Abstract

The geometry of the accretion flow around stellar-mass black holes can change on timescales of days to months1,2,3. When a black hole emerges from quiescence (that is, it ‘turns on’ after accreting material from its companion) it has a very hard (high-energy) X-ray spectrum produced by a hot corona4,5 positioned above its accretion disk, and then transitions to a soft (lower-energy) spectrum dominated by emission from the geometrically thin accretion disk, which extends to the innermost stable circular orbit6,7. Much debate persists over how this transition occurs and whether it is driven largely by a reduction in the truncation radius of the disk8,9 or by a reduction in the spatial extent of the corona10,11. Observations of X-ray reverberation lags in supermassive black-hole systems12,13 suggest that the corona is compact and that the disk extends nearly to the central black hole14,15. Observations of stellar-mass black holes, however, reveal equivalent (mass-scaled) reverberation lags that are much larger16, leading to the suggestion that the accretion disk in the hard-X-ray state of stellar-mass black holes is truncated at a few hundreds of gravitational radii from the black hole17,18. Here we report X-ray observations of the black-hole transient MAXI J1820+07019,20. We find that the reverberation time lags between the continuum-emitting corona and the irradiated accretion disk are 6 to 20 times shorter than previously seen. The timescale of the reverberation lags shortens by an order of magnitude over a period of weeks, whereas the shape of the broadened iron K emission line remains remarkably constant. This suggests a reduction in the spatial extent of the corona, rather than a change in the inner edge of the accretion disk.

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Data availability

The datasets analysed during this study are available at NASA’s High Energy Astrophysics Science Archive Research Center (HEASARC; https://heasarc.gsfc.nasa.gov/).

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Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Acknowledgements

E.K. thanks G. Ryan and P. Teuben for discussions on ways to speed up the Python code and J. Garcia and D. Buisson for discussions on NuSTAR observations of MAXI J1820+070. E.K. acknowledges support from the Hubble Fellowship Program and the University of Maryland Joint Space Science Institute and the Neil Gehrels Endowment in Astrophysics through the Neil Gehrels Prize Postdoctoral Fellowship. Support for program number HST-HF2-51360.001-A was provided by NASA through a Hubble Fellowship grant from the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS5-26555. J.F.S. was supported by NASA Einstein Fellowship grant PF5-160144. E.M.C. acknowledges NSF CAREER award AST-1351222. D.A. acknowledges support from the Royal Society. This work was supported by NASA through the NICER mission and the Astrophysics Explorers Program, and made use of data and software provided by the High Energy Astrophysics Science Archive Research Center (HEASARC).

Reviewer information

Nature thanks D. Haggard and the other anonymous reviewer for their contribution to the peer review of this work.

Author information

Affiliations

  1. University of Maryland, College Park, MD, USA

    • E. Kara
  2. NASA Goddard Space Flight Center, Greenbelt, MD, USA

    • E. Kara
    • , K. C. Gendreau
    •  & Z. Arzoumanian
  3. Joint Space Science Institute, University of Maryland, College Park, MD, USA

    • E. Kara
  4. MIT Kavli Institute for Astrophysics and Space Research, Cambridge, MA, USA

    • E. Kara
    • , J. F. Steiner
    •  & R. A. Remillard
  5. Institute of Astronomy, Cambridge, UK

    • A. C. Fabian
  6. Wayne State University, Department of Physics and Astronomy, Detroit, MI, USA

    • E. M. Cackett
  7. Anton Pannekoek Institute for Astronomy, University of Amsterdam, Amsterdam, The Netherlands

    • P. Uttley
  8. School of Physics and Astronomy, University of Southampton, Southampton, UK

    • D. Altamirano
  9. Department of Astronomy, University of Florida, Gainesville, FL, USA

    • S. Eikenberry
  10. Department of Physics, University of Florida, Gainesville, FL, USA

    • S. Eikenberry
  11. Hakubi Center for Advanced Research and Department of Astronomy, Kyoto University, Kyoto, Japan

