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Gamma-ray Pulsar Emission is Mostly Stable on Timescales from Minutes to Years

T0 review · 2 major / 5 minor · reviewed 2026-08-05 · deepseek-v4-flash

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Pith's one-line read Gamma-ray pulsars hold their brightness steady for years, a 115-pulsar study finds.

desk verdict A careful matched-filter search that rules out strong quasiperiodic switching in 115 gamma-ray pulsars; the 'mostly stable' headline is real but narrower than the abstract says. read the letter →

arxiv 2508.18195 v1 pith:DCB7JBM4 submitted 2025-08-25 astro-ph.HE

Matthew Kerr This is my paper
classification astro-ph.HE
keywords gamma-raypulsarspulsarmagnetospheresfluxvariabilitystateswitchingFermiLATmatchedfilterBayesianblocksspindownpower
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 tries to establish that the gamma-ray brightness of pulsars barely changes on any timescale from about ten minutes to years, and that most radio state changes are not mirrored by changes in gamma-ray flux. It develops a statistical search that can spot faint, quasi-periodic switches in flux even when individual photons cannot be cleanly assigned to the pulsar. Applied to the 115 brightest gamma-ray pulsars observed by Fermi LAT over 15.6 years, the search finds no new instances of state changes and limits flux swings to below 10 percent for most of the sample, with the best cases restricted to 1 percent or less. If correct, this means a gamma-ray pulsar's magnetosphere normally stays in a single configuration or a narrow range of configurations with nearly constant power output, and the known case of PSR J2021+4026 is unique. The result directly constrains theories of how pulsar magnetospheres switch between states.

What carries the argument

The central object is the matched-filter statistic C^2_D, built from the response function R(f): the expected power spectrum that a candidate flux-modulation process would produce after convolution with Fermi's exposure window. R(f) is computed by simulating the proposed two-state process many times and averaging the resulting spectra; C^2_D then weights the observed power spectrum by R(f), collecting spectral leakage that a plain peak search would miss. The variability model is an asymmetric, quasi-periodic square wave parameterized by modulation M, asymmetry A, and randomness Q, whose power-spectrum templates are approximated for four values of |A| and a grid of spectral widths. This machi

What would settle it

Re-analyze the marginal candidate PSR J0613-0200 with pulse-phase weighting and full background modeling: if its roughly 33/day quasi-periodic excess survives above 7 sigma, the claim that fast state changes are absent in the sample is wrong for at least one pulsar. Separately, compute R(f) for a state-switching process with unbounded residence times; if it yields a flat spectrum, the paper's limits do not cover the most aperiodic switching models.

Watch

Extended reading notes

Core claim

The central claim is that gamma-ray pulsar flux state changes are neither widespread nor strong. Using a two-state quasiperiodic square-wave model, parameterized by modulation strength M, asymmetry A, and randomness Q, the author builds matched filters that gather the power a true periodic signal would leak across Fermi's complicated exposure window. The search spans timescales from about 10 minutes to a few days, after slow variations are modeled and filtered with Bayesian blocks. No new state changes are found: slow flux variability is limited to the 10 percent level across the sample, fast variability to roughly 10-20 percent for nearly periodic switching, and full nulling is excluded in

Load-bearing premise

The search assumes real state-switching would leave a non-flat power spectrum, so a process whose states last for unbounded, aperiodic times could hide completely and the reported stability limits would not apply.

Editorial extensions

If this is right

  • If gamma-ray flux traces spindown power, gamma-ray pulsars spend essentially all of their time in a force-free magnetosphere state, with excursions limited to 1-10 percent.
  • PSR J2021+4026 remains the only known gamma-ray flux state changer, so any general theory of pulsar state changing must explain why this pulsar is unique among the brightest 115.
  • The 0.1-10 percent spindown variations seen in radio pulsar timing are not accompanied by comparable gamma-ray flux changes on short timescales, suggesting those variations either operate on longer timescales or occur in regions that do not affect the gamma-ray-emitting magnetosphere.
  • Substantial nulling of gamma-ray emission is excluded for nearly all of the sample, so gamma-ray pulsars do not null the way some radio pulsars do.
  • Pulse-phase weighting should improve sensitivity by more than a factor of 3, allowing the best limits to be pushed below 1 percent and enabling searches for pulse-profile shape variations.

