Pith. sign in

REVIEW 3 major objections 4 minor 88 references

Slow and steady: long-term evolution of the 76-second pulsar J0901$-$4046

T0 review · 3 major / 4 minor · reviewed 2026-08-15 · deepseek-v4-flash

Pith's one-line read This paper argues that the 75.88-second pulsar J0901−4046 has a remarkably stable timing solution over 2.60 years, with arrival-time scatter of just 7.6 ms, about 10^-4 of its rotation period.

desk verdict A solid observational follow-up that confirms long-term timing stability for J0901–4046; the secondary claims are interesting but rest on small samples. read the letter →

arxiv 2505.04430 v1 pith:FJWVRJ4H submitted 2025-05-07 astro-ph.HE

classification astro-ph.HE
keywords pulsarsneutronstarsradioastronomytimingresidualspulsemorphologyquasi-periodicoscillationsradius-to-frequencymappingultra-longperiod
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 reports on 46 hours of follow-up of PSR J0901−4046, a neutron star candidate spinning once every 75.88 seconds, and argues that its radio emission is far more regular than its strange period suggests. The central claim is that the source's timing solution is stable over 2.6 years, with arrival-time scatter of 7.6 ms, about one ten-thousandth of the rotation period. That stability matters because ultra-long-period neutron stars are usually expected to behave like magnetars—erupting, glitching, and changing their pulse shapes. Instead, this source shows a constant profile envelope, a nearly frequency-independent pulse width, and no secular flux decline, while still hosting quasi-periodic sub-pulse oscillations at 73 ms and 21 ms. The authors take this as evidence that the source's identification as an ultra-long-period magnetar is not straightforward.

What carries the argument

The argument is carried by the coherent timing solution: single-pulse arrival times are fitted to an analytic template profile built from each dataset, then combined in a weighted fit for spin period and period derivative with an inter-telescope phase jump; the resulting 7.6 ms RMS residual is the measure of profile-envelope stability. Supporting machinery includes autocorrelation-function analysis of single-pulse intensities to extract quasi-periodic microstructure timescales, a Thorsett-type power-law fit to width versus frequency, and a chi-square homogeneity test on pulse-shape category counts.

What would settle it

Rebuild the timing solution using one fixed, high signal-to-noise template from a single long observation to generate times of arrival for all epochs; if the RMS residual grows by a factor of several above 7.6 ms, the quoted stability is an artifact of per-epoch template fitting. Alternatively, a single observation showing a fundamentally different average pulse shape, or a glitch-like change in the period derivative, would break the steady-spin model.

Watch

Extended reading notes

Core claim

The paper's central discovery is that PSR J0901−4046, a 75.88-second pulsar candidate with a surface field above the quantum critical limit, has a coherent timing solution over 2.60 years whose RMS residual is 7.6 ms, about $10^{-4}$ of the pulse period. Pulse arrival times scatter little despite large pulse-to-pulse morphological changes, implying the average profile envelope is highly stable from epoch to epoch. The paper also finds no evidence for the previously reported secular flux decline, measures a pulse width that is nearly constant from 544 to 4032 MHz (consistent with zero radius-to-frequency mapping), detects two quasi-periodic microstructure timescales of roughly 73 ms and 21 ms, and documents a statistically significant shift in the prevalence of pulse morphologies relative to the discovery epoch.

Load-bearing premise

The 7.6 ms timing residual assumes that every pulse can be compared against a single template profile derived from its own epoch, so unmodelled phase jitter or mode changes count as measurement scatter rather than as evolution of the pulse shape.

Editorial extensions

If this is right

  • If the timing stability persists, J0901−4046 offers a reliable clock for detecting future glitches or spin-down changes, and strengthens the case that some ultra-long-period sources behave like ordinary pulsars rather than magnetars.
  • The nearly constant pulse width from 544 to 4032 MHz implies that the beam opening angle does not grow toward lower frequencies, constraining radius-to-frequency mapping models in a star with a very large light cylinder.
  • The measured shift in pulse-morphology proportions (normal-type pulses rising from 37% to 68%) suggests the magnetosphere's state changes on year timescales, an effect that continued monitoring could track.
  • The two quasi-periodic timescales, roughly 73 ms and 21 ms, with the longer one following the roughly $P\times10^{-3}$ scaling seen across neutron stars, link this source to a universal sub-pulse emission mechanism.
  • Non-detection below 500 MHz, if a true spectral turnover, means wide-field low-frequency surveys could systematically miss such sources, biasing the census of ultra-long-period neutron stars.

Reading between the lines

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

  • If the per-epoch template approach is masking slow profile evolution, the true envelope stability could be lower than claimed; a fixed-template re-analysis is a direct test that the authors do not perform.
  • The absence of glitches over 2.6 years, if the source is a magnetar, may indicate that its spin-down is governed by magnetic dipole radiation rather than the wind and particle losses that drive magnetar timing noise.
  • The roughly $P\times10^{-3}$ quasi-period scaling could be tested for FRB sub-burst structure: applying the same autocorrelation analysis to repeating FRB pulses would show whether the scaling extends to shorter periods or breaks.
  • The morphology shift could be converted into a quantitative classification using unsupervised clustering; if the result confirms a non-Poissonian change, it would strengthen the magnetospheric-evolution interpretation.
Share X Bluesky LinkedIn Reddit HN

Signed reviews

No signed human review yet.

