Pulsar glitches in the presence of vortex traps

Anantharaman Sekharipuram Viswanathan; Dipankar Bhattacharya; Erbil G\"ugercino\u{g}lu; M. Ali Alpar

REVIEW 3 major objections 3 minor 42 references

Pulsar glitches in the presence of vortex traps

T0 review · 3 major / 3 minor · reviewed 2026-08-01 · deepseek-v4-flash

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

Pith's one-line read The paper argues that networks of vortex traps—crustal regions with enhanced pinning—leave two observable fingerprints on pulsar glitches: staggered rise profiles and, under quake-triggered multi-trap releases, a bimodal glitch-size distrib

desk verdict A useful computational step and an honest, transparent qualitative study of vortex traps, but the headline observational signatures are not shown to survive at the physical trap geometry, and the quantitative anchor is a fitted amplification factor. read the letter →

arxiv 2607.20398 v1 pith:OMXBOS2P submitted 2026-07-22 astro-ph.HE

Anantharaman Sekharipuram Viswanathan , Dipankar Bhattacharya , M. Ali Alpar , Erbil Gügercinoğlu This is my paper · ORCID

classification astro-ph.HE

keywords pulsarglitchesvortextrapsneutronstarcrustsuperfluidvorticesglitch-sizedistributionstaggeredglitchriseavalanchesN-bodysimulation

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

Pulsar glitches are believed to be sudden transfers of angular momentum from the superfluid inside a neutron star to the crust, mediated by avalanches of quantized vortices. This paper adds vortex traps—crustal regions of enhanced pinning surrounded by vortex-free voids—and shows, with simulations of up to 10^5 vortices, that glitches then rise in a staggered fashion as vortices hop from trap to trap. It also shows that when a crustal quake releases several traps at once, the glitch-size distribution can become bimodal, matching a feature reported for the young pulsar PSR J0537-6910. A third result is that even with uniform pinning, an initially uniform vortex array spontaneously develops macroscopic vortex-free pockets. These are concrete, testable predictions for glitch rise profiles and glitch-size statistics.

What carries the argument

The central machinery is the vortex trap network embedded in a two-dimensional point-vortex simulation of the neutron-star superfluid. Traps are regions of strong pinning separated by pinning-free voids; the paper initializes vortices inside traps and lets them relax into an equilibrium with a surrounding void. The simulation uses a hierarchical tree approximation to compute vortex–vortex interactions in O(N log N) time, enabling runs with up to 10^5 vortices, and a 'trigger' mechanism that temporarily switches off pinning in one or more randomly chosen traps to mimic crustal quakes. The quantitative link between trigger and glitch size is the angular-momentum-conservation estimate ΔΩ_c/Ω_0

What would settle it

A direct simulation of the same trap-network model with trap ratio set to the physically estimated 0.9875 (or scanned from 0.5 to 0.99) would determine whether staggered glitch rises and bimodal glitch-size distributions survive at realistic packing; if they vanish, the predictions are artefacts of isolated traps. On the observational side, high-time-resolution timing of a Vela-like glitch—resolving the rise phase—could directly detect or exclude the predicted steps.

Watch

Extended reading notes

Core claim

The paper's central claim is that the vortex-trap network shapes glitch phenomenology in two identifiable ways. First, glitches rise in stages: vortices unpin from one trap, travel through the vortex-free void, and stimulate release from neighboring traps, so the spin-up shows a staggered profile—the authors call this 'a clear signature of the trap network.' Second, when a quake triggers the simultaneous release of several traps, the avalanche involves far more vortices than the traps originally held, and repeated such triggers can produce a bimodal glitch-size distribution with a secondary peak in the observationally relevant tail, as previously reported for PSR J0537-6910. The authors also

Load-bearing premise

The results assume that traps are large, widely separated, and strongly pinning, whereas the paper's own estimate of real neutron-star crusts puts traps so close together (a trap ratio of about 0.99) that the configuration would be indistinguishable from a uniform array.

Editorial extensions

If this is right

Staggered glitch rise becomes a diagnostic for the presence of a trap network: pulsars with high time-resolution glitch data (for example, Vela) should be checked for step-like increases in rotation frequency rather than a smooth rise.
Quake-triggered multi-trap releases can explain bimodal glitch-size distributions like that reported for PSR J0537-6910, meaning quakes and vortex avalanches are complementary rather than competing mechanisms.
The spontaneous formation of vortex-free pockets in a uniformly pinned array means that observations cannot assume a homogeneous vortex distribution even without pre-existing crustal structure; models of glitch statistics may need to include this clustering as a background effect.
The empirical amplification factor γ decreasing with more triggered traps implies that the largest glitches are not simply proportional to the number of traps involved; the relationship is nonlinear and depends on the stress state of the array.

