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Continuum Reverberation Mapping of Accretion Disks Surrounding Supermassive Black Hole Binaries: Observational Signatures

T0 review · 3 major / 4 minor · reviewed 2026-08-06 · deepseek-v4-flash

Pith's one-line read The low-density cavity opened by a binary black hole's tidal torque imprints a measurable break on the inter-band continuum lag relation, offering a new electromagnetic route to identifying sub-parsec supermassive black hole binaries.

desk verdict The paper has a genuinely new forward model predicting a flat-to-λ^(4/3) break in τ(λ) for SMBHBs, but the PG1302-102 data do not yet discriminate it from single-disk alternatives. read the letter →

arxiv 2507.21671 v2 pith:3VYQJFHB submitted 2025-07-29 astro-ph.GA astro-ph.HE

classification astro-ph.GAastro-ph.HE
keywords supermassiveblackholebinariescontinuumreverberationmappingaccretiondiskcavityinter-bandtimelagslamp-postreprocessingcircumbinarytransferfunctionPG1302-102
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

This paper proposes that the low-density cavity between the two mini-disks and the circumbinary disk of a supermassive black hole binary leaves a distinctive fingerprint in continuum reverberation mapping: the inter-band time-lag–wavelength relation is flat at short wavelengths, where the tidally truncated mini-disk dominates, and then breaks into the familiar $\lambda^{4/3}$ power law at long wavelengths, where the circumbinary disk dominates. The signature is distinct from the single smooth $\lambda^{4/3}$ relation of a standard disk around a single black hole, and the transition wavelength typically lands in the UV/optical bands for binaries with total mass near $10^8\,M_\odot$ and orbital periods of a few years. The authors construct a simple lamp-post reverberation model, compute the resulting bimodal transfer functions, and show that for the candidate PG 1302-102 the model reproduces the measured inter-band lags while the inferred total mass and orbital period agree with independent estimates. If the claim holds, multi-band time-domain surveys gain a new handle on sub-parsec black hole binaries that are otherwise hard to distinguish from single black holes.

What carries the argument

The central object is the responsivity-weighted transfer function $\psi(\lambda,\tau)$, which gives the contribution of each disk surface element to the observed flux variation as a function of time delay and wavelength (Equation 16). For a single lamp-post corona above the secondary black hole, $\psi$ is bimodal: a short-lag bump from the mini-disk truncated at $r_{\rm out,s}=\xi r_{\rm R,s}$ (a fraction $\xi$ of the Roche lobe) and a long-lag bump from the circumbinary disk with inner edge $r_{\rm in,c}\approx a_B/(1+q)+r_{\rm H,s}$, separated by the null response of the cavity. Convolving $\psi$ with the auto-correlation function of the driving light curve converts the bimodal response into measurable peak and centroid time lags, and the break wavelength is approximately $\lambda_{\rm tran}\approx 2700\,f^{-1/4}(M_t/10^8\,M_\odot)^{1/4}(\dot{m}_c/0.1)^{-1/4}(a_B/100\,R_{g,t})^{3/4}$ Å, set by the temperature at the inner edge of the circumbinary disk.

What would settle it

From high-cadence, multi-band light curves of a confirmed or candidate binary such as PG 1302-102, measure the continuum transfer function directly, or use frequency-resolved lags: if the response is a single smooth bump with no null region near the light-crossing time of the Hill radius, or if the $\tau(\lambda)$ relation is a single $\lambda^{4/3}$ power law with no break between roughly 3000 and 5000 Å, the central claim is falsified.

Watch

Extended reading notes

Core claim

The paper's central claim is that the cavity—a gas-depleted region between the tidally truncated mini-disk around the secondary black hole and the circumbinary disk—imprints a distinguishable break on the continuum reverberation signal of a low-mass-ratio supermassive black hole binary. In this picture the responsivity-weighted transfer function is bimodal: a narrow short-lag bump from the mini-disk, whose outer edge is set by a fraction of the Roche lobe, plus a broad long-lag bump from the circumbinary disk, whose inner edge is set by the Hill radius, with a null-response gap from the cavity in between. The measurable consequence is that the $\tau(\lambda)$ relation is flat at short wavelengths and then transitions to the canonical $\lambda^{4/3}$ power law, with the break wavelength set by the characteristic temperature at the inner edge of the circumbinary disk. Applying the model to the intensive multiwavelength monitoring data of the SMBHB candidate PG 1302-102, the authors find that the SMBHB model reproduces the measured inter-band time lags and yields an inferred total mass and orbital period consistent with independent estimates, while the current data cannot yet discriminate the SMBHB scenario from single-disk power-law models.

Load-bearing premise

The signature rests on the assumption that a single, stationary X-ray lamp-post above the secondary black hole drives the continuum variability of both the mini-disk and the circumbinary disk; if the UV/optical variations instead come from intrinsic accretion-rate fluctuations or from two separate coronae, the predicted bimodal transfer function and the flat-then-steep break in the lag relation need not appear.

Editorial extensions

If this is right

  • Multi-band continuum reverberation campaigns can flag SMBHB candidates by finding lag relations that are flat at short wavelengths and then break to roughly $\lambda^{4/3}$, instead of a single smooth power law.
  • Fitting the full $\tau(\lambda)$ relation yields binary parameters, including total mass, orbital period, and the truncation radius of the mini-disk, that can be cross-checked against optical periodicity searches and virial mass estimates, as demonstrated for PG 1302-102.
  • Because the break wavelength falls in the UV/optical bands for total masses above about $10^8\,M_\odot$ with orbital periods of a few years, the signature is most accessible for the massive, short-period binaries that are also promising nano-hertz gravitational wave sources.
  • The inferred mini-disk truncation of roughly 100 gravitational radii (about a tenth of the Roche lobe) for PG 1302-102 matches the expectation that tidal torques truncate the mini-disk well inside its Roche lobe.
  • With improved sampling and precision, directly inferring the transfer function from light curves would reveal the predicted bimodal shape, which is the clearest discriminant between the SMBHB geometry and single-disk models.

