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REVIEW 3 major objections 5 minor 11 cited by

Spectral siren cosmology from gravitational-wave observations in GWTC-4.0

T0 review · 3 major / 5 minor · reviewed 2026-08-05 · deepseek-v4-flash

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Pith's one-line read Spectral siren cosmology on 152 GWTC-4.0 black hole mergers, combined with the GW170817 bright siren, yields H0 = 69 (+7/−6) km/s/Mpc, a 10% measurement.

desk verdict First spectral-siren H0 constraint from GWTC-4.0, a clean application of standard methods; the headline 10% number rests on the authors' own GP model and on an unquantified no-redshift-evolution assumption. read the letter →

arxiv 2509.03607 v1 pith:HGOLNENF submitted 2025-09-03 astro-ph.CO astro-ph.HE

Ignacio Magaña Hernandez , Antonella Palmese This is my paper
classification astro-ph.COastro-ph.HE
keywords gravitationalwavesspectralsirensHubbleconstantblackholemassspectrumGWTC-4.0hierarchicalBayesianinferenceGaussianprocessstandard
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

Gravitational-wave events are standard sirens, but their redshifts are usually hard to get. This paper uses spectral sirens instead: features in the black-hole mass spectrum serve as a ruler, because the same features appear at different detector-frame masses depending on how much the waves were redshifted. Applying this to 152 binary black holes from the new GWTC-4.0 catalog, the paper derives the Hubble constant with three mass models, and the most flexible one gives H0 = 69 (+7/−6) km/s/Mpc (10% precision) when combined with the GW170817 bright siren. The paper argues that the extra structure in the 10–40 solar-mass range, visible in the flexible models, pulls the inferred Hubble constant down. If right, spectral sirens are close to matching galaxy-catalog dark-siren precision without needing electromagnetic counterparts or complete galaxy catalogs.

What carries the argument

The spectral-siren ruler: observed detector-frame masses relate to source-frame masses by m_det = (1+z) m_source, so a fixed feature in the source-frame mass spectrum appears at different detector-frame masses depending on the redshift. The analysis scans over the Hubble constant, and the value that best aligns all events' inferred source-frame masses with the model's peaks and gaps wins. The three population models provide the feature templates, with the Gaussian Process model's flexibility capturing the 10–40 solar-mass structure and the ~45 solar-mass pair-instability shoulder that carry the tightest H0 information.

What would settle it

Split the GWTC-4.0 BBH sample by inferred redshift and compare the position of the ~10 solar-mass peak under the Gaussian Process model at fixed H0; if the peak's location shifts with redshift by more than the posterior uncertainty, the no-evolution assumption fails.

Watch

Extended reading notes

Core claim

Using 152 confident binary-black-hole mergers from GWTC-4.0, the paper reports the first spectral-siren Hubble-constant measurement with this catalog. Three mass models give BBH-only H0 = 78 (+93/−33), 66 (+48/−32), and 61 (+29/−13) km/s/Mpc. Combining the Gaussian Process model with the GW170817 bright-siren measurement gives H0 = 69 (+7/−6) km/s/Mpc, a 10% constraint. The paper argues that the extra 10–40 solar-mass structure—chiefly the ~10 solar-mass peak shifting upward—drives the lower H0 relative to Powerlaw + Peak, and that the Gaussian Process model's 45 and 60–70 solar-mass features carry the added constraining power.

Load-bearing premise

The black-hole mass spectrum is assumed to have the same shape at every redshift; if the peaks and bumps move to different masses in the past, the inferred Hubble constant will be biased.

Editorial extensions

If this is right

  • Spectral sirens can measure H0 without electromagnetic counterparts or complete galaxy catalogs, reaching 10% precision when a flexible mass model is combined with a single bright siren.
  • Model choice changes the BBH-only central H0 by about 17 km/s/Mpc (78 versus 61), so the mass model is now a dominant systematic for this method.
  • The pair-instability-related features (the ~45 solar-mass shoulder and the 60–70 solar-mass excess) act as extra calibrators; better population modeling should tighten H0 further as events accumulate.
  • The resulting H0 overlaps both CMB and local distance-ladder measurements within its error bars, so spectral sirens currently probe the Hubble tension without resolving it.
  • As the catalog grows, this framework points toward percent-level H0 measurements from spectral sirens alone.

