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A data-driven decomposition of GWTC-4 shows that the 35 solar-mass peak is produced by one subpopulation of equal-mass, isotropically spinning binaries, and that this subpopulation can be entirely assembled in globular clusters with black h

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2026-08-03 19:50 UTC pith:FVPRRSES

load-bearing objection Careful 3D BGP characterization of the 35 M_sun peak, but the exclusive-GC and merger-rate-lower-bound claims rest on a four-curve CMC grid and post-hoc subpopulation selection. the 4 major comments →

arxiv 2511.22093 v2 pith:FVPRRSES submitted 2025-11-27 astro-ph.HE astro-ph.GA

Characterizing Binary Black Hole Subpopulations in GWTC-4 with Binned Gaussian Processes: On the Origins of the 35M_(odot) Peak

Omkar Sridhar , Anarya Ray , Vicky Kalogera This is my paper
classification astro-ph.HE astro-ph.GA
keywords gravitational wavesbinary black holesGWTC-4population inferencebinned Gaussian processesglobular clusterseffective inspiral spinblack hole mass spectrum
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

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

Using a flexible, binned Gaussian-process model of the joint distribution of primary mass, mass ratio, and effective inspiral spin, this paper separates the 153 GWTC-4 events into three subpopulations and shows that only one—a population of equal-mass binaries with near-zero, isotropically oriented spins—carries the ≈35 M⊙ peak. Comparing that subpopulation to published dynamical-cluster simulations, the authors find it is fully consistent with exclusively globular-cluster assembly, provided black holes are born with spins 0.1–0.2, and they place a lower bound of 0.69^{+0.23}_{-0.33} Gpc^{-3} yr^{-1} on the globular cluster merger rate. If correct, the 30–40 M⊙ excess has a dynamical origin in dense star clusters rather than a stellar-evolution pile-up, giving a concrete, testable rate for future gravitational-wave catalogs.

Core claim

Central claim: in the joint space of primary mass, mass ratio, and effective inspiral spin, the inferred merger rate density of GWTC-4 decomposes into three subpopulations, and only one of them—spanning roughly 31.6–44.2 M⊙—carries the 35 M⊙ peak. This subpopulation is characterized by mass ratios that rail against q≈1 and a χeff distribution symmetric about zero, the signature of isotropic spin orientations. Comparing this component with published Cluster Monte Carlo simulations of first-generation globular cluster mergers, the authors find it is fully consistent at the 90% level with a purely dynamical origin, but only for black hole birth spins in the range 0.1–0.2; higher or lower birth

What carries the argument

The central object is a binned Gaussian process (BGP) merger rate density, nγ = dNγ/(dlog m1 dq dχeff dVc dts), a three-dimensional piecewise-constant model of the rate density in primary mass, mass ratio, and effective inspiral spin, regularized by a Gaussian-process prior that smooths over bins. The GP prior handles sparse regions of parameter space, and the joint posterior over rate densities and GP hyperparameters (mean, amplitude, correlation length scales) is sampled with Hamiltonian Monte Carlo. This machinery does two jobs: it reconstructs the joint distribution without imposing a parametric form, letting subpopulations emerge directly from the data; and it yields rate-density bounds

Load-bearing premise

The load-bearing premise is that the four precomputed Cluster Monte Carlo simulations—first-generation mergers with birth spins of only 0, 0.1, 0.2, and 0.5—faithfully represent the globular cluster channel, since the exclusivity and the 0.1–0.2 birth-spin constraint come from matching the data to those curves at the 90% level rather than from a posterior over cluster parameters.

What would settle it

If future, larger catalogs show the 30–40 M⊙ subpopulation's effective-spin distribution is not symmetric about zero, or its mass-ratio distribution does not rail toward q≈1, the exclusive globular cluster claim would be falsified; likewise, re-running the CMC comparison with hierarchical mergers and a continuous birth-spin grid would falsify the 0.1–0.2 constraint if no birth-spin value reproduces the inferred width.

Watch this falsifier — get emailed when new claim-graph text bears on it.

If this is right

  • If correct, the 30–40 M⊙ excess in GWTC-4 is produced predominantly by dynamically assembled binaries in globular clusters, not by a pile-up of pair-instability supernovae.
  • Black hole birth spins in the globular cluster channel would be pinned to roughly 0.1–0.2, because neither the 0, 0.1, nor 0.5 simulation reproduces the inferred effective-spin width.
  • The globular cluster merger rate is at least 0.69^{+0.23}_{-0.33} Gpc^{-3} yr^{-1}, a lower bound consistent with the range 0.2–57 Gpc^{-3} yr^{-1} spanned by theoretical predictions.
  • The other two subpopulations (low-mass and high-mass) require substantial contributions from other formation channels, so the 35 M⊙ feature is not a universal mass-spin correlation of all black hole mergers.
  • No significant mass-ratio–effective-spin correlation is required to explain the data, indicating the identified subpopulations are not an artifact of marginalizing over an underlying q–χeff correlation.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The 0.1–0.2 birth-spin window, if real, becomes a direct constraint on stellar collapse simulations; a continuous grid of natal spins would sharpen it into a posterior rather than a four-point comparison.
  • The paper's logic implies the 35 M⊙ peak may be a 'shoulder'—a roughly flat globular-cluster mass distribution falling off above ≈40 M⊙—so searches for a sharp, narrow peak at exactly 35 M⊙ may be looking for the wrong signature.
  • Because χeff only measures the projection of spins onto the orbit, measuring the precession parameter χp for events in the 30–40 M⊙ subpopulation would provide an independent test: dynamically assembled binaries should show measurable precession, whereas isolated binaries would not.
  • The three-subpopulation split is suggestive rather than model-selected, since the inference does not produce Bayesian evidences; a parametric model guided by these trends could convert the lower bound into a full posterior over globular cluster merger rate.