Reading between the lines

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

Because the paper demonstrates its signatures at trap ratio 0.5 while estimating the physical ratio at ~0.99, a natural extension is to run the same simulations at intermediate ratios (0.7–0.9) to map where the staggered rise and bimodality fade; the paper hints minor changes up to 0.7 but does not quantify the threshold.
The spontaneous pockets seen in uniform arrays resemble trap-like voids; if real pulsars show glitch-size bimodality or staggered rises, one would need to distinguish whether they come from physical crustal traps or from this self-organized clustering, perhaps by comparing the size distribution of voids or the waiting-time statistics.
The amplification factor γ being largest for single-trap triggers suggests that rare, isolated quake events may be disproportionately effective at producing large glitches; if so, the rate of crustal quakes could be inferred from the rate of large glitches in pulsars like Vela, where individual traps may act as 'seeds' for avalanches.

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.

Desk Editor's Note

read the letter

Colleague,

Quick take: this is a competent and unusually transparent simulation paper. The Barnes-Hut adaptation for point vortices with image boundaries is a genuine technical contribution—they benchmark 1e5 vortices against exact forces with delta-H ~6e-3, and the code is public. The trap-network simulations are new, and the animations and parameter tables show careful work. The qualitative ideas—staggered glitch rises from traps, bimodal size distributions from triggered multi-trap release, spontaneous vortex-free pockets in uniform arrays—are plausible and worth taking seriously as simulation results.

But the evidence for the observational claims is weaker than the abstract suggests. The two headline signatures (staggered rise, bimodality) are demonstrated only at trap ratio 0.5, where the traps are large and well separated. Section 4.2.2 estimates the physical ratio at ~0.9875 and says such a configuration would be practically indistinguishable from uniform. That is not a dismissed quibble; it is the difference between a waffle pattern and a uniform distribution. The paper briefly says increasing to 0.7 gives minor changes, but that is not a demonstration that the signatures persist. This is a real external-validity gap, and it is load-bearing because the abstract presents these as mechanism-specific predictions.

The numerical anchor is also softer than it looks. Eq. (9) estimates a single-trap glitch of 1.4e-3, but the simulations produce triggered avalanches at 2-3e-2. The resolution is an amplification factor gamma fitted to the largest glitch per run (Table 2), which turns the quantitative claim into a fit. And the 1e5-vortex capability is only a benchmark; the physics runs use 5e3. None of this is fatal to the qualitative core, but it does mean the paper's strongest statements outrun its support.

All that said, the paper is not sloppy. It flags its own gaps: the pinning range in traps is admitted to be unphysical, the physical trap ratio is explicitly computed, and the future-work pointer for the staggered-rise probe is honest. The citation pattern is mostly fine, though the J0537-6910 bimodality reference leans partly on the authors' own prior work.

Who gets value from this? Glitch modelers picking a simulation approach, and observers wanting a list of possible rise-profile caveats. It deserves a serious referee: a good referee would push for a sensitivity study of the trap ratio and a prediction from first principles instead of a fitted gamma. I would not desk-reject it, but I would send it back with those asks.

Best, [You]

Referee Report

3 major / 3 minor

Summary. The paper presents a Barnes-Hut accelerated two-dimensional point-vortex simulator for neutron star superfluid dynamics, extending earlier uniform-pinning simulations to systems with up to 10^5 vortices. Using this tool, the authors investigate the effect of 'vortex traps'—regions of strong pinning surrounded by vortex-free voids—on glitch dynamics. They report that, in the presence of a trap network, glitch rises become staggered, and that crustquake-like triggers that temporarily switch off pinning in one or more traps can produce bimodal glitch-size distributions, which they connect to observations of PSR J0537-6910. They also report the spontaneous formation of vortex-free regions in an initially uniform array. The central observable claims are the staggered rise and trigger-induced bimodality as signatures of trap networks.