Reading between the lines

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

  • Editorial inference: if the 10–40 solar-mass structure traces metallicity-driven evolution, the lower H0 preferred by flexible models could partly be unmodeled redshift evolution masquerading as cosmology.
  • Editorial inference: cross-checking spectral-siren H0 against dark-siren galaxy-catalog analyses on the same events would isolate method-specific systematics, since the two routes break the mass–redshift degeneracy differently.
  • Editorial inference: the apparent pair-instability features could be calibrated with independent stellar-population or electromagnetic constraints, converting an astrophysical feature into an absolute mass standard for H0.
  • Editorial inference: extending the Gaussian Process model to jointly infer mass and redshift evolution—the paper's stated next step—would turn the main caveat into a measured parameter, letting the data choose between a fixed and an evolving mass spectrum.
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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

3 major / 5 minor

Summary. The paper presents a spectral-siren measurement of the Hubble constant using 152 binary black hole (BBH) mergers from GWTC-4.0. It uses three models for the source-frame black hole mass distribution: the Powerlaw + Peak and Broken Powerlaw + 2 Peaks parametric models, and a non-parametric Gaussian Process (GP) model. The analysis jointly infers population and cosmological parameters in a hierarchical Bayesian framework with selection effects estimated from public injections. The main result is that the GP model combined with the GW170817 bright-siren measurement yields H0 = 69^{+7}_{-6} km/s/Mpc (10% precision), while the parametric models give broader constraints. The paper claims broad consistency among the three models and compares with Planck and SH0ES.

Significance. If the result holds, this is a useful step for spectral-siren cosmology: it is one of the first cosmological measurements with GWTC-4.0, it uses three population models, and it demonstrates that a flexible non-parametric mass model can improve H0 precision compared to simple parametric forms. The analysis uses public GWTC-4.0 data and injections, follows standard hierarchical Bayesian methods, and is transparent about its main caveat regarding redshift evolution of the mass distribution. However, the headline 10% precision rests on the GP model, whose astrophysically motivated features may partly be prior-driven, and on an assumed redshift-invariant mass spectrum that the paper itself acknowledges is unquantified. The quoted GW170817 posterior also appears to be misreported. These issues limit the importance of the central claim until addressed.

