Pith. sign in

REVIEW 3 major objections 6 minor 46 references

Extending the short gamma-ray burst population from sub-threshold triggers in Fermi/GBM and GECAM data and its implications

T0 review · 3 major / 6 minor · reviewed 2026-08-05 · deepseek-v4-flash

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

Pith's one-line read Jointly checking Fermi/GBM sub-threshold triggers against GECAM data recovers dozens of short gamma-ray bursts that onboard triggers miss, potentially doubling the measured short-GRB rate.

desk verdict Useful sample paper: first GECAM cross-check of GBM sub-threshold triggers yields 49 confirmed transients, but the ~80/yr rate extrapolation is not yet supported. read the letter →

arxiv 2509.02995 v1 pith:5IRCCFVP submitted 2025-09-03 astro-ph.HE

Ce Cai , Shao-Lin Xiong , Yan-Qiu Zhang , Jin-Peng Zhang , Ping Wang , Yao-Guang Zheng , Shi-Jie Zheng , Shuo Xiao
show 16 more authors
Hao-Xuan Guo Jia-Cong Liu Yang-Zhao Ren Wen-Jun Tan Chen-Wei Wang Yue Wang Sheng-Lun Xie Wang-Chen Xue Zheng-Hang Yu Peng Zhang Wen-Long Zhang Chao Zheng Jia-Wei Luo Shuai Zhang Li-Ming Song Shuang-Nan Zhang
This is my paper
classification astro-ph.HE
keywords shortgamma-rayburstsFermi/GBMsub-thresholdtriggersGECAMmulti-instrumentjointanalysiscompactobjectmergersbinaryneutronstarmergerrategravitational-wavecounterparts
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

The paper targets short gamma-ray bursts that are real astrophysical events but fall below the on-board trigger threshold of Fermi/GBM. By running a joint likelihood-ratio search that combines GBM data with GECAM-B and GECAM-C data, the authors verify 49 of 181 visible sub-threshold candidates as real transients and classify 41 as short GRBs. They argue that this raises GBM's short-GRB detection rate from about 40 triggered events per year to roughly 50 per year, and that a complete joint monitoring program could reach about 80 per year, a factor-of-two improvement. If right, current short-GRB catalogs and the binary neutron star merger rates built on them are substantially incomplete.

What carries the argument

The engine is the paper's joint likelihood-ratio targeted search, which treats up to 49 detectors (GBM NaI detectors plus GECAM-B and GECAM-C GRDs) as one instrument. For a known source direction it computes, per detector, the log-likelihood of signal-plus-background versus background-only, then sums to a joint likelihood ratio. Expected counts come from Band-function spectral templates (soft, normal, hard) convolved with each detector response. The likelihood ratio both detects weak signals and screens them: candidates whose GBM-only likelihood ratio exceeds the joint value are rejected as local or single-instrument events such as particle hits or background fluctuations, and the remaining

What would settle it

Run the same joint search on all 466 REL>=5 sub-threshold events from 2021-2024 with full localization propagation and complete GECAM coverage, then compare the confirmed short-GRB count per year with the roughly 10 per year claimed here and the roughly 41 per year extrapolation; if the visible subset is not representative, the projected 80 per year will not reproduce.

Watch

Extended reading notes

Core claim

The central discovery is a verified multi-instrument sample of 41 short gamma-ray bursts hiding in the Fermi/GBM sub-threshold trigger archive between 2021 and 2024, plus 8 additional confirmed transients that are not short. For each of 466 sub-threshold events with reliability score at least 5, the authors search GBM and GECAM data jointly under signal-plus-background versus background-only hypotheses. Among the 181 events whose central position is visible to GECAM, 116 pass the likelihood threshold and 49 survive multi-instrument coincidence and manual checks. The paper's rate argument converts the observed confirmation rates (35% short-burst fraction at the highest reliability level, 6% a

Load-bearing premise

The entire 80-per-year projection rests on assuming that the short-burst confirmation rates measured on the 181 GBM sub-threshold events visible to GECAM (35% at the highest reliability level, 6% at the lower level) apply to all 2057 events in the archive, even though visibility was judged by central position only and the paper says this neglects localization uncertainty.

