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REVIEW 3 major objections 5 minor 42 references

Low radio frequency detections of known pulsars and identification of new candidates with GLEAM-X: GP

T0 review · 3 major / 5 minor · reviewed 2026-08-05 · deepseek-v4-flash

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Pith's one-line read A low-frequency continuum survey detects 193 known pulsars, 106 of them for the first time below 400 MHz, by matching compact radio sources to the ATNF pulsar catalogue and Fermi-LAT unassociated gamma-ray sources.

desk verdict Useful low-frequency pulsar catalogue from GLEAM-X; the 'first detections' count is softer than it looks but the data are solid. read the letter →

arxiv 2509.02919 v1 pith:44DI7BDW submitted 2025-09-03 astro-ph.GA astro-ph.HE

Silvia Mantovanini , N. Hurley-Walker , G. Anderson , K. Ross , S. W. Duchesne , T. J. Galvin This is my paper · ORCID
classification astro-ph.GAastro-ph.HE
keywords pulsarsradiocontinuumsurveyslow-frequencyGLEAM-XspectralenergydistributionsFermi-LATunassociatedsourcespulsarcandidatesGalacticplane
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper uses the GLEAM-X Galactic Plane survey's 72–231 MHz images to find radio counterparts of known pulsars without detecting pulses. It reports 193 known pulsars with measured flux densities across 20 sub-bands, of which 106 are labelled first detections below 400 MHz. The new low-frequency points change the fitted spectra of most sources: only about 23 percent of the matched pulsars are well described by a simple power law, the rest showing turnovers or cutoffs. The same radio images are cross-matched with unassociated Fermi-LAT gamma-ray sources, filtered for pulsar-like curvature, photon index, and variability, yielding 106 compact radio sources as pulsar candidates with arcsecond positions. If the detections and associations are genuine, the paper expands the low-frequency pulsar census and gives follow-up pulsation searches precise targets.

What carries the argument

The mechanism is image-domain pulsar detection: instead of searching for periodic pulses, the survey finds pulsars as unresolved, steep-spectrum radio sources in deep continuum images, taking advantage of long integrations that average over pulse phase and scintillation. The data release is the GLEAM-X Galactic Plane survey, 72–231 MHz in 20 sub-bands with ~3-arcsecond positions and a compact-source catalogue of 98,207 elements (compactness defined by the Meyers et al. 2017 criterion). For spectra, the pulsar_spectra Bayesian fitting package fits power-law, broken-power-law, low-frequency-turnover, high-frequency-cutoff, and double-turnover models, with AIC model selection. For candidates, t

What would settle it

Search the full ATNF catalogue and the pulsar_spectra compilation for any prior sub-400 MHz flux measurement for the 106 pulsars claimed as first detections; one prior published flux point would invalidate the count. Independently, take the 193 matched sources and estimate how many fall inside the ~4% random-match probability near the Galactic plane, where the source density is higher; if the actual overlap rate significantly exceeds the expected 7, some SEDs will be background contaminants.

Watch

Extended reading notes

Core claim

The central claim is that continuum imaging at 72–231 MHz can recover a substantial fraction of the known Galactic-plane pulsar population: 193 pulsars in the GLEAM-X: GP data release have compact radio counterparts, and 106 of these are argued to be first detections below 400 MHz, with 36 first detected below 300 MHz. For each source the authors fit five spectral models to the 20-sub-band flux densities together with prior literature, selecting the best by the Akaike information criterion. Separately, they claim that cross-matching compact radio sources with unassociated 4FGL-DR4 sources, after cuts on gamma-ray spectral curvature, photon index (1.8–3.0), and variability, yields 106 radio a

Load-bearing premise

The headline count of 106 first detections below 400 MHz assumes that the ATNF catalogue and pulsar_spectra literature compilation contain every prior low-frequency measurement for these pulsars; the paper itself notes the compilation is not fully current.

