PINT but note that they too may be
slightly underestimated. There is also a contribution to the uncertainties on
$f$ and $\dot{f}$ from our uncertainties in the ATCA imaging position, which
is not taken into account by PINT. Using Appendix A of Hartman et al. (2008),
we find uncertainties of $6\times 10^{-10}\,$Hz and $1.3\times 10^{-16}\,{\rm
Hz\,s}^{-1}$ on $f$ and $\dot{f}$ from the position uncertainties, comparable
to those from the timing analysis. In the future, once the data span exceeds 1
yr, we will be able to fit for a more precise timing position and reduce those
uncertainties further.

We find that the pulsar is young, with a characteristic age of only 34.6 kyr.
Given the modest timespan of the current data, we cannot determine useful
constraints on any higher timing derivatives. Allowing a fit for the second
frequency derivative $\ddot{f}$ finds $\ddot{f}=-(1.2\pm 0.9)\times
10^{-22}\,{\rm Hz\,s}^{-2}$, consistent with 0, and implying a 3$\sigma$ upper
limit on the braking index of $n\equiv f\ddot{f}/\dot{f}^{2}<102$. The
distance to the pulsar is highly uncertain, with values from 4.3 kpc (YMW16
model, Yao et al., 2017) to $>50\,$kpc (NE2001 model, Cordes & Lazio, 2002)
depending on the Galactic electron density model.

Figure 1: Timing residuals for PSR J1032$-$5804 from Parkes/Murriyang data. We
plot the phase residuals (left y-axis) or time residuals (right y-axis)
against the observation date (MJD). Table 1: Measured and derived parameters
for PSR J1032$-$5804.

Parameter | Value
---|---
Right Ascension (J2000)aaDerived from ATCA imaging. | $10^{\rm h}32^{\rm m}50\fs 54(1)$
Declination (J2000)aaDerived from ATCA imaging. | $-58{\arcdeg}04\arcmin 34.9(2)\arcsec$
Start (MJD) | 59999.6
End (MJD) | 60219.1
Frequency (Hz) | 12.6998621581(4)
Frequency Derivative (Hz s-1) | $-5.81654(10)\times 10^{-12}$
Epoch of Period (MJD) | 60100
$\chi^{2}$/DOF | 45.5/23
RMS residual ($\mu$s) | 504.7
Dispersion Measure (pc cm-3) | 819$\pm$4
Rotation Measure (rad m-2) |  $-2000$ $\pm$ 1
Galactic Longitude (deg) | 285.436
Galactic Latitude (deg) | +0.008
Period (s) | 0.078741012111(2)
Period Derivative (s s-1) | $3.60634(6)\times 10^{-14}$
Characteristic Age (kyr) | 34.6
Surface Magnetic Field (G) | $1.7\times 10^{12}$
Spin-down Luminosity (erg s-1) | $2.9\times 10^{36}$
Distance (kpc) | 4.3bbFrom the Yao et al. (2017) electron density model.
|  $>50$ccFrom the Cordes & Lazio (2002) electron density model.

Note. — Quantities in parentheses are 1$\sigma$ uncertainties on the last
digit, without any additional scaling. The JPL DE405 solar system ephemeris
has been used and times refer to TDB (using TT = TAI+32.184 s).

Once we had a timing solution, we co-added all of the available
Parkes/Murriyang data into a single high-S/N dataset. We then fit for an
exponential scattering model (e.g., Lorimer & Kramer, 2012). We assumed that
the underlying profile model was a Gaussian, and that scattering convolved
this with a frequency-dependent exponential. Dividing up the data above
$2.5\,$GHz into 4 sub-bands, we obtained the fits in Figure 2. The scattering
timescale for each sub-band was fit independently: when we fit for a power-law
frequency dependence we obtain a spectral index $\alpha_{s}=-4.7\pm 0.7$ (with
$\tau(\nu)\propto\nu^{\alpha_{s}}$), consistent with expectations from
Kolmogorov turbulence (Cordes et al., 1986; Romani et al., 1986; Cordes &
Rickett, 1998; Bhat et al., 2004), and a scattering timescale at 3 GHz of
$22\pm 2$ ms. The implied scattering timescale at 1 GHz was 3845 ms
($>40\times$ the pulse period), a factor of 3 greater than that predicted by
Bhat et al. (2004) based on the DM, a factor of 27 greater than that predicted
by Lewandowski et al. (2015a), and a factor of 28 greater than that predicted
by Yao et al. (2017)666The model of Cordes & Lazio (2002) is not sensible
along this line-of-sight for DM $>$ 620 pc cm-3.. However, the scattering
timescale of PSR J1032$-$5804 is still largely consistent with the whole
pulsar population (see Figure 3) considering the large internal uncertainties
of these models.