major comments (3)
  1. [Section IV and Table I] The headline 10% result assumes that the BBH source-frame mass distribution does not evolve with redshift. The authors explicitly state this caveat and cite Refs. [13,23,53] showing that redshift-evolving features can bias cosmological inference, but they do not quantify the resulting systematic uncertainty. Since the spectral-siren mapping in Eq. (1) identifies features in the mass spectrum, even a mild drift of the 10–40 Msun structure could shift H0 by more than the quoted 69^{+7}_{-6}. The paper should add a sensitivity test, e.g., by injecting mock populations with redshift-dependent peaks or by using a redshift-evolving GP model, and should either include the resulting systematic in the error budget or justify why it is negligible. As written, the quoted precision is conditional on an unquantified assumption.
  2. [Section III, Table I] The GW170817 posterior used in the combined constraints is misreported. The text says "H0 = 71^{+23}_{-8} km/s/Mpc obtained from Ref. [8]", but Ref. [8] (Abbott et al. 2017, Nature 551, 85) reports H0 = 70.0^{+12.0}_{-8.0} km/s/Mpc. The upper error is wrong by roughly a factor of two. Because the second column of Table I is obtained by combining the BBH-only posteriors with this GW170817 measurement, the combined H0 values and their uncertainties need to be recomputed with the correct posterior. If a different posterior is intended, it must be cited explicitly.
  3. [Section II C and Figure 2] The most constraining result comes from the Gaussian Process model of Ref. [36]. The paper states that the GP model captures a "shoulder-like feature around ~45 Msun" and a suppression consistent with the PISN mass gap, and that these features are "consistent with Ref. [36]". These features are the ones that drive the spectral-siren H0 constraint, but the paper does not show the GP prior versus the posterior, nor any sensitivity to the GP kernel or hyperparameters. Because Ref. [36] is by the same authors and the model is described as "astrophysics informed", it is important to demonstrate that these mass-spectrum features are actually demanded by the data rather than imposed by the prior. Please add a prior/posterior comparison or a hyperparameter sensitivity study for the GP model.
minor comments (5)
  1. [Equation (4)] The selection function β(Λ) is introduced in Eq. (4) but never defined explicitly. Please provide its integral form or point to the exact equation in the cited injection papers [20,21,26,51].
  2. [Section II C] The functional forms of the three mass models are not given; the reader is referred to other papers. For a self-contained journal submission, at least the Powerlaw + Peak and Broken Powerlaw + 2 Peaks formulas should be included in an appendix or stated explicitly.
  3. [Figure 1 caption] The caption describes the light blue band as "standard candle type 1A SN measurements" from [45]. This is imprecise: SH0ES is a Cepheid-calibrated Type Ia supernova distance ladder, not simply a type-Ia measurement. Please clarify.
  4. [References] Many bibliography entries are incomplete, containing only an arXiv URL and year (e.g., [1], [2], [3], [4], [15], [21], [36], [37], [43]). Journal style requires full author/title information. Please complete all references.
  5. [Abstract / Section III] The abstract states 153 significant BBH mergers, but the analysis uses 152 after excluding GW231123. The exclusion is explained in Section III, but the abstract should be consistent or note the exclusion explicitly.

Circularity Check

0 steps flagged · score 2.0 of 10

No significant circularity: H0 is a free parameter in a joint hierarchical fit; the same-author GP model is a model choice, not a pre-fitted H0 input.

full rationale

The paper infers H0 through a hierarchical Bayesian likelihood (Eq. 4) in which H0 is a free parameter controlling the mapping between detector-frame and source-frame masses (Eq. 1). The reported H0 posteriors are the output of this joint fit, not a re-statement of an input. The redshift-evolution caveat quoted in Section IV is an explicitly stated modeling assumption, not a circular definition: it does not define H0 in terms of the mass distribution or vice versa. The only same-author citation is Ref. [36] for the 'astrophysics informed Gaussian Process' model. That model is a population-model choice; its parameters are re-fit jointly with H0 in this work, and its features (e.g., PISN gap) are motivated by astrophysical theory rather than by the target H0. The phrase 'extending the results of Ref. [36] under a fixed cosmological model' indicates that the earlier work fixed a cosmology, but this paper varies H0 as a free parameter, and no equation or passage shows that the GP model's output is equivalent to its input. Therefore no circular step meeting the required evidence threshold is present; the self-citation is minor and not load-bearing.

Assumptions & free parameters 4 free parameters · 5 assumptions · 0 invented entities

The central H0 claim rests on: (1) a standard hierarchical Bayesian framework already present in the cited literature (Eqs. 3 and 4); (2) three population models inherited from other papers, including the authors' own GP model from Ref [36], whose hyperparameters and astrophysical priors are not shown here; (3) the flat LCDM mapping of Eq. 7; (4) the explicit assumption of no redshift evolution of the mass spectrum (Section IV); and (5) the GW170817 posterior combination. No new entities are postulated. The fitted quantities are the H0 and Omega_m targets plus the mass-model hyperparameters, all jointly constrained by the same 152 events, which is why the no-evolution assumption and the unshown GP details are the most exposed load-bearing inputs. H0 itself is the measured target with a uniform [20, 220] prior, so it is not listed as a free parameter.

