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arxiv: 2604.25994 · v1 · submitted 2026-04-28 · 🌌 astro-ph.HE · astro-ph.GA

Recognition: unknown

Properties of black hole mergers in disks of active galactic nuclei

Hiromichi Tagawa , Zolt\'an Haiman , Bence Kocsis
Authors on Pith no claims yet

Pith reviewed 2026-05-07 15:21 UTC · model grok-4.3

classification 🌌 astro-ph.HE astro-ph.GA
keywords black hole mergersAGN accretion disksgravitational waveshierarchical mergerseffective spinmass ratioschirp massN-body simulations
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The pith

Black hole mergers in AGN disks reproduce observed mass, mass-ratio, and spin distributions when gas accretion and hierarchical mergers are included.

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

The authors run one-dimensional N-body simulations of black holes embedded in AGN gas disks, supplemented by analytical rules for how the holes accrete gas, align their spins, and merge. In the standard case the resulting population of mergers shows mass and mass-ratio ranges close to those seen in current gravitational-wave catalogs, yet both ranges shift strongly when the disk lifetime, density, or accretion efficiency changes. The data trends linking lower mass ratios to higher effective spins and higher chirp masses to higher effective spins appear once gas torques align spins and once some black holes merge repeatedly across multiple generations.

Core claim

In the fiducial model, black hole mergers in AGN disks produce mass and mass-ratio distributions similar to those observed in gravitational wave events. The most massive mergers require either efficient gas accretion onto the black holes or hierarchical mergers involving at least three generations. The negative correlation between mass ratio and effective spin, together with the positive correlation between effective spin and chirp mass, results from spin alignment driven by gas accretion combined with the high effective spins and low mass ratios produced by repeated mergers. Hierarchical mergers further account for the anticorrelation between mass ratio and the dispersion in effective spin.

What carries the argument

One-dimensional N-body simulations combined with semi-analytical prescriptions for gas accretion, spin alignment, and merger outcomes.

If this is right

  • Increasing AGN disk lifetime or density produces systematically higher-mass mergers.
  • Efficient gas accretion drives spin alignment and thereby the observed anticorrelation between mass ratio and effective spin.
  • Hierarchical mergers of three or more generations generate the highest-mass events and the positive correlation between effective spin and chirp mass.
  • Repeated mergers also produce the predicted anticorrelation between mass ratio and the dispersion of effective spin.

Where Pith is reading between the lines

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

  • If AGN disks supply a substantial fraction of mergers, the fraction of high-mass or high-spin events should rise in epochs when AGN activity is higher.
  • Future detectors sensitive to eccentricity or precession could test whether the dense-disk environment leaves measurable waveform signatures beyond the mass and spin trends already reported.
  • Adding three-dimensional orbital dynamics or resolved hydrodynamics would show whether the present matches to observations persist under more realistic conditions.

Load-bearing premise

The one-dimensional N-body approximation and the semi-analytical prescriptions for gas accretion, spin alignment, and merger outcomes capture the dominant physical processes without major omissions.

What would settle it

A large catalog of mergers showing no negative correlation between mass ratio and effective spin, or an absence of very high-mass events accompanied by low mass-ratio binaries, would contradict the reported explanation.

Figures

Figures reproduced from arXiv: 2604.25994 by Bence Kocsis, Hiromichi Tagawa, Zolt\'an Haiman.