Figure 2: Normalized pulse profiles created from the summed Parkes UWL data of
PSR J1032$-$5804 as a function of observing frequency. We show profiles (gray)
at 3.8, 3.5, 3.1 and 2.7 GHz vertically offset from top to bottom, along with
the best-fit exponential scattering model fits (red). The timescales for the
scattering fits are given. A power-law fit to the frequency dependence of
$\tau$ gives $\alpha_{s}=-4.7\pm 0.7$ (with
$\tau(\nu)\propto\nu^{\alpha_{s}}$) and a scattering timescale at 3 GHz of
$22\pm 2$ ms.  Figure 3: Scattering timescale as a function of the dispersion
measure for PSR J1032$-$5804 (red star) and pulsars (gray dots) in the ATNF
pulsar catalog (v. 1.70, Manchester et al., 2005). The dashed line corresponds
to the scattering timescale and DM relation fitted by Bhat et al. (2004) while
the dotted line corresponds to the one fitted by Lewandowski et al. (2015a).

Using the full Stokes fold mode (coherently dedispered) UWL observations we
also conducted flux and polarization calibration. For polarization
calibration, we used a short $\sim$2-min observation of a linearly polarized
noise diode, which was obtained at the start of each observing session. We
used the radio Galaxy PKS B0407–658 as a flux density reference, which is a
more reliable calibration source for the UWL. Prior to performing any analysis
all observations were manually cleaned from RFI. For both polarimetric and
flux calibration of pulsar observations, we used PSRCHIVE’s pac pulsar archive
calibration program which was first used to generate a calibrator database.
This database file was then used to obtain a flux and polarization calibrated
file. This methodology of flux and polarization calibration is similar to the
one outlined in Lower et al. (2020) and references therein.

Figure 4: Dispersion measure (DM) vs. rotation measure (RM) for sources in the
ATNF pulsar catalog (v. 1.70, Manchester et al., 2005). Sources with positive
RM are filled, and those with negative RM are empty. Individual sources with
$|{\rm RM}|>2000\,{\rm rad\,m}^{-2}$ are labeled, and PSR J1032$-$5804 is the
red star. We also plot a line indicating $|{\rm RM}|/{\rm DM}=2.44\,{\rm
rad}\,{\rm cm}^{3}\,{\rm pc}^{-1}\,{\rm m}^{-2}$, corresponding to an average
interstellar magnetic field along the line-of-sight of $3\,\mu$G.

We then used the rmfit tool of PSRCHIVE to fit for the rotation measure (RM)
in one of the highest signal-to-noise ratio observations. We find a strong
detection777We used an RM search range between $-3000$ to 3000 rad m-2 to
obtain the best rmfit value. with ${\rm RM}=-2000\pm 1\,{\rm rad\,m}^{-2}$.
Though the RM measurement of PSR J1032$-$5804 is almost three times the most
extreme $|{\rm RM}|$ of known pulsars within 5 degrees of PSR J1032$-$5804,
the average interstellar magnetic field along the line-of-sight $B=1.232\,{\rm
RM}/{\rm DM}\approx-3\,\mu$G is consistent with the Galactic magnetic field
model fitted by Han et al. (2018), and also with the Galactic pulsar
distribution (see Figure 4). Based on the pulse profiles (see Figure 5), we
find a circular polarization fraction of 10% at a frequency of 3 GHz, which is
not consistent with the value of $\sim$25% found from ASKAP imaging at 843
MHz. We also check the polarization evolution at three UWL frequencies (2.7,
3.2, 3 8 GHz) and find that the circular polarization fraction remains similar
across these three UWL bands. However, we caution that the very broad pulse
profile makes establishing a reliable pulse baseline – and therefore the
total-intensity pulsed flux density – difficult. We also find that there is
very little position-angle change across the pulse, likely due to the long
scattering timescale even at these frequencies (e.g., Li & Han, 2003; Noutsos
et al., 2015).

Figure 5: Dynamic spectra and polarization profiles of PSR J1032$-$5804 from a
52 min observation using the Parkes UWL receiver on 2023 May 02. The bottom
panel shows the dynamic spectrum over the frequency range of 2.5–4 GHz in
which pulsar is visible. The horizontal stripes correspond to the parts of the
band that have been removed due to the presence of RFI. The middle panel shows
the frequency-averaged profiles of the total intensity (in black), linear
polarization (in red), and circular polarization (in blue). The top panel
shows the polarization position angle (P.A) at a central frequency of 3.25
GHz.