free parameters (4)
  • Mass model hyperparameters (Powerlaw + Peak, Broken Powerlaw + 2 Peaks, Gaussian Process) = Not stated in this paper
    The three population models, whose parameters (slopes, peak positions and widths, mmax, GP hyperparameters) are fit to the 152 events, are defined only by reference to Refs [2, 11, 36, 48]. The GP hyperparameters, which set the feature structure that drives the H0 result, are not reproduced here.
  • kappa (merger rate redshift evolution slope) = Not stated in this paper
    Eq. 3 parameterizes the rate evolution as psi(z) = (1+z)^kappa; kappa is jointly fit and, if wrong, affects the redshift weighting of events.
  • beta (mass-ratio pairing slope) = Not stated in this paper
    Eq. 6 sets the pairing function f(m1,m2) = (m2/m1)^beta; beta is jointly fit.
  • Omega_m (matter density) = Uniform prior [0, 1]
    Eq. 7 maps z to D_L using flat LCDM with Omega_m; Omega_m is jointly varied with a wide prior, coupling into the mass-redshift mapping.
assumptions (5)
  • domain assumption Flat LCDM cosmology with H(z) = H0 sqrt(Omega_m (1+z)^3 + (1 - Omega_m))
    Eq. 7 assumes a specific cosmological model; spectral siren H0 inference shifts if modified GW propagation or non-flat geometry is allowed (Refs [22, 33, 34]).
  • domain assumption The BBH mass distribution does not evolve with redshift
    Stated as a caveat in Section IV and motivated by Refs [2, 44]; it is load-bearing for feature-based redshift inference and is not marginalized over.
  • domain assumption Functional forms and priors of the three mass models are taken at face value from Refs [2, 11, 36, 48]
    Section II C defers all model definitions to cited works, including the GP model of Ref [36] where the astrophysical priors (PISN gap features) are set by the same authors.
  • standard math Hierarchical Bayesian likelihood with importance sampling and injection-based selection (Eqs. 3 and 4)
    Standard framework from Refs [50, 54, 27, 49]; assumes the single-event posteriors and the injection campaign are unbiased and converged.
  • domain assumption GW170817 bright siren posterior of H0 = 71 +23/-8 km/s/Mpc is a valid external constraint for combination
    Section III combines the BBH posteriors with this value, quoted from Ref [8]. The broadening relative to Ref [8]'s published 70 +12/-8 is unexplained, and the combination prescription (simple posterior product) is not detailed.

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Cite this review

Pith. "Pith review of Spectral siren cosmology from gravitational-wave observations in GWTC-4.0." pith.science (2026). https://pith.science/paper/HGOLNENF

@misc{pith2026250903607,
  author       = {Pith},
  title        = {Pith review of: Spectral siren cosmology from gravitational-wave observations in GWTC-4.0},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/HGOLNENF}},
  note         = {Machine review of arXiv:2509.03607}
}
abstract

Gravitational wave standard sirens offer a promising avenue for cosmological inference, particularly in measuring the expansion history of the universe. Traditionally, bright sirens require an electromagnetic counterpart to determine the redshift of the emission source while dark sirens rely on the presence of complete galaxy catalogs over large sky regions. Spectral sirens, using GW data alone, can circumvent these limitations by leveraging features in the mass distribution of compact binaries. With the recent release of the Gravitational-Wave Transient Catalog 4 (GWTC-4.0), the number of significant binary black hole (BBH) merger candidates has increased to 153, enabling more robust population studies and cosmological constraints. This work builds upon previous spectral siren analyses by analyzing the latest BBH observations with parametric and non-parametric models. In particular, we consider a parametric approach using the Powerlaw + Peak and Broken Powerlaw + 2 Peaks models as well as a more flexible non-parametric model based on Gaussian processes. We find broad consistency in the inferred Hubble constant $H_0$ constraints across models. Our most constraining result is from the Gaussian Process model, which, combined with the GW170817 bright siren measurement, results in $H_0 = 69^{+7}_{-6} \ \mathrm{km\,s^{-1}\,Mpc^{-1}}$, a 10% precision measurement. For the Powerlaw + Peak and Broken Powerlaw + 2 Peaks we find fractional uncertainties of 17% and 13% respectively.