Significance. The computational advance is genuine and well documented: the Barnes-Hut implementation is benchmarked against exact calculations (ΔH = 6 × 10^−3 at 10^4 vortices), the code is publicly released, and 10^5 vortices can be simulated in 13 hours, orders of magnitude faster than prior point-vortex simulations. If the claimed signatures were robust, they would represent mechanism-specific, testable predictions that could distinguish trap-based glitch models from uniform-pinning models. However, the paper's evidence for these signatures is tied to an artificially strong trap geometry (trap ratio 0.5, zero pinning outside traps) and depends on a post-hoc amplification factor fitted to the largest glitch in each simulation. The physical extrapolation is therefore not yet established, and the central interpretive claims outpace the demonstrated parameter range.

major comments (3)

[§4.2.2 / Appendix A2] The simulations fix the trap ratio (trap size / inter-trap distance) at 0.5, with zero pinning outside traps and an enlarged pinning radius ξ=0.5a. Section 4.2.2 estimates the physically expected trap ratio as (1 − Ω_cr/Ω)^1/2 ≈ 0.9875, corresponding to gaps of only ~10 cm between 10-m traps, and states that such a configuration "will be practically indistinguishable from a uniform distribution." The staggered-rise signal (Sec. 3.1) and trigger-induced bimodality (Sec. 4.1) are therefore demonstrated only for well-separated, isolated traps. The brief remark that increasing the ratio to 0.7 leads to "minor changes" does not establish that the signatures survive as the ratio approaches the physical value; in fact, the paper's own argument suggests they should weaken. Because the abstract and conclusions present these signatures as testable mechanism-specific predictions, the external valid
[§4.1, Eqs. (9)–(10), Table 2] The quantitative anchor is circular. Equation (9) estimates the single-trap glitch size as 1.4 × 10^−3 using simulation-derived inputs (n=15, k/I_s=1.6×10^−4). The triggered glitches in the simulations are one order of magnitude larger, with largest values in Table 2 ranging from 1.6 × 10^−2 to 3.3 × 10^−2. Equation (10) then introduces an amplification factor γ that is fitted to the largest triggered glitch in each simulation (Table 2). Since γ is chosen to match the simulations, the apparent agreement of Eq. (10) with the distributions is tautological. Moreover, γ varies by a factor of ~18 across the runs and no first-principles model is provided for it. This undermines the claim that the trap-involvement scenario quantitatively explains the observed glitch-size tail.
[§4.1, Figs. 4 and 5] The bimodality claim rests on visual inspection of kernel density estimates, e.g., "a low albeit clear second peak around 3×10^−2" in the middle panel of Fig. 4. No statistical test (e.g., dip test, Gaussian mixture fit, or bootstrap interval) is applied to assess whether the secondary peaks are significant given the limited statistics (five iterations per setup). Since the comparison with the reported bimodality of PSR J0537-6910 is a headline result, a quantitative test is required before this can be claimed as a signature.

minor comments (3)

[§5] The spontaneous inhomogeneity claim is based on a single qualitative run (Fig. 6) with no quantitative measure of void properties or persistence across realizations. Consider reporting statistics over multiple initial conditions.
[Abstract / §2.3] The abstract highlights simulation of 10^5 vortices, but the scientific runs in the trap sections use only 5×10^3 vortices. Please clarify in the text that the 10^5 run is a benchmark, not a production run.
[Title page] There are typographical errors in the header ('MNRAS000, 1–10 (20262025)' and 'L ATEX'). Please correct.

Circularity Check

0 steps flagged · score 1.0 of 10

No load-bearing circularity: Eq. (9) is an honest single-trap estimate, Eq. (10) is explicitly post-hoc, and the headline signatures are simulation outputs; the unphysical trap-ratio limitation affects external validity, not circularity.