Apart from examining the highest S/N observation, we also examined other
observations taken at different epochs and found discrepancies in the RM
values of up to 50 rad m-2 between them. These variations might resemble the
changes in the magneto-ionic conditions observed in pulsars within the
Galactic Center (albeit on a smaller scale; Desvignes et al., 2018; Abbate et
al., 2023) or elsewhere (Johnston et al., 2021). They could also be due to
instrumental effects. Furthermore, different levels of RFI excision and
changing SNRs coupled with the highly scattered pulse profiles can potentially
cause these discrepancies. Our ongoing investigation aims to ascertain whether
these fluctuations stem from instrumental factors, determine the time frame of
these variations, and establish any potential correlations with changes in DM.
This comprehensive analysis is the subject of future work.

###  3.2 Radio Continuum

Figure 6: Total intensity (Stokes I) flux densities of PSR J1032$-$5804 from
the VAST survey (top), along with circular polarization fractions (bottom).
Both are consistent with constant values (dashed lines). We find a mean Stokes
I flux density of $3.82\pm 0.13$ mJy, and a mean circular polarization
fraction of $-0.24\pm 0.02$.

We looked at all available epochs of ASKAP data from VAST (22 observations so
far) to probe the flux variability of PSR J1032$-$5804 (see Figure 6). We used
forced flux measurements888We performed the fitting at the source position
with the synthesized beam of that epoch. to deal with non-detections. Both the
flux density and circular polarization fraction are consistent with no
variability, with $\chi^{2}$ of $14.7$ for the flux density and $10.8$ for the
polarization fraction, both for 21 degrees-of-freedom.

We also checked other ASKAP surveys from the CSIRO ASKAP Science Data Archive
(CASDA). PSR J1032$-$5804 was detected in the RACS-mid survey (Duchesne et
al., 2023) with a peak flux density of $2.84\pm 0.38\,$mJy beam-1 at 1367.5
MHz. It was also detected in the Evolutionary Map of the Universe (EMU; Norris
et al. 2011, 2021) project with a peak flux density of $5.16\pm 0.36\,$mJy
beam-1 and $4.96\pm 0.37\,$mJy beam-1 in the EMU fields 1017$-$60 (Schedule
Block 46953) and 1029$-$55 (Schedule Block 46915) at 943.5 MHz,
respectively999The EMU observations are typically $\sim$10 hrs, and the high
flux uncertainties are mainly from the extended emission nearby..

We also checked the GaLactic and Extragalactic All-sky Murchison Widefield
Array (GLEAM; Wayth et al., 2015; Hurley-Walker et al., 2017) survey data.
There were no detections of the pulsar in any GLEAM bands, with a 3$\sigma$
upper limit of 1.62 Jy beam-1, 0.78 Jy beam-1, 0.28 Jy beam-1, and 0.14 Jy
beam-1 at 88 MHz, 118 MHz, 154 MHz, and 200 MHz, respectively. The elliptical
structure in the ASKAP images is visible, albeit at low resolution and
significance.

Unlike most pulsars whose radio spectra can be modeled by a simple power law
(e.g., Bates et al., 2013), the spectrum of PSR J1032$-$5804 may peak at
$\sim$1 GHz and decline at higher and lower frequencies. To obtain the
spectral energy distribution over a wide frequency range, we observed PSR
J1032$-$5804 with the Australian Telescope Compact Array (ATCA) on 2023 Aug 21
(project code C3363) with 6D configuration in L (1–3 GHz) and C/X (5–7 GHz and
8–10 GHz) bands for three hours each. The observations were calibrated using
PKS B1934–638 (catalog PKS B1934-638) for the flux density scale and the
instrumental bandpass. PMN J1047–6217 (catalog PMN J1047-6217) was used for
phase calibration. We used Casa to perform both the data calibration and the
continuum imaging. We split each band into two parts to image the data. We
detected a compact radio source at the pulsar position in all six subbands
(see Table 2). The best-fit position of PSR J1032$-$5804 from the ATCA
observation (based on the X-band data) is RA $10^{\rm h}32^{\rm m}50\fs 54\pm
0\fs 01$, Dec $-58{\arcdeg}04\arcmin 34\farcs 9\pm 0\farcs 2$, which is within
the ASKAP $1\sigma$ positional error circle.