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 4 minor

Summary. PSR J0901−4046 is a 75.88-s radio-loud neutron star discovered by Caleb et al. (2022a). The manuscript reports 46.25 h of follow-up with MeerKAT, Murriyang, GMRT, and MWA. It derives a coherent timing solution over 2.60 yr from 55 single-pulse TOAs, with P and P-dot consistent with the discovery values and an RMS residual of 7.6 ms, about 10^-4 of the spin period. Additional results include: a wideband (544–4032 MHz) average profile with nearly frequency-independent W50 and a Thorsett-fit eta' = 0.00 ± 0.02; power-law spectra with alpha near −1; a single-epoch pulse-energy distribution with log-normal fits; a claimed change in the distribution of seven by-eye pulse morphologies compared with C22 (chi^2 = 46.9); ACF-based quasi-periods with means of 72.86 ms (quasi-periodic pulses) and 20.87 ms (spiky pulses); and non-detections below 500 MHz suggesting a spectral turnover. The paper interprets these findings as constraining ultra-long-period magnetar interpretations.

Significance. The source is one of the most extreme radio pulsars known, and a long, coherent timing baseline plus wideband spectral and single-pulse characterization is exactly what the field needs to discriminate between neutron-star, magnetar, and white-dwarf interpretations. The paper adds genuinely new data: the wideband profile, the sub-band quasi-period measurements with bootstrap errors, and the comparison of morphology statistics with C22. The timing solution, if robust, would be an important reference result for ultra-long-period sources. However, the headline stability claim is not yet strongly supported: the fit's reduced chi-square and visible jitter mean the 7.6 ms RMS is model-dependent. The morphology and QPO-mode claims also rely on small, subjectively classified samples. These issues are correctable with additional analysis or more cautious wording.

major comments (3)
  1. [§3.1, Table 2] The central stability claim rests on the 7.6 ms RMS residual, but the timing fit is statistically poor: chi^2/ndof = 805.29/52, i.e. reduced chi^2 ≈ 15.5, and no EFAC/EQUAD or jitter-noise term is described in the model. The text itself states that 'some pulse phase jitter is visible where the scatter in arrival times is larger than the error bars.' Because every single-pulse TOA is derived from an analytic template built from the same dataset, the RMS is a property of the fitted model (template shape, noise weighting, and the fitted UWL–MeerKAT JUMP), not an independent measurement of intrinsic profile stability. Please re-fit with a jitter term or renormalized uncertainties, report both weighted and unweighted residual RMS, and either support or substantially soften the statement that the pulse-profile envelope is 'highly stable from epoch to epoch.' The coherent P and P-dot solution remains a valid result, but the abstract's 'RMS arrival-time uncertainty of just ~10^-4' should not be presented as a model-independent measurement.
  2. [§3.4, Table 4] The claim that the pulse-morphology distribution has changed between C22 and this work is based on a chi^2 test performed on by-eye classifications, yet the paper admits that 'a proportion of the classifications are unavoidably ambiguous.' Classification error is not propagated into the test, and the two samples were taken under different conditions (band, RFI environment, pulse selection), which could bias the category counts. The observed chi^2 = 46.9 therefore does not by itself establish a physical change in the source. Please add a robustness check (e.g., multiple independent classifiers or a conservative reclassification) or rephrase the conclusion as evidence for a difference between the two datasets rather than a definitive change in the source's magnetosphere.
  3. [§3.5, Table 5] The abstract's 'two distinct quasi-periodic oscillation modes' are based on only five quasi-periodic and four spiky pulses, selected by visual classification from a single epoch. The quoted bootstrap uncertainties (e.g., 60.894(2) ms) quantify the ACF peak location for each chosen pulse, not the scatter of the population or the selection uncertainty. With n = 4 for the spiky class, the 20.87 ms 'mode' should be presented as a tentative characteristic timescale in a small sample, not a distinct mode of the source. Please either add supporting statistics (e.g., a significance test against red noise or a larger sample) or temper the wording.
minor comments (4)
  1. [§4] The Discussion states that the RMS of the timing model is '~8 μs', which is inconsistent with Table 2's 7.6 ms (7600 μs) by three orders of magnitude; this should be corrected.
  2. [Abstract, Table 2] The abstract says the timing solution spans 'more than three years', while Table 2 reports a data span of 2.60 yr and an MJD range of 59119.1–60083.4 (about 2.64 yr); please reconcile these numbers, and check whether the 2024 observations mentioned in §2 are included in the timing analysis.
  3. [Table 1] The row for 2021/12/12 lists a 120-min MeerKAT observation with 47 rotations, but a 120-min observation at P = 75.88 s should contain about 94 rotations; this appears to be a transcription error.
  4. [§2.1] The text says FBFUSE data were not coherently de-dispersed, while PTUSE data were; this difference in de-dispersion could affect timing and morphology results and is not discussed in the error budget.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the paper reports measured properties of a known pulsar and compares them with external or directly fitted quantities, without reducing any claim to its own inputs.

full rationale

This paper is an observational study: its central quantities are measured from data, not derived from fitted models of the same quantities. The timing analysis in Section 3.1 follows standard pulsar timing practice: analytic templates are constructed per dataset with paas, ToAs are generated with pat, and a model with P, Pdot, and an inter-instrument jump is fit with tempo2. The quoted 7.6 ms RMS residual is a fit-quality statistic, not a first-principles prediction, and the statement that the pulse envelope is 'highly stable' is an interpretation of those residuals, not a claim that the model predicts its own input. No equation is defined in terms of the result it is supposed to establish. The quasi-periods in Section 3.5 are measured directly via autocorrelation of single-pulse intensities, and the comparison to the P x 10^-3 scaling is a published empirical relation from Kramer et al. (2024), not an imported uniqueness or forcing condition. The W50/RFM analysis fits the standard Thorsett function to measured widths; the derived eta' is a re-expression of that fit rather than a hidden input, and the near-constancy of width is also directly visible in the measured frequency-resolved widths. Self-citations to C22 provide discovery context, prior ToAs, and morphology definitions, but the new conclusions rest on 46.25 hours of new multi-telescope observations. Concerns about template dependence and phase jitter affecting the timing residual are model-dependence or correctness issues, not circularity; no circular step can be exhibited from the paper's own equations or argument chain.

