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Discovery of post-mass-transfer helium-burning red giants using asteroseismology

Nature Astronomy volume 6, pages 673–680 (2022)Cite this article

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Abstract

A star expands to become a red giant when it has fused all the hydrogen in its core into helium. If the star is in a binary system, its envelope can overflow onto its companion or be ejected into space, leaving a hot core and potentially forming a subdwarf B star1,2,3. However, most red giants that have partially transferred envelopes in this way remain cool on the surface and are almost indistinguishable from those that have not. Among ~7,000 helium-burning red giants observed by NASA’s Kepler mission, we use asteroseismology to identify two classes of stars that must have undergone considerable mass loss, presumably due to stripping in binary interactions. The first class comprises about seven underluminous stars with smaller helium-burning cores than their single-star counterparts. Theoretical models show that these small cores imply the stars had much larger masses when ascending the red giant branch. The second class consists of 32 red giants with masses down to 0.5 M⊙, whose implied ages would exceed the age of the universe had no mass loss occurred. The numbers are consistent with binary statistics, and our results open up new possibilities to study the evolution of post-mass-transfer binary systems.

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Fig. 1: Fundamental parameters of CHeB stars in the Kepler red giant sample.
Fig. 2: [M/H] versus mass for CHeB stars in the Kepler red giant sample.
Fig. 3: Mass distributions of low-luminosity RGB (νmax > 80 μHz) and CHeB stars in the Kepler red giant sample (Methods).

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Data availability

We made use of publicly available data in this work. Kepler data are available from the MAST portal at https://archive.stsci.edu/access-mast-data, APOGEE data at https://www.sdss.org/dr16/, LAMOST data at http://dr5.lamost.org/v3/doc/vac and https://github.com/hypergravity/paperdata and Gaia data at https://gea.esac.esa.int/archive/. The data needed to reproduce this work are available at GitHub (https://github.com/parallelpro/Yaguang_stripped_rg_repo). All other data are available from the corresponding author upon reasonable request.

Code availability

This work is made possible by the following open-source software: NumPy130, SciPy131, Matplotlib132, Astropy133,134, Pandas135, MESA88,89,90,91,92, MESA SDK136, GYRE93, pySYD82, Lightkurve137, EchellePlotter (https://github.com/9yifanchen9/EchellePy) and ISOCLASSIFY119,120. The scripts used in this work is available at a curated GitHub repository (https://github.com/parallelpro/Yaguang_stripped_rg_repo).

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Acknowledgements

We thank M. Hon, K. Brogaard and Y. Elsworth for their comments.

T.R.B and D.H. acknowledge funding from the Australian Research Council (Discovery Project DP210103119). D.H. also acknowledges support from the Alfred P. Sloan Foundation and the National Aeronautics and Space Administration (80NSSC19K0597). M.J. acknowledges the Lasker Fellowship grant. S.B. acknowledges the Joint Research Fund in Astronomy (U2031203) under a cooperative agreement between the National Natural Science Foundation of China (NSFC) and Chinese Academy of Sciences (CAS) and the NSFC grants 12090040 and 12090042. G.L. acknowledges support from the project BEAMING ANR-18-CE31-0001 of the French National Research Agency (ANR) and from the Centre National d’Etudes Spatiales (CNES).

We gratefully acknowledge the Kepler teams, whose efforts made these results possible. Funding for the Kepler mission is provided by the NASA Science Mission Directorate. This paper includes data collected by the Kepler mission and obtained from the MAST data archive at the Space Telescope Science Institute (STScI). STScI is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5–26555.

Guoshoujing Telescope (LAMOST) is a National Major Scientific Project built by the Chinese Academy of Sciences. Funding for the project has been provided by the National Development and Reform Commission. LAMOST is operated and managed by the National Astronomical Observatories, Chinese Academy of Sciences.

This work presents results from the European Space Agency (ESA) space mission Gaia. Gaia data are being processed by the Gaia Data Processing and Analysis Consortium (DPAC). Funding for the DPAC is provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement (MLA). The Gaia mission website is https://www.cosmos.esa.int/gaia. The Gaia archive website is https://archives.esac.esa.int/gaia.

Funding for the Sloan Digital Sky Survey IV has been provided by the Alfred P. Sloan Foundation, the US Department of Energy Office of Science and the participating institutions.

We acknowledge Sydney Informatics (a core research facility of the University of Sydney), the high performance computing (HPC) cluster Artemis from the University of Sydney, the HPC cluster headnode from the School of Physics and the HPC cluster Gadi from the National Computational Infrastructure (NCI Australia, an NCRIS-enabled capability supported by the Australian Government) for providing the HPC resources that have contributed to the research results reported within this paper.