Table 2: ATCA flux density measurement for PSR J1032$-$5804\. Non-detections are denoted by 3$\sigma$ upper limits based on the local noise.  Frequency Range | $S_{\rm StokesI}$ | $S_{\rm StokesV}$
---|---|---
(MHz) | (mJy/beam) | (mJy/beam)
1076–2100 | $2.09\pm 0.64$ | $-0.56\pm 0.07$
2100–3124 | $1.76\pm 0.20$ | $-0.19\pm 0.06$
4476–5500 | $0.73\pm 0.04$ | $<0.14$
5500–6524 | $0.56\pm 0.05$ | $<0.13$
7976–9000 | $0.22\pm 0.03$ | $<0.10$
9000–10024 | $0.19\pm 0.03$ | $<0.12$

###  3.3 Swift X-ray Observations

Motivated by the fact that PSR J1032$-$5804 seems to be young and energetic,
we looked for available X-ray data but there were no observations with Chandra
or XMM-Newton that covered this location. There was one short observation with
the Neil Gehrels Swift Observatory (Gehrels et al., 2004), but the duration
was only 400 s. Therefore we requested a longer Director’s Discretionary Time
observation. We observed PSR J1032$-$5804 using the Swift X-ray Telescope
(XRT; Burrows et al. 2005) for a total of 2242 s in two exposures on 2023 May
22 and 2023 May 26. We retrieved the merged data-set created with the online
analysis tools101010https://www.swift.ac.uk/user_objects/.. We find 0 events
within $15\arcsec$ of PSR J1032$-$5804, and derive a 95% upper limit on the
count-rate of $5\times 10^{-4}\,{\rm s}^{-1}$.

To interpret the X-ray upper limit, we first convert the DM into a hydrogen
column density using the relationship of He et al. (2013), and find $N_{\rm
H}\approx 2.5\times 10^{22}\,{\rm cm}^{-2}$. We assume a power-law X-ray
spectrum with index $\Gamma=1.5$, typical of young pulsars like PSR
J1032$-$5804 (Helfand et al., 2007; Kargaltsev & Pavlov, 2008; Kargaltsev et
al., 2012, although Gotthelf 2003 would predict a flatter spectrum for this
$\dot{E}$). This then gives an upper limit to the unabsorbed flux (0.5–8 keV)
of $5.5\times 10^{-14}\,{\rm erg\,cm}^{-2}\,{\rm s}^{-1}$, or an upper limit
to the luminosity of $1.6\times 10^{32}d_{5}^{2}\,{\rm erg\,s}^{-1}$, where
the distance is $5d_{5}\,$kpc. We can compare this with the spin-down
luminosity and find $L_{X}/\dot{E}<5\times 10^{-5}d_{5}^{2}$. This is lower
than many young pulsars but not inconsistent with the tail of the population
(Kargaltsev & Pavlov, 2008; Kargaltsev et al., 2012). A deeper X-ray
observation may be able to more robustly constrain any X-ray emission,
although the highly-uncertain distance will make any constraints somewhat
weak.

##  4 Discussion

PSR J1032$-$5804 was detected as a point source in all ASKAP and ATCA
observations. Despite the large scattering timescale, the angular broadening
effect is small compared to the synthesized beam of all images. For a source
at a distance $d$ scattered by a single thin screen at a distance $s$, the
expected full width at half maximum of angular broadening follows

$\theta=\sqrt{\frac{8\ln 2c\left(d-s\right)\tau}{ds}}$

where $\tau$ is the scattering timescale and $c$ is the speed of light (Cordes
& Lazio, 1997). Assuming $d=4.3\,$kpc, and $s=d/2$, the expected angular
broadening is $\theta\approx 2\farcs 1\left(\nu/1\,{\rm GHz}\right)^{-2.2}$.
All synthesized beam sizes are much larger than the expected value at
corresponding frequencies (e.g., $\theta_{2.1\,{\rm GHz}}\approx 0\farcs 4$,
while the ATCA synthesized beam at 2.1 GHz is $\sim 5\arcsec$). The large
scattering timescale also leads to low-level time variability in the image
domain. Assuming a Kolmogorov spectrum (e.g., Rickett, 1977), we calculated a
diffractive scintillation bandwidth of $\Delta f_{\rm DISS}\ll 1\,$kHz and a
scintillation timescale of $\ll 10\,$s at 888 MHz. Both the scintillation
bandwidth and the timescale are much smaller than those for typical VAST
observations (288 MHz and 12 mins), which could explain the non-variability of
the source in the VAST survey.

Figure 7: Field of PSR J1032$-$5804, observed with ASKAP at 943 MHz (from EMU,
Norris et al. 2011; left), WISE (from the ALLWISE data release; Cutri et al.
2013) 12 $\mu$m (middle left), and H$\alpha$ from the VST Photometric
H$\alpha$ Survey (VPHAS; Drew et al. 2014) (middle right). All images are
roughly $0.8\arcdeg$ on a side with north up. The position of PSR J1032$-$5804
is shown by the red plus. The Galactic plane is indicated with the black
dotted line. On the ASKAP image, we show the outline of a potential SNR shell
(cyan dashed ellipse) and a more compact pulsar wind nebulae (magenta circle).
On the WISE image we also show contours from the ASKAP image (red). We also
showed a composite of radio (EMU, red), infrared (WISE, blue), and H$\alpha$
(VPHAS, green) emission (right), where the position of PSR J1032$-$5804 is
shown by the cyan circle.