Editorial extensions

If this is right

  • The 193 measured spectral energy distributions substantially extend the low-frequency sample of pulsar spectra, and the fits show that a simple power law is the minority case for these sources.
  • The 106 Fermi-associated radio positions narrow blind searches from ~0.5-degree error ellipses to ~3-arcsecond targets, increasing the sensitivity of follow-up pulsation searches.
  • The image-averaged flux densities give a stable estimate of average pulsar emission, largely bypassing scintillation variability that complicates low-frequency pulse measurements.
  • The detected sample is biased toward high-DM, high-fractional-width pulsars, so the technique complements periodicity searches and can probe pulsars that are scattered or dispersed beyond the reach of time-domain searches.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • Extension: the 106 Fermi candidates could be ranked for follow-up by predicting their pulse-detection sensitivity from the measured 200-MHz flux densities and fitted spectral index; the paper stops at identification.
  • Extension: if a handful of the 106 candidates are confirmed, the efficiency of gamma-ray-selected, image-localised pulsar searches would likely exceed blind periodicity searches in the same field, as earlier Fermi-guided campaigns suggested.
  • Extension: applying the same cross-match method to the full GLEAM-X sky or to future low-frequency surveys could test whether the simple-power-law fraction seen here is a selection effect of image sensitivity or a real population property.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 5 minor

Summary. This paper cross-matches the GLEAM-X: GP compact source catalogue with the ATNF pulsar catalogue v2.6.2 over the Galactic plane (|b|<11 deg), reporting 72-231 MHz flux densities for 193 known pulsars and claiming that 106 of these are first detections below 400 MHz. It also filters unassociated Fermi 4FGL-DR4 sources by pulsar-like gamma-ray spectral and variability properties, cross-matches the survivors against GLEAM-X compact sources, and identifies 106 radio counterparts to 73 gamma-ray sources as promising pulsar candidates. Spectral energy distributions are modelled with the pulsar_spectra package, and the detected pulsar sample is compared with the known population in period, flux density, and dispersion measure.

Significance. If the results hold, the paper delivers a valuable new low-frequency flux density catalogue for 193 known pulsars, nearly doubling (or at least substantially expanding) the number of pulsars with sub-400 MHz continuum measurements in the GLEAM-X footprint, and provides a prioritised list of 106 radio counterparts for follow-up pulsation searches in Fermi error ellipses. Strengths include the clear description of the cross-matching and spectral-fitting procedures, the transparency about the ~4% random-match probability for the pulsar sample (corresponding to ~7 expected false associations), and the commitment to release machine-readable catalogues and SED plots. The Fermi candidate selection is more speculative, but the authors frame it appropriately as a list for follow-up rather than as confirmed detections.

major comments (3)
  1. [Section 5.1 and Abstract] The claim that 106 pulsars are detected below 400 MHz for the first time is a headline result, but the verification is not described. The paper does not state the criterion used to define a 'first detection' or describe a systematic literature search beyond ATNF v2.6.2 and the pulsar_spectra compilation. Since Section 3.2 notes that pulsar_spectra relies on an older ATNF version and does not recognise 8 of the matched sources, the compilation is demonstrably incomplete. Any of the 106 could have prior sub-400 MHz flux density measurements (e.g., from LOFAR, GMRT, MWA, or GLEAM) not captured by these sources. Please either (i) perform a systematic per-pulsar literature check for prior sub-400 MHz measurements, or (ii) rephrase the claim as 'first detection in the GLEAM-X: GP survey' / 'no previous measurement in ATNF v2.6.2 or pulsar_spectra', and propagate this caveat through the abstrac
  2. [Sections 3.1 and 5.1] The reported number of detected pulsars is internally inconsistent. Section 3.1 gives 426 associations for 202 distinct pulsars, excludes seven with >5 matches, and leaves two pulsars with 2-4 matches in the analysis, which implies 195 distinct pulsars. Section 5.1 first states 'the 193 known pulsars detected', then discusses J1708-52 and J1534-46 as the two multiple-match pulsars, and concludes 'The remaining 193 pulsars each had a single, unambiguous match.' This is contradictory. Please clarify the exact sample size and use the same number in the abstract, Section 5.1, and conclusions.
  3. [Sections 4 and 5.2] The Fermi candidate list of 106 radio associations (73 unique gamma-ray sources) is a central deliverable, but no chance-coincidence probability is estimated. Given that the 4FGL error ellipses can have semi-major axes up to 0.5 degrees and the GLEAM-X source density near the Galactic plane is high, the number of spurious associations may be substantial. The authors note that 'many of the matches... may be chance coincidences' but do not quantify this. A Monte Carlo simulation or density-based estimate of the expected number of false associations would allow the reader to assess the purity of the candidate list. Without it, the yield of 106 candidates is difficult to interpret.
minor comments (5)
  1. [Section 3.1] Typo: 'ANTF catalogue' should be 'ATNF catalogue'.
  2. [Figure 7] The text refers to 'the top pie chart' and 'the bottom pie chart', but the figure contains four labelled panels (a)-(d). Please reference the specific panels explicitly.
  3. [Table 1] The column header 'E 100× 10−12' is unclear. Define the energy-flux column explicitly, e.g., 'E (100 MeV) [10^-12 erg cm^-2 s^-1]'.
  4. [Section 1] 'Stokes i images' should be 'Stokes I images' (capital I).
  5. [Throughout] The paper mentions that SEDs are available online, but listing a short table of the 106 claimed first detections in the printed text would improve readability and allow readers to quickly assess the headline claim.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: observational catalogue paper with direct measurements and externally benchmarked cross-matches.