Reading between the lines

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

  • A natural extension of this picture is that frequency-resolved lag measurements might expose the two response components more cleanly than centroid lags do, because the short-lag mini-disk response and the long-lag circumbinary response enter at different Fourier frequencies.
  • Because the model fixes the orbital phase, one could test the binary interpretation by monitoring long enough to see the long-wavelength lags drift as the secondary moves around the orbit; a single-disk model has no phase dependence of this kind.
  • The paper itself notes that bowl-like single-disk models can also produce a lag break, so a decisive test would be to check whether the break wavelength scales with inferred orbital parameters as $\lambda_{\rm tran}\propto a_B^{3/4}M_t^{1/4}$ across a sample of candidates.
  • The fit implies the secondary accretes at a super-Eddington rate, which raises the question of whether such rates are sustainable over long timescales; modeling the mini-disk spectral energy distribution could test this.
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Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 4 minor

Summary. This paper develops a forward model of continuum reverberation mapping for low-mass-ratio supermassive black hole binaries (SMBHBs). The authors assume a lamp-post corona above the secondary black hole illuminates a truncated mini-disk and a circumbinary disk separated by a low-density cavity (Equations 1-17), compute responsivity-weighted transfer functions, and predict that the inter-band lag-wavelength relation tau(lambda) is flat at short wavelengths and transitions to a lambda^(4/3) power law at long wavelengths, unlike the uniform lambda^(4/3) relation for a single SMBH. They explore the dependence on inclination, orbital phase, orbital separation, mass ratio, and mini-disk outer radius (Figures 5-7), provide an approximate formula for the transition wavelength (Equations 27-30), and apply the model to PG1302-102 using merged Swift/LCO light curves and MICA/ICCF lag measurements. The SMBHB fit yields log(Mt/Msun)=9.9±0.9 and log(PB/day)=3.3±0.4, consistent with independent estimates, but the model is statistically comparable to a free power law (BIC 9.6 versus 8.9 in Section 4.2) and the observed transition is described as not statistically significant.

Significance. If the predicted break in tau(lambda) were unique to SMBHBs and recoverable in real campaigns, this would open a new electromagnetic identification channel for sub-parsec SMBHBs and complement pulsar-timing-array searches. The forward modeling is transparent and internally consistent, and the application to real data with MICA is a strength; the paper also gives a compact scaling formula for the break wavelength and is unusually candid about its limitations. The significance is currently limited because the uniqueness of the signature with respect to bowl-like single-disk models is not demonstrated, and the PG1302-102 data do not discriminate between the SMBHB model and power-law alternatives.

major comments (3)
  1. [Section 6 and Section 4.2] The central claim that the flat-to-lambda^(4/3) transition is a distinguishing SMBHB signature is not supported by the presented evidence. Section 6 acknowledges that a bowl-like single-SMBH disk model can also produce a transition feature (Starkey et al. 2023; Edelson et al. 2024), but this alternative is never fitted to the same PG1302-102 lags. Section 4.2 reports BIC values of 9.6 (SMBHB), 8.9 (free power law), and 10.6 (fixed 4/3 power law), and the text states that the models are comparable and that the observed transition is not statistically significant. The paper therefore demonstrates a plausible forward model, not that continuum reverberation mapping can discriminate SMBHBs from single disks; a quantitative comparison to the bowl-like model, or a demonstration that the bimodal transfer function is recoverable from data of realistic quality, is required for the central claim.
  2. [Section 2.3 and Section 5.1] The paper does not show that the predicted bimodal transfer function or the tau(lambda) break can actually be recovered from realistic monitoring campaigns. The convolution with a DRW ACF (Equation 22) already "severely blurs" the two response bumps (Section 3.1.2 and the right panel of Figure 3), and direct transfer-function inference is explicitly deferred to future work at the end of Section 2.3. No simulated light curves are generated to test how the break in tau(lambda) or the bimodal psi(lambda,tau) would appear with the cadence, duration, and photometric noise of the PG1302-102 campaign or of LSST/WFS. Without such a recovery test, the observational signature remains a theoretical prediction rather than a demonstrated observable.
  3. [Section 3.4, Eq. (27)] There is a numerical inconsistency in the approximate transition-temperature formula. For the fiducial parameters of Table 1, Equation (27) gives Ttran ~ 10^4 x (5.25)^(-1/4) x (3)^(-3/4) ~ 2.9 x 10^3 K, while Section 3.1.2 states the inner edge of the circumbinary disk has T ~ 6 x 10^3 K; direct evaluation of T^4 = 3GMt Mdot_c / (8 pi sigma aB^3) with Mdot_c = 0.1 L_Edd/(0.1 c^2) gives roughly 5.4 x 10^3 K before applying the f factor. Consequently Equations (29)-(30) underestimate lambda_tran by approximately a factor of two, which is material for the survey-feasibility statements in Section 5.2. The prefactors should be recalibrated against the numerical tau(lambda) calculation.
minor comments (4)
  1. [Section 4.2] The dimensionless accretion rates mdoto_c = 0.022 and mdoto_s = 6.28 appear to use eta = 0.1 for the Eddington rate while Mdot_c = 3.7 Msun/yr was derived with eta = 0.3; this mixing of radiative efficiencies should be fixed, as it changes the stated super-Eddington accretion rate of the secondary.
  2. [Section 2.3, Eqs. (18)-(25)] The model compares observed inter-band lags to differences of each band's lag relative to the driving light curve, but for a CCF between two observed bands the peak or centroid is not in general the difference of the individual peak or centroid lags when the transfer functions have different shapes; this approximation should be stated explicitly and tested with simulated light curves.
  3. [Throughout] There are numerous typographical errors, including "cicumbinary" (Section 2.2), "nomenclaturally" (Section 2.2), "conocial" (Section 6), "capble" (Section 6), and "orbtial" (Section 3.2); a careful proofreading pass is needed.
  4. [Section 2.2, Eq. (23)] The DRW damping timescale tau_D is calibrated from V-band AGN variability but is applied to the X-ray driving light curve; the paper should note that this is an approximation and, ideally, test the sensitivity of the predicted peak lags to tau_D.

Circularity Check

1 steps flagged · score 3.0 of 10

PG1302-102 'reproduction' partly rests on a mini-disk truncation parameter tuned to the same lags; the transition-feature prediction itself is forward-modeled and not circular.

  1. fitted input called prediction [Section 3.1 (fiducial parameter choice) and Section 4.2 (application to PG 1302-102)]
    "The outer radius of the mini-disk around the secondary black hole is set to r_out,s = 0.1 r_R,s (see Equation 5). As demonstrated in Section 4, this choice aligns with the inference from fitting our SMBHB model to the observed data of the SMBHB candidate PG 1302-102."

    The mini-disk truncation parameter ξ, entering through r_out,s = ξ r_R,s, is the key ingredient producing the flat short-wavelength part of τ(λ). The paper explicitly states that the fiducial value ξ = 0.1 was chosen because it aligns with the inference from fitting the same PG 1302-102 lag data. When Section 4 then reports that the SMBHB model 'can reproduce the inter-band time lags' of PG 1302-102, that reproduction is partly guaranteed by the earlier calibration: one model parameter was tuned to those very lags. This makes the PG 1302-102 agreement a postdiction rather than an independent test.

full rationale

The central prediction—a bimodal transfer function and a flat-to-λ^(4/3) transition in τ(λ)—is a forward calculation from an explicitly stated physical model: a tidally truncated mini-disk, a circumbinary disk with an inner edge set by the Hill radius, a low-density cavity, and a single lamp-post corona. The transition wavelength is derived from assumed disk temperatures and orbital parameters (Equations 27–30), not from fitting the PG 1302-102 lags. Thus the core claim is not circular by construction. The PG 1302-102 application is a genuine fit with six free parameters, and in the free-orbital-period case the inferred period is compared with, not forced to equal, the independently known optical periodicity; this provides some independent support. The main circular element is the fiducial choice ξ = 0.1 r_R,s, which the paper states was selected to align with the PG 1302-102 fitting inference and then reused as evidence that the model reproduces the same data. This is a fitted input presented as a successful demonstration, warranting a score of 3 rather than 0. The acknowledged degeneracy with the bowl-like disk model (Section 6) is a scientific limitation about uniqueness, not a circularity, and the paper honestly states that current data cannot discriminate between the SMBHB model and power-law models.