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

4 major / 5 minor

Summary. The paper presents a binned Gaussian-process (BGP) analysis of the joint distribution of primary mass, mass ratio, and effective spin for 153 BBH events in GWTC-4. It identifies three subpopulations: a low-mass group (5–31.6 Msun), a mid-mass group (31.6–44.2 Msun) containing the 35 Msun peak with equal-mass and isotropic-spin preferences, and a high-mass group (>44.2 Msun). The paper argues that the mid-mass subpopulation can be exclusively explained by dynamically assembled BBHs in globular clusters (GCs), specifically for black hole birth spins in 0.1–0.2, based on comparison with four fixed CMC simulation tracks. It further quotes a lower bound on the GC BBH merger rate of 0.69^{+0.23}_{-0.33} Gpc^{-3} yr^{-1}. The authors conclude that dynamical formation in GCs is a strong candidate for the 30–40 Msun excess.

Significance. If the central interpretation were fully supported, this would be an important result: a data-driven identification of a subpopulation responsible for the 35 Msun peak, with specific implications for GC formation and BH birth spins. The methodological infrastructure is a clear strength: Monte Carlo integration convergence is penalized in the likelihood (App. D), an uncorrelated injection study checks against model artifacts (App. C), an alternate binning is shown to give consistent results (App. B), and the gppop pipeline is public. These elements substantiate the non-parametric inference itself. However, the astrophysical conclusion—exclusive GC origin and the GC rate lower bound—rests on a post-hoc consistency check against a fixed, discrete set of CMC predictions, not on a statistical model comparison. As written, the gap between the inference and the astrophysical claims is the main weakness.

major comments (4)
  1. [Sec. 4 / Fig. 3] The claim that Subpopulation 2 'can exclusively comprise' GC binaries with birth spins 0.1–0.2 is supported only by comparing the inferred conditional chi_eff and q distributions to four noiseless CMC curves (birth spins 0, 0.1, 0.2, 0.5). No mixture model includes a GC fraction; there is no posterior over birth spin or over cluster population parameters; and the phrase 'fully consistent (at the 90% level of the inferred distributions)' is not defined by a quantitative statistic. At most this analysis shows that the data are consistent with one of the four tracks; it does not license an exclusivity claim. A proper model comparison, or at least an explicit Bayes factor or posterior-predictive p-value, is needed.
  2. [Sec. 4 / merger-rate lower bound] The step from the inferred binned rate in the 31.6–44.2 Msun, q>0.8, chi_eff near 0 region to a 'lower bound on the merger rate of BBHs in globular clusters' (0.69^{+0.23}_{-0.33} Gpc^{-3} yr^{-1}) is not justified. That rate is the total merger rate over all formation channels in that slice of parameter space. Without a model separating GC from field/other channels, it cannot be a lower bound on the GC channel unless one has already assumed that the region is exclusively GC—which is exactly the claim in question. The text should clarify that 0.69 is the inferred total rate in that slice, not a channel-specific rate.
  3. [Sec. 3.1 / Sec. 4] The subpopulations are defined post hoc: Subpopulation 2 is selected as the mass range (31.6–44.2 Msun), q>0.8, chi_eff near 0 because these are the signatures expected from GCs. The subsequent agreement with CMC predictions is therefore not independent confirmation. The 'more than 90% significance' statements in Sec. 3.1 are conditional posterior overlaps, not model-comparison significances, and no multiple-testing correction is applied. This weakens the evidential weight of the central claim; the analysis should be framed as exploratory, with confirmation requiring targeted parametric models (as the authors themselves note in the final paragraph).
  4. [Fig. 3 caption / Sec. 4] The CMC comparison uses only 1G+1G mergers and omits hierarchical mergers, which can be a significant fraction of GC events (as acknowledged in the same section for Subpopulation 3, Fig. 5). Without an assessment of the hierarchical-merger contribution in the 31.6–44.2 Msun range and its effect on chi_eff, the 'exclusively' claim is premature. Additionally, with only four discrete birth-spin values, the statement that birth spins are in 'the range (0.1–0.2)' is not a posterior constraint on a continuous parameter; it is a statement about two grid points. The language should be changed accordingly.
minor comments (5)
  1. [Abstract] The abstract says the subpopulation 'can exclusively comprise' GC systems, while Sec. 4 concludes the 35 Msun feature 'likely arises' from GCs; these are different epistemic claims. Please align the language.
  2. [Table 1] The notation 'log-uniform(5, 200, 23)' is not self-explanatory; clarify whether it means 23 bins log-uniformly spaced between 5 and 200 Msun, and consider listing the actual bin edges.
  3. [Sec. 3] The text says 'excluding clear population outliers' but does not specify which events or criteria were used. This matters for reproducibility and for interpreting the sample size of 153.
  4. [Fig. 2] The 'Prior' curve for the Pearson correlation coefficient is shown but the text does not explain how it is computed from the GP prior; please add a sentence of description.
  5. [References] Several DOIs appear to be placeholders (e.g., Antonini et al. 2025a, doi: 10.1103/nxnr-pdyx; Essick et al. 2025, doi: 10.1103/44x3-hv3y). These should be verified before publication.