Reading between the lines

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

  • The reported limits apply only to switching that is at least quasi-periodic; a magnetosphere that switched on unbounded, aperiodic residence times would leave a flat power spectrum and escape the matched filter, so the 'mostly stable' conclusion may not cover the most irregular state-changing process.
  • If flux variations track spindown power, gamma-ray-bright pulsars' spin-down is now constrained to be stable on minute-to-day timescales, a new restriction on models that locate state-changing mechanisms near the polar cap rather than in the outer magnetosphere.
  • The marginal fast-variability candidates, such as PSR J0613-0200 at about 33/day and PSR J1658-5324, are natural targets for the proposed pulse-phase-resolved analysis; if one survives full background modeling, the sample would not be perfectly stable.
  • The same two-stage matched-filter framework could be extended to other Fermi LAT source classes, such as blazars or binary systems, where exposure leakage similarly limits searches for quasi-periodic flux modulation.
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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

2 major / 5 minor

Summary. The paper develops a two-stage search for flux variability in 115 bright gamma-ray pulsars using Fermi-LAT photon weights. Slow variability (timescales >= 2 weeks) is modeled and filtered with Bayesian blocks; fast variability (down to ~10 min) is searched with matched-filter statistics built from simulated response functions for a two-state quasiperiodic square-wave process with bounded random state durations. The author reports no confirmed new state changes, gives upper limits on modulation amplitude for the model family (typically <10%, and <=1% for the best cases), and interprets the null results as evidence that gamma-ray pulsar magnetospheres maintain a nearly constant single configuration. The paper is careful about exposure systematics (Appendix B), trial accounting, and sensitivity calibration, and it explicitly acknowledges in Section 7 that a state-switching process with unbounded residence times would evade the search.

Significance. If the central claim holds, this is a valuable ensemble result: it places the first sub-hour flux-variability constraints on a large sample of gamma-ray pulsars and substantially extends the parameter space probed by earlier slow-variability and single-pulse searches. The method itself is a useful contribution: the matched-filter aggregation of leaked power (Eq. 5) and the explicit response-function construction are sound, and the validation with injected signals (Figure 3) and the percent-level exposure agreement (Appendix B) are strengths. The upper limits on two-state quasiperiodic switching, especially the exclusion of strong nulling over most of the sample, are a concrete falsifiable result. The paper's astrophysical interpretation, however, is broader than the model family actually searched, and the abstract's 'no new instances' claim sits uneasily with the >7-sigma candidate excesses reported in Section 6.1.

major comments (2)
  1. [§7 and abstract] The caveat stated at the end of Section 7 — 'a state switching process with an unbounded maximum state residence time would evade detection' — is load-bearing for the headline conclusion. The model in Section 2 (Eqs. 1–4) has bounded uniform state durations (0≤W_f≤T_f, 0≤W_b≤T_b), and the search templates (Section 6 and Appendix A) cover only four asymmetry values |A|≤0.94 and harmonically structured spectra. Real state-changing phenomena cited in Section 1, such as mode changing, nulling, and intermittent pulsars, are often aperiodic and can have heavy-tailed or exponential residence times, whose power is mostly broadband and partially removed by the slow-variability filtering. Thus the abstract's 'wide range of possible state changing models' and 'variations of any sort to ≤1%' are not established for that model family. Please restrict the abstract and conclusions to the bounded quasip
  2. [§6.1, §6, and abstract] Several candidates exceed the adopted 7σ threshold: J1658−5324 at 8.5σ, J0218+4232 at 7.6σ, and J0613−0200 and J1816+4510 at 7.3σ. For J0613−0200 the text states there is 'no obvious background contamination,' and for J1658−5324 the excess is very broad. Calling the result 'no new instances of state changes' in the abstract is therefore overstated unless 'instances' means 'confirmed state changes after a more stringent criterion.' The paper should state the expected number of false positives under the quoted trial estimate, and either report these as candidate state changes or justify their assignment to background more explicitly, especially for J0613−0200 and J1658−5324.
minor comments (5)
  1. [§4, §5.3, §7, Figure 5] Typos: 'methodlogy' (Section 4), 'suparass' (Section 5.3), 'impossible to difficult' and 'pulars' (Section 7), and 'Cygnux X-3' (Figure 5 caption).
  2. [§5.3 and Figure 6] The slow-variability sensitivity estimate uses a generic σ_v for the modulation and then labels the limit 'M,' the same symbol as the two-state modulation factor in Eq. 1. Rename or explicitly distinguish this quantity to avoid conflating the slow and fast model families.
  3. [§4] The sentence 'We select the known γ-ray pulsars those that have a 4FGL-DR4...' is a grammatical fragment; please rephrase.
  4. [§2, after Eq. 3] The phrase 'low (infinite) variance in the A→1 (A→−1) limits' is confusingly worded; clarify that the variance diverges as A→−1 and vanishes as A→1.
  5. [Figure 9] The figure includes Q<1 cases labeled 'not meaningful.' Consider removing them or adding an explicit note that they are outside the physical range, so readers do not interpret them as valid templates.