full rationale

I walked the claimed derivation chain. The central claims—staggered glitch rise and triggered-release bimodality—are presented as simulation outcomes, not as derived from fitted quantities. The trap geometry is chosen openly: "we take the distance between the traps to be twice the size of the traps" (Section 3), and the subsequent signature is read off the simulations (Fig. 2, Anim1). Equation (9), the only a priori estimate, uses simulation-measured k/I_s and n along with assumed r_A and r_B; the paper explicitly compares it with the runs: "Prior to the simulations, we make the estimates presented above. After the simulations, we compare the resulting distribution with the above predictions." The disagreement (predicted 1.4e-3 vs. observed second peak around 3e-2) shows it is not fitted to the target. Equation (10) introduces the amplification factor gamma, but gamma is derived from the largest glitch in each simulation (Table 2) and the paper states "Addressing this from first principles shall be pursued in a future work," honestly labeling it as post-hoc parametrization rather than a prediction. The bimodality claim cites both Celora et al. (2020) and the authors' own Anantharaman & Bhattacharya (2025); the external citation carries the observational precedent, so the self-citation is corroborative, not load-bearing. The Barnes-Hut implementation is benchmarked against exact calculation (ΔH = 6e-3) and the code is described as "fully independent of the one presented in Howitt et al. (2020)." The paper's self-acknowledged limitation that the physical trap ratio ~0.9875 is "practically indistinguishable from a uniform distribution" (Section 4.2.2) is an external-validity caveat, not a circular step: it weakens the extrapolation from the simulated ratio 0.5 to real pulsars, but does not make the simulation outputs equivalent to their inputs by construction. No self-definitional reduction, no fitted-input-called-prediction, no uniqueness theorem imported from authors, and no ansatz smuggled via citation was found. Minor self-citations and the transparent gamma fit warrant only a minimal non-zero score.

Assumptions & free parameters 9 free parameters · 6 assumptions · 1 invented entities

Every quantitative glitch-size claim rests on dimensionless simulation units, chosen constants (I_rel = 1, Omega_0 = 40, V_0 = 1e4, xi = 0.5a, trap ratio 0.5, cut-off 3e-3), simulation-derived values (k/I_s, n), and a fitted amplification factor gamma. Physical inputs are scaled from a real star (~1e17 vortices; traps with ~1e11 vortices) down to 5e3 vortices / ~15 vortices per trap with no demonstrated scale invariance.

free parameters (9)

Amplification factor gamma = 1.3-23.6 (Table 2)
Introduced in Eq. (10) after Eq. (9) failed; fitted to the largest triggered glitch in each simulation run.
I_rel = I_s/I_c (superfluid/crust moment-of-inertia ratio) = 1
'The actual glitch size scales with I_rel' (Eq. 8); chosen as unity, not tied to a specific pulsar.
Initial rotation rate Omega_0 = 40
Tuned 'to minimize the exit of vortices during the relaxation phase'; the uniform-array value would be 50 (Section 4.1).
Trap ratio (trap size / inter-trap distance) = 0.5
Chosen to visually highlight the waffle pattern; physical estimate is 0.9875, where the array is 'practically indistinguishable from a uniform distribution' (Section 4.2.2).
Glitch-size cut-off = 3e-3
Chosen 'appropriately such that only observationally relevant variations... are accounted for'; found empirically from the simulations (Section 4).
Pinning range in traps xi = 0.5a (half the pinning-site spacing)
Admitted 'not reflective of an individual site in a neutron star' (Appendix A2); needed to keep vortices trapped during relaxation.
Constant k/I_s = 1.6e-4
'We find that the constant k/I_s = 1.6e-4' from the simulations; enters Eq. (9), the failed single-trap estimate.
Average vortices per trap n = 15
Empirical average from the trap simulations (Section 4.1); real traps are expected to hold ~1e11 vortices.
Numeric/dissipative settings: phi, V_0, N_ext/I_c, theta, dt = 0.1; 1e4; -2.5e-4 Omega_0/T_0; 0.5; 0.005 T_0
Dimensionless choices carried from Howitt et al. 2020 or chosen; the absolute glitch-size scale depends on them.

assumptions (6)

domain assumption A 2D point-vortex array with image-vortex boundaries captures inner-crust glitch dynamics
Section 2.1: the star is a cylindrical 2D 'container' of superfluid; vortices evolve by Eqs (1)-(3).
domain assumption Core superfluid is rigidly coupled to the crust on glitch rise timescales (vortex magnetization, Alpar et al. 1984)
Section 1: justifies treating only the inner-crust/outer-core superfluid as active and lumping the rest into the normal crust.
domain assumption Crustal cracking produces traps: volumes of enhanced vortex density with strong pinning, surrounded by vortex-free voids
Section 3, following Cheng et al. 1988, Alpar et al. 1996, G�ugercinoglu & Alpar 2020; traps are inherited from prior literature, not newly derived.
ad hoc to paper A crustquake is modeled as simultaneously switching off all pinning sites in a trap and re-enabling them after ~1 rotation period
Section 3.2: 'We switch off the pinning sites within a trap to release all the vortices within it simultaneously.'
ad hoc to paper Initial condition places all vortices inside traps; relaxation ejects excess vortices, some leaving the system
Section 3: 'we initialize all the vortices within the traps... many of them exit the system.'
domain assumption Barnes-Hut with theta = 0.5 and tolerance 1e-5 preserves glitch statistics
Section 2.3: validated by delta-H = 6e-3 for one 1e4-vortex case; not validated for the trap runs or the 1e5-vortex benchmark.

