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Structure and Skewness of the Effective Inspiral Spin Distribution of Binary Black Hole Mergers

T0 review · 4 major / 6 minor · reviewed 2026-08-10 · deepseek-v4-flash

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Pith's one-line read Merging black hole spins are non-Gaussian, exposing an aligned subpopulation of at least 12-17%.

desk verdict A careful empirical chi_eff analysis whose headline aligned-subpopulation floor is real but less robust than claimed once the symmetry caveat in the footnote is taken seriously. read the letter →

arxiv 2501.06712 v2 pith:FJTW4TFC submitted 2025-01-12 astro-ph.HE gr-qc

Sharan Banagiri , Thomas A. Callister , Christian Adamcewicz , Zoheyr Doctor , Vicky Kalogera This is my paper · ORCID
classification astro-ph.HEgr-qc
keywords gravitationalwavesbinaryblackholeseffectiveinspiralspinalignmentformationchannelspopulationinferenceskewness
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

Black hole binaries that merge within a Hubble time can form through several channels, and the authors argue that the distribution of the effective inspiral spin $\chi_{\rm eff}$ — the mass-weighted projection of the component spins onto the orbital angular momentum — is a sharper probe of these channels than individual spins. Using the first three observing runs of the current gravitational-wave detector network, they find that the $\chi_{\rm eff}$ distribution is positively skewed and asymmetric about zero, but shows no statistically significant bimodality. They interpret the asymmetry as evidence that a subpopulation of binaries forms with spins preferentially aligned to the orbit, and conservatively place the size of this subpopulation at at least $12\%$--$17\%$ (90% credibility) without assuming a particular shape for the aligned channel's spin distribution. The same analysis requires that at least $\sim 20\%$ of binaries have negative $\chi_{\rm eff}$, and it finds no evidence for a sharp excess of non-spinning systems.

What carries the argument

The central object is the effective inspiral spin parameter $\chi_{\rm eff} = (m_1 \vec{a}_1 + m_2 \vec{a}_2)\cdot \hat{L}/(m_1+m_2)$, the mass-weighted projection of the two black holes' dimensionless spin vectors onto the orbital angular momentum; it is a constant of motion at 2PN order and is far better measured than individual component spins. The argument is carried by three unimodal population models (truncated normal, skew-normal, and $\epsilon$-skew-normal) that allow skewed and asymmetric shapes, and by a mixture model that combines a zero-centered truncated normal (representing a random-spin channel such as dynamical assembly) with a skew-normal (representing a preferentially aligned channel). The key diagnostics are the asymmetry measure $\alpha(\chi_0)$, the difference between integrated probabilities above and below $\chi_0$, and the residual $R(\chi)$, which subtracts the negative tail from the positive tail to expose the excess from aligned channels.

What would settle it

Measure the $\chi_{\rm eff}$ distribution of dynamically assembled binary black holes — from cluster-formed mergers in existing catalogs or from new simulations that do not impose tilt symmetry — and test whether its mean is zero. A mean offset of a few percent (e.g., $\langle \chi_{\rm eff} \rangle > 0.02$) would break the symmetry assumption behind $\alpha(0)$ and $R(\chi)$, invalidating the $12\%$--$17\%$ lower-limit interpretation; conversely, if the next catalog drives $R(\chi)$ to zero at all $\chi$, the aligned-subpopulation claim would collapse.

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Extended reading notes

Core claim

On its own terms, the paper establishes that the observed $\chi_{\rm eff}$ distribution of binary black hole mergers is not a symmetric Gaussian: three empirical models — a truncated normal, a skew-normal, and an $\epsilon$-skew-normal — all yield a positive skewness and an asymmetry about $\chi_{\rm eff}=0$, with a mode consistent with zero. The asymmetry metric $\alpha(0)$, defined as the integrated probability above $\chi_{\rm eff}=0$ minus the integrated probability below it, has a 90% lower limit of $12\%$--$17\%$ across the models, which the authors treat as a conservative floor on the fraction of the population formed through preferentially aligned channels. They further construct a residual $R(\chi)=p(\chi_{\rm eff}=\chi)-p(\chi_{\rm eff}=-\chi)$ for $\chi\ge 0$, which isolates the positive excess attributable to aligned formation under the assumption that random-spin channels are symmetric about zero; this residual is confined to $\chi\lesssim 0.4$, implying the aligned subpopulation has small spins. A two-component mixture model separating a random channel from an aligned channel finds no strong evidence for bimodality, instead favoring either a small aligned population with positive spins or a large aligned population centered near zero.

Load-bearing premise

The floor on the aligned subpopulation assumes that random-spin formation channels, such as dynamical assembly in dense clusters, produce a $\chi_{\rm eff}$ distribution that is exactly symmetric about zero; if those channels themselves generate slightly aligned spins, the floor no longer cleanly separates aligned from random formation.

Editorial extensions

If this is right

  • At least $12\%$--$17\%$ of merging binary black holes (at 90% credibility) are produced by a channel that preferentially aligns spins with the orbital angular momentum, such as isolated binary evolution.
  • At least $\sim 20\%$ of binaries have negative $\chi_{\rm eff}$, meaning at least one black hole spins opposite to the orbit, which disfavors models in which nearly all mergers are field binaries with negligible spins.
  • If preferentially aligned mergers dominate the population, they must have small spins, with the positive residual concentrated at $\chi_{\rm eff} \lesssim 0.2$ and a tail to $\sim 0.4$.
  • Current data do not support a sharp excess of non-spinning binaries; a mixture model adding a delta-function spike at $\chi_{\rm eff}=0$ is disfavored by a log Bayes factor of $-3.0$ relative to the skew-normal model alone.
  • The known $\chi_{\rm eff}$--$q$ anti-correlation can be reproduced by two channels with different mass-ratio distributions, with mild support for a flatter $q$ distribution in the aligned channel ($\beta_R > \beta_A$ at 65% credibility).