Figure 1
Figure 1. Figure 1: The timescales and conditions characterizing the evo￾lution of 30 M⊙ BHs in AGN disks. The orange, cyan, and blue lines represent the fiducial, TQM, and SG models, respectively. In the second to fourth panels, dashed and solid lines indicate results without and with gaps, respectively. The top panel shows the cap￾ture timescale for a BH with a relative velocity equal to 0.1× the local Keplerian velocity wi… view at source ↗
Figure 2
Figure 2. Figure 2: The linearly interpolated distribution of chirp mass (top row) and the primary BH mass (bottom row) of the merging binaries for models M1–M20. For model M1 (leftmost panel), the results at t = 1 Myr–30 Myr are presented, while those at t = 3 Myr are shown for the other models (other panels). The dashed and dotted black lines represent the median and the 90% credible intervals inferred from the LVK O1–O3 da… view at source ↗
Figure 3
Figure 3. Figure 3: Similar to view at source ↗
Figure 4
Figure 4. Figure 4: The distribution of primary and secondary BH masses in mergers. To reduce Poisson noise, we performed 100 simulations. 5 4 3 2 1 0 log10 (r/pc) 10 0 10 1 10 2 10 3 d N / dlo g r M1 t = 1 Myr M1 t = 3 Myr M1 t = 10 Myr M1 t = 30 Myr 5 4 3 2 1 0 log10 (r/pc) 10 0 10 1 10 2 10 3 M2 iso, t = 3 Myr M2 iso, t = 10 Myr M3 v = 1 M4 low BH density 5 4 3 2 1 0 log10 (r/pc) 10 0 10 1 10 2 10 3 M5 BS in 2D M6 MSMBH × … view at source ↗
Figure 5
Figure 5. Figure 5: The linearly interpolated distribution of the distance from the SMBH of the mergers for models M1–M20. 5 4 3 2 1 0 log10 (r/pc) 10 0 10 1 10 2 10 3 d N / dlo g r M1 t = 3 Myr 5 4 3 2 1 0 log10 (r/pc) 10 0 10 1 10 2 10 3 M1 t = 30 Myr 5 4 3 2 1 0 log10 (r/pc) 10 0 10 1 10 2 10 3 M4 low BH density 5 4 3 2 1 0 log10 (r/pc) 10 0 10 1 10 2 10 3 M5 2D BS interactions 5 4 3 2 1 0 log10 (r/pc) 10 0 10 1 10 2 10 3 … view at source ↗
Figure 6
Figure 6. Figure 6: The distribution of the distance of mergers from the SMBH for different binary formation mechanisms in models M1, M4, M5, M13, and M15. The purple, blue, orange, red, and cyan lines represent mergers from binaries formed as primordial binaries, through gas capture processes, dynamical interactions, GW capture during single-single interactions, and GW capture mechanisms during binary-single interactions, re… view at source ↗
Figure 7
Figure 7. Figure 7: The distribution of the binary mass and their distance from the SMBH for all merging BHs in models M1, M4, M5, M13, and M15 view at source ↗
Figure 8
Figure 8. Figure 8: Similar to view at source ↗
Figure 9
Figure 9. Figure 9: Similar to view at source ↗
Figure 10
Figure 10. Figure 10: Similar to view at source ↗
Figure 11
Figure 11. Figure 11: The average and dispersion of the absolute value of the effective spin parameter as a function of the chirp mass for models M1– M20. The dashed and dotted black lines represent the median and the 90% credible intervals for the aligned spin magnitude χz, as inferred from the LVK O1–O4a data estimated in The LIGO Scientific Collaboration et al. (2025c). When the number of mergers in a bin is less than 2, we… view at source ↗
Figure 12
Figure 12. Figure 12: The average and dispersion of χeff as a function of m1 for models M1–M20. 0.00 0.25 0.50 0.75 1.00 q 0.4 0.2 0.0 0.2 0.4 X eff M1 t = 1 Myr M1 t = 3 Myr M1 t = 10 Myr M1 t = 30 Myr 0.00 0.25 0.50 0.75 1.00 q 0.4 0.2 0.0 0.2 0.4 M2 iso, t = 3 Myr M2 iso, t = 10 Myr M3 v = 1 M4 low BH density 0.00 0.25 0.50 0.75 1.00 q 0.4 0.2 0.0 0.2 0.4 M5 BS in 2D M6 MSMBH × = 10 M7 Mout = 0.1 MEdd M8 m1g 45 Msun 0.00 0.… view at source ↗
Figure 13
Figure 13. Figure 13: The average and dispersion of the effective spin parameter as a function of the mass ratio for models M1–M20. The three black lines represent 50%, 90%, and 99% credible regions inferred from the LVK O1–O4a data estimated using the LINEAR model in The LIGO Scientific Collaboration et al. (2025c) view at source ↗
Figure 14
Figure 14. Figure 14: Same as view at source ↗
Figure 15
Figure 15. Figure 15: The linearly interpolated distribution of the orbital eccentricity of merging binaries for models M1–M20. 0 5 10 15 N1 0 2 4 6 8 10 N 2 M1 t = 3 Myr 0 5 10 15 N1 M1 t = 10 Myr 0 5 10 15 N1 M8 m1g 45 Msun 0 5 10 15 N1 M17 s = 0.5 0 5 10 15 N1 M19 ZEBRA 0 5 10 15 N1 M20 ZEBRA factive = 0.1 10 0 10 1 10 2 N view at source ↗
Figure 16
Figure 16. Figure 16: The distribution of the number of generations composing the primary and secondary BHs in mergers among massive BHs (m1 ≥ 100 M⊙ and m2 ≥ 50 M⊙). To reduce Poisson noise, we performed 100 simulations. 1 0 1 eff 10 0 10 1 10 2 d N / d eff M1 t = 1 Myr M1 t = 3 Myr M1 t = 10 Myr M1 t = 30 Myr 1 0 1 eff 10 0 10 1 10 2 M2 iso, t = 3 Myr M2 iso, t = 10 Myr M3 v = 1 M4 low BH density 1 0 1 eff 10 0 10 1 10 2 M5 … view at source ↗
Figure 17
Figure 17. Figure 17: The linearly interpolated distribution of χeff for mergers among massive BHs. paramerters are: m1 = 85+21 −14 M⊙, m2 = 66+17 −18 M⊙, χeff = 0.08+0.27 −0.36, χp = 0.68+0.25 −0.37, a1 = 0.69+0.27 −0.62, and a2 = 0.73+0.24 −0.64. For GW231123 (Abac et al. 2025a), the parameters are: m1 = 137+22 −17 M⊙, m2 = 103+20 −52 M⊙, χeff = 0.31+0.24 −0.39, χp = 0.77+0.17 −0.19, a1 = 0.90+0.10 −0.19, and a2 = 0.80+0.20 … view at source ↗
Figure 18
Figure 18. Figure 18: The linearly interpolated distribution of χp for mergers among massive BHs. 0.0 0.5 1.0 a 10 0 10 1 10 2 d N / d a M1 t = 1 Myr M1 t = 3 Myr M1 t = 10 Myr M1 t = 30 Myr 0.0 0.5 1.0 a 10 0 10 1 10 2 M2 iso, t = 3 Myr M2 iso, t = 10 Myr M3 v = 1 M4 low BH density 0.0 0.5 1.0 a 10 0 10 1 10 2 M5 BS in 2D M6 MSMBH × = 10 M7 Mout = 0.1 MEdd M8 m1g 45 Msun 0.0 0.5 1.0 a 10 0 10 1 10 2 M9 no migration M10 therma… view at source ↗
Figure 19
Figure 19. Figure 19: The linearly interpolated distribution of the spin magnitude of merging binaries composed of massive BHs. Solid and dashed lines represent distributions of the spin magnitudes of the primary and secondary BHs, respectively. 5 4 3 2 1 0 log10 (r/pc) 10 0 10 1 10 2 d N / dlo g r M1 t = 1 Myr M1 t = 3 Myr M1 t = 10 Myr M1 t = 30 Myr 5 4 3 2 1 0 log10 (r/pc) 10 0 10 1 10 2 M2 iso, t = 3 Myr M2 iso, t = 10 Myr… view at source ↗
Figure 20
Figure 20. Figure 20: The linearly interpolated distribution of the distance from the SMBH of the mergers among massive BHs view at source ↗
read the original abstract