invented entities (1)

Vortex traps and surrounding vortex-free voids
purpose: Provide sites of enhanced pinning whose collective unpinning triggers avalanches, staggered rises, and bimodal glitch-size distributions
Adopted from Cheng et al. 1988 / Alpar et al. 1996 / G�ugercinoglu & Alpar 2020; the only external handle is the indirect interpretation of the 2016 Vela slowdown (Palfreyman et al. 2018) as trap formation. No direct falsifiable signature independent of this interpretation chain is provided.

how reviews work

0 comments

Cite this review

Pith. "Pith review of Pulsar glitches in the presence of vortex traps." pith.science (2026). https://pith.science/paper/OMXBOS2P

@misc{pith2026260720398,
  author       = {Pith},
  title        = {Pith review of: Pulsar glitches in the presence of vortex traps},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/OMXBOS2P}},
  note         = {Machine review of arXiv:2607.20398}
}

abstract

Pulsar glitches are thought to originate when angular momentum is transferred to the crust of the neutron star from the superfluid enclosed within, mediated by vortex avalanches. This idea has been qualitatively validated in the existing literature by simulating a star with a small number ($\sim 10^{3}$) of superfluid vortices, subject to deceleration and uniform pinning. Here, we employ the Barnes-Hut approximation to simulate up to $10^{5}$ vortices in a reasonable time. Using the new setup, we probe glitches that originate in the presence of inhomogeneous pinning. The inner crust of a neutron star is expected to crack as the star spins down, relieving stresses and resulting in rearrangements within the crustal lattice. These regions become centres for pinning with large pinning energies. Many such vortex traps are expected to exist in mature pulsars like Vela. We simulate one such star and find that the rise of the glitch is now staggered, a clear signature of the trap network. In young to middle-aged stars like PSR J0537-6910, we expect quakes which result in new traps and also unpin the vortices in existing ones. We observe that such a configuration involving the simultaneous release of several traps could introduce a bimodality in the glitch-size distribution, a feature that has previously been reported for PSR J0537-6910. Our simulations also indicate that macroscopic inhomogeneities in the distribution of vortices could spontaneously develop in a star with uniform pinning sites.

Figures

Figures reproduced from arXiv: 2607.20398 by the authors.

**Figure 1.** A schematic illustrating the role of the parameter 𝜃 in our adaptation of the Barnes-Hut algorithm. The lower the value of 𝜃, the closer are the results to the exact calculation. The bounding box of size R indicates the region that is partitioned while approximating the effect of real vortices on a given vortex. The image vortices, up to a distance of 100 R are also partitioned, but are not displayed here to reduce … view at source ↗

**Figure 2.** Four chronologically arranged snapshots of a glitch in the presence of traps, occurring in the bottom quarter of a star. The glitch lasts for a total of 0.8 𝑇0. The four panels show the vortex array at 0.1 𝑇0, 0.2 𝑇0, 0.4 𝑇0, and 0.7 𝑇0 from the start of the glitch. Panel 1: Some vortices from a trap are released due to the Magnus force exceeding the pinning force. Panel 2: Vortices from neighbouring traps are relea… view at source ↗

**Figure 3.** Four chronologically arranged snapshots of a vortex trap being triggered, spanning a total of 0.15 𝑇0. Only the relevant section of the star is presented. The four panels show the vortex array at 0.0 𝑇0, 0.05 𝑇0, 0.1 𝑇0, and 0.15 𝑇0 from the start of the trigger. Panel 1: A randomly chosen trap (marked by a black box) is triggered. Panel 2: A few vortices exit the trap and enter a neighbouring trap. Some get repinne… view at source ↗

Figures from the paper (3 more)

**Figure 4.** Figure 4: Distribution of glitch sizes resulting from various simulations involving vortex traps. Perspective 1: Each panel considers simulations having the same number of triggered traps, varying only in the number of triggers implemented during the runtime. MNRAS 000, 1–10 (20…

**Figure 5.** Figure 5: Distribution of glitch sizes resulting from various simulations involving vortex traps. Perspective 2: Each panel considers simulations having the same number of runtime triggers, varying only in the involvement of traps. exit of vortices during the relaxation phase. T…