Assumptions & free parameters 10 free parameters · 7 assumptions · 0 invented entities

The model is a forward calculation built on standard thin-disk physics plus several simplifying assumptions about the binary geometry; no new physical entities are introduced. The main hand-chosen and fitted parameters control the disk sizes, masses, and geometry, and several are poorly constrained by the current data.

free parameters (10)
  • Mini-disk outer radius fraction ξ (rs,out) = log(rs,out/Rg,s) ≈ 2.0 (≈100 Rg,s) for PG1302; fiducial ξ=0.1
    Controls the flat short-wavelength lag plateau and the transition wavelength; free in the fit, and its fiducial value was calibrated on PG1302 data (Section 3.1).
  • Total mass Mt = log(Mt/Msun) ≈ 9.9 ± 0.9
    Fitted to the PG1302 inter-band lags; sets the physical scale of the disk system.
  • Mass ratio q = log q ≈ -2.4 (+1.2/-1.0)
    Fitted but poorly constrained; determines the secondary mass and mini-disk temperature.
  • Orbital period PB = log(PB/day) ≈ 3.3 ± 0.4
    Fitted; the recovered period is compared with the independent periodicity.
  • Inclination i = cos i ≈ 0.5 ± 0.3
    Fitted but poorly constrained; affects the lag geometry.
  • Orbital phase θs = ≈ 95° ± 60°
    Fitted but poorly constrained; changes the circumbinary disk lags.
  • Corona height hs = 6 Rg,s (fixed)
    Hand-chosen from X-ray microlensing and reflection constraints; affects the illumination pattern.
  • Disk albedo a and corona luminosity fraction fb = a=0.1, fb=1 (fixed)
    Hand-chosen; only the combination fb(1-a) matters for the heating ratio.
  • Radiative efficiency η and bolometric correction = η=0.3, bolometric correction 10 for PG1302
    Converts observed luminosity to accretion rate; the paper notes uncertainty in these transfers directly to the inferred Mt (Section 4.2).
  • DRW damping timescale τD = ≈15 days for fiducial Ms from Lu et al. (2019) scaling
    Used in the ACF convolution; applied uniformly to all bands, an approximation.
assumptions (7)
  • domain assumption Accretion disks are geometrically thin, optically thick, and radiate locally as Planck blackbodies (Equation 1).
    Standard thin-disk assumption used throughout the transfer function calculation.
  • domain assumption A single lamp-post corona above the secondary black hole drives all UV/optical variability, with isotropic emission and constant height (Equations 10-12).
    Core driving mechanism; the authors concede X-ray/UV correlations are observed to be diverse (Section 5.1).
  • domain assumption The circumbinary disk inner radius follows r_in,c ≈ aB/(1+q) + r_H,s (Equation 2), and the Roche radius formula (Equation 4) sets the mini-disk truncation scale.
    From prior binary-disk literature; the actual cavity shape is irregular in simulations, acknowledged in Section 5.1.
  • domain assumption Accretion from the circumbinary disk feeds only the secondary black hole (Ṁc=Ṁs); the primary's mini-disk is neglected.
    Valid for low mass ratio per cited simulations; breaks down as q grows (Section 5.1).
  • domain assumption The orbital phase θs is constant during the RM campaign, and the variable corona luminosity Lb(t) can be replaced by the mean luminosity Lμ for temperature calculation.
    Quasi-stationarity and linear response approximations stated in Section 2.2.
  • domain assumption AGN variability follows the DRW process with an exponential ACF (Equation 20), with τD from the empirical Lu et al. (2019) scaling.
    Used to convert transfer functions to CCF lags; applied uniformly across bands.
  • domain assumption The responsivity-weighted transfer function (Equation 16) is the correct quantity for comparing with CCF lags.
    Argued via Li & Wang (2025); an emissivity-weighted alternative could give different lags.

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Cite this review

Pith. "Pith review of Continuum Reverberation Mapping of Accretion Disks Surrounding Supermassive Black Hole Binaries: Observational Signatures." pith.science (2026). https://pith.science/paper/3VYQJFHB

@misc{pith2026250721671,
  author       = {Pith},
  title        = {Pith review of: Continuum Reverberation Mapping of Accretion Disks Surrounding Supermassive Black Hole Binaries: Observational Signatures},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/3VYQJFHB}},
  note         = {Machine review of arXiv:2507.21671}
}
abstract

It has remained challenging to reliably identify sub-parsec supermassive black hole binaries (SMBHBs), despite them being expected to be ubiquitous. We propose a new method using multi-band continuum reverberation mapping to identify low-mass-ratio SMBHBs in active galactic nuclei. The basic principle is that, due to the presence of a low-density cavity between the mini-disks and the circumbinary disk, the continuum emissions show a deficit at certain wavelengths, leading to a distinguishing feature in the relation between the inter-band time lag and wavelengths $\tau(\lambda)$. Specifically, the relation appears flat at short wavelengths because of the truncated sizes of the mini-disks and transits to a power law $\lambda^{4/3}$ at long wavelength stemming from the circumbinary disk. This transition feature is distinct from the uniform relation $\lambda^{4/3}$ of the standard accretion disk around a single black hole. Using the lamp-post scenario and assuming that only the secondary black hole is active in a low-mass-ratio SMBHB, we design a simple continuum reverberation model to calculate the transfer function of the accretion disks and the resulting $\tau(\lambda)$ relations for various SMBHB orbital parameters. The transition wavelength typically can lie at UV/optical bands, mainly depending on the total mass and orbital separation of the SMBHB. We apply our SMBHB model to the intensive multiwavelength monitoring data of the SMBHB candidate PG1302-102 and find that the SMBHB model can reproduce the inter-band time lags. Remarkably, the inferred total mass and orbital period from the SMBHB fitting are consistent with values derived from other independent methods.

Figures

Figures reproduced from arXiv: 2507.21671 by the authors.