    • T. Enoto
  12. Eureka Scientific, Oakland, CA, USA

    • J. Homan
  13. SRON, Netherlands Institute for Space Research, Utrecht, The Netherlands

    • J. Homan
  14. Villanova University, Department of Physics, Villanova, PA, USA

    • J. Neilsen
  15. Department of Physics and Astronomy, Michigan State University, East Lansing, MI, USA

    • A. L. Stevens

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Contributions

E.K. led timing analysis and interpretation of results. J.F.S. produced the HID and contributed to interpretation of results. A.C.F. performed spectral modelling and contributed to interpretation of results. E.M.C. and P.U. performed cross-checks of analysis software and contributed to interpretation of results. R.A.R. contributed to background modelling and interpretation of results. K.C.G. and Z.A. scheduled the NICER observations and contributed to data reduction. D.A., J.H., S.E., T.E., J.N. and A.L.S. contributed to interpretation of results.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to E. Kara.

Extended data figures and tables

  1. Extended Data Fig. 1 The power spectral evolution.

    The 0.3–10-keV Poisson noise-subtracted power spectra (in units of (root-mean-square/mean)2 with 1σ errors) for the six epochs of interest (same colour scheme throughout). The solid lines on the top-right portion of the figure indicate the frequencies used in the lag–energy analysis (Fig. 3).

  2. Extended Data Fig. 2 The low-frequency lag–energy spectra.

    The low-frequency (0.1–1-Hz) lag–energy spectra for the six epochs. The lags have been shifted such that the lowest-energy lag starts at zero. No thermal lag is seen at low frequencies. Error bars indicate 1σ confidence intervals.

  3. Extended Data Fig. 3 Modelling the lag–energy spectra.

    a, Case A; b, case B. The top panels show the best-fitting models fitted to epoch 1 (ObsID 1200120106), demonstrating how the significance and amplitude of the Fe K lag are determined. The middle panels show the ratio of the data to the null hypothesis (POWERLAW+DISKBB). The case A null hypothesis is assuming a continuum lag power-law index of zero, whereas case B allows for a non-zero continuum lag. The bottom panels show the ratio of the data to the best-fitting model (POWERLAW+DISKBB+LAOR+LAOR), again where case B allows for a non-zero power-law continuum lag. See text and Extended Data Table 2 for details on the best-fit parameters and χ2 fit statistics. Error bars indicate 1σ confidence intervals.

  4. Extended Data Figure 4 Lags from other observations.

    a, The frequency range of the high-frequency soft lags (lags between 0.5–1 keV and between 1–10 keV) for all observations between epoch 1 and 6. The general trend is that the soft lags increase to higher frequencies over time. The coloured dots show the frequency ranges for the six epochs studied. b, The hardness–intensity diagram, defined as the total 0.2–12-keV count rate versus the ratio of hard (4–12 keV) to soft (2–4 keV) count rates (as in Fig. 1c) for all available data up to MJD 58,344. This extended hardness–intensity diagram shows the recent transition to the soft state. In the right two panels, we show the lags from the earliest observations from the beginning of the outburst (dark-red hashed region) and from the latest times where we can measure high-frequency time lags, at the beginning of the transition to the soft state (purple hashed region). c, Comparison of the lag–frequency spectrum of the first epoch (ObsID 06) and the five co-added ObsIDs that preceded it (MJD 58,189 to MJD 58,193). The inset shows a comparison of the ratio of the energy spectra in these epochs to a power-law fit in the range 3–10 keV. d, The corresponding lag–energy spectra for the 3–30-Hz range, where Fe K lags were seen in epoch 1. The earlier observations (ObsIDs 01–05) show a dominating hard lag at high energies, and no evidence for Fe K lags. e, f, As in c and d, but comparing the lag–frequency spectra and lag–energy spectra of epoch 6 to later observations as the source begins to transition to the soft state. Error bars indicate 1σ confidence intervals.

  5. Extended Data Table 1 Overview of the observations used in this analysis
  6. Extended Data Table 2 Fit parameters of the case A model
  7. Extended Data Table 3 Fit parameters of the case B model

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