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Long-duration GW Searches for Sub-solar NSs and Superkilonovae using CoCoA

T0 review · 2 major / 6 minor · reviewed 2026-08-15 · deepseek-v4-flash

Pith's one-line read This paper argues that electromagnetic-triggered CoCoA searches could detect long-duration sub-solar neutron-star merger chirps in current detectors out to tens of megaparsecs.

desk verdict A useful, honest feasibility study of CoCoA for sub-solar NS chirps; the rate arithmetic in Eq. 2.3 needs a clearer definition of R_true_0,coll, but the sensitivity results hold up. read the letter →

arxiv 2608.11387 v1 pith:TJFPLENZ submitted 2026-08-11 astro-ph.HE gr-qc

classification astro-ph.HEgr-qc
keywords gravitationalwavessub-solar-massneutronstarssuperkilonovacross-correlationalgorithmlong-durationgravitational-wavetransientslowermassgapelectromagnetic-triggeredsearchescore-collapsesupernovae
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

This paper asks whether long-duration gravitational-wave chirps from 'superkilonova' mergers, in which sub-solar-mass neutron stars formed in a collapsar disk spiral into a lower-mass-gap black hole, can be detected when the waveforms are too uncertain for standard matched-filter templates. The authors argue that electromagnetic-triggered searches using the cross-correlation algorithm CoCoA can reach such signals in current-generation two-detector data out to roughly 32–104 Mpc, comparable to the ~40 Mpc distances of the nearest known supernova/GRB-associated explosions. They further show that only next-generation detectors reach the ~400 Mpc distance of SN 2025ulz and can localize the source tightly enough for gravitational-wave-triggered follow-up. A rate estimate anchored on an assumed 1% superkilonova branching fraction yields an upper bound of about 7 Gpc⁻³ yr⁻¹, implying that a confident yearly detection requires horizons of several hundred megaparsecs.

What carries the argument

The load-bearing object is CoCoA, the Cross-Correlation Algorithm, a triggered search that cross-correlates short Fourier transforms (SFTs) of detector data along modeled time–frequency tracks. This paper uses CoCoA in its stochastic limit, where only SFT pairs from different detectors at the same time are correlated, trading sensitivity for robustness against waveform mismatch. The detection condition is that the signal's RMS amplitude at the detector, computed from approximate analytical in-spiral waveforms for the outer neutron-star–black-hole binary, must exceed a threshold set by noise spectral densities, SFT duration (9 ms here), false-alarm and false-dismissal probabilities, and antenna-pattern factors. The rate argument is carried by a branching-fraction identity that multiplies the fraction of collapsars that fragment, form at least two surviving sub-solar neutron stars, bind them into a binary, and merge that binary before disk dispersal; with a fiducial 1% product, the well-measured local core-collapse supernova rate bounds the superkilonova rate at about 7 Gpc⁻³ yr⁻¹.

What would settle it

A concrete test would be to run a CoCoA electromagnetic-triggered stochastic search over the sky position of SN 2025ulz and the merger-time window of S250818k in existing two-detector data; a null detection would directly bound the nearby superkilonova rate and weaken the claim that ~40 Mpc events are accessible.

Watch

Extended reading notes

Core claim

The central claim is that CoCoA in its stochastic limit can detect the long-duration chirps predicted in the superkilonova scenario, provided the search is electromagnetic-triggered and the source is nearby. For black-hole masses of 3–5 solar masses and neutron-star remnant masses of 0.1–0.5 solar masses, single-trial CoCoA horizons in current-generation detector noise range from about 32 Mpc to 104 Mpc, covering the ~40 Mpc distances of the nearest known gravitational-wave/GRB-related explosions; the same waveforms would be visible to roughly 230–970 Mpc with a next-generation network of planned 40 km and 15 km detectors. These numbers imply that superkilonova searches in current data are worth doing only as targeted, electromagnetic-triggered campaigns, while the population as a whole becomes accessible only to next-generation detectors, which also shrink 90% localization areas by at least two orders of magnitude compared with current networks. The paper is careful to present this as a detectability roadmap for an unconfirmed hypothesis, not as evidence that superkilonovae exist.

Load-bearing premise

The whole rate-and-reach interpretation rests on an unmeasured assumption, the idea that about one in a hundred collapsing massive stars produces a superkilonova; if the true fraction is far smaller, the quoted detection probabilities and the conclusion that a confident yearly detection is plausible at several hundred megaparsecs collapse.

Editorial extensions

If this is right

  • Electromagnetic-triggered CoCoA searches in current-generation detector data could already probe the nearest superkilonova-like events, since the reach in Table III overlaps the ~40 Mpc distances of known nearby GRB/SN explosions.
  • A planned sensitivity upgrade (A#) would extend current-generation reach to roughly 150 Mpc, the volume where transient surveys already classify several stripped-envelope supernovae per year, making follow-up more systematic.
  • Next-generation detectors are required both to reach ~400 Mpc events like SN 2025ulz and to provide small enough sky localizations for gravitational-wave-triggered searches to be practical.
  • Under the fiducial 1% branching fraction, the superkilonova rate upper bound of roughly 7 Gpc⁻³ yr⁻¹ implies that yearly confident detection is plausible only at horizons of several hundred megaparsecs.