Motivated by the youth of PSR J1032$-$5804, we searched for an associated
supernova remnant (SNR). There are no cataloged SNRs coincident with the
pulsar, with the closest $>1.5\arcdeg$ away (Green, 2019, 2022 December
version). We therefore examined deeper radio images from the EMU
project111111The ATCA images from Section 3.2 were not useful in searching for
extended emission because of limited $uv$ coverage.. The 10-hour EMU
observation reaches a sensitivity of 28 $\mu$Jy beam-1 with a resolution of
15′′. We retrieved EMU field 1017$-$60 from CASDA. Figure 7 shows a cutout of
the region around PSR J1032$-$5804\. There is a considerable amount of
extended emission around the position of PSR J1032$-$5804 in the EMU image,
with a potential SNR shell outlined in cyan and a more compact emission region
(potentially a pulsar wind nebula or PWN) outlined in blue. However, we
caution that there is a lot of other extended emission in this region and it
is not confined to only the area around PSR J1032$-$5804, suggesting that
there could be contributions from Galactic H II regions or unrelated
synchrotron emission. Unfortunately, difficulties in robustly deconvolving the
complex extended emission in this region prevent us from establishing a
reliable in-band spectral index that might help discriminate between these
sources of emission. Nor can we identify a radio image at another wavelength
to do the same. Instead we examined the 12 $\mu$m image from ALLWISE (Cutri et
al., 2013). We also assembled an H$\alpha$ mosaic from 6 individual exposures
from the VST Photometric H$\alpha$ Survey (VPHAS; Drew et al. 2014), which we
mosaiced together with swarp (Bertin et al., 2002) to remove the gaps between
the individual detectors. These images are shown in Figure 7. Plotting the EMU
contours on the ALLWISE image, we see that most of the radio emission is
roughly traced by the 12 $\mu$m emission as expected for thermal
bremsstrahlung emission from H II regions (e.g., Condon et al., 1999; Condon &
Ransom, 2016; Khan et al., 2022). However, the central emission closest to PSR
J1032$-$5804, the putative PWN, does not show any emission at 12 $\mu$m. That
region is bright in H$\alpha$, and there is also a good correspondence between
the diffuse radio emission (putative PWN) surrounding PSR J1032$-$5804 and the
diffuse H$\alpha$ emission, including narrow filaments (putative shell). Other
regions that are bright at 12 $\mu$m are seen at radio and optical
wavelengths, suggesting thermal emission, but the region surrounding the
pulsar generally lacks mid-infrared emission. This suggests that it may in
fact be non-thermal emission associated with PSR J1032$-$5804, but we will
need better multi-wavelength imaging (including potentially deeper X-ray
images) or optical spectroscopy to confirm this.

The SED of PSR J1032$-$5804 is shown in Figure 8 (we excluded GLEAM data
points here as they are not constraining). The SED is ambiguous and noisy: it
may continue as a typical pulsar power-law, but it also may peak at a
frequency $\sim 1\,$GHz. This may be evidence of gigahertz-peaked spectrum
(GPS) behavior. Previous studies have suggested that the origin of the
gigahertz spectral turnover is likely caused by the absorption from the pulsar
ambient environment, such as supernova remnants (SNRs), pulsar wind nebula
(PWNe), and H II regions (e.g., Kijak et al., 2011; Rajwade et al., 2016). In
Figure 8, we fit the SED of PSR J1032$-$5804 with a simple power-law and the
thermal free-free absorption model described by Lewandowski et al. (2015b)

$S\left(\nu\right)=S_{1}\left(\nu/{1\,{\rm
GHz}}\right)^{\alpha}e^{-B\nu^{-2.1}}$

where $S_{1}$ is the pulsar’s intrinsic flux density at 1 GHz, $\alpha$ is the
pulsar’s intrinsic spectral index, and $B=0.08235\times T_{e}^{-1.35}{\rm EM}$
(emission measure ${\rm EM}=n_{e}^{2}s$; $n_{e}$, $s$, and $T_{e}$ are the
absorbing material electron density, size, and electron temperature,
respectively). For the power-law model, we found a spectral index of $-1.13\pm
0.03$. For the absorption model we estimated $S_{1}=9.61^{+1.52}_{-1.19}$,
$\alpha=-1.66^{+0.08}_{-0.08}$, and $B=0.86^{+0.12}_{-0.12}$, and found the
peak frequency $\nu_{p}=1.04\,$GHz. The peak frequency for PSR J1032$-$5804 is
consistent with the known GPS pulsar population (see Figure 7 in Kijak et al.
2021). We also note that there are deviations from both the free-free
absorption model and the power-law model. We compared these two models using
the $F$-statistic (e.g., Weisberg, 2005). The distribution of the
$F$-statistic follows an $F$-distribution with $d_{1}=1$, $d_{2}=6$ degrees of
freedom. We calculated an $F$-statistic of 6.80 with a corresponding $p$-value
of 0.04, which means that the free-free absorption model fits significantly
better than the power law model.

