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arxiv: 2606.23903 · v1 · pith:KJNMLMVNnew · submitted 2026-06-22 · 🌌 astro-ph.HE · astro-ph.SR

Indication for Decreasing Dispersion Measure in the Population of Repeating Fast Radio Bursts and Connection to Young Supernova Remnant Expansion

Xiang-han Cui , Cheng-min Zhang , Di Li , Pei Wang , Erbil G\"ugercino\u{g}lu , Joeri van Leeuwen , Yi-dan Wang , Chao-wei Tsai
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Xiang-lei Chen Wen-qi Ma Habtamu Menberu Tedila
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Pith reviewed 2026-06-26 06:59 UTC · model grok-4.3

classification 🌌 astro-ph.HE astro-ph.SR
keywords fast radio burstsdispersion measure evolutionrepeating FRBssupernova remnantsCHIME observationselectron density
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The pith

Repeating fast radio bursts more commonly exhibit decreasing dispersion measure trends.

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

The paper selects 19 repeating FRBs with over ten bursts each from CHIME monitoring and identifies seven with significant long-term DM changes. Five of these show decreasing DM while two show increasing DM. A binomial test combining these with literature sources produces a p-value of 0.033 against the null hypothesis of equal likelihood for either trend. This result indicates that decreasing DM is more prevalent in the population, which would follow if the electron density near the sources is generally falling with time. Such a decrease aligns with the expansion of young supernova remnants surrounding the FRB progenitors.

Core claim

The current combined sample of repeating FRBs with reported DM change rates gives a p-value of 0.033 in a binomial test, supporting that decreasing DM trends are more common than increasing ones in the repeating FRB population. This is consistent with the local electron density around repeaters generally decreasing with time, for example due to expansion of a young supernova remnant.

What carries the argument

Binomial test under the null hypothesis that decreasing and increasing DM variation trends have equal probabilities, applied to the golden sample of seven sources plus literature data.

Load-bearing premise

The binomial test treats each source as equally likely to show either trend under the null hypothesis, assuming no selection effects from detection thresholds or varying monitoring durations.

What would settle it

Finding that the number of repeating FRBs with increasing DM trends equals or surpasses those with decreasing trends in an expanded sample would undermine the claimed preference for decreasing trends.

Figures

Figures reproduced from arXiv: 2606.23903 by Chao-Wei Tsai, Cheng-Min Zhang, Di Li, Erbil G\"ugercino\u{g}lu, Habtamu Menberu Tedila, Joeri van Leeuwen, Pei Wang, Wen-Qi Ma, Xiang-Han Cui, Xiang-Lei Chen, Yi-Dan Wang.

Figure 1
Figure 1. Figure 1: A clear case where a DM rate of change can be established (FRB 20240209A). Blue points represent indi￾vidual DMexc with original errors. The orange solid line and black dashed line represent the best-fits from weighted least￾squares (WLS) and Bayesian method, respectively, with their 95% confidence level (CL). The gray shaded region shows the 95% CL envelope from the WLS fit. The gray dashed-dot line indic… view at source ↗
Figure 2
Figure 2. Figure 2: A group of all repeaters with an overall decreasing DMexc trend. Sources marked with an asterisk “*” are considered golden samples. Other annotations are the same as in [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: A group of all repeaters with an overall increasing DMexc trend. Sources marked with an “*” belong golden samples. Other annotations are the same as in [PITH_FULL_IMAGE:figures/full_fig_p006_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Histogram of the annual DMexc variation rates for the golden sample. Upper panel: Blue and orange bars represent sources with decreasing and increasing DM, respec￾tively. Blue and red dash-dotted lines mark the correspond￾ing median DM variation rates. Lower panel: Smoothed histograms that consider the uncertainties of individual DM variation rates. The light blue and light orange curves show the probabili… view at source ↗
Figure 5
Figure 5. Figure 5: Variation of the binomial test p-value with in￾creasing number of golden sources. The blue, orange, and green curves represent different initial ratios of decreasing to increasing sources, respectively. The 5:2 case uses all golden sample sources in this work. The 4:1 caes excludes two sources in this work that may be affected by isolated data points in the fit, that are FRB 20240316A and FRB 20220912A. Th… view at source ↗
Figure 6
Figure 6. Figure 6: Schematic illustration of the SNR expansion. Rr, Rc, and Rb represent the radii of the reverse shock, the contact discontinuity, and the shocked ISM, respectively, adapted from Piro & Gaensler (2018). the shocked ejecta is significantly higher than that in the surrounding regions, and thus dominates the contribu￾tion to the dispersion measure (Piro & Gaensler 2018). The DM contribution from the SNR can the… view at source ↗
Figure 7
Figure 7. Figure 7: Illustration of FRB estimated evolutionary ages and DMSNR contributions within the SNR framework. Up￾per panel: Orange horizontal dashed lines show the DMexc best-fit rate for each source. The star size is reflecting burst rate. The blue solid curve represents the SNR model assum￾ing a progenitor mass of 8M⊙. The light red shaded regions (vertical extent has no physical meaning) indicate the un￾certainties… view at source ↗
read the original abstract