Editorial extensions

If this is right

  • Fermi/GBM's measured short-GRB rate rises from about 40 triggered events per year to about 50 per year once GECAM-confirmed sub-threshold events are included.
  • If the confirmation rates hold across the full archive, complete joint GBM plus GECAM monitoring would recover about 41 additional sub-threshold short GRBs per year, bringing the total near 80 per year, roughly double the triggered-only rate.
  • The confirmed sub-threshold population is dominated by the highest-reliability archive events, with 36 of the 41 short GRBs coming from the REL=8 class, so the archive's reliability score is a useful prior for real astrophysical origin.
  • No gravitational-wave coincidence was found within plus-or-minus 30 seconds for the short-GRB candidates overlapping the O4 run, consistent with the rarity of joint detections and with the sample still being small.
  • The improved rates directly affect estimates of the local formation rate of short GRBs and the binary neutron star merger rate, though the paper does not quantify the shift.

Reading between the lines

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

  • If the factor-of-two rate increase is real, volumetric short-GRB and binary neutron star merger rates derived from triggered catalogs alone are likely underestimated by a comparable factor; the paper flags this consequence but leaves it unquantified.
  • Because visibility was judged from central GBM positions while neglecting localization uncertainty, the true number of sub-threshold events inside GECAM's field of view is probably higher than 181, which would push the extrapolated rate above 80 per year rather than below.
  • The same joint-search machinery could be applied to the long-duration sub-threshold population; the paper reports only counts for comparison, so a comparable population of missed long gamma-ray bursts remains unquantified.
  • A direct test of the extrapolation is to extend the joint search to the full GBM sub-threshold archive using any other wide-field gamma-ray monitor for cross-checks; independent instruments would separate true astrophysical events from residual particle backgrounds.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 6 minor

Summary. The paper presents a targeted search for gamma-ray transients in the Fermi/GBM sub-threshold trigger archive using the ETJASMIN joint likelihood pipeline together with GECAM-B and GECAM-C data. From 466 GBM sub-threshold events with reliability ≥5 during 2021–2024, 181 are considered visible to GECAM; joint analysis yields 116 LR candidates, of which 49 survive multi-instrument coincidence checks and manual inspection. Of these, 41 are classified as SGRBs, implying an additional ~10 SGRBs/yr, and the paper claims a combined GBM triggered plus GECAM-recovered rate of ~50 SGRBs/yr. The authors then extrapolate from the GECAM-visible short-burst fractions (35% for REL=8 and 6% for REL=5) to the full 8-year sub-threshold archive, projecting ~80 SGRBs/yr under complete multi-instrument monitoring. A search for temporal coincidences with LIGO-Virgo-KAGRA O4 GW candidates yields no associations.

Significance. If the in-sample result holds, the 49-event catalog is a valuable extension of the faint SGRB population and a useful demonstration of multi-instrument sub-threshold recovery. The use of independent GECAM data to confirm GBM sub-threshold triggers is a strong cross-check, and Table 1 is a useful resource. However, the headline extrapolated rate of ~80/yr is not currently supported: it relies on an unquantified manual screening step, an unspecified/borrowed LR threshold, and a selection-function-free extrapolation from a visibility-limited sample. The paper itself acknowledges that the visibility estimate is a lower bound, which makes the extrapolation particularly fragile. With a proper statistical treatment, the central catalog result could be publishable, but the rate projection must be revised or heavily qualified.