**Figure 6.** Figure 6: Evolution of the vortex array in a star from 0𝑇0 to 2000𝑇0, a duration comparable to the spin-down time. The panels are arranged chronologically, left to right, and top to bottom, beginning from the top left. The initially uniform array develops a few vacancies which g…

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

42 extracted references · 17 canonical work pages

[1]

Plasticity of Neutron Star Crusts

Caplan, Matthew E. and Smith, Nevin T. and Bransgrove, Ashley J. and Horowitz, Charles J. , year = 2026, month = jun, number =. Plasticity of. doi:10.48550/arXiv.2606.06706 , urldate =. arXiv , keywords =:2606.06706 , primaryclass =

work page Pith review arXiv doi:10.48550/arxiv.2606.06706 2026
[2]

and Ingargiola, Antonino , title =

Newville, Matthew and Stensitzki, Till and Allen, Daniel B. and Ingargiola, Antonino , title =. doi:10.5281/zenodo.11813 , url =

doi:10.5281/zenodo.11813
[3]

, author =

Rapid Postglitch Spin-up of the Superfluid Core in Pulsars. , author =. The Astrophysical Journal , volume =. doi:10.1086/162232 , urldate =

doi:10.1086/162232
[4]

Alpar, M. A. and Chau, H. F. and Cheng, K. S. and Pines, D. , year = 1996, month = mar, journal =. Postglitch. doi:10.1086/176935 , urldate =

work page doi:10.1086/176935 1996
[5]

Anantharaman, S V and Bhattacharya, Dipankar , year = 2025, month = jun, journal =. On. doi:10.1093/mnras/staf702 , urldate =

work page doi:10.1093/mnras/staf702 2025
[6]

Nature , volume =

Pulsar Glitches and Restlessness as a Hard Superfluidity Phenomenon , author =. Nature , volume =. doi:10.1038/256025a0 , urldate =

doi:10.1038/256025a0
[7]

Pulsar Glitches: Observations and Physical Interpretation , shorttitle =

Antonopoulou, Danai and Haskell, Brynmor and Espinoza, Crist. Pulsar Glitches: Observations and Physical Interpretation , shorttitle =. Reports on Progress in Physics , volume =. doi:10.1088/1361-6633/ac9ced , urldate =

doi:10.1088/1361-6633/ac9ced
[8]

Monthly Notices of the Royal Astronomical Society , volume =

Breaking Properties of Neutron Star Crust , author =. Monthly Notices of the Royal Astronomical Society , volume =. doi:10.1093/mnras/sty2259 , urldate =

doi:10.1093/mnras/sty2259

Show all 42 references

[9]

A Hierarchical

Barnes, Josh and Hut, Piet , year = 1986, month = dec, journal =. A Hierarchical. doi:10.1038/324446a0 , urldate =

1986 doi
[10]

Baym, Gordon and Pethick, Christopher and Pines, David and Ruderman, Malvin , year = 1969, month = nov, journal =. Spin. doi:10.1038/224872a0 , urldate =

1969 doi
[11]

Annals of Physics , volume =

Neutron Starquakes and Pulsar Speedup , author =. Annals of Physics , volume =. doi:10.1016/0003-4916(71)90084-4 , urldate =

doi
[12]

Monthly Notices of the Royal Astronomical Society , volume =

The Effect of Non-Linear Mutual Friction on Pulsar Glitch Sizes and Rise Times , author =. Monthly Notices of the Royal Astronomical Society , volume =. doi:10.1093/mnras/staa1930 , urldate =

doi
[13]

The Astrophysical Journal , volume =

Spontaneous Superfluid Unpinning and the Inhomogeneous Distribution of Vortex Lines in Neutron Stars , author =. The Astrophysical Journal , volume =. doi:10.1086/166517 , urldate =

doi
[14]

Persistent Gravitational Radiation from Glitching Pulsars --

Cheunchitra, T and Melatos, A and Carlin, J B and Howitt, G , year = 2024, month = jan, journal =. Persistent Gravitational Radiation from Glitching Pulsars --. doi:10.1093/mnras/stae130 , urldate =

2024 doi
[15]

Monthly Notices of the Royal Astronomical Society , volume =

Neutron Star Glitches Have a Substantial Minimum Size , author =. Monthly Notices of the Royal Astronomical Society , volume =. doi:10.1093/mnras/stu395 , urldate =

doi
[16]

