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arxiv: 2605.24664 · v2 · pith:UBHT3OSOnew · submitted 2026-05-23 · 🌌 astro-ph.HE

Model dependence of XRISM black-hole spin constraints in Cyg X-1

Andrzej A. Zdziarski , Swadesh Chand , Michal Szanecki , Gulab Dewangan , Barbara De Marco This is my paper

Pith reviewed 2026-06-30 12:52 UTC · model grok-4.3

classification 🌌 astro-ph.HE
keywords Cyg X-1black hole spinXRISMrelativistic reflectionrelxillComptonizationaccretion diskgravitational waves
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The pith

Black hole spin in Cyg X-1 depends on the X-ray reflection model

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

This paper studies XRISM Resolve spectra of the black hole X-ray binary Cyg X-1 taken simultaneously with NICER and NuSTAR in the hard state. It shows that the simplest relativistic reflection model applied to the Resolve data alone produces a near-maximal black hole spin. In contrast, improved Comptonization-based models produce a low spin value. Fits to the combined data sets are consistent with any spin value. The authors conclude that the spin is strongly model-dependent, although low values remain consistent with gravitational wave constraints. All models constrain the inner disk radius to less than 10 gravitational radii.

Core claim

Fits of the Resolve data alone with the simplest available relativistic reflection model, relxill, yield a black hole spin parameter close to the maximum, a_* = 0.99. However, fitting with an improved, Comptonization-based model, relxillCp, yields a low a_*=0.0^{+0.17}. A similarly low range is obtained with another Comptonization-based model, reflkerrD. Then, fits to the combined data require two Comptonization models but are consistent with any spin value. We conclude that the spin value of Cyg X-1 is strongly model-dependent. However, low spin values are consistent with the constraints from gravitational waves. All of the models constrain the inner disk radius to be <10 gravitational radi

What carries the argument

Choice between the simplest relativistic reflection model relxill and Comptonization-based models relxillCp or reflkerrD when fitting the iron line and reflection spectrum

If this is right

  • The derived spin changes from near-maximal to near-zero with model choice on the same data.
  • Low spin values are allowed and align with gravitational wave constraints from black hole mergers.
  • The inner accretion disk radius is constrained below 10 gravitational radii in every model.
  • An outflowing disk corona is indicated as the geometry of the X-ray source.
  • The same geometry accounts for the observed X-ray polarization from the source.

Where Pith is reading between the lines

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

  • Applying similar model comparisons to other X-ray binaries could test whether spin estimates are generally model-dependent.
  • Reverberation lag measurements that independently confirm or refute the inner disk radius limit would test the robustness of the result.
  • This model dependence suggests that published spin values for other sources may require re-analysis with multiple reflection models.

Load-bearing premise

Differences in fitted spin arise purely from the choice of reflection model rather than from unaccounted systematic effects in data calibration, background subtraction, or unmodeled spectral components.

What would settle it

An independent spin measurement for the black hole in Cyg X-1, such as from gravitational waves in a future merger, that lies outside the range permitted by the Comptonization models.

Figures

Figures reproduced from arXiv: 2605.24664 by Andrzej A. Zdziarski, Barbara de Marco, Gulab Dewangan, Michal Szanecki, Swadesh Chand.