Reading between the lines

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

  • If random-spin formation channels are not exactly symmetric about zero — for instance if stellar collisions in clusters impart small aligned spins, as recent simulations suggest — then $\alpha(0)$ and $R(\chi)$ would no longer cleanly separate aligned from random channels, and the $12\%$--$17\%$ floor would need reinterpretation as a blended quantity.
  • The same asymmetry diagnostics could be applied to other spin parameters such as the precessing spin $\chi_p$, or to subpopulations split by mass or redshift, to test whether the aligned fraction changes with lookback time or grows at high masses where hierarchical mergers contribute.
  • With a larger catalog from the next observing run, the residual $R(\chi)$ can be measured at higher significance: a persistent positive excess confined to $\chi_{\rm eff}<0.4$ would confirm small aligned spins from isolated binaries, while an excess extending to higher $\chi_{\rm eff}$ would point to an additional aligned channel such as AGN disks.
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Formalized claims in Lean

  1. Claim #1: The inferred `chi_eff` distribution is non-Gaussian, with positive skewness and asymmetry about zero.

  2. Claim #2: The 90% credible lower bound on the aligned subpopulation fraction is between 12% and 17%.

  3. Claim #3: At least about 20% of binary black hole mergers have negative `chi_eff`.

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

4 major / 6 minor

Summary. This paper analyzes the effective inspiral spin (χ_eff) distribution of 69 binary black hole mergers from the first three LIGO-Virgo-KAGRA observing runs using hierarchical Bayesian inference. The authors fit several empirical population models: a truncated normal, two skew-normal variants, and mixture models with a zero-centered random component plus a skew-normal aligned component. They report positive skewness and asymmetry about χ_eff=0, with Bayes factors of 3.5 and 1.8 relative to the truncated normal, a 90% lower limit of 12%–17% on the fraction of a preferentially aligned subpopulation, and a lower limit of ~20% on systems with negative χ_eff. They find no strong evidence for bimodality and interpret the results as 'robust evidence' for an aligned subpopulation with small spins.

Significance. If the central claim held, the paper would provide one of the first direct population-level constraints on the aligned versus random formation-channel fraction using χ_eff alone, complementing component-spin analyses. The hierarchical machinery is careful: selection effects are treated via injection sets, the mass/redshift models follow the LIGO-Virgo-KAGRA standard, and the paper examines multiple parametrizations to test model dependence. The paper also makes concrete, falsifiable predictions: the ~20% negative-χ_eff floor, the small spin magnitudes of the aligned component, and the absence of bimodality. However, as detailed below, the central claim rests on an assumption—exact symmetry of the random-spin channel—that the paper itself flags as uncertain; the modest Bayes factors undercut the word 'robust'; and some secondary claims in Sec. 5.2 are not fully supported.

major comments (4)
  1. [Sec. 3.1, Eq. (5), footnote 1] The interpretation of α(0) as a conservative lower limit on the preferentially aligned subpopulation fraction requires that the random-spin channel produce a χ_eff distribution exactly symmetric about zero. The paper states this assumption in Sec. 3.1 ('we expect a subpopulation from a random spin channel to be completely symmetric about χ_eff=0...'), but its own footnote 1 cites Kıroğlu et al. (2025), which predicts that cluster collisions of BBHs with stars generate a population with small aligned spins. If the random channel possesses a small positive mean μ_r, its contribution to α(0) is approximately sqrt(2/π) μ_r/σ_r; for μ_r ≈ 0.02–0.05 and σ_r ≈ 0.1–0.2 this is of order 10–20%, comparable to the claimed 12–17% floor. The footnoted caveat is not propagated into the interpretation, so the headline claim is not yet robust to this well-motivated physical alternative. I recommend either adding an explicit offset-mean 'random' component to the model and testing whether the asymmetry persists, or reframing the result as a measurement of asymmetry rather than a lower limit on an aligned subpopulation.
  2. [Sec. 3] The evidence for skewness relative to the truncated normal is modest: Bayes factors of 3.5 (skewnormal) and 1.8 (ε-skewnormal). Under standard Jeffreys scales these constitute 'positive' rather than 'strong' evidence, and the ε-skewnormal preference is barely worth mentioning. The abstract and Sec. 5 describe the features as 'robust evidence'; this overstates the statistical support. Please temper the language or provide supplemental tests (e.g., injection-recovery calibrations, posterior predictive checks, or fractional false-alarm rates in simulated catalogs) that would justify the stronger wording.
  3. [Sec. 4, Eq. (7)] The mixture model fixes the random component's normal distribution to have zero mean. This makes λ_al degenerate with the true mean of the random channel: any positive asymmetry in the random channel is absorbed into the aligned component. The bimodal posterior for λ_al in Fig. 8 may therefore reflect not two physical formation scenarios but the model's inability to represent a single skewed random channel. The paper notes the degeneracy qualitatively but does not test it by allowing a free mean for the random component. Since the aligned fraction is a central quantity, this test is necessary to support the conclusions drawn from the mixture model.
  4. [Sec. 5.2] The estimate that 'at least about 40% of merging BBHs come from some sort of dynamical formation channel' rests on the assumption that preferentially-aligned spin pathways cannot produce negative χ_eff. This contradicts the more conservative treatment in Sec. 3.1, where the authors explicitly allow preferentially-aligned binaries to have negative χ_eff (citing strong natal kicks or internal gravity-wave spin-up). The two interpretations cannot both be used without a stated conditional framework; if the conservative assumption is adopted, the 40% dynamical fraction does not follow, and if the strong assumption is adopted, the 12–17% aligned floor is no longer conservative.
minor comments (6)
  1. [Sec. 2, footnote 1] The caveat about Kıroğlu et al. (2025) is important enough to be moved into the main text of Sec. 3.1 and discussed alongside Eq. (5).
  2. [Sec. 3, Fig. 3] The color description 'blue traces' is not meaningful if the figure is printed in grayscale; consider labeling draws by alpha or line style.
  3. [Sec. 3] The statement 'η_eff ≥ 0 at 99.1% credence' should specify whether this is a one-sided or two-sided credible interval, to avoid ambiguity.
  4. [Sec. 4.1] The 65% credibility for β_R > β_A is very weak; the text says 'mild preference' but this is close to uninformative. Consider highlighting this explicitly in the abstract or discussion to avoid overreading.
  5. [Sec. 5.2] The claim that previous analyses (Tong et al. 2022; Adamcewicz et al. 2024) suffered from a normalization error is a serious assertion. If it is not fully detailed in this paper, please provide a reference or an appendix that substantiates it, since it could mislead readers about the reliability of prior work.
  6. [Table 1] The table caption could define the 90% lower limit more precisely (i.e., the 5th percentile of the posterior for α), as the current phrasing is ambiguous.