Reading between the lines

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

  • The same CoCoA horizon machinery transfers to any long-duration quasi-periodic gravitational-wave signal with uncertain phase evolution; the 9 ms SFT and stochastic limit make the quoted reaches conservative relative to matched filtering by a factor of several.
  • If upcoming wide-field infrared surveys identify superkilonova-like transients with accurate sky positions, the electromagnetic-triggered strategy becomes the fastest route to detection because timing uncertainty, not sky localization, is then the dominant sensitivity loss.
  • A direct archival test would be to run a CoCoA electromagnetic-triggered search over the SN 2025ulz sky position and the S250818k merger-time window in existing two-detector data; a null result would directly bound the nearby superkilonova rate.
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Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

2 major / 6 minor

Summary. Prompted by the tentative association between the sub-threshold GW candidate S250818k and the Type IIb supernova SN 2025ulz, this paper investigates whether long-duration, non-standard GW chirps from hierarchical mergers involving sub-solar-mass neutron stars and lower-mass-gap black holes could be detected with the Cross-Correlation Algorithm (CoCoA). The paper derives a superkilonova rate bound from a fiducial branching fraction, constructs approximate analytic and LAL IMRPhenomD waveforms, computes single-trial matched-filter and CoCoA stochastic horizon distances for O4 and next-generation detector sensitivities, and estimates sky-localization areas for O4, O5, A#, and XG networks. The main conclusion is that EM-triggered CoCoA searches are worthwhile in current-generation data for nearby events at ~40 Mpc, while reaching the ~400 Mpc distance of SN 2025ulz requires next-generation detectors; this conclusion is explicitly acknowledged to depend on an unmeasured superkilonova branching fraction.

Significance. Assuming the rate ambiguity is resolved, the paper is a well-scoped, transparent detectability roadmap. Its strengths are that all sensitivity inputs come from public ASD curves, the CoCoA formalism is taken from a peer-reviewed derivation, the analytic waveforms are cross-checked against IMRPhenomD, and the choices are conservative in several places (neglect of tidal deformability, single-trial horizons, Hanning-window treatment of spectral leakage). The comparison between matched-filter and CoCoA reach and the network-localization curves are useful for planning EM-triggered and GW-triggered searches. The rate-based statements are the fragile part: they scale as the cube root of the assumed rate, so the Section VII claim that a confident yearly detection requires hundreds of Mpc is only as strong as the fiducial branching fraction.

major comments (2)
  1. [Section II, Eq. (2.3)] The inequality R0,SKNe ≲ 7 Gpc−3 yr−1 does not follow from the definitions printed immediately above it. Equation (2.2) and the surrounding text treat R0,CCSN ≈ 7×10^4 Gpc−3 yr−1 as the baseline collapsar rate, so fSKN|coll = 10−2 yields R0,SKNe ≈ 7×10^2 Gpc−3 yr−1; the value 7 is obtained only if R_true_0,coll is identified with the LLGRB/collapsar rate ≈7×10^2 Gpc−3 yr−1, a redefinition that the paper does not state. Because the 95% detection distances in Section II and the "≲85% probability" in Section VI A scale as R^{−1/3}, this factor-of-100 ambiguity changes the required distance by about 4.6 and changes the Section VII conclusion about whether current-generation horizons are sufficient. Please define R_true_0,coll explicitly and correct Eq. (2.3) or the baseline rate.
  2. [Sections II and VI A] The paper calls R0,SKNe ≲ 7 Gpc−3 yr−1 an upper bound and uses it to compute detection probabilities, but Section II states that fSKN|coll = 10−2 is a fiducial benchmark rather than an empirically measured rate. The manuscript should consistently label Eq. (2.3), the 470 Mpc and 218 Mpc horizons in Section II, and the ~85% figure in Section VI A as conditional on that benchmark, and should state explicitly how these numbers scale if fSKN|coll differs. This is not merely a wording issue, because the central conclusion in Section VII about the value of current-generation versus next-generation detectors is driven by this rate input.
minor comments (6)
  1. [Table III, header row] The unit '(Gpc)' for the O4 CoCoA stochastic horizon column appears to be a typographical error; the values (32.2, 53.7, ...) are used in the text as megaparsecs, and the comparison with the ~40 Mpc events in Section VI A confirms that the intended unit is Mpc.
  2. [Section III A, Eq. (3.2)] The last approximation in Eq. (3.2) assumes m1 ≫ m2, but for the outer binary the mass ratio can be as large as ~0.3 (e.g., MBH = 3 M⊙, Mrem = 0.8 M⊙); please state the range of validity or use the exact Peters formula.
  3. [Sections IV A and VII] The claimed robustness of CoCoA to waveform deviations from the superkilonova scenario is not demonstrated with mismodeled or eccentric injections; the paper should either add a caveat that the quoted horizons assume the quasi-circular time-frequency tracks are accurate, or include a quantitative robustness test.
  4. [Section II, Eq. (2.1)] The individual factors ffrag, f≥2NS|frag, fpair|≥2NS, and fmerge|pair are not assigned fiducial values; since only their product is used, the paper should state that the decomposition is schematic or provide the assumed values.
  5. [References [4] and [5]] References [4] and [5] appear to be the same arXiv identifier (2605.05444) and should be merged or corrected.
  6. [Section VI A] The '≲85% probability' estimate assumes 100% search efficiency out to 400 Mpc and does not fold in the EM selection effects inherent to an EM-triggered strategy; please state this explicitly or introduce an efficiency factor.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the CoCoA sensitivity estimates are self-contained and benchmarked against external waveforms, and the superkilonova rate bound is an explicitly admitted fiducial assumption rather than a fitted output.

