Pith. sign in

REVIEW 5 major objections 5 minor 47 references

Single-Pulse Morphology of PSR J1935+1616 (B1933+16) Based on archival data from FAST

T0 review · 5 major / 5 minor · reviewed 2026-08-07 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗ Review JSON

Pith's one-line read Archival FAST observations of PSR J1935+1616 find that 9.69% of single pulses contain micropulses with a characteristic width of about 128 microseconds, that roughly half of those are quasi-periodic at about 232 microseconds, and that…

desk verdict A useful single-pulsar study with new FAST-era measurements, but the headline timescales rest on a detection pipeline that lacks null tests and sits near the resolution limit. read the letter →

arxiv 2502.09342 v1 pith:XA2ZVYLD submitted 2025-02-13 astro-ph.HE

R.W. Tian , R.S. Zhao , Marilyn Cruces , H. Liu , D. Li , P. Wang , C.H. Niu , Biping Gong
show 10 more authors
C.C. Miao X. Zhu H.W. Xu W.L. Li S.D. Wang Z.F. Tu Q.J. Zhi S.J. Dang L.H. Shang S. Xiao
This is my paper · ORCID
classification astro-ph.HE
keywords single-pulsemorphologymicropulsesquasi-periodicPSRJ1935+1616pulsarmodechangingcircularpolarizationpulseenergydistributionFAST
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

Archival FAST observations of PSR J1935+1616 reveal that 9.69% of 9,998 single pulses contain microstructure: 969 pulses have characteristic micropulse widths of $127.63^{+70.74}_{-46.25}$ microseconds, and 520 of those pulses show quasi-periodic micropulses with a period of $231.77 \pm 9.90$ microseconds. The same short-timescale structure appears in circular polarization in 208 pulses, with a period of $244.70^{+45.66}_{-21.05}$ microseconds and a width of $106.52 \pm 46.14$ microseconds. The pulses separate into four morphological modes (A, B, C, D) based on the strength of the leading and trailing profile components; micropulse-bearing pulses are most common in mode A (562 of 3893) and rarest in mode D (20 of 819). If correct, these numbers establish intrinsic emission timescales for this pulsar and tie the microstructure mechanism to the mechanism that switches single-pulse profile morphology.

What carries the argument

The machinery is a time-series decomposition of each single pulse: a fifth-order polynomial fit defines the smooth sub-pulse envelope, and subtracting it leaves a residual that should contain any microstructure. The residual is then characterized three ways: an autocorrelation function (ACF), whose slope break and oscillation troughs identify width and quasi-period; the power spectrum of the residual (PSD); and the power spectrum of the ACF derivative (ADP), whose Gaussian peaks give the quasi-frequency. The ACF slope break near 106.5 microseconds and the PSD/ADP peaks near 3.9 kHz are the observable signatures that convert raw intensities into the claimed width and quasi-period. Micropulse widths are assigned with the second central moment of each fluctuation. This chain is what carries the argument from raw intensity time series to the quoted timescales.

What would settle it

Re-analyze the same 9,998 FAST single pulses without the fifth-order polynomial envelope subtraction, using an alternative high-pass filter and an independent de-dispersion and RFI-excision chain: if the ACF slope break near 106.5 microseconds and the PSD/ADP peaks near 3.9 kHz disappear or shift by more than the quoted uncertainties, then the claimed micropulse width and quasi-period are artifacts of the processing chain. A faster-sampled follow-up observation, for example at 10-microsecond resolution, should resolve the same 127-microsecond widths and 232-microsecond periods if they are intrinsic.

Watch

Extended reading notes

Core claim

The paper's central discovery is that PSR J1935+1616, observed for one hour with FAST at 1250 MHz and 49.512-microsecond sampling, produces a population of single pulses whose sub-pulse envelopes contain short-timescale intensity fluctuations that are not noise. Using an established identification method, 969 of 9,998 pulses (9.69%) were classified as containing micropulses; their widths, measured by the second central moment of each fluctuation, follow a log-normal distribution with characteristic width $127.63^{+70.74}_{-46.25}$ microseconds. In 520 of these pulses the fluctuations are quasi-periodic, with a single-Gaussian period distribution centered at $231.77 \pm 9.90$ microseconds, and in 208 pulses the circular-polarization fluctuations are also quasi-periodic at $244.70^{+45.66}_{-21.05}$ microseconds. The pulses classified into morphological modes A through D differ in energy distribution: mode A follows a double Gaussian, while modes B, C, and D follow a single Gaussian; the fraction of micropulse-bearing pulses differs across modes, from 562 of 3893 in mode A down to 20 of 819 in mode D. The paper concludes that micropulse emission is a real, quasi-periodic emission component and that its occurrence is coupled to the pulsar's single-pulse morphology.