Circularity Check

0 steps flagged · score 0.0 of 10

No circularity: limits are derived from forward simulations and null-hypothesis calibration, not from fitting; K19 citation is an independent tool.

full rationale

The central result is a null/upper-limit analysis. For fast variability, the statistic C_D (Eq. 5) is a matched filter that weights the observed Leahy-normalized power spectrum P(f) by response functions R(f) obtained by forward-simulating the assumed two-state quasiperiodic process and averaging the resulting power spectra (Section 3.2, Figure 4). Sensitivity limits (Figure 8) are computed by injecting the maximal modulation M=1, using the expectation CD(M=1), and solving Eq. 7 for the modulation M required to reach a 5-sigma threshold. The observed power spectra are compared to the chi-square null; no parameter is fitted to the data to produce the central limits. Slow variability uses Bayesian blocks against the constant hypothesis. The paper explicitly states in Section 7 that a state-switching process with unbounded maximum residence time would evade detection; this is a scope limitation, not a circular definition. K19 is self-cited for the weighted-power-spectrum estimator and exposure/godot tools, but that estimator is independently established prior work and is not used to define the target result. No reduction of the claim to its inputs occurs.

Assumptions & free parameters 5 free parameters · 7 assumptions · 0 invented entities

The central null result rests on the assumption that any genuine fast state switching is quasiperiodic enough to appear in a power spectrum, plus the standard approximations of the weighted-photon likelihood. The detection thresholds and search grids are analysis choices that set how strong the reported limits are.

free parameters (5)
  • Bayesian blocks change-point prior exponent = -10
    Prior on number of change points chosen by hand; a conservative value that suppresses spurious slow variability detections (Section 5).
  • Fast variability trial-corrected detection threshold = 7 sigma
    Adopted after estimating ~7e8 independent trials and observing a 5-6.5 sigma null distribution; candidates below threshold are not reported as state changes (Section 6).
  • Sensitivity reporting threshold = 2 sigma (slow), 5 sigma (fast)
    Used to quote upper limits in Figures 6 and 8; not fitted to data.
  • Model asymmetry grid = |A| = 0, 0.5, 0.82, 0.94
    Four representative values chosen to span the two-state process space; the search interpolates over this grid (Section 6, Appendix A).
  • Spectral width grid = W = 1 to 32768 bins in powers of 2
    Chosen to cover a wide range of process randomness Q; a coarser grid would miss broad or narrow signals (Section 6).
assumptions (7)
  • domain assumption Two-state quasiperiodic square-wave model (Eqs. 1-4) with bounded state durations captures the relevant fast flux variability in gamma-ray pulsars.
    The search strategy and sensitivity limits are computed within this model family; the author notes in Section 7 that processes with unbounded state residence times would evade detection.
  • domain assumption Gamma-ray flux variations are a proxy for variations in spindown power Edot or particle acceleration.
    Stated in the abstract and Section 1; the title's 'stable emission' is extended to 'stable magnetosphere' only under this identification, further qualified in Section 7: 'If we interpret these flux constraints as also limiting the variations in Edot'.
  • standard math The power spectrum estimator P(f) from K19 is chi-square distributed under the null hypothesis of a constant Poisson rate, with negligible off-diagonal covariance between Fourier modes.
    Taken from K19; off-diagonal elements are a few percent of diagonal (K19, Section 3.2), so the matched-filter statistic inherits this approximation.
  • domain assumption The Fermi LAT exposure model (godot) is accurate at the percent level after the improvements described in Section 4.
    Appendix B shows percent-level residuals for Vela, but accuracy for every pulsar is assumed; residual exposure errors could otherwise create spurious power.
  • domain assumption Slow variability can be removed by Bayesian blocks and re-weighting so that residual leakage into the fast band is negligible.
    Two-stage strategy in Sections 3 and 5; spectral leakage from unfiltered slow signals would masquerade as fast variability, and the paper filters known periods (orbital, precession) to mitigate.
  • ad hoc to paper The spectral feature width scales as sigma_f proportional to f/Q^2, and Gaussian-plus-pedestal templates approximate exact response functions.
    Appendix A: this scaling and the template parameters were tuned to match simulations; the approximation is validated only for the four representative A values and a limited frequency range.
  • domain assumption The sample of 115 pulsars with 4FGL TS > 1000 is representative enough for the conclusion about gamma-ray pulsar state changing.
    Sample selection in Section 4.1; fainter pulsars could harbor variability below the sensitivity limit, acknowledged in Section 7.

