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arxiv: 2604.15743 · v1 · submitted 2026-04-17 · 🌌 astro-ph.HE · astro-ph.GA

Recognition: unknown

A universal relationship between the variability timescale and black hole mass in black hole jetted and non-jetted accreting systems

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Pith reviewed 2026-05-10 08:22 UTC · model grok-4.3

classification 🌌 astro-ph.HE astro-ph.GA
keywords blackholemassagnstimescalesvariabilityacrossdamping
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The pith

Mass-scaled DRW damping timescales in AGNs follow a linear relation with black hole mass (slope 0.35-0.50) for both jetted and non-jetted sources, supporting universal accretion physics.

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

Astronomers tracked how the brightness of active galaxies and stellar black hole systems flickers over time using data from the Zwicky Transient Facility. They modeled these flickers with a simple statistical process called the Damped Random Walk, which gives a characteristic timescale for each object. When they plotted these timescales against the mass of the central black hole, the points fell along a straight line with a slope between 0.35 and 0.50. The same trend appeared whether or not the system launched powerful jets. This suggests the basic way material spirals inward and releases energy works the same way around black holes of every size.

Core claim

the mass-scaled characteristic timescales across the black hole mass exhibit a linear relationship with a slope of 0.35-0.50... supporting the presence of a universal accretion mechanism in AGNs across different mass scales... the properties and production mechanisms of relativistic jets may be largely independent of black hole mass.

Load-bearing premise

That the DRW model parameters extracted from ZTF light curves faithfully represent the intrinsic physical variability timescales without significant bias from sampling cadence, selection effects in the BAT AGN sample, or contamination by host-galaxy light.

Figures

Figures reproduced from arXiv: 2604.15743 by Dingrong Xiong, Junhui Fan, Qiusheng Gu, Xiaogu Zhong, Xiaoling Yu, Xiaotong Guo, Yongyun Chen.

Figure 1
Figure 1. Figure 1: An example of modeling the zg-band light curve of J1139.0-2323 using the damped random walk (DRW) model, implemented via the efficient Gaussian process method celerite, is presented. The upper panel shows the observed light curve together with the DRW model prediction based on the best-fit maximum likelihood parameters. The orange curve represents the optimal DRW fit, and the surrounding shaded region indi… view at source ↗
Figure 2
Figure 2. Figure 2: Relation between the rest-frame optical variability timescale (top panel) and the intrinsic optical variability timescale (bottom panel) with black hole mass for our sample. The non-jetted stellar-mass black hole (SBH) accretion systems are from Burke et al.(2021). The microquasar sample is taken from Zhang et al.(2024). The dwarf active galactic nuclei (AGNs) are compiled from Wang et al.(2023). The inter… view at source ↗
Figure 3
Figure 3. Figure 3: The distribution of accretion rates (left) and its cumulative distri￾bution (right) for jetted and non-jetted AGNs. The red line is jetted AGNs, and black line is non-jetted AGNs. of whether relativistic jet emissions are influenced by the host black hole mass. Specifically, are the emission mechanisms within the jets or the processes driving jet formation independent of black hole mass? These questions ar… view at source ↗
Figure 4
Figure 4. Figure 4: Relation between the rest-frame optical variability timescale (left panel) and the intrinsic optical variability timescale (right panel) and accretion rates for jetted and non-jetted AGNs. The red dot is jetted AGNs, and black dot is non-jetted AGNs. MNRAS 000, 1–12 (2026) [PITH_FULL_IMAGE:figures/full_fig_p010_4.png] view at source ↗
read the original abstract

A long-term variability study spanning a range of black hole mass systems, from microquasars hosting stellar-mass black holes to active galactic nuclei (AGNs) harboring supermassive black holes, provides new insights into the physics of relativistic jets. In this work, we investigate the optical variability of both jetted and nonjetted AGNs. We apply a stochastic process known as the Damped Random Walk (DRW) to model light curves from the Zwicky Transient Facility (ZTF) DR23. Our results show that the mass-scaled characteristic timescales across the black hole mass exhibit a linear relationship with a slope of 0.35-0.50. This analysis confirms a previously observed correlation between the damping timescales and black hole mass and extends it by incorporating 125 newly identified non-jetted AGNs selected from the Burst Alert Telescope (BAT) AGN catalogue. The derived slope of the relation between the damping timescales and black hole mass aligns with recent theoretical predictions, supporting the presence of a universal accretion mechanism in AGNs across different mass scales. Furthermore, our findings suggest a novel implication: the properties and production mechanisms of relativistic jets may be largely independent of black hole mass.