Figure 1
Figure 1. Figure 1: The light curves from NICER, NuSTAR, and XRISM Resolve (from top to bottom), together with the corresponding hard￾ness ratios, for the first 42 h studied in this work. The zero time is set to the start time of the Resolve observation, i.e., 2024-04-07 17:56:58. 2. THE DATA, LIGHTCURVES AND VARIABILITY We use the same XRISM observation as in D25. Cyg X￾1 was observed over half of its orbital period, at the … view at source ↗
Figure 2
Figure 2. Figure 2: (a) the 2–20 keV count rate vs. the (4–10)/(2–4) keV hardness ratio. (b) The (10–20)/(4–10) keV hardness ratio vs. the (4–10)/(2–4) keV hardness ratio (the color-color diagram). Both panels show MAXI data binned over 10-day intervals. The MAXI data averaged over the days of the XRISM observation used by us are shown as red symbols. resolution primary (Hp) events and excluded pixels 12 and 27. The small (S)… view at source ↗
Figure 3
Figure 3. Figure 3: The rms(E) in the 0.01–1 Hz frequency range for NICER (red) and XRISM Resolve (blue). For comparison, the black symbols show the rms(E) from NICER in the soft spectral state (Zdziarski et al. 2024). We see similar trends in soft X-rays, with broad peaks around 1 keV, though the soft-state rms is much lower. Above that, we observe a decrease with energy in the hard state and an increase in the soft state, w… view at source ↗
Figure 4
Figure 4. Figure 4: The Resolve unfolded spectrum (top) and data-to-model ratio (bottom) for the fit using relxillCp. The total and unab￾sorbed model spectra are shown by the solid black and cyan curves, respectively. The incident and reflection components are shown by the blue and red curves, respectively. Here and in Figures 5 and 6 below, the spectra have been rebinned for plotting. reflection strength to R ≤ 2 and obtaine… view at source ↗
Figure 5
Figure 5. Figure 5: The NICER (green), Resolve (black), and NuSTAR (blue and red) unfolded spectra (top) and data-to-model ratios (bottom) for the fit with two reflkerrD components. The total and unab￾sorbed model spectra are shown by the solid black and cyan curves, respectively. The incident and reflection components are shown by the blue and red curves for the hard component, and by the green and magenta curves for the sof… view at source ↗
Figure 6
Figure 6. Figure 6: The NICER (green), Resolve (black), and NuSTAR (blue and red) data-to-model ratios for the fit with the two-reflkerrD model, covering the full NuSTAR spectral range, 3–79 keV. We observe a substantial excess of Resolve counts in the Fe K range compared with those from NuSTAR and NICER. We also show the Xtend 0.5–10 keV spectrum unfolded with that model (not fitted). 0.15+0.11 −0.01 keV, fully agrees with t… view at source ↗
read the original abstract

We study the persistent black hole X-ray binary Cyg X-1, recently observed by XRISM Resolve and simultaneously by NICER and NuSTAR in its hard spectral state. We confirm the result of Draghis et al. that fits of the Resolve data alone with the simplest available relativistic reflection model, relxill, yield a black hole spin parameter close to the maximum, $a_* = 0.99$. However, fitting with an improved, Comptonization-based model, relxillCp, yields a low $a_*=0.0^{+0.17}$. A similarly low range is obtained with another Comptonization-based model, reflkerrD. Then, fits to the combined data require two Comptonization models but are consistent with any spin value. We conclude that the spin value of Cyg X-1 is strongly model-dependent. However, low spin values are consistent with the constraints from gravitational waves. All of the models constrain the inner disk radius to be <10 gravitational radii, which is consistent with a recent finding of the weakness of thermal reverberation in Cyg X-1. The suggested source geometry is that of an outflowing disk corona, which was also proposed to explain the X-ray polarization observed from this source.

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

2 major / 1 minor

Summary. The manuscript analyzes XRISM Resolve spectra of Cyg X-1 in the hard state, both alone and jointly with NICER/NuSTAR data, using three relativistic reflection models. It reports that the simplest model (relxill) returns a near-maximal spin a* = 0.99 while Comptonization-based models (relxillCp, reflkerrD) return a* = 0, with joint fits allowing any spin; the inner disk radius is constrained to <10 Rg in all cases. The authors conclude that the spin measurement is strongly model-dependent but that low-spin solutions are consistent with gravitational-wave constraints, favoring an outflowing corona geometry.

Significance. If the reported model dependence is robust, the result would caution against over-interpreting high spins obtained with the simplest reflection models and would strengthen the case for low spin in Cyg X-1, aligning X-ray reflection with gravitational-wave constraints. The consistent inner-radius limit across models also provides supporting evidence for the proposed corona geometry.

major comments (2)
  1. [Abstract] Abstract: the central claim of strong model dependence rests on the reported best-fit spins (a* = 0.99 vs a* = 0) differing between relxill and the Comptonization-based models, yet no fit statistics (reduced chi-squared, degrees of freedom, or null-hypothesis probabilities) are quoted, preventing assessment of whether the low-spin solutions are statistically preferred or merely allowed.
  2. [Results] The attribution of the spin discrepancy exclusively to the choice of reflection model assumes that data reduction, background subtraction, and calibration are identical across all fits; no quantitative test or table demonstrating that these systematics are held fixed is provided, leaving open the possibility that unmodeled components (e.g., the second Comptonization component required only in joint fits) contribute to the difference.
minor comments (1)
  1. A summary table listing best-fit parameters, uncertainties, and fit statistics for every model–dataset combination would make the model-dependence claim easier to evaluate.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their careful reading and constructive comments on our manuscript. We address each major comment point by point below.

read point-by-point responses

  1. Referee: [Abstract] Abstract: the central claim of strong model dependence rests on the reported best-fit spins (a* = 0.99 vs a* = 0) differing between relxill and the Comptonization-based models, yet no fit statistics (reduced chi-squared, degrees of freedom, or null-hypothesis probabilities) are quoted, preventing assessment of whether the low-spin solutions are statistically preferred or merely allowed.

