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arxiv: 1906.08310 · v1 · pith:VQQL3CK4new · submitted 2019-06-19 · 🌌 astro-ph.HE

A public relativistic transfer function model for X-ray reverberation mapping of accreting black holes

Pith reviewed 2026-05-25 19:59 UTC · model grok-4.3

classification 🌌 astro-ph.HE
keywords reltransX-ray reverberation mappingblack hole mass measurementaccretion disk ionizationMrk 335active galactic nucleirelativistic transfer functionX-ray lags
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The pith

The reltrans model fits X-ray spectra and lag spectra simultaneously to measure black hole masses and correct prior geometric biases.

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

The paper introduces the public reltrans model, which computes the general relativistic light-crossing delays and energy shifts for X-ray photons emitted near a black hole, reflected from the accretion disk, and scattered into the line of sight. The model is fast enough to fit jointly to the time-averaged spectrum and the energy-dependent cross-spectrum at multiple Fourier frequencies. It incorporates a self-consistent radial ionization profile for the disk and the telescope response function. Application to Mrk 335 data returns a black hole mass of roughly 7 million solar masses. The authors conclude that earlier spectral fits without the ionization profile yielded artificially low source heights and that timing analyses without the response function underestimated soft lags in AGN while overestimating thermal reverberation lags in X-ray binaries.

Core claim

reltrans is a relativistic transfer function model that calculates light-crossing delays and energy shifts experienced by X-ray photons reflecting from an accretion disk, accounting for all general relativistic effects. The model enables simultaneous fitting to spectra and lags, incorporates a self-consistent radial ionization profile, and includes telescope response effects. Fitting to the lag-energy spectrum of Mrk 335 gives a best-fit black hole mass of approximately 7 million solar masses, smaller than the 14-26 million solar masses from prior optical reverberation measurements, while revealing that previous analyses measured artificially low source heights and misestimated lag sizes.

What carries the argument

The reltrans model, a fast relativistic transfer function that computes photon delays, energy shifts, and reflection including general relativity, self-consistent disk ionization, and instrument response.

If this is right

  • Simultaneous fitting of the time-averaged spectrum and lag spectra yields tighter constraints on accretion geometry than spectrum fitting alone.
  • Black hole masses in both active galactic nuclei and X-ray binaries can be measured directly from X-ray timing data.
  • Prior spectral analyses that omitted the radial ionization profile measured source heights that were too low.
  • Prior timing analyses that omitted the telescope response underestimated the magnitude of soft lags in AGN and overestimated thermal reverberation lags in X-ray binaries.

Where Pith is reading between the lines

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

  • The lower mass for Mrk 335 may require re-examination of its accretion rate and other derived properties in multi-wavelength studies.
  • Applying the same model to additional AGN could resolve systematic differences between X-ray and optical mass estimates across the population.
  • Correcting for ionization and response effects in existing archival data might alter interpretations of reflection features in many sources.

Load-bearing premise

The disk ionization parameter varies radially in a way fully determined by the illuminating flux and disk density profile without extra free parameters that would alter the predicted lags.

What would settle it

An independent mass measurement for Mrk 335, such as from optical reverberation mapping or stellar dynamics, that confirms a value of 14-26 million solar masses rather than 7 million would falsify the X-ray lag result.

Figures

Figures reproduced from arXiv: 1906.08310 by Adam Ingram, Guglielmo Mastroserio, Javier A. Garc\'ia, Michiel van der Klis, Pieter Hovenkamp, Thomas Dauser.