Fast Radio Bursts (FRBs) are millisecond-duration, highly energetic radio transients of uncertain origin. Repeating FRBs provide an excellent population for investigating their nature, particularly through studies of parameter evolution. Out of the 63 repeaters monitored by CHIME, we select the 19 sources with more than ten detected bursts, and examine their long-term dispersion measure (DM) evolution. Seven sources show statistically significant DM evolution and are classified as the golden sample. Of these, five exhibit a decreasing DM trend and two shows an increasing trend. We then perform a binomial test under the null hypothesis that decreasing and increasing DM variation trends have equal probabilities. The current combined sample, including our golden sample and additional repeaters with reported DM change rate from the literature, gives a p-value of 0.033, supporting that decreasing DM trends are more common in the repeating FRB population. This statistical result is consistent with scenarios in that the local electron density around repeaters generally decreases with time, for example due to expansion of a young supernova remnant (SNR). Finally, within the SNR expansion model, we provide an illustrative estimate of the SNR contributions to the DM for different ejecta masses.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The manuscript examines long-term dispersion measure (DM) evolution in repeating fast radio bursts (FRBs) using CHIME data on 19 sources with more than ten bursts. Seven sources show statistically significant DM evolution, with five decreasing and two increasing. A binomial test on the combined sample (CHIME golden sample plus literature sources) yields p=0.033, interpreted as evidence that decreasing DM trends are more common. This is linked to possible young supernova remnant (SNR) expansion, with illustrative estimates of SNR DM contributions for different ejecta masses.

Significance. If the statistical finding is robust after addressing selection effects, it would suggest that local electron densities around repeating FRBs tend to decrease over time, providing support for progenitor models involving young SNRs. The work identifies a 'golden sample' from systematic CHIME monitoring and combines it with literature values, offering a population-level view. The SNR connection is presented as illustrative rather than a quantitative fit to the data.

major comments (2)
  1. [Statistical analysis of DM trends] Binomial test on combined sample: the p=0.033 result (abstract and statistical analysis) treats the seven CHIME golden-sample sources plus literature repeaters as i.i.d. draws with equal probability of increasing or decreasing DM under the null. Literature sources enter only when DM change rates are reported, violating this assumption via potential publication/selection bias toward decreasing trends consistent with the SNR scenario. The CHIME-only subset alone yields p≈0.23 and does not support the claim.
  2. [Sample selection and golden sample] Golden-sample definition and multiple testing: the seven sources are selected post-hoc for statistically significant DM evolution among the 19 with >10 bursts (abstract). No correction for multiple testing across the initial 19 sources or for varying monitoring durations is described, rendering the binomial test sensitive to these choices and the small N=7.
minor comments (2)
  1. [Abstract] Abstract: 'two shows an increasing trend' contains a subject-verb agreement error and should read 'two show an increasing trend'.
  2. [SNR expansion model] SNR model section: the illustrative DM estimates depend on the free parameter 'ejecta mass'; state explicitly how the quoted DM contributions vary with this parameter and whether they can be falsified against the observed rates.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the careful and constructive review. We address the two major comments point by point below, acknowledging where the concerns are valid and outlining the changes we will implement.

read point-by-point responses

  1. Referee: [Statistical analysis of DM trends] Binomial test on combined sample: the p=0.033 result (abstract and statistical analysis) treats the seven CHIME golden-sample sources plus literature repeaters as i.i.d. draws with equal probability of increasing or decreasing DM under the null. Literature sources enter only when DM change rates are reported, violating this assumption via potential publication/selection bias toward decreasing trends consistent with the SNR scenario. The CHIME-only subset alone yields p≈0.23 and does not support the claim.