Assumptions & free parameters 4 free parameters · 3 assumptions · 0 invented entities

The paper introduces no new physical entities. Its free parameters are standard fit parameters of pulsar timing, spectral, and width models. The assumptions are standard domain assumptions in pulsar astronomy. The heaviest tacit input is the subjective classification of pulse morphologies, which is a methodological choice rather than a parameter. The small number of pulses used for the quasi-periodic analysis is the main quantitative weakness.

free parameters (4)
  • Timing model parameters (P, P-dot, JUMP) = P=75.88554698 s; P-dot=2.44e-13; JUMP between UWL and MeerKAT
    These are fitted to the 55 TOAs and are standard pulsar timing parameters. They are not free parameters in the sense of being tuned to force a conclusion, but the timing model includes a jump between UWL and MeerKAT data that absorbs any systematic offset between instruments.
  • Thorsett width fit parameters A, mu, W10,0 = A=5300+-2700, mu=-2.14+-0.47, W10,0=1.98 deg+-0.09
    These are fitted to the measured pulse widths across 20 frequency channels. The uncertainty on A is large and the parameters are strongly correlated, as the paper notes, so the derived eta'=0.00 is not strongly constraining.
  • Spectral index alpha per band = alpha=-0.92+-0.01 (UHF), -1.15+-0.12 (L), -1.02+-0.05 (UWL)
    Fitted to measured flux densities in each band after excluding 3-sigma outliers. Standard spectral fit.
  • Weibull shape parameter k for normal pulse wait times = k=0.99+-0.15
    Fitted to wait time distribution to test clustering; consistent with unity, so no clustering found.
assumptions (3)
  • domain assumption PSR J0901-4046 is a neutron star, not a white dwarf or other object.
    The paper states that without detection of a companion or evidence for binarity, a NS origin is assumed. This is a background astrophysical assumption, reasonable but not proven.
  • domain assumption The dispersion measure is fixed at 52.6 pc cm^-3.
    Data are de-dispersed at this DM from C22, and the timing model does not fit DM. If the DM is wrong or variable, pulse arrival times could be biased, but the cross-band consistency of sub-pulse features provides some support.
  • domain assumption The radio flux density conversion uses assumed system temperatures, gains, and sky model values.
    The flux densities are derived using the radiometer equation with T_rec=18K at L-band and 24K at UHF, G=2.8 K/Jy, and pygdsm sky temperatures. These are good estimates but not calibrated against in-field flux calibrators, so absolute fluxes have systematic uncertainty.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Slow and steady: long-term evolution of the 76-second pulsar J0901$-$4046." pith.science (2026). https://pith.science/paper/FJWVRJ4H

@misc{pith2026250504430,
  author       = {Pith},
  title        = {Pith review of: Slow and steady: long-term evolution of the 76-second pulsar J0901$-$4046},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/FJWVRJ4H}},
  note         = {Machine review of arXiv:2505.04430}
}
abstract

PSR J0901$-$4046, a likely radio-loud neutron star with a period of 75.88 seconds, challenges conventional models of neutron star radio emission. Here, we showcase results from 46 hours of follow-up observations of PSR J0901$-$4046 using the MeerKAT, Murriyang, GMRT, and MWA radio telescopes. We demonstrate the intriguing stability of the source's timing solution over more than three years, leading to an RMS arrival-time uncertainty of just $\sim$10$^{-4}$ of the rotation period. Furthermore, non-detection below 500 MHz may indicate a low-frequency turnover in the source's spectrum, while no secular decline in the flux density of the source over time, as was apparent from previous observations, has been observed. Using high time-resolution MeerKAT data, we demonstrate two distinct quasi-periodic oscillation modes present in single pulses, with characteristic time scales of 73 ms and 21 ms. We also observe a statistically significant change in the relative prevalence of distinct pulse morphologies compared to previous observations, possibly indicating a shift in the magnetospheric composition over time. Finally, we show that the W$_{50}$ pulse width is nearly constant from 544-4032 MHz, consistent with zero radius-to-frequency mapping. The very short duty cycle ($\sim$1.4$^{\circ}$) is more similar to radio pulsars with periods $>$5 seconds than to radio-loud magnetars. This, along with the lack of magnetar-like outbursts or timing glitches, complicates the identification of the source with ultra-long period magnetar models.

Figures

Figures reproduced from arXiv: 2505.04430 by the authors.