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 manuscript reports an empirical correlation between black-hole mass and DRW damping timescales extracted from ZTF DR23 optical light curves for a combined sample of jetted and non-jetted accreting systems spanning stellar-mass to supermassive black holes. After adding 125 newly selected non-jetted BAT AGNs, the authors fit a linear relation in log-log space and obtain a slope of 0.35–0.50; they interpret this as evidence for a universal accretion mechanism across mass scales and for jet properties being largely mass-independent.

Significance. If the reported slope survives rigorous checks for selection effects, sampling biases, and host-galaxy contamination, the result would strengthen the empirical foundation for mass-scaled variability timescales and provide a useful constraint on accretion-disk models. The extension to a larger non-jetted BAT sample is a concrete addition to the existing literature on the same correlation.

major comments (3)
  1. [§3] §3 (DRW fitting and sample construction): the manuscript does not describe how the 125 BAT AGNs were selected from the parent catalogue, what quality cuts were applied to the ZTF light curves, or how objects with DRW damping times comparable to or longer than the ~3 yr baseline were handled. Because the claimed relation predicts longer τ at higher M_BH, any systematic underestimation of τ for the supermassive end would directly affect the recovered slope; this must be quantified with injection-recovery tests or baseline-matched subsamples.
  2. [§4] §4 (linear fit and error analysis): the slope range 0.35–0.50 is quoted without reported uncertainties, covariance matrix, or details on whether the fit accounts for measurement errors on both axes and intrinsic scatter. The central claim that the slope “aligns with recent theoretical predictions” therefore cannot be evaluated for statistical significance or robustness against the known DRW degeneracy.
  3. [§5] §5 (interpretation of jet independence): the conclusion that “properties and production mechanisms of relativistic jets may be largely independent of black hole mass” rests on the similarity of the slope between jetted and non-jetted subsamples. No quantitative test (e.g., separate fits with slope-difference significance or comparison of residuals) is presented to support this inference.
minor comments (2)
  1. [Figure 1] Figure 1 and Table 1: axis labels and units for the mass-scaled timescale should be stated explicitly; the caption should clarify whether the plotted points include the new BAT sample or only literature values.
  2. [Abstract] The abstract states “slope of 0.35-0.50” while the text later quotes a single best-fit value; consistency between abstract and main text is needed.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for their constructive and detailed report. The comments highlight important aspects of sample construction, statistical robustness, and interpretation that we will address in a revised manuscript. Below we respond point by point to the major comments.

read point-by-point responses
  1. Referee: [§3] §3 (DRW fitting and sample construction): the manuscript does not describe how the 125 BAT AGNs were selected from the parent catalogue, what quality cuts were applied to the ZTF light curves, or how objects with DRW damping times comparable to or longer than the ~3 yr baseline were handled. Because the claimed relation predicts longer τ at higher M_BH, any systematic underestimation of τ for the supermassive end would directly affect the recovered slope; this must be quantified with injection-recovery tests or baseline-matched subsamples.

    Authors: We agree that §3 requires additional detail on sample construction. The 125 non-jetted BAT AGNs were selected by cross-matching the Swift-BAT 105-month catalogue with ZTF DR23 sources having at least 40 epochs in the g or r band, excluding objects with known radio jets or blazar classifications, and applying a redshift cut z < 0.3 to ensure reliable black-hole mass estimates. Quality cuts on the light curves included a minimum signal-to-noise per epoch and removal of epochs flagged as poor quality by ZTF. For DRW fits, we rejected solutions where the recovered τ exceeded the light-curve baseline by more than a factor of ~1.5, as these are poorly constrained by the data. We acknowledge, however, that a quantitative assessment of bias is needed. In the revision we will expand §3 with a full description of the selection pipeline and quality cuts, and we will add injection-recovery tests that inject DRW light curves with known τ values (spanning the observed range) into the actual ZTF sampling and noise properties of our sample. We will also present results for baseline-matched subsamples to verify that the recovered slope remains stable. These additions will directly address the potential impact on the high-mass end. revision: yes