full rationale

The paper's central derivations are conditional detectability estimates, not circular predictions. The waveform inputs come from Chen & Metzger (2025) and from the external LAL model IMRPhenomD, and the CoCoA detection statistics are taken from the prior peer-reviewed derivation of Coyne et al. (2016), with stated assumptions about Gaussian noise, SFT duration, false-alarm and false-dismissal probabilities; none of these inputs contains the horizon distances that the paper reports. The rate bound in Section II is also explicitly a fiducial benchmark: the paper states that f_SKN|coll is 'presently unconstrained' and adopts 10^-2 'as a fiducial benchmark rather than an empirically measured rate,' so the resulting R0,SKNe <= 7 Gpc^-3 yr^-1 is an assumed input used only to contextualize the astrophysical interest of the horizons, not a fitted quantity renamed as a prediction. Several cited works include current authors (notably the CoCoA papers and the radio constraints on engine-driven SNe), but those citations are either parameter-free analytical results with stated assumptions or external observational constraints; they are not uniqueness theorems invoked to forbid alternatives, and no load-bearing step reduces to an unverified self-citation. One correctness caveat, distinct from circularity, is that Eq. (2.3) appears internally inconsistent with the printed definitions if R_true_0,coll in Eq. (2.2) is read as the CCSN rate R0,CCSN = 7e4 Gpc^-3 yr^-1, since f_SKN|coll = 10^-2 would then give 7e2 rather than 7; the quoted 7 follows only if R_true_0,coll is instead identified with the LLGRB true rate of about 7e2 Gpc^-3 yr^-1, which the text does not explicitly state. This ambiguity affects the rate interpretation and the distance-horizon framing, but it does not make the signal-to-noise or CoCoA detectability calculation self-referential. The overall circularity score is therefore 0.

Assumptions & free parameters 4 free parameters · 4 assumptions · 0 invented entities

The central claim rests on two external pillars: the formation and waveform model of superkilonovae imported from Chen and Metzger, Wu et al., and Metzger et al., and the CoCoA detection-statistic formalism from Coyne et al. Within the paper, the only genuinely free numerical input is the fiducial branching fraction fSKN|coll, plus a few chosen scale parameters. No new entities are introduced.

free parameters (4)
  • fSKN|coll = 0.01 (fiducial benchmark)
    Fraction of collapsars assumed to produce superkilonovae; adopted in Section II to convert CCSN rate into an upper bound R0,SKNe <= 7 Gpc^-3 yr^-1. Not measured, and the quoted yearly detection probabilities scale directly with it.
  • a0,out (initial outer binary separation) = 200 Rg
    Initial NS-BH separation in the outer inspiral, chosen to match the gravitational instability radius in Chen and Metzger disk simulations (Section III A); horizon distances depend on it through merger time.
  • a0,in (initial inner binary separation) = RH/10
    Assumed inner NS-NS separation set to a tenth of the Hill radius to ensure NS-NS merger before outer merger; affects the emitted signal timing, not the outer horizon strongly.
  • Tchirp fudge factor = 1.1
    Multiplier applied to chirp time in Section III B to include ringdown when estimating waveform durations in Figure 2; minor and well-flagged.
assumptions (4)
  • domain assumption Sub-solar NSs can form via disk fragmentation or core fission in collapsars and merge hierarchically with a central BH
    Imported from Chen and Metzger (2025), Wu et al. (2026), and Metzger et al. (2024); the paper does not simulate this formation channel and explicitly notes the scenario is unconfirmed.
  • domain assumption Waveforms of the outer NS-BH inspiral are well approximated by IMRPhenomD or the Chen-Metzger analytical formula
    Central to computing h_rms and horizons; waveform mismatch would change all Table III numbers.
  • domain assumption Signals are quasi-monochromatic on SFT timescales and the CoCoA stochastic-limit statistic with Gaussian noise applies
    Basis for Equations 4.5 to 4.7; the paper uses ideal Gaussian noise and zero-noise SFT estimates.
  • domain assumption Antenna factors are constant over the signal duration
    Explicitly assumed in Section IV.A following Coyne et al.; valid for fixed sky location but ignores Earth rotation effects over signals lasting hundreds to thousands of seconds.