major comments (3)
  1. [§6.1, rate extrapolation] The headline '~80 SGRBs/yr' rests on multiplying full-archive REL=8 and REL=5 counts (709 and 1348) by short-GRB fractions measured only in the GECAM-visible subsample (36/102=0.35 and 5/79=0.06). This assumes the visible subsample is representative of all sub-threshold events, but the visibility selection is based only on central-position geometry (a lower bound, as the paper acknowledges) and GECAM's detection efficiency is not folded in. No selection-function correction or uncertainty is given. The statistical error on the REL=5 fraction alone is large (5 counts; Poisson 95% CI roughly 2–15%). In addition, the visibility fractions stated in the same section—'~17% of REL=5' and '~22% of REL=8'—are inconsistent with the sample counts (79/239≈33%, 102/227≈45%), so the reader cannot tell which numbers to trust. Please recompute the extrapolation with a proper selection function, or presen
  2. [§4.2, burst identification] The 116 LR candidates are reduced to 49 by a step described as 'manual inspection guided by empirical judgment' in addition to the quantitative GBM-only LR vs joint LR cut. The manual step is not specified: no list of rejected candidates, no decision criteria, and no blind-injection validation. Because the central result (49 confirmed events) depends directly on this screening, the procedure needs to be made reproducible—for example, by quantifying the visual criteria, reporting how many candidates were rejected for each reason (localization mismatch, single-instrument excess, particle event), and demonstrating via simulations that the manual step does not bias the sample. Without this, the catalog cannot be independently re-derived.
  3. [§4.1, detection threshold] The joint LR threshold is not stated in this paper; it is adopted 'based on empirical experience from the GECAM search pipeline' and referenced to Table 1 of Cai et al. (2025a). Since the present search uses a different detector set (GBM + GECAM-B + GECAM-C) and a different time window, the false-alarm rate of the adopted threshold for this specific configuration should be demonstrated. The 10^5 background simulations are described, but the threshold value and the resulting expected number of false positives among the 466 events are not reported. Please give the threshold in LR units and the expected false-positive count.
minor comments (6)
  1. [§6.1] The '17%' and '22%' visibility fractions appear to be computed relative to the total 466 events (79/466 and 102/466), not relative to the REL=5 and REL=8 subsamples as worded. Please correct the wording or the calculation.
  2. [§6.2] There is an extra parenthesis in 'Figure 6))'; also ensure all figure callouts match the actual figure numbering.
  3. [References] The entry 'Zhang, Y. Q., et al. 2025' is incomplete and conflicts with 'Zhang et al. 2025' in the text; provide the full author list and journal reference.
  4. [Table 1] For the GECAM-B and GECAM-C flags, clarify whether 0 means 'not in field of view' or 'in field of view but not detected'—the current note only defines 1.
  5. [General] The terms 'sub-threshold' and 'subthreshold' are used inconsistently; pick one form.
  6. [§6.3] For the GW search, please state explicitly the number of O4 GW candidates used, the exact time window, and whether localization information was used or only temporal coincidence.

Circularity Check

0 steps flagged · score 0.0 of 10

No circularity: the core 49-event confirmation rests on independent GECAM data; the ~80/yr extrapolation is a flagged selection-function assumption, not a definitional reduction.

full rationale

The central empirical claim (49 confirmed transients, 41 SGRBs) is a count of events that pass a joint likelihood search and show temporally coincident excesses in independent GECAM-B/C data; it is not defined in terms of the conclusion. The likelihood-ratio formalism (Eqs. 1-4) is a standard method, and the spectral templates are taken from external work (Band et al. 1993; Connaughton et al. 2015). The detection threshold is adopted from the authors' prior pipeline paper (Cai et al. 2025a), but that threshold is an input parameter and does not encode the SGRB-rate claim; this is normal methodological self-citation, not a load-bearing circular step. The ~80/yr figure does not reduce to its inputs by construction: it multiplies measured confirmation fractions (35% for REL=8, 6% for REL=5) by full-catalog counts, an extrapolation that assumes the GECAM-visible subsample is representative. The paper itself flags the visibility criterion as an approximate lower bound that neglects localization uncertainty (Section 3 and Section 6.1), and the REL=5 short-burst fraction is based on only 5 events, giving large Poisson uncertainty. These are statistical/selection-function limitations, not circularity. No equation is equivalent to its own input, no fitted parameter is renamed as a prediction, and no uniqueness claim is imported from self-citations. Therefore no significant circularity is found.