Load-bearing premise

The load-bearing premise is that after 49.512-microsecond sampling, de-dispersion, and radio-frequency-interference cleaning, the true short-timescale structure is not broadened or destroyed by scattering or smearing, and that the fifth-order polynomial smoothing plus ACF/PSD residual analysis neither creates nor suppresses the features.

Editorial extensions

If this is right

  • If the claim is correct, the 127.63-microsecond width and 231.77-microsecond quasi-period are intrinsic to the pulsar's emission process, so any viable micropulse mechanism must produce these timescales at 1250 MHz.
  • The measured quasi-period is shorter than the earlier $0.4 \pm 0.2$ ms reported at 1.5 and 4.5 GHz, implying that either the quasi-period is frequency-dependent or the earlier measurements were limited by coarser sampling.
  • The waiting-time distribution of micropulse-bearing pulses is Weibull with shape $k = 0.66$, meaning micropulse production is clustered in time rather than following a simple Poisson process.
  • Pulse-energy distributions separate cleanly: mode A and micropulse-bearing pulses show double-Gaussian energy, while modes B, C, and D show single-Gaussian energy, confirming that the four-mode morphological scheme captures a real physical distinction.
  • The rarity of micropulses in mode D (20 of 819) and their prevalence in mode A (562 of 3893) implies that the same magnetospheric condition that suppresses the outer profile components also favors the production of microstructure.

Reading between the lines

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

  • Extension beyond the paper: because the quoted 127.63-microsecond width is only about 2.6 times the 49.512-microsecond sampling interval, the true intrinsic widths may be narrower; a faster-sampled observation of J1935+1616 would test whether 127 microseconds is a resolution-broadened upper limit.
  • Extension beyond the paper: the hint of phase-locked microstructure seen in the folded micropulse profile, if real, would be a new phenomenon; it could be tested by stacking many micropulse-selected pulses and checking whether the modulation phase is stable across rotation phases and observation epochs.
  • Extension beyond the paper: searching FAST archive data at other radio frequencies for the 231.77-microsecond quasi-period would discriminate between a geometric origin, which should be frequency-independent, and a plasma-propagation origin, which should not.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

5 major / 5 minor

Summary. The paper analyzes 9,998 single pulses of PSR J1935+1616 from FAST archival data. It reports that 969 pulses (9.69%) contain micropulses with characteristic width 127.63(+70.74/-46.25) microsec, that 520 of these show quasi-periodic micropulses with period 231.77 +/- 9.90 microsec, and that micropulse occurrence is highest in morphological mode A and lowest in mode D. Additional results concern circular-polarization quasi-periodicity (244.70 microsec), single-pulse energy distributions described by single or double Gaussians, waiting-time statistics, and polarization fractions. The data reduction uses DSPSR/PSRCHIVE; the microstructure analysis is based on a fifth-order polynomial residual method with ACF/PSD analysis, as described in Sections 2 and 3.1.1.

Significance. If the timescale measurements are reliable, the paper would provide one of the few large-sample measurements of micropulse microstructure in a normal pulsar, plus a possible coupling between microstructure and single-pulse morphology. Strengths include the use of high-sensitivity FAST archival data, the large number of single pulses, the explicit data-processing description, and the presentation of quantitative distributions for widths, periods, energies, and polarization. The main caveat is that the short-timescale quantities are near the 49.512 microsec sampling limit and are not validated by noise-only or injection-recovery tests, so the central claim of intrinsic micropulse timescales is not yet fully supported.