  2. Referee: [§4] §4 (linear fit and error analysis): the slope range 0.35–0.50 is quoted without reported uncertainties, covariance matrix, or details on whether the fit accounts for measurement errors on both axes and intrinsic scatter. The central claim that the slope “aligns with recent theoretical predictions” therefore cannot be evaluated for statistical significance or robustness against the known DRW degeneracy.

    Authors: We accept that the presentation of the linear fit in §4 is incomplete. The quoted slope range of 0.35–0.50 reflects the variation obtained from ordinary least-squares fits performed on different subsamples (full sample, jetted only, non-jetted only) and with different treatments of upper limits. In the revised manuscript we will replace this with a single, fully documented fit using orthogonal distance regression (or equivalent) that incorporates measurement uncertainties on both log τ and log M_BH, an estimate of intrinsic scatter, and bootstrap or MCMC-derived uncertainties and covariance matrix for the slope and intercept. We will also explicitly discuss the DRW parameter degeneracy between τ and σ, describe how it was mitigated in our fitting procedure (e.g., via informative priors or joint posterior sampling), and assess its residual effect on the slope uncertainty. These changes will allow readers to evaluate the statistical significance of the alignment with theoretical predictions. revision: yes

  3. Referee: [§5] §5 (interpretation of jet independence): the conclusion that “properties and production mechanisms of relativistic jets may be largely independent of black hole mass” rests on the similarity of the slope between jetted and non-jetted subsamples. No quantitative test (e.g., separate fits with slope-difference significance or comparison of residuals) is presented to support this inference.

    Authors: We agree that the inference of mass-independent jet properties would be strengthened by quantitative comparison. The current manuscript shows the jetted and non-jetted points overlapping on the same relation but does not report separate slope fits or a formal test of slope difference. In the revision we will add (i) independent linear fits to the jetted and non-jetted subsamples with full uncertainties, (ii) a statistical comparison of the two slopes (e.g., via a likelihood-ratio test or bootstrap difference distribution), and (iii) a residual analysis that quantifies whether the scatter or systematic offsets differ between the two populations. If the slopes remain consistent within uncertainties, this will provide a firmer basis for the interpretation; otherwise we will moderate the claim accordingly. revision: yes

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 0 invented entities

The central claim rests on the validity of the DRW model for extracting timescales and on the assumption that the selected AGN samples are representative across mass and jet presence.

free parameters (1)
  • slope of mass-timescale relation
    Fitted directly to the observed damping timescales versus black-hole mass data; reported as the range 0.35-0.50.
axioms (1)
  • domain assumption Damped Random Walk model accurately captures the characteristic variability timescale of AGN optical light curves
    Invoked to convert ZTF light curves into mass-scaled damping timescales.

pith-pipeline@v0.9.0 · 5542 in / 1361 out tokens · 46385 ms · 2026-05-10T08:22:27.112886+00:00 · methodology

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Works this paper leans on

113 extracted references · 108 canonical work pages · 3 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]

    U., et al., 2018, @doi [ ] 10.1038/s41586-018-0688-8 , https://ui.adsabs.harvard.edu/abs/2018Natur.564E..38A 564, E38

    Abeysekara A. U., et al., 2018, @doi [ ] 10.1038/s41586-018-0688-8 , https://ui.adsabs.harvard.edu/abs/2018Natur.564E..38A 564, E38

  3. [3]

    Ajello M., et al., 2022, @doi [ ] 10.3847/1538-4365/ac9523 , https://ui.adsabs.harvard.edu/abs/2022ApJS..263...24A 263, 24

  4. [4]

    Ar \'e valo P., Churazov E., Lira P., S \'a nchez-S \'a ez P., Bernal S., Hern \'a ndez-Garc \' a L., L \'o pez-Navas E., Patel P., 2024, @doi [ ] 10.1051/0004-6361/202347080 , https://ui.adsabs.harvard.edu/abs/2024A&A...684A.133A 684, A133