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Cite this review

Pith. "Pith review of Gamma-ray Pulsar Emission is Mostly Stable on Timescales from Minutes to Years." pith.science (2026). https://pith.science/paper/DCB7JBM4

@misc{pith2026250818195,
  author       = {Pith},
  title        = {Pith review of: Gamma-ray Pulsar Emission is Mostly Stable on Timescales from Minutes to Years},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/DCB7JBM4}},
  note         = {Machine review of arXiv:2508.18195}
}
abstract

We present a method for the detection and characterization of random changes in the flux from $\gamma$-ray pulsars on sub-hour timescales, much shorter than variations that can be accessed using direct flux measurements. Flux variations are a proxy for the variations in spindown power ($\dot{E}$) or particle acceleration, which can be produced by random switches between quasi-stable configurations of the pulsar magnetosphere. This technique therefore probes the stability of pulsar magnetospheres and discrete spindown states on timescales much shorter than can be achieved with pulsar timing. We apply the method to a sample of 115 bright $\gamma$-ray pulsars, finding no new instances of state changes. We derive the sensitivity of the method and find that, for a wide range of possible state changing models, over a wide range of timescales, we can limit the amplitude of flux ($\dot{E}$) variations to $<$10%. Substantial nulling is excluded in nearly all cases. The best cases limit variations of any sort to $\leq$1%. These results indicate that $\gamma$-ray pulsar magnetospheres maintain a single configuration or narrow range of configurations with nearly constant power output.

Figures

Figures reproduced from arXiv: 2508.18195 by the authors.