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Authors and Affiliations

  1. Sydney Institute for Astronomy (SIfA), School of Physics, University of Sydney, Sydney, New South Wales, Australia

    Yaguang Li, Timothy R. Bedding, Simon J. Murphy, Yifan Chen, Dion Marks, Michael R. Hayden, Daniel R. Hey & Sanjib Sharma

  2. Stellar Astrophysics Centre, Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark

    Yaguang Li, Timothy R. Bedding, Simon J. Murphy, Dennis Stello & Daniel R. Hey

  3. School of Physics, University of New South Wales, Sydney, New South Wales, Australia

    Dennis Stello & Benjamin T. Montet

  4. Institute for Astronomy, University of Hawaiʻi, 2680 Woodlawn Drive, Honolulu, HI, 96822, USA

    Daniel Huber

  5. Space Telescope Science Institute, Baltimore, MD, USA

    Meridith Joyce

  6. Department of Astronomy, Beijing Normal University, Beijing, China

    Xianfei Zhang & Shaolan Bi

  7. Department of Astrophysics, American Museum of Natural History, Manhattan, NY, USA

    Isabel L. Colman

  8. IRAP, Université de Toulouse, CNRS, CNES, UPS, Toulouse, France

    Gang Li

  9. UNSW Data Science Hub, University of New South Wales, Sydney, New South Wales, Australia

    Benjamin T. Montet

  10. Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences, Beijing, China

    Yaqian Wu

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  1. Yaguang Li
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Contributions

Y.L., T.R.B., D.S., Y.C., I.L.C. and G.L. analysed photometric data; S.J.M., D.H., X.Z., S.B and D.R.H. contributed to binary confirmation; Y.L., M.J. and D.M. constructed theoretical models; B.T.M., M.R.H., S.S. and Y.W. interpreted spectroscopic data. All authors discussed the results and commented on the manuscript.

Corresponding authors

Correspondence to Yaguang Li or Timothy R. Bedding.

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Nature Astronomy thanks Nicholas Rui, Oliver Hall and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Galaxia simulation of CHeB stars in the Kepler field.

a, The seismic quantity \({\nu }_{\max }^{0.75}/{{\Delta }}\nu\) versus \({\nu }_{\max }\). The ZAHeB edge (the black dashed line) is represented by a spline (defined by the crosses). The inset of a shows the distribution of the vertical distances to the edge. The distribution is fitted by a half-Gaussian half-Lorentzian profile, shown by the green line. The standard deviation of the half-Gaussian profile represents the intrinsic broadening of the ZAHeB edge. b, The metallicity–mass diagram. The dashed line is the lowest mass a star can be without mass loss given a metallicity, determined with MIST models (see Methods).

Extended Data Fig. 2 Power spectra for three representative stars, including a regular CHeB star (a), an underluminous star (b), and a very low-mass star (c).

The right panels show their locations on the mass–radius diagram marked by the star symbols. The power spectra (grey lines) are smoothed by 0.06Δν (overlaid black lines). The integers 0–2 represent the angular-degree l. The locations of \({\nu }_{\max }\) are indicated by the arrows. The observed values of Δν and ΔP (see Extended Data Fig. 3) are represented by the lengths of the black line segments.

Extended Data Fig. 3 Period échelle diagrams for the regular CHeB star (a), the under-luminous star (b), and the very-low-mass star (c) that are shown in Extended Fig. 2.

The modes are marked by circles (l = 0), triangles (l = 1) and squares (l = 2). Error bars are not shown. The blue dashed lines connect the l = 1 modes in order. We adjusted the widths of the échelle diagrams such that the l = 1 modes form a “zigzag” pattern37. Those widths correspond to the period spacings of l = 1 modes, which confirm them as CHeB stars.

Extended Data Fig. 4 Stellar models for KIC 8367834 within 3σ of the classical constraints, colour-coded with probability using constraints from parallax, Teff, metallicity, and oscillation frequencies.

a, The Hertzsprung–Russell diagram. b, The mass–radius diagram. c, The seismic quantity \({\nu }_{\max }^{0.75}/{{\Delta }}\nu\) versus \({\nu }_{\max }\). d, Mass versus \({\nu }_{\max }\). The black boxes show the 1.5σ confidence regions, either directly from observations (L, Teff, \({\nu }_{\max }\), Δν) or from the scaling relations (M, R).

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Supplementary Fig. 1 and Tables 1 and 2.

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Li, Y., Bedding, T.R., Murphy, S.J. et al. Discovery of post-mass-transfer helium-burning red giants using asteroseismology. Nat Astron 6, 673–680 (2022). https://doi.org/10.1038/s41550-022-01648-5

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