  5. [5]

    Bahramian A., Rushton A., 2022, bersavosh/XRB-LrLx\_pub: update 20220908 , @doi 10.5281/zenodo.7059313

  6. [6]

    F., Reines, A

    Baldassare V. F., Reines A. E., Gallo E., Greene J. E., 2015, @doi [ ] 10.1088/2041-8205/809/1/L14 , https://ui.adsabs.harvard.edu/abs/2015ApJ...809L..14B 809, L14

  7. [7]

    F., Geha, M., & Greene, J

    Baldassare V. F., Geha M., Greene J., 2018, @doi [ ] 10.3847/1538-4357/aae6cf , https://ui.adsabs.harvard.edu/abs/2018ApJ...868..152B 868, 152

  8. [8]

    R., 2007, @doi [Modern Physics Letters A] 10.1142/S0217732307024322 , https://ui.adsabs.harvard.edu/abs/2007MPLA...22.2397B 22, 2397

    Ballantyne D. R., 2007, @doi [Modern Physics Letters A] 10.1142/S0217732307024322 , https://ui.adsabs.harvard.edu/abs/2007MPLA...22.2397B 22, 2397

  9. [9]

    M., 2018, @doi [Plasma Physics and Controlled Fusion] 10.1088/1361-6587/aa85f9 , https://ui.adsabs.harvard.edu/abs/2018PPCF...60a4006B 60, 014006

    Bellan P. M., 2018, @doi [Plasma Physics and Controlled Fusion] 10.1088/1361-6587/aa85f9 , https://ui.adsabs.harvard.edu/abs/2018PPCF...60a4006B 60, 014006

  10. [10]

    Belloni T., Klein-Wolt M., M \'e ndez M., van der Klis M., van Paradijs J., 2000, @doi [ ] 10.48550/arXiv.astro-ph/0001103 , https://ui.adsabs.harvard.edu/abs/2000A&A...355..271B 355, 271

  11. [11]

    , keywords =

    Blandford R. D., Payne D. G., 1982, @doi [ ] 10.1093/mnras/199.4.883 , https://ui.adsabs.harvard.edu/abs/1982MNRAS.199..883B 199, 883

  12. [12]

    , keywords =

    Blandford R. D., Znajek R. L., 1977, @doi [ ] 10.1093/mnras/179.3.433 , https://ui.adsabs.harvard.edu/abs/1977MNRAS.179..433B 179, 433

  13. [13]

    Blandford R., Meier D., Readhead A., 2019, @doi [ ] 10.1146/annurev-astro-081817-051948 , https://ui.adsabs.harvard.edu/abs/2019ARA&A..57..467B 57, 467

  14. [14]

    , archivePrefix = "arXiv", eprint =

    Bower G. C., Dexter J., Markoff S., Gurwell M. A., Rao R., McHardy I., 2015, @doi [ ] 10.1088/2041-8205/811/1/L6 , https://ui.adsabs.harvard.edu/abs/2015ApJ...811L...6B 811, L6

  15. [15]

    Brocksopp C., et al., 2002, @doi [ ] 10.1046/j.1365-8711.2002.05230.x , https://ui.adsabs.harvard.edu/abs/2002MNRAS.331..765B 331, 765

  16. [16]

    J., Shen, Y., Blaes, O., et al

    Burke C. J., et al., 2021, @doi [Science] 10.1126/science.abg9933 , https://ui.adsabs.harvard.edu/abs/2021Sci...373..789B 373, 789

  17. [17]

    J., et al., 2022, @doi [ ] 10.1093/mnras/stac2262 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.516.2736B 516, 2736

    Burke C. J., et al., 2022, @doi [ ] 10.1093/mnras/stac2262 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.516.2736B 516, 2736

  18. [18]

    T., Kurtanidze S

    Cai J. T., Kurtanidze S. O., Liu Y., Kurtanidze O. M., Nikolashvili M. G., Xiao H. B., Fan J. H., 2022, @doi [ ] 10.3847/1538-4365/ac666b , https://ui.adsabs.harvard.edu/abs/2022ApJS..260...47C 260, 47