Figures

Figures reproduced from arXiv: 2509.03607 by the authors.

Figure 1
Figure 1. FIG. 1. Posterior distributions on the Hubble constant [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗
Figure 2
Figure 2. FIG. 2. Inferred primary (top panel), secondary (middle [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗

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Forward citations

Cited by 11 Pith papers

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Reference graph

Works this paper leans on

54 extracted references · 21 canonical work pages · cited by 9 Pith papers

  1. [8]

    P., et al

    Abbott, B. P., et al. 2017, Nature, 551, 85, doi: 10.1038/ nature24471

    work page 2017

  2. [36]

    —. 2025. https://arxiv.org/abs/2508.19208

    arXiv 2025

  3. [1]

    https://arxiv.org/abs/2508.18082

    2025. https://arxiv.org/abs/2508.18082

    arXiv 2025

  4. [2]

    https://arxiv.org/abs/2508.18083

    2025. https://arxiv.org/abs/2508.18083

    arXiv 2025

  5. [3]

    G., et al

    Abac, A. G., et al. 2025. https://arxiv.org/abs/2508. 18081

    work page 2025

  6. [4]

    —. 2025. https://arxiv.org/abs/2507.08219

    arXiv 2025

  7. [5]

    2017, Phys

    Abbott, B., et al. 2017, Phys. Rev. Lett., 119, 161101, doi: 10.1103/PhysRevLett.119.161101

    doi:10.1103/physrevlett.119.161101 2017

  8. [6]

    2019, Physical Review X, 9, 011001

    Abbott, B., Abbott, R., Abbott, T., et al. 2019, Physical Review X, 9, 011001

    work page 2019

Show all 54 references
  1. [7]

    P., Abbott, R., Abbott, T., et al

    Abbott, B. P., Abbott, R., Abbott, T., et al. 2017, The Astrophysical Journal Letters, 848, L13 6

    2017

  2. [9]

    2021, Astrophys

    Abbott, R., et al. 2021, Astrophys. J. Lett., 913, L7, doi: 10.3847/2041-8213/abe949

    2021 doi

  3. [10]

    2023, Phys

    —. 2023, Phys. Rev. X, 13, 041039, doi: 10.1103/ PhysRevX.13.041039

    2023

  4. [11]

    2023, Phys

    —. 2023, Phys. Rev. X, 13, 011048, doi: 10.1103/ PhysRevX.13.011048

    2023

  5. [12]

    2023, Astrophys

    —. 2023, Astrophys. J., 949, 76, doi: 10.3847/ 1538-4357/ac74bb

    2023

  6. [13]

    2025, Blinded Mock Data Challenge for Gravitational-Wave Cosmology-I: Assessing the Robustness of Methods Us- ing Binary Black Holes Mass Spectrum

    Agarwal, A., Dupletsa, U., Leyde, K., et al. 2025, Blinded Mock Data Challenge for Gravitational-Wave Cosmology-I: Assessing the Robustness of Methods Us- ing Binary Black Holes Mass Spectrum. https://arxiv. org/abs/2412.14244

    2025 arXiv

  7. [14]

    2020, As- tronomy & Astrophysics, 641, A6

    Aghanim, N., Akrami, Y., Ashdown, M., et al. 2020, As- tronomy & Astrophysics, 641, A6

    2020

  8. [15]

    Antonini, F., Callister, T., Dosopoulou, F., Romero- Shaw, I., & Chattopadhyay, D. 2025. https://arxiv. org/abs/2506.09154

    2025 arXiv

  9. [16]

    R., Alfradique, V., Palmese, A., et al

    Bom, C. R., Alfradique, V., Palmese, A., et al. 2024, Mon. Not. Roy. Astron. Soc., 535, 961, doi: 10.1093/ mnras/stae2390

    2024

  10. [17]