    Authors: We agree that explicit fit statistics in the abstract would aid assessment. The manuscript body and tables report reduced chi-squared values and degrees of freedom for all models; the Comptonization-based models yield statistically acceptable fits (reduced chi^2 comparable to or lower than relxill). We will revise the abstract to include a concise statement noting that all models provide acceptable fits to the Resolve data. revision: yes

  2. Referee: [Results] The attribution of the spin discrepancy exclusively to the choice of reflection model assumes that data reduction, background subtraction, and calibration are identical across all fits; no quantitative test or table demonstrating that these systematics are held fixed is provided, leaving open the possibility that unmodeled components (e.g., the second Comptonization component required only in joint fits) contribute to the difference.

    Authors: All fits in the manuscript (Resolve-only and joint) employ identical data reduction, background subtraction, and calibration for the XRISM, NICER, and NuSTAR datasets. The second Comptonization component appears only in joint fits to accommodate the wider bandpass; Resolve-only fits use a single component consistent with each reflection model. We will add an explicit statement in the data analysis section confirming that processing steps are held fixed across all model comparisons. revision: yes

Circularity Check

0 steps flagged

No circularity; results are direct outputs of independent model fits to data

full rationale

The paper reports spin constraints obtained by fitting named public reflection models (relxill, relxillCp, reflkerrD) to XRISM Resolve, NICER, and NuSTAR spectra. The differing a* values (0.99 vs. 0) and the joint-fit consistency with any spin are direct numerical outputs of those fits, not quantities defined in terms of themselves or reduced by construction from the paper's own equations. No self-citations are invoked to justify uniqueness or load-bearing premises, no ansatzes are smuggled via prior work, and no fitted parameters are relabeled as predictions. The derivation chain is therefore self-contained against external data and standard models.

Axiom & Free-Parameter Ledger

2 free parameters · 1 axioms · 0 invented entities

The central claim rests on the assumption that the chosen reflection models capture the dominant physics and that differences between them reflect real model uncertainty rather than data artifacts.

free parameters (2)
  • black hole spin a_*
    Primary fitted parameter whose value changes dramatically between models.
  • inner disk radius R_in
    Fitted parameter constrained to <10 R_g by all models.
axioms (1)
  • domain assumption The relativistic reflection models relxill, relxillCp, and reflkerrD provide adequate descriptions of the hard-state spectrum of Cyg X-1.
    Invoked when interpreting fit results as physical constraints on spin and geometry.

pith-pipeline@v0.9.1-grok · 5770 in / 1383 out tokens · 44038 ms · 2026-06-30T12:52:29.616101+00:00 · methodology

discussion (0)

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Works this paper leans on

79 extracted references · 76 canonical work pages · 5 internal anchors

  1. [1]

    A., Czerny, B., Lasota, J

    Abramowicz, M. A., Czerny, B., Lasota, J. P., & Szuszkiewicz, E. 1988, ApJ, 332, 646, doi: 10.1086/166683

    work page doi:10.1086/166683 1988

  2. [2]

    Gravitational-wave constraints on the pair-instability mass gap and nuclear burning in massive stars

    Antonini, F., Romero-Shaw, I., Callister, T., et al. 2025, arXiv e-prints, arXiv:2509.04637, doi: 10.48550/arXiv.2509.04637

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.48550/arxiv.2509.04637 2025

  3. [3]

    Arnaud, K. A. 1996, ASPC, V ol. 101, XSPEC: The First Ten Years, ed. G. H. Jacoby & J. Barnes (ASP), 17

    1996

  4. [4]

    2018, ApJL, 853, L21, doi: 10.3847/2041-8213/aaa83b

    Bachetti, M., & Huppenkothen, D. 2018, ApJL, 853, L21, doi: 10.3847/2041-8213/aaa83b

    work page doi:10.3847/2041-8213/aaa83b 2018

  5. [5]

    A., Cook, R., et al

    Bachetti, M., Harrison, F. A., Cook, R., et al. 2015, ApJ, 800, 109, doi: 10.1088/0004-637X/800/2/109

    work page doi:10.1088/0004-637x/800/2/109 2015

  6. [6]

    Identification of the soft X-ray excess in Cygnus X-1 with disc emission

    Balucinska-Church, M., Belloni, T., Church, M. J., & Hasinger, G. 1995, A&A, 302, L5, doi: 10.48550/arXiv.astro-ph/9509020

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.48550/arxiv.astro-ph/9509020 1995

  7. [7]