Figure 1
Figure 1. A schematic for accretion disks around an SMBHB (not to scale). The left panel shows the face-on view and the right panel shows the cutaway view. The binary black holes move around each other with a circular orbit. The secondary black hole carries a mini-disk, which has an outer radius 𝑟out,s. The circumbinary disk is coplanar with the mini-disk and has an inner radius 𝑟in,s . Between the mini-disk and circumbinary … view at source ↗
Figure 2
Figure 2. The responsivity-weighted transfer function of a SMBHB (red solid line) at 4000 Å with the fiducial parameters listed in [PITH_FULL_IMAGE:figures/full_fig_p006_2.png] view at source ↗
Figure 3
Figure 3. (Left) The responsivity-weighted transfer functions of a SMBHB at different wavelengths. Note that the scales of both horizontal and vertical axes are adjusted to be “symmetric logarithmic”, namely, linear between 0 and 1 and logarithmic beyond 1. (Right) The transfer functions in the left panel convolved with an exponential ACF (see Equation 22). The characteristic timescale of the ACF is set to 𝜏D ≈ 15 days for 𝑀•… view at source ↗
Figures from the paper (9 more)
Figure 4
Figure 4. Figure 4: The 𝜏 (𝜆) relation of an SMBHB with the fiducial parameters listed in [PITH_FULL_IMAGE:figures/full_fig_p007_4.png]
Figure 5
Figure 5. Figure 5: The responsivity-weighted transfer function for different inclinations (top left), phase angles (top right), orbital separation (bottom left), and total mass (bottom right). In each case, the rest parameters are set as the fiducial values listed in [PITH_FULL_IMAGE:fi…
Figure 6
Figure 6. Figure 6: The 𝜏 (𝜆) relation of SMBHB for different inclinations (first and second row), phase angles (third row), orbit separation (fourth row), total mass (fifth row), mass ratio(sixth row) and outer radius of the mini-disk(seventh row) . In each case, the rest parameters are …
Figure 6
Figure 6. Figure 6: (Continued). respectively. Both the outer radius of the mini-disk 𝑟out,s and inner radius of the circumbinary disk 𝑟in,c increase linearly with 𝑎B (see Equation 5 and Equation 2), resulting in a proportional increase in the time lags. Meanwhile, the temperature at both…
Figure 7
Figure 7. Figure 7: The transition wavelength 𝜆tran from Equation (29) while varying (left) the total mass 𝑀t , (middle) accretion rate of the circumbinary disk 𝑚¤ c, and (right) the orbital separation 𝑎B. The text along with each line marks the value of the parameter under changing. The …
Figure 8
Figure 8. Figure 8: The inter-band time lag analysis of PG 1302-102 using MICA. (Left) Histograms of MCMC samples of the centroid time lags (observed-frame) of the Gaussian transfer functions. (Middle) The inferred Gaussian transfer functions (solid lines) and 1𝜎 uncertainties (shaded ban…
Figure 9
Figure 9. Figure 9: The 𝜏 (𝜆) relation of PG 1302-102 and the fits using the SMBHB model. The blue points represent the inter-band time lags measured from MICA. The red solid line represents the central lags of the 1000 best-fitting parameter groups selected from the posterior samples. Th…
Figure 10
Figure 10. Figure 10 [PITH_FULL_IMAGE:figures/full_fig_p015_10.png]
Figure 11
Figure 11. Figure 11: Same as [PITH_FULL_IMAGE:figures/full_fig_p016_11.png]

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Works this paper leans on

101 extracted references · 15 canonical work pages

  1. [1]

    Abdollahi S., et al., 2024, @doi [ ] 10.3847/1538-4357/ad64c5 , https://ui.adsabs.harvard.edu/abs/2024ApJ...976..203A 976, 203

  2. [2]

    D., Baron F., Bentz M

    Anderson M. D., Baron F., Bentz M. C., 2021, @doi [ ] 10.1093/mnras/stab1394 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.505.2903A 505, 2903

  3. [3]

    Antonucci R. R. J., 2023, @doi [Galaxies] 10.3390/galaxies11050102 , https://ui.adsabs.harvard.edu/abs/2023Galax..11..102A 11, 102

  4. [4]

    H., 1994, @doi [ ] 10.1086/173679 , https://ui.adsabs.harvard.edu/abs/1994ApJ...421..651A 421, 651

    Artymowicz P., Lubow S. H., 1994, @doi [ ] 10.1086/173679 , https://ui.adsabs.harvard.edu/abs/1994ApJ...421..651A 421, 651

  5. [5]

    H., 1996, @doi [ ] 10.1086/310200 , https://ui.adsabs.harvard.edu/abs/1996ApJ...467L..77A 467, L77

    Artymowicz P., Lubow S. H., 1996, @doi [ ] 10.1086/310200 , https://ui.adsabs.harvard.edu/abs/1996ApJ...467L..77A 467, L77

  6. [6]

    C., Blandford R

    Begelman M. C., Blandford R. D., Rees M. J., 1980, @doi [ ] 10.1038/287307a0 , https://ui.adsabs.harvard.edu/abs/1980Natur.287..307B 287, 307

  7. [7]

    Bon E., et al., 2012, @doi [ ] 10.1088/0004-637X/759/2/118 , https://ui.adsabs.harvard.edu/abs/2012ApJ...759..118B 759, 118

  8. [8]

    B., Mewes V., Noble S

    Bowen D. B., Mewes V., Noble S. C., Avara M., Campanelli M., Krolik J. H., 2019, @doi [ ] 10.3847/1538-4357/ab2453 , https://ui.adsabs.harvard.edu/abs/2019ApJ...879...76B 879, 76

Show all 101 references
  1. [9]

    J., P \'a rtay L

    Brewer B. J., P \'a rtay L. B., Cs \'a nyi G., 2010, DNEST: Diffusive Nested Sampling , Astrophysics Source Code Library, record ascl:1010.029

  2. [10]

    M., Horne K., Winkler H., 2007, @doi [ ] 10.1111/j.1365-2966.2007.12098.x , https://ui.adsabs.harvard.edu/abs/2007MNRAS.380..669C 380, 669

    Cackett E. M., Horne K., Winkler H., 2007, @doi [ ] 10.1111/j.1365-2966.2007.12098.x , https://ui.adsabs.harvard.edu/abs/2007MNRAS.380..669C 380, 669

  3. [11]

    M., Chiang C.-Y., McHardy I., Edelson R., Goad M

    Cackett E. M., Chiang C.-Y., McHardy I., Edelson R., Goad M. R., Horne K., Korista K. T., 2018, @doi [ ] 10.3847/1538-4357/aab4f7 , https://ui.adsabs.harvard.edu/abs/2018ApJ...857...53C 857, 53

  4. [12]

    M., et al., 2020, @doi [ ] 10.3847/1538-4357/ab91b5 , https://ui.adsabs.harvard.edu/abs/2020ApJ...896....1C 896, 1

    Cackett E. M., et al., 2020, @doi [ ] 10.3847/1538-4357/ab91b5 , https://ui.adsabs.harvard.edu/abs/2020ApJ...896....1C 896, 1

  5. [13]

    M., Bentz M

    Cackett E. M., Bentz M. C., Kara E., 2021, @doi [iScience] 10.1016/j.isci.2021.102557 , https://ui.adsabs.harvard.edu/abs/2021iSci...24j2557C 24, 102557

  6. [14]