    A., & Farr, W

    Callister, T. A., & Farr, W. M. 2024, Phys. Rev. X, 14, 021005, doi: 10.1103/PhysRevX.14.021005

    2024 doi

  11. [18]

    M., & Gupta, I

    Chen, H.-Y., Ezquiaga, J. M., & Gupta, I. 2024. https: //arxiv.org/abs/2402.03120

    2024 arXiv

  12. [19]

    2023, Astrophys

    Edelman, B., Farr, B., & Doctor, Z. 2023, Astrophys. J., 946, 16, doi: 10.3847/1538-4357/acb5ed

    2023 doi

  13. [20]

    2022, Precision Requirements for Monte Carlo Sums within Hierarchical Bayesian Infer- ence

    Essick, R., & Farr, W. 2022, Precision Requirements for Monte Carlo Sums within Hierarchical Bayesian Infer- ence. https://arxiv.org/abs/2204.00461

    2022 arXiv

  14. [21]

    Essick, R., et al. 2025. https://arxiv.org/abs/2508. 10638

    2025

  15. [22]

    Ezquiaga, J. M. 2021, Phys. Lett. B, 822, 136665, doi:10. 1016/j.physletb.2021.136665

    2021

  16. [23]

    M., & Holz, D

    Ezquiaga, J. M., & Holz, D. E. 2022, Phys. Rev. Lett., 129, 061102, doi: 10.1103/PhysRevLett.129.061102

    2022 doi

  17. [24]

    M., Callister, T

    Farah, A. M., Callister, T. A., Ezquiaga, J. M., Zevin, M., & Holz, D. E. 2025, Astrophys. J., 978, 153, doi: 10. 3847/1538-4357/ad9253

    2025

  18. [25]

    M., Fishbach, M., & Holz, D

    Farah, A. M., Fishbach, M., & Holz, D. E. 2024, Astro- phys. J., 962, 69, doi: 10.3847/1538-4357/ad0558

    2024 doi

  19. [26]

    Farr, W. M. 2019, Research Notes of the AAS, 3, 66, doi: 10.3847/2515-5172/ab1d5f

    2019 doi

  20. [27]

    M., Fishbach, M., Ye, J., & Holz, D

    Farr, W. M., Fishbach, M., Ye, J., & Holz, D. 2019, Astrophys. J. Lett., 883, L42, doi: 10.3847/2041-8213/ ab4284

    2019 doi

  21. [28]

    Fishbach, M., & Holz, D. E. 2020, Astrophys. J. Lett., 891, L27, doi: 10.3847/2041-8213/ab7247

    2020 doi

  22. [29]

    E., & Farr, W

    Fishbach, M., Holz, D. E., & Farr, W. M. 2018, Astro- phys. J. Lett., 863, L41, doi: 10.3847/2041-8213/aad800

    2018 doi

  23. [30]

    Golomb, J., Isi, M., & Farr, W. M. 2024, Astrophys. J., 976, 121, doi: 10.3847/1538-4357/ad8572

    2024 doi

  24. [31]

    2025, Phys

    Heinzel, J., Mould, M., ´Alvarez-L´ opez, S., & Vitale, S. 2025, Phys. Rev. D, 111, 063043, doi: 10.1103/ PhysRevD.111.063043

    2025

  25. [32]

    E., & Hughes, S

    Holz, D. E., & Hughes, S. A. 2005, Astrophys. J., 629, 15, doi: 10.1086/431341

    2005 doi

  26. [33]

    2022, Journal of Cos- mology and Astroparticle Physics, 2022, 012, doi: 10

    Leyde, K., Mastrogiovanni, S., Steer, D., Chassande- Mottin, E., & Karathanasis, C. 2022, Journal of Cos- mology and Astroparticle Physics, 2022, 012, doi: 10. 1088/1475-7516/2022/09/012

    2022

  27. [34]

    2023, Phys

    Maga˜ na Hernandez, I. 2023, Phys. Rev. D, 107, 084033, doi: 10.1103/PhysRevD.107.084033