Circularity Check

0 steps flagged · score 2.0 of 10

The paper shows no significant circularity: the aligned-subpopulation fraction is a posterior measurement from fitted chi_eff models, not an input, and the cited self-work is peripheral to the headline claim.

full rationale

This paper is an observational population analysis rather than a derivation from first principles, and its central claims do not reduce to their inputs. The skewnormal, epsilon-skewnormal, truncated-normal, and mixture models are hierarchical fits to public LIGO-Virgo-KAGRA data with explicit priors described in Appendix A; the reported skewness, asymmetry alpha(0), p(chi_eff <= 0), and the 12-17% lower limit are posterior summaries of those fits computed from Eq. (5) after fitting, so they are measurements rather than parameters inserted by hand. The inference that the asymmetry implies a preferentially aligned subpopulation rests on the stated physical assumption that random-spin channels produce a chi_eff distribution symmetric about zero (Sec. 3.1), which is an assumption and not a circular definition; the paper itself flags a mechanism that can break this assumption in footnote 1 (Kiroglu et al. 2025) and in the residual discussion. Self-citations (Callister et al. 2021; Adamcewicz et al. 2023, 2024; Baibhav et al. 2023) are used for prior modeling context or for the chi_eff-q correlation, which is independently corroborated by external LVK analyses; none is load-bearing for the headline asymmetry or the 12-17% floor. No fitted parameter is renamed as a prediction, no uniqueness theorem is imported, and no known result is merely relabeled as unification. Accordingly, there is no significant circularity.

Assumptions & free parameters 12 free parameters · 6 assumptions · 0 invented entities

All spin claims come from fitting flexible parametric models to public GWTC-3 data. The free parameters are the shape parameters constrained by the data; no new physical entities are introduced. The central interpretive step, the symmetry assumption on the random channel chi_eff distribution, is a domain assumption rather than a derivation.

free parameters (12)
  • mu_eff = posterior; mode consistent with zero under skew models
    Location parameter of the chi_eff distribution, fitted to data in all three unimodal models.
  • sigma_eff = posterior; not quoted precisely
    Scale parameter of the chi_eff distribution, fitted in all models.
  • eta_eff = eta_eff >= 2.9 at 90% credibility; non-negative at 99.1% credence
    Skewness parameter of the skewnormal model, used in Sec. 3 to detect tail asymmetry.
  • epsilon_eff = epsilon_eff < 0 at 90.1% credibility
    Skewness parameter of the epsilon-skewnormal model, an alternative parameterization of tail asymmetry.
  • lambda_al = posterior; bimodal with modes favoring either low or high aligned fraction
    Branching fraction of the preferentially aligned population in the mixture model, Eq. 7.
  • mu_al = posterior; near zero in the high-lambda_al mode
    Location of the aligned skewnormal component in the mixture model.
  • sigma_al = posterior; not quoted precisely
    Scale of the aligned component in the mixture model.
  • eta_al = posterior; broad
    Skewness of the aligned component in the mixture model.
  • sigma_r = posterior; not quoted precisely
    Scale of the random channel truncated normal component in the mixture model.
  • beta_A = posterior; beta_R > beta_A at 65% credence
    Mass ratio power-law index for the aligned population in the separate-p(q) model.
  • beta_R = posterior; not quoted precisely
    Mass ratio power-law index for the random population in the separate-p(q) model.
  • Nuisance mass/redshift/chi_p hyperparameters = posterior distributions, not central
    Mass, redshift, and precession models used only for marginalization; shape inferences could shift if these are misspecified.
assumptions (6)
  • domain assumption Random spin channels produce a chi_eff distribution exactly symmetric about zero
    Used in Sec. 3.1 and Eq. 6 to interpret alpha(0) as a lower bound on the preferentially aligned subpopulation and to define the residual R(chi). If false, the 12-17% floor loses its clean formation channel interpretation.
  • domain assumption Preferentially aligned channels may produce systems with negative chi_eff
    This makes alpha(0) a conservative lower limit rather than an exact aligned fraction. The paper allows aligned channels to have negative effective spin; if aligned channels were strictly non-negative, alpha(0) would instead equal the aligned fraction.
  • domain assumption The hierarchical likelihood, selection function, and PE sample weighting are unbiased
    Eq. A1 and the LVK injection-based zeta(Λ) calculation assume the released posterior samples and detection sensitivity estimates are correct, and that chi_eff and chi_p can be modeled independently.
  • ad hoc to paper Skewnormal and epsilon-skewnormal families are flexible enough to represent the true chi_eff distribution
    The detection of skewness is only meaningful if these two functional forms do not force skewness through their parameterization. The paper does not run injection-recovery tests to verify this.
  • ad hoc to paper The mixture model's random component is exactly centered at zero
    Eq. 7 fixes the random channel as a zero-mean truncated normal. This is the cleanest way to measure an aligned excess but rules out a shifted random channel by construction.
  • standard math Monte Carlo integration and nested sampling convergence
    The hierarchical evidence integrals are estimated with dynesty and jax; standard numerical assumptions apply.