    Authors: We agree that combining the CHIME golden sample with literature sources risks publication bias, since literature values are included only when DM evolution rates have been reported. The CHIME-only binomial test indeed yields p≈0.23 and does not reach conventional significance. In the revised manuscript we will designate the CHIME golden sample as the primary analysis, report its binomial test result explicitly in the abstract and main text, and move the combined-sample result to a supplementary discussion that clearly states the selection limitations. We will also add a dedicated paragraph on possible biases in the literature compilation. revision: yes

  2. Referee: [Sample selection and golden sample] Golden-sample definition and multiple testing: the seven sources are selected post-hoc for statistically significant DM evolution among the 19 with >10 bursts (abstract). No correction for multiple testing across the initial 19 sources or for varying monitoring durations is described, rendering the binomial test sensitive to these choices and the small N=7.

    Authors: The golden sample is defined by the presence of statistically significant DM evolution within the 19 sources that have >10 bursts. We did not apply a multiple-testing correction to the initial search for significant trends. We accept that this choice, together with the small number of sources showing evolution (N=7), makes the binomial test sensitive to the adopted significance threshold and monitoring lengths. In revision we will add an explicit discussion of multiple-testing considerations, present the trend directions for all 19 sources as a robustness check, and note the limited sample size as a caveat on the strength of the population-level conclusion. revision: yes

Circularity Check

0 steps flagged

No circularity: binomial test is a direct count statistic on observed trends; SNR link is interpretive consistency only

full rationale

The paper's central step is selecting 19 CHIME repeaters, identifying 7 with significant DM evolution (5 decreasing, 2 increasing), then applying a standard binomial test under a 50/50 null to the combined sample (including literature sources) to obtain p=0.033. This is a straightforward statistical summary of the direction counts and does not reduce to the input data by construction, nor does it involve any fitted parameter renamed as a prediction. The SNR expansion scenario is explicitly offered only as one consistent interpretation, not as a model whose equations or parameters are derived from or forced by the same counts. No self-citations, uniqueness theorems, or ansatzes appear in the derivation chain. The analysis therefore remains self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 0 invented entities

The statistical preference rests on the binomial null hypothesis and the assumption that the selected sources are representative. The SNR link is an interpretive scenario rather than a derived quantity. No new entities are postulated.

free parameters (1)
  • ejecta mass in SNR model
    Used in the illustrative estimate of SNR DM contribution; values are chosen to demonstrate possible ranges rather than fitted to the FRB sample.
axioms (1)
  • domain assumption Under the null, decreasing and increasing DM trends are equally probable for each source.
    Invoked for the binomial test on the combined sample.

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Works this paper leans on

68 extracted references · 65 canonical work pages · 1 internal anchor

  1. [1]

    Radio Monitoring Campaign of Active Repeater FRB 20220912A with CHIME

    Abbott, T. C., Pearlman, A. B., Kaspi, V. M., et al. 2026, arXiv e-prints, arXiv:2604.09098, doi: 10.48550/arXiv.2604.09098

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.48550/arxiv.2604.09098 2026

  2. [2]

    C., Wong, T., & Valanju, J

    Backer, D. C., Wong, T., & Valanju, J. 2000, The Astrophysical Journal, 543, 740, doi: 10.1086/317150 14

    work page doi:10.1086/317150 2000

  3. [3]

    2022, Science, 378, abj3043, doi: 10.1126/science.abj3043

    Bailes, M. 2022, Science, 378, abj3043, doi: 10.1126/science.abj3043

    work page doi:10.1126/science.abj3043 2022

  4. [4]

    V., van Leeuwen, J., Maan, Y., et al

    Bilous, A. V., van Leeuwen, J., Maan, Y., et al. 2025, A&A, 696, A194, doi: 10.1051/0004-6361/202451413

    work page doi:10.1051/0004-6361/202451413 2025

  5. [5]

    , keywords =

    Bochenek, C. D., Ravi, V., Belov, K. V., et al. 2020, Nature, 587, 59, doi: 10.1038/s41586-020-2872-x

    work page doi:10.1038/s41586-020-2872-x 2020

  6. [6]