Assumptions & free parameters 3 free parameters · 5 assumptions · 0 invented entities

The paper introduces no new physical entities or parameters beyond the empirically chosen detection threshold, per-event timescales, and template choices. The load-bearing assumptions are observational: the REL prior, the visibility approximation, the transferability of the pipeline threshold, the reliability of manual screening, and the representativeness of the visible subsample for the extrapolated rate.

free parameters (3)
  • Joint LR detection threshold = not stated in this paper; adopted from Table 1 of Cai et al. (2025a)
    The threshold determining which candidates are selected (116 out of 181) is empirically set by background simulations and past GECAM search experience; it directly determines the sample size and rates.
  • Per-event search timescale = 0.05, 0.1, 0.2, 0.5, 1, or 2 s (Table 1)
    For each burst, the timescale bin that maximizes the joint LR is chosen, so the LR and significance depend on this per-event choice.
  • Per-event spectral template = RspSoft, RspNorm, or RspHard
    Each event is assigned one of three template spectra from Connaughton et al. (2015) to compute expected counts; the choice affects the LR and amplitude estimate.
assumptions (5)
  • domain assumption GBM sub-threshold reliability score REL >= 5 indicates a candidate with meaningful probability of astrophysical origin
    Defines the sample of 466 events (Section 3); no independent validation of REL's calibration is provided.
  • domain assumption GECAM visibility can be judged from the GBM-reported central sky position, ignoring localization uncertainty
    Section 3 explicitly states this approximation; leads to 181 events, and the paper admits the visible fraction is a lower bound.
  • domain assumption The joint LR threshold calibrated on synthetic background light curves in prior self-cited work applies to these real data
    Section 4.1 adopts the threshold 'based on empirical experience' from Cai et al. (2025a); the exact value and its transferability are not shown.
  • domain assumption Multi-instrument coincidence plus visual inspection reliably separates astrophysical transients from particle or background events
    Section 4.2 uses manual inspection to remove 67 candidates; no objective classifier or false-alarm estimate for this step is provided.
  • ad hoc to paper Confirmation rates measured in the GECAM-visible subset apply to all GBM sub-threshold events
    Section 6.1 extrapolates 709 x 0.35 and 1348 x 0.06 to estimate about 248 plus 80 short GRBs; this assumes the visible subset is representative, which is not justified and is acknowledged only as a lower-bound visibility approximation.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Extending the short gamma-ray burst population from sub-threshold triggers in Fermi/GBM and GECAM data and its implications." pith.science (2026). https://pith.science/paper/5IRCCFVP

@misc{pith2026250902995,
  author       = {Pith},
  title        = {Pith review of: Extending the short gamma-ray burst population from sub-threshold triggers in Fermi/GBM and GECAM data and its implications},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/5IRCCFVP}},
  note         = {Machine review of arXiv:2509.02995}
}
read the original abstract

Detection of short gamma-ray bursts (SGRBs) is critically important for the research of compact object mergers and multi-messenger astrophysics, but a significant part of SGRBs fall below the trigger threshold of GRB detectors, and thus are often missed. Here we present a systematic search for and verification of missed SGRBs using Fermi/GBM subthreshold triggers, jointly analyzing data from GBM, GECAM-B, and GECAM-C. Among 466 Fermi/GBM sub-threshold events (with reliability >= 5) from 2021 to 2024, 181 are within GECAM's field of view. We find that 49 out of 181 are confirmed astrophysical transients, and 41 can be classified as SGRBs. Thus, the SGRB detection rate of Fermi/GBM is increased to about 50 per year. Additionally, a complete multi-instrument monitoring and systematic verification of GBM sub-threshold events is expected to further increase the SGRB rate to about 80 per year, which is about 100% improvement relative to the GBM-triggered SGRBs. These results may have important implications on the local formation rate of SGRBs and the binary neutron star merger rate. We also searched for potential temporal coincidences between these SGRBs and gravitational waves from the LIGO-Virgo-KAGRA O4 run resulting in no detection.

Figures

Figures reproduced from arXiv: 2509.02995 by the authors.