full rationale

This is an observational catalogue study, not a derivation or predictive modelling paper. The central products are (1) cross-matches between known ATNF pulsars and GLEAM-X: GP compact sources, (2) measured 72–231 MHz flux densities, and (3) SED fits to those data plus literature measurements. No quantity is constructed from fitted parameters and then presented as an independent prediction: the flux densities are direct measurements from the survey images, and the spectral model parameters are outputs of an MCMC fit to data that include external literature measurements. The Fermi cross-match candidate list is likewise produced by applying fixed, independently established gamma-ray selection cuts (curvature significance, photon index, variability index) and positional matching, not by tuning a model to reproduce the final candidate list. The paper's reliance on the authors' own GLEAM-X: GP data release and on earlier GLEAM-X survey papers is data provenance rather than a load-bearing self-citation: the survey catalogue is a separate, publicly released data product, and the current paper does not cite its own conclusions as evidence. The 'first detection below 400 MHz' claim is a statement about absence from the ATNF v2.6.2 catalogue and the pulsar_spectra literature compilation; this is an external completeness assumption that could be incorrect, but it is not a circular derivation. The paper even acknowledges the incompleteness of pulsar_spectra for eight pulsars, showing that the claim is not definitionally forced by the analysis. No equation or fitted parameter is reused as an input to produce the claimed result. Therefore no material circularity is present.

Assumptions & free parameters 3 free parameters · 5 assumptions · 0 invented entities

This paper does not derive a result from axioms; it produces measurement catalogues. The central numbers depend on (a) the completeness of public catalogues (ATNF, Fermi 4FGL-DR4, GLEAM-X: GP), (b) hand-chosen selection thresholds for the gamma-ray filter and match-multiplicity caps, and (c) the assumption that standard spectral models describe pulsar radio emission. No new physical entities are introduced.

free parameters (3)
  • Fermi pulsar-like filtering thresholds = log curvature significance 0-2.0; photon index 1.8-3.0; log variability index 0.4-1.7
    Hand-set parameter ranges applied to the 4FGL-DR4 unassociated sample (Section 4.1). They directly determine which gamma-ray sources are retained and hence the final count of 106 candidate associations.
  • Gamma-ray match multiplicity cap = exclude 4FGL sources with >5 radio matches
    Hand-chosen cap to reject unreliable localisations in crowded fields (Section 4.1). Removing this cap or changing it would change the candidate sample.
  • Pulsar match multiplicity cap = pulsars with >5 GLEAM-X counterparts excluded; two with 2-4 retained
    Hand-chosen exclusion criterion in Section 3.1 that reduces the sample from 202 distinct pulsars to 195 (193 single plus 2 multiple), directly shaping the reported counts.
assumptions (5)
  • domain assumption ATNF catalogue positions and uncertainties are correct.
    The cross-match in Section 3.1 uses ATNF v2.6.2 error ellipses; seven pulsars with large uncertainties were excluded, but the rest are assumed accurate enough that overlapping GLEAM-X sources are candidate counterparts.
  • domain assumption The pulsar_spectra literature compilation is complete enough to identify prior sub-400 MHz detections.
    The '106 first detections below 400 MHz' claim (Section 5.1) relies on this compilation; Section 3.2 notes the package uses an older ATNF version and does not recognise 8 of the new matches.
  • domain assumption GLEAM-X: GP flux densities are reliable average pulsar flux measurements at 72-231 MHz.
    The SEDs and spectral fits in Sections 3.2 and 5.1 treat the 20 sub-band flux densities as the pulsar's mean emission; this assumes the survey calibration and source extraction are correct for these compact sources.
  • domain assumption The five spectral models used by pulsar_spectra cover the plausible physical spectral shapes.
    The statistical result that only 23% of detected pulsars are simple power laws (Section 5.1) is conditional on this assumed model set (Section 3.2).
  • domain assumption The gamma-ray parameter cuts select pulsar-like sources.
    The candidate list in Section 4 is built on published distributions of pulsar and AGN gamma-ray properties; if some AGN contaminate the filtered sample, some candidates will be false.