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Cite this review

Pith. "Pith review of Structure and Skewness of the Effective Inspiral Spin Distribution of Binary Black Hole Mergers." pith.science (2026). https://pith.science/paper/FJTW4TFC

@misc{pith2026250106712,
  author       = {Pith},
  title        = {Pith review of: Structure and Skewness of the Effective Inspiral Spin Distribution of Binary Black Hole Mergers},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/FJTW4TFC}},
  note         = {Machine review of arXiv:2501.06712}
}
abstract

The detection of gravitational waves has brought to light a population of binary black holes that merge within a Hubble time. Multiple formation channels can contribute to this population, making it difficult to definitively associate particular population features with underlying stellar physics. Black hole spins are considered an important discriminator between various channels, but they are less well-measured than masses, making conclusive astrophysical statements using spins difficult thus far. In this paper, we consider the distribution of the effective inspiral spin $\chi_{\rm eff}$ -- a quantity much better measured than individual component spins. We show that non-Gaussian features like skewness, asymmetry about zero, and multimodality can naturally arise in the $\chi_{\rm eff}$ distribution when multiple channels contribute to the population. Searching for such features, we find signs of skewness and asymmetry already in the current catalogs, but no statistically significant signs of bimodality. These features provide robust evidence for the presence of a subpopulation with spins preferentially aligned to the binary's orbital angular momentum; and we conservatively estimate the fraction of this subpopulation to be at least $12 \% - 17\%$ (at $90\%$ credibility). Our models do not find an excess of non-spinning systems and instead find that at least $\sim 20 \%$ of the binaries have some degree of negative $\chi_{\rm eff}$. The data also suggest that, if preferentially aligned mergers form a significant fraction of the population, they must have small spins.

Figures

Figures reproduced from arXiv: 2501.06712 by the authors.

Figure 1
Figure 1. A illustration of tilt angles under random and preferentially-aligned spin channels. The tilt distribution is uniform for a random spin channel. A preferentially￾aligned spin channel can present some degree of alignment or anti-alignment. Furthermore, based on the physics of the preferentially-aligned spin channel, the tilt distribution can also be skewed about its mode. such a channel (Kalogera 2000; Gerosa et al. … view at source ↗
Figure 2
Figure 2. Illustrative plots showing how the effective distributions of a random and aligned population can look like and what the combined population can look like. The plot on the left shows the case where a random spin channel dominates the population, while the plot on the right illustrates a case where a positively preferentially-aligned spin channel dominates. sequently, the χeff distribution of a random spin chan￾nel w… view at source ↗
Figure 3
Figure 3. The χeff PPD under the skewnormal model on the left, and the ε-skewnormal model on the right, using data from the first three observing runs of the LVK. The blue traces show the probability distribution for individual draws from the posterior. The solid black line is the median value of p(χeff |d) at each χeff while the dashed black lines are the 90% credible levels. We return to the astrophysical implications of sk… view at source ↗
Figures from the paper (6 more)
Figure 4
Figure 4. Figure 4: Residual of the skewnormal fit on the left, and the ε-skewnormal fit on the right (as defined by Eq. 6). If negative effective spins are assumed to arise purely from random formation channels (like dynamical assembly in dense clusters), then R(χeff ) can be interpreted…
Figure 5
Figure 5. Figure 5: PPDs of the two modes of λal in the mixture model analysis of Sec. 4. The plot on the left shows the χeff distribution of the λal ≤ 0.5 mode, while the plot on the right shows the λal > 0.5 mode. The orange and green solid lines show the medians of the random and align…
Figure 6
Figure 6. Figure 6: The posterior distributions of the mass-ratio power-law indices for the aligned population (βA) and the random population (βR). We find that the data has a mild preference for βR > βA. The dashed red line corresponds to βR = βA. We comment more on the astrophysical imp…
Figure 7
Figure 7. Figure 7: Two different instances of the skewnormal model. The blue curve shows an instance with high skewness (η = 10) but with no probability mass at χeff < 0. The gold￾colored curve, on the other hand, shows a distribution with the same skewness but with significant probabili…
Figure 8
Figure 8. Figure 8: Corner plot for the parameters of the m1 and χeff distribution for the skewnormal mixture model. Note in particular the distribution of λal which is bimodal. This suggests that the population is either dominated by either a random spin channel or a preferentially-align…
Figure 9
Figure 9. Figure 9: Corner plot for the parameters of the χeff distribution for the mixture model with distinct p(q) described in Sec. 4.1. We see the same bimodality in λal as in [PITH_FULL_IMAGE:figures/full_fig_p019_9.png]

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Forward citations

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Reference graph

Works this paper leans on

118 extracted references · 3 canonical work pages · cited by 6 Pith papers

  1. [1]

    2015, Class

    Aasi, J., et al. 2015, Class. Quant. Grav., 32, 074001, 10.1088/0264-9381/32/7/074001

    doi:10.1088/0264-9381/32/7/074001 2015

  2. [2]

    P., et al

    Abbott, B. P., et al. 2016, Phys. Rev. Lett., 116, 061102, 10.1103/PhysRevLett.116.061102

    doi:10.1103/physrevlett.116.061102 2016

  3. [3]

    2019, Phys

    ---. 2019, Phys. Rev. X, 9, 031040, 10.1103/PhysRevX.9.031040

    doi:10.1103/physrevx.9.031040 2019

  4. [4]

    2020, Astrophys

    Abbott, R., et al. 2020, Astrophys. J. Lett., 900, L13, 10.3847/2041-8213/aba493

    doi:10.3847/2041-8213/aba493 2020

  5. [5]

    2021 a , Astrophys

    ---. 2021 a , Astrophys. J. Lett., 913, L7, 10.3847/2041-8213/abe949

    doi:10.3847/2041-8213/abe949 2021

  6. [6]

    2021 b , Phys

    ---. 2021 b , Phys. Rev. X, 11, 021053, 10.1103/PhysRevX.11.021053

    doi:10.1103/physrevx.11.021053 2021

  7. [7]

    2023 a , Phys

    ---. 2023 a , Phys. Rev. X, 13, 041039, 10.1103/PhysRevX.13.041039

    doi:10.1103/physrevx.13.041039 2023

  8. [8]

    2023 b , Phys

    ---. 2023 b , Phys. Rev. X, 13, 011048, 10.1103/PhysRevX.13.011048

    doi:10.1103/physrevx.13.011048 2023

Show all 118 references
  1. [9]