Ground-based gravitational wave (GW) observatories have detected approximately 200 binary black hole (BH) mergers. The astrophysical origin of these events are debated, with evidence suggesting that at least a subset originated from dynamic environments characterized by frequent close encounters. Accretion disks in active galactic nuclei (AGNs) are of particular interest, as certain observed features could be more readily produced within such environments. In this paper, we investigate the expected properties of mergers in these environments, and their dependence on various parameters, using one-dimensional $N$-body simulations combined with a comprehensive semi-analytical model. In our fiducial model, the distributions of masses and mass ratios ($q$) are similar to those observed. However, they depend strongly on the lifetime and density of the AGN disk and on the number and accretion efficiency of BHs, with higher masses predicted as these quantities increase. The most massive mergers, such as GW231123, can be produced either by efficient gas accretion or by hierarchical mergers among $\geq 3$ generations of BHs. The observed negative correlation between $q$ and the average effective spin ($\chi_{\rm eff}$), along with the positive correlation between $\chi_{\rm eff}$ and the chirp mass ($M_{\rm chirp}$), can be explained by a combination of efficient gas accretion, which promotes spin alignment, and hierarchical mergers, which produce high-$|\chi_{\rm eff}|$ and low-$q$ binaries. Hierarchical mergers can also explain the negative correlation between $q$ and the dispersion of $\chi_{\rm eff}$, as well as the positive correlation between $|\chi_{\rm eff}|$ and $M_{\rm chirp}$. We present a comprehensive study on how the expected distribution of each of these quantities depends on model parameters and assumptions, which will aid the interpretation of observed GW population properties.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