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Cite this review

Pith. "Pith review of Long-duration GW Searches for Sub-solar NSs and Superkilonovae using CoCoA." pith.science (2026). https://pith.science/paper/TJFPLENZ

@misc{pith2026260811387,
  author       = {Pith},
  title        = {Pith review of: Long-duration GW Searches for Sub-solar NSs and Superkilonovae using CoCoA},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/TJFPLENZ}},
  note         = {Machine review of arXiv:2608.11387}
}
read the original abstract

On 2025 August 18, the LIGO-Virgo-KAGRA collaboration reported a sub-threshold gravitational-wave (GW) candidate, S250818k, consistent with a binary neutron star (NS) merger potentially involving a sub-solar-mass compact object. Follow-up electromagnetic (EM) observations identified a Type IIb supernova, SN 2025ulz within the broad localization area of the GW signal. This potential link between a sub-solar GW event candidate and a Type IIb SN, while not confirmed given the low statistical significance of S250818k, has nonetheless sparked renewed interest in the "superkilonova" scenario, where sub-solar-mass NSs form through processes like the fragmentation of an accretion disk or core fission in a collapsing star. In this picture, the in-spiral and merger of a sub-solar NS-NS binary is followed by the merger of the NS-NS remnant with the central black hole (BH), producing chirp-like GW signals. For sub-solar NSs with masses in the (0.1-1)M_sun range and BH masses in the so-called lower mass gap range of ~(3-5) M_sun, these signals can persist in the 20 - 1024 Hz frequency band of ground-based GW detectors for (10^2-10^3)s, potentially offering an opportunity to probe the superkilonova scenario, as well as the lower mass gap between NSs and stellar-mass BHs. However, the complexity of the underlying astrophysics may yield waveforms that deviate from standard templates, limiting the use of matched filtering in real GW searches. We therefore explore the detectability of such signals using the Cross-Correlation Algorithm (CoCoA), a more robust though less sensitive cross-correlation method. We discuss general strategies for implementing CoCoA superkilonova searches via either targeted follow-up of candidate chirps identified in matched-filter searches, or EM-triggered searches of stripped-envelope core-collapse SNe.

Figures

Figures reproduced from arXiv: 2608.11387 by the authors.

Figure 1
Figure 1. FIG. 1: TOP: GW strain amplitude as a function of in-band time (where we take [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗
Figure 2
Figure 2. FIG. 2: Approximate GW waveform durations for [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗
Figure 3
Figure 3. FIG. 3: Amplitude spectral density (ASD) curves for all [PITH_FULL_IMAGE:figures/full_fig_p007_3.png] view at source ↗
Figures from the paper (2 more)
Figure 4
Figure 4. Figure 4: FIG. 4: Subsolar waveform GW horizons across the search strategies analyzed in this work. See Section VI A for [PITH_FULL_IMAGE:figures/full_fig_p009_4.png]
Figure 5
Figure 5. Figure 5: FIG. 5: 90% Localization area (deg [PITH_FULL_IMAGE:figures/full_fig_p010_5.png]

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Works this paper leans on

109 extracted references · 19 canonical work pages

  1. [1]

    O4 network: LIGO Livingston (L), H, and Virgo (V) detectors with LIGO detectors taken at O4c sensitivity [8, 32, 64] and Virgo at Advanced Virgo design sensitivity [17]

  2. [2]

    O5 network: L, H, and V detectors with LIGO detectors taken at O5c/A+ sensitivity [8, 65] and Virgo at Advanced Virgo design sensitivity [17]

  3. [3]

    A# network: L, H, and LIGO-India [55] (I) detec- tors, all at A# sensitivity [8, 66]

  4. [4]

    The locations of all the detectors considered in these networks are given in Table I

    XG network: CE40 at default sensitivity in [33], a 20 km Cosmic Explorer (CE20) at default sen- sitivity for CE20 in [33], and two 15 km Einstein Telescopes (ET-L1, ET-L2) in L–configuration at ET15 sensitivity [42] used in the CoBA study [1]. The locations of all the detectors considered in these networks are given in Table I. 8 VI. RESUL TS A. GW distan...

  5. [5]

    Abac, A., et al. 2026, J. Cosmology Astropart. Phys., 2026, 081, doi:10.1088/1475-7516/2026/03/081

  6. [6]

    G., Abbott, R., Abouelfettouh, I., et al

    Abac, A. G., Abbott, R., Abouelfettouh, I., et al. 2025, ApJ, 985, 183, doi:10.3847/1538-4357/adc681

  7. [7]

    G., Abe, A., Abouelfettouh, I., et al

    Abac, A. G., Abe, A., Abouelfettouh, I., et al. 2026, arXiv e-prints, arXiv:2605.27226, doi:10.48550/arXiv. 2605.27226

  8. [9]

    2026, arXiv e-prints, arXiv:2605.05444, doi:10

    —. 2026, arXiv e-prints, arXiv:2605.05444, doi:10. 48550/arXiv.2605.05444

Show all 109 references
  1. [10]

    G., Abouelfettouh, I., Acernese, F., et al

    Abac, A. G., Abouelfettouh, I., Acernese, F., et al. 2026, Phys. Rev. D, 113, 082004, doi:10.1103/83j3-pgk1

  2. [11]

    G., Abouelfettouh, I., Acernese, F., et al

    Abac, A. G., Abouelfettouh, I., Acernese, F., et al. 2025, arXiv e-prints, arXiv:2508.18082, doi:10.48550/arXiv. 2508.18082

  3. [12]

    P., Abbott, R., Abbott, T

    Abbott, B. P., Abbott, R., Abbott, T. D., et al. 2018, Living Reviews in Relativity, 21, 3, doi:10.1007/ s41114-018-0012-9

  4. [13]

    P., Abbott, R., Abbott, T

    Abbott, B. P., Abbott, R., Abbott, T. D., et al. 2020, Phys. Rev. D, 101, 084002, doi:10.1103/PhysRevD. 101.084002

  5. [14]