Figure 1
Figure 1. Figure 1: Schematic of a source and detector with surface areas (measured in their own restframes) dAs and dAdet respectively. The blue line represents a photon path that emerges parallel to the source surface area vector (in the source restframe) and ar￾rives parallel to the detector surface area vector (in the detector restframe). Only photons emerging from the source within the solid angle dΩdet will eventually h… view at source ↗
Figure 2
Figure 2. Figure 2: Schematic of the on-axis lamppost geometry. A disk patch with area dAd subtends a solid angle dΩd according to the irradiating source. The disk patch corresponds to an area dαdβ on the image plane, where α and β are respectively horizontal and vertical impact parameters at infinity. The bundle of rays within the represented solid angle are assumed to follow the trajectory (green dashed lines) defined by th… view at source ↗
Figure 3
Figure 3. Figure 3: Left: Reflection fraction plotted against source height for three inclination angles, with the disk extending down to the ISCO for black hole spin a = 0.998 (red) and a = 0 (blue). The solid lines are ‘system’ reflection fraction as defined by Dauser et al. (2016) (see our equation 30) and the dashed lines are the observer’s reflection fraction as defined by our equation 31. The system reflection fraction … view at source ↗
Figure 5
Figure 5. Figure 5: Time-averaged direct and reflected spectrum for rel￾trans (black), and the most recent version of relxilllp (red, dashed). We see good agreement between the two models. 3.2 Time-averaged spectrum [PITH_FULL_IMAGE:figures/full_fig_p009_5.png] view at source ↗
Figure 4
Figure 4. Figure 4: Contributions to the radial emissivity profile, designed for comparison to [PITH_FULL_IMAGE:figures/full_fig_p009_4.png] view at source ↗
Figure 6
Figure 6. Figure 6: Cosine of the emission angle (black) and incidence angle (red) as a function of radius for the default parameters (i = 30◦ ). We see that the emission angle depends on azimuth as well as radius, whereas the incidence angle is a monotonic function of radius. The grey points at r & 400 Rg are computed assuming that rays travel in straight lines. The smooth joins from the full GR treatment used for r . 400 Rg… view at source ↗
Figure 7
Figure 7. Figure 7: reltrans time-averaged spectrum (a), 1 − 2 × 10−5 Hz time lags (b) and absolute variability amplitude (c) calculated for the default parameters. Left and right hand panels correspond to inclination angles of 30◦ and 80◦ respectively. For the black lines, we set the emission angle δe equal to the inclination angle i and ignore the radial dependence of Ecu t as measured in the disk restframe. For the other l… view at source ↗
Figure 8
Figure 8. Figure 8: The black lines are radial ionization profiles calcu￾lated assuming a zone A density profile (solid) and constant den￾sity (dashed). The red lines are effective ionization profiles, which have been adjusted to account for the radial dependence of the incidence angle. function is a correct representation of the underlying spec￾tral model if all the channels used for the reference band are considered to be w… view at source ↗
Figure 9
Figure 9. Figure 9: reltrans time-averaged spectrum (a), time lags (b) and absolute variability amplitude for different assumptions re￾garding the radial ionization profile. For all lines, we assume the default parameters, and for the time lag we assume that the ref￾erence band was the 2 − 10 keV EPIC-pn flux. For simplicity, we ignore the µe and Ecu t dependencies explored in [PITH_FULL_IMAGE:figures/full_fig_p012_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: Same as [PITH_FULL_IMAGE:figures/full_fig_p013_10.png] view at source ↗
Figure 13
Figure 13. Figure 13: Time lags calculated for the default parameters. The black line is for the model only, and so does not account for a telescope response matrix. The red and blue lines assume the pn response and absorption column densities of Nh = 0 and 1022cm−2 respectively. We calculate φA for all three assuming the reference band is the 2 − 10 keV band of the pn. the reverberation lags dominate over the intrinsic hard l… view at source ↗
Figure 12
Figure 12. Figure 12: a: φA(ν) calculated using the default model param￾eters of reltransCp (default environment variables), assuming that the reference band is the 2 − 10 keV EPIC-pn flux. b: Time lag versus energy for the same parameters using the same cal￾culation for φA(ν). The black, red, green, blue, cyan, magenta, yellow, orange, light green and light blue lines (top to bottom) are calculated for different frequency ran… view at source ↗
Figure 14
Figure 14. Figure 14: Log-linear time lag as a function of energy (black), with the parameters chosen to roughly match the 1 − 30 Hz lag spectrum of GX 339-4 in observation ‘O1’ from De Marco et al. (2017) and Mahmoud et al. (2018). The red line is the time lag that would be observed by XMM-Newton assuming that the in￾trinsic lag-energy spectrum is given by the black (log-linear) line. To calculate this, we take the argument o… view at source ↗
Figure 15
Figure 15. Figure 15: Unfolded fake data and model (top) and fake data to model ratio (bottom). The data were generated from a model with a radial ionization profile calculated assuming a zone A Shakura-Sunyaev density profile. Left and right hand plots respectively show the results of fitting the input model and an alternative model with a single ionization parameter (red) plus an extra xillver component (grey). Results are f… view at source ↗
Figure 16
Figure 16. Figure 16: Left: Time lag as a function of energy in the frequency range [2−7.5] × 10−4 Hz for XMM-Newton data from Mrk 335 (black points), alongside three reltrans model fits (reference band: 0.3−10 keV). For the blue solid line, the black hole mass is a free parameter, and for the red dotted and yellow dashed lines we fix it to two different optical reverberation values from the literature. Right: Time lag, averag… view at source ↗
Figure 17
Figure 17. Figure 17: 2D χ 2 contour plot of black hole mass and source height resulting from fitting reltrans to the lag versus energy spectrum of Mrk 335 in the frequency range [2 − 7.5] × 10−4 Hz. The green cross marks the best fit and the blue crosses mark the best fit for for the two optical reverberation masses. height h and the boost parameter 1/B (for which we set the hard ranges > 2 Rg and 0 − 3 respectively). The blu… view at source ↗
read the original abstract