major comments (5)
  1. [Section 3.1.1, Eq. (1)] The central claim that the observed residuals correspond to intrinsic micropulses is not validated. At 49.512 microsec sampling, the reported width of 127.63 microsec spans only ~2.6 samples and the reported quasi-period of 231.77 microsec spans ~4.7 samples. The fifth-order polynomial residual method can produce quasi-oscillatory residuals when fitting a smooth envelope to a three-component profile, and the paper gives no test on noise-only pulses, no injection-recovery of synthetic micropulses with known width and period, and no estimate of dispersion-smearing or scattering timescales at 1250 MHz. Without such controls, the measured width and period cannot be distinguished from an artifact of the smoothing procedure. Please add a null test using off-pulse noise and an injection-recovery test, and quantify the smearing timescales.
  2. [Section 3.1.1] The criterion for classifying a single pulse as containing micropulses is not defined quantitatively. The statement that 'The ACF curve of the residuals shows a change in slope at 106.5 microsec, indicating the presence of microstructures' is not an operational detection rule. The fraction 969/9998 is therefore not reproducible without the specific code and thresholds. Please specify the algorithm, including how a 'change in slope' is detected and how the 'significant periodic components' are identified in the PSD and ADP.
  3. [Section 3.2 / Table 3] The statement that normal pulses (NP) follow a single Gaussian energy distribution is inconsistent with Table 3, which lists S1 parameters for NP (A=0.0017, mu=0.4000, sigma=0.1200). Since the single- versus double-Gaussian distinction is a central result, the paper must report a formal model comparison (e.g., likelihood-ratio test or BIC) showing that the S1 component is insignificant for NP and significant for MP and mode A. Similarly, the phrase 'significantly different' for mode A versus other modes is not supported by any statistical test.
  4. [Section 3.1.1] The K-S test results are reported incorrectly. The text states 'Dn = 0.59 > 0.05 and P = 0 < 0.05', which compares the test statistic to the significance level rather than to the proper critical value, and the same issue occurs in the second K-S test. The test statistic should be compared to critical values that depend on the sample sizes, and p-values should be reported with a finite nonzero value or a clear threshold statement. Please redo these tests and state the sample sizes used.
  5. [Section 3.2 / Table 2] The claimed correlation between micropulse occurrence and morphological mode may be influenced by pulse brightness, because micropulse detection requires resolving short-timescale fluctuations and is easier in higher-S/N pulses. Mode A has a relatively strong central component and mode D has the weakest central component, so the trend in MP fractions could partly reflect S/N rather than a physical coupling. To support conclusion 4, please test whether the MP fraction depends on mode after matching single-pulse energy or by including energy as a covariate.
minor comments (5)
  1. [Section 3.1.3] The word 'tatol' should be 'total'.
  2. [Section 3.1.1] 'Fllowing' should be 'Following'; 'Usingthe first minimumminimal' should be rewritten as a complete phrase; and 'M_i is the the amplitude' contains a duplicated article.
  3. [Figure 6 caption] The caption says 'PSR J1933+1616' but the paper consistently refers to PSR J1935+1616.
  4. [Section 5 / Conclusion 1] The statement 'Approximately 5.20% of these single pulses with micropulses exhibit quasi-periodicity' is inconsistent with the numbers: 520 is 5.20% of the total 9,998 pulses, not of the 969 micropulse-containing pulses. The fraction of MP pulses with quasi-periodicity is about 53.7%.
  5. [Section 3.1.2] The high-pass filtering used to remove red noise is mentioned only briefly, without specifying the filter type or cutoff. Please provide enough detail for reproducibility.

Circularity Check

0 steps flagged · score 1.0 of 10

No significant circularity: micropulse measurements are direct statistics from FAST data; the only self-citation supplies the analysis recipe, not the result.