Research in Astronomy and Astrophysics , volume =

On the Distributions of Pulsar Glitch Sizes and the Inter-Glitch Time Intervals , author =. Research in Astronomy and Astrophysics , volume =. doi:10.1088/1674-4527/19/6/89 , urldate =

doi
[17]

Astronomy & Astrophysics , volume =

The Glitch Activity of Neutron Stars , author =. Astronomy & Astrophysics , volume =. doi:10.1051/0004-6361/201731519 , urldate =. arXiv , keywords =:1710.00952 , primaryclass =

arXiv
[18]

Astronomy & Astrophysics , volume =

Glitch Time Series and Size Distributions in Eight Prolific Pulsars , author =. Astronomy & Astrophysics , volume =. doi:10.1051/0004-6361/201935939 , urldate =. arXiv , keywords =:1907.09887 , primaryclass =

1907 arXiv
[19]

Monthly Notices of the Royal Astronomical Society , volume =

Modelling Strains and Stresses in Continuously Stratified Rotating Neutron Stars , author =. Monthly Notices of the Royal Astronomical Society , volume =. doi:10.1093/mnras/stz3099 , urldate =

doi
[20]

G. Vortex. The Astrophysical Journal , volume =. doi:10.1088/2041-8205/788/1/L11 , urldate =

doi
[21]

The Largest

G. The Largest. Monthly Notices of the Royal Astronomical Society , volume =. doi:10.1093/mnras/stz1831 , urldate =

doi
[22]

The 2016

G. The 2016. Monthly Notices of the Royal Astronomical Society , volume =. doi:10.1093/mnras/staa1672 , urldate =

2016 doi
[23]

Proceedings of the National Academy of Sciences , volume =

Vortex Filament Method as a Tool for Computational Visualization of Quantum Turbulence , author =. Proceedings of the National Academy of Sciences , volume =. doi:10.1073/pnas.1312535111 , urldate =

doi
[24]

International Journal of Modern Physics D , volume =

Models of Pulsar Glitches , author =. International Journal of Modern Physics D , volume =. doi:10.1142/S0218271815300086 , urldate =

doi
[25]

Horowitz, C. J. and Kadau, Kai , year = 2009, month = may, journal =. Breaking. doi:10.1103/PhysRevLett.102.191102 , urldate =

2009 doi
[26]

and Melatos, A

Howitt, G. and Melatos, A. and Delaigle, A. , year = 2018, month = oct, journal =. Nonparametric. doi:10.3847/1538-4357/aae20a , urldate =

2018 doi
[27]

and Melatos, A

Howitt, G. and Melatos, A. and Haskell, B. , year = 2020, month = oct, journal =. Simulating Pulsar Glitches: An. doi:10.1093/mnras/staa2314 , urldate =. arXiv , keywords =:2008.00365 , primaryclass =

2020 arXiv
[28]

Konar, Sushan and Arjunwadkar, Mihir , year = 2014, month = feb, journal =. Glitch

2014
[29]

Physical Review D , volume =

Large-Scale Unpinning and Pulsar Glitches Due to the Forced Oscillation of Vortices , author =. Physical Review D , volume =. doi:10.1103/bwrd-v7b4 , urldate =

doi
[30]

Superfluid

Levin, Yuri and Link, Bennett , year = 2023, month = dec, journal =. Superfluid. doi:10.3847/1538-4357/ad0031 , urldate =

2023 doi
[31]

and Barenghi, Carlo F

Liu, I-Kang and Baggaley, Andrew W. and Barenghi, Carlo F. and Wood, Toby S. , year = 2025, month = apr, journal =. Vortex. doi:10.3847/1538-4357/adc383 , urldate =

2025 doi
[32]

Lyne, A. G. and Smith, F. Graham and Pritchard, R. S. , year = 1992, month = oct, journal =. Spin-up and Recovery in the 1989 Glitch of the. doi:10.1038/359706a0 , urldate =

1992 doi
[33]

and Hotan, Aidan and Ellingsen, Simon and

Palfreyman, Jim and Dickey, John M. and Hotan, Aidan and Ellingsen, Simon and. Alteration of the Magnetosphere of the. Nature , volume =. doi:10.1038/s41586-018-0001-x , urldate =

doi
[34]

Parzen, Emanuel , year = 1962, month = sep, journal =. On. doi:10.1214/aoms/1177704472 , urldate =