    M., Zoghbi A., Ulrich O., 2022, @doi [ ] 10.3847/1538-4357/ac3913 , https://ui.adsabs.harvard.edu/abs/2022ApJ...925...29C 925, 29

    Cackett E. M., Zoghbi A., Ulrich O., 2022, @doi [ ] 10.3847/1538-4357/ac3913 , https://ui.adsabs.harvard.edu/abs/2022ApJ...925...29C 925, 29

  7. [15]

    J., Kara E., 2016, @doi [ ] 10.1093/mnras/stw1105 , https://ui.adsabs.harvard.edu/abs/2016MNRAS.460.3076C 460, 3076

    Chainakun P., Young A. J., Kara E., 2016, @doi [ ] 10.1093/mnras/stw1105 , https://ui.adsabs.harvard.edu/abs/2016MNRAS.460.3076C 460, 3076

  8. [16]

    M., Graham M

    Charisi M., Bartos I., Haiman Z., Price-Whelan A. M., Graham M. J., Bellm E. C., Laher R. R., M \'a rka S., 2016, @doi [ ] 10.1093/mnras/stw1838 , https://ui.adsabs.harvard.edu/abs/2016MNRAS.463.2145C 463, 2145

  9. [17]

    S., Chartas G., Blackburne J

    Chen B., Dai X., Kochanek C. S., Chartas G., Blackburne J. A., Morgan C. W., 2012, @doi [ ] 10.1088/0004-637X/755/1/24 , https://ui.adsabs.harvard.edu/abs/2012ApJ...755...24C 755, 24

  10. [18]

    Chen Y., Yu Q., Lu Y., 2020, @doi [ ] 10.3847/1538-4357/ab9594 , https://ui.adsabs.harvard.edu/abs/2020ApJ...897...86C 897, 86

  11. [19]

    Chen Y.-J., et al., 2024, @doi [ ] 10.1093/mnras/stad3981 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.52712154C 527, 12154

  12. [20]

    G., Baugh C

    Cole S., Lacey C. G., Baugh C. M., Frenk C. S., 2000, @doi [ ] 10.1046/j.1365-8711.2000.03879.x , https://ui.adsabs.harvard.edu/abs/2000MNRAS.319..168C 319, 168

  13. [21]

    Colpi M., 2014, @doi [ ] 10.1007/s11214-014-0067-1 , https://ui.adsabs.harvard.edu/abs/2014SSRv..183..189C 183, 189

  14. [22]

    G., Campanelli M., Noble S

    Combi L., Lopez Armengol F. G., Campanelli M., Noble S. C., Avara M., Krolik J. H., Bowen D., 2022, @doi [ ] 10.3847/1538-4357/ac532a , https://ui.adsabs.harvard.edu/abs/2022ApJ...928..187C 928, 187

  15. [23]

    J., Charisi M., 2023, @doi [arXiv e-prints] 10.48550/arXiv.2310.16896 , https://ui.adsabs.harvard.edu/abs/2023arXiv231016896D p

    D'Orazio D. J., Charisi M., 2023, @doi [arXiv e-prints] 10.48550/arXiv.2310.16896 , https://ui.adsabs.harvard.edu/abs/2023arXiv231016896D p. arXiv:2310.16896

  16. [24]

    J., Haiman Z., MacFadyen A., 2013, @doi [ ] 10.1093/mnras/stt1787 , https://ui.adsabs.harvard.edu/abs/2013MNRAS.436.2997D 436, 2997

    D'Orazio D. J., Haiman Z., MacFadyen A., 2013, @doi [ ] 10.1093/mnras/stt1787 , https://ui.adsabs.harvard.edu/abs/2013MNRAS.436.2997D 436, 2997

  17. [25]

    J., Haiman Z., Schiminovich D., 2015, @doi [ ] 10.1038/nature15262 , https://ui.adsabs.harvard.edu/abs/2015Natur.525..351D 525, 351

    D'Orazio D. J., Haiman Z., Schiminovich D., 2015, @doi [ ] 10.1038/nature15262 , https://ui.adsabs.harvard.edu/abs/2015Natur.525..351D 525, 351

  18. [26]

    J., Haiman Z., Duffell P., MacFadyen A., Farris B., 2016, @doi [ ] 10.1093/mnras/stw792 , https://ui.adsabs.harvard.edu/abs/2016MNRAS.459.2379D 459, 2379

    D'Orazio D. J., Haiman Z., Duffell P., MacFadyen A., Farris B., 2016, @doi [ ] 10.1093/mnras/stw792 , https://ui.adsabs.harvard.edu/abs/2016MNRAS.459.2379D 459, 2379

  19. [27]

    R., et al., 2023, @doi [ ] 10.1093/mnras/stad1409 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.523..545D 523, 545

    Donnan F. R., et al., 2023, @doi [ ] 10.1093/mnras/stad1409 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.523..545D 523, 545

  20. [28]

    J., et al., 2009, @doi [ ] 10.1088/0004-637X/696/1/870 , https://ui.adsabs.harvard.edu/abs/2009ApJ...696..870D 696, 870

    Drake A. J., et al., 2009, @doi [ ] 10.1088/0004-637X/696/1/870 , https://ui.adsabs.harvard.edu/abs/2009ApJ...696..870D 696, 870

  21. [29]

    Edelson R., et al., 2019, @doi [ ] 10.3847/1538-4357/aaf3b4 , https://ui.adsabs.harvard.edu/abs/2019ApJ...870..123E 870, 123

  22. [30]

    M., Gelbord J., Horne K., Goad M., McHardy I., Vaughan S., Vestergaard M., 2024, @doi [ ] 10.3847/1538-4357/ad64d4 , https://ui.adsabs.harvard.edu/abs/2024ApJ...973..152E 973, 152

    Edelson R., Peterson B. M., Gelbord J., Horne K., Goad M., McHardy I., Vaughan S., Vestergaard M., 2024, @doi [ ] 10.3847/1538-4357/ad64d4 , https://ui.adsabs.harvard.edu/abs/2024ApJ...973..152E 973, 152

  23. [31]

    P., 1983, @doi [ ] 10.1086/160960 , https://ui.adsabs.harvard.edu/abs/1983ApJ...268..368E 268, 368

    Eggleton P. P., 1983, @doi [ ] 10.1086/160960 , https://ui.adsabs.harvard.edu/abs/1983ApJ...268..368E 268, 368

  24. [32]

    E., Dov c iak M., Pech \'a c ek T., Emmanoulopoulos D., Karas V., McHardy I

    Epitropakis A., Papadakis I. E., Dov c iak M., Pech \'a c ek T., Emmanoulopoulos D., Karas V., McHardy I. M., 2016, @doi [ ] 10.1051/0004-6361/201527748 , https://ui.adsabs.harvard.edu/abs/2016A&A...594A..71E 594, A71

  25. [33]