Figure 1
Figure 1. The window function as realized by the Fourier transform of the expected source counts, s(t), towards PSR J0633+1746. The dominant peaks occur at the space￾craft orbital frequency, f ≈ 15.1 d−1 , at f ≈ 1 d−1 , and at beats of these frequencies. The inset shows low-fre￾quency power, including at the spacecraft precessional pe￾riod, fprec ≈ 0.019 d−1 . We emphasize that there is no in￾trinsic source variability: the … view at source ↗
Figure 2
Figure 2. The frequency response R(f) to a f = 2 d−1 pure sinusoid for 15.6 yr of data towards PSR J0633+1746, normalized to a peak value of 1. The first panel demonstrates the dominance of the main signal lobe. The grey region with R(f) < 0.0215 is shaded and expanded in the second panel to show the 1–2% spectral leakage to a wide range of frequencies. The grey regions in this panel are further expanded in panels three and f… view at source ↗
Figure 3
Figure 3. The equivalent significances in σ units for 100 realizations of a simulated period signal using the different detection statistics as described in the text. The detection statistic using the computed response function for the correct frequency results in roughly twice the significance. of frequencies, and the collective leaked power substan￾tially exceeds that in the main signal lobe. This response function reveals … view at source ↗
Figures from the paper (8 more)
Figure 4
Figure 4. Figure 4: Four examples of the variability process described in §2. The top four panels show 100 cycles of the process, with each 10 cycles wrapped to the next higher line. The bottom four panels show the frequency response R(f) for the process, obtained by simulating it many ti…
Figure 5
Figure 5. Figure 5: An example of using the BB algorithm to identify—and filter—long-term variability. Left: variations in the total background driven by activity of Cygnux X-3. Center: variations in the source intensity after correction for background variations; these are the state chan…
Figure 6
Figure 6. Figure 6: The 2σ confidence upper limit on modulation fraction (Eq. 1) estimated per §5.3. The estimates are shown for three representative timescales for each pulsar after sort￾ing in order of decreasing source brightness. Modulation fractions >3–10% are ruled out for most puls…
Figure 7
Figure 7. Figure 7: The significance of fast variability for PSR J1658−5324 over the targeted frequency range. Each line indicates the results for a matched filter of increasing width, i.e. an increasing level of randomness in the duration of each state. The maximum signal in any filter i…
Figure 8
Figure 8. Figure 8: The modulation fraction M required to exceed a 5σ detection threshold. The curves shows the constraints for the indicated value of W, which is the width of spectral features (σf ) expressed in frequency bins. W is related to the process randomness and timescale. The le…
Figure 9
Figure 9. Figure 9: Approximate filters for asymmetry A = 0 (top) and |A| = 29/31 (bottom). The light grey solid line shows the exact R(f), while the dashed line shows a close-matching approximate version. The signal frequency increases left to right and is expressed as a fraction of the …
Figure 10
Figure 10. Figure 10: The observed versus computed counts for PSR J0835−4510 (Vela) for various selection of the incidence angle from boresight, θ and the wrapped azimuthal angle ϕw ≡ 2 [PITH_FULL_IMAGE:figures/full_fig_p016_10.png]
Figure 11
Figure 11. Figure 11: As [PITH_FULL_IMAGE:figures/full_fig_p017_11.png]

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Reference graph

Works this paper leans on

61 extracted references · 13 canonical work pages · cited by 1 Pith paper

  1. [1]

    A., Ackermann, M., Ajello, M., et al

    Abdo, A. A., Ackermann, M., Ajello, M., et al. 2009, Science, 326, 1512, doi: 10.1126/science.1182174

    doi:10.1126/science.1182174 2009

  2. [2]

    A., Ackermann, M., Ajello, M., et al

    Abdo, A. A., Ackermann, M., Ajello, M., et al. 2011, Science, 331, 739, doi: 10.1126/science.1199705

    doi:10.1126/science.1199705 2011

  3. [3]

    2020, ApJS, 247, 33, doi: 10.3847/1538-4365/ab6bcb

    Abdollahi, S., Acero, F., Ackermann, M., et al. 2020, ApJS, 247, 33, doi: 10.3847/1538-4365/ab6bcb

    doi:10.3847/1538-4365/ab6bcb 2020

  4. [4]

    2012, Science, 335, 189, doi: 10.1126/science.1213974

    Ackermann, M., Ajello, M., Ballet, J., et al. 2012, Science, 335, 189, doi: 10.1126/science.1213974

    doi:10.1126/science.1213974 2012

  5. [5]

    B., Baldini, L., et al

    Ajello, M., Atwood, W. B., Baldini, L., et al. 2022, Science, 376, 521, doi: 10.1126/science.abm3231

    doi:10.1126/science.abm3231 2022

  6. [6]

    2013, ApJL, 777, L2, doi: 10.1088/2041-8205/777/1/L2

    Allafort, A., Baldini, L., Ballet, J., et al. 2013, ApJL, 777, L2, doi: 10.1088/2041-8205/777/1/L2

    doi:10.1088/2041-8205/777/1/l2 2013

  7. [7]

    2013, arXiv e-prints, arXiv:1303.3514

    Atwood, W., Albert, A., Baldini, L., et al. 2013, arXiv e-prints, arXiv:1303.3514. https://arxiv.org/abs/1303.3514

    arXiv 2013

  8. [8]

    B., Abdo, A

    Atwood, W. B., Abdo, A. A., Ackermann, M., et al. 2009, ApJ, 697, 1071, doi: 10.1088/0004-637X/697/2/1071

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

Show all 61 references
  1. [9]

    H., Lott, B., & The Fermi-LAT collaboration

    Ballet, J., Bruel, P., Burnett, T. H., Lott, B., & The Fermi-LAT collaboration. 2023, arXiv e-prints, arXiv:2307.12546, doi: 10.48550/arXiv.2307.12546