    W., Dauser, T., et al

    Bambi, C., Brenneman, L. W., Dauser, T., et al. 2021, SSRv, 217, 65, doi: doi.org/10.1007/s11214-021-00841-8

    work page doi:10.1007/s11214-021-00841-8 2021

  8. [8]

    2025, MNRAS, 542, 982, doi: 10.1093/mnras/staf1155

    Basak, A., Uttley, P., Bollemeijer, N., et al. 2025, MNRAS, 542, 982, doi: 10.1093/mnras/staf1155

    work page doi:10.1093/mnras/staf1155 2025

  9. [9]

    A., Parker, M., & Islam, N

    Basak, R., Zdziarski, A. A., Parker, M., & Islam, N. 2017, MNRAS, 472, 4220, doi: 10.1093/mnras/stx2283 Belczy´nski, K., Done, C., Hagen, S., Lasota, J.-P., & Sen, K. 2024, A&A, 690, A21, doi: 10.1051/0004-6361/202450229 Belczy´nski, K., Klencki, J., Fields, C. E., et al. 2020, A&A, 636, A104, doi: 10.1051/0004-6361/201936528

    work page doi:10.1093/mnras/stx2283 2017

  10. [10]

    Beloborodov, A. M. 1999, ApJL, 510, L123, doi: 10.1086/311810

    work page doi:10.1086/311810 1999

  11. [11]

    T., Chubb, T

    Bowyer, S., Byram, E. T., Chubb, T. A., & Friedman, H. 1965, Science, 147, 394, doi: 10.1126/science.147.3656.394

    work page doi:10.1126/science.147.3656.394 1965

  12. [12]

    S., & Brenneman, L

    Dauser, T., Wilms, J., Reynolds, C. S., & Brenneman, L. W. 2010, MNRAS, 409, 1534, doi: 10.1111/j.1365-2966.2010.17393.x

    work page doi:10.1111/j.1365-2966.2010.17393.x 2010

  13. [13]

    W., & El-Abd, S

    Davis, S. W., & El-Abd, S. 2019, ApJ, 874, 23, doi: 10.3847/1538-4357/ab05c5 De Marco, B., & Ponti, G. 2016, ApJ, 826, 70, doi: 10.3847/0004-637X/826/1/70 De Marco, B., Ponti, G., Muñoz-Darias, T., & Nandra, K. 2015, MNRAS, 454, 2360, doi: 10.1093/mnras/stv1990 De Marco, B., Zdziarski, A. A., Ponti, G., et al. 2021, A&A, 654, A14, doi: 10.1051/0004-6361/2...

    work page doi:10.3847/1538-4357/ab05c5 2019

  14. [14]

    2007, A&A Rv, 15, 1, doi: 10.1007/s00159-007-0006-1

    Done, C., Gierli´nski, M., & Kubota, A. 2007, A&A Rv, 15, 1, doi: 10.1007/s00159-007-0006-1

    work page doi:10.1007/s00159-007-0006-1 2007

  15. [15]

    A., Miller, J

    Draghis, P. A., Miller, J. M., Brenneman, L., et al. 2025a, ApJ, 989, 227, doi: 10.3847/1538-4357/adec85

    work page doi:10.3847/1538-4357/adec85

  16. [16]

    A., Miller, J

    Draghis, P. A., Miller, J. M., Costantini, E., et al. 2024, ApJ, 969, 40, doi: 10.3847/1538-4357/ad43ea

    work page doi:10.3847/1538-4357/ad43ea 2024

  17. [17]

    A., Miller, J

    Draghis, P. A., Miller, J. M., Kara, E., et al. 2025b, ApJL, 995, L12, doi: 10.3847/2041-8213/ae2276

    work page doi:10.3847/2041-8213/ae2276 2041

  18. [18]

    A., Miller, J

    Draghis, P. A., Miller, J. M., Zoghbi, A., et al. 2023, ApJ, 946, 19, doi: 10.3847/1538-4357/acafe7

    work page doi:10.3847/1538-4357/acafe7 2023

  19. [19]

    2011, A&A, 533, L3, doi: 10.1051/0004-6361/201117446 Dziełak, M

    Duro, R., Dauser, T., Wilms, J., et al. 2011, A&A, 533, L3, doi: 10.1051/0004-6361/201117446 Dziełak, M. A., De Marco, B., & Zdziarski, A. A. 2021, MNRAS, 506, 2020, doi: 10.1093/mnras/stab1700

    work page doi:10.1051/0004-6361/201117446 2011

  20. [20]