    2015, Class

    Acernese, F., et al. 2015, Class. Quant. Grav., 32, 024001, 10.1088/0264-9381/32/2/024001

    2015 doi

  2. [10]

    D., & Thrane, E

    Adamcewicz, C., Galaudage, S., Lasky, P. D., & Thrane, E. 2024, Astrophys. J. Lett., 964, L6, 10.3847/2041-8213/ad2df2

    2024 doi

  3. [11]

    D., & Thrane, E

    Adamcewicz, C., Lasky, P. D., & Thrane, E. 2023, Astrophys. J., 958, 13, 10.3847/1538-4357/acf763

    2023 doi

  4. [12]

    2022, Mon

    Adamcewicz, C., & Thrane, E. 2022, Mon. Not. Roy. Astron. Soc., 517, 3928, 10.1093/mnras/stac2961

    2022 doi

  5. [13]

    2025, in prep

    Adamcewicz, C., et al. 2025, in prep

    2025

  6. [14]

    2011, Physical Review Letters, 106, 241101, 10.1103/PhysRevLett.106.241101

    Ajith, P., Hannam, M., Husa, S., et al. 2011, Physical Review Letters, 106, 241101, 10.1103/PhysRevLett.106.241101

    2011 doi

  7. [15]

    2021, PTEP, 2021, 05A101, 10.1093/ptep/ptaa125

    Akutsu, T., et al. 2021, PTEP, 2021, 05A101, 10.1093/ptep/ptaa125

    2021 doi

  8. [16]

    J., Bavera , S

    Andrews , J. J., Bavera , S. S., Briel , M., et al. 2024, arXiv e-prints, arXiv:2411.02376, 10.48550/arXiv.2411.02376

    2024 doi arXiv

  9. [17]

    Antonini, F., & Rasio, F. A. 2016, Astrophys. J., 831, 187, 10.3847/0004-637X/831/2/187

    2016 doi

  10. [18]

    M., & Callister , T

    Antonini , F., Romero-Shaw , I. M., & Callister , T. 2024, arXiv e-prints, arXiv:2406.19044, 10.48550/arXiv.2406.19044

    2024 doi arXiv

  11. [19]

    2019, Astrophys

    Ashton, G., et al. 2019, Astrophys. J. Suppl., 241, 27, 10.3847/1538-4365/ab06fc

    2019 doi

  12. [20]

    1985, Scandinavian journal of statistics, 171

    Azzalini, A. 1985, Scandinavian journal of statistics, 171

    1985

  13. [21]

    2023, Astrophys

    Baibhav, V., Doctor, Z., & Kalogera, V. 2023, Astrophys. J., 946, 50, 10.3847/1538-4357/acbf4c

    2023 doi

  14. [22]

    Baibhav, V., & Kalogera, V. 2024. 2412.03461

    2024 arXiv

  15. [23]

    2009, Monthly Notices of the Royal Astronomical Society, 402, 371–380, 10.1111/j.1365-2966.2009.15880.x

    Banerjee, S., Baumgardt, H., & Kroupa, P. 2009, Monthly Notices of the Royal Astronomical Society, 402, 371–380, 10.1111/j.1365-2966.2009.15880.x

    2009

  16. [24]

    S., et al

    Bavera, S. S., et al. 2021, Astron. Astrophys., 647, A153, 10.1051/0004-6361/202039804

    2021 doi

  17. [25]

    E., et al

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

    2016 doi

  18. [26]

    A., Haster, C.-J., et al

    Biscoveanu, S., Callister, T. A., Haster, C.-J., et al. 2022, Astrophys. J. Lett., 932, L19, 10.3847/2041-8213/ac71a8

    2022 doi

  19. [27]

    2020, The Astrophysical Journal, 898, 71, 10.3847/1538-4357/ab9d85

    Breivik , K., Coughlin , S., Zevin , M., et al. 2020, The Astrophysical Journal, 898, 71, 10.3847/1538-4357/ab9d85

    2020 doi

  20. [28]

    A., & Farr, W

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

    2024 doi

  21. [29]

    A., Haster, C.-J., Ng, K

    Callister, T. A., Haster, C.-J., Ng, K. K. Y., Vitale, S., & Farr, W. M. 2021, Astrophys. J. Lett., 922, L5, 10.3847/2041-8213/ac2ccc

    2021 doi

  22. [30]

    A., Miller, S

    Callister, T. A., Miller, S. J., Chatziioannou, K., & Farr, W. M. 2022, Astrophys. J. Lett., 937, L13, 10.3847/2041-8213/ac847e

    2022 doi

  23. [31]

    E., McKernan , B., Ford , K

    Cook , H. E., McKernan , B., Ford , K. E. S., et al. 2024, arXiv e-prints, arXiv:2411.10590, 10.48550/arXiv.2411.10590

    2024 doi arXiv

  24. [32]

    M., Casares, J., Munoz-Darias, T., et al

    Corral-Santana, J. M., Casares, J., Munoz-Darias, T., et al. 2016, Astron. Astrophys., 587, A61, 10.1051/0004-6361/201527130

    2016 doi

  25. [33]

    2001, Phys

    Damour, T. 2001, Phys. Rev. D, 64, 124013, 10.1103/PhysRevD.64.124013

    2001 doi

  26. [34]

    E., & Mandel, I

    de Mink, S. E., & Mandel, I. 2016, Mon. Not. Roy. Astron. Soc., 460, 3545, 10.1093/mnras/stw1219

    2016 doi

  27. [35]

    2023, , 946, 16, 10.3847/1538-4357/acb5ed

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

    2023 doi

  28. [36]

    J., Stanway , E

    Eldridge , J. J., Stanway , E. R., Xiao , L., et al. 2017, Publications of the Astronomical Society of Australia, 34, e058, 10.1017/pasa.2017.51

    2017 doi

  29. [37]

    Essick, R., & Farr, W. 2022. 2204.00461

    2022 arXiv

  30. [38]