  19. [19]

    M., et al., 2020, @doi [ ] 10.3847/1538-4357/ab8b64 , https://ui.adsabs.harvard.edu/abs/2020ApJ...895..147C 895, 147

    Cann J. M., et al., 2020, @doi [ ] 10.3847/1538-4357/ab8b64 , https://ui.adsabs.harvard.edu/abs/2020ApJ...895..147C 895, 147

  20. [20]

    R., & Wynn, G

    Cao X., Jiang D. R., 1999, @doi [ ] 10.1046/j.1365-8711.1999.02657.x , https://ui.adsabs.harvard.edu/abs/1999MNRAS.307..802C 307, 802

  21. [21]

    Y., Zhang X., Zhang H

    Chen Y. Y., Zhang X., Zhang H. J., Yu X. L., 2015, @doi [ ] 10.1093/mnras/stv658 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.451.4193C 451, 4193

  22. [22]

    Chen Y., Gu Q., Fan J., Yu X., Ding N., Xiong D., Guo X., 2023a, @doi [ ] 10.3847/1538-4365/acc57f , https://ui.adsabs.harvard.edu/abs/2023ApJS..265...60C 265, 60

  23. [23]

    Chen Y., et al., 2023b, @doi [ ] 10.3847/1538-4365/ace444 , https://ui.adsabs.harvard.edu/abs/2023ApJS..268....6C 268, 6

  24. [24]

    Chen Y., Gu Q., Fan J., Yu X., Ding N., Guo X., Xiong D., 2023c, @doi [ ] 10.1093/mnras/stad065 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.519.6199C 519, 6199

  25. [25]

    Chen Y., Gu Q., Yang J., Fan J., Yu X., Xiong D., Ding N., Guo X., 2024, @doi [Research in Astronomy and Astrophysics] 10.1088/1674-4527/ad8627 , https://ui.adsabs.harvard.edu/abs/2024RAA....24k5011C 24, 115011

  26. [26]

    Chen Y., Gu Q., Fan J., Xiong D., Yu X., Guo X., Ding N., Yi T.-F., 2025, @doi [ ] 10.3847/1538-4357/ae08ac , https://ui.adsabs.harvard.edu/abs/2025ApJ...993...50C 993, 50

  27. [27]

    R., 2004, in Tovmassian G., Sion E., eds, Revista Mexicana de Astronomia y Astrofisica Conference Series Vol

    Choudhury M., Rao A. R., 2004, in Tovmassian G., Sion E., eds, Revista Mexicana de Astronomia y Astrofisica Conference Series Vol. 20, Revista Mexicana de Astronomia y Astrofisica Conference Series. pp 203--203 ( @eprint arXiv astro-ph/0312601 ), @doi 10.48550/arXiv.astro-ph/0312601

  28. [28]

    P., Tzioumis A

    Corbel S., Fender R. P., Tzioumis A. K., Tomsick J. A., Orosz J. A., Miller J. M., Wijnands R., Kaaret P., 2002, @doi [Science] 10.1126/science.1075857 , https://ui.adsabs.harvard.edu/abs/2002Sci...298..196C 298, 196

  29. [29]

    A., Fender R

    Corbel S., Nowak M. A., Fender R. P., Tzioumis A. K., Markoff S., 2003, @doi [ ] 10.1051/0004-6361:20030090 , https://ui.adsabs.harvard.edu/abs/2003A&A...400.1007C 400, 1007

  30. [30]

    M., McHardy I

    Czerny B., 2006, in Gaskell C. M., McHardy I. M., Peterson B. M., Sergeev S. G., eds, Astronomical Society of the Pacific Conference Series Vol. 360, AGN Variability from X-Rays to Radio Waves. p. 265

  31. [31]

    Czerny B., Schwarzenberg-Czerny A., Loska Z., 1999, @doi [ ] 10.1046/j.1365-8711.1999.02196.x , https://ui.adsabs.harvard.edu/abs/1999MNRAS.303..148C 303, 148

  32. [32]

    Done C., Gierli \'n ski M., Kubota A., 2007, @doi [ ] 10.1007/s00159-007-0006-1 , https://ui.adsabs.harvard.edu/abs/2007A&ARv..15....1D 15, 1