In Figure 9, we show the constraints on the electron density and temperature
of the absorber based on the fitted parameters and considered three scenarios:
a dense SNR filament (with $s=0.1\,$pc), a PWN (with $s=1.0\,$pc), and a cold
H II region (with $s=10.0\,$pc). The results are broadly consistent with
either the SNR filament or the PWN scenario (see Kijak et al. 2021, and
references therein), which agrees with the EMU extended emission analysis
above. For both scenarios, the expected fractional DM contribution from the
local environment is around 50%, which could potentially break the inferences
we made in previous discussions regarding the correlations between DM, RM, and
scattering timescale. For example, with a large DM contribution, the magnetic
field of the local environment could dominate the RM value we measured, which
could lead to a wrong estimation of the average interstellar magnetic field
along the line of sight. The relation between scattering timescales and DMs
could also be significantly affected if there are additional screens near the
pulsar (e.g., Cordes et al., 2016).

Besides free-free absorption, synchrotron self-absorption in the pulsar
magnetosphere (Sieber, 1973) or flux dilution caused by anomalous scattering
(Cordes & Lazio, 2001; Dembska et al., 2014) can also lead to a decrease in
the flux density at lower frequencies. Given that the data we have are all
above $\sim$0.8 GHz, it is hard to get a robust constraint on the surrounding
environment for PSR J1032$-$5804 without low-frequency observations. Further
deep radio continuum observations (especially at lower frequencies) of the
pulsar itself and the surrounding extended emission and/or deeper X-ray images
may be helpful in understanding the nature of the pulsar spectrum and probing
the interstellar medium in the pulsar’s local environment (e.g., potential SNR
association).

Figure 8: The radio spectrum of PSR J1032$-$5804\. Besides the ATCA data
listed in Table 2, we also used VAST, EMU, and RACS-mid data in this fit. For
the surveys with multiple observations (VAST and EMU), we used the mean flux
density mentioned in Section 3.2. The orange line shows the fitted free-free
absorption model and the red dashed line shows the corresponding peak
frequency, while the blue line shows the simple power law fit with a spectra
index of $-1.13\pm 0.03$. Figure 9: Constraints on the electron temperature
$T_{e}$ (white dashed lines) and electron density $n_{e}$ (heat map) based on
the best-fitted parameters (i.e., $B=0.99$). The x-axis shows the fractional
DM contribution from the absorber, and the y-axis shows the size of the
absorber on a logarithmic scale. We show expected values for different
absorbers in shaded regions: 1) SNR filament with $n_{e}\gtrsim 10^{3}\,$cm-3
and $T_{e}\sim 5000\,$K (e.g., Lee et al., 2013); 2) PWN with $n_{e}\sim
50-250\,$cm-3 and $T_{e}\sim 1500$ K (e.g., Gaensler & Slane, 2006); 3) H II
region with $n_{e}\gtrsim 10^{2}\,$cm-3 and $T_{e}\sim 1000-5000\,$K. (e.g.,
Shabala et al., 2006). The typical sizes of an SNR filament, PWN, and H II are
$0.1\,$pc, $1\,$pc, and $10\,$pc, respectively. Assuming a free-free
absorption model, our result largely agrees with the SNR filament or PWN
scenario.  Figure 10: Dispersion measure vs. pulse period $P$ for sources in
the ATNF pulsar catalog (v. 1.70). Pulsars without cataloged scattering
timescales are shown as black points. Those with cataloged scattering
timescales $\tau_{s}$ at 1.4 GHz are colored according to the ratio of the
timescale divided by the pulse period, with the color-bar shown on the right.
We also plot contours of constant $\tau_{s}/P$ based on the model of Bhat et
al. (2004). Sources with $\tau_{s}/P>1$ should not be detectable as pulsed
sources at 1.4 GHz. Individual highly-scattered pulsars are labeled, with
values for PSR J1410$-$6132 taken from O’Brien et al. (2008) and PSR
J1747$-$2809 taken from Camilo et al. (2009). PSR J1032$-$5804 is the star
with the red outline.