Figure 1
Figure 1. Observation dates of PSR J0901−4046 using the GMRT radio telescope, the MeerKAT radio telescope’s UHF-band and L-band receivers, and the Murriyang radio telescope’s UWL receiver. The blue lines indicate the dates of simultaneous multi-instrument observations. The second simultaneous observation included an MWA observation at 140–170 MHz that did not produce any detections of the pulsar [PITH_FULL_IMAGE:figures/full… view at source ↗
Figure 2
Figure 2. Timing residuals of PSR J0901−4046 pulses. Blue data points are determined from MeerKAT data, while orange data points are determined from Murriyang UWL data. The right-hand panel is zoomed in on the MeerKAT data points only. The vertical cyan line separates the data points used for the timing analysis in C22 from subsequent measurements. The error bars are 1-𝜎. 2.25(10)×10−13 s s−1 within 2-𝜎. These timing paramete… view at source ↗
Figure 3
Figure 3. Profile (top) and dynamic spectrum (bottom) of PSR J0901−4046 averaged over the Murriyang UWL band, GMRT Band-4, and the MeerKAT L band and UHF band. The fluxes are indicated in arbitrary units. Profiles averaged over the combined band (black), UWL only (blue), Band-4 only (vi￾olet), MeerKAT L band only (green), and MeerKAT UHF band only (orange) are shown. The red horizontal lines in the dynamic spectrum indicate t… view at source ↗
Figures from the paper (11 more)
Figure 4
Figure 4. Figure 4: Measured time-averaged pulse energies as a function of frequency in the MeerKAT UHF band, with best-fit power law spectral fit. The gray data points were ignored in the fit as outliers [PITH_FULL_IMAGE:figures/full_fig_p007_4.png]
Figure 6
Figure 6. Figure 6: Histograms comparing the best-fit 𝜇 (top) and 𝜂′ (bottom) param￾eters with shaded errors for PSR J0901−4046 compared to the 150 pulsars in the Chen & Wang (2014) sample. a zero-DM RFI spike had been removed. The on-pulse and off-pulse energy distributions (PEDs) derive…
Figure 5
Figure 5. Figure 5: Left: W10 pulse widths of PSR J0901−4046 in 20 frequency chan￾nels covering 0.5–4 GHz. The blue line represents the best-fit model using Eq. 1, with 1-𝜎 errors shaded. Right: The pulse profile in each channel. we computed relative pulse energies in both bands for the 1…
Figure 7
Figure 7. Figure 7: Pulse energy distribution of PSR J0901−4046 single pulses observed simultaneously in the MeerKAT L band (left) and UHF band (right). In each plot, the black outlined bars indicate the off-pulse energy, while the solid grey bars indicate the on-pulse energy. The energie…
Figure 8
Figure 8. Figure 8: Average peak flux density measurements of single pulses detected during MeerKAT observations. The line of best fit, with 1-𝜎 uncertainty, has a slope of 4.8±2.1×10−3 mJy/day. cal types in these data may suggest clustering in time. For example, eleven of the 24 split-pe…
Figure 9
Figure 9. Figure 9: High time-resolution profile (top) and dynamic spectrum (bottom) made using 151 PSR J0901−4046 single pulses observed in the MeerKAT L band and UHF band concurrently. Profiles summed over the combined band (black), MeerKAT L-band only (blue), and MeerKAT UHF-band only …
Figure 10
Figure 10. Figure 10: Profiles (top) and dynamic spectra (bottom) of representative single pulses from each of the seven PSR J0901−4046 pulse morphology types identified in C22. The profile averaged over the combined band (black), L band only (orange), and UHF band only (blue) are shown. T…
Figure 11
Figure 11. Figure 11: Times of MeerKAT PTUSE detections of PSR J0901−4046, categorised based on pulse shape type. MNRAS 000, 1–15 (2024) [PITH_FULL_IMAGE:figures/full_fig_p011_11.png]
Figure 12
Figure 12. Figure 12: Probability density function of wait times between subsequent PSR J0901−4046 single pulses of the normal type. The solid curve (with 1-𝜎 errors shaded) indicates the best-fit Weibull distribution with 𝑘 and the burst rate (𝑟) as free parameters. The dashed curve shows…
Figure 13
Figure 13. Figure 13: Profiles (top) and dynamic spectra (bottom) of three PSR J0901−4046 pulses showing evidence of variable frequency-dependence of sub-pulses. Black profiles are averaged over the entire combined MeerKAT band, while the blue and orange profiles are averaged over the L-ba…
Figure 14
Figure 14. Figure 14: Pulse profiles (left) and ACFs (right) of a representative quasi-periodic PSR J0901−4046 pulse across the full band and three sub-bands. The dashed vertical lines in the ACF plot indicate the peak of the ACF in each sub-band, and thus the quasi-period, with 1-𝜎 error …

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

88 extracted references · 4 canonical work pages

  1. [1]

    H., et al., 2021, @doi [ ] 10.1093/mnras/stab2496 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.508.1102A 508, 1102

    Agar C. H., et al., 2021, @doi [ ] 10.1093/mnras/stab2496 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.508.1102A 508, 1102

  2. [2]

    Bailes M., et al., 2020, @doi [ ] 10.1017/pasa.2020.19 , https://ui.adsabs.harvard.edu/abs/2020PASA...37...28B 37, e028

  3. [3]

    G., Harding A

    Baring M. G., Harding A. K., 1998, @doi [ ] 10.1086/311679 , https://ui.adsabs.harvard.edu/abs/1998ApJ...507L..55B 507, L55

  4. [4]

    Becker W., Kramer M., Sesana A., 2018, @doi [ ] 10.1007/s11214-017-0459-0 , https://ui.adsabs.harvard.edu/abs/2018SSRv..214...30B 214, 30