We present the publicly available model \textsc{reltrans} that calculates the light-crossing delays and energy shifts experienced by X-ray photons originally emitted close to the black hole when they reflect from the accretion disk and are scattered into our line-of-sight, accounting for all general relativistic effects. Our model is fast and flexible enough to be simultaneously fit to the observed energy-dependent cross-spectrum for a large range of Fourier frequencies, as well as to the time-averaged spectrum. This not only enables better geometric constraints than only modelling the relativistically broadened reflection features in the time-averaged spectrum, but additionally enables constraints on the mass of supermassive black holes in active galactic nuclei and stellar-mass black holes in X-ray binaries. We include a self-consistently calculated radial profile of the disk ionization parameter and properly account for the effect that the telescope response has on the predicted time lags. We find that a number of previous spectral analyses have measured artificially low source heights due to not accounting for the former effect and that timing analyses have been affected by the latter. In particular, the magnitude of the soft lags in active galactic nuclei may have been under-estimated, and the magnitude of lags attributed to thermal reverberation in X-ray binaries may have been over-estimated. We fit \textsc{reltrans} to the lag-energy spectrum of the Seyfert galaxy Mrk 335, resulting in a best fitting black hole mass that is smaller than previous optical reverberation measurements ($\sim 7$ million compared with $\sim14-26$ million $M_\odot$).

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

0 major / 3 minor

Summary. The manuscript introduces the publicly available reltrans model, which computes light-crossing delays and energy shifts for X-ray photons emitted near a black hole, reflected from the accretion disk, and observed after accounting for all general relativistic effects. The model incorporates a self-consistently calculated radial ionization profile of the disk and the effects of telescope response, and is designed to be fit simultaneously to time-averaged spectra and energy-dependent cross-spectra over a range of Fourier frequencies. Application to the lag-energy spectrum of Mrk 335 yields a best-fit black hole mass of approximately 7 million solar masses (smaller than prior optical reverberation estimates of 14-26 million solar masses), with the authors concluding that previous spectral analyses underestimated source heights due to neglecting the ionization profile and that timing analyses have been affected by not accounting for telescope response.

Significance. If the implementation and fits prove robust, reltrans represents a useful public tool for joint spectral-timing analysis that can tighten geometric and mass constraints on both supermassive and stellar-mass black holes. The emphasis on self-consistent ionization and proper treatment of instrument response addresses potential systematics in earlier work, and the public release supports reproducibility and community use.

minor comments (3)
  1. The abstract states that the radial ionization profile is calculated self-consistently from illuminating flux and disk density without additional free parameters, but the manuscript should explicitly state the assumed functional form of the density profile (e.g., in the methods section) to allow readers to assess whether this choice affects the predicted lags.
  2. The claim that prior spectral analyses measured artificially low source heights would be strengthened by a direct side-by-side comparison (perhaps in a table or figure) of fits with and without the ionization profile for the same dataset.
  3. The manuscript would benefit from including quantitative benchmarks (e.g., runtime per frequency bin or comparison to existing codes such as relxill) to support the statement that the model is 'fast and flexible enough' for simultaneous fitting.

Simulated Author's Rebuttal

0 responses · 0 unresolved

We thank the referee for their positive assessment of the manuscript and for recommending minor revision. The report highlights the utility of reltrans for joint spectral-timing analysis and notes the importance of self-consistent ionization and instrument response. No major comments were raised in the report.

Circularity Check

0 steps flagged

No significant circularity; forward GR transfer function model

full rationale

The paper constructs reltrans as an explicit forward computation of photon trajectories, light-crossing times, energy shifts and reflection spectra under general relativity, using a self-consistently computed ionization profile derived from illuminating flux and an assumed disk density (no free parameters added to alter lags). The Mrk 335 mass is obtained by fitting this model to observed lag-energy spectra; the output lags are not defined in terms of the fitted mass or height, nor does any equation reduce the result to a prior fit or self-citation. No load-bearing step matches any enumerated circularity pattern.

