# An Image-Based Search for Pulsar Candidates in the MeerKAT Bulge Survey

Dale A. Frail National Radio Astronomy Observatory, P.O. Box O, Socorro, NM
87801, USA  Emil Polisensky U.S. Naval Research Laboratory, 4555 Overlook Ave
SW, Washington, DC 20375, USA  Scott D. Hyman Department of Engineering and
Physics, Sweet Briar College, Sweet Briar, VA 24595, USA  W. M. Cotton
National Radio Astronomy Observatory, 520 Edgemont Road, Charlottesville, VA
22903, USA  Namir E. Kassim U.S. Naval Research Laboratory, 4555 Overlook Ave
SW, Washington, DC 20375, USA  Michele L. Silverstein NRC Research Associate
U.S. Naval Research Laboratory, 4555 Overlook Ave SW, Washington, DC 20375,
USA  Rahul Sengar Center for Gravitation, Cosmology, and Astrophysics,
Department of Physics, University of Wisconsin-Milwaukee, PO Box 413,
Milwaukee, WI 53201, USA  David L. Kaplan Center for Gravitation, Cosmology,
and Astrophysics, Department of Physics, University of Wisconsin-Milwaukee, PO
Box 413, Milwaukee, WI 53201, USA  Francesca Calore Laboratoire d’Annecy-le-
Vieux de Physique Théorique, CNRS, F-74000 Annecy, France  Joanna Berteaud
University of Maryland, Department of Astronomy, College Park, MD 20742, USA
NASA Goddard Space Flight Center, Code 662, Greenbelt, MD 20771, USA  Maïca
Clavel Université Grenoble Alpes, CNRS, IPAG, F-38000 Grenoble, France  Marisa
Geyer High Energy Physics, Cosmology and Astrophysics Theory (HEPCAT) Group,
Department of Mathematics and Applied Mathematics, University of Cape Town,
Rondebosch 7701, South Africa  South African Radio Astronomy Observatory, 2
Fir Street, Black River Park, Observatory 7925, South Africa  Samuel Legodi
South African Radio Astronomy Observatory, 2 Fir Street, Black River Park,
Observatory 7925, South Africa  Vasaant Krishnan South African Radio Astronomy
Observatory, 2 Fir Street, Black River Park, Observatory 7925, South Africa
Sarah Buchner South African Radio Astronomy Observatory, 2 Fir Street, Black
River Park, Observatory 7925, South Africa  Fernando Camilo South African
Radio Astronomy Observatory, 2 Fir Street, Black River Park, Observatory 7925,
South Africa Dale A. Frail<EMAIL_ADDRESS>
###### Abstract

We report on the results of an image-based search for pulsar candidates toward
the Galactic bulge. We used mosaic images from the MeerKAT radio telescope,
that were taken as part of a 173 deg2 survey of the bulge and Galactic center
of our Galaxy at L band (856-1712 MHz) in all four Stokes I, Q, U and V. The
image root-mean-square noise levels of 12-17 $\mu$Jy ba-1 represent a
significant increase in sensitivity over past image-based pulsar searches. Our
primary search criterion was circular polarization, but we used other criteria
including linear polarization, in-band spectral index, compactness,
variability and multi-wavelength counterparts to select pulsar candidates. We
first demonstrate the efficacy of this technique by searching for polarized
emission from known pulsars, and comparing our results with measurements from
the literature. Our search resulted in a sample of 75 polarized pulsar
candidates. Bright stars or young stellar objects were associated with 28 of
these sources, including a small sample of highly polarized dwarf stars with
pulsar-like steep spectra. Comparing the properties of this sample with the
known pulsars, we identified 30 compelling candidates for pulsation follow-up,
including two sources with both strong circular and linear polarization. The
remaining 17 sources are either pulsars or stars, but we cannot rule out an
extragalactic origin or image artifacts among the brighter, flat spectrum
objects.

††facilities: MeerKAT, Parkes††software: PyBDSF (Mohan & Rafferty, 2015),
astropy (Astropy Collaboration et al., 2013, 2018), TOPCAT (Taylor, 2005,
2011),

##  1 Introduction

With the advent of a new generation of sensitive wide-field radio
interferometers, there has been a renewed interest in imaging the Galactic
center (GC) and the bulge of our Galaxy (Heywood et al., 2022; Wang et al.,
2022b; Goedhart et al., 2023). Early pioneering efforts revealed a significant
population of compact radio sources (LaRosa et al., 2000; Nord et al., 2004;
Lazio & Cordes, 2008), while time-domain monitoring led to the discovery of
new classes of transients and variables objects (e.g., Zhao et al., 1992;
Hyman et al., 2005; Wang et al., 2021; Zhao et al., 2022).

Another important application of image-based radio surveys is the
identification of pulsar candidates (e.g., Kaplan et al., 2000; de Gasperin et
al., 2018). It has long been argued that the enhanced stellar densities in the
GC and Galactic bulge could lead to a significant number of pulsars, and in
particular millisecond pulsars (Muno et al., 2006; Macquart & Kanekar, 2015;
Berteaud et al., 2021). There is an on-going debate on whether the diffuse
gamma-ray emission from the Galactic bulge, the so-called gamma-ray excess
identified by the Fermi Large Area Gamma-Ray Telescope, originates from a
population of thousands (or more) millisecond pulsars (MSPs) or is the first,
non-gravitational, signature of particles dark matter annihilation (e.g.,
Calore et al., 2021; Song et al., 2024), see Murgia (2020) for a review.
Identifying pulsations from this putative MSP population would go a long way
in resolving this controversy, but the existing census of pulsars is
inadequate (Calore et al., 2016). Traditional pulsation searches suffer from a
number of special challenges in this direction (Calore et al., 2016) but they
can be effective when used together with image-based methods (Frail et al.,
2018; McCarver et al., 2023; Wang et al., 2023; Anna-Thomas et al., 2024),
also combined with multi-wavelength cross-correlations (Berteaud et al.,
2023).

The initial image-based pulsar searches in the Galactic bulge and GC relied on
only two pulsar properties: their compactness and steep spectral indices
(Bhakta et al., 2017; Hyman et al., 2019). Variability has been re-discovered
as a sufficient but not necessary condition for identifying promising pulsar
candidates (Wang et al., 2022b; Heywood, 2023; Sett et al., 2023), but
polarization has proven to be an even more powerful search criterion. Pulsars
appear to be unique among compact radio sources for having both steep spectra
and high degrees of linear and/or circular polarization (Johnston & Kerr,
2018; Sobey et al., 2021). Identifying pulsar candidates by a high degree of
polarization in the image plane was first used to identify the young,
energetic pulsar PSR B1951+32 in the supernova remnant CTB 80 (Strom, 1987),
and then again to identify the luminous MSP PSR J0218+4232 (Navarro et al.,
1995). Recently there has been a resurgence in imaging surveys with an
emphasis on polarization (Lenc et al., 2018; Sobey et al., 2022; Wang et al.,
2022a; Duchesne et al., 2023; Callingham et al., 2023). There has been some
initial success at identifying promising pulsar candidates in the GC and bulge
using polarization as an additional search criterion (Hyman et al., 2021; Wang
et al., 2022a, b).

In this paper we build upon these efforts by using a new sensitive survey of
the Galactic bulge and GC region in full Stokes in a search for pulsar
candidates. The paper is organized in the following sections: we present the
data analyzed and data reduction pipeline in section 2 and 3 respectively. In
section 4, we illustrate the method followed to build our main source catalog,
including a discussion of survey properties and known data issues. In section
5, we put forward our selection strategy for pulsar candidates, mainly based
on polarization characteristics. In section 6, we comment on other important
selection criteria. The main results are presented in section 7, where we
present the pulsar candidate list and a detailed discussion about the non-
detection of some of these in previous pulsation-searches campaigns. We
conclude in section 8.

##  2 Observations

For this work we have used an archival South African Radio Astronomy
Observatory (SARAO) Legacy Survey of the Galactic Center Region (Code
SSV-20180505-FC-01), taken with the 64-element MeerKAT Radio Telescope array
(Jonas & MeerKAT Team, 2016; Camilo et al., 2018; Mauch et al., 2020). A
vertical strip at approximately $|{b}|<20^{\circ}$ and at least
$|{l}|<1.5^{\circ}$ (widening to $\pm{4.5}^{\circ}$ at lower latitudes) was
observed toward the GC, using the L-band receivers (856-1712 MHz). A total of
315 individual pointings were made during 42 sessions from 2019 Dec. 26 to
2020 Aug. 5. A single session was typically 8-10 hours in duration, during
which 7 or 8 pointings were observed, each receiving approximately one hour in
total integration time. Pointings were widely spaced in hour angle to maximize
spatial frequency ($uv$) coverage.

The MeerKAT correlator was configured to produce 4096 channels across the full
bandwidth in 8-s sampling in all four combinations (XX, YY, XY, and YX) of the
orthogonal linearly polarized feeds. PKS B1934$-$638 was used as the
photometric and bandpass calibrator, 3C 286 as the polarization calibrator,
and a nearby astrometric calibrator was used for each session. For a similar
observational setup see Heywood et al. (2022), or consult the MeerKAT
Knowledge
Base111https://skaafrica.atlassian.net/wiki/spaces/ESDKB/overview?homepageId=41025669
for current best practices.

##  3 Data Reduction

All calibration, imaging and mosaicing was carried out in the Obit software
package222http://www.cv.nrao.edu/~bcotton/Obit.html following standard
procedures. We summarize this process here but a full description is given in
the recently released SARAO MeerKAT 1.3 GHz Galactic Plane Survey (Goedhart et
al., 2023).

Calibration and editing followed procedures established by Mauch et al.
(2020), in which instrumental data errors and radio interference were
identified and flagged. The data were then calibrated for phase, amplitude,
bandpass, and group delays as described by Knowles et al. (2022). Polarization
calibration followed the same procedure outlined in Goedhart et al. (2023),
using 3C 286 as a polarized calibrator, and PKS B1934$-$638 as an unpolarized
source.

Figure 1: Galactic distribution of the 20 mosaic pointings used in this
survey. Each square is 3.125∘ × 3.125∘ in size. The full survey symmetric
about the GC and covers a vertical strip $\pm{20}^{\circ}$ in latitude and at
least $\pm{1.5}^{\circ}$ in longitude, but widens to $\pm{4.5}^{\circ}$ at
lower latitudes. The positions of the known pulsars that lie within the survey
area are indicated by filled circles.

Once calibrated the individual pointings in all four Stokes I, Q, U and V were
imaged and deconvolved within Obit. These individual pointings were formed
into 20 partially overlapping linear mosaics each 3.125∘×3.125∘ in size using
the optimal weighting scheme described in Goedhart et al. (2023). Each mosaic
was also imaged in 14 subbands, with bandwidths ranging from 43 to 74 MHz.
However, the middle two subbands were severely affected by radio frequency
interference (RFI) and had to be discarded. As a result, there are 6 good
subband images that span frequencies from 886 to 1171 MHz, and another 6 that
span frequencies from 1286 to 1681 MHz.

The 20 different mosaic fields given in the Galactic coordinate system
($l,b$), along with their properties are shown in Table 1 and plotted in Fig.
1. In Fig.2 we show an example of the Stokes I (left) and Stokes V (right)
mosaic images for the G0.0+5.5 pointing.

Figure 2: A typical 3.125∘×3.125∘ mosaic field for one of the 20 pointings. These are Stokes I (left) and Stokes V (right) images for the G0.0+5.5 mosaic field. There are approximately continuum 25,000 radio sources. After eliminating image artifacts and other false positives (see §5) we identify 4 known pulsars, 7 circularly polarized pulsar candidates but no linear polarized pulsar candidates in this mosaic field. Table 1: Observational Properties of Bulge Mosaics $l$ | $b$ | # of | rms |  |  | Known | Candi.
---|---|---|---|---|---|---|---
($\deg$) | ($\deg$) | Sources | ($\mu$Jy/ba) |  |  | PSRs | (V, P)
000.0 | +17.5 | 21,532 | 14.6 |  |  | 1 | 1, 0
000.0 | +14.5 | 23,088 | 13.9 |  |  | 1 | 0, 0
000.0 | +11.5 | 17,287 | 16.9 |  |  | 0 | 2, 1
000.0 | +8.5 | 17,966 | 17.7 |  |  | 2 | 3, 1
003.0 | +5.5 | 15,819 | 16.0 |  |  | 4 | 1, 2
357.0 | +5.5 | 13,367 | 17.4 |  |  | 3 | 4, 0
000.0 | +5.5 | 25,086 | 12.5 |  |  | 4 | 7, 0
003.0 | +2.5 | 17,769 | 14.7 |  |  | 7 | 2, 0
357.0 | +2.5 | 14,261 | 15.3 |  |  | 9 | 0, 1
000.0 | +2.5 | 18,815 | 14.3 |  |  | 10 | 4, 2
000.0 |  $-$2.5 | 19,709 | 14.0 |  |  | 18 | 6, 0
357.0 |  $-$2.5 | 14,451 | 14.7 |  |  | 7 | 3, 0
003.0 |  $-$2.5 | 12,715 | 16.8 |  |  | 11 | 4, 0
000.0 |  $-$5.5 | 29,992 | 10.7 |  |  | 4 | 1, 0
357.0 |  $-$5.5 | 22,252 | 11.9 |  |  | 5 | 3, 0
003.0 |  $-$5.5 | 21,019 | 11.9 |  |  | 2 | 3, 0
000.0 |  $-$8.5 | 23,350 | 13.4 |  |  | 0 | 6, 4
000.0 |  $-$11.5 | 20,847 | 13.5 |  |  | 1 | 4, 1
000.0 |  $-$14.5 | 27,358 | 11.4 |  |  | 0 | 4, 0
000.0 |  $-$17.5 | 26,322 | 12.1 |  |  | 1 | 9, 0

##  4 Source Catalog

For the source catalog and the following analysis we used a preliminary
version of the mosaic images. For the entire survey, including full Stokes
mosaic images and a gallery of extended sources, we refer the reader to
(Cotton & SARAO Meerkat Bulge Survey Team, , 2024 in preparation). As our
primary scientific goal is producing a list of pulsar candidates, the
following discussions on source catalogs, their properties, and any data
issues are focused on unresolved point sources.