    D., Duffell P., MacFadyen A

    Farris B. D., Duffell P., MacFadyen A. I., Haiman Z., 2014, @doi [ ] 10.1088/0004-637X/783/2/134 , https://ui.adsabs.harvard.edu/abs/2014ApJ...783..134F 783, 134

  26. [34]

    M., et al., 2016, @doi [ ] 10.3847/0004-637X/821/1/56 , https://ui.adsabs.harvard.edu/abs/2016ApJ...821...56F 821, 56

    Fausnaugh M. M., et al., 2016, @doi [ ] 10.3847/0004-637X/821/1/56 , https://ui.adsabs.harvard.edu/abs/2016ApJ...821...56F 821, 56

  27. [35]

    W., Lang D., Goodman J., 2013, @doi [ ] 10.1086/670067 , https://ui.adsabs.harvard.edu/abs/2013PASP..125..306F 125, 306

    Foreman-Mackey D., Hogg D. W., Lang D., Goodman J., 2013, @doi [ ] 10.1086/670067 , https://ui.adsabs.harvard.edu/abs/2013PASP..125..306F 125, 306

  28. [36]

    Gardner E., Done C., 2017, @doi [ ] 10.1093/mnras/stx946 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.470.3591G 470, 3591

  29. [37]

    M., Peterson B

    Gaskell C. M., Peterson B. M., 1987, @doi [ ] 10.1086/191216 , https://ui.adsabs.harvard.edu/abs/1987ApJS...65....1G 65, 1

  30. [38]

    M., Sparke L

    Gaskell C. M., Sparke L. S., 1986, @doi [ ] 10.1086/164238 , https://ui.adsabs.harvard.edu/abs/1986ApJ...305..175G 305, 175

  31. [39]

    H., Hern \'a ndez Santisteban J

    Gonz \'a lez-Buitrago D. H., Hern \'a ndez Santisteban J. V., Barth A. J., Jimenez-Bail \'o n E., Li Y.-R., Garc \' a-D \' az M. T., Lopez Vargas A., Herrera-Endoqui M., 2022, @doi [ ] 10.1093/mnras/stac1945 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.515.2890G 515, 2890

  32. [40]

    J., et al., 2015, @doi [ ] 10.1038/nature14143 , https://ui.adsabs.harvard.edu/abs/2015Natur.518...74G 518, 74

    Graham M. J., et al., 2015, @doi [ ] 10.1038/nature14143 , https://ui.adsabs.harvard.edu/abs/2015Natur.518...74G 518, 74

  33. [41]

    M., 2012, @doi [ ] 10.1088/0004-637X/761/2/90 , https://ui.adsabs.harvard.edu/abs/2012ApJ...761...90G 761, 90

    G \"u ltekin K., Miller J. M., 2012, @doi [ ] 10.1088/0004-637X/761/2/90 , https://ui.adsabs.harvard.edu/abs/2012ApJ...761...90G 761, 90

  34. [42]

    C., Wang J.-M., 2022, @doi [ ] 10.3847/1538-4357/ac4e84 , https://ui.adsabs.harvard.edu/abs/2022ApJ...929...19G 929, 19

    Guo W.-J., Li Y.-R., Zhang Z.-X., Ho L. C., Wang J.-M., 2022, @doi [ ] 10.3847/1538-4357/ac4e84 , https://ui.adsabs.harvard.edu/abs/2022ApJ...929...19G 929, 19

  35. [43]

    V., et al., 2020, @doi [ ] 10.1093/mnras/staa2365 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.498.5399H 498, 5399

    Hern \'a ndez Santisteban J. V., et al., 2020, @doi [ ] 10.1093/mnras/staa2365 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.498.5399H 498, 5399

  36. [44]

    M., Horne K., Peterson B

    Horne K., 1994, in Gondhalekar P. M., Horne K., Peterson B. M., eds, Astronomical Society of the Pacific Conference Series Vol. 69, Reverberation Mapping of the Broad-Line Region in Active Galactic Nuclei. p. 23

  37. [45]

    Ivezi \'c Z ., et al., 2019, @doi [ ] 10.3847/1538-4357/ab042c , https://ui.adsabs.harvard.edu/abs/2019ApJ...873..111I 873, 111

  38. [46]

    Jester S., et al., 2005, @doi [ ] 10.1086/432466 , https://ui.adsabs.harvard.edu/abs/2005AJ....130..873J 130, 873

  39. [47]

    Kara E., et al., 2021, @doi [ ] 10.3847/1538-4357/ac2159 , https://ui.adsabs.harvard.edu/abs/2021ApJ...922..151K 922, 151

  40. [48]

    Kara E., et al., 2023, @doi [ ] 10.3847/1538-4357/acbcd3 , https://ui.adsabs.harvard.edu/abs/2023ApJ...947...62K 947, 62

  41. [49]

    C., Bechtold J., Siemiginowska A., 2009, @doi [ ] 10.1088/0004-637X/698/1/895 , https://ui.adsabs.harvard.edu/abs/2009ApJ...698..895K 698, 895

    Kelly B. C., Bechtold J., Siemiginowska A., 2009, @doi [ ] 10.1088/0004-637X/698/1/895 , https://ui.adsabs.harvard.edu/abs/2009ApJ...698..895K 698, 895

  42. [50]

    B., Popovi \'c L

    Kova c evi \'c A. B., Popovi \'c L. C ., Simi \'c S., Ili \'c D., 2019, @doi [ ] 10.3847/1538-4357/aaf731 , https://ui.adsabs.harvard.edu/abs/2019ApJ...871...32K 871, 32

  43. [51]

    M., Terndrup D

    Leighly K. M., Terndrup D. M., Gallagher S. C., Lucy A. B., 2016, @doi [ ] 10.3847/0004-637X/829/1/4 , https://ui.adsabs.harvard.edu/abs/2016ApJ...829....4L 829, 4

  44. [52]

    Li Y.-R., Wang J.-M., 2025, @doi [ ] 10.3847/1538-4357/ad9fee , https://ui.adsabs.harvard.edu/abs/2025ApJ...979..126L 979, 126

  45. [53]

    C., Du P., Bai J.-M., 2013, @doi [ ] 10.1088/0004-637X/779/2/110 , https://ui.adsabs.harvard.edu/abs/2013ApJ...779..110L 779, 110

    Li Y.-R., Wang J.-M., Ho L. C., Du P., Bai J.-M., 2013, @doi [ ] 10.1088/0004-637X/779/2/110 , https://ui.adsabs.harvard.edu/abs/2013ApJ...779..110L 779, 110

  46. [54]

    Li Y.-R., Wang J.-M., Hu C., Du P., Bai J.-M., 2014, @doi [ ] 10.1088/2041-8205/786/1/L6 , https://ui.adsabs.harvard.edu/abs/2014ApJ...786L...6L 786, L6

  47. [55]

    Li Y.-R., et al., 2016a, @doi [ ] 10.3847/0004-637X/822/1/4 , https://ui.adsabs.harvard.edu/abs/2016ApJ...822....4L 822, 4

  48. [56]