    2012, MNRAS, 425, 1371, doi: 10.1111/j.1365-2966.2012.21554.x

    Fabian, A. C., Wilkins, D. R., Miller, J. M., et al. 2012, MNRAS, 424, 217, doi: 10.1111/j.1365-2966.2012.21185.x

    work page doi:10.1111/j.1365-2966.2012.21185.x 2012

  21. [21]

    C., Middleton, M

    Fragile, P. C., Middleton, M. J., Bollimpalli, D. A., & Smith, Z. 2025, MNRAS, 540, 2820, doi: 10.1093/mnras/staf890

    work page doi:10.1093/mnras/staf890 2025

  22. [22]

    2019, ApJL, 881, L1, doi: 10.3847/2041-8213/ab339b García, J., & Kallman, T

    Fuller, J., & Ma, L. 2019, ApJL, 881, L1, doi: 10.3847/2041-8213/ab339b García, J., & Kallman, T. R. 2010, ApJ, 718, 695, doi: 10.1088/0004-637X/718/2/695 García, J. A., Dauser, T., Reynolds, C. S., et al. 2013, ApJ, 768, 146, doi: 10.1088/0004-637X/768/2/146 García, J. A., Steiner, J. F., Grinberg, V ., et al. 2018, ApJ, 864, 25, doi: 10.3847/1538-4357/aad231

    work page doi:10.3847/2041-8213/ab339b 2019

  23. [23]

    C., Arzoumanian, Z., Adkins, P

    Gendreau, K. C., Arzoumanian, Z., Adkins, P. W., et al. 2016, Proc. SPIE, 9905, 99051H, doi: 10.1117/12.2231304 Gierli´nski, M., & Done, C. 2004, MNRAS, 347, 885, doi: 10.1111/j.1365-2966.2004.07266.x Gierli´nski, M., Zdziarski, A. A., Done, C., et al. 1997, MNRAS, 288, 958

    work page doi:10.1117/12.2231304 2016

  24. [24]

    R., Bolton, C

    Gies, D. R., Bolton, C. T., Blake, R. M., et al. 2008, ApJ, 678, 1237, doi: 10.1086/586690

    work page doi:10.1086/586690 2008

  25. [25]

    E., Liu, J., et al

    Gou, L., McClintock, J. E., Liu, J., et al. 2009, ApJ, 701, 1076, doi: 10.1088/0004-637X/701/2/1076

    work page doi:10.1088/0004-637x/701/2/1076 2009

  26. [26]

    1991, ApJL, 380, L51, doi: 10.1086/186171

    Haardt, F., & Maraschi, L. 1991, ApJL, 380, L51, doi: 10.1086/186171

    work page doi:10.1086/186171 1991

  27. [27]

    A., Craig, W

    Harrison, F. A., Craig, W. W., Christensen, F. E., et al. 2013, ApJ, 770, 103, doi: 10.1088/0004-637X/770/2/103 HI4PI Collaboration, Ben Bekhti, N., Flöer, L., et al. 2016, A&A, 594, A116, doi: 10.1051/0004-6361/201629178

    work page doi:10.1088/0004-637x/770/2/103 2013

  28. [28]

    2019a, The Journal of Open Source Software, 4, 1393, doi: 10.21105/joss.01393 11

    Huppenkothen, D., Bachetti, M., Stevens, A., et al. 2019a, The Journal of Open Source Software, 4, 1393, doi: 10.21105/joss.01393 11

    work page doi:10.21105/joss.01393

  29. [29]

    L., et al

    Huppenkothen, D., Bachetti, M., Stevens, A. L., et al. 2019b, ApJ, 881, 39, doi: 10.3847/1538-4357/ab258d

    work page doi:10.3847/1538-4357/ab258d

  30. [30]

    S., & Bleeker, J

    Kaastra, J. S., & Bleeker, J. A. M. 2016, A&A, 587, A151, doi: 10.1051/0004-6361/201527395

    work page doi:10.1051/0004-6361/201527395 2016

  31. [31]

    2001, ApJS, 133, 221, doi: 10.1086/319184

    Kallman, T., & Bautista, M. 2001, ApJS, 133, 221, doi: 10.1086/319184

    work page doi:10.1086/319184 2001

  32. [32]

    2001, MNRAS, 327, 799, doi: 10.1046/j.1365-8711.2001.04769.x

    Kotov, O., Churazov, E., & Gilfanov, M. 2001, MNRAS, 327, 799, doi: 10.1046/j.1365-8711.2001.04769.x

    work page doi:10.1046/j.1365-8711.2001.04769.x 2001

  33. [33]

    2022, Science, 378, 650, doi: 10.1126/science.add5399

    Krawczynski, H., Muleri, F., Dovˇciak, M., et al. 2022, Science, 378, 650, doi: 10.1126/science.add5399

    work page doi:10.1126/science.add5399 2022

  34. [34]