Circularity Check

1 steps flagged

Central GC-origin claim rests on an external CMC comparison rather than a circular reduction; one internal step (defining the peak-exhibiting subpopulation around the 35 M_sun over-density) is partially definitional.

specific steps
  1. self definitional [Sec. 3.1 (subpopulation definitions) and Sec. 4 (first paragraph)]
    "Guided by the over-densities in the marginal mass-distribution, we reconstruct the conditional distribution of BBH mass-ratios given different ranges of primary mass... Subpopulation 2 contributes to the ∼35M⊙ peak in the mass distribution... By reconstructing the primary mass distributions of each subpopulation, we find that only Subpopulation 2 demonstrates the 35M⊙ peak, whereas the other two exhibit a monotonic fall off."

    Subpopulation 2's mass window (31.6–44.2 M_sun) is selected because it contains the over-density / 35 M_sun peak in the marginal m1 distribution. The later statement that only Subpopulation 2 exhibits the 35 M_sun peak is therefore partly a restatement of the bin definition rather than an independent finding. The non-trivial content—the symmetric chi_eff distribution near zero, the q distribution railing at 1, and consistency with the external CMC tracks at birth spins 0.1–0.2—does not reduce to the bin choice and carries the paper's substantive inference.

full rationale

The chain from data to population inference is self-contained and non-circular: the BGP rate-density model (Eqs. 1–2) is a flexible, data-driven three-dimensional binned inference with a GP prior, validated against uncorrelated injections (Appendix C), alternative binning (Appendix B), and Monte Carlo convergence checks (Appendix D). The central astrophysical claim—that the 35 M_sun-peak subpopulation can be exclusively GC dynamical mergers if BH birth spins are ~0.1–0.2—is tested against the fixed external CMC simulations of Rodriguez et al. (2019) / the Zevin (2020) data release; those simulations are not fitted to GWTC-4 data, so the agreement is an external consistency check rather than a self-fulfilling fit. The quoted lower bound on the GC merger rate (0.69^{+0.23}_{-0.33} Gpc^{-3} yr^{-1}) is derived conditionally from the inferred rate in the 30–40 M_sun range given the argued GC dominance; it is a logical step, not an identity with the input. The paper explicitly disclaims what it cannot do: "the sampling techniques necessitated by such complex models do not yield Bayesian evidences, which makes it difficult to rigorously ascertain how much the data prefers the existence of these specific subpopulations" and states that targeted parametric modeling / model comparison is "ongoing"; this caveat is weighed here as evidence that the subpopulation interpretation is presented as an indication, not a forced result. The only partially definitional element is the segmentation itself: Subpopulation 2's mass window is chosen from the over-density at the 35 M_sun peak, and the paper then reports that this subpopulation is the one exhibiting the peak. Because the distinctive chi_eff and q signatures and the CMC comparison are not definitional, this is a mild labeling artifact. Score 3 reflects one modest self-definitional step while the principal derivation remains independent of its inputs.

Axiom & Free-Parameter Ledger

3 free parameters · 7 axioms · 0 invented entities

The paper introduces no new entities. Its load-bearing ingredients are the per-bin rate densities plus GP hyperparameters (all inferred), and a set of modeling assumptions: Planck2015 cosmology, faithful GWTC-4 selection/injections, adequacy of the GP smoothing, representativeness of the CMC 1G+1G simulations, and the chi_eff-to-orientation interpretation.

free parameters (3)
  • Per-bin merger rate densities n_gamma = joint posterior (23 m1 bins x 16 chi_eff bins x 9 q bins, minus unphysical bins)
    Central inferred quantities; GP prior regularizes them but they are estimated from data.
  • GP hyperparameters (mean, covariance amplitude, length scales) = inferred simultaneously; priors standard normal, half-normal, log-normal
    Control smoothing of the rate-density field and affect the apparent subpopulation structure.
  • Redshift evolution parameter kappa = not stated in text
    Appears in Eq. 2; the text says the likelihood is precomputed for a given kappa but does not report whether kappa is fixed or fitted, or its value/prior.
axioms (7)
  • standard math Poisson process likelihood for an inhomogeneous Poisson population (Eq. 2) with hierarchical Bayesian inference
    Standard framework (Messenger & Veitch 2013; Mandel et al. 2019; Wysocki et al. 2019).
  • domain assumption Planck2015 cosmology used for source-frame masses and luminosity distances
    Sec. 3: 'we assume Planck2015'.
  • domain assumption GWTC-4 detection sample, injections, and selection function accurately represent the detector population; 'clear population outliers' are excluded without specification
    Sec. 3; if outliers or injection set are mis-specified, inferred rate densities shift.
  • domain assumption The binned GP prior with exponential quadratic kernel and chosen length-scale priors adequately regularizes the 3D rate field; only alternate m1 binning is checked, not alternate q or chi_eff binning
    Sec. 2, Table 1, App. B.
  • domain assumption CMC simulations from Rodriguez et al. (2019)/Zevin (2020) with 1G+1G mergers and discrete birth spins {0, 0.1, 0.2, 0.5} represent the GC dynamical formation channel
    Sec. 4, Fig. 3; the exclusivity and birth-spin conclusions depend on this.
  • domain assumption A symmetric chi_eff distribution peaking at zero is interpreted as isotropic spin orientations
    Sec. 4 and final discussion; the authors acknowledge chi_eff cannot constrain precession/misalignment.
  • domain assumption The redshift-evolution parameter kappa is fixed or inferred but unreported; conclusions may depend on its value
    Eq. 2, Sec. 2; not specified.