Axiom & Free-Parameter Ledger

2 free parameters · 2 axioms · 0 invented entities

The central claim rests on standard general-relativistic ray tracing and a domain-standard thin-disk reflection geometry; no new entities are postulated and the only fitted quantities are geometric parameters and black-hole mass.

free parameters (2)
  • black hole mass = ~7 million solar masses
    Fitted directly to the Mrk 335 lag-energy spectrum
  • source height
    Geometric parameter whose value affects the predicted lags and is noted to have been biased low in prior work
axioms (2)
  • standard math General-relativistic photon trajectories and energy shifts near a Kerr black hole
    Invoked throughout the model description as the basis for light-crossing delays
  • domain assumption Thin accretion disk with radially dependent ionization set by illuminating flux
    Self-consistent profile is stated as an improvement over prior constant-ionization assumptions

pith-pipeline@v0.9.0 · 5843 in / 1316 out tokens · 20318 ms · 2026-05-25T19:59:40.926546+00:00 · methodology

discussion (0)

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Reference graph

Works this paper leans on

136 extracted references · 136 canonical work pages · 9 internal anchors

  1. [1]

    write newline

    " write newline "" before.all 'output.state := FUNCTION fin.entry write newline FUNCTION new.block output.state before.all = 'skip after.block 'output.state := if FUNCTION new.sentence output.state after.block = 'skip output.state before.all = 'skip after.sentence 'output.state := if if FUNCTION not #0 #1 if FUNCTION and 'skip pop #0 if FUNCTION or pop #1...

  2. [2]

    Ar \'e valo P., Uttley P., 2006, @doi [ ] 10.1111/j.1365-2966.2006.09989.x , http://adsabs.harvard.edu/abs/2006MNRAS.367..801A 367, 801

  3. [3]

    M., Press W

    Bardeen J. M., Press W. H., Teukolsky S. A., 1972, @doi [ ] 10.1086/151796 , http://adsabs.harvard.edu/abs/1972ApJ...178..347B 178, 347

  4. [4]

    A., Parker M., Islam N., 2017, @doi [ ] 10.1093/mnras/stx2283 , http://adsabs.harvard.edu/abs/2017MNRAS.472.4220B 472, 4220

    Basak R., Zdziarski A. A., Parker M., Islam N., 2017, @doi [ ] 10.1093/mnras/stx2283 , http://adsabs.harvard.edu/abs/2017MNRAS.472.4220B 472, 4220

  5. [5]

    S., Piersol A

    Bendat J. S., Piersol A. G., 2010, Random Data: Analysis and measurement procedures; 4th edition . Wiley, 2010

  6. [6]

    Beuchert T., et al., 2017, @doi [ ] 10.1051/0004-6361/201630293 , http://adsabs.harvard.edu/abs/2017A

  7. [7]

    Testing the X-ray reverberation model KYNREFREV in a sample of Seyfert 1 Active Galactic Nuclei

    Caballero-Garcia M. D., Papadakis I. E., Dovciak M., Bursa M., Epitropakis A., Karas V., Svoboda J., 2018, preprint, http://adsabs.harvard.edu/abs/2018arXiv180403503C ( @eprint arXiv 1804.03503 )

  8. [8]

    M., Zoghbi A., Reynolds C., Fabian A

    Cackett E. M., Zoghbi A., Reynolds C., Fabian A. C., Kara E., Uttley P., Wilkins D. R., 2014, @doi [ ] 10.1093/mnras/stt2424 , http://adsabs.harvard.edu/abs/2014MNRAS.438.2980C 438, 2980

  9. [9]

    Caiazzo I., et al., 2019, arXiv e-prints, http://adsabs.harvard.edu/abs/2019arXiv190306760C

  10. [10]

    Campana S., Stella L., 1995, @doi [ ] 10.1093/mnras/272.3.585 , http://adsabs.harvard.edu/abs/1995MNRAS.272..585C 272, 585

  11. [11]

    Rev., 174, 1559

    Carter B., 1968, Phys. Rev., 174, 1559

  12. [12]

    J., 2015, @doi [ ] 10.1093/mnras/stv1333 , http://adsabs.harvard.edu/abs/2015MNRAS.452..333C 452, 333

    Chainakun P., Young A. J., 2015, @doi [ ] 10.1093/mnras/stv1333 , http://adsabs.harvard.edu/abs/2015MNRAS.452..333C 452, 333

  13. [13]

    J., 2017, @doi [ ] 10.1093/mnras/stw2964 , http://adsabs.harvard.edu/abs/2017MNRAS.465.3965C 465, 3965

