Abstract
The atmospheres of a large proportion of white dwarf stars are polluted by heavy elements1 that are expected to sink out of visible layers on short timescales2,3. This has been interpreted as a signature of ongoing accretion of debris from asteroids4, comets5 and giant planets6. This scenario is supported by the detection of debris discs7 and transits of planetary fragments8 around some white dwarfs. However, photospheric metals are only indirect evidence for ongoing accretion, and the inferred accretion rates and parent body compositions heavily depend on models of diffusion and mixing processes within the white dwarf atmosphere9,10,11. Here we report a 4.4σ detection of X-rays from a polluted white dwarf, G29–38. From the measured X-ray luminosity, we derive an instantaneous accretion rate of \({\dot{M}}_{{\rm{X}}}={1.63}_{-0.40}^{+1.29}\times {10}^{9}\,{\rm{g}}\,{{\rm{s}}}^{-1}\), which is independent of stellar atmosphere models. This rate is higher than estimates from past studies of the photospheric abundances of G29–38, suggesting that convective overshoot may be needed to model the spectra of debris-accreting white dwarfs. We measure a low plasma temperature of kBT = 0.5 ± 0.2 keV, corroborating the predicted bombardment solution for white dwarfs accreting at low accretion rates12,13.
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Data availability
The data that support the plots within this Article and other findings of this study are available from the Chandra Data Archive. The observation ID numbers are given in Extended Data Table 1.
Code availability
The official Chandra reduction software package CIAO, which includes merge_obs, wavdetect and XPSEC, is freely and publicly available (cxc.cfa.harvard.edu/ciao/), as is the Python package scipy.
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Acknowledgements
This research was supported by a Leverhulme Trust Grant (ID RPG-2020-366). P.J.W., B.T.G. and P.-E.T. were supported by the UK STFC consolidated grant no. ST/T000406/1. P.-E.T. received funding from the European Research Council under the European Union’s Horizon 2020 research and innovation programme no. 677706 (WD3D). B.T.G. was supported by a Leverhulme Research Fellowship, O.T. was supported by a Leverhulme Trust Research Project Grant and FONDECYT project no. 32103, and D.V. acknowledges the support of the STFC via an Ernest Rutherford Fellowship (grant no. ST/P003850/1). This research has made use of data obtained from the Chandra Data Archive and the Chandra Source Catalog, and software provided by the Chandra X-ray Center (CXC) in the application packages CIAO and Sherpa. This work has made use of data from the European Space Agency (ESA) mission Gaia (https://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC, https://www.cosmos.esa.int/web/gaia/dpac/consortium). Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. The Pan-STARRS1 Surveys (PS1) and the PS1 public science archive have been made possible through contributions by the Institute for Astronomy, the University of Hawaii, the Pan-STARRS Project Office, the Max-Planck Society and its participating institutes, the Max Planck Institute for Astronomy, Heidelberg and the Max Planck Institute for Extraterrestrial Physics, Garching, The Johns Hopkins University, Durham University, the University of Edinburgh, the Queen’s University Belfast, the arvard-Smithsonian Center for Astrophysics, the Las Cumbres Observatory Global Telescope Network Incorporated, the National Central University of Taiwan, the Space Telescope Science Institute, the National Aeronautics and Space Administration under grant no. NNX08AR22G issued through the Planetary Science Division of the NASA Science Mission Directorate, the National Science Foundation grant no. AST-1238877, the University of Maryland, Eotvos Lorand University (ELTE), the Los Alamos National Laboratory and the Gordon and Betty Moore Foundation.
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T.C. performed most of the data analysis and led the writing of the manuscript. P.J.W. contributed to the original observing proposal, the data analysis and the writing of the manuscript. P.-E.T and B.T.G. contributed to the writing of the manuscript and discussions on the various constraints on accretion rates. G.W.K., O.T. and D.V. contributed to the original observing proposal and to discussions throughout the project.
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Extended data figures and tables
Extended Data Fig. 1 Estimate of sky density from a source detection algorithm.
Output of the wavdetect source detection algorithm using the recommended significance threshold, sigthresh, of s1 = 10−6. a–c, are the results for the science bands used in this study; soft, soft + medium and broad, respectively, with 1, 2, and 3 counts shown in cyan, magenta, and white, respectively. a–c, Full field of view of the S3 chip on ACIS-S with sources identified by wavdetect shown in green. d, e, A magnified view of the vicinity near the target for the soft and soft + medium bands respectively, where the white square has sides of length 30 arcsec and is centered on the target coordinates. The source at the sky location of G29–38 is detected in the soft and soft + medium band images. The number of sources and corresponding sky density for each band can be found in Extended Data Table 3. f, Broadband (0.5–7.0 keV) events recorded near the sky position of the only Gaia source (EDR3 source ID: 2661110815469507072) in the full CCD image which has a detected X-ray source in the broadband image within 5 arcsec. The output of wavdetect gives the coordinates for the center of the detected source in (RA, DEC) as (352.182358 ± 0.000022, +5.341529 ± 0.000020), shown in the figure with a cyan cross. The coordinates of the Gaia EDR3 source, corrected for proper motion, are (352.18248533 ± 0.00000007, +5.34150200 ± 0.00000008), indicated in the figure with a white cross. The Chandra source is offset compared to the expected Gaia position by (−0.46 ± 0.08, 0.10 ± 0.07), which is consistent with the offset of our target from the expected position (see Fig. 2).