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Cite this review

Pith. "Pith review of Low radio frequency detections of known pulsars and identification of new candidates with GLEAM-X: GP." pith.science (2026). https://pith.science/paper/44DI7BDW

@misc{pith2026250902919,
  author       = {Pith},
  title        = {Pith review of: Low radio frequency detections of known pulsars and identification of new candidates with GLEAM-X: GP},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/44DI7BDW}},
  note         = {Machine review of arXiv:2509.02919}
}
read the original abstract

Image-based searches have become a complementary approach for identifying pulsars, particularly at MHz frequencies where scattering and high dispersion measures affect high-time resolution observations. In this work, we searched the Galactic Plane (GP) data release from the GaLactic and Extragalactic All-Sky Murchison Widefield Array eXtended (GLEAM-X) survey, a widefield continuum radio survey covering the 72 - 231 MHz frequency range, at the positions of known pulsars in the ATNF catalogue (version 2.6.2) that lie within its sky coverage. We present the spectral energy distribution for 193 known pulsars located at |b| < 11deg. Notably, 106 of these represent the first detections below 400 MHz. We also cross-match the GLEAM-X: GP compact source catalogue with unassociated sources in the Fermi Large Area Telescope (LAT) catalogue, filtering for gamma-ray spectral and variability properties, as well as coincidence with Active Galactic Nuclei (AGN). We have identified 106 possible pulsar candidates. This work demonstrates the importance of sensitive, low-frequency Galactic plane surveys for detecting emission from known pulsars and presents a potential way of searching for new pulsar candidates that would otherwise be missed by traditional time-domain searches.

Figures

Figures reproduced from arXiv: 2509.02919 by the authors.

Figure 1
Figure 1. Distribution of known pulsars from the ATNF Pulsar Catalogue (light blue dots) and those detected in GLEAM-X: GP (green circles), as presented in this work. MSPs are highlighted in red squares. 3.1 Sample selection We used the Australia Telescope National Facility (ATNF) pulsar catalogue v2.6.2 (Manchester et al. 2005) 1 to perform a cross-match with the GLEAM-X: GP catalogue to identify potential associations. We c… view at source ↗
Figure 3
Figure 3. Histogram of angular separations between matched ATNF pulsars and GLEAM-X: GP sources, reported in arcminutes. The x-axis is shown on a logarithmic scale. pulsar_spectra software package specifically for modelling pulsar flux density measurements across a broad frequency range. The soft￾ware supports multiple spectral models - including single power￾law, broken power-law, and low frequency turnovers - allowing flexi… view at source ↗
Figure 4
Figure 4. Example SED fit for pulsars using the five models available in the pulsar_spectra software package: power-law (a), broken power-law (b), low-frequency turnover power-law (c), high frequency cutoff power-law (d), and double turnover power-law (e). Blue circles represent data points for flux densities measured in this work with associated uncertainties. • Low variability (log variability index 0.4−1.7): Pulsars presen… view at source ↗
Figures from the paper (5 more)
Figure 5
Figure 5. Figure 5: Distribution of the unassociated compact sources from the 4FGL￾DR4 Catalogue (light grey dots) and potential associated radio sources de￾tected in GLEAM-X: GP (blue circles). GLEAM-X: GP compact source. We considered a match to occur when the position of a GLEAM-X: GP …
Figure 6
Figure 6. Figure 6: Spectral distributions of the two pulsars with multiple associations. The lack of high-frequency data points makes the matched sources equally believable. All the sources in the GLEAM-X: GP catalogue are shown in a different colour to make a clear distinction. pulsars …
Figure 7
Figure 7. Figure 7: Percentage of pulsars fitted by each model across different datasets. The top two charts display results for all known pulsars from the ATNF catalogue, without (a) and with (b) low-frequency data. The bottom two panels show only sources matched with the GLEAM-X: GP cat…
Figure 8
Figure 8. Figure 8: Distribution of the fractional pulse width (left), flux density (middle), and DM (right) for the matched pulsars, shown in comparison with the known pulsar population from the ATNF catalogue (version 2.6.2). All histograms are represented on a logarithmic scale. 0.0 0.…
Figure 9
Figure 9. Figure 9: Corner plot illustrating the distribution of key parameters (photon index, significance curve, and variability index) used in this work to filter the sample of pulsar-like sources (blue), shown in comparison with known pulsars (grey) and MSPs (magenta). Diagonal panels…