We utilized PyBDSF (Mohan & Rafferty, 2015) to generate source catalogs for
all images. PyBDSF subtracts a mean background map from the pixel intensities
and normalizes each pixel value to the local noise, which is determined
through interpolation from a coarsely sampled grid. Extensive testing showed a
grid sampling of 25 pixels provides robust background subtraction and source
flux measurements. The mean pixel intensity and standard deviation is
calculated within a square box of 75 pixels on a side centered at each grid
point. Pixels belonging to sources are excluded from the background
calculation by iteratively rejecting outliers with large positive values.
Islands of connected pixels that exceed 3 times the local noise are used to
define sources, with elliptical Gaussian fitting initiated at the locations of
pixel peaks within these islands. Sources with a signal-to-noise ratio (S/N)
$<$ 5 and sources within 10 pixels of the image borders are discarded. We use
the source catalogs of combined Gaussian components to separate mutli-
component from single-component sources, a characteristic of unresolved point
sources. Negative polarizations were cataloged by running PyBDSF on the
negated Stokes Q, U, and V images.

Linear polarization images were created for each subband
($P=\sqrt{Q^{2}+U^{2}}$) and for the full bandwidth by averaging $P$ over all
subbands. Additionally, half bandwidth and quarter bandwidth images were
constructed by averaging subbands in groups of 6 and 3, respectively, for all
polarizations. Source spectra (S${}_{\nu}\propto\nu^{\alpha}$) were
independently determined in the half-band, quarter-band, and subband images
through inverse-variance weighted fits to sources detected more than once.
Note that we neglected to correct our linear polarization images for noise
bias (George et al., 2012). While the primary focus of this work was circular
polarization, this oversight does have some impact, which we discuss in §5.1.

The presence of blanked regions in the mosaic subbands complicates determining
source spectra in the half-band and quarter-band images. At lower frequencies,
these blanked regions are randomly distributed across the field due to the
need for RFI flagging of entire pointings. At higher frequencies, the field of
view is smaller, and blanking tends to occur near the mosaic edges. To account
for this, we calculated the average frequency across the subband-combined
images, excluding the blanked regions. We then used these position-dependent
frequencies for fitting source spectra.

The full bandwidth mosaic’s Stokes I catalog serves as the foundation for the
complete source catalog in each field. Polarized sources were identified by
locating the nearest source within 5 arcsec in the polarization catalogs.
Spectral indices were assigned by matching the full bandwidth catalog to the
half-band, quarter-band, and subband source catalogs.

To classify sources as compact or extended, we adopt the popular method (e.g.,
Intema et al., 2017; de Gasperin et al., 2018) analyzing the total-to-peak
flux ratio ($R$) of single-component sources binned by S/N for each field
catalog. We calculate the average and standard deviation of $R$ within each
bin after iteratively removing $2\sigma$ outliers to exclude extended sources.
We then fit a smoothly varying function of S/N to the $+2\sigma$ envelope
using an empirical equation adapted from Williams et al. (2013). We defined a
compactness metric as the ratio of $R$ obtained from the fitted equation to
the value measured for the source, serving as a statistical measure of source
extent. Single-component sources with a compactness greater than 1 have a
$\sim 97\%$ probability of being unresolved.

###  4.1 Survey Properties

Table 1 displays the number of sources in each field catalog. By associating
sources within 5 arcsec across different fields, we identified 387,875 unique
sources within the 173 deg2 survey area. Among these, 375,286 are classified
as single-component, with 298,785 being unresolved (compactness $>1$). 188,753
sources lack in-band spectral index determinations. For circularly polarized
sources without spectral indices (§5.2), we utilize PyBDSF in forced-fitting
mode where the full-band source position is used to initiate Gaussian fitting
in the individual subbands and subband combination images, enabling spectral
indices to be obtained with flux measurements of weaker detections (S/N $>3$).

The number of International Celestial Reference Frame (ICRF, Charlot et al.,
2020) sources within our survery area is insufficient for direct astrometric
correction calculation. To tackle this issue, we employed a two-step
correction process. First, we corrected each field to the RACS-mid catalog
(Duchesne et al., 2023), utilizing the median offset of unresolved sources
isolated from their nearest neighbors by at least 16 arcsec and within 8
arcsec of an unresolved RACS-mid source. We achieved $235-369$ matches per
field, with median offsets and standard deviations of $\Delta\alpha$
$\cos\delta=$ ($-0.33$ \- $1.02$) $\pm$ ($0.50$ \- $0.85$) arcsec, and
$\Delta\delta=$ ($-0.53$ \- $1.43$) $\pm$ ($0.43$ \- $0.92$) arcsec. The
astrometric offset magnitudes are less than 1 pixel for all fields. Second, we
determined the correction to ICRF using the offset of unresolved RACS-mid
sources within 8 arcsec of ICRF sources. To account for potential systematic
effects, we limited our calculation to RACS-mid sources within 40 degrees of
the GC. From 134 matches, we obtained $\Delta\alpha$ $\cos\delta=-0.21\pm
0.35$ arcsec and $\Delta\delta=0.10\pm 0.31$ arcsec. These offsets are within
1$\sigma$ of those calculated for the entire catalog (Duchesne et al., 2023).

Figure 3 shows the offset distribution for all 6766 sources with RACS-mid
matches, after correcting for the median offset. The standard deviation is
0.65 arcsec in both coordinates for the entire sample.

Figure 3: Angular offsets in right ascension and declination for 6766
unresolved sources detected in both this survey and the RACS-mid, after
applying astrometric corrections. See §4.1 for details.

###  4.2 Known Data Issues

These data were taken during an active development and commissioning stage of
MeerKAT and thus there are a number of potential instrumental and calibration
issues (e.g., labeling errors, calibrator position errors, delay tracking
errors). These errors are detailed in Heywood et al. (2022) but at the time of
these observations the dominant error was the delay tracking error; basically
the existing correlator model did not accurately transfer phases when
switching between calibrator and target. In §4.1 we looked for systematic
errors in the astrometry and attempted to correct for the bulk of these
uncertainties. Our resulting offsets and rms deviations in source positions
are comparable to similar values estimated for other datasets taken around the
same time and using similar methods (Heywood et al., 2022; Goedhart et al.,
2023; Taylor et al., 2024).

In order to improve S/N of the in-band spectral indices we averaged different
subbands together in six and three adjacent frequency bands (see §4). To test
the reliability of this averaging method we compared these derived spectral
indices with those fitted using all 12 subbands. This is shown in Fig. 4 where
we compare the difference between the un-averaged subbands and the half-band
averages (6 adjacent frequencies) for 85,273 compact, single component
sources. The difference between these two spectral index values is within the
best-fit errors for 73% of these compact, single-component sources, with the
larger scatter occurring for low S/N sources. In our search for known and
candidate pulsars below we primarily used the $\alpha$ values formed from the
six sub-band averages. However, when we saw significant deviations between the
other measures of $\alpha$, we visually inspected the un-averaged spectra. The
differences were usually due to RFI or low S/N resulting in a poor fit from
PyBDSF. In those few cases we simply manually re-fit the data but there was an
interesting subset of steep spectrum sources that were too faint at higher
frequencies that required a different search strategy (see §5.4). Goedhart et
al. (2023) and Cotton et al. (2024) have detailed other issues related to the
derivation of source spectral indices related to the lack of short spacings in
these Galactic fields. This leads to a frequency dependent “zero offset” error
that can steepen $\alpha$ from its true value. As this project is concerned
with unresolved point sources, it should not be a serious problem unless the
source is embedded in diffuse emission. Such cases can be identified by
inspecting the images directly.

Figure 4: The difference in source spectral index derived using the two half-
band averaged images and the individual 12 subband images for 85,273 compact,
single component sources. Sources are colored according to their S/N in the
full-band image.

Interferometers like MeerKAT with orthogonal linearly polarized feeds have
other instrumental effects. The most notable for polarimetric imaging is due
to antenna pointing errors, which result in a frequency-dependent instrumental
polarization signal also called “beam squint” (Sekhar et al., 2022). Taylor et
al. (2024) have shown that the polarization leakage for MeerKAT is negligible
($<0.2$%) over most of the L-band frequency range, but rises to several
percent for frequencies above 1.4 GHz for sources whose position is offset
more than 0.45∘ from the pointing center of the primary beam. For this
particular project there is an added effect that reduces beam squint. We are
looking for pulsars whose typically steep spectra ($\alpha\simeq{-1.7}$)
weight down the instrumental polarization by a factor of three at higher
frequencies compared to the lower frequencies. Some bright, flat spectrum
candidates with values of polarization of order 1-2% could still be
instrumental artifacts, but in any case their spectra would not make them
promising pulsar candidates.

In Fig. 5 we plot all 353 sources with detectable circular polarization as a
function of S/N. As we discussed above, we see a large number of detections at
the 1% level that are likely instrumental artifacts arising from polarization
leakage. For this reason bright Stokes I sources with $|{\rm V/I}|<1$% were
eliminated as candidates. This value is in line with other estimates of
polarization leakage from recent ASKAP and LOFAR polarimetric imaging surveys
(Wang et al., 2022b; Callingham et al., 2023). We will discuss the additional
image artifacts (open circles) and the histogram in §5.2.

Figure 5: Polarized flux fraction distribution for 353 circularly polarized
sources. Open circles are identified as image artifacts in §5.2 and not
included in the upper histogram plot.

##  5 Polarization Candidate Search

###  5.1 Known Pulsars

The efficacy of this survey for finding pulsar candidates can be tested using
the sample of known pulsars. There are 81 known pulsars that lie within the
survey area (see Fig. 1 and Table 1). This is an under count of the true
number of pulsars. There are two globular clusters (NGC 6522 and Terzan 5)
that collectively have at least 45 pulsars. However, unless the pulsar is well
separated from the cluster core, our images lack the angular resolution to
resolve them individually, (Urquhart et al., 2020; Zhang et al., 2020; Abbate
et al., 2023). We identified three discrete, polarized point sources in these
clusters for inclusion in Table 2. We suspect that the polarized radio source
identified as PSR J1748$-$2446ab may be an amalgamation of several overlapping
pulsars.

For each mosaic pointing we first cross-matched our source catalog with the
ATNF pulsar catalog333 http://www.atnf.csiro.au/research/pulsar/psrcat
(Manchester et al., 2005). When possible we substituted ATNF catalog positions
with newer values from the literature. For example, the identification of the
RRAT PSR J1739$-$2521 used a position from Cui et al. (2017). For Stokes I,
this resulted in nearly a 100% detection rate. The quality of the pulsar
position errors in this sample varies considerably; with sub-arcsec accuracy
for well-timed MSPs, to arcminute positions for RRATs. As a result, and given
our superb continuum sensitivity, it is likely that identifying pulsars
relying on only Stokes I would result in large number of detections of
unrelated background extragalactic radio sources. To reduce these false
positives, we required a positive pulsar match to also have either linear or
circular polarization.

Table 2 lists the properties of the 39 known polarized pulsars detected in
this survey. Circular polarization is listed under the column V/I, while
linear polarization is listed under P/I; S/N of each value is listed in the
adjacent column. Our failure to correct our linear polarization images for a
well-known noise bias (see §4), has a minor effect on the P/I values but
overestimates the S/N in some cases by a factor of two.