Figure 1
Figure 1. Distribution of the joint likelihood ratio (LR) values for the 116 candidates exceeding the LR thresholds (marked in gray). The blue bars represent all events exceed￾ing the predefined LR thresholds that were not confirmed by manual inspection, while the orange bars indicate those further confirmed through visual inspection [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Distribution of the likelihood ratio (LR) for the 49 validated events, separated by GBM reliability score. Events with a reliability score of 5 are shown in yellow, while those with a score of 8 are shown in blue [PITH_FULL_IMAGE:figures/full_fig_p003_2.png] view at source ↗
Figure 5
Figure 5. Light curves of a sub-threshold burst detected by GBM and GECAM-B. The event occurred at T0 = 2021-08-22T15:32:13.83 (UTC). Count rates are plotted with 50 ms resolution. The shaded region indicates the time bin that maximizes the joint signal significance (approximately 12 σ). are analyzed jointly to maximize sensitivity. This joint analysis is enabled by the similar detector responses among the NaI and GRD instrum… view at source ↗
Figures from the paper (4 more)
Figure 4
Figure 4. Figure 4: Light curves of a sub-threshold burst detected jointly by GBM and GECAM-C. The event occurred at T0 = 2023-02-04T03:06:30.391 (UTC). Count rates are shown with 50 ms bins. The shaded region indicates the time bin that maximizes the joint signal significance (approximat…
Figure 6
Figure 6. Figure 6: Joint light curves of a sub-threshold burst detected on 2022 December 15 at T0 = 08:23:07.50 (UTC). The left panels show the summed counts from all detectors in GBM , GECAM-B, and GECAM-C. The right panels present the optimized light curves, where counts from all detec…
Figure 7
Figure 7. Figure 7: Likelihood ratio vs. the time offset (∆t) between the GBM trigger time and the center of the detection window that resulted in the highest signal significance for the burst in our sample. Events are separated by duration: short￾duration bursts (<2 s, blue circles) and …
Figure 8
Figure 8. Figure 8: Distribution of burst durations for the 49 sub￾threshold events. Orange bars represent short-duration bursts (<2 s), and blue bars represent long-duration bursts (≥2 s). As shown in [PITH_FULL_IMAGE:figures/full_fig_p007_8.png]

Discussion (0). Sign in to comment.

Reference graph

Works this paper leans on

46 extracted references · 24 canonical work pages

  1. [1]

    P., Abbott, R., Abbott, T

    Abbott, B. P., Abbott, R., Abbott, T. D., et al. 2016, PhRvD, 93, 122003, doi: 10.1103/PhysRevD.93.122003 —. 2017a, PhRvL, 119, 161101, doi: 10.1103/PhysRevLett.119.161101 —. 2017b, ApJL, 848, L13, doi: 10.3847/2041-8213/aa920c —. 2019, Physical Review X, 9, 031040, doi: 10.1103/PhysRevX.9.031040

    doi:10.1103/physrevd.93.122003 2016

  2. [2]

    D., Abraham, S., et al

    Abbott, R., Abbott, T. D., Abraham, S., et al. 2021, Physical Review X, 11, 021053, doi: 10.1103/PhysRevX.11.021053

    doi:10.1103/physrevx.11.021053 2021

  3. [3]

    D., Acernese, F., et al

    Abbott, R., Abbott, T. D., Acernese, F., et al. 2023, Phys. Rev. X, 13, 041039, doi: 10.1103/PhysRevX.13.041039

    doi:10.1103/physrevx.13.041039 2023

  4. [4]

    2015, Classical and Quantum Gravity, 32, 024001, doi: 10.1088/0264-9381/32/2/024001

    Acernese, F., Agathos, M., Agatsuma, K., et al. 2015, Classical and Quantum Gravity, 32, 024001, doi: 10.1088/0264-9381/32/2/024001

    doi:10.1088/0264-9381/32/2/024001 2015

  5. [5]

    2021, Progress of Theoretical and Experimental Physics, 2021, 05A101, doi: 10.1093/ptep/ptaa125

    Akutsu, T., Ando, M., Arai, K., et al. 2021, Progress of Theoretical and Experimental Physics, 2021, 05A101, doi: 10.1093/ptep/ptaa125

    doi:10.1093/ptep/ptaa125 2021

  6. [6]