    2019, Phys

    —. 2019, Phys. Rev. Lett., 123, 161102, doi:10.1103/ PhysRevLett.123.161102

  6. [15]

    P., Abbott, R., Abbott, T

    Abbott, B. P., Abbott, R., Abbott, T. D., et al. 2019, ApJ, 875, 160, doi:10.3847/1538-4357/ab0f3d

  7. [16]

    D., Acernese, F., et al

    Abbott, R., Abbott, T. D., Acernese, F., et al. 2022, Phys. Rev. Lett., 129, 061104, doi:10.1103/ PhysRevLett.129.061104

  8. [17]

    D., Acernese, F., et al

    Abbott, R., Abbott, T. D., Acernese, F., et al. 2022, ApJ, 928, 186, doi:10.3847/1538-4357/ac532b

  9. [18]

    2022, The Astrophysical Journal Letters, 941, L30, doi:10.3847/ 2041-8213/aca1b0

    Abbott, R., Abe, H., Acernese, F., et al. 2022, The Astrophysical Journal Letters, 941, L30, doi:10.3847/ 2041-8213/aca1b0

  10. [19]

    2022, Phys

    —. 2022, Phys. Rev. D, 106, 102008, doi:10.1103/ PhysRevD.106.102008

  11. [20]

    D., Acernese, F., et al

    Abbott, R., Abbott, T. D., Acernese, F., et al. 2023, Physical Review X, 13, 011048, doi:10.1103/PhysRevX. 13.011048

  12. [21]

    2015, Classical and Quantum Gravity, 32, 024001, doi:10

    Acernese, F., Agathos, M., Agatsuma, K., et al. 2015, Classical and Quantum Gravity, 32, 024001, doi:10. 1088/0264-9381/32/2/024001

  13. [22]

    T., Boye, A., et al

    Ackley, K., Botticella, M. T., Boye, A., et al. 2026, arXiv e-prints, arXiv:2605.02639, doi:10.48550/arXiv. 2605.02639

  14. [23]

    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

  15. [24]

    G., Brady, P

    Allen, B., Anderson, W. G., Brady, P. R., Brown, D. A., & Creighton, J. D. E. 2012, Phys. Rev. D, 85, 122006, doi:10.1103/PhysRevD.85.122006

  16. [25]

    P., et al

    An, J., Liu, X., Zhu, Z. P., et al. 2025, GRB Coordinates Network, 41503, 1

  17. [26]

    M., Dornic, D., et al

    Angulo, C., Watson, A. M., Dornic, D., et al. 2025, GRB Coordinates Network, 41518, 1

  18. [27]

    2025, GRB Coor- dinates Network, 41519, 1

    Antier, S., Pillas, M., Akl, D., et al. 2025, GRB Coor- dinates Network, 41519, 1

  19. [28]

    M., Shappee, B

    Antognini, J. M., Shappee, B. J., Thompson, T. A., & Amaro-Seoane, P. 2014, MNRAS, 439, 1079, doi:10. 1093/mnras/stu039

  20. [29]

    P., Pignata, G., et al

    Ayala, B., Anderson, J. P., Pignata, G., et al. 2025, A&A, 701, A128, doi:10.1051/0004-6361/202554370

  21. [30]

    2017, Reports on Progress in Physics, 80, 096901, doi:10.1088/1361-6633/aa67bb

    Baiotti, L., & Rezzolla, L. 2017, Reports on Progress in Physics, 80, 096901, doi:10.1088/1361-6633/aa67bb

  22. [31]

    J., et al

    Banerjee, S., Botticella, M.-T., Brennan, S. J., et al. 2025, GRB Coordinates Network, 41532, 1

  23. [32]

    Barnes, J., & Metzger, B. D. 2022, ApJ, 939, L29, doi:10.3847/2041-8213/ac9b41

  24. [33]

    2002, ApJ, 572, 407, doi:10.1086/340304

    Belczynski, K., Kalogera, V., & Bulik, T. 2002, ApJ, 572, 407, doi:10.1086/340304

  25. [34]

    E., et al

    Belczynski, K., Repetto, S., Holz, D. E., et al. 2016, ApJ, 819, 108, doi:10.3847/0004-637X/819/2/108

  26. [35]

    E., Guidorzi, C., Amati, L., et al

    Camisasca, A. E., Guidorzi, C., Amati, L., et al. 2023, A&A, 671, A112, doi:10.1051/0004-6361/202245657

  27. [36]

    2025, Phys

    Capote, E., Jia, W., Aritomi, N., et al. 2025, Phys. Rev. D, 111, 062002, doi:10.1103/PhysRevD.111.062002

  28. [37]

    2024, Cosmic Explorer Strain Sensitivity.https://dcc.cosmicexplorer.org/ CE-T2000017-v8/public

    CE Consortium. 2024, Cosmic Explorer Strain Sensitivity.https://dcc.cosmicexplorer.org/ CE-T2000017-v8/public

  29. [38]

    Chen, Y.-X., & Metzger, B. D. 2025, ApJ, 991, L22, doi:10.3847/2041-8213/ae045d

  30. [39]

    Cornish, N. C. N., K¨ uhnel, F., Sakellariadou, M., & Guanga, A. S. V. 2026.https://arxiv.org/abs/2607. 23119

  31. [40]