    2023 doi arXiv

  2. [10]

    Beloborodov, A. M. 2008, The Astrophysical Journal, 683, L41, doi: 10.1086/590079

    2008 doi

  3. [11]

    2008, ApJ, 685, 384, doi: 10.1086/590399

    Bickel, P., Kleijn, B., & Rice, J. 2008, ApJ, 685, 384, doi: 10.1086/590399

    2008 doi

  4. [12]

    K., & Kazanas, D

    Harding, A. K., & Kazanas, D. 2018, ApJ, 858, 81, doi: 10.3847/1538-4357/aab3e1

    2018 doi

  5. [13]

    R., Karastergiou, A., Johnston, S., et al

    Brook, P. R., Karastergiou, A., Johnston, S., et al. 2016, Monthly Notices of the Royal Astronomical Society, 456, 1374, doi: 10.1093/mnras/stv2715

    2016 doi

  6. [14]

    H., Digel, S

    Bruel, P., Burnett, T. H., Digel, S. W., et al. 2018, arXiv e-prints, arXiv:1810.11394. https://arxiv.org/abs/1810.11394

    2018 arXiv

  7. [15]

    D., Blandford, R

    Buehler, R., Scargle, J. D., Blandford, R. D., et al. 2012, ApJ, 749, 26, doi: 10.1088/0004-637X/749/1/26

    2012 doi

  8. [16]

    2012, The Astrophysical Journal, 746, 63, doi: 10.1088/0004-637X/746/1/63

    Demorest, P. 2012, The Astrophysical Journal, 746, 63, doi: 10.1088/0004-637X/746/1/63

    2012 doi

  9. [17]

    2015, MNRAS, 448, 606, doi: 10.1093/mnras/stv042

    Cerutti, B., Philippov, A., Parfrey, K., & Spitkovsky, A. 2015, MNRAS, 448, 606, doi: 10.1093/mnras/stv042

    2015 doi

  10. [18]

    Y., & Beloborodov, A

    Chen, A. Y., & Beloborodov, A. M. 2014, ApJL, 795, L22, doi: 10.1088/2041-8205/795/1/L22

    2014 doi

  11. [19]

    Y., Cruz, F., & Spitkovsky, A

    Chen, A. Y., Cruz, F., & Spitkovsky, A. 2020, ApJ, 889, 69, doi: 10.3847/1538-4357/ab5c20

    2020 doi

  12. [20]

    J., Kerr, M., Barr, E

    Clark, C. J., Kerr, M., Barr, E. D., et al. 2023, Nature Astronomy, 7, 451, doi: 10.1038/s41550-022-01874-x

    2023 doi

  13. [21]

    1999, ApJ, 511, 351, doi: 10.1086/306652

    Contopoulos, I., Kazanas, D., & Fendt, C. 1999, ApJ, 511, 351, doi: 10.1086/306652

    1999 doi

  14. [22]

    Cordes, J. M. 2013, The Astrophysical Journal, 775, 47, doi: 10.1088/0004-637X/775/1/47

    2013 doi

  15. [23]

    K., et al

    Fiori, A., Razzano, M., Harding, A. K., et al. 2024, Astronomy and Astrophysics, 685, A70, doi: 10.1051/0004-6361/202348924 γ-ray pulsar variability 13

    2024 doi

  16. [24]

    Goldreich, P., & Julian, W. H. 1969, The Astrophysical Journal, 157, 869, doi: 10.1086/150119

    1969 doi

  17. [25]

    E., Lupsasca, A., & Philippov, A

    Gralla, S. E., Lupsasca, A., & Philippov, A. 2017, The Astrophysical Journal, 851, 137, doi: 10.3847/1538-4357/aa978d

    2017 doi

  18. [26]

    2023, The Astrophysical Journal, 943, 105, doi: 10.3847/1538-4357/acab05

    Hakobyan, H., Philippov, A., & Spitkovsky, A. 2023, The Astrophysical Journal, 943, 105, doi: 10.3847/1538-4357/acab05

    2023 doi

  19. [27]

    Hermsen, W., Hessels, J. W. T., Kuiper, L., et al. 2013, Science, 339, 436, doi: 10.1126/science.1230960