In a number of cases the uncertainties on our measured positions (RA/DEC),
flux density (I), spectral indices ($\alpha$) and polarization values are
significant improvements over what is available in the literature. For the
majority of the cases our positions are consistent with the known pulsar
positions within joint measurement uncertainties, with a few exceptions.
Specifically, the radio source identified with the MSP PSR J1653$-$2054 is
4-arcsec from its timing position, while for PSRs J1720$-$2446 and
J1751$-$3323 the timing vs interferometic positions are offset by 1.5$\sigma$
and 2$\sigma$, respectively. It is unlikely that these steep spectrum,
polarized point sources are false pulsar identifications as such sources are
rare. We show in the next section that the source density of circularly
polarized sources is only 0.5 deg-2, and de Gasperin et al. (2018) showed that
$<1$% of radio sources have $\alpha<-1.5$. Proper motion might explain the
offsets but there are no published values in the literature. It seems likely
that unmodeled timing residuals or optimistic position error estimates could
account for the two normal pulsars, but the 4-arcsec offset for the MSP is
difficult to explain.

The peak flux densities (I) of the pulsars in Table 2 range from about 0.4 to
40 mJy, and are broadly consistent with the values in the ATNF catalog. The
spectral indices $\alpha$ range from +0.07 to $-3.5$, with a median value of
$-1.8\pm{0.8}$, in reasonable agreement with the weighted mean spectral index
of 441 pulsars of $-1.60\pm{0.03}$ (Jankowski et al., 2018) and from the more
recent value of $-1.78\pm{0.6}$ from 168 pulsars (Anumarlapudi et al., 2023).
Nearly all of the pulsars have significant linear polarization, while less
than 2/3 have significant circular polarization. The maximum linear
polarization in Table 2 is 45%, while the maximum circular polarization is
about half this amount. This range in polarization and the absolute values of
the polarization percentages are consistent with the pulse-weighted averages
from a large sample of pulsars (Johnston & Kerr, 2018; Rickard & Cronyn, 1979;
Anumarlapudi et al., 2023). From the Johnston & Kerr (2018) sample of 600
pulsars, the mean linear polarization is 27% with a range from 1-100%, while
the mean circular polarization is 8.4%, with a range from 1-40%, with rare
cases in excess of 60%. Moreover, there are 18 pulsars in Table 2 which are
also found in common with Johnston & Kerr (2018). We detect linear and/or
circular polarization of the right magnitude from all but their two faintest
pulsars. The direction of polarization is reversed in these two samples,
suggesting different conventions between MeerKAT polarization and the known
pulsar sample.

Summarizing, we find polarized point sources coincident with approximately 50%
of the known pulsars, and their properties (flux density, spectral index and
polarization) are consistent with these radio sources as known pulsars.

Table 2: The Polarization Properties of Known Pulsars

PSR Name | P | DM | RA | DEC | I | $\alpha$ | V/I | S/N | P/I | S/N |
---|---|---|---|---|---|---|---|---|---|---|---
| (ms) | (pc cm-3) | (h m s) | (∘ ′ $"$) | (mJy) |  | (%) |  | (%) |  |
J1653$-$2054 | 4.1 | 56.5 | 16:53:30.79 |  $-$20:54:58.1 | 2.19$\pm$0.01 |  $-$1.33$\pm$0.02 |  |  | 1.7 | 6.2 |
J1719$-$2330 | 454.0 | 101.0 | 17:19:36.44 |  $-$23:30:07.3 | 2.89$\pm$0.09 |  $-$1.16$\pm$0.44 |  |  | 3.8 | 6.9 |
J1720$-$2446 | 874.3 | 104.3 | 17:20:22.57 |  $-$24:46:09.0 | 0.45$\pm$0.02 |  $-$2.52$\pm$0.19 |  |  | 14.1 | 7.1 |
B1717$-$29 | 620.4 | 42.6 | 17:20:34.11 |  $-$29:33:16.1 | 2.68$\pm$0.01 |  $-$1.16$\pm$0.03 |  $-$6.3 | 19.4 | 9.5 | 22.8 |
J1721$-$2457 | 3.5 | 48.2 | 17:21:05.50 |  $-$24:57:06.7 | 1.37$\pm$0.01 |  $-$1.17$\pm$0.05 |  $-$12.8 | 23.5 | 5.0 | 10.8 |
J1727$-$2739 | 1293.1 | 146.0 | 17:27:31.03 |  $-$27:38:53.0 | 1.76$\pm$0.01 |  $-$1.50$\pm$0.04 | 7.3 | 15.4 | 37.1 | 48.8 |
J1730$-$2304 | 8.1 | 9.6 | 17:30:21.69 |  $-$23:04:31.3 | 4.36$\pm$0.02 |  $-$0.31$\pm$0.03 | 20.9 | 86.4 | 21.6 | 120.6 |
B1730$-$22 | 871.7 | 41.1 | 17:33:26.41 |  $-$22:28:45.3 | 12.97$\pm$0.09 |  $-$3.10$\pm$0.18 | 3.1 | 12.5 | 12.6 | 61.9 |
J1734$-$2415 | 612.5 | 126.3 | 17:34:41.37 |  $-$24:16:15.0 | 0.60$\pm$0.01 |  $-$1.45$\pm$0.10 |  |  | 46.8 | 30.2 |
J1736$-$2457 | 2642.2 | 169.4 | 17:36:45.37 |  $-$24:58:02.4 | 1.06$\pm$0.01 |  $-$2.14$\pm$0.05 |  |  | 24.3 | 19.4 |
B1736$-$29 | 322.9 | 138.6 | 17:39:34.28 |  $-$29:03:02.7 | 4.86$\pm$0.04 |  $-$1.55$\pm$0.07 |  |  | 4.2 | 10.1 |
J1739$-$2521 | 1818.5 | 186.4 | 17:39:32.79 |  $-$25:21:09.3 | 0.35$\pm$0.01 |  $-$2.54$\pm$0.16 |  |  | 15.9 | 6.2 |
J1741$-$2733 | 893.0 | 147.4 | 17:41:01.33 |  $-$27:33:56.2 | 1.89$\pm$0.02 |  $-$2.35$\pm$0.05 |  $-$5.7 | 10.1 | 17.0 | 23.7 |
B1740$-$31 | 2414.7 | 193.1 | 17:43:36.72 |  $-$31:50:22.5 | 2.09$\pm$0.02 |  $-$2.54$\pm$0.05 | 4.2 | 8.2 | 13.7 | 32.4 |
J1743$-$3153 | 193.1 | 505.7 | 17:43:15.59 |  $-$31:53:05.8 | 0.73$\pm$0.02 | +0.07$\pm$0.15 |  $-$22.0 | 14.0 | 23.1 | 17.7 |
J1744$-$3130 | 1066.1 | 192.9 | 17:44:05.71 |  $-$31:30:06.5 | 0.74$\pm$0.02 |  $-$1.37$\pm$0.05 |  |  | 13.3 | 10.1 |
B1742$-$30 | 367.4 | 88.4 | 17:45:56.32 |  $-$30:40:22.9 | 18.85$\pm$0.04 |  $-$1.87$\pm$0.10 | 2.2 | 27.2 | 43.4 | 530.1 |
B1744$-$24A | 11.6 | 242.1 | 17:48:02.26 |  $-$24:46:37.7 | 3.45$\pm$0.04 |  $-$2.48$\pm$0.11 |  |  | 4.0 | 6.0 |
J1748$-$2446ab | 5.1 | 242.2 | 17:48:04.74 |  $-$24:46:41.8 | 0.9$\pm$0.04 |  |  |  | 19.0 | 7.2 |
J1748$-$3009 | 9.7 | 420.2 | 17:48:23.75 |  $-$30:09:11.6 | 2.19$\pm$0.17 |  $-$2.25$\pm$0.38 |  $-$7.1 | 6.8 | 16.6 | 19.8 |
B1746$-$30 | 609.9 | 509.4 | 17:49:13.51 |  $-$30:02:36.4 | 4.84$\pm$0.05 |  $-$1.99$\pm$0.06 |  $-$10.9 | 26.8 | 11.3 | 29.8 |
B1747$-$31 | 910.4 | 206.3 | 17:50:47.31 |  $-$31:57:44.5 | 1.64$\pm$0.01 |  $-$1.58$\pm$0.03 | 3.3 | 7.6 | 27.6 | 46.1 |
J1751$-$2857 | 3.9 | 42.8 | 17:51:32.65 |  $-$28:57:47.1 | 0.85$\pm$0.07 |  $-$2.42$\pm$0.75 |  |  | 37.0 | 14.6 |
J1751$-$3323 | 548.2 | 296.7 | 17:51:32.76 |  $-$33:23:34.5 | 1.59$\pm$0.01 |  $-$0.59$\pm$0.03 |  |  | 15.4 | 40.2 |
B1749$-$28 | 562.6 | 50.4 | 17:52:58.67 |  $-$28:06:38.3 | 39.22$\pm$0.05 |  $-$3.01$\pm$0.01 |  $-$3.2 | 73.9 | 11.2 | 267.7 |
J1754$-$3443 | 361.7 | 188.7 | 17:54:37.34 |  $-$34:43:55.0 | 1.01$\pm$0.03 |  $-$1.63$\pm$0.59 | 16.2 | 6.2 | 10.3 | 5.6 |
J1759$-$2922 | 574.4 | 79.4 | 17:59:48.26 |  $-$29:22:08.1 | 0.83$\pm$0.01 |  $-$2.61$\pm$0.07 | 5.5 | 5.3 | 19.9 | 21.7 |
J1759$-$3107 | 1079.0 | 128.3 | 17:59:22.05 |  $-$31:07:22.0 | 1.31$\pm$0.01 |  $-$1.49$\pm$0.04 |  $-$3.9 | 6.7 | 16.8 | 27.1 |
B1758$-$29 | 1081.9 | 125.6 | 18:01:46.82 |  $-$29:20:39.6 | 2.95$\pm$0.01 |  $-$1.79$\pm$0.02 | 8.0 | 31.6 | 43.5 | 170.4 |
J1801$-$3210 | 7.5 | 177.7 | 18:01:25.90 |  $-$32:10:53.8 | 0.67$\pm$0.01 |  $-$2.15$\pm$0.10 |  |  | 13.0 | 13.7 |
B1800$-$27 | 334.4 | 165.5 | 18:03:31.70 |  $-$27:12:05.2 | 1.41$\pm$0.02 |  $-$1.27$\pm$0.09 | 7.5 | 8.4 | 33.4 | 46.7 |
J1803$-$3002A | 7.1 | 192.6 | 18:03:35.11 |  $-$30:02:00.8 | 0.66$\pm$0.01 |  $-$2.15$\pm$0.09 |  $-$6.9 | 5.8 |  |  |
J1803$-$3329 | 633.4 | 170.9 | 18:03:44.45 |  $-$33:29:10.9 | 0.92$\pm$0.01 |  $-$1.26$\pm$0.05 |  $-$9.1 | 13.9 | 8.3 | 13.4 |
J1804$-$2717 | 9.3 | 24.7 | 18:04:21.15 |  $-$27:17:32.2 | 0.69$\pm$0.03 |  $-$3.50$\pm$0.18 |  $-$15.2 | 8.4 | 39.7 | 28.0 |
J1804$-$2858 | 1.5 | 232.5 | 18:04:01.53 |  $-$28:58:47.2 | 1.09$\pm$0.01 |  $-$2.45$\pm$0.05 | 9.9 | 15.5 | 5.4 | 8.6 |
B1804$-$27 | 827.8 | 313.0 | 18:07:08.50 |  $-$27:15:03.7 | 1.54$\pm$0.03 |  $-$3.19$\pm$0.22 |  $-$6.1 | 5.0 |  |  |
J1808$-$3249 | 364.9 | 147.3 | 18:08:04.51 |  $-$32:49:32.9 | 1.65$\pm$0.01 |  $-$1.10$\pm$0.03 | 6.8 | 16.6 | 8.8 | 21.5 |
J1812$-$2748 | 237.0 | 104.0 | 18:12:40.59 |  $-$27:48:04.5 | 0.41$\pm$0.04 |  $-$0.42$\pm$1.40 |  |  | 25.8 | 5.9 |
J1812$-$3039 | 587.5 | 141.4 | 18:12:44.90 |  $-$30:39:22.2 | 0.46$\pm$0.01 |  $-$2.19$\pm$0.12 |  |  | 28.1 | 18.7 |

Note. — The positions (RA/DEC), flux densities (I), spectral indices
($\alpha$) and polarization fraction V/I and P/I come from this work, while
the period (P) and dispersion measure (DM) are taken from the ATNF Pulsar
Catalog (Manchester et al., 2005).

###  5.2 Circularly Polarized Candidates

For each mosaic field we carried out a search for circular polarized sources.
We started by identifying circularly polarized sources within the catalog made
from each mosaic with $|{\rm V/I}|\geq$1%. The source density of circularly
polarized sources is only 0.5 deg-2, so this approach was sufficient to
identify all the radio sources with non-zero Stokes V, and sort them in order
of decreasing fractional polarization.