  5. [5]

    D., 2020, @doi [ ] 10.1093/mnras/staa1783 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.496.3390B 496, 3390

    Beniamini P., Wadiasingh Z., Metzger B. D., 2020, @doi [ ] 10.1093/mnras/staa1783 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.496.3390B 496, 3390

  6. [6]

    C., 2022, PhD thesis, University of Manchester

    Bezuidenhout M. C., 2022, PhD thesis, University of Manchester

  7. [7]

    D., Ravi V., Belov K

    Bochenek C. D., Ravi V., Belov K. V., Hallinan G., Kocz J., Kulkarni S. R., McKenna D. L., 2020, @doi [ ] 10.1038/s41586-020-2872-x , https://ui.adsabs.harvard.edu/abs/2020Natur.587...59B 587, 59

  8. [8]

    CHIME/FRB Collaboration et al., 2020, @doi [ ] 10.1038/s41586-020-2863-y , https://ui.adsabs.harvard.edu/abs/2020Natur.587...54C 587, 54

Show all 88 references
  1. [9]

    CHIME/FRB Collaboration et al., 2022, @doi [ ] 10.1038/s41586-022-04841-8 , https://ui.adsabs.harvard.edu/abs/2022Natur.607..256C 607, 256

  2. [10]

    Caleb M., et al., 2022a, @doi [Nature Astronomy] 10.1038/s41550-022-01688-x , https://ui.adsabs.harvard.edu/abs/2022NatAs...6..828C 6, 828

  3. [11]

    Caleb M., et al., 2022b, @doi [ ] 10.1093/mnras/stab3223 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.510.1996C 510, 1996

  4. [12]

    Caleb M., et al., 2024, @doi [Nature Astronomy] 10.1038/s41550-024-02277-w , https://ui.adsabs.harvard.edu/abs/2024NatAs...8.1159C 8, 1159

  5. [13]

    M., Halpern J

    Camilo F., Ransom S. M., Halpern J. P., Reynolds J., Helfand D. J., Zimmerman N., Sarkissian J., 2006, @doi [ ] 10.1038/nature04986 , https://ui.adsabs.harvard.edu/abs/2006Natur.442..892C 442, 892

  6. [14]

    M., Halpern J

    Camilo F., Ransom S. M., Halpern J. P., Reynolds J., 2007a, @doi [ ] 10.1086/521826 , https://ui.adsabs.harvard.edu/abs/2007ApJ...666L..93C 666, L93

  7. [15]

    Camilo F., et al., 2007b, @doi [ ] 10.1086/521548 , https://ui.adsabs.harvard.edu/abs/2007ApJ...669..561C 669, 561

  8. [16]

    Camilo F., et al., 2018, @doi [ ] 10.3847/1538-4357/aab35a , https://ui.adsabs.harvard.edu/abs/2018ApJ...856..180C 856, 180

  9. [17]

    L., Wang H

    Chen J. L., Wang H. G., 2014, @doi [ ] 10.1088/0067-0049/215/1/11 , https://ui.adsabs.harvard.edu/abs/2014ApJS..215...11C 215, 11

  10. [18]

    Chen W., Barr E., Karuppusamy R., Kramer M., Stappers B., 2021, @doi [Journal of Astronomical Instrumentation] 10.1142/S2251171721500136 , https://ui.adsabs.harvard.edu/abs/2021JAI....1050013C 10, 2150013

  11. [19]

    M., 1978, @doi [ ] 10.1086/156218 , https://ui.adsabs.harvard.edu/abs/1978ApJ...222.1006C 222, 1006

    Cordes J. M., 1978, @doi [ ] 10.1086/156218 , https://ui.adsabs.harvard.edu/abs/1978ApJ...222.1006C 222, 1006

  12. [20]

    M., 1979, @doi [Australian Journal of Physics] 10.1071/PH790009 , https://ui.adsabs.harvard.edu/abs/1979AuJPh..32....9C 32, 9

    Cordes J. M., 1979, @doi [Australian Journal of Physics] 10.1071/PH790009 , https://ui.adsabs.harvard.edu/abs/1979AuJPh..32....9C 32, 9

  13. [21]

    M., Chatterjee S., 2019, @doi [ ] 10.1146/annurev-astro-091918-104501 , https://ui.adsabs.harvard.edu/abs/2019ARA&A..57..417C 57, 417

    Cordes J. M., Chatterjee S., 2019, @doi [ ] 10.1146/annurev-astro-091918-104501 , https://ui.adsabs.harvard.edu/abs/2019ARA&A..57..417C 57, 417

  14. [22]

    M., Lazio T

    Cordes J. M., Lazio T. J. W., 2002, @doi [arXiv e-prints] 10.48550/arXiv.astro-ph/0207156 , https://ui.adsabs.harvard.edu/abs/2002astro.ph..7156C pp astro--ph/0207156

  15. [23]

    De K., Gupta Y., Sharma P., 2016, @doi [ ] 10.3847/2041-8213/833/1/L10 , https://ui.adsabs.harvard.edu/abs/2016ApJ...833L..10D 833, L10

  16. [24]

    A., et al., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2407.07480 , https://ui.adsabs.harvard.edu/abs/2024arXiv240707480D p

    Dong F. A., et al., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2407.07480 , https://ui.adsabs.harvard.edu/abs/2024arXiv240707480D p. arXiv:2407.07480

  17. [25]