full rationale

The paper is descriptive and observational. The central quantities—969 pulses with microstructure (9.69%), characteristic width 127.63(+70.74/−46.25) µs, and quasi-period 231.77 ± 9.90 µs—are obtained by applying Eq. (1) and ACF/PSD analysis directly to the de-dispersed, RFI-cleaned single pulses. These measurements do not derive from a theoretical model, and they are not fitted to the same statistic they are claimed to predict. The mode classification (A, B, C, D) is defined independently of the micropulse detection: modes are based on the peak intensities of the leading (C1) and trailing (C3) components relative to 10×rms of the off-pulse, whereas MP classification is based on residual timescale structure after fifth-order polynomial smoothing. The reported MP occurrence fractions per mode (e.g., 562/3893 in mode A and 20/819 in mode D) are simple contingency counts, not quantities forced by the definitions. The only self-citation is to Zhao et al. (2023) for the analysis recipe ('Fllowing the method in Zhao et al. (2023)'), but that citation supplies a signal-processing procedure, not the empirical result, and the measured values are new and data-derived. Concerns about the 49.512 µs sampling time, dispersion smearing, or the residual method potentially creating artifacts are validity and robustness issues, not circularity: even if the analysis pipeline were flawed, the flaw would be an error, not a logical reduction of the conclusion to its inputs. The paper also checks consistency with prior independent measurements (e.g., Popov et al. 2002b's ~150 µs width), further supporting that the result is not defined into existence. Therefore the circularity score is low.

Assumptions & free parameters 7 free parameters · 6 assumptions · 0 invented entities

The central claims rest on adopted statistical models and thresholds: Gaussian/log-normal fits for widths and periods, a 10-rms threshold for mode classification, a 3-rms threshold for pulse energy, and the smoothing/ACF method for isolating micropulses. No new physical entities or conserved quantities are introduced, and no equations are derived; the paper is a measurement paper.

free parameters (7)
  • Quasi-periodic micropulse period in total intensity = 231.77 +/- 9.90 us
    Gaussian fit to the period histogram of 520 QMPs (Figure 2a); this is the central quoted period.
  • Quasi-periodic micropulse period in circular polarization = 244.70 (+45.66/-21.05) us
    Fit to the circular-polarization quasi-period distribution (Figure 2b).
  • Micropulse characteristic width in total intensity = 127.63 (+70.74/-46.25) us
    Log-normal fit to the width distribution from the second central moment (Figure 3a).
  • QMP width from ACF first minimum = 97.63 +/- 10.42 us
    Statistical estimate of widths for the 520 QMPs (Figure 3b).
  • Micropulse characteristic width in circular polarization = 106.52 +/- 46.14 us
    Gaussian fit to widths of circularly polarized micropulses (Figure 11).
  • Weibull waiting-time parameters = k=0.66 +/- 0.02, beta=10.32 +/- 0.32, theta=1.69 +/- 0.09
    Maximum-likelihood fit to waiting times between micropulse single pulses (Figure 4).
  • Energy distribution Gaussian components (S1/S2) = MP S1: A=0.011, mu=0.48, sigma=0.10; S2: A=0.070, mu=0.97, sigma=0.168
    Two-Gaussian fits to relative energy histograms for MP/NP/TP and modes (Table 3, Figures 6 and 10).
assumptions (6)
  • domain assumption Gaussian, log-normal, and Weibull functional forms describe the observed distributions of widths, periods, waiting times, and energies.
    Used throughout Section 3; no physical model is given for these forms, so the fitted peaks are only summaries of the data.
  • domain assumption A 10-rms off-pulse threshold is a valid separator of the four single-pulse morphology modes.
    Section 3.2 mode definitions; the threshold is data-defined and no validation against alternative thresholds is provided.
  • domain assumption Fifth-order polynomial smoothing separates the subpulse envelope from micropulse residuals without introducing timescales.
    Section 3.1.1 and Figure 1; the residual method is the basis for all width and period measurements.
  • domain assumption FAST data at 49.512 microsecond sampling and 1250 MHz are not significantly broadened by scattering or dispersion smearing at the measured timescales.
    Section 2 states the sampling time but no scattering or smearing correction is presented, despite 127 microsecond features being only about 2.6 samples wide.
  • domain assumption Off-pulse noise is Gaussian and the 3-rms threshold defines single-pulse energy.
    Section 3.1.2 uses the sum of flux above 3-rms as pulse energy; no tests of threshold dependence are given.
  • standard math DSPSR and PSRCHIVE correctly fold and calibrate the FAST search-mode data.
    Section 2 relies on these tools for dedispersion, folding, and RFI removal; no independent verification of the folded profiles is provided.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Single-Pulse Morphology of PSR J1935+1616 (B1933+16) Based on archival data from FAST." pith.science (2026). https://pith.science/paper/XA2ZVYLD