3 major / 2 minor

Summary. The paper uses one-dimensional N-body simulations combined with semi-analytical modeling of gas accretion, spin evolution, and merger outcomes to study black hole binary mergers in AGN disks. In the fiducial model, the resulting black hole mass and mass-ratio (q) distributions are reported to be similar to those observed in GW events. The authors argue that the observed negative correlation between q and effective spin χ_eff, the positive correlation between χ_eff and chirp mass M_chirp, and related trends in |χ_eff| and q can be reproduced by efficient gas accretion (promoting spin alignment) together with hierarchical mergers (producing high-|χ_eff| low-q systems). All reported distributions depend strongly on AGN disk lifetime, density, number of BHs, and accretion efficiency; the most massive events can arise either from prolonged accretion or from ≥3-generation hierarchical mergers.

Significance. If the modeling framework is shown to be robust, the work supplies a concrete mechanism within the AGN channel for several correlations seen in the current GW catalog that are not easily produced by isolated binary evolution. The parameter survey is useful for mapping how disk properties translate into observable population statistics and for guiding future comparisons with LIGO/Virgo/KAGRA data releases.

major comments (3)
  1. [§2 and §3] §2 (Methods) and §3 (fiducial model): The central claim that the reported q–χ_eff and χ_eff–M_chirp correlations are explained by gas accretion plus hierarchical mergers rests on the 1D N-body plus semi-analytical prescriptions. No direct comparison to 2D/3D hydrodynamical or full 3D N-body benchmarks is presented; vertical structure, inclinations, and 3D scattering could systematically alter migration timescales and encounter rates, thereby shifting the predicted correlations. A quantitative assessment of this uncertainty is required before the correlations can be regarded as robust predictions.
  2. [§4] §4 (parameter dependence): The abstract and results state that mass and q distributions depend strongly on disk lifetime, density, BH number, and accretion efficiency. It is therefore essential to demonstrate that the negative q–χ_eff correlation and positive χ_eff–M_chirp correlation persist across a representative range of these parameters rather than appearing only in the single fiducial run; otherwise the explanatory power for the observed trends is limited.
  3. [§5] §5 (hierarchical mergers and GW231123): The claim that the most massive events can be produced either by efficient accretion or by ≥3-generation mergers is plausible but requires explicit quantification of the relative fractions and the parameter boundaries separating the two channels; without this, it remains unclear which mechanism dominates under realistic AGN conditions.
minor comments (2)
  1. [Figures] Figure captions should explicitly list the parameter values (lifetime, density, accretion efficiency, BH number) used for each panel to allow readers to connect trends to the parameter study.
  2. [Notation] Ensure consistent notation for χ_eff (including the absolute-value version |χ_eff|) and M_chirp throughout the text and figures.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for their constructive and detailed comments, which have helped clarify the strengths and limitations of our modeling approach. We address each major comment point by point below, indicating where revisions will be made to the manuscript.

read point-by-point responses

  1. Referee: [§2 and §3] §2 (Methods) and §3 (fiducial model): The central claim that the reported q–χ_eff and χ_eff–M_chirp correlations are explained by gas accretion plus hierarchical mergers rests on the 1D N-body plus semi-analytical prescriptions. No direct comparison to 2D/3D hydrodynamical or full 3D N-body benchmarks is presented; vertical structure, inclinations, and 3D scattering could systematically alter migration timescales and encounter rates, thereby shifting the predicted correlations. A quantitative assessment of this uncertainty is required before the correlations can be regarded as robust predictions.