    R., et al

    Corsi, A., Gal-Yam, A., Kulkarni, S. R., et al. 2016, ApJ, 830, 42, doi:10.3847/0004-637X/830/1/42

  32. [41]

    Corsi, A., Ho, A. Y. Q., Cenko, S. B., et al. 2023, ApJ, 953, 179, doi:10.3847/1538-4357/acd3f2

  33. [42]

    Coyne, R., Corsi, A., & Owen, B. J. 2016, Phys. Rev. D, 93, 104059, doi:10.1103/PhysRevD.93.104059

  34. [43]

    B., Levan, A

    Davies, M. B., Levan, A. J., & King, A. R. 2005, MN- RAS, 356, 54, doi:10.1111/j.1365-2966.2004.08423. x

  35. [44]

    Dhurandhar, S., Krishnan, B., Mukhopadhyay, H., & Whelan, J. T. 2008, Phys. Rev. D, 77, 082001, doi:10. 1103/PhysRevD.77.082001

  36. [45]

    F., Zhang, Z

    Dong, X. F., Zhang, Z. B., Li, Q. M., Huang, Y. F., & Bian, K. 2023, ApJ, 958, 37, doi:10.3847/1538-4357/ acf852

  37. [46]

    2023, ET sensitivity curves used for CoBA Science Study.https://apps.et-gw.eu/tds/ ?r=18213

    ET Collaboration. 2023, ET sensitivity curves used for CoBA Science Study.https://apps.et-gw.eu/tds/ ?r=18213

  38. [47]

    X., Afle, C., et al

    Evans, M., Adhikari, R. X., Afle, C., et al. 2021, arXiv 12 e-prints, arXiv:2109.09882, doi:10.48550/arXiv.2109. 09882

  39. [48]

    2009, New J

    Fairhurst, S. 2009, New J. Phys., 11, 123006, doi:10. 1088/1367-2630/11/12/123006

  40. [49]

    2018, Class

    —. 2018, Class. Quant. Grav., 35, 105002, doi:10.1088/ 1361-6382/aab675

  41. [50]

    Fairhurst, S., Hoy, C., Green, R., Mills, C., & Usman, S. A. 2023, Phys. Rev. D, 108, 082006, doi:10.1103/ PhysRevD.108.082006

  42. [51]

    D., et al

    Franz, N., Subrayan, B., Kilpatrick, C. D., et al. 2025, ApJ, 994, L45, doi:10.3847/2041-8213/ae17a8

  43. [52]

    J., Vreeswijk, P

    Galama, T. J., Vreeswijk, P. M., van Paradijs, J., et al. 1998, Nature, 395, 670, doi:10.1038/27150

  44. [53]

    H., Huber, M

    Gillanders, J. H., Huber, M. E., Nicholl, M., et al. 2025, ApJ, 995, L27, doi:10.3847/2041-8213/ae2125

  45. [54]

    J., Stein, R., O’Connor, B., & Palmese, A

    Hall, X. J., Stein, R., O’Connor, B., & Palmese, A. 2025, GRB Coordinates Network, 41453, 1

  46. [55]

    J., Busmann, M., Koehn, H., et al

    Hall, X. J., Busmann, M., Koehn, H., et al. 2025, arXiv e-prints, arXiv:2510.24620, doi:10.48550/arXiv.2510. 24620

  47. [56]

    J., Tanvir, N

    Hjorth, J., Levan, A. J., Tanvir, N. R., et al. 2017, ApJ, 848, L31, doi:10.3847/2041-8213/aa9110

  48. [57]

    2016, Phys

    Husa, S., Khan, S., Hannam, M., et al. 2016, Phys. Rev. D, 93, 044006, doi:10.1103/PhysRevD.93.044006

  49. [58]

    M., Tyson, J

    Ivezi´ c,ˇZ., Kahn, S. M., Tyson, J. A., et al. 2019, ApJ, 873, 111, doi:10.3847/1538-4357/ab042c

  50. [59]

    S., et al

    Iyer, B., Souradeep, T., Unnikrishnan, C. S., et al. 2011, LIGO-India, Proposal of the Consortium for In- dian Initiative in Gravitational-wave Observations (In- dIGO), Tech. Rep. LIGO-M1100296-v2, LIGO.https: //dcc.ligo.org/LIGO-M1100296/public

  51. [60]

    D., Salvaterra, R., et al

    Japelj, J., Vergani, S. D., Salvaterra, R., et al. 2018, A&A, 617, A105, doi:10.1051/0004-6361/201833209

  52. [61]

    M., Ahumada, T., Stein, R., et al

    Kasliwal, M. M., Ahumada, T., Stein, R., et al. 2025, arXiv e-prints, arXiv:2510.23732, doi:10.48550/arXiv. 2510.23732

  53. [62]

    M., Karambelkar, V., Fremling, C., et al

    Kasliwal, M. M., Karambelkar, V., Fremling, C., et al. 2025, GRB Coordinates Network, 41538, 1

  54. [63]

    2016, Phys

    Khan, S., Husa, S., Hannam, M., et al. 2016, Phys. Rev. D, 93, 044007, doi:10.1103/PhysRevD.93.044007

  55. [64]

    Khanam, T., Corsi, A., Coyne, R., & Pierre, M. S. 2026, Phys. Rev. D, 113, 103034, doi:10.1103/yc6h-g481

  56. [65]