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Works this paper leans on

42 extracted references · 8 canonical work pages

  1. [1]

    write newline

    " write newline "" before.all 'output.state := FUNCTION fin.entry write newline FUNCTION new.block output.state before.all = 'skip after.block 'output.state := if FUNCTION new.sentence output.state after.block = 'skip output.state before.all = 'skip after.sentence 'output.state := if if FUNCTION not #0 #1 if FUNCTION and 'skip pop #0 if FUNCTION or pop #1...

  2. [2]

    Abdollahi S., et al., 2020, @doi [ ] 10.3847/1538-4365/ab6bcb , https://ui.adsabs.harvard.edu/abs/2020ApJS..247...33A 247, 33

    doi:10.3847/1538-4365/ab6bcb 2020

  3. [3]

    Abdollahi S., et al., 2022, @doi [ ] 10.3847/1538-4365/ac6751 , https://ui.adsabs.harvard.edu/abs/2022ApJS..260...53A 260, 53

    doi:10.3847/1538-4365/ac6751 2022

  4. [4]

    Ajello M., et al., 2020, @doi [ ] 10.3847/1538-4357/ab791e , https://ui.adsabs.harvard.edu/abs/2020ApJ...892..105A 892, 105

    doi:10.3847/1538-4357/ab791e 2020

  5. [5]

    B., et al., 2009, @doi [ ] 10.1088/0004-637X/697/2/1071 , https://ui.adsabs.harvard.edu/abs/2009ApJ...697.1071A 697, 1071

    Atwood W. B., et al., 2009, @doi [ ] 10.1088/0004-637X/697/2/1071 , https://ui.adsabs.harvard.edu/abs/2009ApJ...697.1071A 697, 1071

    doi:10.1088/0004-637x/697/2/1071 2009

  6. [6]

    H., Lott B., The Fermi-LAT collaboration 2023, @doi [arXiv e-prints] 10.48550/arXiv.2307.12546 , https://ui.adsabs.harvard.edu/abs/2023arXiv230712546B p

    Ballet J., Bruel P., Burnett T. H., Lott B., The Fermi-LAT collaboration 2023, @doi [arXiv e-prints] 10.48550/arXiv.2307.12546 , https://ui.adsabs.harvard.edu/abs/2023arXiv230712546B p. arXiv:2307.12546

    arXiv doi:10.48550/arxiv.2307.12546 2023

  7. [7]

    D., Lorimer D

    Bates S. D., Lorimer D. R., Verbiest J. P. W., 2013, @doi [ ] 10.1093/mnras/stt257 , https://ui.adsabs.harvard.edu/abs/2013MNRAS.431.1352B 431, 1352

    doi:10.1093/mnras/stt257 2013

  8. [8]

    S., Chernov S

    Beskin V. S., Chernov S. V., Gwinn C. R., Tchekhovskoy A. A., 2015, @doi [ ] 10.1007/s11214-015-0173-8 , https://ui.adsabs.harvard.edu/abs/2015SSRv..191..207B 191, 207

    doi:10.1007/s11214-015-0173-8 2015

Show all 42 references
  1. [9]

    Bhat N. D. R., Cordes J. M., Camilo F., Nice D. J., Lorimer D. R., 2004, @doi [ ] 10.1086/382680 , https://ui.adsabs.harvard.edu/abs/2004ApJ...605..759B 605, 759

    2004 doi

  2. [10]

    V., et al., 2016, @doi [ ] 10.1051/0004-6361/201527702 , https://ui.adsabs.harvard.edu/abs/2016A&A...591A.134B 591, A134

    Bilous A. V., et al., 2016, @doi [ ] 10.1051/0004-6361/201527702 , https://ui.adsabs.harvard.edu/abs/2016A&A...591A.134B 591, A134

    2016 doi

  3. [11]

    J., et al., 2023, @doi [ ] 10.1093/mnras/stac3742 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.519.5590C 519, 5590

    Clark C. J., et al., 2023, @doi [ ] 10.1093/mnras/stac3742 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.519.5590C 519, 5590

    2023 doi

  4. [12]