    Chainakun P., Young A. J., 2017, @doi [ ] 10.1093/mnras/stw2964 , http://adsabs.harvard.edu/abs/2017MNRAS.465.3965C 465, 3965

  14. [14]

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

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

  15. [15]

    W., Falanga M., Fukumura K., Reynolds C

    Dauser T., Garcia J., Wilms J., B \"o ck M., Brenneman L. W., Falanga M., Fukumura K., Reynolds C. S., 2013, @doi [ ] 10.1093/mnras/sts710 , http://adsabs.harvard.edu/abs/2013MNRAS.430.1694D 430, 1694

  16. [16]

    L., Fabian A

    Dauser T., Garc \' a J., Parker M. L., Fabian A. C., Wilms J., 2014, @doi [ ] 10.1093/mnrasl/slu125 , http://adsabs.harvard.edu/abs/2014MNRAS.444L.100D 444, L100

  17. [17]

    J., Eikmann W., Kallman T., McClintock J., Wilms J., 2016, @doi [ ] 10.1051/0004-6361/201628135 , http://adsabs.harvard.edu/abs/2016A

    Dauser T., Garc \' a J., Walton D. J., Eikmann W., Kallman T., McClintock J., Wilms J., 2016, @doi [ ] 10.1051/0004-6361/201628135 , http://adsabs.harvard.edu/abs/2016A

  18. [18]

    M., Fabian A

    De Marco B., Ponti G., Cappi M., Dadina M., Uttley P., Cackett E. M., Fabian A. C., Miniutti G., 2013, @doi [ ] 10.1093/mnras/stt339 , http://adsabs.harvard.edu/abs/2013MNRAS.431.2441D 431, 2441

  19. [19]

    De Marco B., Ponti G., Mu \ n oz-Darias T., Nandra K., 2015, @doi [ ] 10.1088/0004-637X/814/1/50 , http://adsabs.harvard.edu/abs/2015ApJ...814...50D 814, 50

  20. [20]

    De Marco B., et al., 2017, @doi [ ] 10.1093/mnras/stx1649 , http://adsabs.harvard.edu/abs/2017MNRAS.471.1475D 471, 1475

  21. [21]

    M., Chakrabarty D., Harrison F

    Degenaar N., Miller J. M., Chakrabarty D., Harrison F. A., Kara E., Fabian A. C., 2015, @doi [ ] 10.1093/mnrasl/slv072 , http://adsabs.harvard.edu/abs/2015MNRAS.451L..85D 451, L85

  22. [22]

    Dexter J., Agol E., 2009, @doi [ ] 10.1088/0004-637X/696/2/1616 , http://adsabs.harvard.edu/abs/2009ApJ...696.1616D 696, 1616

  23. [23]

    Done C., Diaz Trigo M., 2010, @doi [ ] 10.1111/j.1365-2966.2010.17092.x , http://adsabs.harvard.edu/abs/2010MNRAS.407.2287D 407, 2287

  24. [24]

    Done C., Nayakshin S., 2007, @doi [ ] 10.1111/j.1745-3933.2007.00303.x , http://adsabs.harvard.edu/abs/2007MNRAS.377L..59D 377, L59

  25. [25]

    Done C., Gierlinski M., Kubota A., 2007, @doi [ ] 10.1007/s00159-007-0006-1 , http://adsabs.harvard.edu/abs/2007A

  26. [26]

    Dovciak M., 2004, PhD thesis

  27. [27]

    M., Lightman A

    Eardley D. M., Lightman A. P., Shapiro S. L., 1975, @doi [ ] 10.1086/181871 , http://adsabs.harvard.edu/abs/1975ApJ...199L.153E 199, L153

  28. [28]

    Ellis G. F. R., 2007, @doi [General Relativity and Gravitation] 10.1007/s10714-006-0355-5 , http://adsabs.harvard.edu/abs/2007GReGr..39.1047E 39, 1047

  29. [29]

    Ellis G. F. R., 2009, @doi [General Relativity and Gravitation] 10.1007/s10714-009-0760-7 , http://adsabs.harvard.edu/abs/2009GReGr..41..581E 41, 581

  30. [30]

    E., Dov c iak M., McHardy I

    Emmanoulopoulos D., Papadakis I. E., Dov c iak M., McHardy I. M., 2014, @doi [ ] 10.1093/mnras/stu249 , http://adsabs.harvard.edu/abs/2014MNRAS.439.3931E 439, 3931

  31. [31]

    E., 2017, @doi [ ] 10.1093/mnras/stx612 , http://adsabs.harvard.edu/abs/2017MNRAS.468.3568E 468, 3568