    Liang, E., Zhang, B., Virgili, F., & Dai, Z. G. 2007, ApJ, 662, 1111, doi:10.1086/517959

  57. [66]

    2005, Phys

    LIGO Scientific Collaboration. 2005, Phys. Rev. D, 72, 042002, doi:10.1103/PhysRevD.72.042002

  58. [67]

    2015, Classical and Quantum Gravity, 32, 074001, doi:10.1088/0264-9381/32/7/074001

    —. 2015, Classical and Quantum Gravity, 32, 074001, doi:10.1088/0264-9381/32/7/074001

  59. [68]

    2025, O4c Reference Sensitivity.https://dcc.ligo.org/LIGO-T2500364

    LIGO Scientific Collaboration. 2025, O4c Reference Sensitivity.https://dcc.ligo.org/LIGO-T2500364

  60. [69]

    2025, A+/O5 strain curve projections.https:// dcc.ligo.org/LIGO-T2500310/public

    —. 2025, A+/O5 strain curve projections.https:// dcc.ligo.org/LIGO-T2500310/public

  61. [70]

    2026, A# Strain Sensitivity.https://dcc.ligo

    —. 2026, A# Strain Sensitivity.https://dcc.ligo. org/LIGO-T2300041/public

  62. [71]

    2018, LVK Algorithm Li- brary - LALSuite, Free software (GPL), doi:10.7935/ GT1W-FZ16

    LIGO Scientific Collaboration, Virgo Collaboration, & KAGRA Collaboration. 2018, LVK Algorithm Li- brary - LALSuite, Free software (GPL), doi:10.7935/ GT1W-FZ16

  63. [72]

    2025, GRB Coordinates Network, 41437, 1

    Ligo Scientific Collaboration, VIRGO Collaboration, & Kagra Collaboration. 2025, GRB Coordinates Network, 41437, 1

  64. [73]

    2025, GRB Coordinates Network, 41440, 1

    —. 2025, GRB Coordinates Network, 41440, 1

  65. [74]

    2025, Phys

    —. 2025, Phys. Rev. D, 112, 102005, doi:10.1103/ wjdz-jdby

  66. [75]

    M., Aykutalp, A., & Johnson, J

    Lloyd-Ronning, N. M., Aykutalp, A., & Johnson, J. L. 2019, MNRAS, 488, 5823, doi:10.1093/mnras/stz2155

  67. [76]

    M., et al

    Margutti, R., Milisavljevic, D., Soderberg, A. M., et al. 2014, ApJ, 797, 107, doi:10.1088/0004-637X/797/2/ 107

  68. [77]

    D., Hui, L., & Cantiello, M

    Metzger, B. D., Hui, L., & Cantiello, M. 2024, ApJ, 971, L34, doi:10.3847/2041-8213/ad6990

  69. [78]

    2016, ARA&A, 54, 441, doi:10.1146/ annurev-astro-081915-023315

    Naoz, S. 2016, ARA&A, 54, 441, doi:10.1146/ annurev-astro-081915-023315

  70. [79]

    2025, ApJ, 995, L47, doi:10.3847/2041-8213/ae16a6

    O’Connor, B., Ricci, R., Troja, E., et al. 2025, ApJ, 995, L47, doi:10.3847/2041-8213/ae16a6

  71. [80]

    2026, arXiv e-prints, arXiv:2604.05128, doi:10.48550/arXiv.2604

    O’Dwyer, T., Corsi, A., Yadav, D., et al. 2026, arXiv e-prints, arXiv:2604.05128, doi:10.48550/arXiv.2604. 05128

  72. [81]

    2026, ApJ, 1002, 194, doi:10.3847/1538-4357/ae522d

    O’Dwyer, T., Corsi, A., Yang, S., et al. 2026, ApJ, 1002, 194, doi:10.3847/1538-4357/ae522d

  73. [82]

    2025, GRB Coordinates Network, 41504, 1

    Passaleva, N., Durbak, J., Guiffreda, O., et al. 2025, GRB Coordinates Network, 41504, 1

  74. [83]

    2016, A&A, 587, A40, doi:10.1051/0004-6361/201526760

    Pescalli, A., Ghirlanda, G., Salvaterra, R., et al. 2016, A&A, 587, A40, doi:10.1051/0004-6361/201526760

  75. [84]

    D., Prieto, J

    Pessi, T., Desai, D. D., Prieto, J. L., et al. 2025, A&A, 703, A34, doi:10.1051/0004-6361/202556799

  76. [85]

    Peters, P. C. 1964, Physical Review, 136, 1224, doi:10. 1103/PhysRev.136.B1224

  77. [86]

    L., & Pfahl, E

    Piro, A. L., & Pfahl, E. 2007, ApJ, 658, 1173, doi:10. 1086/511672

  78. [87]

    2021, Phys

    Pratten, G., et al. 2021, Phys. Rev. D, 103, 104056, doi:10.1103/PhysRevD.103.104056

  79. [88]

    2010, Classical and Quantum Gravity, 27, 084007, doi:10

    Punturo, M., Abernathy, M., Acernese, F., et al. 2010, Classical and Quantum Gravity, 27, 084007, doi:10. 1088/0264-9381/27/8/084007

  80. [89]