    E., Coles W

    Dai S., Johnston S., Bell M. E., Coles W. A., Hobbs G., Ekers R. D., Lenc E., 2016, @doi [ ] 10.1093/mnras/stw1871 , https://ui.adsabs.harvard.edu/abs/2016MNRAS.462.3115D 462, 3115

    2016 doi

  5. [13]

    A., Mooley K

    Frail D. A., Mooley K. P., Jagannathan P., Intema H. T., 2016a, @doi [ ] 10.1093/mnras/stw1390 , https://ui.adsabs.harvard.edu/abs/2016MNRAS.461.1062F 461, 1062

    doi

  6. [14]

    A., Jagannathan P., Mooley K

    Frail D. A., Jagannathan P., Mooley K. P., Intema H. T., 2016b, @doi [ ] 10.3847/0004-637X/829/2/119 , https://ui.adsabs.harvard.edu/abs/2016ApJ...829..119F 829, 119

    doi

  7. [15]

    A., et al., 2018, @doi [ ] 10.1093/mnras/stx3281 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.475..942F 475, 942

    Frail D. A., et al., 2018, @doi [ ] 10.1093/mnras/stx3281 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.475..942F 475, 942

    2018 doi

  8. [16]

    Geyer M., et al., 2017, @doi [ ] 10.1093/mnras/stx1151 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.470.2659G 470, 2659

    2017 doi

  9. [17]

    Hurley-Walker N., et al., 2017, @doi [ ] 10.1093/mnras/stw2337 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.464.1146H 464, 1146

    2017 doi

  10. [18]

    Hurley-Walker N., et al., 2019, @doi [ ] 10.1017/pasa.2019.37 , https://ui.adsabs.harvard.edu/abs/2019PASA...36...47H 36, e047

    2019 doi

  11. [19]

    Hurley-Walker N., et al., 2022, @doi [ ] 10.1017/pasa.2022.17 , https://ui.adsabs.harvard.edu/abs/2022PASA...39...35H 39, e035

    2022 doi

  12. [20]

    F., Bailes M., Barr E

    Jankowski F., van Straten W., Keane E. F., Bailes M., Barr E. D., Johnston S., Kerr M., 2018, @doi [ ] 10.1093/mnras/stx2476 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.473.4436J 473, 4436

    2018 doi

  13. [21]

    J., Green D

    Kijak J., Lewandowski W., Gupta Y., 2009, in Saikia D. J., Green D. A., Gupta Y., Venturi T., eds, Astronomical Society of the Pacific Conference Series Vol. 407, The Low-Frequency Radio Universe. p. 341

    2009

  14. [22]

    Kuniyoshi M., Verbiest J. P. W., Lee K. J., Adebahr B., Kramer M., Noutsos A., 2015, @doi [ ] 10.1093/mnras/stv1604 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.453..828K 453, 828

    2015 doi

  15. [23]

    Mainzer A., et al., 2011, @doi [ ] 10.1088/0004-637X/731/1/53 , https://ui.adsabs.harvard.edu/abs/2011ApJ...731...53M 731, 53

    2011 doi

  16. [24]

    N., Hobbs G

    Manchester R. N., Hobbs G. B., Teoh A., Hobbs M., 2005, @doi [The Astronomical Journal] 10.1086/428488 , 129, 1993

    2005 doi

  17. [25]

    W., et al., 2017, @doi [ ] 10.1017/pasa.2017.5 , https://ui.adsabs.harvard.edu/abs/2017PASA...34...13M 34, e013

    Meyers B. W., et al., 2017, @doi [ ] 10.1017/pasa.2017.5 , https://ui.adsabs.harvard.edu/abs/2017PASA...34...13M 34, e013

    2017 doi

  18. [26]

    J., Mahesh N., Monsalve R

    Mozdzen T. J., Mahesh N., Monsalve R. A., Rogers A. E. E., Bowman J. D., 2019, @doi [ ] 10.1093/mnras/sty3410 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.483.4411M 483, 4411

    2019 doi

  19. [27]

    Murphy T., et al., 2017, @doi [ ] 10.1017/pasa.2017.13 , https://ui.adsabs.harvard.edu/abs/2017PASA...34...20M 34, e020

    2017 doi

  20. [28]

    arXiv:2406.06921

    Ross K., et al., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2406.06921 , https://ui.adsabs.harvard.edu/abs/2024arXiv240606921R p. arXiv:2406.06921

    2024 doi arXiv

  21. [29]