Extended Data Fig. 2 Monte Carlo aperture photometry.
a, c, The blue points show the positions of the approximately 100,000 test apertures, each 1 arcsec in radius, used to sample 100 arcsec around the target. The absolute number of test apertures, after removing those that fell within a masked region, is shown in the panels. The sky coordinates of all recorded events that fall within a masked region are shown in orange. b, d, The normalized histogram shows the fraction of test apertures with event counts equal to or greater than that of a given bin. The Monte Carlo was performed on the soft (a, b) and soft + medium (c, d) bands. The soft band analysis has 0.001% of test apertures returning four counts, enableing us to rule out chance alignment at 4.4σ.
Extended Data Fig. 3 Spectral modelling of observed X-ray events.
a, Bottom, in units of instrumental counts we show the five recorded events (black) and six best-fit spectral models assuming Solar39 (magenta), bulk Earth40 (blue) and photospheric17 (red) abundances, with either the vvapec isothermal (solid) and mkcflow cooling flow (dotted) plasma models. We also indicate the dominant metal emission lines (O, Mg, Si and Fe) from the isothermal, photospheric abundance model. Middle, in real flux units, we show the synthetic spectra for the photospheric abundances with the isothermal (solid) and cooling flow (dotted) plasma models. The modelling suggests the most likely origin of the source photon at 1.3 keV was a Mg transition. Top, the effective area of the ACIS-S detector is shown in green, hatch. The absence of harder X-ray events (>2.0 keV) in the Chandra observations demonstrates that the plasma emission spectrum is very soft. b, Spectral energy distribution of the best-fit isothermal (blue) and cooling flow (orange) plasma models with bulk Earth abundances down to the extreme ultraviolet (EUV) energy regime. Also shown are the standard Chandra science bands; soft, medium and hard. Both models provide a convergent fit within the Chandra ACIS-S passband, but the cooling flow provides a more physical and larger estimate of the lower-energy flux. c, The X-ray flux measured in 3 bands: 0.5–7.0 keV, 0.3–7.0 keV and 0.0136–100 keV, using the cooling flow model for the photospheric abundances17 is shown in open diamonds. The filled horizontal bands show the 68% and 90% confidence intervals on the X-ray accretion rate, which is computed using Equation (1). The X-ray accretion rates are computed using Equation (1), with A = 1, RWD = 0.0129R⊙, and MWD = 0.6M⊙. The spectroscopic accretion rates (solid lines) are the same as shown in Fig. 3, with the 1σ uncertainty shown with dashed lines. Also shown in solid circles (blue and orange) are the previously published inferred accretion rates for G29–38, based on photospheric abundances from spectroscopic observations17,28.
Extended Data Fig. 4 Limit on cyclotron emission cooling as source of additional luminosity.
a, An estimate for the total luminosity from the measured X-ray luminosity, accounting for cyclotron emission cooling. We compare the measured plasma temperature, kBTX = (0.61 ± 0.28) keV, given by the cooling flow model and photospheric abundances, with the critical plasma temperature, TB, above which cyclotron emission cooling dominates, defined by equation 10 from ref. 22. The authors provide the ratio \({T}_{{\rm{X}}}/{T}_{B}\approx {L}_{{\rm{tot}}}/{L}_{{\rm{X}}}\) as an estimate of, for a range of accretion rates and global magnetic field strengths, the predicted increase in total luminosity compared to X-ray luminosity if the plasma temperature is sufficient to be dominated by cyclotron emission cooling. The horizontal dotted line indicates TX/TB = 1, where no correction is expected below this. The vertical dotted line indicates the 3σ upper limit on the magnetic field strength from FORS2 spectropolarimetric observations22. The solid lines indicate the increase in total luminosity when compared to the observed X-ray luminosity. b, Predicted additional luminosity for an assumed global magnetic field at the 3σ limit (1.5 kG) across the full range of plasma temperatures and accretion rates calculated in this work (see Extended Data Tables 5 & 6). White space indicates no additional luminosity. The upper plasma temperature from the cooling flow model and accretion rate derived from the isothermal plasma model is shown (solid) along with the 68% uncertainty (dashed). Even at the observational upper limit, the predicted increase due to cyclotron emission cooling is a factor of \({1.1}_{-0.1}^{+0.6}\).
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Cunningham, T., Wheatley, P.J., Tremblay, PE. et al. A white dwarf accreting planetary material determined from X-ray observations. Nature 602, 219–222 (2022). https://doi.org/10.1038/s41586-021-04300-w
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DOI: https://doi.org/10.1038/s41586-021-04300-w
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