pith-pipeline@v1.3.0-alltime-deepseek · 19957 in / 14952 out tokens · 128302 ms · 2026-08-03T19:50:34.435530+00:00 · methodology

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read the original abstract

Understanding the astrophysical origins of binary black holes requires accurate and flexible modeling of multi-dimensional population properties. In this \textit{Letter}, using a data-driven framework based on binned Gaussian processes, we characterize the joint distribution of BBH primary masses, mass ratios, and effective inspiral spins. We identify three distinct subpopulations in the GWTC-4 sample of observations and investigate their astrophysical origins. We find that only one of the three subpopulations exhibits the $35M_{\odot}$ peak, which is characterized by a strong preference for equal mass systems and isotropic spin orientations. Our inferred distributions are consistent with a predominantly dynamical origin of this feature. By comparing with theoretical simulations, we further show that the subpopulation that exhibits the $35M_{\sun}$ peak can exclusively comprise dynamically assembled systems in globular clusters, specifically if black hole birth spins are in the range~$(0.1-0.2)$, whereas the other two subpopulations require substantial contributions from alternative formation channels. We constrain the \textit{lower bound} on the merger rate of BBHs in globular clusters to be $0.69^{+0.23}_{-0.33} \rm{Gpc}^{-3}\rm{yr}^{-1}$, which is consistent with most theoretical predictions(that can range from $0.2-57\rm{Gpc}^{-3}\rm{yr}^{-1}$ depending on modeling assumptions). We conclude that dynamical formation in globular clusters remains a strong candidate for the origin of this excess near $30-40M_{\odot}$ and that more data and targeted parametric models are necessary to rigorously establish this interpretation.

Figures

Figures reproduced from arXiv: 2511.22093 by Anarya Ray, Omkar Sridhar, Vicky Kalogera.

Figure 1
Figure 1. Figure 1: Marginal and conditional distributions of primary mass, mass-ratio and effective spin inferred from GWTC-4 for the bin choice described in [PITH_FULL_IMAGE:figures/full_fig_p005_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: The Pearson correlation coefficient posteri￾ors between effective spin and mass-ratio for three differ￾ent mass ranges, namely m1 ∈ (5.0M⊙, 31.6M⊙), m1 ∈ (31.6M⊙, 44.2M⊙) and m1 ∈ (44.2M⊙, 200M⊙), along with the same marginalized across the entire primary mass space and for the prior distribution. q − χeff correlation in the underlying population. How￾ever, given our measurement uncertainties, we do not ne… view at source ↗
Figure 3
Figure 3. Figure 3: Comparison of conditional mass-ratio and effective spin distributions for the three subpopulations with the 1G+1G component of CMC simulations (which do not include hierarchical mergers) (Rodriguez et al. 2019). The faintest to brightest lines correspond to birth spins of 0, 0.1, 0.2 and 0.5 respectively. tion peaking near χeff = 0, and a mass-ratio dis￾tribution railing against q = 1; and 3. High primary … view at source ↗
Figure 4
Figure 4. Figure 4: The mass-ratio distribution (top) and fraction of events with χeff < 0 (bottom) for the low-mass (m1 < 30M⊙) subpopulation. Next, we turn to Subpopulation 1, whose positively skewed effective spin distribution peaking away from zero implies preference towards aligned systems and non-negligible spin magnitudes. This is consistent with the predictions of isolated binary evolution (Fuller & Ma 2019; Zevin & B… view at source ↗
Figure 5
Figure 5. Figure 5: Fraction of events with q > 0.6 (top) and χeff < 0 (bottom) for the high-mass (m1 > 40M⊙) subpop￾ulation. The orange line represents all hierarchical mergers from the simulations of Rodriguez et al. (2019), with the models corresponding to each BH birth spin combined with equal weightage. Our findings for Subpopulation 3 are broadly consis￾tent with previous studies that have explored trends in high-mass B… view at source ↗
Figure 6
Figure 6. Figure 6: Inferred distributions highlighting the absence of support for a correlation between mass-ratio and effective spin. The top panels display 2d slices of the median merger rate density distribution obtained from GWTC-4, for the three primary mass ranges as in [PITH_FULL_IMAGE:figures/full_fig_p010_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Marginal and conditional distributions of primary mass, mass-ratio and effective spin inferred from GWTC-4 for an alternate bin choice with non-uniform primary mass bins. B. VARIATION OF BINNING CHOICE We show in [PITH_FULL_IMAGE:figures/full_fig_p011_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Marginal and conditional distributions of BBH primary mass, mass ratio and effective spin for the simulated catalog with no intrinsic correlations between the three parameters, for two different m1 bin resolutions (log uniform on top and a non-uniform choice at the bottom). from this control population to those observed in the actual LVK data, we assess whether the empirical correlations are driven by mode… view at source ↗