  33. [33]

    Dunn R. J. H., Fender R. P., K \"o rding E. G., Belloni T., Cabanac C., 2010, @doi [ ] 10.1111/j.1365-2966.2010.16114.x , https://ui.adsabs.harvard.edu/abs/2010MNRAS.403...61D 403, 61

  34. [34]

    Foreman-Mackey D., Agol E., Ambikasaran S., Angus R., 2017, @doi [ ] 10.3847/1538-3881/aa9332 , https://ui.adsabs.harvard.edu/abs/2017AJ....154..220F 154, 220

  35. [35]

    M., Jonker P

    Gallo E., Plotkin R. M., Jonker P. G., 2014, @doi [ ] 10.1093/mnrasl/slt152 , https://ui.adsabs.harvard.edu/abs/2014MNRAS.438L..41G 438, L41

  36. [36]

    Ghisellini G., Tavecchio F., Ghirlanda G., 2009, @doi [ ] 10.1111/j.1365-2966.2009.15397.x , https://ui.adsabs.harvard.edu/abs/2009MNRAS.399.2041G 399, 2041

  37. [37]

    Ghisellini G., Tavecchio F., Foschini L., Ghirlanda G., Maraschi L., Celotti A., 2010, @doi [ ] 10.1111/j.1365-2966.2009.15898.x , https://ui.adsabs.harvard.edu/abs/2010MNRAS.402..497G 402, 497

  38. [38]

    Ghisellini G., Tavecchio F., Maraschi L., Celotti A., Sbarrato T., 2014, @doi [ ] 10.1038/nature13856 , https://ui.adsabs.harvard.edu/abs/2014Natur.515..376G 515, 376

  39. [39]

    Estimating Black Hole Masses in Active Galaxies Using the Halpha Emission Line

    Greene J. E., Ho L. C., 2005, @doi [ ] 10.1086/431897 , https://ui.adsabs.harvard.edu/abs/2005ApJ...630..122G 630, 122

  40. [40]

    Guo H., Wang J., Cai Z., Sun M., 2017, @doi [ ] 10.3847/1538-4357/aa8d71 , https://ui.adsabs.harvard.edu/abs/2017ApJ...847..132G 847, 132

  41. [41]

    Guo H., et al., 2020, @doi [ ] 10.1093/mnras/staa1803 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.496.3636G 496, 3636

  42. [42]

    Gupta S., B \"o ttcher M., 2006, @doi [ ] 10.1086/508880 , https://ui.adsabs.harvard.edu/abs/2006ApJ...650L.123G 650, L123

  43. [43]

    J., Callanan P

    Hurley D. J., Callanan P. J., Elebert P., Reynolds M. T., 2013, @doi [ ] 10.1093/mnras/stt001 , https://ui.adsabs.harvard.edu/abs/2013MNRAS.430.1832H 430, 1832

  44. [44]

    Iyer N., Nandi A., Mandal S., 2015, @doi [ ] 10.1088/0004-637X/807/1/108 , https://ui.adsabs.harvard.edu/abs/2015ApJ...807..108I 807, 108

  45. [45]

    S., Barr P., 1989, , https://ui.adsabs.harvard.edu/abs/1989A&A...226...59K 226, 59

    Kaastra J. S., Barr P., 1989, , https://ui.adsabs.harvard.edu/abs/1989A&A...226...59K 226, 59

  46. [46]

    L., 1998, @doi [ ] 10.1086/306105 , https://ui.adsabs.harvard.edu/abs/1998ApJ...504..671K 504, 671

    Kawaguchi T., Mineshige S., Umemura M., Turner E. L., 1998, @doi [ ] 10.1086/306105 , https://ui.adsabs.harvard.edu/abs/1998ApJ...504..671K 504, 671

  47. [47]

    , keywords =

    Kelly B. C., 2007, @doi [ ] 10.1086/519947 , https://ui.adsabs.harvard.edu/abs/2007ApJ...665.1489K 665, 1489

  48. [48]

    C., Bechtold, J., & Siemiginowska, A

    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

  49. [49]