    Esposito P., et al., 2020, @doi [ ] 10.3847/2041-8213/ab9742 , https://ui.adsabs.harvard.edu/abs/2020ApJ...896L..30E 896, L30

  18. [26]

    Fender R., et al., 2016, in MeerKAT Science: On the Pathway to the SKA. p. 13 ( @eprint arXiv 1711.04132 ), @doi 10.22323/1.277.0013

  19. [27]

    Gupta Y., et al., 2017, @doi [Current Science] 10.18520/cs/v113/i04/707-714 , https://ui.adsabs.harvard.edu/abs/2017CSci..113..707G 113, 707

  20. [28]

    Hessels J. W. T., et al., 2019, @doi [ ] 10.3847/2041-8213/ab13ae , https://ui.adsabs.harvard.edu/abs/2019ApJ...876L..23H 876, L23

  21. [29]

    S., Hernquist L., 2005, @doi [ ] 10.1111/j.1365-2966.2005.09338.x , https://ui.adsabs.harvard.edu/abs/2005MNRAS.362..777H 362, 777

    Heyl J. S., Hernquist L., 2005, @doi [ ] 10.1111/j.1365-2966.2005.09338.x , https://ui.adsabs.harvard.edu/abs/2005MNRAS.362..777H 362, 777

  22. [30]

    B., Edwards R

    Hobbs G. B., Edwards R. T., Manchester R. N., 2006, @doi [ ] 10.1111/j.1365-2966.2006.10302.x , https://ui.adsabs.harvard.edu/abs/2006MNRAS.369..655H 369, 655

  23. [31]

    Hobbs G., et al., 2020, @doi [ ] 10.1017/pasa.2020.2 , https://ui.adsabs.harvard.edu/abs/2020PASA...37...12H 37, e012

  24. [32]

    W., van Straten W., Manchester R

    Hotan A. W., van Straten W., Manchester R. N., 2004, @doi [ ] 10.1071/AS04022 , https://ui.adsabs.harvard.edu/abs/2004PASA...21..302H 21, 302

  25. [33]

    Hu C.-P., et al., 2020, @doi [ ] 10.3847/1538-4357/abb3c9 , https://ui.adsabs.harvard.edu/abs/2020ApJ...902....1H 902, 1

  26. [34]

    Hurley-Walker N., et al., 2022, @doi [ ] 10.1038/s41586-021-04272-x , https://ui.adsabs.harvard.edu/abs/2022Natur.601..526H 601, 526

  27. [35]

    Hurley-Walker N., et al., 2023, @doi [ ] 10.1038/s41586-023-06202-5 , https://ui.adsabs.harvard.edu/abs/2023Natur.619..487H 619, 487

  28. [36]

    Hurley-Walker N., et al., 2024, @doi [ ] 10.3847/2041-8213/ad890e , https://ui.adsabs.harvard.edu/abs/2024ApJ...976L..21H 976, L21

  29. [37]

    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

  30. [38]

    E., Pierfedereci F., Teuben P., eds, Astronomical Society of the Pacific Conference Series Vol

    Jankowski F., et al., 2022, in Ruiz J. E., Pierfedereci F., Teuben P., eds, Astronomical Society of the Pacific Conference Series Vol. 532, Astronomical Data Analysis Software and Systems XXX. p. 273 ( @eprint arXiv 2012.05173 ), @doi 10.48550/arXiv.2012.05173

  31. [40]

    Jonas J., MeerKAT Team 2016, in MeerKAT Science: On the Pathway to the SKA. p. 1, @doi 10.22323/1.277.0001

  32. [41]

    M., Beloborodov A

    Kaspi V. M., Beloborodov A. M., 2017, @doi [ ] 10.1146/annurev-astro-081915-023329 , https://ui.adsabs.harvard.edu/abs/2017ARA&A..55..261K 55, 261

  33. [42]

    Kijak J., Kramer M., Wielebinski R., Jessner A., 1998, @doi [ ] 10.1051/aas:1998340 , https://ui.adsabs.harvard.edu/abs/1998A&AS..127..153K 127, 153

  34. [43]

    Kijak J., Basu R., Lewandowski W., Ro \.z ko K., Dembska M., 2017, @doi [ ] 10.3847/1538-4357/aa6ff2 , https://ui.adsabs.harvard.edu/abs/2017ApJ...840..108K 840, 108

  35. [44]

    Kramer M., Johnston S., van Straten W., 2002, @doi [ ] 10.1046/j.1365-8711.2002.05478.x , https://ui.adsabs.harvard.edu/abs/2002MNRAS.334..523K 334, 523

  36. [45]

    W., 2024, @doi [Nature Astronomy] 10.1038/s41550-023-02125-3 , https://ui.adsabs.harvard.edu/abs/2024NatAs...8..230K 8, 230

    Kramer M., Liu K., Desvignes G., Karuppusamy R., Stappers B. W., 2024, @doi [Nature Astronomy] 10.1038/s41550-023-02125-3 , https://ui.adsabs.harvard.edu/abs/2024NatAs...8..230K 8, 230

  37. [46]

    Lange C., Kramer M., Wielebinski R., Jessner A., 1998, , https://ui.adsabs.harvard.edu/abs/1998A&A...332..111L 332, 111

  38. [47]

    W., Lyne A

    Lazaridis K., Jessner A., Kramer M., Stappers B. W., Lyne A. G., Jordan C. A., Serylak M., Zensus J. A., 2008, @doi [ ] 10.1111/j.1365-2966.2008.13794.x , https://ui.adsabs.harvard.edu/abs/2008MNRAS.390..839L 390, 839