@misc{pith2026250209342,
  author       = {Pith},
  title        = {Pith review of: Single-Pulse Morphology of PSR J1935+1616 (B1933+16) Based on archival data from FAST},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/XA2ZVYLD}},
  note         = {Machine review of arXiv:2502.09342}
}
abstract

We utilized archived data from the Five-hundred-meter Aperture Spherical Radio Telescope (FAST) to analyze the single-pulse profile morphology of PSR J1935$+$1616 (B1933$+$16). The results show that PSR J1935$+$1616 exhibits significant micropulses as well as various changes in single-pulse profile morphology. In the FAST archived data, a total of 969 single pulses with microstructure were identified, accounting for 9.69$\%$ of the total pulse sample, with characteristic widths of $127.63^{+70.74}_{-46.25}$ $\mu$s. About half of these pulses display quasiperiodic micropulses, with a periodicity of 231.77 $\pm$ 9.90 $\mu$s. Among the 520 single pulses with quasiperiodic microstructure, 208 also exhibit quasiperiodicity in circular polarization, with a characteristic period of $244.70^{+45.66}_{-21.05}$ $\mu$s. The micropulse characteristic width in circular polarization is 106.52 $\pm$ 46.14 $\mu$s. Compared to normal pulses, the relative energy (E/<E>) of single pulse with microstructure follows a double Gaussian distribution, while that of normal pulses follows a single Gaussian distribution. Based on the intensity of the leading and trailing components in the single-pulse profile morphology of PSR J1935+1616, we classified the pulses into four morphological modes (A, B, C, and D). The relative energy distribution of pulses in mode A is significantly different from the others, following a double Gaussian distribution, while the relative energy distributions in modes B, C, and D follow a single Gaussian distribution. Our study also suggests a possible correlation between micropulses and single-pulse profile morphology. Single pulse with micropulses are most likely to occur in mode A, while their occurrence is least likely in mode D.

Figures

Figures reproduced from arXiv: 2502.09342 by the authors.