To complete the search, these remaining candidates were visually inspected
directly from the Stokes I and V images to look for suspect signals (see
§4.2). The most common V Stokes artifacts were produced from sidelobe
contamination from bright radio sources, while a smaller number were flagged
as suspicious as they were found at the far edge of the antenna’s field-of-
view, or the Stokes V signal was offset from the Stokes I peak by a
significant fraction of the synthesized beam. Of the 100 initial candidates
from the catalog search, 38 were flagged as suspicious or image artifacts,
another was a duplicate identification from two adjacent mosaics, and another
was a known pulsar that was found due to an improved timing position (Zhang et
al., 2020). The V/I values for the artifacts (open circles) and for both the
known pulsars and our candidates (filled circles) are shown in Fig. 5. While
the V/I values for the known pulsars in Table 2 are evenly distributed, the
candidates in Table 3 are skewed toward more positive V/I values. Other
polarization samples exhibit a slight skew in positive V/I (e.g., Johnston &
Kerr, 2018), but our sample has a nearly 2:1 ratio.

The “V” entries in column 6 of Table 1 list the number of circularly polarized
candidates found in each of the mosaic pointings. Our final sample of 60
circularly polarized candidates is given in Table 3 and is plotted in Fig. 6
(left). While the number of known pulsars in Fig. 1 increases with decreasing
Galactic latitude as expected, the distribution of circular polarized sources
in Table 1 is more uniform, with clusters of candidates at high latitude
(e.g., G000.0$-$17.5). This is suggestive that not all of these circular
polarized sources are pulsars, but rather some other source population(s).
This hypothesis is further supported by the source distribution in Fig. 6. The
mean spectral index of our 60 candidates is $-0.6$, versus $-1.8$ for the
known pulsars in Table 2. Likewise, the fractional polarization for the known
pulsars in these fields ranges from 2-20%, while the candidates are
distributed over a much larger range.

The absence of sources in the bottom left hand corner of Fig. 6 is due to a
noise bias, the result of cutting off low S/N detections (see also Pritchard
et al., 2021; Wang et al., 2022b; Sobey et al., 2022; Callingham et al.,
2023). The fixed MeerKAT integrations introduce a strong bias in our
polarization measurements. For example, our candidates must have a peak Stokes
I flux in excess of $\sim$1 mJy to have a measured V/I$<$5%. As this is rather
bright, we expect that most such pulsars will have been found by previous
time-domain surveys, while our candidates on average will be fainter than
that. The real distribution of circular polarization with peak flux is closer
approximated by the large sample of Johnston & Kerr (2018) plotted in Fig. 6
as light grey points. In that sample, there is no noise bias because the
integration times for each of the pulsars are determined in order to achieve a
S/N sufficient to measure their polarization properties.

The lack of bright, highly polarized sources, however, is real (i.e, upper
right corner). As we noted in §4.2, the cluster of bright ($>$3 mJy) weakly
polarized (1-2%) candidates in the bottom right corner could still have some
false positives among them. While there are some steep spectrum sources in
this low polarization sample that may have been missed by previous pulsation
searches, we suspect that most are extragalactic sources with weak circular
polarization or beam squint artifacts. There is support for this hypothesis
since the median spectral index of this small sample more closely resembles
that of extragalactic sources than pulsars (de Gasperin et al., 2018). In §6
we will use multi-wavelength counterparts in an effort to distinguish
promising pulsar candidates from other source populations.

Figure 6: Polarized candidates (red) and known pulsars (blue). The left panel
plots the absolute value of the circular polarization fraction versus Stokes I
flux density, while the right plots the linear polarization versus Stokes I
flux density. The size of the circle for each point is proportional to the
spectral index, with larger circles indicating steeper negative spectral
indices. Grey points are polarization and flux density values taken from the
compilation of Johnston & Kerr (2018).

Table 3: Circularly Polarization Candidates  RA | DEC | $l$ | $b$ | I | $\alpha$ | V/I | S/N | Notes
---|---|---|---|---|---|---|---|---
(h m s) | (∘ ′ $"$) | (deg) | (deg) | (mJy) |  | (%) |  |
16:45:59.27 |  $-$18:22:20.1 | 0.96 | 17.21 | 0.39$\pm$0.01 | 0.53$\pm$0.3 | 13.5 | 7.0 | O,IR; YSO
16:56:48.02 |  $-$23:09:01.8 | 358.6 | 12.31 | 0.81$\pm$0.02 | 0.21$\pm$0.16 |  $-$7.9 | 5.2 | O,IR; A05 star
17:00:27.74 |  $-$22:07:42.7 | 359.96 | 12.24 | 0.08$\pm$0.01 | -1.07$\pm$0.70 |  $-$67.6 | 8.0 | O, IR; Late M dwarf
17:11:23.02 |  $-$24:38:49.6 | 359.37 | 8.74 | 0.16$\pm$0.02 | -0.64$\pm$0.64 |  $-$42.8 | 9.6 | O,IR: YSO
17:12:08.72 |  $-$23:09:49.8 | 0.7 | 9.45 | 0.26$\pm$0.01 | 0.16$\pm$0.31 | 20.4 | 7.8 | O,IR: YSO
17:13:34.15 |  $-$24:10:44.5 | 0.05 | 8.6 | 3.88$\pm$0.01 | 0.07$\pm$0.03 |  $-$1.1 | 5.6 |
17:16:29.81 |  $-$26:55:16.7 | 358.16 | 6.49 | 0.19$\pm$0.01 | 0.43$\pm$0.96 | 60.6 | 12.5 | X,O,IR: YSO
17:17:41.97 |  $-$28:56:19.4 | 356.65 | 5.11 | 0.08$\pm$0.01 | -1.12$\pm$0.96 | 64.4 | 6.3 | X,O,IR: YSO
17:19:56.71 |  $-$24:57:04.2 | 0.24 | 6.97 | 0.32$\pm$0.01 | 1.12$\pm$0.4 |  $-$27.4 | 11.1 | O,IR: YSO
17:20:18.40 |  $-$26:52:07.8 | 358.69 | 5.82 | 0.20$\pm$0.01 |  $-$1.87$\pm$0.31 |  $-$27.8 | 7.9 |
17:20:55.04 |  $-$27:20:41.5 | 358.38 | 5.44 | 0.27$\pm$0.01 | 0.15$\pm$0.31 |  $-$33.8 | 12.6 | X,O,IR: Binary star
17:23:29.79 |  $-$28:20:36.1 | 357.87 | 4.4 | 0.59$\pm$0.01 |  $-$1.52$\pm$0.11 |  $-$12.5 | 6.2 |
17:24:16.36 |  $-$27:30:43.8 | 358.66 | 4.73 | 0.53$\pm$0.01 | 0.88$\pm$0.17 | 17.3 | 11.7 | X,O,IR: YSO
17:27:28.51 |  $-$25:28:20.6 | 0.76 | 5.26 | 0.57$\pm$0.01 | 0.51$\pm$0.13 | 13.9 | 10.0 | O,IR: YSO
17:27:52.07 |  $-$27:27:24.6 | 359.15 | 4.09 | 0.18$\pm$0.02 |  $-$1.99$\pm$0.45 | 26.4 | 6.2 |
17:28:20.26 |  $-$26:08:16.6 | 0.31 | 4.73 | 0.22$\pm$0.01 |  $-$2.9$\pm$0.26 | 17.8 | 5.5 |
17:29:31.96 |  $-$27:31:37.8 | 359.29 | 3.75 | 0.11$\pm$0.02 |  $-$1.05$\pm$0.67 | 60.1 | 7.8 |
17:32:50.03 |  $-$23:54:14.4 | 2.75 | 5.1 | 5.31$\pm$0.01 |  $-$1.16$\pm$0.01 |  $-$1.4 | 9.8 |
17:37:57.25 |  $-$27:33:05.3 | 0.29 | 2.16 | 3.74$\pm$0.01 |  $-$0.13$\pm$0.02 |  $-$1.7 | 7.0 |
17:40:06.78 |  $-$28:05:33.9 | 0.08 | 1.47 | 0.86$\pm$0.02 |  $-$1.46$\pm$0.15 | 30.0 | 22.2 |
17:44:08.71 |  $-$24:24:53.4 | 3.69 | 2.64 | 1.19$\pm$0.02 |  $-$2.20$\pm$0.09 | 19.9 | 18.8 |
17:45:43.03 |  $-$26:58:53.9 | 1.68 | 1.0 | 3.34$\pm$0.02 |  $-$0.57$\pm$0.04 |  $-$1.8 | 5.1 | X
17:47:18.05 |  $-$33:09:17.4 | 356.58 |  $-$2.5 | 0.91$\pm$0.01 |  $-$1.99$\pm$0.08 |  $-$23.9 | 24.4 |
17:51:06.84 |  $-$32:18:28.5 | 357.72 |  $-$2.75 | 0.58$\pm$0.01 | 0.92$\pm$0.15 | 18.4 | 14.6 | X,O,IR: YSO
17:51:15.97 |  $-$29:43:52.0 | 359.95 |  $-$1.46 | 0.8$\pm$0.03 |  $-$1.74$\pm$0.22 | 8.3 | 5.6 |
17:52:29.06 |  $-$28:49:05.6 | 0.87 |  $-$1.23 | 1.07$\pm$0.02 |  $-$0.86$\pm$0.12 | 9.0 | 7.1 |
17:53:06.42 |  $-$29:30:00.8 | 0.36 |  $-$1.69 | 0.26$\pm$0.02 |  $-$1.51$\pm$0.51 | 26.0 | 6.5 |
17:53:06.50 |  $-$28:51:26.2 | 0.91 |  $-$1.37 | 0.22$\pm$0.02 |  $-$0.84$\pm$0.53 | 46.0 | 8.4 | G: PSR?
17:53:39.01 |  $-$33:31:28.4 | 356.94 |  $-$3.83 | 0.15$\pm$0.01 |  $-$1.17$\pm$0.38 | 23.7 | 5.4 |
17:55:24.86 |  $-$33:58:30.7 | 356.73 |  $-$4.37 | 0.16$\pm$0.01 |  $-$0.28$\pm$0.37 | 39.5 | 9.0 | O,IR
17:59:20.04 |  $-$28:29:56.6 | 1.91 |  $-$2.37 | 0.13$\pm$0.01 |  $-$2.24$\pm$0.57 |  $-$33.7 | 5.3 |
17:59:20.59 |  $-$30:15:48.7 | 0.37 |  $-$3.24 | 0.17$\pm$0.01 | 1.66$\pm$0.58 | 22.1 | 5.2 | O,IR: $\beta$ Cep.
18:00:12.33 |  $-$27:44:32.5 | 2.66 |  $-$2.16 | 0.12$\pm$0.02 | 0.25$\pm$1.63 | 69.1 | 8.3 | crowded field
18:00:32.14 |  $-$27:35:36.0 | 2.83 |  $-$2.15 | 0.29$\pm$0.02 |  $-$2.93$\pm$0.28 |  $-$20.9 | 6.2 |
18:04:03.38 |  $-$33:31:53.0 | 358.01 |  $-$5.72 | 3.73$\pm$0.01 | 0.26$\pm$0.02 |  $-$1.0 | 5.9 | X
18:05:26.44 |  $-$29:29:54.6 | 1.69 |  $-$4.02 | 0.18$\pm$0.01 |  $-$4.31$\pm$0.38 | 86.3 | 21.5 | X,O,IR: K star
18:06:31.55 |  $-$29:21:37.0 | 1.93 |  $-$4.16 | 0.06$\pm$0.01 | 0.27$\pm$0.99 | 85.2 | 7.0 |
18:11:37.21 |  $-$32:06:50.9 | 0.02 |  $-$6.44 | 0.36$\pm$0.01 |  $-$0.49$\pm$0.13 | 17.4 | 9.3 |
18:13:45.72 |  $-$33:17:38.6 | 359.18 |  $-$7.39 | 0.18$\pm$0.01 |  $-$1.71$\pm$0.45 | 106.8 | 24.8 | O; M dwarf
18:15:21.88 |  $-$32:53:02.1 | 359.71 |  $-$7.49 | 3.17$\pm$0.01 |  $-$0.7$\pm$0.02 | 1.3 | 5.9 |
18:16:34.34 |  $-$32:34:12.4 | 0.11 |  $-$7.57 | 0.45$\pm$0.01 |  $-$1.06$\pm$0.11 | 7.2 | 5.1 |
18:17:09.82 |  $-$33:17:31.2 | 359.52 |  $-$8.02 | 0.13$\pm$0.01 | 0.62$\pm$0.48 |  $-$24.6 | 5.5 | O,IR: YSO
18:18:31.06 |  $-$32:54:18.2 | 360.0 |  $-$8.09 | 0.2$\pm$0.01 |  $-$1.18$\pm$0.25 | 45.7 | 14.2 |
18:19:52.24 |  $-$29:16:34.4 | 3.38 |  $-$6.68 | 0.27$\pm$0.02 | 0.68$\pm$0.63 |  $-$27.2 | 5.1 | O,IR: Binary star
18:29:52.06 |  $-$33:55:40.8 | 0.13 |  $-$10.67 | 0.2$\pm$0.01 | 1.2$\pm$0.4 | 41.2 | 12.2 | O,IR: YSO
18:29:52.97 |  $-$33:43:04.7 | 0.33 |  $-$10.58 | 0.16$\pm$0.01 | 0.61$\pm$0.37 | 46.0 | 11.0 | O,IR: Star
18:34:49.11 |  $-$35:05:25.8 | 359.51 |  $-$12.09 | 5.4$\pm$0.01 |  $-$0.5$\pm$0.02 |  $-$1.2 | 9.6 |
18:35:01.56 |  $-$34:18:20.1 | 0.25 |  $-$11.79 | 3.18$\pm$0.01 | 0.33$\pm$0.02 | 1.1 | 5.1 |
18:41:54.78 |  $-$36:07:49.2 | 359.14 |  $-$13.83 | 0.14$\pm$0.01 |  $-$1.58$\pm$0.55 |  $-$38.4 | 8.5 |
18:43:58.38 |  $-$35:59:10.0 | 359.45 |  $-$14.15 | 0.28$\pm$0.01 | 1.31$\pm$0.27 | 12.3 | 5.7 | O,IR: YSO
18:50:19.66 |  $-$36:29:12.8 | 359.49 |  $-$15.53 | 3.97$\pm$0.01 |  $-$0.14$\pm$0.01 | 1.0 | 6.5 |
18:52:26.04 |  $-$37:30:37.8 | 358.67 |  $-$16.3 | 0.21$\pm$0.01 |  $-$2.70$\pm$0.37 | 41.2 | 9.5 | X,O,IR: M4.5 dwarf
18:57:45.15 |  $-$37:19:38.3 | 359.25 |  $-$17.22 | 0.53$\pm$0.01 |  $-$0.05$\pm$0.12 |  $-$28.7 | 22.7 | X,O,IR: YSO
19:00:51.24 |  $-$36:13:15.8 | 0.57 |  $-$17.39 | 0.06$\pm$0.01 |  $-$0.63$\pm$0.69 | 53.4 | 5.2 | IR: YSO
19:01:40.56 |  $-$36:44:32.4 | 0.12 |  $-$17.74 | 0.08$\pm$0.01 | 2.08$\pm$0.76 | 63.3 | 9.4 | O,IR: YSO
19:01:48.04 |  $-$36:57:20.5 | 359.92 |  $-$17.84 | 0.61$\pm$0.01 | 0.56$\pm$0.12 | 18.0 | 18.7 | IR: YSO
19:01:55.64 |  $-$37:39:41.1 | 359.24 |  $-$18.11 | 5.34$\pm$0.01 | 0.75$\pm$0.01 |  $-$1.5 | 13.0 | X,O,IR: YSO
19:03:06.35 |  $-$37:16:41.7 | 359.7 |  $-$18.19 | 0.16$\pm$0.01 |  $-$0.55$\pm$0.28 | 44.8 | 12.2 | O,IR: YSO
19:06:25.66 |  $-$37:03:49.5 | 0.16 |  $-$18.74 | 0.19$\pm$0.01 |  $-$0.18$\pm$0.32 | 85.6 | 24.7 |
19:07:38.78 |  $-$37:08:55.9 | 0.16 |  $-$19.0 | 6.64$\pm$0.01 |  $-$1.08$\pm$0.01 |  $-$1.1 | 7.7 |