    Epitropakis A., Papadakis I. E., 2017, @doi [ ] 10.1093/mnras/stx612 , http://adsabs.harvard.edu/abs/2017MNRAS.468.3568E 468, 3568

  32. [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 , http://adsabs.harvard.edu/abs/2016A

  33. [33]

    Etherington I. M. H., 1933, Philosophical Magazine, http://adsabs.harvard.edu/abs/1933PMag...15..761E 15

  34. [34]

    C., Rees M

    Fabian A. C., Rees M. J., Stella L., White N. E., 1989, , http://adsabs.harvard.edu/abs/1989MNRAS.238..729F 238, 729

  35. [35]

    C., et al., 2009, @doi [ ] 10.1038/nature08007 , http://adsabs.harvard.edu/abs/2009Natur.459..540F 459, 540

    Fabian A. C., et al., 2009, @doi [ ] 10.1038/nature08007 , http://adsabs.harvard.edu/abs/2009Natur.459..540F 459, 540

  36. [36]

    and Shibahashi , H

    Fabian A. C., et al., 2012, @doi [ ] 10.1111/j.1365-2966.2012.21185.x , http://adsabs.harvard.edu/abs/2012MNRAS.424..217F 424, 217

  37. [37]

    Fender R., et al., 1999, @doi [ ] 10.1086/312128 , http://adsabs.harvard.edu/abs/1999ApJ...519L.165F 519, L165

  38. [38]

    A., Rosner R., Vaiana G

    Galeev A. A., Rosner R., Vaiana G. S., 1979, @doi [ ] 10.1086/156957 , http://adsabs.harvard.edu/abs/1979ApJ...229..318G 229, 318

  39. [39]

    R., 2010, @doi [ ] 10.1088/0004-637X/718/2/695 , http://adsabs.harvard.edu/abs/2010ApJ...718..695G 718, 695

    Garc \' a J., Kallman T. R., 2010, @doi [ ] 10.1088/0004-637X/718/2/695 , http://adsabs.harvard.edu/abs/2010ApJ...718..695G 718, 695

  40. [40]

    S., Kallman T

    Garc \' a J., Dauser T., Reynolds C. S., Kallman T. R., McClintock J. E., Wilms J., Eikmann W., 2013, @doi [ ] 10.1088/0004-637X/768/2/146 , http://adsabs.harvard.edu/abs/2013ApJ...768..146G 768, 146

  41. [41]

    Garc \' a J., et al., 2014, @doi [ ] 10.1088/0004-637X/782/2/76 , http://adsabs.harvard.edu/abs/2014ApJ...782...76G 782, 76

  42. [42]

    A., Steiner J

    Garc \' a J. A., Steiner J. F., McClintock J. E., Remillard R. A., Grinberg V., Dauser T., 2015, @doi [ ] 10.1088/0004-637X/813/2/84 , http://adsabs.harvard.edu/abs/2015ApJ...813...84G 813, 84

  43. [43]

    A., Fabian A

    Garc \' a J. A., Fabian A. C., Kallman T. R., Dauser T., Parker M. L., McClintock J. E., Steiner J. F., Wilms J., 2016, @doi [ ] 10.1093/mnras/stw1696 , http://adsabs.harvard.edu/abs/2016MNRAS.462..751G 462, 751

  44. [44]

    The Problem of the High Iron Abundance in Accretion Disks around Black Holes

    Garc \' a J. A., Kallman T. R., Bautista M., Mendoza C., Deprince J., Palmeri P., Quinet P., 2018, preprint, http://adsabs.harvard.edu/abs/2018arXiv180500581G ( @eprint arXiv 1805.00581 )

  45. [45]

    C., et al., 2016, in Space Telescopes and Instrumentation 2016: Ultraviolet to Gamma Ray

    Gendreau K. C., et al., 2016, in Space Telescopes and Instrumentation 2016: Ultraviolet to Gamma Ray. p. 99051H, @doi 10.1117/12.2231304

  46. [46]

    M., Fabian A

    George I. M., Fabian A. C., 1991, , http://adsabs.harvard.edu/abs/1991MNRAS.249..352G 249, 352

  47. [47]

    Gilfanov M., Churazov E., Revnivtsev M., 2000, @doi [ ] 10.1046/j.1365-8711.2000.03686.x , http://adsabs.harvard.edu/abs/2000MNRAS.316..923G 316, 923

  48. [48]

    J., et al., 2012, @doi [ ] 10.1088/2041-8205/744/1/L4 , http://adsabs.harvard.edu/abs/2012ApJ...744L...4G 744, L4