  39. [48]

    Lee Y. W. J., et al., 2025, @doi [arXiv e-prints] 10.48550/arXiv.2501.09133 , https://ui.adsabs.harvard.edu/abs/2025arXiv250109133L p. arXiv:2501.09133

  40. [49]

    Levin L., et al., 2010, @doi [ ] 10.1088/2041-8205/721/1/L33 , https://ui.adsabs.harvard.edu/abs/2010ApJ...721L..33L 721, L33

  41. [50]

    Levin L., et al., 2019, @doi [ ] 10.1093/mnras/stz2074 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.488.5251L 488, 5251

  42. [51]

    R., 2011, SIGPROC: Pulsar Signal Processing Programs , Astrophysics Source Code Library, record ascl:1107.016

    Lorimer D. R., 2011, SIGPROC: Pulsar Signal Processing Programs , Astrophysics Source Code Library, record ascl:1107.016

  43. [52]

    R., Kramer M., 2012, Handbook of Pulsar Astronomy

    Lorimer D. R., Kramer M., 2012, Handbook of Pulsar Astronomy . Cambridge University Press

  44. [53]

    A., et al., 2021, @doi [ ] 10.3847/2041-8213/ac1921 , https://ui.adsabs.harvard.edu/abs/2021ApJ...919L...6M 919, L6

    Majid W. A., et al., 2021, @doi [ ] 10.3847/2041-8213/ac1921 , https://ui.adsabs.harvard.edu/abs/2021ApJ...919L...6M 919, L6

  45. [54]

    R., Mol J

    Malenta M., et al., 2020, in Pizzo R., Deul E. R., Mol J. D., de Plaa J., Verkouter H., eds, Astronomical Society of the Pacific Conference Series Vol. 527, Astronomical Society of the Pacific Conference Series. p. 457

  46. [55]

    R., et al., 2016, @doi [ ] 10.1038/nature18620 , https://ui.adsabs.harvard.edu/abs/2016Natur.537..374M 537, 374

    Marsh T. R., et al., 2016, @doi [ ] 10.1038/nature18620 , https://ui.adsabs.harvard.edu/abs/2016Natur.537..374M 537, 374

  47. [56]

    M., 1996, in Johnston S., Walker M

    McKinnon M. M., 1996, in Johnston S., Walker M. A., Bailes M., eds, Astronomical Society of the Pacific Conference Series Vol. 105, IAU Colloq. 160: Pulsars: Problems and Progress. p. 253

  48. [57]

    J., Smith L., Bhat N

    McSweeney S. J., Smith L., Bhat N. D. R., Wright G., 2023, @doi [ ] 10.3847/1538-4357/acdcf2 , https://ui.adsabs.harvard.edu/abs/2023ApJ...952...73M 952, 73

  49. [58]

    D., Berger E., Margalit B., 2017, @doi [ ] 10.3847/1538-4357/aa633d , https://ui.adsabs.harvard.edu/abs/2017ApJ...841...14M 841, 14

    Metzger B. D., Berger E., Margalit B., 2017, @doi [ ] 10.3847/1538-4357/aa633d , https://ui.adsabs.harvard.edu/abs/2017ApJ...841...14M 841, 14

  50. [59]

    Morello V., et al., 2019, @doi [ ] 10.1093/mnras/sty3328 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.483.3673M 483, 3673

  51. [60]

    S., et al., 2023, @doi [ ] 10.1017/pasa.2023.15 , https://ui.adsabs.harvard.edu/abs/2023PASA...40...19M 40, e019

    Morrison I. S., et al., 2023, @doi [ ] 10.1017/pasa.2023.15 , https://ui.adsabs.harvard.edu/abs/2023PASA...40...19M 40, e019

  52. [61]

    B., Ingargiola A., 2014, LMFIT: Non-Linear Least-Square Minimization and Curve-Fitting for Python , @doi 10.5281/zenodo.11813

    Newville M., Stensitzki T., Allen D. B., Ingargiola A., 2014, LMFIT: Non-Linear Least-Square Minimization and Curve-Fitting for Python , @doi 10.5281/zenodo.11813

  53. [62]

    A., Kaspi V

    Olausen S. A., Kaspi V. M., 2014, @doi [ ] 10.1088/0067-0049/212/1/6 , https://ui.adsabs.harvard.edu/abs/2014ApJS..212....6O 212, 6

  54. [63]

    Olszanski T. E. E., Mitra D., Rankin J. M., 2019, @doi [ ] 10.1093/mnras/stz2172 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.489.1543O 489, 1543

  55. [64]

    Oppermann N., Yu H.-R., Pen U.-L., 2018, @doi [ ] 10.1093/mnras/sty004 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.475.5109O 475, 5109

  56. [65]

    M., Tremblay S

    Ord S. M., Tremblay S. E., McSweeney S. J., Bhat N. D. R., Sobey C., Mitchell D. A., Hancock P. J., Kirsten F., 2019, @doi [ ] 10.1017/pasa.2019.17 , https://ui.adsabs.harvard.edu/abs/2019PASA...36...30O 36, e030

  57. [66]

    V., et al., 2023, @doi [ ] 10.1093/mnras/stad1900 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.524.1291P 524, 1291

    Padmanabh P. V., et al., 2023, @doi [ ] 10.1093/mnras/stad1900 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.524.1291P 524, 1291

  58. [67]