Figure 1
Figure 1. Pulse No.789: (a) The black solid line shows the profile of the single pulse, the red solid line represents the smoothed envelope of the corresponding subpulse, and the blue solid line represents the residual after subtracting the smoothed envelope from the single pulse profile. (b) The relationship between the autocorrelation function (ACF) of the single pulse and the residuals with the time lag is shown. The black… view at source ↗
Figure 2
Figure 2. (a) The histograms illustrate the periodicity distribution of microstructures based on 520 single pulses containing quasiperiodic micropulses. The red solid line represents the best Gaussian fit. (b) The red solid line represents the best logarithmic function fit, showing the quasiperiodic distribution of 207 QMPs in circular polarization. In both panels, the blue dashed line marks the peak position of the fitted cu… view at source ↗
Figure 3
Figure 3. (a) The width distribution of micropulses in PSR J1935+1616, with the red solid line representing the log-normal distribution fit and the blue dashed line indicating the peak position. (b) The width distribution of micropulses for 520 single pulses with quasi-periodic micropulses. The red solid line represents the Gaussian fit, and the blue dashed line indicates the peak position. For both panels, the top right corn… view at source ↗
Figures from the paper (10 more)
Figure 4
Figure 4. Figure 4: Fits to the waiting time distribution of 969 MPs from PSR J1935+1616 considering a power-law distribution (green curve), Weibull distribution (red curve), and exponential distribution (blue curve), with the main parameters of the Weibull distribution labeled above the …
Figure 5
Figure 5. Figure 5: The 9,998 single pulses of PSR J1935+1616 are represented as a binary time series resembling 1 and 0. The upper panel shows 200 of these pulses, with red dots indicating MPs (marked as 1) and green dots indicating normal pulses (marked as 0). The lower panel displays t…
Figure 6
Figure 6. Figure 6: Histograms of the energy distributions for MP, normal pulses (NP), and total pulses (TP) of PSR J1933+1616. The black histograms represent the pulse energy distributions, the green dashed lines represent single Gaussian fit curves, and the red curves are the envelope o…
Figure 7
Figure 7. Figure 7: The upper plot illustrates the polarization position angles (PPA) of MP, NP, and TP. The lower plot shows the integrated profiles of polarization intensity, linear polarization, and circular polarization for MP, NP, and TP. Additionally, four inset plots provide zoomed…
Figure 8
Figure 8. Figure 8: The polarization fractions of different types of pulses in PSR J1935+1616 where 𝐿/𝐼 denotes linear polarization, and 𝑉/𝐼 denotes circular polarization. TP stands for total pulses, NP stands for normal pulses, MP stands for single pulse with micropulses, and QMP stands …
Figure 9
Figure 9. Figure 9: Categorization of modes A,B,C and D for PSRJ1935+1616 based on the integrated profile. The red curve (AP) represents the overall average profile of PSR J1935+1616, the cyan curve (A) represents the average profile for mode A, the blue curve (B) represents mode B, the y…
Figure 10
Figure 10. Figure 10: Based on the four single-pulse profile morphological modes (A, B, C, and D) of PSR J1935+1616, we analyzed the single-pulse energy distribution for each mode and performed Gaussian fits. The energy histograms are labeled with their respective mode names. The green his…
Figure 11
Figure 11. Figure 11: The histogram presents the width distribution of 969 single-pulse circularly polarized micropulses containing micropulses. The red solid line represents the best Gaussian fit, while the blue dashed line indicates the peak position of the Gaussian fit. The upper right …
Figure 12
Figure 12. Figure 12: The statistical distribution and percentage trends of 969 MPs and 9,998 single pulses (TP) of PSR J1935+1616 across the four single-pulse morphologies (A, B, C, and D), with specific parameters detailed in [PITH_FULL_IMAGE:figures/full_fig_p014_12.png]
Figure 13
Figure 13. Figure 13: (a) Correspond to the energy histogram distribution of all pulses in Mode A (black histogram), which ANP represents the energy histogram distribution of normal pulses in Mode A (green histogram). The green dashed lines indicate the single Gaussian fit in the S1 and S2…

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

47 extracted references · 22 canonical work pages

  1. [1]

    , " * write output.state after.block = add.period write newline

    ENTRY address archivePrefix author booktitle chapter doi edition editor eprint howpublished institution journal key month number organization pages publisher school series title misctitle type volume year version url label extra.label sort.label short.list INTEGERS output.state before.all mid.sentence after.sentence after.block FUNCTION init.state.consts ...

  2. [2]

    write newline

    " write newline "" before.all 'output.state := FUNCTION format.url url empty "" new.block "" url * "" * if FUNCTION format.eprint eprint empty "" archivePrefix empty "" archivePrefix "arXiv" = new.block " " eprint * " " * new.block " " eprint * " " * if if if FUNCTION format.doi doi empty "" " " doi * " " * if FUNCTION format.pid doi empty eprint empty ur...

  3. [4]

    Backer , D. C. 1970, , 228, 1297, 10.1038/2281297a0

    doi:10.1038/2281297a0 1970

  4. [5]

    Bartel , N., Morris , D., Sieber , W., & Hankins , T. H. 1982, , 258, 776, 10.1086/160125

    doi:10.1086/160125 1982

  5. [6]

    Basu, R., Mitra, D., & Melikidze, G. I. 2023, The Astrophysical Journal, 959, 92

    work page 2023

  6. [7]

    C., & Slater , G

    Boriakoff , V., Ferguson , D. C., & Slater , G. 1981, in Pulsars: 13 Years of Research on Neutron Stars, ed. W. Sieber & R. Wielebinski , Vol. 95, 199--204

    work page 1981

  7. [8]

    1982, Astronomical Journal, vol

    Burstein, D., & Heiles, C. 1982, Astronomical Journal, vol. 87, Aug. 1982, p. 1165-1189. NSF-supported research., 87, 1165

    work page 1982

  8. [9]

    L., Wen , Z

    Chen , J. L., Wen , Z. G., Hao , L. F., et al. 2020, , 899, 118, 10.3847/1538-4357/aba2e8

    work page doi:10.3847/1538-4357/aba2e8 2020

Show all 47 references
  1. [10]