    2024, Nature, 632, 1014, doi: 10.1038/s41586-024-07782-6

    Bruni, G., Piro, L., Yang, Y.-P., et al. 2024, Nature, 632, 1014, doi: 10.1038/s41586-024-07782-6

    work page doi:10.1038/s41586-024-07782-6 2024

  7. [7]

    P., et al

    Bruni, G., Piro, L., Yang, Y. P., et al. 2025, A&A, 695, L12, doi: 10.1051/0004-6361/202453233

    work page doi:10.1051/0004-6361/202453233 2025

  8. [8]

    Chatterjee, C

    Chatterjee, S., Law, C. J., Wharton, R. S., et al. 2017, Nature, 541, 58, doi: 10.1038/nature20797 CHIME/FRB Collaboration, Amiri, M., Bandura, K., et al. 2018, ApJ, 863, 48, doi: 10.3847/1538-4357/aad188 CHIME/FRB Collaboration, Andersen, B. C., Bandura, K. M., et al. 2020a, Nature, 587, 54, doi: 10.1038/s41586-020-2863-y CHIME/FRB Collaboration, Amiri, ...

    work page doi:10.1038/nature20797 2017

  9. [9]

    A gas-rich cosmic web revealed by the partitioning of the missing baryons.Nature Astronomy, 9: 1226, 2025

    Connor, L., Ravi, V., Sharma, K., et al. 2025, Nature Astronomy, 9, 1226, doi: 10.1038/s41550-025-02566-y

    work page doi:10.1038/s41550-025-02566-y 2025

  10. [10]

    M., Shin, K., Pleunis, Z., et al

    Cook, A. M., Shin, K., Pleunis, Z., et al. 2026, arXiv e-prints, arXiv:2605.08410. https://arxiv.org/abs/2605.08410

    Pith/arXiv arXiv 2026

  11. [11]

    , keywords =

    Cordes, J. M., & Chatterjee, S. 2019, ARA&A, 57, 417, doi: 10.1146/annurev-astro-091918-104501

    work page doi:10.1146/annurev-astro-091918-104501 2019

  12. [12]

    W., Li, D., & Zhang, C.-M

    Cui, X.-H., James, C. W., Li, D., & Zhang, C.-M. 2025, ApJ, 982, 158, doi: 10.3847/1538-4357/adbbcb

    work page doi:10.3847/1538-4357/adbbcb 2025

  13. [13]

    , keywords =

    Cui, X.-H., Zhang, C.-M., Wang, S.-Q., et al. 2021, MNRAS, 500, 3275, doi: 10.1093/mnras/staa3351

    work page doi:10.1093/mnras/staa3351 2021

  14. [14]

    2022, Ap&SS, 367, 66, doi: 10.1007/s10509-022-04093-y

    Cui, X.-H., Zhang, C.-M., Li, D., et al. 2022, Ap&SS, 367, 66, doi: 10.1007/s10509-022-04093-y

    work page doi:10.1007/s10509-022-04093-y 2022

  15. [15]

    , keywords =

    Curtin, A. P., Sand, K. R., Pleunis, Z., et al. 2025, ApJ, 992, 206, doi: 10.3847/1538-4357/adf844

    work page doi:10.3847/1538-4357/adf844 2025

  16. [16]

    2026, ApJ, 1004, 179, doi: 10.3847/1538-4357/ae731b

    Feng, Y., Zhou, D., Zhang, Y., et al. 2026, ApJ, 1004, 179, doi: 10.3847/1538-4357/ae731b

    work page doi:10.3847/1538-4357/ae731b 2026

  17. [17]

    Science , keywords =

    Feng, Y., Li, D., Yang, Y.-P., et al. 2022, Science, 375, 1266, doi: 10.1126/science.abl7759

    work page doi:10.1126/science.abl7759 2022

  18. [18]

    , keywords =

    Fonseca, E., Andersen, B. C., Bhardwaj, M., et al. 2020, ApJL, 891, L6, doi: 10.3847/2041-8213/ab7208

    work page doi:10.3847/2041-8213/ab7208 2020

  19. [19]

    doi:10.1086/175038 , eprint =

    Frail, D. A., Goss, W. M., & Whiteoak, J. B. Z. 1994, ApJ, 437, 781, doi: 10.1086/175038

    work page doi:10.1086/175038 1994

  20. [20]