###  5.3 Linearly Polarized Candidates

A different approach was needed for identifying linear polarized pulsar
candidates. The Stokes Q and U mosaic images have rich structure, likely due
to Faraday rotation from the interstellar medium of large scale Galactic
emission. Moreover, the areal density of linearly polarized sources in the
master catalog is large, approximately 40 deg-2, with the majority of the
polarized emission coming from extended sources (AGN jets, supernova remnants,
etc.). More stringent selection criteria were needed to achieve a manageable
number of pulsar candidates. For each mosaic pointing we first eliminated
extended sources by requiring that the compactness criterion exceed 0.9 and
that the source not be fit by multiple Gaussian components (see §4).

Once we identified a sample of compact radio sources, we further required that
the spectral index $\alpha\lesssim-1.5$ and the fractional linear polarization
$|{\rm{P/I}}|>5\%$. These criteria restrict the phase space to pulsar-like
properties in order to keep the false positives to a manageable level, but
also introduces a selection bias in the sample. Approximately 50% of all known
pulsars have spectral indices steeper than $-1.5$ (Jankowski et al., 2018) and
95% of pulsars have linear polarization above 5% (Johnston & Kerr, 2018).
Despite these more restrictive criteria, visual inspection of the polarization
images resulted in about 80% of the candidates being identified as either
image artifacts or extra-galactic. The largest false positives were
extragalactic sources, seen as compact polarized knots in jets, double radio
sources, and clusters of radio sources. Our final sample of 10 linear
polarized candidates is given in Table 4 and is plotted in Fig. 6. The ”P”
entries in column 6 of Table 1 lists the number of linear polarized candidates
found in each of the mosaic pointings, including two candidates identified in
more than one mosaic field.

The properties of these linear polarized candidates are listed in Table 4 and
plotted in Figure 6 (right). Not surprisingly, given our selection criteria,
the spectral index distribution and high fractional polarization are similar
to the known pulsars in Table 2 and the larger sample of linear polarization
measurements from Johnston & Kerr (2018). There are some compelling candidates
in Table 4 based on the compactness, steep spectrum and polarization criteria.
J173121.50$-$250235.7 is an exceptionally bright steep spectrum source with a
Stokes I flux density of 12 mJy and is 16% polarized, while
J174408.71$-$242453.4 is also bright (I=1.2 mJy) and steep spectrum but has
both significant linear and circular polarization. It is likely, however, that
these candidates are relatively nearby and not in the bulge. Given our central
observing frequency ($\nu$=1284 MHz) and the bandwidth of the 12 sub-band
averages ($\delta\nu\simeq$50 MHz) that we used (§2), we expect significant
Faraday bandwidth depolarization for rotation measures (RM) in excess of 235
rad m-2 (see Eqn 1 of Hyman et al., 2021), well below RM values reported near
the GC (Livingston et al., 2021).

Table 4: Linear Polarization Candidates  RA | DEC | $l$ | $b$ | I | $\alpha$ | P/I | S/N
---|---|---|---|---|---|---|---
(h m s) | (∘ ′ $"$) | (deg) | (deg) | (mJy) |  | (%) |
17:01:54.67 |  $-$22:50:08.3 | 359.58 | 11.55 | 0.73$\pm$0.01 |  $-$2.00$\pm$0.09 | 13.3 | 11.6
17:18:37.15 |  $-$23:35:10.5 | 1.21 | 7.99 | 1.62$\pm$0.02 |  $-$1.52$\pm$0.11 | 7.2 | 10.4
17:26:26.80 |  $-$30:48:09.2 | 356.19 | 2.5 | 3.63$\pm$0.03 |  $-$1.65$\pm$0.08 | 6.9 | 14.9
17:31:21.50 |  $-$25:02:35.7 | 1.6 | 4.76 | 12.33$\pm$0.02 |  $-$1.48$\pm$0.01 | 14.0 | 197.0
17:44:08.71 |  $-$24:24:53.4 | 3.69 | 2.64 | 1.19$\pm$0.02 |  $-$2.20$\pm$0.09 | 14.3 | 12.8
18:18:22.84 |  $-$32:44:16.0 | 0.13 |  $-$7.99 | 0.23$\pm$0.01 |  $-$2.34$\pm$0.26 | 31.0 | 12.1
18:21:46.77 |  $-$32:47:27.8 | 0.41 |  $-$8.65 | 0.26$\pm$0.01 |  $-$1.48$\pm$0.33 | 16.6 | 7.3
18:24:17.96 |  $-$32:38:05.4 | 0.79 |  $-$9.05 | 0.60$\pm$0.06 |  $-$2.66$\pm$0.54 | 23.7 | 13.6
18:27:31.72 |  $-$32:52:38.9 | 0.88 |  $-$9.77 | 1.33$\pm$0.02 |  $-$1.51$\pm$0.08 | 5.9 | 12.3
18:37:36.28 |  $-$33:50:13.8 | 0.92 |  $-$12.08 | 0.25$\pm$0.01 |  $-$3.04$\pm$0.29 | 16.3 | 7.4

###  5.4 Low-Band Circularly Polarized Candidates

There are significant numbers of sources in the catalog that are not detected
with 5$\sigma$ significance across the full frequency range of the MeerKAT
L-band receivers. This may be the result of channel flagging due to RFI, or
that the source has a sufficiently steep spectrum that it falls below the
noise threshold at higher frequencies. As we are looking for steep-spectrum
pulsars, we considered additional candidates which met our selection criteria
using only the lower half of the band centered at 1.022 GHz. We might expect
that the majority of such sources will be weak and steep spectrum in order for
them to have been missed by the selection criteria in §5.2 and §5.3.

Using only the low frequency end of L-band, we found a total of 9 compact,
circularly polarized ($|$V/I$|>$1%) candidates and 32 linearly polarized
(P/I$>$5%) candidates. None of the low-band linear polarized candidates passed
our visual inspection. Of the 9 low-band circularly polarized sources, three
were image artifacts and one was an known pulsar, PSR J1748$-$3009 (Table 2).
The final list of five candidates is shown in Table 5. The full-band peak flux
density is listed, whereas the percent polarization and S/N are derived from
the low end of the band. We note that one of these candidates,
J182417.96$-$323805.4, is also detected as a linearly polarized source in
Table 4.

Table 5: Low-Band Circularly Polarized Candidates  RA | DEC | $l$ | $b$ | I | $\alpha$ | V/I | S/N
---|---|---|---|---|---|---|---
(h m s) | (∘ ′ $"$) | (deg) | (deg) | (mJy) |  | (%) |
17:27:34.51 |  $-$26:09:57.1 | 0.19 | 4.86 | 0.07$\pm$0.01 |  $-$1.87$\pm$0.72 | 64.0 | 5.5
17:31:14.95 |  $-$27:35:32.4 | 359.45 | 3.39 | 0.30$\pm$0.01 |  $-$2.18$\pm$0.22 | 13.9 | 5.3
18:02:21.53 |  $-$32:54:38.0 | 358.38 |  $-$5.10 | 3.46$\pm$0.01 |  $-$1.61$\pm$0.01 | 1.3 | 5.5
18:24:17.96 |  $-$32:38:05.4 | 0.79 |  $-$9.05 | 0.60$\pm$0.06 |  $-$2.66$\pm$0.54 | 12.4 | 6.2
18:51:20.86 |  $-$35:46:19.5 | 0.26 |  $-$15.44 | 0.18$\pm$0.01 |  $-$1.36$\pm$0.29 | 20.0 | 5.3

##  6 Additional Selection Criteria

As previously noted in §5.2, there are other source populations among the
circularly polarized sources in Table 3 that are not pulsars. This is less
likely for the linear polarized candidates in Table 4 since we have used more
stringent pulsar-like criteria to limit the false positives. Extragalactic
radio sources are not expected to be a significant contaminant for circular
polarization. Apart from fast radio bursts, which we do not expect to detect,
the circular polarization from extragalactic radio sources rarely exceeds 1%
(Macquart, 2002). On the other hand, magnetically active single and binary
stars can produce non-thermal (coherent and incoherent) radio emission that
can be strongly polarized. A comprehensive list of the types of radio stars
expected and the origin of their polarized emission can be found in Pritchard
et al. (2021) and Callingham et al. (2023) for centimeter and decimeter
wavelengths, respectively.

A multi-wavelength approach can be useful for both identifying these stellar
populations and for bolstering pulsar candidates. To this end, in the next
several subsections we search for counterparts to our polarized radio sources
at gamma-rays, X-rays, optical and infrared wavelengths. Where possible, we
also include archival radio data to better constrain the in-band spectral
indices and to search for variability. However, before focusing on any
wavelength-specific searches, we began by searching a 2-arcmin radius around
each of the sources in Tables 3-5 using the SIMBAD database (Wenger et al.,
2000). There are two immediate findings from this search that help to inform
the multi-wavelength searches below. The first is that given our astrometry
accuracy (§4.1), the high stellar densities in the bulge will likely result in
significant false positives in the optical/NIR. We discuss our efforts to
mitigate this in §6.2. The second finding is that there are a large number of
unexpectedly bright, nearby stars or young stellar objects within 5-arcsec of
our circularly polarized candidates. For example, one of our strongly
polarized sources (V/I=86%), J190625.66$-$370349.5 lies close to the high
proper motion, naked eye star $\gamma$ CrA with G=4.8 mag. Proper motion
corrections will be needed to assess whether these are real associations (see
§6.2), but the preponderance of SIMBAD matches of stars with G-band magnitudes
in excess of 10-15 mag is suggestive, given their rarity among the known Gaia
stellar brightness distribution (Gaia Collaboration et al., 2021).