PSR J1032$-$5804 is the third most scattered pulsar known, which makes it hard
to detect in periodicity searches. In Figure 10 we plot the DM vs. period for
the pulsars in the ATNF pulsar catalog (Manchester et al., 2005). In general,
as DM increases so does the scattering (Cordes & Lazio, 2002; Bhat et al.,
2004; Lewandowski et al., 2015a; Yao et al., 2017). Those sources with the
highest DMs and the shortest periods will then be the hardest to detect in a
pulsation search. This is illustrated not only by the case of PSR
J1032$-$5804, but by other similar sources such as PSR J1813$-$1749 (Camilo et
al., 2021; Gotthelf & Halpern, 2009; Halpern et al., 2012; Dzib et al., 2010).
While PSR J1813$-$1749 is even more scattered than PSR J1032$-$5804, both of
them are undetectable as pulsed sources at the normal search frequency of 1.4
GHz. This is consistent with the fact that the location of PSR J1032$-$5804
was searched as part of the Parkes multi-beam pulsar survey (Manchester et
al., 2001) and the deeper High Time Resolution Universe mid-latitude survey
(Keith et al., 2010; Bates et al., 2011a), both centered at 1.4 GHz, but it
was not identified.

Many previous pulsar surveys are not sensitive to the highly scattered short-
period pulsars as most of them were conducted at lower frequencies (ranging
from $\sim$300 to 1400 MHz). Searching for pulsars at high frequency is one of
the ways to detect more new pulsars of this kind. However, only a few new
pulsars have been discovered in previous very high frequency ($\nu\gtrsim
5\,$GHz) pulsar surveys (e.g., Bates et al., 2011b; Eatough et al., 2021;
Torne et al., 2021; Suresh et al., 2022), which is possibly due to the limited
sensitivity (flux densities of pulsars will be low at high frequencies due to
their steep radio spectra) and insufficient sky coverage (small beam size at
high frequency makes it hard to tile the sky efficiently). With new high-
frequency pulsar surveys, such as MMGPS at S-band (1.7–3.5 GHz), more
scattered pulsars are expected to be discovered (Padmanabh et al., 2023). To
roughly quantify this, we used PsrPopPy (Bates et al., 2014)
121212https://github.com/samb8s/PsrPopPy to model the millisecond pulsar (MSP)
and normal pulsar populations. We found that $\sim$20% ($\sim$5%) of MSPs
(normal pulsars) could be missed in pulsar surveys at 1.4 GHz (assuming the
sensitivity to be $\sim$0.1 mJy) due to scattering (i.e., scattering timescale
longer than the period). When we change the central frequency to $3\,$GHz,
$\sim$70% of pulsars will be undetectable due to the lower flux density
(assuming that the sensitivities for 1.4 GHz and 3 GHz surveys are both 0.1
mJy), but $\sim$70% (90%) of previously undiscovered MSPs (normal pulsars)
will be visible to the 3 GHz survey, though the computational cost could be
prohibitively expensive due to the need to search for a large number of
pointings.

The prospects for new pulsar discovery in imaging domain are promising with
the development of new radio continuum surveys, including the GaLactic and
Extragalactic All-Sky MWA Extended Survey ((GLEAM-X Hurley-Walker et al.,
2022), the LOFAR Two-metre Sky Survey (LoTSS; Shimwell et al., 2017), the
ASKAP Rapid Continuum Survey (RACS; McConnell et al. 2020; Duchesne et al.
2023), the Evolutionary Map of the Universe survey with ASKAP(EMU; Norris et
al., 2011, 2021), the Karl G. Jansky Very Large Array (VLA) Sky Survey (VLASS;
Lacy et al., 2020), and The HUNt for Dynamic and Explosive Radio transients
with MeerKAT (THUNDERKAT; Fender et al., 2016) survey. For ASKAP surveys, we
considered shallow surveys ( with $\sim$12 mins integration time achieving a
typical detection threshold of $\sim$1.5 mJy) and deep surveys (with $\sim$10
hrs integration time achieving a typical detection threshold of $\sim$50
$\mu$Jy), and quantified the potential new detections with PsrPopPy (Bates et
al., 2014). We expected to detect 4 (8) highly scattered 131313Here we only
considered the pulsars that are undetectable with a 1.4 GHz pulsar survey.
Some of the pulsars discussed below are expected to be detected in a 3 GHz
pulsar survey as well. MSPs (normal pulsars) in shallow surveys, and 483 (600)
in deep surveys. Assuming $\sim$10% of pulsars are detected with circularly
polarized emission (e.g., Johnston & Kerr, 2018), the number of highly
scattered MSPs (normal pulsars) that can be detected via circular polarization
searches alone with ASKAP is expected to be 1 (1) for shallow surveys and 48
(60) for deep surveys. It is unlikely for shallow surveys to discover a large
number of highly scattered pulsars with circular polarization searches, but
using deep surveys or stacking several shallow surveys can potentially
discover a handful of new scattered pulsars. Besides circular polarization
searches, other image domain techniques, such as searching for steep spectrum
sources, high energy sources (e.g., X-ray, $\gamma$-ray) associations, and
potential SNRs (candidate) associations, can also be used in discovering
extremely scattered pulsars.