    2013 doi

  20. [28]

    Hermsen, W., Kuiper, L., Hessels, J. W. T., et al. 2017, Monthly Notices of the Royal Astronomical Society, 466, 1688, doi: 10.1093/mnras/stw3135

    2017 doi

  21. [29]

    J., Ray, P

    Johnson, T. J., Ray, P. S., Roy, J., et al. 2015, ApJ, 806, 91, doi: 10.1088/0004-637X/806/1/91

    2015 doi

  22. [30]

    2011, ApJ, 732, 38, doi: 10.1088/0004-637X/732/1/38

    Kerr, M. 2011, ApJ, 732, 38, doi: 10.1088/0004-637X/732/1/38

    2011 doi

  23. [31]

    2019, ApJ, 885, 92, doi: 10.3847/1538-4357/ab459f

    Kerr, M. 2019, ApJ, 885, 92, doi: 10.3847/1538-4357/ab459f

    2019 doi

  24. [32]

    2022, ApJ, 934, 30, doi: 10.3847/1538-4357/ac7877

    Kerr, M. 2022, ApJ, 934, 30, doi: 10.3847/1538-4357/ac7877

    2022 doi

  25. [33]

    Kerr, M., Hobbs, G., Johnston, S., & Shannon, R. M. 2016, MNRAS, 455, 1845, doi: 10.1093/mnras/stv2457

    2016 doi

  26. [34]

    M., et al

    Kerr, M., Hobbs, G., Shannon, R. M., et al. 2014, MNRAS, 445, 320, doi: 10.1093/mnras/stu1716

    2014 doi

  27. [35]

    J., et al

    Kerr, M., Camilo, F., Johnson, T. J., et al. 2012, ApJL, 748, L2, doi: 10.1088/2041-8205/748/1/L2

    2012 doi

  28. [36]

    Lorimer, D. R. 2006, Science, 312, 549, doi: 10.1126/science.1124060

    2006 doi

  29. [37]

    Krause-Polstorff, J., & Michel, F. C. 1985, MNRAS, 213, 43, doi: 10.1093/mnras/213.1.43P

    1985 doi

  30. [38]

    E., Johnston, S., Karastergiou, A., et al

    Lower, M. E., Johnston, S., Karastergiou, A., et al. 2023, Monthly Notices of the Royal Astronomical Society, 524, 5904, doi: 10.1093/mnras/stad2243

    2023 doi

  31. [39]

    E., Karastergiou, A., Johnston, S., et al

    Lower, M. E., Karastergiou, A., Johnston, S., et al. 2025, The ubiquity of variable radio emission and spin-down rates in pulsars, doi: 10.48550/arXiv.2501.03500

    2025 doi arXiv

  32. [40]

    2010, Science, 329, 408, doi: 10.1126/science.1186683

    Lyne, A., Hobbs, G., Kramer, M., Stairs, I., & Stappers, B. 2010, Science, 329, 408, doi: 10.1126/science.1186683

    2010 doi

  33. [41]

    G., Stappers, B

    Lyne, A. G., Stappers, B. W., Freire, P. C. C., et al. 2017, The Astrophysical Journal, 834, 72, doi: 10.3847/1538-4357/834/1/72

    2017 doi

  34. [42]

    2014, Monthly Notices of the Royal Astronomical Society, 437, 21, doi: 10.1093/mnras/stt1828

    Melatos, A., & Link, B. 2014, Monthly Notices of the Royal Astronomical Society, 437, 21, doi: 10.1093/mnras/stt1828

    2014 doi

  35. [43]

    2022, Annual Review of Astronomy and Astrophysics, 60, 495, doi: 10.1146/annurev-astro-052920-112338

    Philippov, A., & Kramer, M. 2022, Annual Review of Astronomy and Astrophysics, 60, 495, doi: 10.1146/annurev-astro-052920-112338

    2022 doi

  36. [44]

    2020, Physical Review Letters, 124, 245101, doi: 10.1103/PhysRevLett.124.245101

    Philippov, A., Timokhin, A., & Spitkovsky, A. 2020, Physical Review Letters, 124, 245101, doi: 10.1103/PhysRevLett.124.245101

    2020 doi

  37. [45]