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Forward citations

Cited by 10 Pith papers

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  2. Reversible-jump MCMC reveals binary black hole subpopulations with distinct redshift evolution

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  3. Stable mass transfer in massive binaries leading to merging black holes

    astro-ph.SR 2025-12 conditional novelty 7.0

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  4. Revealing Four Subpopulations of Binary Black-Hole Mergers with the Fifth Gravitational-Wave Transient Catalog

    astro-ph.HE 2026-07 conditional novelty 6.0

    GWTC-5.0 black-hole mergers split into four subpopulations: a dominant ~10 solar-mass group, an unequal-mass branch, a near-equal-mass 30–35 solar-mass branch, and a rare high-mass hierarchical group.

  5. A Strongly Parametrized Mass Ratio Model for the Stable Mass Transfer Channel: a Case Study of the $10 \, \rm{M}_{\odot}$ Peak

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  6. Second-Generation Mass Peak in the Gravitational-Wave Population as a Probe of Globular Clusters

    astro-ph.HE 2026-04 unverdicted novelty 6.0

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  7. Measurement prospects for the pair-instability mass cutoff with gravitational waves

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Reference graph

Works this paper leans on

123 extracted references · 5 canonical work pages · cited by 10 Pith papers

  1. [1]

    , " * write output.state after.block = add.period write newline

    ENTRY address archivePrefix author booktitle chapter doi edition editor eprint howpublished institution journal key month number organization pages publisher school series title misctitle type volume year version url label extra.label sort.label short.list INTEGERS output.state before.all mid.sentence after.sentence after.block FUNCTION init.state.consts ...

  2. [2]

    write newline

    " write newline "" before.all 'output.state := FUNCTION format.url url empty "" new.block "" url * "" * if FUNCTION format.eprint eprint empty "" archivePrefix empty "" archivePrefix "arXiv" = new.block " " eprint * " " * new.block " " eprint * " " * if if if FUNCTION format.doi doi empty "" " " doi * " " * if FUNCTION format.pid doi empty eprint empty ur...

  3. [3]

    - [1] #1 = = ^ ^ ^ .\!\!^ d .\!\!^ h .\!\!^ m .\!\!^ s .\!\!^ @mss

    thebibliography [1] 20pt to REFERENCES 6pt =0pt -12pt 10pt plus 3pt =0pt =0pt =1pt plus 1pt =0pt =0pt -12pt =13pt plus 1pt =20pt =13pt plus 1pt \@M =10000 =-1.0em =0pt =0pt 0pt =0pt =1.0em @enumiv\@empty 10000 10000 `\.\@m \@noitemerr \@latex@warning Empty `thebibliography' environment \@ifnextchar \@reference \@latexerr Missing key on reference command E...

    2021

  4. [4]

    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

  5. [5]

    G., et al

    Abac, A. G., et al. 2025 a . 2508.18082

    Pith/arXiv arXiv 2025

  6. [6]

    ---. 2025 b . 2508.18079

    Pith/arXiv arXiv 2025

  7. [7]

    ---. 2025 c . 2508.18083

    Pith/arXiv arXiv 2025

  8. [8]

    P., et al

    Abbott, B. P., et al. 2019, Phys. Rev. X, 9, 031040, 10.1103/PhysRevX.9.031040

    doi:10.1103/physrevx.9.031040 2019

  9. [9]

    D., Abraham, S., et al

    Abbott, R., Abbott, T. D., Abraham, S., et al. 2020, The Astrophysical Journal Letters, 896, L44, 10.3847/2041-8213/ab960f

    doi:10.3847/2041-8213/ab960f 2020

  10. [10]

    2021, The Astrophysical Journal Letters, 913, L7, 10.3847/2041-8213/abe949

    ---. 2021, The Astrophysical Journal Letters, 913, L7, 10.3847/2041-8213/abe949

    doi:10.3847/2041-8213/abe949 2021

  11. [11]

    2023, Physical Review X, 13, 011048, 10.1103/PhysRevX.13.011048

    ---. 2023, Physical Review X, 13, 011048, 10.1103/PhysRevX.13.011048

    doi:10.1103/physrevx.13.011048 2023

  12. [12]

    2014, Classical and Quantum Gravity, 32, 024001, 10.1088/0264-9381/32/2/024001

    Acernese, F., Agathos, M., Agatsuma, K., et al. 2014, Classical and Quantum Gravity, 32, 024001, 10.1088/0264-9381/32/2/024001

    doi:10.1088/0264-9381/32/2/024001 2014

  13. [13]