###  6.1 High Energy Counterpart Searches

The Fermi Gamma-ray Space Telescope has discovered pulsed emission from nearly
300 pulsars (Smith et al., 2023), but there remain many more candidates with
distinct spectral and temporal signatures among the unknown or unassociated
gamma-ray sources (Abdollahi et al., 2022). We searched for matches between
our polarized pulsar candidates and the 2577 unknown or unassociated _Fermi_
gamma-ray sources in the latest 14-year Fermi-LAT incremental catalog (Ballet
et al., 2023). We find one match of 4FGL J1753.2$-$2848 with the circularly
polarized source J175306.50$-$285126.2 ($|{\rm{V/I}}|$=46%) in Table 3. The
unknown Fermi source is associated to the X-ray source 1RXS
J175328.7$-$285014, and its best-fit energy spectrum is compatible with pulsar
spectral characteristics (Smith et al., 2023). We note that the 86 msec period
PSR J1753$-$28 lies 94-arcsec from this polarized radio source, but the pulsar
position is poorly constrained ($\pm{7}^{\prime}$; Cameron et al., 2020),
preventing us from making a positive identification (see Fig.7). An improved
timing position for PSR J1753$-$28 and a measurement of its period derivative
and spindown energy, could test whether this polarized radio source is the
pulsar and whether it is capable of powering the gamma-ray emission. None of
the candidates tn Tables 4 and 5 have _Fermi_ counterparts.

Figure 7: Stokes I (left) and Stokes V (right) cutout images centered on our
circularly polarized pulsar candidate J175306.50$-$285126.2 (red circle). We
show the error circles for the Fermi source 4FGL J1753.2$-$2848 and the known
pulsar PSR J1753$-$28\. A possible association is suggested but not proven
between our polarized radio source, the known pulsar and the gamma-ray source.

Young radio pulsars and MSPs show a scaling of their spindown energy
($\dot{\rm{E}}$) with X-ray flux (e.g., Possenti et al., 2002). To this end we
searched for X-ray counterparts of our polarized radio sources (Tables 3-5) in
the _Chandra_ and _SWIFT_ bulge surveys (Jonker et al., 2011, 2014; Bahramian
et al., 2021). No matches were found at the lower Galactic latitudes where
these X-rays surveys were carried out. There was more success using the
Chandra Source Catalog 2.0 (Evans et al., 2010) and the recently released
6-month sky survey with the eROSITA telescope array in the 0.2-2.3 keV energy
range (Merloni et al., 2024). In the Chandra catalog we found two point
sources within 4′′ of the circularly polarized candidates in Table 3. In the
eRosita catalog we found eight X-ray sources that lie within the joint
radio/X-ray position uncertainties, despite the fact that this initial data
release covers only half of our bulge survey area (i.e., all Galactic
latitudes for longitudes west of Sgr A*). There were no X-ray counterparts to
any of the polarized sources in Tables 4 and 5.

Most of the radio spectra of these X-ray sources are flat or inverted (i.e.,
$\alpha\gtrsim-0.6$) with one exception. J180526.44$-$292954.6 has
$\alpha=-4.31$ and appears to be associated with 2CXO J180526.4-292952. We
discuss this and other sources in more detail in §6.2 and we show that the
majority of the X-ray associations likely originate from active stars and
young stellar objects. All of these gamma-ray and X-ray matches are identified
in the Table 3 as G or X, respectively.

###  6.2 Optical and Infrared Counterparts

Our search for optical and infrared counterparts of the polarized candidates
(Tables 3-5) used the latest Gaia data release (Gaia Collaboration et al.,
2023) and the ALLWISE catalog from the Wide-field Infrared Survey Explorer
(Wright et al., 2010). Astropy code was written in order to make proper motion
corrections of the Gaia stars to the mean epoch of the MeerKAT observations
(2020.3) for all radio candidates in Tables 3-5.

Most isolated pulsars do not have detectable O/IR emission (Antoniadis, 2021).
Thus the detection of optical/IR emission at centimeter wavelengths generally
means that the circularly polarized source is a star, e.g., magnetically
active dwarfs, young stellar object (YSOs) and interacting binaries (Pritchard
et al., 2021). However, caution is warranted since our main goal is
identifying MSP candidates in the bulge and they can have a faint optical/IR
companion. In the compilation of Koljonen & Linares (2023) the majority of
known compact MSP binaries have G-band magnitudes companions fainter than 18th
mag, but there are a small number of systems in the 14-18 mag range. When
possible we use other criteria (e.g., colors) in looking at matches in this
magnitude range.

Wilson & Naylor (2018) point out two additional challenges. The first problem
is false identifications arising due to the high star density and extreme
crowding in the bulge. For each possible association of a star of magnitude G
(or W1 for WISE) we estimate the probability of chance coincidence by using
the number density of stars above this magnitude within a 1-arcmin radius of
the radio source. We flag as suspect any associations with probabilities above
0.5%. In practice, given our astrometric error, this resulted in a magnitude
cutoff of about G$>$15.6 mag for Gaia sources. As a final check we visually
inspect available optical and WISE images of each field to identify directions
with extreme crowding. A second issue raised by Wilson & Naylor (2018) is the
non-identification of the brightest sources (G$<10$ or W1$<$8 mag). This is in
part due to position errors caused by the saturation of the detectors, and
small systematic effects in the proper motion of stars (Cantat-Gaudin &
Brandt, 2021).

None of the 10 (steep-spectrum) linear polarized sources in Table 4 had IR
counterparts or Gaia proper motion corrected matches within the uncertainty of
our radio positions. A similar null result was obtained for the candidates in
Table 5.

The source matching of the ALLWISE catalog with our circularly polarized
candidates in Table 3 gave an unexpected result. Most of the 28 positive
matches came from sources with a spectral index $\alpha>-0.55$. As this is
nearly half our sample, this result points to a real (non-pulsar) source
population. Using the WISE colors we identified that a significant fraction of
these matches were likely from YSOs (Koenig & Leisawitz, 2014). Radio emission
from YSOs has been detected with a range of spectral indices similar to what
is seen here (i.e., $-0.6$ to +1). This emission is thought to originate via
either thermal free-free emission from ionized gas or non-thermal emission
generated by jet shocks. YSOs can be time-variable, with high degrees of
circular polarization, and may have counterparts at X-rays, infrared and sub-
millimeter wavelengths (Feigelson et al., 1998; Forbrich et al., 2006; Feeney-
Johansson et al., 2021). Further support for these YSO identifications came
from SIMBAD and the Gaia/ALLWISE catalog of YSO candidates (Marton et al.,
2019). All of these YSO matches are identified in Table 3 as“YSO”.

Apart from young stellar objects associated with star formation, there is a
heterogeneous collection of radio-emitting stars. For example,
J165648.02$-$230901.8 is 24 Oph. A (HD 152849), a 6th magnitude star of
spectral type A05, and may be a new case of (polarized) radio emission from a
rapidly-rotating A star (White et al., 2021). J172055.04$-$272041.5 is HD
156848B, part of a spectroscopic binary (G=9.1 mag). According to SIMBAD, one
member is a F7/8 subgiant star while the other component being either an F or
G type star, and is listed as a possible ROSAT source by Haakonsen & Rutledge
(2009). 175920.59$-$301548.7 is HD 316903 and is listed in SIMBAD as a
pulsating variable of spectral class B8, making it only the second $\beta$
Cepheid variable for which radio emission has been detected (Tapia et al.,
2014). J181952.24$-$291634.4 is HD 168210, a bright (G=8.7 mag) eclipsing
binary dominated by a G5 main sequence star. It is listed as a possible member
of the nearby $\beta$ Pictoris moving group, and is a likely ROSAT source
(Haakonsen & Rutledge, 2009; Gagné et al., 2018; Couture et al., 2023).

There are at least three nearby M dwarfs in our sample, which appear to be
fully convective according to their G͡aia colors and absolute magnitudes.
J170027.74$-$220742.7 is the high proper motion star, 2MASS
J17002789$-$2207322\. It has the colors of a late M dwarf (Pecaut & Mamajek,
2013)444https://www.pas.rochester.edu/~emamajek/EEM_dwarf_UBVIJHK_colors_Teff.txt
and it is listed as an ultracool dwarf in the planet transit candidate survey
by Sebastian et al. (2021). J185226.04$-$373037.8 is our most polarized source
in the sample. J181345.72$-$331738.6 has been previously cataloged in SIMBAD
as L 489-43, a high proper motion M4.5 dwarf with X-ray emission (Riaz et al.,
2006).

Our most unusual source is J180526.44$-$292954.6, with extreme polarization
(V/I=86.3%) and spectral index $\alpha=-4.31$ values. The radio source is
coincident with HD 317101A, the bright primary (G=9.9 mag) of a nearby (d=33
pc) high proper motion (146.5 mas/yr) visual binary system (Bailer-Jones et
al., 2021). Based on the temperature and colors of these stars, both appear to
be K dwarfs (Pecaut et al., 2012; Stassun et al., 2019). As noted in §6.1, HD
317101A is also a X-ray source. The radio source was observed in several
MeerKAT pointings, three at or within the half-power point of the primary beam
on 2020 June 28 and July 10, and each consisting of 12 five-min scans observed
over 9 hours. Images made from the combination of all 12 scans on each date
vary by $\sim$25% from each other.

With its strong variability, an active phase that persists for weeks or
months, a high degree of polarization and a very steep radio spectrum,
J180526.44$-$292954.6 appears to share many of the characteristics of a group
of GC radio transients (GCRT; Hyman et al., 2005, 2007, 2009; Wang et al.,
2021). However, unlike other GCRTs (e.g., Rickard & Cronyn, 1979; Kaplan et
al., 2008), we appear to have identified a likely multi-wavelength counterpart
and its distance. While time-variable, polarized radio (and X-ray) emission
has been seen toward K dwarfs (Gudel, 1992; Pritchard et al., 2021), the
properties of this source seem extreme and are thus worthy of further study.

###  6.3 Radio Variability

In addition to pulse-to-pulse fluctuations, the flux density of pulsars can
vary significantly on longer timescales due to intrinsic effects (e.g.
nulling, eclipses) and extrinsic effects (e.g., refractive and diffractive
scattering). While variability was used as an early pulsar search strategy
(aka ”scintars”; Rickard & Cronyn, 1979), and it helped to identify the first
millisecond pulsar (Backer et al., 1982), it has only recently been used in
conjunction with other search criteria in imaging surveys (i.e., Wang et al.,
2021; Sett et al., 2023).

Our approach to studying variability was to look in existing archival surveys
for radio flux density measurements of the pulsar candidates in Tables 3-5. We
began first by excluding those 28 candidates previously identified as stars in
§6.2, resulting in 47 candidates. We next looked at existing archival
datasests or surveys which were observed at or near the same frequency of this
MeerKAT bulge dataset (Condon et al., 1998; Murphy et al., 2021; Hale et al.,
2021; Duchesne et al., 2024). Recall that our MeerKAT flux densities in Tables
3-5 were derived from the mosaic images. Although this results in fitted
MeerKAT spectra with very low uncertainties, they are not useful for studying
variability alone since they are time-averages over multiple pointings. We
consider a L-band source to be a variable candidate if a survey flux density
differs from the MeerKAT interpolated value by more than 20% and 3$\sigma$.
This constraint yields 11 candidates with 25 - 60% variations based on
available survey results. The circularly polarized pulsar candidates
J181521.88$-$325302.1 (shown in Fig. 8) and J172329.79$-$282036.1 are notable
examples of variability. The latter is detected at 887 MHz with a flux density
60% and 4$\sigma$ higher than expected from the MeerKAT spectrum. Also of note
is an additional tenth candidate, J180032.14$-$273536.0, which has no survey
detections, but a 5$\sigma$ upper limit at 887 MHz that is 50% lower than the
expected value. We include the spectrum of PSR J1804$-$2858 in Fig. 8 to
illustrate the consistency between the MeerKAT in-band measurements of the
spectral index, extrapolated to archival survey measurements.

A second, less reliable, measure of variability comes from comparing our
results with surveys at different sky frequencies (Intema et al., 2017;
Hurley-Walker et al., 2017, 2019; Lacy et al., 2020). In addition to these
published surveys, we inspected the extensive database from the VLA Low-band
Ionosphere and Transient Experiment (VLITE) which regular monitors the radio
sky at 340 MHz commensal with the regular observing at the VLA (Clarke et al.,
2016; Polisensky et al., 2016). In all these instances we are looking for
significant deviations from the power law fits extrapolated outside the
MeerKAT band. Such deviations are less robust reliable indicators of
variability since they could originate from real deviations in the pulsar’s
spectrum from a simple power-law.

We list variable radio sources in column six of Table 6. Radio sources with
archival flux densities measured near or within the MeerKAT L band are either
labeled Y1 or N, indicating variable or not-variable, respectively. Note that
the variability timescale is poorly constrained as the epochs vary from months
to decades. Variability outside of the MeerKAT frequency range (i.e.
significant deviations from power-law extrapolations) is labeled as Y2.
Sources without archival radio observations are left blank. We will discuss
variability and other properties in Table 6 in more detail in §7.