    1998, PASJ, 50, 667, doi: 10.1093/pasj/50.6.667

    Kubota, A., Tanaka, Y ., Makishima, K., et al. 1998, PASJ, 50, 667, doi: 10.1093/pasj/50.6.667

    work page doi:10.1093/pasj/50.6.667 1998

  35. [35]

    1976, ApJ, 208, 177, doi: 10.1086/154592

    Lampton, M., Margon, B., & Bowyer, S. 1976, ApJ, 208, 177, doi: 10.1086/154592

    work page doi:10.1086/154592 1976

  36. [36]

    P., & Eardley, D

    Lightman, A. P., & Eardley, D. M. 1974, ApJL, 187, L1, doi: 10.1086/181377

    work page doi:10.1086/181377 1974

  37. [37]

    K., et al

    Liu, H., Kong, L., Adegoke, O. K., et al. 2026, arXiv e-prints, arXiv:2603.06883, doi: 10.48550/arXiv.2603.06883

    work page doi:10.48550/arxiv.2603.06883 2026

  38. [38]

    E., Narayan, R., Davis, S

    Liu, J., McClintock, J. E., Narayan, R., Davis, S. W., & Orosz, J. A. 2008, ApJL, 679, L37, doi: 10.1086/588840

    work page doi:10.1086/588840 2008

  39. [39]

    2023, ApJ, 952, 53, doi: 10.3847/1538-4357/acdb74

    Ma, L., & Fuller, J. 2023, ApJ, 952, 53, doi: 10.3847/1538-4357/acdb74

    work page doi:10.3847/1538-4357/acdb74 2023

  40. [40]

    2008, PASJ, 60, 585, doi: 10.1093/pasj/60.3.585

    Makishima, K., Takahashi, H., Yamada, S., et al. 2008, PASJ, 60, 585, doi: 10.1093/pasj/60.3.585

    work page doi:10.1093/pasj/60.3.585 2008

  41. [41]

    2020, ApJL, 895, L28, doi: 10.3847/2041-8213/ab8e41

    Mandel, I., & Fragos, T. 2020, ApJL, 895, L28, doi: 10.3847/2041-8213/ab8e41

    work page doi:10.3847/2041-8213/ab8e41 2020

  42. [42]

    2009, PASJ, 61, 999, doi: 10.1093/pasj/61.5.999

    Matsuoka, M., Kawasaki, K., Ueno, S., et al. 2009, PASJ, 61, 999, doi: 10.1093/pasj/61.5.999

    work page doi:10.1093/pasj/61.5.999 2009

  43. [43]

    E., Narayan, R., & Steiner, J

    McClintock, J. E., Narayan, R., & Steiner, J. F. 2014, SSRv, 183, 295, doi: 10.1007/s11214-013-0003-9

    work page doi:10.1007/s11214-013-0003-9 2014

  44. [44]

    L., Zdziarski, A

    McConnell, M. L., Zdziarski, A. A., Bennett, K., et al. 2002, ApJ, 572, 984, doi: 10.1086/340436

    work page doi:10.1086/340436 2002

  45. [45]

    Miller-Jones, J. C. A., Bahramian, A., Orosz, J. A., et al. 2021, Science, 371, 1046, doi: 10.1126/science.abb3363

    work page doi:10.1126/science.abb3363 2021

  46. [46]

    1984, PASJ, 36, 741 Nied´ zwiecki, A., Szanecki, M., & Zdziarski, A

    Mitsuda, K., Inoue, H., Koyama, K., et al. 1984, PASJ, 36, 741 Nied´ zwiecki, A., Szanecki, M., & Zdziarski, A. A. 2019, MNRAS, 485, 2942, doi: 10.1093/mnras/stz487

    work page doi:10.1093/mnras/stz487 1984

  47. [47]

    D., & Thorne, K

    Novikov, I. D., & Thorne, K. S. 1973, in Black Holes (Les Astres Occlus), ed. C. Dewitt & B. S. Dewitt (Gordon and Breach: New

    1973

  48. [48]

    2021, ApJL, 921, L2, doi: 10.3847/2041-8213/ac2f48

    Olejak, A., & Belczy´nski, K. 2021, ApJL, 921, L2, doi: 10.3847/2041-8213/ac2f48

    work page doi:10.3847/2041-8213/ac2f48 2021

  49. [49]

    1996, ApJ, 470, 249, doi: 10.1086/177865

    Poutanen, J., & Svensson, R. 1996, ApJ, 470, 249, doi: 10.1086/177865

    work page doi:10.1086/177865 1996

  50. [50]