##  5 Conclusions

We discovered a young, highly scattered pulsar PSR J1032$-$5804 in the
Galactic plane in a search for circularly polarized sources as part of the
ongoing ASKAP-VAST survey. The pulsar has a period of 78.7 ms and a DM of
$819\pm 4\,$pc cm-3. The long scattering timescale $\tau_{\rm 1\,GHz}\approx
3.84\,$s makes it the third most scattered pulsar known and also explains the
non-detection in previous pulsar surveys despite its high flux density.
Besides circular polarization, linear polarization emission was also detected
in the follow-up observations with Murriyang/Parkes. The pulsar has an RM of
$-2000\pm 1\,$rad m-2. Though the measured RM is among the highest RM
detected, it is consistent with the general RM–DM trend, and also the Galactic
large-scale magnetic field model (e.g., Han et al., 2018).

PSR J1032$-$5804 is young, with a characteristic age of $34.6$ kyr. No X-ray
emission was detected in Swift observations, which gives an upper limit to the
0.5-8 keV X-ray luminosity of $1.6\times 10^{32}d^{2}_{5}\,$erg s-1. The ratio
of the X-ray luminosity to the spin-down luminosity is lower than many young
pulsars, but is still consistent with the tail of the population. Further
deeper X-ray observation may be able to constrain any X-ray emission from the
pulsar itself, the PWN, or the SNR shell. ATCA observations combined with the
archival ASKAP observations revealed that PSR J1032$-$5804 is a potential GPS
source, which suggested strong absorption along the line-of-sight. A
preliminary analysis in this work based on the surrounding extended radio
emission and the pulsar radio spectrum may infer the existence of the PWN or
SNR. Further observations to measure the spectral energy distribution of the
pulsar itself and the spectral map of the extended emission are useful to
understand its local environment, and hence probe the properties of the
interstellar medium in the vicinity of the pulsar.

This discovery highlights the possibility of discovering new pulsars
(especially extreme ones) from continuum images. We can identify more highly
scattered pulsars like PSR J1032$-$5804 with the high sensitivity and good
resolution data from the ongoing ASKAP surveys. In the future, with the
construction of next-generation radio telescopes such as the Square Kilometre
Array, the Deep Synoptic Array, and the Next Generation Very Large Array,
imaging domain searches will become a more powerful tool for discovering
extreme pulsars (e.g., highly accelerated, highly scattered, and highly
intermittent) that are hard to find via traditional surveys.

We thank an anonymous referee for helpful comments. We thank Marcus Lower, and
Apurba Bera for useful discussions. We thank Jackson Taylor and Scott Ransom
for help with Algorithmic Pulsar Timing. RS is supported by NSF grant
AST-1816904. DK is supported by NSF grants AST-1816492 and AST-1816904. AA is
supported by NSF grant AST-1816492. N.H.-W. is the recipient of an Australian
Research Council Future Fellowship (project number FT190100231). This
scientific work uses data obtained from Inyarrimanha Ilgari Bundara / the
Murchison Radio-astronomy Observatory. We acknowledge the Wajarri Yamaji
People as the Traditional Owners and native title holders of the Observatory
site. CSIRO’s ASKAP radio telescope is part of the Australia Telescope
National Facility (https://ror.org/05qajvd42). 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 Research Centre. Establishment of ASKAP, Inyarrimanha Ilgari
Bundara, the CSIRO Murchison Radio-astronomy Observatory and the Pawsey
Supercomputing Research Centre are initiatives of the Australian Government,
with support from the Government of Western Australia and the Science and
Industry Endowment Fund. The Parkes radio telescope is part of the Australia
Telescope National Facility which is funded by the Australian Government for
operation as a National Facility managed by CSIRO. We acknowledge the
Wiradjuri people as the Traditional Owners of the Observatory site. The
Australia Telescope Compact Array is part of the Australia Telescope National
Facility (https://ror.org/05qajvd42) which is funded by the Australian
Government for operation as a National Facility managed by CSIRO. We
acknowledge the Gomeroi people as the Traditional Owners of the Observatory
site. This paper includes archived data obtained through the CSIRO ASKAP
Science Data Archive, CASDA (http://data.csiro.au). This research has made use
of the NASA/IPAC Infrared Science Archive, which is funded by the National
Aeronautics and Space Administration and operated by the California Institute
of Technology. Based on data products from observations made with ESO
Telescopes at the La Silla Paranal Observatory under programme ID 177.D-3023,
as part of the VST Photometric H$\alpha$ Survey of the Southern Galactic Plane
and Bulge (VPHAS+, www.vphas.eu).

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