1962
[35]

Astronomy & Astrophysics , volume =

Revisiting Neutron Starquakes Caused by Spin-Down , author =. Astronomy & Astrophysics , volume =. doi:10.1051/0004-6361/202141499 , urldate =

doi
[36]

, year = 1969, month = aug, journal =

Ruderman, M. , year = 1969, month = aug, journal =. Neutron. doi:10.1038/223597b0 , urldate =

1969 doi
[37]

The Largest Glitch Observed in the

Shaw, B and Lyne, A G and Stappers, B W and Weltevrede, P and Bassa, C G and Lien, A Y and Mickaliger, M B and Breton, R P and Jordan, C A and Keith, M J and Krimm, H A , year = 2018, month = aug, journal =. The Largest Glitch Observed in the. doi:10.1093/mnras/sty1294 , urldate =

2018 doi
[38]

and Levin, Yuri , year = 2026, month = mar, journal =

Sheng, Xin and Link, Bennett and Caplan, Matthew E. and Levin, Yuri , year = 2026, month = mar, journal =. Vortex. doi:10.3847/1538-4357/ae4b32 , urldate =

2026 doi
[39]

Monthly Notices of the Royal Astronomical Society , volume =

A Cellular Automaton Model of Pulsar Glitches , author =. Monthly Notices of the Royal Astronomical Society , volume =. doi:10.1111/j.1365-2966.2008.13662.x , urldate =

2008
[40]

and Melatos, A

Warszawski, L. and Melatos, A. , year = 2011, month = aug, journal =. Gross--. doi:10.1111/j.1365-2966.2011.18803.x , urldate =

2011
[41]

Wong, Tony and Backer, D. C. and Lyne, A. G. , year = 2001, month = feb, journal =. Observations of a. doi:10.1086/318657 , urldate =

2001 doi
[42]

Zhou, Shiqi and G. Pulsar. Universe , volume =. doi:10.3390/universe8120641 , urldate =

doi

Pith tools

Reviewed August 1, 2026 · model on record in the stance chip above.

[1] [1]

Plasticity of Neutron Star Crusts

Caplan, Matthew E. and Smith, Nevin T. and Bransgrove, Ashley J. and Horowitz, Charles J. , year = 2026, month = jun, number =. Plasticity of. doi:10.48550/arXiv.2606.06706 , urldate =. arXiv , keywords =:2606.06706 , primaryclass =

work page Pith review arXiv doi:10.48550/arxiv.2606.06706 2026

[2] [2]

and Ingargiola, Antonino , title =

Newville, Matthew and Stensitzki, Till and Allen, Daniel B. and Ingargiola, Antonino , title =. doi:10.5281/zenodo.11813 , url =

doi:10.5281/zenodo.11813

[3] [3]

, author =

Rapid Postglitch Spin-up of the Superfluid Core in Pulsars. , author =. The Astrophysical Journal , volume =. doi:10.1086/162232 , urldate =

doi:10.1086/162232

[4] [4]

Alpar, M. A. and Chau, H. F. and Cheng, K. S. and Pines, D. , year = 1996, month = mar, journal =. Postglitch. doi:10.1086/176935 , urldate =

work page doi:10.1086/176935 1996

[5] [5]

Anantharaman, S V and Bhattacharya, Dipankar , year = 2025, month = jun, journal =. On. doi:10.1093/mnras/staf702 , urldate =

work page doi:10.1093/mnras/staf702 2025

[6] [6]

Nature , volume =

Pulsar Glitches and Restlessness as a Hard Superfluidity Phenomenon , author =. Nature , volume =. doi:10.1038/256025a0 , urldate =

doi:10.1038/256025a0

[7] [7]

Pulsar Glitches: Observations and Physical Interpretation , shorttitle =

Antonopoulou, Danai and Haskell, Brynmor and Espinoza, Crist. Pulsar Glitches: Observations and Physical Interpretation , shorttitle =. Reports on Progress in Physics , volume =. doi:10.1088/1361-6633/ac9ced , urldate =

doi:10.1088/1361-6633/ac9ced

[8] [8]

Monthly Notices of the Royal Astronomical Society , volume =

Breaking Properties of Neutron Star Crust , author =. Monthly Notices of the Royal Astronomical Society , volume =. doi:10.1093/mnras/sty2259 , urldate =

doi:10.1093/mnras/sty2259