    Poutanen, J., Veledina, A., & Beloborodov, A. M. 2023, ApJL, 949, L10, doi: 10.3847/2041-8213/acd33e

    work page doi:10.3847/2041-8213/acd33e 2023

  51. [51]

    Poutanen, J., Veledina, A., & Zdziarski, A. A. 2018, A&A, 614, A79, doi: 10.1051/0004-6361/201732345

    work page doi:10.1051/0004-6361/201732345 2018

  52. [52]

    2018, A&A, 616, A28, doi: 10.1051/0004-6361/201832839

    Qin, Y ., Fragos, T., Meynet, G., et al. 2018, A&A, 616, A28, doi: 10.1051/0004-6361/201832839

    work page doi:10.1051/0004-6361/201832839 2018

  53. [53]

    2022, Research in Astronomy and Astrophysics, 22, 035023, doi: 10.1088/1674-4527/ac4ca4

    Qin, Y ., Shu, X., Yi, S., & Wang, Y .-Z. 2022, Research in Astronomy and Astrophysics, 22, 035023, doi: 10.1088/1674-4527/ac4ca4

    work page doi:10.1088/1674-4527/ac4ca4 2022

  54. [54]

    Ramachandran, V ., Sander, A. A. C., Oskinova, L. M., et al. 2025, A&A, 698, A37, doi: 10.1051/0004-6361/202554184

    work page doi:10.1051/0004-6361/202554184 2025

  55. [55]

    I., & Sunyaev, R

    Shakura, N. I., & Sunyaev, R. A. 1976, MNRAS, 175, 613, doi: 10.1093/mnras/175.3.613 Simón-Díaz, S., Godart, M., Castro, N., et al. 2017, A&A, 597, A22, doi: 10.1051/0004-6361/201628541 S˛ adowski, A. 2009, ApJS, 183, 171, doi: 10.1088/0067-0049/183/2/171

    work page doi:10.1093/mnras/175.3.613 1976

  56. [56]

    Spruit, H. C. 2002, A&A, 381, 923, doi: 10.1051/0004-6361:20011465

    work page doi:10.1051/0004-6361:20011465 2002

  57. [57]

    F., McClintock, J

    Steiner, J. F., McClintock, J. E., Remillard, R. A., et al. 2010, ApJL, 718, L117, doi: 10.1088/2041-8205/718/2/L117

    work page doi:10.1088/2041-8205/718/2/l117 2010

  58. [58]

    F., Nathan, E., Hu, K., et al

    Steiner, J. F., Nathan, E., Hu, K., et al. 2024, ApJL, 969, L30, doi: 10.3847/2041-8213/ad58e4

    work page doi:10.3847/2041-8213/ad58e4 2024

  59. [59]

    2021, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference

    Tashiro, M., Maejima, H., Toda, K., et al. 2021, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference

    2021

  60. [60]

    GWTC-4.0: Population Properties of Merging Compact Binaries

    Series, V ol. 11444, Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, ed. J.-W. A. den Herder, S. Nikzad, & K. Nakazawa, 1144422, doi: 10.1117/12.2565812 The LIGO Scientific Collaboration, the Virgo Collaboration, & the KAGRA Collaboration. 2025, arXiv e-prints, arXiv:2508.18083, doi: 10.48550/arXiv.2508.18083

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.1117/12.2565812 2025

  61. [61]

    A., Nowak, M

    Tomsick, J. A., Nowak, M. A., Parker, M., et al. 2014, ApJ, 780, 78, doi: 10.1088/0004-637X/780/1/78

    work page doi:10.1088/0004-637x/780/1/78 2014

  62. [62]

    A., Parker, M

    Tomsick, J. A., Parker, M. L., García, J. A., et al. 2018, ApJ, 855, 3, doi: 10.3847/1538-4357/aaaab1

    work page doi:10.3847/1538-4357/aaaab1 2018

  63. [63]

    Evidence of the pair instability gap from black hole masses

    Tong, H., Fishbach, M., Thrane, E., et al. 2025, arXiv e-prints, arXiv:2509.04151, doi: 10.48550/arXiv.2509.04151

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.48550/arxiv.2509.04151 2025

  64. [64]

    M., Fabian, A

    Uttley, P., Cackett, E. M., Fabian, A. C., Kara, E., & Wilkins, D. R. 2014, A&A Rv, 22, 72, doi: 10.1007/s00159-014-0072-0

    work page doi:10.1007/s00159-014-0072-0 2014

  65. [65]