    Li Y.-R., Wang J.-M., Bai J.-M., 2016b, @doi [ ] 10.3847/0004-637X/831/2/206 , https://ui.adsabs.harvard.edu/abs/2016ApJ...831..206L 831, 206

  49. [57]

    Li Y.-R., et al., 2019, @doi [ ] 10.3847/1538-4365/ab0ec5 , https://ui.adsabs.harvard.edu/abs/2019ApJS..241...33L 241, 33

  50. [58]

    Li Y.-R., Xiao M., Wang J.-M., 2021, @doi [ ] 10.3847/1538-4357/ac1c71 , https://ui.adsabs.harvard.edu/abs/2021ApJ...921..151L 921, 151

  51. [59]

    C., 2018, @doi [ ] 10.3847/2041-8213/aac2ed , https://ui.adsabs.harvard.edu/abs/2018ApJ...859L..12L 859, L12

    Liu T., Gezari S., Miller M. C., 2018, @doi [ ] 10.3847/2041-8213/aac2ed , https://ui.adsabs.harvard.edu/abs/2018ApJ...859L..12L 859, L12

  52. [60]

    Liu T., et al., 2019, @doi [ ] 10.3847/1538-4357/ab40cb , https://ui.adsabs.harvard.edu/abs/2019ApJ...884...36L 884, 36

  53. [61]

    Liu T., et al., 2024, @doi [ ] 10.3847/1538-4357/ad23e2 , https://ui.adsabs.harvard.edu/abs/2024ApJ...964..167L 964, 167

  54. [62]

    G., et al., 2021, @doi [ ] 10.3847/1538-4357/abf0af , https://ui.adsabs.harvard.edu/abs/2021ApJ...913...16L 913, 16

    Lopez Armengol F. G., et al., 2021, @doi [ ] 10.3847/1538-4357/abf0af , https://ui.adsabs.harvard.edu/abs/2021ApJ...913...16L 913, 16

  55. [63]

    Lu K.-X., et al., 2019, @doi [ ] 10.3847/1538-4357/ab16e8 , https://ui.adsabs.harvard.edu/abs/2019ApJ...877...23L 877, 23

  56. [64]

    Luo D., Jiang N., Liu X., 2025, @doi [ ] 10.3847/1538-4357/ad9245 , https://ui.adsabs.harvard.edu/abs/2025ApJ...978...86L 978, 86

  57. [65]

    Maoz D., et al., 1991, @doi [ ] 10.1086/169646 , https://ui.adsabs.harvard.edu/abs/1991ApJ...367..493M 367, 493

  58. [66]

    K., Maiolino R., Salvati M., 2004, @doi [ ] 10.1111/j.1365-2966.2004.07765.x , https://ui.adsabs.harvard.edu/abs/2004MNRAS.351..169M 351, 169

    Marconi A., Risaliti G., Gilli R., Hunt L. K., Maiolino R., Salvati M., 2004, @doi [ ] 10.1111/j.1365-2966.2004.07765.x , https://ui.adsabs.harvard.edu/abs/2004MNRAS.351..169M 351, 169

  59. [67]

    Merritt D., Milosavljevi \'c M., 2005, @doi [Living Reviews in Relativity] 10.12942/lrr-2005-8 , https://ui.adsabs.harvard.edu/abs/2005LRR.....8....8M 8, 8

  60. [68]

    W., et al., 2012, @doi [ ] 10.1088/0004-637X/756/1/52 , https://ui.adsabs.harvard.edu/abs/2012ApJ...756...52M 756, 52

    Morgan C. W., et al., 2012, @doi [ ] 10.1088/0004-637X/756/1/52 , https://ui.adsabs.harvard.edu/abs/2012ApJ...756...52M 756, 52

  61. [69]

    O'Neill S., et al., 2022, @doi [ ] 10.3847/2041-8213/ac504b , https://ui.adsabs.harvard.edu/abs/2022ApJ...926L..35O 926, L35

  62. [70]

    M., Wanders I., Horne K., Collier S., Alexander T., Kaspi S., Maoz D., 1998, @doi [ ] 10.1086/316177 , https://ui.adsabs.harvard.edu/abs/1998PASP..110..660P 110, 660

    Peterson B. M., Wanders I., Horne K., Collier S., Alexander T., Kaspi S., Maoz D., 1998, @doi [ ] 10.1086/316177 , https://ui.adsabs.harvard.edu/abs/1998PASP..110..660P 110, 660

  63. [71]

    Prince R., et al., 2025, @doi [ ] 10.1093/mnras/staf983 , https://ui.adsabs.harvard.edu/abs/2025MNRAS.541..642P 541, 642

  64. [72]

    S., Kotilainen J., 2020, @doi [ ] 10.3847/1538-4365/ab99c5 , https://ui.adsabs.harvard.edu/abs/2020ApJS..249...17R 249, 17

    Rakshit S., Stalin C. S., Kotilainen J., 2020, @doi [ ] 10.3847/1538-4365/ab99c5 , https://ui.adsabs.harvard.edu/abs/2020ApJS..249...17R 249, 17

  65. [73]

    Rigamonti F., et al., 2025, @doi [ ] 10.1051/0004-6361/202452830 , https://ui.adsabs.harvard.edu/abs/2025A&A...693A.117R 693, A117

  66. [74]

    Roedig C., Sesana A., Dotti M., Cuadra J., Amaro-Seoane P., Haardt F., 2012, @doi [ ] 10.1051/0004-6361/201219986 , https://ui.adsabs.harvard.edu/abs/2012A&A...545A.127R 545, A127

  67. [75]

    H., Miller M

    Roedig C., Krolik J. H., Miller M. C., 2014, @doi [ ] 10.1088/0004-637X/785/2/115 , https://ui.adsabs.harvard.edu/abs/2014ApJ...785..115R 785, 115

  68. [76]

    Ryan G., MacFadyen A., 2017, @doi [ ] 10.3847/1538-4357/835/2/199 , https://ui.adsabs.harvard.edu/abs/2017ApJ...835..199R 835, 199

  69. [77]

    F., Finkbeiner D

    Schlafly E. F., Finkbeiner D. P., 2011, @doi [ ] 10.1088/0004-637X/737/2/103 , https://ui.adsabs.harvard.edu/abs/2011ApJ...737..103S 737, 103

  70. [78]

    J., Finkbeiner D

    Schlegel D. J., Finkbeiner D. P., Davis M., 1998, @doi [ ] 10.1086/305772 , https://ui.adsabs.harvard.edu/abs/1998ApJ...500..525S 500, 525

  71. [79]

    Schwarz G., 1978, Annals of Statistics, https://ui.adsabs.harvard.edu/abs/1978AnSta...6..461S 6, 461

  72. [80]

    Sesana A., Haardt F., Madau P., Volonteri M., 2004, @doi [ ] 10.1086/422185 , https://ui.adsabs.harvard.edu/abs/2004ApJ...611..623S 611, 623