    Authors: We agree that higher-dimensional effects represent a source of systematic uncertainty not directly quantified in the current work. Our 1D N-body framework was chosen to enable efficient exploration of a wide parameter space over long timescales, which remains computationally prohibitive in 3D for the BH populations considered. We will revise §2 to expand the discussion of model assumptions, citing literature on 1D vs. 3D migration and scattering rates in AGN disks that support the timescales adopted. A full quantitative benchmark against new 3D simulations is beyond the scope of this paper but will be noted as a limitation and direction for future work. This is a partial revision emphasizing transparency. revision: partial

  2. Referee: [§4] §4 (parameter dependence): The abstract and results state that mass and q distributions depend strongly on disk lifetime, density, BH number, and accretion efficiency. It is therefore essential to demonstrate that the negative q–χ_eff correlation and positive χ_eff–M_chirp correlation persist across a representative range of these parameters rather than appearing only in the single fiducial run; otherwise the explanatory power for the observed trends is limited.

    Authors: Section 4 already varies disk lifetime, density, BH number, and accretion efficiency, showing the resulting shifts in mass and q distributions. To strengthen the claim, we will revise this section to explicitly verify and report that the q–χ_eff and χ_eff–M_chirp correlations remain present (with similar signs and strengths) across the explored parameter grid. This will include additional summary statistics or supplementary figures for non-fiducial cases. We agree this improves the robustness of the interpretation. revision: yes

  3. Referee: [§5] §5 (hierarchical mergers and GW231123): The claim that the most massive events can be produced either by efficient accretion or by ≥3-generation mergers is plausible but requires explicit quantification of the relative fractions and the parameter boundaries separating the two channels; without this, it remains unclear which mechanism dominates under realistic AGN conditions.

    Authors: We will revise §5 to include the requested quantification. Post-processing the existing simulation outputs, we will report the relative fractions of the most massive mergers arising from prolonged accretion versus ≥3-generation hierarchical mergers, along with the critical boundaries in disk lifetime, density, and accretion efficiency that separate the two channels. These will be presented for both the fiducial model and selected variations to clarify dominance under different AGN conditions. revision: yes

Circularity Check

0 steps flagged

No circularity: simulation outputs depend on varied parameters without algebraic reduction to inputs or self-citation chains.

full rationale

The paper runs 1D N-body simulations plus semi-analytical prescriptions for accretion, spin evolution, and mergers, then varies disk lifetime, density, BH number, and accretion efficiency to map how mass, q, and χ_eff distributions change. Observed correlations are presented as emergent from efficient accretion plus hierarchical mergers within those runs. No equation or result is shown to equal its own fitted input by construction, no uniqueness theorem is imported from prior self-work to force the model, and no renaming of known patterns occurs. The approach is parameter exploration against external GW data, not a closed deductive loop.

Axiom & Free-Parameter Ledger

4 free parameters · 2 axioms · 0 invented entities

Model depends on several tunable quantities for the AGN disk and black-hole population that are not derived from first principles.

free parameters (4)
  • AGN disk lifetime
    Controls mass distributions; varied to produce higher-mass mergers.
  • AGN disk density
    Affects encounter rates and accretion; varied to change merger properties.
  • Number of black holes
    Influences hierarchical merger probability.
  • Accretion efficiency
    Determines mass growth and spin alignment; key for high-mass events and correlations.
axioms (2)
  • domain assumption One-dimensional N-body dynamics capture black-hole orbital evolution and encounters inside the disk.
    Basis for all simulations; 3D effects neglected.
  • domain assumption Semi-analytical prescriptions for gas accretion, spin evolution, and mergers are accurate.
    Required to produce reported mass and spin distributions.

pith-pipeline@v0.9.0 · 9006 in / 1307 out tokens · 106585 ms · 2026-05-07T15:21:12.759834+00:00 · methodology

discussion (0)

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Reference graph

Works this paper leans on

15 extracted references · 12 canonical work pages · 3 internal anchors

  1. [1]

    J., & Heggie, D

    Aarseth, S. J., & Heggie, D. C. 1976, A&A, 53,

    1976

  2. [2]