    Grier C. J., et al., 2012, @doi [ ] 10.1088/2041-8205/744/1/L4 , http://adsabs.harvard.edu/abs/2012ApJ...744L...4G 744, L4

  49. [49]

    Haardt F., Maraschi L., 1991, @doi [ ] 10.1086/186171 , http://adsabs.harvard.edu/abs/1991ApJ...380L..51H 380, L51

  50. [50]

    Harrison F. A. e. a., 2013, @doi [ ] 10.1088/0004-637X/770/2/103 , http://adsabs.harvard.edu/abs/2013ApJ...770..103H 770, 103

  51. [51]

    G., Torres M

    Heida M., Jonker P. G., Torres M. A. P., Chiavassa A., 2017, @doi [ ] 10.3847/1538-4357/aa85df , http://adsabs.harvard.edu/abs/2017ApJ...846..132H 846, 132

  52. [52]

    Ichimaru S., 1977, @doi [ ] 10.1086/155314 , http://adsabs.harvard.edu/abs/1977ApJ...214..840I 214, 840

  53. [53]

    Ingram A., van der Klis M. v. d., 2013, @doi [ ] 10.1093/mnras/stt1107 , http://adsabs.harvard.edu/abs/2013MNRAS.434.1476I 434, 1476

  54. [54]

    Ingram A., van der Klis M., 2015, @doi [ ] 10.1093/mnras/stu2373 , http://adsabs.harvard.edu/abs/2015MNRAS.446.3516I 446, 3516

  55. [55]

    J., Poutanen J., Krawczynski H., 2015, @doi [ ] 10.1088/0004-637X/807/1/53 , http://adsabs.harvard.edu/abs/2015ApJ...807...53I 807, 53

    Ingram A., Maccarone T. J., Poutanen J., Krawczynski H., 2015, @doi [ ] 10.1088/0004-637X/807/1/53 , http://adsabs.harvard.edu/abs/2015ApJ...807...53I 807, 53

  56. [56]

    Ingram A., van der Klis M., Middleton M., Done C., Altamirano D., Heil L., Uttley P., Axelsson M., 2016, @doi [ ] 10.1093/mnras/stw1245 , http://adsabs.harvard.edu/abs/2016MNRAS.461.1967I 461, 1967

  57. [57]

    Ingram A., van der Klis M., Middleton M., Altamirano D., Uttley P., 2017, @doi [ ] 10.1093/mnras/stw2581 , http://adsabs.harvard.edu/abs/2017MNRAS.464.2979I 464, 2979

  58. [58]

    Jansen F., et al., 2001, @doi [ ] 10.1051/0004-6361:20000036 , http://adsabs.harvard.edu/abs/2001A

  59. [59]

    W., 2019, arXiv e-prints, http://adsabs.harvard.edu/abs/2019arXiv190401674J

    Jiang Y.-F., Blaes O., Stone J., Davis S. W., 2019, arXiv e-prints, http://adsabs.harvard.edu/abs/2019arXiv190401674J

  60. [60]

    Kalberla P. M. W., Burton W. B., Hartmann D., Arnal E. M., Bajaja E., Morras R., P \"o ppel W. G. L., 2005, @doi [ ] 10.1051/0004-6361:20041864 , http://adsabs.harvard.edu/abs/2005A

  61. [61]

    S., Dom c ek V., Svoboda J., Dov c iak M., Matt G., 2019, @doi [ ] 10.1093/mnras/stz408 , http://adsabs.harvard.edu/abs/2019MNRAS.485..239K 485, 239

    Kammoun E. S., Dom c ek V., Svoboda J., Dov c iak M., Matt G., 2019, @doi [ ] 10.1093/mnras/stz408 , http://adsabs.harvard.edu/abs/2019MNRAS.485..239K 485, 239

  62. [62]

    C., Cackett E

    Kara E., Fabian A. C., Cackett E. M., Uttley P., Wilkins D. R., Zoghbi A., 2013, @doi [ ] 10.1093/mnras/stt1055 , http://adsabs.harvard.edu/abs/2013MNRAS.434.1129K 434, 1129

  63. [63]

    Kara E., et al., 2015, @doi [ ] 10.1093/mnras/stv304 , http://adsabs.harvard.edu/abs/2015MNRAS.449..234K 449, 234

  64. [64]

    N., Fabian A

    Kara E., Alston W. N., Fabian A. C., Cackett E. M., Uttley P., Reynolds C. S., Zoghbi A., 2016, @doi [ ] 10.1093/mnras/stw1695 , http://adsabs.harvard.edu/abs/2016MNRAS.462..511K 462, 511