    Frank, J., King, A., & Raine, D. J. 2002, Accretion Power in Astrophysics: Third Edition FRB Collaboration, Abbott, T., Andersen, B. C., et al. 2026, arXiv e-prints, arXiv:2601.09399, doi: 10.48550/arXiv.2601.09399

    work page doi:10.48550/arxiv.2601.09399 2002

  21. [21]

    , keywords =

    Gardenier, D. W., Connor, L., van Leeuwen, J., Oostrum, L. C., & Petroff, E. 2021, A&A, 647, A30, doi: 10.1051/0004-6361/202039626

    work page doi:10.1051/0004-6361/202039626 2021

  22. [22]

    2024, A&A, 692, A170, doi: 10.1051/0004-6361/202450740

    Iraci, F., Chalumeau, A., Tiburzi, C., et al. 2024, A&A, 692, A170, doi: 10.1051/0004-6361/202450740

    work page doi:10.1051/0004-6361/202450740 2024

  23. [23]

    , keywords =

    James, C. W., Prochaska, J. X., Macquart, J. P., et al. 2022, MNRAS, 509, 4775, doi: 10.1093/mnras/stab3051

    work page doi:10.1093/mnras/stab3051 2022

  24. [24]

    2017, ApJ, 837, 84, doi: 10.3847/1538-4357/aa618e

    Janka, H.-T. 2017, ApJ, 837, 84, doi: 10.3847/1538-4357/aa618e

    work page doi:10.3847/1538-4357/aa618e 2017

  25. [25]

    C., et al

    Kumar, P., Luo, R., Price, D. C., et al. 2023, MNRAS, 526, 3652, doi: 10.1093/mnras/stad2969

    work page doi:10.1093/mnras/stad2969 2023

  26. [26]

    Y., Jordan, C

    Kuzmin, A., Losovsky, B. Y., Jordan, C. A., & Smith, F. G. 2008, A&A, 483, 13, doi: 10.1051/0004-6361:20079211

    work page doi:10.1051/0004-6361:20079211 2008

  27. [27]

    2024, ApJL, 967, L44, doi: 10.3847/2041-8213/ad4ae8

    Lan, H.-T., Zhao, Z.-Y., Wei, Y.-J., & Wang, F.-Y. 2024, ApJL, 967, L44, doi: 10.3847/2041-8213/ad4ae8

    work page doi:10.3847/2041-8213/ad4ae8 2024

  28. [28]

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

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

    work page doi:10.1109/mmm.2018.2802178 2018

  29. [29]

    , keywords =

    Li, D., Wang, P., Zhu, W. W., et al. 2021, Nature, 598, 267, doi: 10.1038/s41586-021-03878-5

    work page doi:10.1038/s41586-021-03878-5 2021

  30. [30]

    B., Yang, Y

    Li, Y., Zhang, S. B., Yang, Y. P., et al. 2026, Science, 391, 280, doi: 10.1126/science.adq3225

    work page doi:10.1126/science.adq3225 2026

  31. [31]

    2024, ApJ, 975, 75, doi: 10.3847/1538-4357/ad779d

    Lin, H.-H., Scholz, P., Ng, C., et al. 2024, ApJ, 975, 75, doi: 10.3847/1538-4357/ad779d

    work page doi:10.3847/1538-4357/ad779d 2024

  32. [32]

    2012, Handbook of Pulsar Astronomy

    Lorimer, D., & Kramer, M. 2012, Handbook of Pulsar Astronomy

    2012

  33. [33]

    A Bright Millisecond Radio Burst of Extragalactic Origin.Science2007,318, 777

    Lorimer, D. R., Bailes, M., McLaughlin, M. A., Narkevic, D. J., & Crawford, F. 2007, Science, 318, 777, doi: 10.1126/science.1147532

    work page doi:10.1126/science.1147532 2007

  34. [34]

    R., & Zhang, B

    Luo, R., Lee, K., Lorimer, D. R., & Zhang, B. 2018, MNRAS, 481, 2320, doi: 10.1093/mnras/sty2364

    work page doi:10.1093/mnras/sty2364 2018

  35. [35]

    P., & Ekers, R

    Macquart, J. P., & Ekers, R. 2018, MNRAS, 480, 4211, doi: 10.1093/mnras/sty2083

    work page doi:10.1093/mnras/sty2083 2018

  36. [36]