    A., & Spitkovsky, A

    Philippov, A. A., & Spitkovsky, A. 2014, The Astrophysical Journal, 785, L33, doi: 10.1088/2041-8205/785/2/L33

    2014 doi

  38. [46]

    A., & Spitkovsky, A

    Philippov, A. A., & Spitkovsky, A. 2018, ApJ, 855, 94, doi: 10.3847/1538-4357/aaabbc

    2018 doi

  39. [47]

    A., Spitkovsky, A., & Cerutti, B

    Philippov, A. A., Spitkovsky, A., & Cerutti, B. 2015, ApJL, 801, L19, doi: 10.1088/2041-8205/801/1/L19

    2015 doi

  40. [48]

    M., et al

    Razzano, M., Fiori, A., Saz Parkinson, P. M., et al. 2023, Astronomy and Astrophysics, 676, A91, doi: 10.1051/0004-6361/202345873

    2023 doi

  41. [49]

    S., Bhattacharyya, B., et al

    Roy, J., Ray, P. S., Bhattacharyya, B., et al. 2015, ApJL, 800, L12, doi: 10.1088/2041-8205/800/1/L12

    2015 doi

  42. [50]

    Scargle, J. D. 1998, ApJ, 504, 405, doi: 10.1086/306064

    1998 doi

  43. [51]

    D., Norris, J

    Scargle, J. D., Norris, J. P., Jackson, B., & Chiang, J. 2013, ApJ, 764, 167, doi: 10.1088/0004-637X/764/2/167

    2013 doi

  44. [52]

    W., Weltevrede, P., et al

    Shaw, B., Stappers, B. W., Weltevrede, P., et al. 2022, Monthly Notices of the Royal Astronomical Society, 513, 5861, doi: 10.1093/mnras/stac1156

    2022 doi

  45. [53]

    A., Abdollahi, S., Ajello, M., et al

    Smith, D. A., Abdollahi, S., Ajello, M., et al. 2023, ApJS

    2023

  46. [54]

    2024, Scaling up global kinetic models of pulsar magnetospheres using a hybrid force-free-PIC numerical approach, doi: 10.48550/arXiv.2406.14512

    Soudais, A., Cerutti, B., & Contopoulos, I. 2024, Scaling up global kinetic models of pulsar magnetospheres using a hybrid force-free-PIC numerical approach, doi: 10.48550/arXiv.2406.14512

    2024 doi arXiv

  47. [55]

    2006, ApJL, 648, L51, doi: 10.1086/507518

    Spitkovsky, A. 2006, ApJL, 648, L51, doi: 10.1086/507518

    2006 doi

  48. [56]

    2002, in Astronomical Society of the Pacific Conference Series, Vol

    Spitkovsky, A., & Arons, J. 2002, in Astronomical Society of the Pacific Conference Series, Vol. 271, Neutron Stars in Supernova Remnants, ed. P. O. Slane & B. M. Gaensler, 81, doi: 10.48550/arXiv.astro-ph/0201360 The Fermi LAT Collaboration, Ajello, M., Axelsson, M., et al. 2...

    2002 doi arXiv

  49. [57]

    Timokhin, A. N. 2006, MNRAS, 368, 1055, doi: 10.1111/j.1365-2966.2006.10192.x

    2006

  50. [58]

    Timokhin, A. N. 2010, MNRAS, 408, L41, doi: 10.1111/j.1745-3933.2010.00924.x

    2010

  51. [59]

    N., & Arons, J

    Timokhin, A. N., & Arons, J. 2013, MNRAS, 429, 20, doi: 10.1093/mnras/sts298

    2013 doi

  52. [60]

    N., & Johnston, S

    Wang, N., Manchester, R. N., & Johnston, S. 2007, MNRAS, 377, 1383, doi: 10.1111/j.1365-2966.2007.11703.x

    2007

  53. [61]

    A., Cherry, M

    Wilson-Hodge, C. A., Cherry, M. L., Case, G. L., et al. 2011, ApJL, 727, L40, doi: 10.1088/2041-8205/727/2/L40 14 Kerr APPENDIX A. APPROXIMATING MATCHED FILTERS Recall that the degree of randomness in the pulsar variability model is governed by Q ≡ (Tf + Tb)/(Wf + Wb). This ra...

    2011 doi

Pith tools

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