    D., & Thrane, E

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

    doi:10.3847/2041-8213/ad2df2 2024

  14. [14]

    D., & Thrane, E

    Adamcewicz, C., Lasky, P. D., & Thrane, E. 2023, The Astrophysical Journal, 956, 63, 10.3847/1538-4357/acf763

    doi:10.3847/1538-4357/acf763 2023

  15. [15]

    Ade, P. A. R., et al. 2016, Astron. Astrophys., 594, A13, 10.1051/0004-6361/201525830

    doi:10.1051/0004-6361/201525830 2016

  16. [16]

    2021, Progress of Theoretical and Experimental Physics, 2021, 05A102, 10.1093/ptep/ptab018

    Akutsu, T., Ando, M., Arai, K., et al. 2021, Progress of Theoretical and Experimental Physics, 2021, 05A102, 10.1093/ptep/ptab018

    doi:10.1093/ptep/ptab018 2021

  17. [17]

    Alvarez-Lopez, S., Heinzel, J., Mould, M., & Vitale, S. 2025. 2506.20731

    Pith/arXiv arXiv 2025

  18. [18]

    M., & Chattopadhyay, D

    Antonini, F., Callister, T., Dosopoulou, F., Romero-Shaw, I. M., & Chattopadhyay, D. 2025 a , Phys. Rev. D, 112, 063040, 10.1103/nxnr-pdyx

    doi:10.1103/nxnr-pdyx 2025

  19. [19]

    2023, Monthly Notices of the Royal Astronomical Society, 522, 466, 10.1093/mnras/stad972

    Antonini, F., Gieles, M., Dosopoulou, F., & Chattopadhyay, D. 2023, Monthly Notices of the Royal Astronomical Society, 522, 466, 10.1093/mnras/stad972

    doi:10.1093/mnras/stad972 2023

  20. [20]

    Antonini, F., & Perets, H. B. 2012, Astrophys. J., 757, 27, 10.1088/0004-637X/757/1/27

    doi:10.1088/0004-637x/757/1/27 2012

  21. [21]

    Antonini, F., Romero-Shaw, I., Callister, T., et al. 2025 b . 2509.04637

    Pith/arXiv arXiv 2025

  22. [22]

    M., & Callister, T

    Antonini, F., Romero-Shaw, I. M., & Callister, T. 2025 c , Phys. Rev. Lett., 134, 011401, 10.1103/PhysRevLett.134.011401

    doi:10.1103/physrevlett.134.011401 2025

  23. [23]

    D., et al

    Ashton, G., Hübner, M., Lasky, P. D., et al. 2019, The Astrophysical Journal Supplement Series, 241, 27, 10.3847/1538-4365/ab06fc

    doi:10.3847/1538-4365/ab06fc 2019

  24. [24]

    Banagiri, S., Thrane, E., & Lasky, P. D. 2025. 2509.15646

    Pith/arXiv arXiv 2025

  25. [25]

    2017, Astrophys

    Bartos, I., Kocsis, B., Haiman, Z., & M \'a rka, S. 2017, Astrophys. J., 835, 165, 10.3847/1538-4357/835/2/165

    doi:10.3847/1538-4357/835/2/165 2017

  26. [26]

    2001, Astrophys

    Belczynski, K., Kalogera, V., & Bulik, T. 2001, Astrophys. J., 572, 407, 10.1086/340304

    doi:10.1086/340304 2001

  27. [27]

    2020, Astron

    Belczynski, K., et al. 2020, Astron. Astrophys., 636, A104, 10.1051/0004-6361/201936528

    doi:10.1051/0004-6361/201936528 2020

  28. [28]

    Biscoveanu, S. 2025. 2502.04278

    Pith/arXiv arXiv 2025

  29. [29]

    M., Stevance, H

    Briel, M. M., Stevance, H. F., & Eldridge, J. J. 2023, Mon. Not. Roy. Astron. Soc., 520, 5724, 10.1093/mnras/stad399

    doi:10.1093/mnras/stad399 2023

  30. [30]

    S., Stevenson, S., & Thrane, E

    Broekgaarden, F. S., Stevenson, S., & Thrane, E. 2022, Astrophys. J., 938, 45, 10.3847/1538-4357/ac8879

    doi:10.3847/1538-4357/ac8879 2022

  31. [31]

    2011, Handbook of Markov Chain Monte Carlo (Chapman and Hall/CRC), 10.1201/b10905

    Brooks, S., Gelman, A., Jones, G., & Meng, X.-L. 2011, Handbook of Markov Chain Monte Carlo (Chapman and Hall/CRC), 10.1201/b10905

    doi:10.1201/b10905 2011

  32. [32]

    A., & Farr, W

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

    doi:10.1103/physrevx.14.021005 2024

  33. [33]

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

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

    doi:10.3847/2041-8213/ac2ccc 2021

  34. [34]

    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

    doi:10.3847/2041-8213/ac847e 2022

  35. [35]

    2022, , 513, 4527, 10.1093/mnras/stac1163

    Chattopadhyay , D., Hurley , J., Stevenson , S., & Raidani , A. 2022, , 513, 4527, 10.1093/mnras/stac1163

    doi:10.1093/mnras/stac1163 2022

  36. [36]