  65. [65]

    Kara E., et al., 2019, @doi [ ] 10.1038/s41586-018-0803-x , http://adsabs.harvard.edu/abs/2019Natur.565..198K 565, 198

  66. [66]

    R., 2016, @doi [ ] 10.1093/mnras/stv2882 , http://adsabs.harvard.edu/abs/2016MNRAS.456.2722K 456, 2722

    Keek L., Ballantyne D. R., 2016, @doi [ ] 10.1093/mnras/stv2882 , http://adsabs.harvard.edu/abs/2016MNRAS.456.2722K 456, 2722

  67. [67]

    Kolehmainen M., Done C., D \' az Trigo M., 2014, @doi [ ] 10.1093/mnras/stt1886 , http://adsabs.harvard.edu/abs/2014MNRAS.437..316K 437, 316

  68. [68]

    Kotov O., Churazov E., Gilfanov M., 2001, @doi [ ] 10.1046/j.1365-8711.2001.04769.x , http://adsabs.harvard.edu/abs/2001MNRAS.327..799K 327, 799

  69. [69]

    Laor A., 1991, @doi [ ] 10.1086/170257 , http://adsabs.harvard.edu/abs/1991ApJ...376...90L 376, 90

  70. [70]

    P., Rybicki G

    Lightman A. P., Rybicki G. B., 1980, @doi [ ] 10.1086/157820 , http://adsabs.harvard.edu/abs/1980ApJ...236..928L 236, 928

  71. [71]

    W., 1966, @doi [Annals of Physics] 10.1016/0003-4916(66)90207-7 , http://adsabs.harvard.edu/abs/1966AnPhy..37..487L 37, 487

    Lindquist R. W., 1966, @doi [Annals of Physics] 10.1016/0003-4916(66)90207-7 , http://adsabs.harvard.edu/abs/1966AnPhy..37..487L 37, 487

  72. [72]

    A Physical Model for the Spectral-Timing Properties of Accreting Black Holes

    Mahmoud R. D., Done C., 2018, preprint, http://adsabs.harvard.edu/abs/2018arXiv180304811M ( @eprint arXiv 1803.04811 )

  73. [73]

    D., Done C., De Marco B., 2018, preprint, http://adsabs.harvard.edu/abs/2018arXiv181106911M ( @eprint arXiv 1811.06911 )

    Mahmoud R. D., Done C., De Marco B., 2018, preprint, http://adsabs.harvard.edu/abs/2018arXiv181106911M ( @eprint arXiv 1811.06911 )

  74. [74]

    A., Wilms J., 2005, @doi [ ] 10.1086/497628 , http://adsabs.harvard.edu/abs/2005ApJ...635.1203M 635, 1203

    Markoff S., Nowak M. A., Wilms J., 2005, @doi [ ] 10.1086/497628 , http://adsabs.harvard.edu/abs/2005ApJ...635.1203M 635, 1203

  75. [75]

    Martocchia A., Matt G., 1996, @doi [ ] 10.1093/mnras/282.4.L53 , http://adsabs.harvard.edu/abs/1996MNRAS.282L..53M 282, L53

  76. [76]

    Mastroserio G., Ingram A., van der Klis M., 2018, @doi [ ] 10.1093/mnras/sty075 , http://adsabs.harvard.edu/abs/2018MNRAS.475.4027M 475, 4027

  77. [77]

    C., Piro L., 1991, , http://adsabs.harvard.edu/abs/1991A

    Matt G., Perola G. C., Piro L., 1991, , http://adsabs.harvard.edu/abs/1991A

  78. [78]

    M., Papadakis I

    McHardy I. M., Papadakis I. E., Uttley P., Page M. J., Mason K. O., 2004, @doi [ ] 10.1111/j.1365-2966.2004.07376.x , http://adsabs.harvard.edu/abs/2004MNRAS.348..783M 348, 783

  79. [79]

    Black hole spin: theory and observation

    Middleton M., 2016, in Bambi C., ed., Astrophysics and Space Science Library Vol. 440, Astrophysics of Black Holes: From Fundamental Aspects to Latest Developments. p. 99 ( @eprint arXiv 1507.06153 ), @doi 10.1007/978-3-662-52859-4_3

  80. [80]

    Dissipation production in a closed two-level quantum system as a test of the obversibility of the dynamics

    Miller J. M., 2007, @doi [ ] 10.1146/annurev.astro.45.051806.110555 , http://adsabs.harvard.edu/abs/2007ARA

Showing first 80 references.