Figure 8: Top: Spectrum of pulsar J1804-2858. Plotted in purple are peak
intensities from the TGSS (150 MHz, Intema et al., 2017), VLITE (340 MHz,
Clarke et al., 2016), RACS-low (888 MHz, Hale et al., 2021), and RACS-mid
(1368 MHz, Duchesne et al., 2023). Blue, red, and green points show flux
measurements from the MeerKAT half-band, quarter-band, and subband images. The
corresponding in-band spectral fits (dashed lines) show excellent agreement
both in-band and with the other radio catalogs. Bottom: Spectrum of pulsar
candidate J181521.88-325302.1 exhibiting variability. Purple catalog values
are from RACS-low, RACS-mid, NVSS (1.4 GHz, Condon et al., 1998), and the
first two VLASS epochs (3 GHz, Lacy et al., 2020). Table 6: Pulsar Candidate
Properties

J2000 Name | Compact | Steep | C Pol. | L Pol. | Variable | HE
---|---|---|---|---|---|---
171334.15$-$241044.5 | Y | N | Y | N | Y1 |
172018.40$-$265207.8 | Y | Y | Y | N |  | N
172329.79$-$282036.1 | Y | Y | Y | N | Y1 | N
172752.07$-$272724.6 | Y | Y | Y | N |  | N
172820.26$-$260816.6 | Y | Y | Y | N | N |
172931.96$-$273137.8 | Y | N | Y | N |  | N
173250.03$-$235414.4 | Y | N | Y | N | Y1 |
173757.25$-$273305.3 | Y | N | Y | N | N |
174006.78$-$280533.9 | Y | N | Y | N | N |
174408.71$-$242453.4 | Y | Y | Y | Y | Y1 |
174543.03$-$265853.9 | Y | N | Y | N | Y2 | Y
174718.05$-$330917.4 | Y | Y | Y | N | N | N
175115.97$-$294352.0 | Y | Y | Y | N | N |
175229.06$-$284905.6 | Y | N | Y | N | N |
175306.42$-$293000.8 | Y | Y | Y | N | N |
175306.50$-$285126.2 | Y | N | Y | N |  | Ya
175339.01$-$333128.4 | Y | N | Y | N | N | N
175920.04$-$282956.6 | Y | Y | Y | N | N |
180012.33$-$274432.5 | Y | N | Y | N |  |
180032.14$-$273536.0 | Y | Y | Y | N | Y1 |
180403.38$-$333153.0 | N | N | Y | N | Y1 | Y
180631.55$-$292137.0 | Y | N | Y | N |  |
181137.21$-$320650.9 | Y | N | Y | N |  |
181521.88$-$325302.1 | N | N | Y | N | Y1 | N
181634.34$-$323412.4 | Y | N | Y | N |  |
181831.06$-$325418.2 | Y | N | Y | N |  |
183449.11$-$350525.8 | N | N | Y | N | N | N
183501.56$-$341820.1 | Y | N | Y | N | Y2 |
184154.78$-$360749.2 | N | Y | Y | N |  | N
185019.66$-$362912.8 | Y | N | Y | N | Y1 | N
190625.66$-$370349.5 | N | N | Y | N |  |
190738.78$-$370855.9 | Y | N | Y | N | Y2 |
170154.67$-$225008.3 | Y | Y | N | Y |  | N
171837.15$-$233510.5 | N | Y | N | Y | N |
172626.80$-$304809.2 | Y | Y | N | Y | N | N
173121.50$-$250235.7 | Y | Y | N | Y | Y1 |
174408.71$-$242453.4 | Y | Y | Y | Y | Y1 |
181822.84$-$324416.0 | Y | Y | N | Y |  |
182146.77$-$324727.8 | N | Y | N | Y |  |
182417.96$-$323805.4 | Y | Y | Y | Y |  |
182731.72$-$325238.9 | Y | Y | N | Y |  |
183736.28$-$335013.8 | Y | Y | N | Y |  |
172734.51$-$260957.1 | Y | Y | Y | N |  |
173114.95$-$273532.4 | Y | Y | Y | N |  | N
180221.53$-$325438.0 | Y | Y | Y | N | Y1 | N
182417.96$-$323805.4 | Y | Y | Y | Y |  |
185120.86$-$354619.5 | Y | N | Y | N |  |

Note. — a. Possibly PSR J1753$-$28 (see §6.1)

###  6.4 Pulsation Searches

While a case can be made that a particular source is a compelling pulsar
candidate using imaging and spectra at X-ray, optical and radio wavelengths
(Karpova et al., 2023; Zic et al., 2024), the final arbitror is the detection
of pulsations. As a pilot project we observed three of the circularly-
polarized candidates identified in the G0.0+5.5 mosaic pointing
(J172018.40$-$265207.8, J172752.07$-$272724.6 and J172820.26$-$260816.6),
using the Ultra-Wide Low-band (UWL; 704-4032 MHz) receiver of the Parkes 64-m
radio telescope (Murriyang; Hobbs et al., 2020). The properties of these
sources are listed in Table 3. For each source, we conducted observations
using the UWL for 72 minutes, with a time resolution of 64 microseconds and a
frequency resolution of 0.250 MHz, corresponding to 13,312 frequency channels
across the 3328 MHz UWL bandwidth. Each observation generated approximately
200 GB of data. We conducted a pulsar search in three different ways using a
GPU-accelerated search code, PEASOUP (Morello et al., 2019):

  1. 1.

The maximum line-of-sight dispersion measure (DM) for these sources, based on
different electron density models, ranges between 250-400 pc cm-3 (Cordes &
Lazio, 2002; Yao et al., 2017). However, we searched over a broader DM range
from 2 to 1500 pc cm-3. We first divided each UWL observation into four
segments of 832 MHz bandwidth each, namely 704-1536 MHz (4345 trial DMs),
1536-2368 MHz (2809 trial DMs), 2368-3200 MHz (1570 trial DMs), and 3200-4032
MHz (853 trial DMs). We then conducted a standard FFT search separately for
each segment. Candidates with a spectral SNR above 6 were folded using dspsr
and diagnostic plots were obtained using PSRCHIVE’s tool pdmp (van Straten &
Bailes, 2011; van Straten et al., 2012). After folding, candidates with a
folded SNR above 8.5 were selected for visual inspection. However, we did not
find any significant candidate resembling a real pulsar.

  2. 2.

We also conducted an acceleration search for the same dataset. The
acceleration range searched was $-$30 ms-2 to +30 ms-2 (which is consistent
with the maximum acceleration shown by the majority of the known binary
pulsars during 1-hr integration), and the DM range was 2-500 pc cm-3. We
folded all candidates with a spectral S/N above 7 and visually inspected each
with folded S/N above 8.5, but this search also did not yield any significant
candidates.

  3. 3.

Furthermore, we divided the UWL observations into smaller segments, each with
a bandwidth of 416 MHz, and conducted an acceleration search similar to that
mentioned in (2). This search also did not detect any candidates.

##  7 Results

###  7.1 Pulsar Candidates

We have identified a sample of 75 polarized candidates in a MeerKAT imaging
survey of the bulge of our Galaxy. A total of 60 candidates were found based
on their circular polarization (§5.2), ten were found from their linear
polarization properties (§5.3) and five were steep-spectrum polarized sources,
detected only in the lower half of the MeerKAT receivers (§5.4). We searched
for multi-wavelength counterparts to each of these candidates at gamma- and
X-ray energies (§6.1), plus optical and infrared wavelengths (§6.2). Based on
optical/infrared identifications we found that 28 of the circular polarized
sources were bright stars or young stellar objects. Removing these, our final
list is shown in the Boolean Table 6. After accounting for duplicates which
were detected both in linear and circular polarization, we have a total of 45
potential pulsar candidates taken from Tables 3-5.

Table 6 lists several source properties common to previous image-based
searches for pulsars: compactness, spectral steepness, circular polarization,
linear polarization, variability, and high energy counterparts. Measures that
define how point-like a radio source is, such as the ratio of the total flux
over the peak flux density (e.g., Frail et al., 2018) or the compactness
ratio, as defined in §4 (Intema et al., 2017), have proven useful in
identifying pulsar candidates. Despite being unresolved in interferometric
images, de Gasperin et al. (2018) noted that pulsars may still have
compactness less than unity (but usually $>0.9$). This occurs if there are
substantial flux density changes within an integration period (scintillation
or pulse-to-pulse variations), or the pulsar is located near extended emission
(e.g., pulsar wind nebulae). In all cases, even the non-compact sources in
Table 6 have a total flux over the peak flux density ratio $R<$1.5, i.e., they
meet the compactness criteria used in Hyman et al. (2019) and elsewhere. For
spectral steepness we have assigned “Y” to those with $\alpha<-1.5$ (see
§5.3), the circular and linear polarization criteria is defined in §5.2-5.4
and variability is defined in §6.3. Finally, we identify all candidates with
high energy counterparts (§6.1). Unlike the eRosita catalog, which covers the
entire 4th Galactic quadrant, sky coverage of the _Chandra_ catalog is patchy
enough that sources in the first Galactic quadrant often lack sufficient data
to rule out X-ray emission.

Of the 45 candidates, there are two sources (J174408.71$-$242453.4 and
J182417.96$-$323805.4) that are notable for being compact, steep spectrum and
are detected with both strong circular and linear polarization ($>$10%).
Pulsars are the only known compact source population with steep radio spectra
to exhibit strong polarization in both forms. These would be high priority
candidates for follow-up pulsation searches. Approximately half of our
candidates (22) in Table 6 are compact, steep spectrum and have linear or
circular polarization. With a few exceptions, which we discuss below, the bulk
of these sources also appear to be attractive candidates for pulsation follow-
up.

Figure 9: (Left) Circular polarization and spectral properties of known
pulsars (blue circles) and stars (green squares) identified in Tables 2 and 3.
Grey points are taken from the compilation of circular polarization and
spectral index values of Johnston & Kerr (2018) and Jankowski et al. (2018).
(Right) Polarization (circular and linear) versus Spectral Index for pulsar
candidates (red) identified in Table 6. Solid circle (open circle) shapes are
candidates that lie outside (inside) the known pulsar distribution. The light
grey points are the same as the adjacent plot.

Five polarized sources (including J174408.71$-$242453.4) are compact, steep
spectrum and exhibit strong in-band variability (Y1) (see §6.3). These warrant
special attention in pulsation follow-up. The remaining variable sources are
flat spectrum and are likely stellar sources. The three high energy
counterpart associations are less instructive than the other indicators. In
§6.1 we suggest that one source (J175306$-$285126.2) may be a known pulsar,
while the remaining two have flat spectral indices similar to the YSOs
identified in §6.2.

Despite our best efforts at using these multiple selection criteria to select
pulsars, there likely remain other source populations among our candidates. To
illustrate this, we plot the spectral index versus the absolute value of the
circular polarization in Fig. 9. On the left are the known pulsars (blue) from
Table 2 together with the stars (green) identified from §6.2. The light grey
points are circular polarization and spectral index values taken from the
compilations of Johnston & Kerr (2018) and Jankowski et al. (2018),
respectively. The known bulge pulsars trace the spectral index and circular
polarization of this larger pulsar sample, except that the larger sample
extends to less steep spectral indices and larger polarization ($\leq 40$%).
It is clear that the majority of stars occupy different phase space in this
diagram. They are distributed over nearly the full range of circular
polarization, and most have distinctively flat or inverted spectral indices.

In the right hand side of Fig. 9 we plot the remaining 45 candidates (red)
from Table 6. Compared to the larger sample of pulsars (light grey), there is
an excess of flat-spectrum candidates in the 1-2% range and a long tail of
strongly polarized sources ($>50$%). We discussed the excess of bright sources
in the 1-2% range in §5.2. With the exception of J180221.53$-$325438.0 with
$\alpha=-1.61$, we suspect the remaining are extragalactic sources with weak
circular polarization or beam squint artifacts.

The long tail of strongly polarized sources ($>40$%) in Fig. 9 is likely real
and not a selection effect or instrumental artifact. Unless there is a pulsar
emission geometry that results in a high percentage polarization while making
pulsations difficult to detect (i.e. aligned rotators), the bulk of this
sample is likely stellar in origin. Many radio stars at this frequency exhibit
high fractional circular polarization (Pritchard et al., 2021, 2024), with
properties similar to the stars identified in Table 3 and Fig. 9. What is more
rare are stellar radio stars whose spectral indices are comparable to those of
pulsars and suggests a coherent process such as electron cyclotron maser
emission (Güdel, 2002). Improved astrometry of these steep spectrum, highly
polarized candidates will help in identifying multi-wavelength counterparts to
show if they are similar to the peculiar J180526.44$-$292954.6 (§6.2), or
remain interesting pulsar candidates. If we confine the source selection to
just those candidates with fractional polarization between 1-45%, and a
negative spectral index, consistent with known pulsar properties, we are left
with 30 strong pulsar candidates. The J2000 names of these candidates are
highlighted in italics in Table 6.