  73. [81]

    S., Ivezi \'c Z ., Morgan D

    Sesar B., Stuart J. S., Ivezi \'c Z ., Morgan D. P., Becker A. C., Wo \'z niak P., 2011, @doi [ ] 10.1088/0004-6256/142/6/190 , https://ui.adsabs.harvard.edu/abs/2011AJ....142..190S 142, 190

  74. [82]

    Shang Z., et al., 2011, @doi [ ] 10.1088/0067-0049/196/1/2 , https://ui.adsabs.harvard.edu/abs/2011ApJS..196....2S 196, 2

  75. [83]

    H., 2015, @doi [ ] 10.1088/0004-637X/807/2/131 , https://ui.adsabs.harvard.edu/abs/2015ApJ...807..131S 807, 131

    Shi J.-M., Krolik J. H., 2015, @doi [ ] 10.1088/0004-637X/807/2/131 , https://ui.adsabs.harvard.edu/abs/2015ApJ...807..131S 807, 131

  76. [84]

    A., Horne K., Villforth C., 2016, @doi [ ] 10.1093/mnras/stv2744 , https://ui.adsabs.harvard.edu/abs/2016MNRAS.456.1960S 456, 1960

    Starkey D. A., Horne K., Villforth C., 2016, @doi [ ] 10.1093/mnras/stv2744 , https://ui.adsabs.harvard.edu/abs/2016MNRAS.456.1960S 456, 1960

  77. [85]

    Starkey D., et al., 2017, @doi [ ] 10.3847/1538-4357/835/1/65 , https://ui.adsabs.harvard.edu/abs/2017ApJ...835...65S 835, 65

  78. [86]

    A., Huang J., Horne K., Lin D

    Starkey D. A., Huang J., Horne K., Lin D. N. C., 2023, @doi [ ] 10.1093/mnras/stac3579 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.519.2754S 519, 2754

  79. [87]

    C., Lacey C

    Su T., Guo Q., Qiao E., Pei W., Ho L. C., Lacey C. G., 2025, @doi [arXiv e-prints] 10.48550/arXiv.2501.10793 , https://ui.adsabs.harvard.edu/abs/2025arXiv250110793S p. arXiv:2501.10793

  80. [88]

    Sun M., et al., 2020, @doi [ ] 10.3847/1538-4357/ab789e , https://ui.adsabs.harvard.edu/abs/2020ApJ...891..178S 891, 178

  81. [89]

    J., et al., 2008, @doi [ ] 10.1038/nature06896 , https://ui.adsabs.harvard.edu/abs/2008Natur.452..851V 452, 851

    Valtonen M. J., et al., 2008, @doi [ ] 10.1038/nature06896 , https://ui.adsabs.harvard.edu/abs/2008Natur.452..851V 452, 851

  82. [90]

    G., Huppenkothen D., Middleton M

    Vaughan S., Uttley P., Markowitz A. G., Huppenkothen D., Middleton M. J., Alston W. N., Scargle J. D., Farr W. M., 2016, @doi [ ] 10.1093/mnras/stw1412 , https://ui.adsabs.harvard.edu/abs/2016MNRAS.461.3145V 461, 3145

  83. [91]

    Wang T., et al., 2023, @doi [Science China Physics, Mechanics, and Astronomy] 10.1007/s11433-023-2197-5 , https://ui.adsabs.harvard.edu/abs/2023SCPMA..6609512W 66, 109512

  84. [92]

    F., 1999, @doi [ ] 10.1086/316457 , https://ui.adsabs.harvard.edu/abs/1999PASP..111.1347W 111, 1347

    Welsh W. F., 1999, @doi [ ] 10.1086/316457 , https://ui.adsabs.harvard.edu/abs/1999PASP..111.1347W 111, 1347

  85. [93]

    R., Zrake J., MacFadyen A., Haiman Z., 2022, @doi [ ] 10.1103/PhysRevD.106.103010 , https://ui.adsabs.harvard.edu/abs/2022PhRvD.106j3010W 106, 103010

    Westernacher-Schneider J. R., Zrake J., MacFadyen A., Haiman Z., 2022, @doi [ ] 10.1103/PhysRevD.106.103010 , https://ui.adsabs.harvard.edu/abs/2022PhRvD.106j3010W 106, 103010

  86. [94]

    Whitley K., Kuznetsova A., G \"u ltekin K., Ruszkowski M., 2024, @doi [ ] 10.1093/mnras/stad3325 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.527.6569W 527, 6569

  87. [95]

    Yan C.-S., Lu Y., Dai X., Yu Q., 2015, @doi [ ] 10.1088/0004-637X/809/2/117 , https://ui.adsabs.harvard.edu/abs/2015ApJ...809..117Y 809, 117

  88. [96]

    Yaqoob T., Tzanavaris P., LaMassa S., 2023, @doi [ ] 10.1093/mnras/stad782 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.522..394Y 522, 394

  89. [97]

    R., Shen Y., Jiang L., Wang J.-X., Chen X., Cuadra J., 2016, @doi [ ] 10.3847/0004-637X/827/1/56 , https://ui.adsabs.harvard.edu/abs/2016ApJ...827...56Z 827, 56

    Zheng Z.-Y., Butler N. R., Shen Y., Jiang L., Wang J.-X., Chen X., Cuadra J., 2016, @doi [ ] 10.3847/0004-637X/827/1/56 , https://ui.adsabs.harvard.edu/abs/2016ApJ...827...56Z 827, 56

  90. [98]

    Zhou S., Sun M., Cai Z.-Y., Ren G., Wang J.-X., Xue Y., 2024, @doi [ ] 10.3847/1538-4357/ad2fbc , https://ui.adsabs.harvard.edu/abs/2024ApJ...966....8Z 966, 8

  91. [99]

    Zhu X.-J., Thrane E., 2020, @doi [ ] 10.3847/1538-4357/abac5a , https://ui.adsabs.harvard.edu/abs/2020ApJ...900..117Z 900, 117

  92. [100]

    M., Cackett E., 2021, @doi [ ] 10.3847/1538-4357/abebd9 , https://ui.adsabs.harvard.edu/abs/2021ApJ...912...42Z 912, 42

    Zoghbi A., Miller J. M., Cackett E., 2021, @doi [ ] 10.3847/1538-4357/abebd9 , https://ui.adsabs.harvard.edu/abs/2021ApJ...912...42Z 912, 42

  93. [101]

    S., Koz owski S., Udalski A., 2013, @doi [ ] 10.1088/0004-637X/765/2/106 , https://ui.adsabs.harvard.edu/abs/2013ApJ...765..106Z 765, 106

    Zu Y., Kochanek C. S., Koz owski S., Udalski A., 2013, @doi [ ] 10.1088/0004-637X/765/2/106 , https://ui.adsabs.harvard.edu/abs/2013ApJ...765..106Z 765, 106

Pith tools

Reviewed August 6, 2026 · model on record in the stance chip above.