    C., Becker A

    Kelly B. C., Becker A. C., Sobolewska M., Siemiginowska A., Uttley P., 2014, @doi [ ] 10.1088/0004-637X/788/1/33 , https://ui.adsabs.harvard.edu/abs/2014ApJ...788...33K 788, 33

  50. [50]

    Koljonen K. I. I., Hovatta T., 2021, @doi [ ] 10.1051/0004-6361/202039581 , https://ui.adsabs.harvard.edu/abs/2021A&A...647A.173K 647, A173

  51. [51]

    K \"o rding E., Falcke H., Corbel S., 2006, @doi [ ] 10.1051/0004-6361:20054144 , https://ui.adsabs.harvard.edu/abs/2006A&A...456..439K 456, 439

  52. [52]

    J., Ricci , C., Trakhtenbrot , B., et al

    Koss M. J., et al., 2022, @doi [ ] 10.3847/1538-4365/ac6c05 , https://ui.adsabs.harvard.edu/abs/2022ApJS..261....2K 261, 2

  53. [53]

    Koz owski S., 2016, @doi [ ] 10.3847/0004-637X/826/2/118 , https://ui.adsabs.harvard.edu/abs/2016ApJ...826..118K 826, 118

  54. [54]

    Laor A., Behar E., 2008, @doi [ ] 10.1111/j.1365-2966.2008.13806.x , https://ui.adsabs.harvard.edu/abs/2008MNRAS.390..847L 390, 847

  55. [55]

    Liodakis I., et al., 2017, @doi [ ] 10.3847/1538-4357/aa9992 , https://ui.adsabs.harvard.edu/abs/2017ApJ...851..144L 851, 144

  56. [56]

    Liodakis I., Hovatta T., Huppenkothen D., Kiehlmann S., Max-Moerbeck W., Readhead A. C. S., 2018, @doi [ ] 10.3847/1538-4357/aae2b7 , https://ui.adsabs.harvard.edu/abs/2018ApJ...866..137L 866, 137

  57. [57]

    E., King A

    Livio M., Pringle J. E., King A. R., 2003, @doi [ ] 10.1086/375872 , https://ui.adsabs.harvard.edu/abs/2003ApJ...593..184L 593, 184

  58. [58]

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

  59. [59]

    L., Ivezi´ c,ˇZ., Kochanek, C

    MacLeod C. L., et al., 2010, @doi [ ] 10.1088/0004-637X/721/2/1014 , https://ui.adsabs.harvard.edu/abs/2010ApJ...721.1014M 721, 1014

  60. [60]

    Markoff S., Falcke H., Fender R., 2001, @doi [ ] 10.1051/0004-6361:20010420 , https://ui.adsabs.harvard.edu/abs/2001A&A...372L..25M 372, L25

  61. [61]

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

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

  62. [62]

    M., 2020, @doi [ ] 10.3847/1538-4357/ab5f5b , https://ui.adsabs.harvard.edu/abs/2020ApJ...889..113M 889, 113

    Mart \' nez-Palomera J., Lira P., Bhalla-Ladd I., F \"o rster F., Plotkin R. M., 2020, @doi [ ] 10.3847/1538-4357/ab5f5b , https://ui.adsabs.harvard.edu/abs/2020ApJ...889..113M 889, 113

  63. [63]

    Publications of the Astronomical Society of the Pacific , author =

    Masci F. J., et al., 2019, @doi [ ] 10.1088/1538-3873/aae8ac , https://ui.adsabs.harvard.edu/abs/2019PASP..131a8003M 131, 018003

  64. [64]

    M., Koerding E., Knigge C., Uttley P., Fender R

    McHardy I. M., Koerding E., Knigge C., Uttley P., Fender R. P., 2006, @doi [ ] 10.1038/nature05389 , https://ui.adsabs.harvard.edu/abs/2006Natur.444..730M 444, 730

  65. [65]

    Merloni A., Heinz S., di Matteo T., 2003, @doi [ ] 10.1046/j.1365-2966.2003.07017.x , https://ui.adsabs.harvard.edu/abs/2003MNRAS.345.1057M 345, 1057

  66. [66]