    2011, MNRAS, 414, L60, doi: 10.1111/j.1745-3933.2011.01056.x van Son, L

    Uttley, P., Wilkinson, T., Cassatella, P., et al. 2011, MNRAS, 414, L60, doi: 10.1111/j.1745-3933.2011.01056.x van Son, L. A. C., De Mink, S. E., Broekgaarden, F. S., et al. 2020, ApJ, 897, 100, doi: 10.3847/1538-4357/ab9809

    work page doi:10.1111/j.1745-3933.2011.01056.x 2011

  66. [66]

    Walborn, N. R. 1973, ApJL, 179, L123, doi: 10.1086/181131

    work page doi:10.1086/181131 1973

  67. [67]

    2010, MNRAS, 402, 497, doi: 10.1111/j.1365-2966.2009.15898.x

    Wilkinson, T., & Uttley, P. 2009, MNRAS, 397, 666, doi: 10.1111/j.1365-2966.2009.15008.x

    work page doi:10.1111/j.1365-2966.2009.15008.x 2009

  68. [68]

    2000, ApJ, 542, 914, doi: 10.1086/317016

    Wilms, J., Allen, A., & McCray, R. 2000, ApJ, 542, 914, doi: 10.1086/317016

    work page internal anchor Pith review doi:10.1086/317016 2000

  69. [69]

    C., Nowak, M

    Xiang, J., Lee, J. C., Nowak, M. A., & Wilms, J. 2011, ApJ, 738, 78, doi: 10.1088/0004-637X/738/1/78

    work page doi:10.1088/0004-637x/738/1/78 2011

  70. [70]

    2013, PASJ, 65, 80, doi: 10.1093/pasj/65.4.80

    Yamada, S., Makishima, K., Done, C., et al. 2013, PASJ, 65, 80, doi: 10.1093/pasj/65.4.80

    work page doi:10.1093/pasj/65.4.80 2013

  71. [71]

    2025, PASJ, 77, 1210, doi: 10.1093/pasj/psaf104

    Yamada, S., Hell, N., Costantini, E., et al. 2025, PASJ, 77, 1210, doi: 10.1093/pasj/psaf104

    work page doi:10.1093/pasj/psaf104 2025

  72. [72]

    A., & De Marco, B

    Zdziarski, A. A., & De Marco, B. 2020, ApJL, 896, L36, doi: 10.3847/2041-8213/ab9899 12

    work page doi:10.3847/2041-8213/ab9899 2020

  73. [73]

    A., Dziełak, M

    Zdziarski, A. A., Dziełak, M. A., De Marco, B., Szanecki, M., & Nied´ zwiecki, A. 2021, ApJL, 909, L9, doi: 10.3847/2041-8213/abe7ef

    work page doi:10.3847/2041-8213/abe7ef 2021

  74. [74]

    A., Johnson, W

    Zdziarski, A. A., Johnson, W. N., & Magdziarz, P. 1996, MNRAS, 283, 193, doi: 10.1093/mnras/283.1.193

    work page doi:10.1093/mnras/283.1.193 1996

  75. [75]

    A., Marcel, G., Veledina, A., Olejak, A., & Lanˇcová, D

    Zdziarski, A. A., Marcel, G., Veledina, A., Olejak, A., & Lanˇcová, D. 2026, New Astronomy Reviews, 102, 101746, doi: 10.1016/j.newar.2025.101746

    work page doi:10.1016/j.newar.2025.101746 2026

  76. [76]

    A., Poutanen, J., Paciesas, W

    Zdziarski, A. A., Poutanen, J., Paciesas, W. S., & Wen, L. 2002, ApJ, 578, 357, doi: 10.1086/342402

    work page doi:10.1086/342402 2002

  77. [77]

    A., Veledina, A., Szanecki, M., et al

    Zdziarski, A. A., Veledina, A., Szanecki, M., et al. 2023, ApJL, 951, L45, doi: 10.3847/2041-8213/ace2c9

    work page doi:10.3847/2041-8213/ace2c9 2023

  78. [78]

    A., Chand, S., Banerjee, S., et al

    Zdziarski, A. A., Chand, S., Banerjee, S., et al. 2024, ApJL, 967, L9, doi: 10.3847/2041-8213/ad43ed

    work page doi:10.3847/2041-8213/ad43ed 2024

  79. [79]

    2021, ApJ, 908, 117, doi: 10.3847/1538-4357/abbcd6

    Zhao, X., Gou, L., Dong, Y ., et al. 2021, ApJ, 908, 117, doi: 10.3847/1538-4357/abbcd6

    work page doi:10.3847/1538-4357/abbcd6 2021