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

    http://adsabs.harvard.edu/abs/1976A%26A....53..259A Abac, A. G., Abouelfettouh, I., Acernese, F., et al. 2025a, ApJL, 993, L25, doi:10.3847/2041-8213/ae0c9c —. 2025b, ApJL, 993, L21, doi:10.3847/2041-8213/ae0d54 Abbott, R., Abbott, T. D., Abraham, S., et al. 2020, Phys. Rev. Lett., 125, 101102, doi:10.1103/PhysRevLett.125.101102 Acernese, F., Agathos, M.,...

    work page doi:10.3847/2041-8213/ae0c9c 2041

  3. [3]

    & Olejak, A

    http://adsabs.harvard.edu/abs/2017MNRAS.467..524B Banerjee, S., & Olejak, A. 2024, arXiv e-prints, arXiv:2411.15112, doi:10.48550/arXiv.2411.15112 Barausse, E., Morozova, V., & Rezzolla, L. 2012, ApJ, 758, 63, doi:10.1088/0004-637X/758/1/63 Bartos, I., & Haiman, Z. 2026, ApJL, 996, L44, doi:10.3847/2041-8213/ae2bff Bartos, I., Haiman, Z., Marka, Z., et al...

    work page doi:10.48550/arxiv.2411.15112 2024

  4. [4]

    R., & Lin, D

    http://adsabs.harvard.edu/abs/2016Natur.534..512B Bell, K. R., & Lin, D. N. C. 1994, ApJ, 427,

    1994

  5. [5]

    M., Mac Low, M.-M., McKernan, B., & Ford, K

    http://adsabs.harvard.edu/abs/1994ApJ...427..987B Bellovary, J. M., Mac Low, M.-M., McKernan, B., & Ford, K. E. S. 2016, ApJL, 819, L17, doi:10.3847/2041-8205/819/2/L17 Binney, J., & Tremaine, S. 2008, Galactic Dynamics (2nd ed.; Princeton, NJ; Princeton Univ. Press). http://adsabs.harvard.edu/abs/2008gady.book.....B Blandford, R. D., & Begelman, M. C. 19...

    work page doi:10.3847/2041-8205/819/2/l17 2016

  6. [6]

    The steep redshift evolution of the hierarchical binary black hole merger rate may cause the $z$-$\chi_{\rm eff}$ correlation

    http://adsabs.harvard.edu/abs/2012ApJ...759...52D Duffell, P. C., Haiman, Z., MacFadyen, A. I., D’Orazio, D. J., & Farris, B. D. 2014, ApJL, 792, L10. http://adsabs.harvard.edu/abs/2014ApJ...792L..10D BH Mergers in AGNs21 Epstein-Martin, M., Tagawa, H., Haiman, Z., & Perna, R. 2025, MNRAS, 537, 3396, doi:10.1093/mnras/staf237 Fabj, G., Tiede, C., Rowan, C...

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.1093/mnras/staf237 2014

  7. [7]

    2023, NatAs, 7, 11, doi: 10.1038/s41550-022-01813-w

    http://adsabs.harvard.edu/abs/2006ApJ...649...91F Gamba, R., Breschi, M., Carullo, G., et al. 2023, Nat. Astron., 7, 11, doi:10.1038/s41550-022-01813-w Gangardt, D., Trani, A. A., Bonnerot, C., & Gerosa, D. 2024, MNRAS, 530, 3689, doi:10.1093/mnras/stae1117 Gayathri, V., Yang, Y., Tagawa, H., Haiman, Z., & Bartos, I. 2021, ApJL, 920, L42, doi:10.3847/2041...

    work page doi:10.1038/s41550-022-01813-w 2023

  8. [8]

    2022, MNRAS, 515, 3299, doi:10.1093/mnras/stac1985 Goodman, J., & Tan, J

    http://adsabs.harvard.edu/abs/2002Natur.420..643G Gond´ an, L., & Kocsis, B. 2022, MNRAS, 515, 3299, doi:10.1093/mnras/stac1985 Goodman, J., & Tan, J. C. 2004, ApJ, 608, 108, doi:10.1086/386360 Gottlieb, O., Metzger, B. D., Issa, D., et al. 2025, ApJL, 993, L54, doi:10.3847/2041-8213/ae0d81 Goyal, S., Villarrubia-Rojo, H., & Zumalacarregui, M. 2025, arXiv...