    , keywords =

    Macquart, J. P., Prochaska, J. X., McQuinn, M., et al. 2020, Nature, 581, 391, doi: 10.1038/s41586-020-2300-2

    work page doi:10.1038/s41586-020-2300-2 2020

  37. [37]

    F., & Truelove, J

    McKee, C. F., & Truelove, J. K. 1995, PhR, 256, 157, doi: 10.1016/0370-1573(94)00106-D

    work page doi:10.1016/0370-1573(94)00106-d 1995

  38. [38]

    W., Lyne, A

    McKee, J. W., Lyne, A. G., Stappers, B. W., Bassa, C. G., & Jordan, C. A. 2018, MNRAS, 479, 4216, doi: 10.1093/mnras/sty1727

    work page doi:10.1093/mnras/sty1727 2018

  39. [39]

    Michilli, D., Seymour, A., Hessels, J. W. T., et al. 2018, Nature, 553, 182, doi: 10.1038/nature25149

    work page doi:10.1038/nature25149 2018

  40. [40]

    M., Bhandari, S., Drout, M

    Moroianu, A. M., Bhandari, S., Drout, M. R., et al. 2025, arXiv e-prints, arXiv:2509.05174, doi: 10.48550/arXiv.2509.05174

    work page doi:10.48550/arxiv.2509.05174 2025

  41. [41]

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

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

    work page doi:10.1142/s0218271811019335 2011

  42. [42]

    , keywords =

    Niu, C. H., Aggarwal, K., Li, D., et al. 2022, Nature, 606, 873, doi: 10.1038/s41586-022-04755-5 15

    work page doi:10.1038/s41586-022-04755-5 2022

  43. [43]

    Science Bulletin , keywords =

    Niu, C.-H., Li, D., Yang, Y.-P., et al. 2025, Science Bulletin, doi: https://doi.org/10.1016/j.scib.2025.11.023

    work page doi:10.1016/j.scib.2025.11.023 2025

  44. [44]

    C., Maan, Y., van Leeuwen, J., et al

    Oostrum, L. C., Maan, Y., van Leeuwen, J., et al. 2020, A&A, 635, A61, doi: 10.1051/0004-6361/201937422

    work page doi:10.1051/0004-6361/201937422 2020

  45. [45]

    2026, ApJL, 1000, L53, doi: 10.3847/2041-8213/ae52f8

    Pandhi, A., Nimmo, K., Andrew, S., et al. 2026, ApJL, 1000, L53, doi: 10.3847/2041-8213/ae52f8

    work page doi:10.3847/2041-8213/ae52f8 2026

  46. [46]

    Petroff, E., Hessels, J. W. T., & Lorimer, D. R. 2022, A&A Rv, 30, 2, doi: 10.1007/s00159-022-00139-w

    work page doi:10.1007/s00159-022-00139-w 2022

  47. [47]

    Shannon, R. M. 2013, MNRAS, 435, 1610, doi: 10.1093/mnras/stt1401

    work page doi:10.1093/mnras/stt1401 2013

  48. [48]

    L., & Gaensler, B

    Piro, A. L., & Gaensler, B. M. 2018, ApJ, 861, 150, doi: 10.3847/1538-4357/aac9bc

    work page doi:10.3847/1538-4357/aac9bc 2018

  49. [49]

    , keywords =

    Rajwade, K. M., Mickaliger, M. B., Stappers, B. W., et al. 2020, MNRAS, 495, 3551, doi: 10.1093/mnras/staa1237

    work page doi:10.1093/mnras/staa1237 2020

  50. [50]

    J., Li, D., et al

    Ravi, V., Law, C. J., Li, D., et al. 2022, MNRAS, 513, 982, doi: 10.1093/mnras/stac465

    work page doi:10.1093/mnras/stac465 2022

  51. [51]

    Sedov, L. I. 1946, Journal of Applied Mathematics and Mechanics, 10, 241

    1946

  52. [52]

    2017, ApJ, 849, 87, doi: 10.3847/1538-4357/aa932c

    Shang, L.-H., Zhang, C.-M., Li, D., et al. 2017, ApJ, 849, 87, doi: 10.3847/1538-4357/aa932c

    work page doi:10.3847/1538-4357/aa932c 2017

  53. [53]