    Chattopadhyay, D., Stegmann, J., Antonini, F., Barber, J., & Romero-Shaw, I. M. 2023, Mon. Not. Roy. Astron. Soc., 526, 4908, 10.1093/mnras/stad3048

    doi:10.1093/mnras/stad3048 2023

  37. [37]

    Q., Zevin, M., & Vitale, S

    Cheng, A. Q., Zevin, M., & Vitale, S. 2023, Astrophys. J., 955, 127, 10.3847/1538-4357/aced98

    doi:10.3847/1538-4357/aced98 2023

  38. [38]

    E., & Mandel, I

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

    doi:10.1093/mnras/stw1219 2016

  39. [39]

    N., Giacobbo, N., Mapelli, M., et al

    Di Carlo, U. N., Giacobbo, N., Mapelli, M., et al. 2019, Mon. Not. Roy. Astron. Soc., 487, 2947, 10.1093/mnras/stz1453

    doi:10.1093/mnras/stz1453 2019

  40. [40]

    N., et al

    Di Carlo, U. N., et al. 2020, Mon. Not. Roy. Astron. Soc., 498, 495, 10.1093/mnras/staa2286

    doi:10.1093/mnras/staa2286 2020

  41. [41]

    E., & Farr, B

    Doctor, Z., Wysocki, D., O’Shaughnessy, R., Holz, D. E., & Farr, B. 2020, The Astrophysical Journal, 893, 35, 10.3847/1538-4357/ab7fac

    doi:10.3847/1538-4357/ab7fac 2020

  42. [42]

    2022, The Astrophysical Journal, 926, 34, 10.3847/1538-4357/ac3978

    Essick, R., Farah, A., Galaudage, S., et al. 2022, The Astrophysical Journal, 926, 34, 10.3847/1538-4357/ac3978

    doi:10.3847/1538-4357/ac3978 2022

  43. [43]

    2022, arXiv preprint arXiv:2204.00461

    Essick, R., & Farr, W. 2022, arXiv preprint arXiv:2204.00461. 2204.00461

    Pith/arXiv arXiv 2022

  44. [44]

    2025, Phys

    Essick, R., et al. 2025, Phys. Rev. D, 112, 102001, 10.1103/44x3-hv3y

    doi:10.1103/44x3-hv3y 2025

  45. [45]

    2020, Astrophys

    Farmer, R., Renzo, M., de Mink, S., Fishbach, M., & Justham, S. 2020, Astrophys. J. Lett., 902, L36, 10.3847/2041-8213/abbadd

    doi:10.3847/2041-8213/abbadd 2020

  46. [46]

    E., Marchant, P., & Justham, S

    Farmer, R., Renzo, M., de Mink, S. E., Marchant, P., & Justham, S. 2019, The Astrophysical Journal, 887, 53, 10.3847/1538-4357/ab518b

    doi:10.3847/1538-4357/ab518b 2019

  47. [47]

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

    doi:10.3847/2515-5172/ab1d5f 2019

  48. [48]

    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

    doi:10.1038/nature23453 2017

  49. [49]

    E., & Farr, B

    Fishbach, M., Holz, D. E., & Farr, B. 2017, The Astrophysical Journal Letters, 840, L24, 10.3847/2041-8213/aa7045

    doi:10.3847/2041-8213/aa7045 2017

  50. [50]

    E., & Farr, W

    Fishbach, M., Holz, D. E., & Farr, W. M. 2018, Astrophys. J. Lett., 863, L41, 10.3847/2041-8213/aaf9a4

    work page doi:10.3847/2041-8213/aaf9a4 2018

  51. [51]

    W., & Morton, T

    Foreman-Mackey, D., Hogg, D. W., & Morton, T. D. 2014, The Astrophysical Journal, 795, 64, 10.1088/0004-637X/795/1/64

    doi:10.1088/0004-637x/795/1/64 2014

  52. [52]

    2019, Astrophys

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

    doi:10.3847/2041-8213/ab339b 2019

  53. [53]

    2017, Phys

    Gerosa, D., & Berti, E. 2017, Phys. Rev. D, 95, 124046, 10.1103/PhysRevD.95.124046

    doi:10.1103/physrevd.95.124046 2017

  54. [54]

    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

    doi:10.1038/s41550-021-01398-w 2021

  55. [55]

    2023, Cosmic Cousins: Identification of a Subpopulation of Binary Black Holes Consistent with Isolated Binary Evolution

    Godfrey, J., Edelman, B., & Farr, B. 2023, Cosmic Cousins: Identification of a Subpopulation of Binary Black Holes Consistent with Isolated Binary Evolution . 2304.01288

    Pith/arXiv arXiv 2023

  56. [56]

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

    doi:10.3847/1538-4357/ad8572 2024

  57. [57]

    2024, Phys

    Heinzel, J., Biscoveanu, S., & Vitale, S. 2024, Phys. Rev. D, 109, 103006, 10.1103/PhysRevD.109.103006

    doi:10.1103/physrevd.109.103006 2024

  58. [58]