    Pastor-Marazuela I., et al., 2023, @doi [ ] 10.1051/0004-6361/202243339 , https://ui.adsabs.harvard.edu/abs/2023A&A...678A.149P 678, A149

  59. [68]

    Pelisoli I., et al., 2023, @doi [Nature Astronomy] 10.1038/s41550-023-01995-x , https://ui.adsabs.harvard.edu/abs/2023NatAs...7..931P 7, 931

  60. [69]

    Philippov A., Kramer M., 2022, @doi [ ] 10.1146/annurev-astro-052920-112338 , https://ui.adsabs.harvard.edu/abs/2022ARA&A..60..495P 60, 495

  61. [70]

    Pilia M., et al., 2016, @doi [ ] 10.1051/0004-6361/201425196 , https://ui.adsabs.harvard.edu/abs/2016A&A...586A..92P 586, A92

  62. [71]

    Posselt B., et al., 2021, @doi [ ] 10.1093/mnras/stab2775 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.508.4249P 508, 4249

  63. [72]

    C., 2016, PyGDSM: Python interface to Global Diffuse Sky Models , Astrophysics Source Code Library, record ascl:1603.013

    Price D. C., 2016, PyGDSM: Python interface to Global Diffuse Sky Models , Astrophysics Source Code Library, record ascl:1603.013

  64. [73]

    J., Bryant J

    Rajwade K., et al., 2020, in Evans C. J., Bryant J. J., Motohara K., eds, Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series Vol. 11447, Ground-based and Airborne Instrumentation for Astronomy VIII. p. 114470J ( @eprint arXiv 2103.08410 ), @doi 10.1117...

  65. [74]

    M., et al., 2022, @doi [ ] 10.1093/mnras/stac446 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.512.1687R 512, 1687

    Rajwade K. M., et al., 2022, @doi [ ] 10.1093/mnras/stac446 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.512.1687R 512, 1687

  66. [75]

    H., et al., 2017, @doi [Journal of Astronomical Instrumentation] 10.1142/S2251171716410117 , https://ui.adsabs.harvard.edu/abs/2017JAI.....641011R 6, 1641011

    Reddy S. H., et al., 2017, @doi [Journal of Astronomical Instrumentation] 10.1142/S2251171716410117 , https://ui.adsabs.harvard.edu/abs/2017JAI.....641011R 6, 1641011

  67. [76]

    C., et al., 2025, @doi [ ] 10.1088/1538-3873/adb0f1 , https://ui.adsabs.harvard.edu/abs/2025PASP..137b4202R 137, 024202

    Rodriguez A. C., et al., 2025, @doi [ ] 10.1088/1538-3873/adb0f1 , https://ui.adsabs.harvard.edu/abs/2025PASP..137b4202R 137, 024202

  68. [77]

    W., 2018, in Weltevrede P., Perera B

    Sanidas S., Caleb M., Driessen L., Morello V., Rajwade K., Stappers B. W., 2018, in Weltevrede P., Perera B. B. P., Preston L. L., Sanidas S., eds, Vol. 337, Pulsar Astrophysics the Next Fifty Years. pp 406--407, @doi 10.1017/S1743921317009310

  69. [78]

    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

  70. [79]

    E., 1991, @doi [ ] 10.1086/170355 , https://ui.adsabs.harvard.edu/abs/1991ApJ...377..263T 377, 263

    Thorsett S. E., 1991, @doi [ ] 10.1086/170355 , https://ui.adsabs.harvard.edu/abs/1991ApJ...377..263T 377, 263

  71. [80]

    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

  72. [81]

    E., et al., 2015, @doi [ ] 10.1017/pasa.2015.6 , https://ui.adsabs.harvard.edu/abs/2015PASA...32....5T 32, e005

    Tremblay S. E., et al., 2015, @doi [ ] 10.1017/pasa.2015.6 , https://ui.adsabs.harvard.edu/abs/2015PASA...32....5T 32, e005

  73. [82]

    Van Straten W., Bailes M., 2011, @doi [ ] 10.1071/AS10021 , https://ui.adsabs.harvard.edu/abs/2011PASA...28....1V 28, 1

  74. [83]

    Wang W., Zhang B., Chen X., Xu R., 2019, @doi [ ] 10.3847/2041-8213/ab1aab , https://ui.adsabs.harvard.edu/abs/2019ApJ...876L..15W 876, L15

  75. [84]

    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

  76. [85]

    Weltevrede P., 2016, @doi [ ] 10.1051/0004-6361/201527950 , https://ui.adsabs.harvard.edu/abs/2016A&A...590A.109W 590, A109

  77. [86]

    M., Manchester R

    Yao J. M., Manchester R. N., Wang N., 2017, @doi [ ] 10.3847/1538-4357/835/1/29 , https://ui.adsabs.harvard.edu/abs/2017ApJ...835...29Y 835, 29

  78. [87]

    Zhao R.-S., et al., 2019, @doi [ ] 10.3847/1538-4357/ab05de , https://ui.adsabs.harvard.edu/abs/2019ApJ...874...64Z 874, 64

  79. [88]

    Zheng H., et al., 2017, @doi [ ] 10.1093/mnras/stw2525 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.464.3486Z 464, 3486

  80. [89]

    arXiv:2408.11536

    de Ruiter I., et al., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2408.11536 , https://ui.adsabs.harvard.edu/abs/2024arXiv240811536D p. arXiv:2408.11536

Pith tools

Reviewed August 15, 2026 · model on record in the stance chip above.