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

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

    2024 doi

  31. [39]

    M., Stevenson, S., Coleman Miller, M., et al

    Farr, W. M., Stevenson, S., Coleman Miller, M., et al. 2017, Nature, 548, 426, 10.1038/nature23453

    2017 doi

  32. [40]

    E., & Farr, W

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

    2018 doi

  33. [41]

    2022, Astrophys

    Fishbach, M., & Kalogera, V. 2022, Astrophys. J. Lett., 929, L26, 10.3847/2041-8213/ac64a5

    2022 doi

  34. [42]

    2022, Astrophys

    Fishbach, M., Kimball, C., & Kalogera, V. 2022, Astrophys. J. Lett., 935, L26, 10.3847/2041-8213/ac86c4

    2022 doi

  35. [43]

    J., Bavera , S

    Fragos , T., Andrews , J. J., Bavera , S. S., et al. 2023, The Astrophysical Journal Supplement Series, 264, 45, 10.3847/1538-4365/ac90c1

    2023 doi

  36. [44]

    2019, Astrophys

    Fuller, J., & Ma, L. 2019, Astrophys. J. Lett., 881, L1, 10.3847/2041-8213/ab339b

    2019 doi

  37. [45]

    2021, Astrophys

    Galaudage, S., et al. 2021, Astrophys. J. Lett., 921, L15, 10.3847/2041-8213/ac2f3c

    2021 doi

  38. [46]

    2023, Nature Astron., 7, 11, 10.1038/s41550-022-01813-w

    Gamba, R., Breschi, M., Carullo, G., et al. 2023, Nature Astron., 7, 11, 10.1038/s41550-022-01813-w

    2023 doi

  39. [47]

    2022, Nature Astron., 6, 344, 10.1038/s41550-021-01568-w

    Gayathri, V., Healy, J., Lange, J., et al. 2022, Nature Astron., 6, 344, 10.1038/s41550-021-01568-w

    2022 doi

  40. [48]

    2018, Phys

    Gerosa, D., Berti, E., O'Shaughnessy, R., et al. 2018, Phys. Rev. D, 98, 084036, 10.1103/PhysRevD.98.084036

    2018 doi

  41. [49]

    2021, Nature Astron., 5, 749, 10.1038/s41550-021-01398-w

    Gerosa, D., & Fishbach, M. 2021, Nature Astron., 5, 749, 10.1038/s41550-021-01398-w

    2021 doi

  42. [50]

    2015, Phys

    Gerosa, D., Kesden, M., Sperhake, U., Berti, E., & O'Shaughnessy, R. 2015, Phys. Rev. D, 92, 064016, 10.1103/PhysRevD.92.064016

    2015 doi

  43. [51]

    2018, Mon

    Giacobbo, N., & Mapelli, M. 2018, Mon. Not. Roy. Astron. Soc., 480, 2011, 10.1093/mnras/sty1999

    2018 doi

  44. [52]

    2018, Monthly Notices of the Royal Astronomical Society, 474, 2959, 10.1093/mnras/stx2933

    Giacobbo , N., Mapelli , M., & Spera , M. 2018, Monthly Notices of the Royal Astronomical Society, 474, 2959, 10.1093/mnras/stx2933

    2018 doi

  45. [53]

    2014, Phys

    Hannam, M., Schmidt, P., Boh\'e, A., et al. 2014, Phys. Rev. Lett., 113, 151101, 10.1103/PhysRevLett.113.151101

    2014 doi

  46. [54]

    2022, Nature, 610, 652, 10.1038/s41586-022-05212-z

    Hannam, M., et al. 2022, Nature, 610, 652, 10.1038/s41586-022-05212-z

    2022 doi

  47. [55]

    2024, arXiv e-prints, arXiv:2406.16844, 10.48550/arXiv.2406.16844

    Heinzel , J., Mould , M., & Vitale , S. 2024, arXiv e-prints, arXiv:2406.16844, 10.48550/arXiv.2406.16844

    2024 doi arXiv

  48. [56]

    Hoy, C., Fairhurst, S., & Mandel, I. 2024. 2408.03410

    2024 arXiv

  49. [57]

    H., et al

    Islam, T., Vajpeyi, A., Shaik, F. H., et al. 2023. 2309.14473

    2023

  50. [58]

    Iwaya, M., Kobayashi, K., Morisaki, S., Hotokezaka, K., & Kinugawa, T. 2024. 2412.14551

    2024 arXiv

  51. [59]

    2000, Astrophys

    Kalogera, V. 2000, Astrophys. J., 541, 319, 10.1086/309400

    2000 doi

  52. [60]

    C., Kremer, K., Vanderzyden, H

    K ro g lu, F., Lombardi, J. C., Kremer, K., Vanderzyden, H. D., & Rasio, F. A. 2025, Astrophys. J. Lett., 983, L9, 10.3847/2041-8213/adc263

    2025 doi

  53. [61]

    S., Rui, N

    Kremer, K., Ye, C. S., Rui, N. Z., et al. 2020, Astrophys. J. Suppl., 247, 48, 10.3847/1538-4365/ab7919

    2020 doi

  54. [62]

    2024, Phys

    Li, Y.-J., Wang, Y.-Z., Tang, S.-P., & Fan, Y.-Z. 2024, Phys. Rev. Lett., 133, 051401, 10.1103/PhysRevLett.133.051401

    2024 doi

  55. [63]

    LVK. 2023 a , GWTC-3: Compact Binary Coalescences Observed by LIGO and Virgo During the Second Part of the Third Observing Run — Parameter estimation data release , Zenodo, 10.5281/zenodo.8177023

    2023 doi

  56. [64]

    ---. 2023 b , GWTC-3: Compact Binary Coalescences Observed by LIGO and Virgo During the Second Part of the Third Observing Run — O3 search sensitivity estimates , Zenodo, 10.5281/zenodo.7890437

    2023 doi

  57. [65]

    Mandel, I., & Broekgaarden, F. S. 2022, Living Rev. Rel., 25, 1, 10.1007/s41114-021-00034-3