    L., Amaro-Seoane, P., Chatterjee, S., et al

    Rodriguez, C. L., Amaro-Seoane, P., Chatterjee, S., et al. 2018, Phys. Rev. D, 98, 123005, doi:10.1103/ PhysRevD.98.123005

  81. [90]

    M., Baltay, C., Hounsell, R., et al

    Rose, B. M., Baltay, C., Hounsell, R., et al. 2021, arXiv e-prints, doi:10.48550/arXiv.2111.03081

  82. [91]

    2021, New A, 83, 101498, doi:10.1016/j.newast.2020

    Rozwadowska, K., Vissani, F., & Cappellaro, E. 2021, New A, 83, 101498, doi:10.1016/j.newast.2020. 101498

  83. [92]

    2018, ApJ, 859, 30, doi:10.3847/1538-4357/aabee4

    Ruffini, R., Rodriguez, J., Muccino, M., et al. 2018, ApJ, 859, 30, doi:10.3847/1538-4357/aabee4

  84. [93]

    M., Agarwal, A., Barnes, J., et al

    Siegel, D. M., Agarwal, A., Barnes, J., et al. 2021, arXiv e-prints, arXiv:2111.03094.https://arxiv.org/abs/ 2111.03094

  85. [94]

    2019, Phys

    Sowell, E., Corsi, A., & Coyne, R. 2019, Phys. Rev. D, 100, 124041, doi:10.1103/PhysRevD.100.124041

  86. [95]

    2015, arXiv e-prints, arXiv:1503.03757.https://arxiv.org/abs/ 1503.03757

    Spergel, D., Gehrels, N., Baltay, C., et al. 2015, arXiv e-prints, arXiv:1503.03757.https://arxiv.org/abs/ 1503.03757

  87. [96]

    P., Yang, S., Anand, S., et al

    Srinivasaragavan, G. P., Yang, S., Anand, S., et al. 2024, ApJ, 976, 71, doi:10.3847/1538-4357/ad7fde

  88. [97]

    2025, ApJ, 991, L54, doi:10.3847/2041-8213/ae055b

    Stegmann, J., & Klencki, J. 2025, ApJ, 991, L54, doi:10.3847/2041-8213/ae055b

  89. [98]

    2025, GRB Coordinates Network, 41414, 1

    Stein, R., Ahumada, T., Kasliwal, M., et al. 2025, GRB Coordinates Network, 41414, 1

  90. [99]

    2015, ApJ, 812, 33, doi:10

    Sun, H., Zhang, B., & Li, Z. 2015, ApJ, 812, 33, doi:10. 1088/0004-637X/812/1/33

  91. [100]

    J., Zheng, Y., Antelis, J

    Szczepa´ nczyk, M. J., Zheng, Y., Antelis, J. M., et al. 2024, Phys. Rev. D, 110, 042007, doi:10.1103/ PhysRevD.110.042007

  92. [101]

    2017, Phys

    The LIGO Scientific Collaboration, & the Virgo Collab- oration. 2017, Phys. Rev. Lett., 119, 161101, doi:10. 1103/PhysRevLett.119.161101

  93. [102]

    2023, Monthly Notices of the Royal Astronomical Society, 524, 5984, doi:10.1093/mnras/stad588

    The LIGO Scientific Collaboration, the Virgo Collab- 13 oration, & the KAGRA Collaboration. 2023, Monthly Notices of the Royal Astronomical Society, 524, 5984, doi:10.1093/mnras/stad588

  94. [103]

    2025, arXiv e-prints, arXiv:2508.18083, doi:10

    —. 2025, arXiv e-prints, arXiv:2508.18083, doi:10. 48550/arXiv.2508.18083

  95. [104]

    2017, ApJ, 848, L13, doi:10.3847/ 2041-8213/aa920c

    The LIGO Scientific Collaboration, the Virgo Collab- oration, et al. 2017, ApJ, 848, L13, doi:10.3847/ 2041-8213/aa920c

  96. [105]

    2017, ApJ, 848, L12, doi:10.3847/2041-8213/ aa91c9

    —. 2017, ApJ, 848, L12, doi:10.3847/2041-8213/ aa91c9

  97. [106]

    Tyson, J. A. 2002, in Survey and Other Telescope Tech- nologies and Discoveries, ed. J. A. Tyson & S. Wolff, Vol. 4836, International Society for Optics and Photon- ics (SPIE), 10 – 20, doi:10.1117/12.456772

  98. [107]

    2010, MNRAS, 406, 1944, doi:10.1111/j.1365-2966.2010.16787.x

    Wanderman, D., & Piran, T. 2010, MNRAS, 406, 1944, doi:10.1111/j.1365-2966.2010.16787.x

  99. [108]

    R., Vu, N

    Wu, J., Most, E. R., Vu, N. L., et al. 2026, arXiv e- prints, arXiv:2604.26912, doi:10.48550/arXiv.2604. 26912

  100. [109]

    2026, ApJ, 996, L24, doi:10.3847/2041-8213/ae2dea

    Yang, Y.-H., Troja, E., Risti´ c, M., et al. 2026, ApJ, 996, L24, doi:10.3847/2041-8213/ae2dea

  101. [110]

    H., & Most, E

    Zenati, Y., Rozner, M., Krolik, J. H., & Most, E. R. 2025, ApJ, 978, 126, doi:10.3847/1538-4357/ad9b87

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