    M., Xu H., Yu P

    Saz Parkinson P. M., Xu H., Yu P. L. H., Salvetti D., Marelli M., Falcone A. D., 2016, @doi [ ] 10.3847/0004-637X/820/1/8 , https://ui.adsabs.harvard.edu/abs/2016ApJ...820....8S 820, 8

    2016 doi

  22. [30]

    Sengar R., et al., 2025, @doi [ ] 10.1093/mnras/stae2716 , https://ui.adsabs.harvard.edu/abs/2025MNRAS.536.3159S 536, 3159

    2025 doi

  23. [31]

    Sett S., Sokolowski M., Lenc E., Bhat N. D. R., 2024, @doi [ ] 10.1017/pasa.2024.62 , https://ui.adsabs.harvard.edu/abs/2024PASA...41...45S 41, e045

    2024 doi

  24. [32]

    Singal J., 2015, @doi [ ] 10.1093/mnras/stv1964 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.454..115S 454, 115

    2015 doi

  25. [33]

    A., et al., 2021, @doi [ ] 10.3847/2041-8213/abec7b , https://ui.adsabs.harvard.edu/abs/2021ApJ...911L..26S 911, L26

    Swainston N. A., et al., 2021, @doi [ ] 10.3847/2041-8213/abec7b , https://ui.adsabs.harvard.edu/abs/2021ApJ...911L..26S 911, L26

    2021 doi

  26. [34]

    A., Lee C

    Swainston N. A., Lee C. P., McSweeney S. J., Bhat N. D. R., 2022, @doi [ ] 10.1017/pasa.2022.52 , https://ui.adsabs.harvard.edu/abs/2022PASA...39...56S 39, e056

    2022 doi

  27. [35]

    K., Rao A

    Swarup G., Ananthakrishnan S., Kapahi V. K., Rao A. P., Subrahmanya C. R., Kulkarni V. K., 1991, Current Science, https://ui.adsabs.harvard.edu/abs/1991CSci...60...95S 60, 95

    1991

  28. [36]

    J., et al., 2013, @doi [ ] 10.1017/pasa.2012.007 , https://ui.adsabs.harvard.edu/abs/2013PASA...30....7T 30, e007

    Tingay S. J., et al., 2013, @doi [ ] 10.1017/pasa.2012.007 , https://ui.adsabs.harvard.edu/abs/2013PASA...30....7T 30, e007

    2013 doi

  29. [37]

    Vohl D., van Leeuwen J., Maan Y., 2024, @doi [ ] 10.1051/0004-6361/202348621 , https://ui.adsabs.harvard.edu/abs/2024A&A...687A.113V 687, A113

    2024 doi

  30. [38]

    B., et al., 2015, @doi [ ] 10.1017/pasa.2015.26 , https://ui.adsabs.harvard.edu/abs/2015PASA...32...25W 32, e025

    Wayth R. B., et al., 2015, @doi [ ] 10.1017/pasa.2015.26 , https://ui.adsabs.harvard.edu/abs/2015PASA...32...25W 32, e025

    2015 doi

  31. [39]

    B., et al., 2018, @doi [ ] 10.1017/pasa.2018.37 , https://ui.adsabs.harvard.edu/abs/2018PASA...35...33W 35, e033

    Wayth R. B., et al., 2018, @doi [ ] 10.1017/pasa.2018.37 , https://ui.adsabs.harvard.edu/abs/2018PASA...35...33W 35, e033

    2018 doi

  32. [40]

    Wenger M., et al., 2000, @doi [ ] 10.1051/aas:2000332 , https://ui.adsabs.harvard.edu/abs/2000A&AS..143....9W 143, 9

    2000 doi

  33. [41]

    L., et al., 2010, @doi [ ] 10.1088/0004-6256/140/6/1868 , https://ui.adsabs.harvard.edu/abs/2010AJ....140.1868W 140, 1868

    Wright E. L., et al., 2010, @doi [ ] 10.1088/0004-6256/140/6/1868 , https://ui.adsabs.harvard.edu/abs/2010AJ....140.1868W 140, 1868

    2010 doi

  34. [42]

    R., Chen J

    Zhu K. R., Chen J. M., Zheng Y. G., Zhang L., 2024, @doi [ ] 10.1093/mnras/stad2813 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.527.1794Z 527, 1794

    2024 doi

Pith tools

Reviewed August 5, 2026 · model on record in the stance chip above.