    2022 doi

  58. [66]

    M., & Gair, J

    Mandel, I., Farr, W. M., & Gair, J. R. 2019, Mon. Not. Roy. Astron. Soc., 486, 1086, 10.1093/mnras/stz896

    2019 doi

  59. [67]

    2020, Proc

    Mapelli, M. 2020, Proc. Int. Sch. Phys. Fermi, 200, 87, 10.3254/ENFI200005

    2020 doi

  60. [68]

    2021, Symmetry, 13, 1678, 10.3390/sym13091678

    Mapelli, M., Santoliquido, F., Bouffanais, Y., et al. 2021, Symmetry, 13, 1678, 10.3390/sym13091678

    2021 doi

  61. [69]

    M., & Moriya, T

    Marchant, P., Langer, N., Podsiadlowski, P., Tauris, T. M., & Moriya, T. J. 2016, Astron. Astrophys., 588, A50, 10.1051/0004-6361/201628133

    2016 doi

  62. [70]

    Martinez , M. A. S., Fragione , G., Kremer , K., et al. 2020, , 903, 67, 10.3847/1538-4357/abba25

    2020 doi

  63. [71]

    McKernan, B., Ford, K. E. S., Callister, T., et al. 2022, Mon. Not. Roy. Astron. Soc., 514, 3886, 10.1093/mnras/stac1570

    2022 doi

  64. [72]

    McKernan, B., Ford, K. E. S., O'Shaughnessy, R., & Wysocki, D. 2020, Mon. Not. Roy. Astron. Soc., 494, 1203, 10.1093/mnras/staa740

    2020 doi

  65. [73]

    2018, Astrophys

    Mckernan, B., et al. 2018, Astrophys. J., 866, 66, 10.3847/1538-4357/aadae5

    2018 doi

  66. [74]

    A., & Farr, W

    Miller, S., Callister, T. A., & Farr, W. 2020, Astrophys. J., 895, 128, 10.3847/1538-4357/ab80c0

    2020 doi

  67. [75]

    J., Isi, M., Chatziioannou, K., Varma, V., & Mandel, I

    Miller, S. J., Isi, M., Chatziioannou, K., Varma, V., & Mandel, I. 2024, Phys. Rev. D, 109, 024024, 10.1103/PhysRevD.109.024024

    2024 doi

  68. [76]

    S., & Hutson, A

    Mudholkar, G. S., & Hutson, A. D. 2000, Journal of Statistical Planning and Inference, 83, 291, https://doi.org/10.1016/S0378-3758(99)00096-8

    2000 doi

  69. [77]

    2016, , 54, 441, 10.1146/annurev-astro-081915-023315

    Naoz , S. 2016, , 54, 441, 10.1146/annurev-astro-081915-023315

    2016 doi

  70. [78]

    J., Vigna-G\'omez, A., Stevenson, S., et al

    Neijssel, C. J., Vigna-G\'omez, A., Stevenson, S., et al. 2019, Mon. Not. Roy. Astron. Soc., 490, 3740, 10.1093/mnras/stz2840

    2019 doi

  71. [79]

    2022, Phys

    Payne, E., Hourihane, S., Golomb, J., et al. 2022, Phys. Rev. D, 106, 104017, 10.1103/PhysRevD.106.104017

    2022 doi

  72. [80]

    2024, Astron

    Pierra, G., Mastrogiovanni, S., & Perri\`es, S. 2024, Astron. Astrophys., 692, A80, 10.1051/0004-6361/202452545

    2024 doi

  73. [81]

    2008, Physical Review D, 78, 044021, 10.1103/PhysRevD.78.044021

    Racine, E. 2008, Physical Review D, 78, 044021, 10.1103/PhysRevD.78.044021

    2008 doi

  74. [82]

    Ray, A., Maga\ na Hernandez, I., Breivik, K., & Creighton, J. 2024. 2404.03166

    2024 arXiv

  75. [83]

    Reynolds, C. S. 2021, Ann. Rev. Astron. Astrophys., 59, 117, 10.1146/annurev-astro-112420-035022

    2021 doi

  76. [84]

    W., et al

    Riley , J., Agrawal , P., Barrett , J. W., et al. 2022, The Astrophysical Journal Supplement Series, 258, 34, 10.3847/1538-4365/ac416c

    2022 doi

  77. [85]

    L., & Antonini, F

    Rodriguez, C. L., & Antonini, F. 2018, Astrophys. J., 863, 7, 10.3847/1538-4357/aacea4

    2018 doi

  78. [86]

    L., Zevin, M., Pankow, C., Kalogera, V., & Rasio, F

    Rodriguez, C. L., Zevin, M., Pankow, C., Kalogera, V., & Rasio, F. A. 2016, Astrophys. J. Lett., 832, L2, 10.3847/2041-8205/832/1/L2

    2016 doi

  79. [87]

    M., Lasky, P

    Romero-Shaw, I. M., Lasky, P. D., Thrane, E., & Bustillo, J. C. 2020, Astrophys. J. Lett., 903, L5, 10.3847/2041-8213/abbe26

    2020 doi

  80. [88]

    S., Olsen, S., et al

    Roulet, J., Chia, H. S., Olsen, S., et al. 2021, Phys. Rev. D, 104, 083010, 10.1103/PhysRevD.104.083010

    2021 doi

  81. [89]

    2019, Monthly Notices of the Royal Astronomical Society, 484, 4216, 10.1093/mnras/stz226

    Roulet, J., & Zaldarriaga, M. 2019, Monthly Notices of the Royal Astronomical Society, 484, 4216, 10.1093/mnras/stz226

    2019 doi

  82. [90]

    2010, Physical Review D, 82, 064016, 10.1103/PhysRevD.82.064016

    Santamaría, L., Ohme, F., Ajith, P., et al. 2010, Physical Review D, 82, 064016, 10.1103/PhysRevD.82.064016

    2010 doi

  83. [91]