    work page doi:10.1093/mnras/stac1985 2022

  9. [9]

    Masers and Broad-Line Mapping Favor Magnetically-Dominated AGN Accretion Disks

    http://adsabs.harvard.edu/abs/2018ApJ...856..140H Hopkins, P. F., Baron, D., & Piotrowska, J. M. 2026, arXiv e-prints, arXiv:2601.06253, doi:10.48550/arXiv.2601.06253 Hopkins, P. F., Grudic, M. Y., Su, K.-Y., et al. 2024, The Open Journal of Astrophysics, 7, 18, doi:10.21105/astro.2309.13115 Hopman, C., & Alexander, T. 2006, ApJL, 645, L133. http://adsabs...

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.48550/arxiv.2601.06253 2026

  10. [10]

    S., Rui, N

    http://adsabs.harvard.edu/abs/2014MNRAS.442.2963K Kremer, K., Ye, C. S., Rui, N. Z., et al. 2020, Astrophys. J. Supp. S., 247, 48, doi:10.3847/1538-4365/ab7919 Kumamoto, J., Fujii, M. S., & Tanikawa, A. 2019, MNRAS, 486, 3942, doi:10.1093/mnras/stz1068 Leigh, N. W. C., Geller, A. M., McKernan, B., et al. 2018, MNRAS, 474, 5672, doi:10.1093/mnras/stx3134 L...

    work page doi:10.3847/1538-4365/ab7919 2020

  11. [11]

    http://adsabs.harvard.edu/abs/2004cbhg.symp..169M Masset, F. S. 2017, MNRAS, 472, 4204, doi:10.1093/mnras/stx2271 McKernan, B., & Ford, K. E. S. 2024, MNRAS, 531, 3479, doi:10.1093/mnras/stae1351 McKernan, B., Ford, K. E. S., Callister, T., et al. 2022, MNRAS, 514, 3886, doi:10.1093/mnras/stac1570 McKernan, B., Ford, K. E. S., O’Shaugnessy, R., & Wysocki,...

    work page doi:10.1093/mnras/stx2271 2017

  12. [12]

    L., & Haiman, Z

    http://adsabs.harvard.edu/abs/2007MNRAS.379...21N O’Leary, R. M., Kocsis, B., & Loeb, A. 2009, MNRAS, 395, 2127, doi:10.1111/j.1365-2966.2009.14653.x O’Leary, R. M., Meiron, Y., & Kocsis, B. 2016, ApJL, 824, L12, doi:10.3847/2041-8205/824/1/L12 Olejak, A., Klencki, J., Xu, X.-T., et al. 2024, A&A, 689, A305, doi:10.1051/0004-6361/202450480 22et al. Ostrik...

    work page doi:10.1111/j.1365-2966.2009.14653.x 2009

  13. [13]

    GW231123: A Case for Binary Microlensing in a Strong Lensing Field,

    http://adsabs.harvard.edu/abs/1973A%26A....24..337S Shan, X., Yang, H., & Mao, S. 2025, arXiv e-prints, arXiv:2512.19118, doi:10.48550/arXiv.2512.19118 Silsbee, K., & Tremaine, S. 2017, ApJ, 836,

    work page doi:10.48550/arxiv.2512.19118 2025

  14. [14]

    2003, MNRAS, 341,

    http://adsabs.harvard.edu/abs/2017ApJ...836...39S Sirko, E., & Goodman, J. 2003, MNRAS, 341,

    2003

  15. [15]

    Electromagnetic Flares from Compact-Object Mergers in AGN Disks: Signatures and Predictions

    http://adsabs.harvard.edu/abs/2003MNRAS.341..501S Spera, M., Mapelli, M., Giacobbo, N., et al. 2019, MNRAS, 485, 889, doi:10.1093/mnras/stz359 Stegmann, J., Olejak, A., & de Mink, S. E. 2025, ApJL, 992, L26, doi:10.3847/2041-8213/ae0e5f Stone, N. C., Metzger, B. D., & Haiman, Z. 2017, MNRAS, 464, 946.http://adsabs.harvard.edu/abs/2017MNRAS.464..946S Syer,...

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.1093/mnras/stz359 2019