    P., Hessels, J

    Snelders, M. P., Hessels, J. W. T., Huang, J., et al. 2025, arXiv e-prints, arXiv:2510.11352, doi: 10.48550/arXiv.2510.11352

    work page doi:10.48550/arxiv.2510.11352 2025

  54. [54]

    M., Connor, L., & van Leeuwen, J

    Straal, S. M., Connor, L., & van Leeuwen, J. 2020, A&A, 634, A105, doi: 10.1051/0004-6361/201833376

    work page doi:10.1051/0004-6361/201833376 2020

  55. [55]

    1950, Proceedings of the Royal Society of London Series A, 201, 159, doi: 10.1098/rspa.1950.0049

    Taylor, G. 1950, Proceedings of the Royal Society of London Series A, 201, 159, doi: 10.1098/rspa.1950.0049

    work page doi:10.1098/rspa.1950.0049 1950

  56. [56]

    , keywords =

    Uttarkar, P. A., Shannon, R. M., Gourdji, K., et al. 2026, MNRAS, 545, staf1997, doi: 10.1093/mnras/staf1997

    work page doi:10.1093/mnras/staf1997 2026

  57. [57]

    Y., Zhang, G

    Wang, F. Y., Zhang, G. Q., Dai, Z. G., & Cheng, K. S. 2022, Nature Communications, 13, 4382, doi: 10.1038/s41467-022-31923-y

    work page doi:10.1038/s41467-022-31923-y 2022

  58. [58]

    S., Yang, Y

    Wang, P., Zhang, J. S., Yang, Y. P., et al. 2025, arXiv e-prints, arXiv:2507.15790, doi: 10.48550/arXiv.2507.15790

    work page doi:10.48550/arxiv.2507.15790 2025

  59. [59]

    , keywords =

    Wang, Y., & van Leeuwen, J. 2024, A&A, 690, A377, doi: 10.1051/0004-6361/202450673

    work page doi:10.1051/0004-6361/202450673 2024

  60. [60]

    2023, MNRAS, 524, 569, doi: 10.1093/mnras/stad1922

    Wang, Y.-B., Kurban, A., Zhou, X., Yu, Y.-W., & Wang, N. 2023, MNRAS, 524, 569, doi: 10.1093/mnras/stad1922

    work page doi:10.1093/mnras/stad1922 2023

  61. [61]

    , author =

    Xu, H., Niu, J. R., Chen, P., et al. 2022, Nature, 609, 685, doi: 10.1038/s41586-022-05071-8

    work page doi:10.1038/s41586-022-05071-8 2022

  62. [62]

    2017, ApJ, 847, 22, doi: 10.3847/1538-4357/aa8721

    Yang, Y.-P., & Zhang, B. 2017, ApJ, 847, 22, doi: 10.3847/1538-4357/aa8721

    work page doi:10.3847/1538-4357/aa8721 2017

  63. [63]

    , author =

    Yao, J. M., Manchester, R. N., & Wang, N. 2017, ApJ, 835, 29, doi: 10.3847/1538-4357/835/1/29

    work page doi:10.3847/1538-4357/835/1/29 2017

  64. [64]

    The physics of fast radio bursts.Rev

    Zhang, B. 2023, Reviews of Modern Physics, 95, 035005, doi: 10.1103/RevModPhys.95.035005

    work page doi:10.1103/revmodphys.95.035005 2023

  65. [65]

    2026, ApJ, 996, 4, doi: 10.3847/1538-4357/ae20f6

    Zhang, J.-h., Niu, C.-H., Zhu, Y.-h., et al. 2026, ApJ, 996, 4, doi: 10.3847/1538-4357/ae20f6

    work page doi:10.3847/1538-4357/ae20f6 2026

  66. [66]

    arXiv e-prints , keywords =

    Zhang, J.-S., Wang, T.-C., Wang, P., et al. 2025, arXiv e-prints, arXiv:2507.14707, doi: 10.48550/arXiv.2507.14707

    work page doi:10.48550/arxiv.2507.14707 2025

  67. [67]

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

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

    work page doi:10.1088/1674-4527/ac98f7 2022

  68. [68]

    , keywords =

    Zhang, Y.-K., Li, D., Zhang, B., et al. 2023, ApJ, 955, 142, doi: 10.3847/1538-4357/aced0b

    work page doi:10.3847/1538-4357/aced0b 2023