    2022, Radiation Detection Technology and Methods, 6, 43

    An, Z.-H., Sun, X.-L., Zhang, D.-L., et al. 2022, Radiation Detection Technology and Methods, 6, 43

    work page 2022

  7. [7]

    2023, arXiv e-prints, arXiv:2303.01203, doi: 10.48550/arXiv.2303.01203

    An, Z.-H., Antier, S., Bi, X.-Z., et al. 2023, arXiv e-prints, arXiv:2303.01203, doi: 10.48550/arXiv.2303.01203

    doi:10.48550/arxiv.2303.01203 2023

  8. [8]

    1993, ApJ, 413, 281, doi: 10.1086/172995

    Band, D., Matteson, J., Ford, L., et al. 1993, ApJ, 413, 281, doi: 10.1086/172995

    doi:10.1086/172995 1993

Show all 46 references
  1. [9]

    S., Camp, J., et al

    Blackburn, L., Briggs, M. S., Camp, J., et al. 2015, ApJS, 217, 8, doi: 10.1088/0067-0049/217/1/8

    2015 doi

  2. [10]

    L., Li, C

    Cai, C., Xiong, S. L., Li, C. K., et al. 2021, MNRAS, 508, 3910, doi: 10.1093/mnras/stab2760

    2021 doi

  3. [11]

    2023, MNRAS, 518, 2005, doi: 10.1093/mnras/stac3075

    Cai, C., Xiong, S.-L., Xue, W.-C., et al. 2023, MNRAS, 518, 2005, doi: 10.1093/mnras/stac3075

    2023 doi

  4. [12]

    2025a, Science China Physics, Mechanics, and Astronomy, 68, 239511, doi: 10.1007/s11433-024-2544-3 —

    Cai, C., Zhang, Y.-Q., Xiong, S.-L., et al. 2025a, Science China Physics, Mechanics, and Astronomy, 68, 239511, doi: 10.1007/s11433-024-2544-3 —. 2025b, ApJS, 277, 9, doi: 10.3847/1538-4365/adacdf

    doi

  5. [13]

    2022, ApJ, 935, 10, doi: 10.3847/1538-4357/ac7ff8

    Chen, Y.-P., Li, J., Xiong, S.-L., et al. 2022, ApJ, 935, 10, doi: 10.3847/1538-4357/ac7ff8

    2022 doi

  6. [14]

    S., Goldstein, A., et al

    Connaughton, V., Briggs, M. S., Goldstein, A., et al. 2015, ApJS, 216, 32, doi: 10.1088/0067-0049/216/2/32

    2015 doi

  7. [15]

    2016, ApJL, 826, L6, doi: 10.3847/2041-8205/826/1/L6

    Connaughton, V., Burns, E., Goldstein, A., et al. 2016, ApJL, 826, L6, doi: 10.3847/2041-8205/826/1/L6

    2016 doi

  8. [16]

    2024, Science China Physics, Mechanics, and Astronomy, 67, 111013, doi: 10.1007/s11433-024-2458-9

    Feng, P.-Y., An, Z.-H., Zhang, D.-L., et al. 2024, Science China Physics, Mechanics, and Astronomy, 67, 111013, doi: 10.1007/s11433-024-2458-9

    2024 doi

  9. [17]

    2024, ApJ, 964, 149, doi: 10.3847/1538-4357/ad1eed

    Fletcher, C., Wood, J., Hamburg, R., et al. 2024, ApJ, 964, 149, doi: 10.3847/1538-4357/ad1eed

    2024 doi

  10. [18]

    2017, ApJL, 848, L14, doi: 10.3847/2041-8213/aa8f41

    Goldstein, A., Veres, P., Burns, E., et al. 2017, ApJL, 848, L14, doi: 10.3847/2041-8213/aa8f41

    2017 doi

  11. [19]

    M., Savchenko, V., & Yu, H

    Greiner, J., Burgess, J. M., Savchenko, V., & Yu, H. F. 2016, ApJL, 827, L38, doi: 10.3847/2041-8205/827/2/L38