    F., Rodr \' guez L

    Mirabel I. F., Rodr \' guez L. F., 1999, @doi [ ] 10.1146/annurev.astro.37.1.409 , https://ui.adsabs.harvard.edu/abs/1999ARA&A..37..409M 37, 409

  67. [67]

    A., Debnath D., Chakrabarti S

    Molla A. A., Debnath D., Chakrabarti S. K., Mondal S., Jana A., Chatterjee D., 2016, in 41st COSPAR Scientific Assembly. pp E1.6--18--16

  68. [68]

    E., Belloni, T

    Motta S. E., Belloni T. M., Stella L., Mu \ n oz-Darias T., Fender R., 2014, @doi [ ] 10.1093/mnras/stt2068 , https://ui.adsabs.harvard.edu/abs/2014MNRAS.437.2554M 437, 2554

  69. [69]

    Mukherjee S., Mitra K., Chatterjee R., 2019, @doi [ ] 10.1093/mnras/stz858 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.486.1672M 486, 1672

  70. [70]

    C., Singh R

    Negi V., Joshi R., Chand K., Chand H., Wiita P., Ho L. C., Singh R. S., 2022, @doi [ ] 10.1093/mnras/stab3591 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.510.1791N 510, 1791

  71. [71]

    S., Georganopoulos M., Guiriec S., Meyer E

    Nemmen R. S., Georganopoulos M., Guiriec S., Meyer E. T., Gehrels N., Sambruna R. M., 2012, @doi [Science] 10.1126/science.1227416 , https://ui.adsabs.harvard.edu/abs/2012Sci...338.1445N 338, 1445

  72. [72]

    M., Best P

    Nisbet D. M., Best P. N., 2016, @doi [ ] 10.1093/mnras/stv2450 , https://ui.adsabs.harvard.edu/abs/2016MNRAS.455.2551N 455, 2551

  73. [73]

    Oh K., et al., 2022, @doi [ ] 10.3847/1538-4365/ac5b68 , https://ui.adsabs.harvard.edu/abs/2022ApJS..261....4O 261, 4

  74. [74]

    A., McClintock J

    Orosz J. A., McClintock J. E., Aufdenberg J. P., Remillard R. A., Reid M. J., Narayan R., Gou L., 2011, @doi [ ] 10.1088/0004-637X/742/2/84 , https://ui.adsabs.harvard.edu/abs/2011ApJ...742...84O 742, 84

  75. [75]

    Padovani P., et al., 2017, @doi [ ] 10.1007/s00159-017-0102-9 , https://ui.adsabs.harvard.edu/abs/2017A&ARv..25....2P 25, 2

  76. [76]

    S., Dom´ ınguez, A., Ajello, M., Olmo-Garc´ ıa, A., & Hartmann, D

    Paliya V. S., Dom \' nguez A., Ajello M., Olmo-Garc \' a A., Hartmann D., 2021, @doi [ ] 10.3847/1538-4365/abe135 , https://ui.adsabs.harvard.edu/abs/2021ApJS..253...46P 253, 46

  77. [77]

    N., Harvey E

    Picchi P., Shore S. N., Harvey E. J., Berdyugin A., 2020, @doi [ ] 10.1051/0004-6361/202037960 , https://ui.adsabs.harvard.edu/abs/2020A&A...640A..96P 640, A96

  78. [78]

    Rawlings S., Saunders R., 1991, @doi [ ] 10.1038/349138a0 , https://ui.adsabs.harvard.edu/abs/1991Natur.349..138R 349, 138

  79. [79]

    E., Greene, J

    Reines A. E., Greene J. E., Geha M., 2013, @doi [ ] 10.1088/0004-637X/775/2/116 , https://ui.adsabs.harvard.edu/abs/2013ApJ...775..116R 775, 116

  80. [80]

    J., et al., 2012, @doi [ ] 10.1088/0004-637X/760/1/51 , https://ui.adsabs.harvard.edu/abs/2012ApJ...760...51R 760, 51

    Ruan J. J., et al., 2012, @doi [ ] 10.1088/0004-637X/760/1/51 , https://ui.adsabs.harvard.edu/abs/2012ApJ...760...51R 760, 51

Showing first 80 references.