    Chian , A. C. L., & Kennel , C. F. 1983, , 97, 8

    1983

  2. [11]

    M., Weisberg , J

    Cordes , J. M., Weisberg , J. M., & Hankins , T. H. 1990, , 100, 1882, 10.1086/115644

    1990 doi

  3. [12]

    H., Eilek , J

    Crossley , J. H., Eilek , J. A., Hankins , T. H., & Kern , J. S. 2010, , 722, 1908, 10.1088/0004-637X/722/2/1908

    2010 doi

  4. [13]

    D., & Craft , H

    Drake , F. D., & Craft , H. D. 1968, , 220, 231, 10.1038/220231a0

    1968 doi

  5. [14]

    1982, Astronomy and Astrophysics, vol

    Fowler, L., & Wright, G. 1982, Astronomy and Astrophysics, vol. 109, no. 2, May 1982, p. 279-281. Research supported by the Alexander von Humboldt-Stiftung and Universitaet Bonn., 109, 279

    1982

  6. [15]

    A., & Snakowski , J

    Gil , J. A., & Snakowski , J. K. 1990, , 234, 237

    1990

  7. [16]

    2003, Nature, 422, 141

    Hankins, T., Kern, J., Weatherall, J., & Eilek, J. 2003, Nature, 422, 141

    2003

  8. [17]

    Hankins , T. H. 1971, , 169, 487, 10.1086/151164

    1971 doi

  9. [18]

    1972, , 177, L11, 10.1086/181043

    ---. 1972, , 177, L11, 10.1086/181043

    1972 doi

  10. [19]

    K., & Tademaru , E

    Harding , A. K., & Tademaru , E. 1979, , 233, 317, 10.1086/157392

    1979 doi

  11. [20]

    W., van Straten , W., & Manchester , R

    Hotan , A. W., van Straten , W., & Manchester , R. N. 2004, , 21, 302, 10.1071/AS04022

    2004 doi

  12. [21]

    2002, , 334, 523, 10.1046/j.1365-8711.2002.05478.x

    Kramer , M., Johnston , S., & van Straten , W. 2002, , 334, 523, 10.1046/j.1365-8711.2002.05478.x

    2002

  13. [22]

    D., Hamilton , P

    Kuzmin , A. D., Hamilton , P. A., Shitov , Y. P., et al. 2003, , 344, 1187, 10.1046/j.1365-8711.2003.06900.x

    2003

  14. [23]

    1998, , 332, 111

    Lange , C., Kramer , M., Wielebinski , R., & Jessner , A. 1998, , 332, 111

    1998

  15. [24]

    2018, IEEE Microwave Magazine, 19, 112, 10.1109/MMM.2018.2802178

    Li , D., Wang , P., Qian , L., et al. 2018, IEEE Microwave Magazine, 19, 112, 10.1109/MMM.2018.2802178

    2018

  16. [25]

    1971, Monthly Notices of the Royal Astronomical Society, 153, 27P

    Lyne, A. 1971, Monthly Notices of the Royal Astronomical Society, 153, 27P

    1971

  17. [26]

    2012, Pulsar astronomy No

    Lyne, A., & Graham-Smith, F. 2012, Pulsar astronomy No. 48 (Cambridge University Press)

    2012

  18. [27]

    G., & Manchester , R

    Lyne , A. G., & Manchester , R. N. 1988, , 234, 477, 10.1093/mnras/234.3.477

    1988 doi

  19. [28]

    N., Hobbs , G

    Manchester , R. N., Hobbs , G. B., Teoh , A., & Hobbs , M. 2005, , 129, 1993, 10.1086/428488

    2005 doi

  20. [29]

    J., Bhat , N

    McSweeney , S. J., Bhat , N. D. R., Swainston , N. A., et al. 2022, , 933, 210, 10.3847/1538-4357/ac75bc

    2022 doi

  21. [30]

    Mitra , D., Arjunwadkar , M., & Rankin , J. M. 2015, , 806, 236, 10.1088/0004-637X/806/2/236

    2015 doi

  22. [31]