    2016 doi

  12. [20]

    2014, ApJS, 211, 12, doi: 10.1088/0067-0049/211/1/12

    Gruber, D., Goldstein, A., Weller von Ahlefeld, V., et al. 2014, ApJS, 211, 12, doi: 10.1088/0067-0049/211/1/12

    2014 doi

  13. [21]

    2020, ApJ, 893, 100, doi: 10.3847/1538-4357/ab7d3e

    Hamburg, R., Fletcher, C., Burns, E., et al. 2020, ApJ, 893, 100, doi: 10.3847/1538-4357/ab7d3e

    2020 doi

  14. [22]

    M., Nakar, E., Singer, L

    Kasliwal, M. M., Nakar, E., Singer, L. P., et al. 2017, Science, 358, 1559, doi: 10.1126/science.aap9455

    2017 doi

  15. [23]

    2018, ApJ, 862, 152, doi: 10.3847/1538-4357/aacb7b

    Kocevski, D., Burns, E., Goldstein, A., et al. 2018, ApJ, 862, 152, doi: 10.3847/1538-4357/aacb7b

    2018 doi

  16. [24]

    2022, Radiation Detection Technology and Methods, 6, 12 LIGO Scientific Collaboration, Aasi, J., Abbott, B

    Li, X., Wen, X., An, Z., et al. 2022, Radiation Detection Technology and Methods, 6, 12 LIGO Scientific Collaboration, Aasi, J., Abbott, B. P., et al. 2015, Classical and Quantum Gravity, 32, 074001, doi: 10.1088/0264-9381/32/7/074001

    2022 doi

  17. [25]

    N., et al

    Meegan, C., Lichti, G., Bhat, P. N., et al. 2009, ApJ, 702, 791, doi: 10.1088/0004-637X/702/1/791

    2009 doi

  18. [26]

    P., Deller, A

    Mooley, K. P., Deller, A. T., Gottlieb, O., et al. 2018, Nature, 561, 355, doi: 10.1038/s41586-018-0486-3 Narayana Bhat, P., Meegan, C. A., von Kienlin, A., et al. 2016, ApJS, 223, 28, doi: 10.3847/0067-0049/223/2/28

    2018 doi

  19. [27]

    2024, Research in Astronomy and Astrophysics, 24, 104005, doi: 10.1088/1674-4527/ad4103

    Qiao, R., Guo, D.-Y., Peng, W.-X., et al. 2024, Research in Astronomy and Astrophysics, 24, 104005, doi: 10.1088/1674-4527/ad4103

    2024 doi

  20. [28]

    2016, ApJL, 820, L36, doi: 10.3847/2041-8205/820/2/L36

    Savchenko, V., Ferrigno, C., Mereghetti, S., et al. 2016, ApJL, 820, L36, doi: 10.3847/2041-8205/820/2/L36

    2016 doi

  21. [29]

    2017, ApJL, 848, L15, doi: 10.3847/2041-8213/aa8f94 Sub-threshold Short Gamma-Ray Burst 13

    Savchenko, V., Ferrigno, C., Kuulkers, E., et al. 2017, ApJL, 848, L15, doi: 10.3847/2041-8213/aa8f94 Sub-threshold Short Gamma-Ray Burst 13

    2017 doi

  22. [30]

    W., Yang, J., et al

    Sun, H., Wang, C. W., Yang, J., et al. 2023, arXiv e-prints, arXiv:2307.05689, doi: 10.48550/arXiv.2307.05689 von Kienlin, A., Meegan, C. A., Paciesas, W. S., et al. 2014, ApJS, 211, 13, doi: 10.1088/0067-0049/211/1/13 —. 2020, ApJ, 893, 46, doi: 10.3847/1538-4357/ab7a18

    2023 doi arXiv

  23. [31]

    2024, Experimental Astronomy, 57, 26, doi: 10.1007/s10686-024-09946-8

    Wang, C., Zhang, J., Zheng, S., et al. 2024, Experimental Astronomy, 57, 26, doi: 10.1007/s10686-024-09946-8

    2024 doi

  24. [32]