To summarize, of the 45 candidates in Table 6 that were initially identified
on the basis of multiple selection criteria (compactness, spectral index,
polarization, variability and multi-wavelength counterparts), we find 30 whose
properties closely follow those of the known pulsar population, and are thus
good candidates for pulsation follow-up.

###  7.2 The Missing Pulsations

There are 81 pulsars that have been previously discovered toward these bulge
mosaic fields (§5.1). In this work we have identified 30 additional pulsar
candidates. The immediate question that needs to be answered is why have
previous pulsation searches, including §6.4, not detected pulsations toward
these sources? The myriad of reasons for non-detection of pulsations have been
previously discussed in the literature and broadly fall into four categories:
instrumental, algorithmic, environmental and intrinsic. The challenges and
strategies for finding pulsations toward the bulge and the GC have been
discussed extensively (Macquart & Kanekar, 2015; Calore et al., 2016; Hyman et
al., 2019, 2021).

Instrumental sensitivity appears to be part of the explanation. The deepest
pulsation surveys at 1.4 GHz that cover the MeerKAT bulge mosaic images are
the Parkes High Time Resolution Universe survey (HTRU; Keith et al., 2010) and
the Parkes Multi-beam Pulsar Survey (PMPS; Manchester et al., 2001). The
majority of the known 81 pulsars were discovered by the PMPS and HTRU. Thanks
to improvements in search algorithms, the re-processing of these datasets has
lead to additional new pulsar discoveries close to the continuum sensitivity
limits (Cameron et al., 2020; Sengar et al., 2023)

The PMPS surveyed $|{b}|<5^{\circ}$, while HTRU had three parts; HTRU-low with
$|{b}|<3.5^{\circ}$, HTRU-mid with $|{b}|<15^{\circ}$ and HTRU-high for all
other Galactic latitudes. The integration time at the low, mid and high
latitudes was 4300 s (twice PMPS), 540 s and 270 s, respectively. HTRU had
smaller channel bandwidths than PMPS, making it less limited by dispersion and
scattering, thus increasing its sensitivity to distant MSPs. The mean limiting
flux density of the HTRU has a strong latitude dependence in part because of
the decreasing integration times from low, to mid to high, but also because of
the variation in sky temperature (Calabretta et al., 2014; Remazeilles et al.,
2015). Taken together, we estimate that the HTRU-high and HTRU-mid was 3.5x
and 2.6x less sensitive than the HTRU-low.

In contrast, the rms noise for the MeerKAT bulge mosaic images do not show a
strong Galactic latitude dependence. The noise is relatively constant with a
mean of 14 $\mu$Jy bm-1 (see Table 1), varying by $\sim$30% owing to changes
in Tsky and varying degrees of RFI. Using the radiometer equation and the
instrumental parameters of the HTRU survey for the outer beams of the 13-beam
receiver (Keith et al., 2010; Cameron et al., 2020) we expect that the
limiting flux density of the MeerKat polarized pulsar candidates to be very
similar to pulsars previously seen by HTRU-low. This indeed appears to be the
case. We find that the limiting flux density for the both the HTRU detections
and the circularly polarized candidates in Tables 3 and 5 are both
approximately 0.1 mJy. Since our pulsar candidates are distributed over
$|{{b}|}<20^{\circ}$ (see Fig. 10), the sharp decrease in the HTRU sensitivity
with latitude likely explains why the fainter pulsar candidates were missed in
previous pulsation searches.

Figure 10: Galactic distribution of the known pulsars in the mosaic fields
(light grey) versus our final pulsar candidates.

Sensitivity cannot explain why the HTRU previously did not detect pulsations
from the brighter candidates. such as J174408.71$-$242453.4; a 1.2 mJy source
that is compact, steep spectrum and has both significant linear and circular
polarization. The sky distribution of our sample, compared to existing
pulsation surveys, offers some clues (Fig. 10). There are two groupings of
candidates in the mosaic fields; a group of seven distributed along a narrow
band of longitude primarily in the G0.0$-8.5$ mosaic, and a less well-defined
group near b=5∘. While this clustering could be random, we note that they
occur in the direction of “voids” wherein there are no known pulsars. We
suggest that anomalous scattering might be responsible for one or more of
these voids. An excellent case in point is the recent discovery of the highly
scattered pulsar PSR J1032$-$5804 from a imaging survey of polarized sources
(Wang et al., 2024).

If sensitivity and interstellar scattering are the main culprits then deeper
searches and/or searches above L band should be successful in detecting
pulsations. Neither of these appears to explain the lack of pulsations from
the three candidates observed in §6.4. The search of these mid-latitude
candidates was conducted with the Parkes telescope using the same integration
time as HTRU-low, over a much wider frequency range (704-4032 MHz), and using
state-of-the-art search algorithms. Using the instrumental parameters from
§6.4 and Tsky at the source positions, we used the radiometer equation to
calculate the rms noise555https://www.parkes.atnf.csiro.au/cgi-
bin/utilities/pks_sens.cgi. For example, at 1400 MHz, Tsky=6.7 K, and a
bandwidth of 1024 MHz, and a S/N threshold of 8.5, the sensitivity is 0.1
mJy$\times\sqrt{w_{t}/({\rm{P}}-w_{t})}$, where P is the pulsar period and
$w_{t}$ is the quadrature sum of the intrinsic pulsar width, temporal
scattering, dispersive smearing and the sampler timescale (Sengar et al.,
2023). We then modeled an isolated MSP with P$\sim$5 ms with a 5-10% pulse
width at a distance of 8300 pc, estimating its dispersion measure and the
degree of scattering using two Galactic electron density models (Cordes &
Lazio, 2002; Yao et al., 2017). We find that pulsations should have been
expected for this putative bulge MSP at high significance over much of the
frequency range of the UWL receiver. Perhaps some of the candidates are rare
and more exotic systems such as tight binaries or pulsars with broad emission
profiles (Navarro et al., 1995; Kaplan et al., 2019), or, as has been
suggested, represent a new galactic population with properties like pulsars
but lacking pulsations (Hyman et al., 2021).

##  8 Discussion and Conclusions

We have carried out an analysis of a sensitive MeerKAT survey of the Galactic
bulge and GC region at L band (856-1712 MHz) in all four Stokes I, Q, U and V
images. The survey covers 173 deg2 in 20 partially overlapping mosaic
pointings, each 3.125∘×3.125∘. Our primary science driver has been to identify
pulsar candidates, with a long-term goal of explaining the origin of the
mysterious gamma-ray emission identified by the _Fermi_ Gamma-Ray Telescope.

Previous image-based candidate searches have been plagued by contaminants
(variables, extragalactic sources, etc.) (e.g., De Breuck et al., 2000; Kaplan
et al., 2000; de Gasperin et al., 2018; Frail et al., 2018; Maan et al., 2018;
Bruzewski et al., 2023). This current work is a substantial improvement over
past image-based pulsar searches in several dimensions: sensitivity, improved
angular resolution/astrometry, polarization, in-band spectra, and the use of
multiple selection criteria. The rms noise levels of these mosaic images is
12-17 $\mu$Jy ba-1 (see Table 1). When past continuum surveys such as the NRAO
VLA Sky Survey (NVSS; Condon et al., 1998), the TIFR GMRT Sky Survey (TGSS;
Intema et al., 2017), and the Galactic and Extragalactic All-sky Murchison
Widefield Array (MWA) survey (GLEAM; Hurley-Walker et al., 2017) are scaled to
L band, using a mean pulsar spectral index, this MeerKAT bulge survey is
nearly a two orders of magnitude increase in sensitivity. Using the MeerKAT
Absorption Line Survey (MALS; Deka et al., 2024), Himes et al. (2024, in
prep.) showed that these earlier surveys were sensitive to between 7-21% of
the known pulsar population, while for MALS the fraction was 80%. The same
conclusion applies to this MeerKAT bulge survey since it is approximately a
factor of two deeper than MALS. More importantly, for the first time the
continuum sensitivity has reached a level that is capable at detecting the
putative population of MSPs in the Galactic bulge, which can be responsible
for the Fermi excess and whose properties have been described by Calore et al.
(2016).

The next generation of all-sky surveys capable of imaging the GC and bulge
will have sensitivities comparable to MeerKAT. One area that MeerKAT retains
an advantage over ASKAP (Murphy et al., 2021; Wang et al., 2022b) and MWA
(Hurley-Walker et al., 2022) is in angular resolution. Higher resolution can
be useful for identifying false positives such as extended, steep-spectrum
high redshift galaxies (Miley & De Breuck, 2008), but for a crowded region
such as the bulge, accurate astrometry is essential to identify multi-
wavelength counterparts (§6).

Another improved capability of these next generation facilities is the ability
to provide full Stokes images. At these sensitivity levels, just using
criteria such as compactness and spectral index (e.g., Kaplan et al., 2000;
Maan et al., 2018; de Gasperin et al., 2018) produces too many candidates. For
example, if we select all compact and steep spectral index sources in the
G0.0+5.5 mosaic using the criteria in §5.3 we find nearly 900 candidates, or
nearly 4% of the cataloged radio sources for a source density of 90 deg-2.
Including a polarization criteria to this sample (§5.2) sharply reduces this
source density. For this bulge survey region, if we include the known pulsars
in Table 2 and the circularly polarized candidates in Tables 3 and 5, the
source density drops to a manageable 0.5 deg-2.

The large fractional bandwidths allow for the measurement of the spectral
index at one time, reducing the rate of false positives. Past searches
determined the spectral index from two or more surveys at different
frequencies but often taken at very different epochs (e.g., Frail et al.,
2016; McCarver et al., 2023). de Gasperin et al. (2018) argued that the tail
of the spectral index distribution at the steep end could be contaminated by
variable extragalactic sources. To our knowledge, this is the first large-
scale study to identify pulsar candidates using both spectral indices and
polarization. As we showed in §7.1, the polarization/spectral index space
(Fig. 9) can be a powerful tool for distinguishing different source
populations. As an added benefit this method should allow us to identify
promising pulsar candidates without restricting the search to the steepest
spectral indices. Finally, we note that this work has followed the recent
trend of using multiple selection criteria (variability, compactness, steep
spectrum, polarization and multi-wavelength counterparts) to bolster claims of
pulsar candidates (Sett et al., 2023).

After applying these selection criteria, we identify 45 pulsar candidates
(§7.1). We noted that there likely remained some false positives in the
sample, owing in part to instrumental artifacts at low fractional polarization
(1-2%) and with the difficulty in identifying optical/infrared counterparts in
these crowded GC fields with our current astrometric accuracy (§4.1). Focusing
on just those which have observational properties similar to the known pulsars
we find 30 strong candidates for pulsation follow-up. We argue that the
absence of pulsations from these candidates from previous surveys is mainly
due to a combination of low sensitivity and interstellar scattering, but other
factors must be involved.

The challenges facing pulsation searches in the Galactic bulge is demonstrated
by the recent discovery of the first MSP close to the Galactic center. X-ray
and radio images showed a compact source embedded within the non-thermal
filament G359.1$-$0.2, but it took at targeted search to find PSR J1744$-$2946
with a period P=8.4 ms (Lower et al., 2024). The pulsar was bright at 2.1 GHz
(0.43 mJy) but faint at 1.4 GHz ($<$0.1 mJy), owing to a spectral turnover,
possibly due to free-free absorption along the line of sight. This explains
why it was missed by the HTRU survey and highlights the importance of wide-
bandwidth searches. Its detection was also aided by a temporal scattering that
was 50% less than model predictions (Cordes & Lazio, 2002; Yao et al., 2017).
If PSR J1744$-$2946 is located within the Galactic bulge, it may lie along the
high-luminosity tail of the putative bulge pulsar population discussed by
Calore et al. (2016). This conclusion also applies to the pulsar candidates
identified here because our polarization criteria limits detection to
$\gtrsim$0.1 mJy. In order to exploit the full power of these sensitive Stokes
I MeerKAT observations in image-based pulsar searches, other multi-wavelength
approaches based of cross-correlation techniques may be needed (Berteaud et
al., 2023, 2024).

The MeerKAT telescope is operated by the South African Radio Astronomy
Observatory, which is a facility of the National Research Foundation, an
agency of the Department of Science and Innovation. Murriyang, 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. The National Radio Astronomy Observatory is a facility of
the National Science Foundation operated under cooperative agreement by
Associated Universities, Inc. 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. RS and DK are supported by
NSF grant AST-1816904. Parts of the results in this work make use of the
colormaps in the CMasher package (van der Velden, 2020). Basic research at NRL
is funded by 6.1 Base programs. This project was supported in part by an
appointment to the NRC Research Associateship Program at the US Naval Research
Laboratory, administered by the Fellowships Office of the National Academies
of Sciences, Engineering, and Medicine.

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