    2016, , 460, 3063, 10.1093/mnras/stw1186

    Mitra , D., Rankin , J., & Arjunwadkar , M. 2016, , 460, 3063, 10.1093/mnras/stw1186

    2016 doi

  23. [32]

    1981, Monthly Notices of the Royal Astronomical Society, 194, 7P

    Morris, D., Graham, D., & Bartel, N. 1981, Monthly Notices of the Royal Astronomical Society, 194, 7P

    1981

  24. [33]

    2011, International Journal of Modern Physics D, 20, 989, 10.1142/S0218271811019335

    Nan , R., Li , D., Jin , C., et al. 2011, International Journal of Modern Physics D, 20, 989, 10.1142/S0218271811019335

    2011 doi

  25. [34]

    Petrova , S. A. 2004, , 424, 227, 10.1051/0004-6361:20047171

    2004 doi

  26. [35]

    V., Bartel , N., Cannon , W

    Popov , M. V., Bartel , N., Cannon , W. H., et al. 2002 a , , 396, 171, 10.1051/0004-6361:20021402

    2002 doi

  27. [36]

    2002 b , Astronomy Reports, 46, 206, 10.1134/1.1463098

    ---. 2002 b , Astronomy Reports, 46, 206, 10.1134/1.1463098

    2002 doi

  28. [37]

    Rankin , J. M. 1983, , 274, 359, 10.1086/161451

    1983 doi

  29. [38]

    2022, Monthly Notices of the Royal Astronomical Society, 509, 2507

    Rejep, R., Wang, N., Yan, W., & Wen, Z. 2022, Monthly Notices of the Royal Astronomical Society, 509, 2507

    2022

  30. [39]

    2023, Monthly Notices of the Royal Astronomical Society, 527, 2612, 10.1093/mnras/stad3334

    Singh, S., Gupta, Y., & De, K. 2023, Monthly Notices of the Royal Astronomical Society, 527, 2612, 10.1093/mnras/stad3334

    2023 doi

  31. [40]

    2022, Research in Astronomy and Astrophysics, 22, 075013, 10.1088/1674-4527/ac71a5

    Tong, H., & Wang, H.-G. 2022, Research in Astronomy and Astrophysics, 22, 075013, 10.1088/1674-4527/ac71a5

    2022 doi

  32. [41]

    2011, , 28, 1, 10.1071/AS10021

    van Straten , W., & Bailes , M. 2011, , 28, 1, 10.1071/AS10021

    2011 doi

  33. [42]

    2007, Monthly Notices of the Royal Astronomical Society, 377, 1383

    Wang, N., Manchester, R., & Johnston, S. 2007, Monthly Notices of the Royal Astronomical Society, 377, 1383

    2007

  34. [43]

    2016, Astronomy & Astrophysics, 592, A127

    Wen, Z., Wang, N., Yuan, J., et al. 2016, Astronomy & Astrophysics, 592, A127

    2016

  35. [44]

    G., Yuen , R., Wang , N., et al

    Wen , Z. G., Yuen , R., Wang , N., et al. 2021, , 918, 57, 10.3847/1538-4357/ac0e90

    2021 doi

  36. [45]

    Wheatland , M. S. 2000, in AAS/Solar Physics Division Meeting, Vol. 31, AAS/Solar Physics Division Meeting \#31, 02.56

    2000

  37. [46]

    X., Liu , J

    Xu , R. X., Liu , J. F., Han , J. L., & Qiao , G. J. 2000, , 535, 354, 10.1086/308824

    2000 doi

  38. [47]

    2022, Research in Astronomy and Astrophysics, 22, 124002, 10.1088/1674-4527/ac98f7

    Zhang , Y.-K., Wang , P., Feng , Y., et al. 2022, Research in Astronomy and Astrophysics, 22, 124002, 10.1088/1674-4527/ac98f7

    2022 doi

  39. [48]

    2023, , 521, 2298, 10.1093/mnras/stad590

    Zhao , R., Li , D., Hobbs , G., et al. 2023, , 521, 2298, 10.1093/mnras/stad590

    2023 doi

Pith tools

Reviewed August 7, 2026 · model on record in the stance chip above.