    2022, MNRAS, 514, 2397, doi: 10.1093/mnras/stac999

    Xiao, S., Xiong, S.-L., Cai, C., et al. 2022, MNRAS, 514, 2397, doi: 10.1093/mnras/stac999

    2022 doi

  25. [33]

    2023, ApJS, 268, 5, doi: 10.3847/1538-4365/ace77c

    Xiao, S., Yang, J.-J., Luo, X.-H., et al. 2023, ApJS, 268, 5, doi: 10.3847/1538-4365/ace77c

    2023 doi

  26. [34]

    2016, arXiv e-prints, arXiv:1605.05447, doi: 10.48550/arXiv.1605.05447

    Xiong, S. 2016, arXiv e-prints, arXiv:1605.05447, doi: 10.48550/arXiv.1605.05447

    2016 doi arXiv

  27. [35]

    2022, Radiation Detection Technology and Methods, 6, 53

    Xu, Y.-B., Li, X.-Q., Sun, X.-L., et al. 2022, Radiation Detection Technology and Methods, 6, 53

    2022

  28. [36]

    X., Wang, C

    Yi, S. X., Wang, C. W., & Zhang, B. 2023, arXiv e-prints, arXiv:2310.07205, doi: 10.48550/arXiv.2310.07205

    2023 doi

  29. [37]

    B., Zhang, B., Sun, H., et al

    Zhang, B. B., Zhang, B., Sun, H., et al. 2018, Nature Communications, 9, 447, doi: 10.1038/s41467-018-02847-3

    2018 doi

  30. [38]

    2022, Nuclear Instruments and Methods in Physics Research Section A:

    Zhang, D., Li, X., Wen, X., et al. 2022, Nuclear Instruments and Methods in Physics Research Section A:

    2022

  31. [39]

    Accelerators, Spectrometers, Detectors and Associated Equipment, 1027, 166222, doi: https://doi.org/10.1016/j.nima.2021.166222

    2021

  32. [41]

    Accelerators, Spectrometers, Detectors and Associated Equipment, 1056, 168586, doi: https://doi.org/10.1016/j.nima.2023.168586

    2023

  33. [42]

    2023c, arXiv e-prints, arXiv:2303.00698, doi: 10.48550/arXiv.2303.00698

    Zhang, Y.-Q., Xiong, S.-L., Qiao, R., et al. 2023c, arXiv e-prints, arXiv:2303.00698, doi: 10.48550/arXiv.2303.00698

    doi arXiv

  34. [43]

    2024, Science China Physics, Mechanics, and Astronomy, 67, 289511, doi: 10.1007/s11433-023-2381-0

    Zhang, Y.-Q., Xiong, S.-L., Mao, J.-R., et al. 2024, Science China Physics, Mechanics, and Astronomy, 67, 289511, doi: 10.1007/s11433-023-2381-0

    2024 doi

  35. [44]

    2025, arXiv e-prints, arXiv:2506.05920, doi: 10.48550/arXiv.2506.05920

    Zhang, Y.-Q., Xue, W.-C., Zhang, J.-P., et al. 2025, arXiv e-prints, arXiv:2506.05920, doi: 10.48550/arXiv.2506.05920

    2025 doi arXiv

  36. [45]

    2021, arXiv e-prints, arXiv:2112.05101, doi: 10.48550/arXiv.2112.05101

    Zhao, X.-Y., Xiong, S.-L., Wen, X.-Y., et al. 2021, arXiv e-prints, arXiv:2112.05101, doi: 10.48550/arXiv.2112.05101

    2021 doi arXiv

  37. [46]

    C., Xiong, S

    Zhao, Y., Liu, J. C., Xiong, S. L., et al. 2023, GRL, 50, e2022GL102325, doi: 10.1029/2022GL102325

    2023 doi

  38. [47]

    2024, apjl, 962, L2, doi: 10.3847/2041-8213/ad2073

    Zheng, C., Zhang, Y.-Q., Xiong, S.-L., et al. 2024, apjl, 962, L2, doi: 10.3847/2041-8213/ad2073

    2024 doi

Pith tools

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