    2025, Phys

    Heinzel, J., Mould, M., & Vitale, S. 2025, Phys. Rev. D, 111, L061305, 10.1103/PhysRevD.111.L061305

    doi:10.1103/physrevd.111.l061305 2025

  59. [59]

    Heinzel, J., & Vitale, S. 2025. 2509.07221

    Pith/arXiv arXiv 2025

  60. [60]

    D., van Son, L

    Hendriks, D. D., van Son, L. A. C., Renzo, M., Izzard, R. G., & Farmer, R. 2023, Mon. Not. Roy. Astron. Soc., 526, 4130, 10.1093/mnras/stad2857

    doi:10.1093/mnras/stad2857 2023

  61. [61]

    M., & Ray, A

    Hernandez, I. M., & Ray, A. 2024, arXiv preprint arXiv:2404.02522. https://arxiv.org/abs/2404.02522

    Pith/arXiv arXiv 2024

  62. [62]

    D., & Gelman, A

    Hoffman, M. D., & Gelman, A. 2014, Journal of Machine Learning Research, 15, 1593. https://www.jmlr.org/papers/volume15/hoffman14a/hoffman14a.pdf

    2014

  63. [63]

    2016, Phys

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

    doi:10.1103/physrevd.93.044006 2016

  64. [64]

    2016, Phys

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

    doi:10.1103/physrevd.93.044007 2016

  65. [65]

    2021, Astrophys

    Kimball, C., et al. 2021, Astrophys. J. Lett., 915, L35, 10.3847/2041-8213/ac0aef

    doi:10.3847/2041-8213/ac0aef 2021

  66. [66]

    2014, Mon

    Kinugawa, T., Inayoshi, K., Hotokezaka, K., Nakauchi, D., & Nakamura, T. 2014, Mon. Not. Roy. Astron. Soc., 442, 2963, 10.1093/mnras/stu1022

    doi:10.1093/mnras/stu1022 2014

  67. [67]

    2021 a , Mon

    Kinugawa, T., Nakamura, T., & Nakano, H. 2021 a , Mon. Not. Roy. Astron. Soc., 501, L49, 10.1093/mnrasl/slaa191

    doi:10.1093/mnrasl/slaa191 2021

  68. [68]

    2021 b , Mon

    ---. 2021 b , Mon. Not. Roy. Astron. Soc., 504, L28, 10.1093/mnrasl/slab032

    doi:10.1093/mnrasl/slab032 2021

  69. [69]

    C., Kremer, K., Vanderzyden, H

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

    doi:10.3847/2041-8213/adc263 2041

  70. [70]

    K ro g lu , F., Kremer , K., Biscoveanu , S., Gonz \'a lez Prieto , E., & Rasio , F. A. 2025a, Astrophys. J., 979, 237, 10.3847/1538-4357/ada26b

    doi:10.3847/1538-4357/ada26b

  71. [71]

    2020, Astrophys

    Kremer, K., Spera, M., Becker, D., et al. 2020, Astrophys. J., 903, 45, 10.3847/1538-4357/abb945

    doi:10.3847/1538-4357/abb945 2020

  72. [72]

    F., McMillan, S., & Hut, P

    Kulkarni, S. F., McMillan, S., & Hut, P. 1993, Nature, 364, 421, 10.1038/364421a0

    doi:10.1038/364421a0 1993

  73. [73]

    Kıroğlu, F., Kremer, K., & Rasio, F. A. 2025c, Astrophys. J. Lett., 994, L37, 10.3847/2041-8213/ae1eeb

    doi:10.3847/2041-8213/ae1eeb 2041

  74. [74]

    2025 a , Phys

    Maga \ n a Hernandez, I., & Palmese, A. 2025 a , Phys. Rev. D, 111, 083031, 10.1103/PhysRevD.111.083031

    work page doi:10.1103/physrevd.111.083031 2025

  75. [75]

    ---. 2025 b . 2508.19208

    Pith/arXiv arXiv 2025

  76. [76]

    2025, Phys

    Mahapatra, P., Chattopadhyay, D., Gupta, A., et al. 2025, Phys. Rev. D, 111, 023013, 10.1103/PhysRevD.111.023013

    doi:10.1103/physrevd.111.023013 2025

  77. [77]

    M., Colonna, A., et al

    Mandel, I., Farr, W. M., Colonna, A., et al. 2017, Monthly Notices of the Royal Astronomical Society, 465, 3254, 10.1093/mnras/stw2883

    doi:10.1093/mnras/stw2883 2017

  78. [78]

    M., & Gair, J

    Mandel, I., Farr, W. M., & Gair, J. R. 2019, Monthly Notices of the Royal Astronomical Society, 486, 1086, 10.1093/mnras/stz896

    doi:10.1093/mnras/stz896 2019

  79. [79]

    A., & Artale, M

    Mapelli, M., Bouffanais, Y., Santoliquido, F., Sedda, M. A., & Artale, M. C. 2022, Mon. Not. Roy. Astron. Soc., 511, 5797, 10.1093/mnras/stac422

    doi:10.1093/mnras/stac422 2022

  80. [80]

    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

    doi:10.1051/0004-6361/201628133 2016

Showing first 80 references.