    2023, Physical Review D, 108, 083033, 10.1103/PhysRevD.108.083033

    Santini , A., Gerosa , D., Cotesta , R., & Berti , E. 2023, Physical Review D, 108, 083033, 10.1103/PhysRevD.108.083033

    2023 doi

  84. [92]

    2015, Phys

    Schmidt, P., Ohme, F., & Hannam, M. 2015, Phys. Rev. D, 91, 024043, 10.1103/PhysRevD.91.024043

    2015 doi

  85. [93]

    2019, Astrophys

    Secunda, A., Bellovary, J., Mac Low, M.-M., et al. 2019, Astrophys. J., 878, 85, 10.3847/1538-4357/ab20ca

    2019 doi

  86. [94]

    2020, Astrophys

    ---. 2020, Astrophys. J., 903, 133, 10.3847/1538-4357/abbc1d

    2020 doi

  87. [95]

    A., Naoz, S., & Kocsis, B

    Sedda, M. A., Naoz, S., & Kocsis, B. 2023, Universe, 9, 138, 10.3390/universe9030138

    2023 doi

  88. [96]

    2017, Astrophys

    Silsbee, K., & Tremaine, S. 2017, Astrophys. J., 836, 39, 10.3847/1538-4357/aa5729

    2017 doi

  89. [97]

    Speagle , J. S. 2020, , 493, 3132, 10.1093/mnras/staa278

    2020 doi

  90. [98]

    2022, SEVN: Stellar EVolution for N-body , Astrophysics Source Code Library, record ascl:2206.019

    Spera , M., Mapelli , M., & Bressan , A. 2022, SEVN: Stellar EVolution for N-body , Astrophysics Source Code Library, record ascl:2206.019

    2022

  91. [99]

    Spruit, H. C. 2002, Astron. Astrophys., 381, 923, 10.1051/0004-6361:20011465

    2002 doi

  92. [100]

    Stevenson, S., Berry, C. P. L., & Mandel, I. 2017 a , Mon. Not. Roy. Astron. Soc., 471, 2801, 10.1093/mnras/stx1764

    2017 doi

  93. [101]

    2017 b , Nature Commun., 8, 14906, 10.1038/ncomms14906

    Stevenson, S., Vigna-G\'omez, A., Mandel, I., et al. 2017 b , Nature Commun., 8, 14906, 10.1038/ncomms14906

    2017 doi

  94. [102]

    2020 a , Astrophys

    Tagawa, H., Haiman, Z., Bartos, I., & Kocsis, B. 2020 a , Astrophys. J., 899, 26, 10.3847/1538-4357/aba2cc

    2020 doi

  95. [103]

    2020 b , Astrophys

    Tagawa, H., Haiman, Z., & Kocsis, B. 2020 b , Astrophys. J., 898, 25, 10.3847/1538-4357/ab9b8c

    2020 doi

  96. [104]

    2023, Mon

    Talbot, C., & Golomb, J. 2023, Mon. Not. Roy. Astron. Soc., 526, 3495, 10.1093/mnras/stad2968

    2023 doi

  97. [105]

    Talbot , C., Smith , R., Thrane , E., & Poole , G. B. 2019, , 100, 043030, 10.1103/PhysRevD.100.043030

    2019 doi

  98. [106]

    2017, Phys

    Talbot, C., & Thrane, E. 2017, Phys. Rev. D, 96, 023012, 10.1103/PhysRevD.96.023012

    2017 doi

  99. [107]

    2018, Astrophys

    ---. 2018, Astrophys. J., 856, 173, 10.3847/1538-4357/aab34c

    2018 doi

  100. [108]

    2019, Publications of the Astronomical Society of Australia, 36, 10.1017/pasa.2019.2

    Thrane, E., & Talbot, C. 2019, Publications of the Astronomical Society of Australia, 36, 10.1017/pasa.2019.2

    2019 doi

  101. [109]

    2022, Phys

    Tong, H., Galaudage, S., & Thrane, E. 2022, Phys. Rev. D, 106, 103019, 10.1103/PhysRevD.106.103019

    2022 doi

  102. [110]

    2024, arXiv e-prints, arXiv:2409.03912, 10.48550/arXiv.2409.03912

    Udall , R., Hourihane , S., Miller , S., et al. 2024, arXiv e-prints, arXiv:2409.03912, 10.48550/arXiv.2409.03912

    2024 doi arXiv

  103. [111]

    van den Heuvel, E. P. J., Portegies Zwart, S. F., & de Mink, S. E. 2017, Mon. Not. Roy. Astron. Soc., 471, 4256, 10.1093/mnras/stx1430

    2017 doi

  104. [112]

    2022, Astron

    Vitale, S., Biscoveanu, S., & Talbot, C. 2022, Astron. Astrophys., 668, L2, 10.1051/0004-6361/202245084

    2022 doi

  105. [113]

    M., & Taylor, S

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

    2020 doi

  106. [114]

    2017, Class

    Vitale, S., Lynch, R., Sturani, R., & Graff, P. 2017, Class. Quant. Grav., 34, 03LT01, 10.1088/1361-6382/aa552e

    2017 doi

  107. [115]

    2021, Astrophys

    Wang, Y.-H., McKernan, B., Ford, S., et al. 2021, Astrophys. J. Lett., 923, L23, 10.3847/2041-8213/ac400a

    2021 doi

  108. [116]

    Wong, K. W. K., Breivik, K., Kremer, K., & Callister, T. 2021, Phys. Rev. D, 103, 083021, 10.1103/PhysRevD.103.083021

    2021 doi

  109. [117]

    2019, Physical Review Letters, 123, 181101, 10.1103/PhysRevLett.123.181101

    Yang , Y., Bartos , I., Gayathri , V., et al. 2019, Physical Review Letters, 123, 181101, 10.1103/PhysRevLett.123.181101

    2019 doi

  110. [118]

    S., Berry, C

    Zevin, M., Bavera, S. S., Berry, C. P. L., et al. 2021, Astrophys. J., 910, 152, 10.3847/1538-4357/abe40e

    2021 doi

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