    2023 doi

  28. [35]

    2025, Phys

    Maga˜ na Hernandez, I., & Palmese, A. 2025, Phys. Rev. D, 111, 083031, doi: 10.1103/PhysRevD.111.083031

    2025 doi

  29. [37]

    2024.https://arxiv

    Maga˜ na Hernandez, I., & Ray, A. 2024.https://arxiv. org/abs/2404.02522

    2024 arXiv

  30. [38]

    2025, Astrophys

    Mali, U., & Essick, R. 2025, Astrophys. J., 980, 85, doi: 10.3847/1538-4357/ad9de7

    2025 doi

  31. [39]

    R., Mucesh, S., & Hartley, W

    Palmese, A., Bom, C. R., Mucesh, S., & Hartley, W. G. 2023, Astrophys. J., 943, 56, doi: 10.3847/1538-4357/ aca6e3

    2023 doi

  32. [40]

    2024, Phys

    Palmese, A., Kaur, R., Hajela, A., et al. 2024, Phys. Rev. D, 109, 063508, doi: 10.1103/PhysRevD.109.063508

    2024 doi

  33. [41]

    Palmese, A., & Mastrogiovanni, S. 2025. https://arxiv. org/abs/2502.00239

    2025 arXiv

  34. [42]

    2024, Phys

    Pierra, G., Mastrogiovanni, S., Perri` es, S., & Mapelli, M. 2024, Phys. Rev. D, 109, 083504, doi: 10.1103/ PhysRevD.109.083504

    2024

  35. [43]

    Ray, A., Maga˜ na Hernandez, I., Breivik, K., & Creighton, J. 2024. https://arxiv.org/abs/2404.03166

    2024 arXiv

  36. [44]

    2023, Astrophys

    Ray, A., Maga˜ na Hernandez, I., Mohite, S., Creighton, J., & Kapadia, S. 2023, Astrophys. J., 957, 37, doi: 10. 3847/1538-4357/acf452

    2023

  37. [45]

    G., Wenlong, Y., Macri Lucas, M., et al

    Riess, A. G., Wenlong, Y., Macri Lucas, M., et al. 2022, Astrophys. J. Lett, 934, L7

    2022

  38. [46]

    K., van Son, L

    Roy, S. K., van Son, L. A. C., & Farr, W. M. 2025. https://arxiv.org/abs/2507.01086

    2025

  39. [47]

    Schutz, B. F. 1986, Nature, 323, 310, doi: 10.1038/ 323310a0

    1986

  40. [48]

    2018, Astrophys

    Talbot, C., & Thrane, E. 2018, Astrophys. J., 856, 173, doi: 10.3847/1538-4357/aab34c

    2018 doi

  41. [49]

    R., & Gair, J

    Taylor, S. R., & Gair, J. R. 2012, Phys. Rev. D, 86, 023502, doi: 10.1103/PhysRevD.86.023502

    2012 doi

  42. [50]

    2019, Publications of the As- tronomical Society of Australia, 36, doi: 10.1017/pasa

    Thrane, E., & Talbot, C. 2019, Publications of the As- tronomical Society of Australia, 36, doi: 10.1017/pasa. 2019.2

    2019 doi

  43. [51]

    2018, Class

    Tiwari, V. 2018, Class. Quant. Grav., 35, 145009, doi:10. 1088/1361-6382/aac89d

    2018

  44. [52]

    2022, Astrophys

    —. 2022, Astrophys. J., 928, 155, doi: 10.3847/ 1538-4357/ac589a

    2022

  45. [53]

    2025, Astrophys

    Tong, H., Fishbach, M., & Thrane, E. 2025, Astrophys. J., 985, 220, doi: 10.3847/1538-4357/adcec5

    2025 doi

  46. [54]

    M., & Taylor, S

    Vitale, S., Gerosa, D., Farr, W. M., & Taylor, S. R. 2020, doi: 10.1007/978-981-15-4702-7_45-1

    2020 doi

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