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Most lithium-rich low-mass evolved stars revealed as red clump stars by asteroseismology and spectroscopy

Nature Astronomy volume 5, pages 86–93 (2021)Cite this article

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Abstract

Lithium has confused scientists for decades at almost every scale of the universe. Lithium-rich giants are peculiar stars with lithium abundances greater than model prediction. A large fraction of lithium-rich low-mass evolved stars are traditionally supposed to be red giant branch (RGB) stars. Recent studies, however, report that red clump (RC) stars are more frequent than RGB stars. Here, we present a uniquely large systematic study that combines direct asteroseismic analysis and spectroscopy of the lithium-rich stars. The majority of lithium-rich stars are confirmed to be RCs, whereas RGBs are a minority. We reveal that the distribution of lithium-rich RGBs declines steeply with increasing lithium abundance, with an upper limit of around 2.6 dex, whereas the lithium abundances of RCs extend to much higher values. We also find that the distributions of mass and nitrogen abundance are notably different between RC and RGB stars. These findings indicate that there is still an unknown process that significantly affects surface chemical composition in low-mass stellar evolution.

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Fig. 1: The distribution of Li abundance in the entire sample.
Fig. 2: The Li abundance and classification of the high-resolution sample.
Fig. 3: The distribution of mass and [N/Fe] in the sample.
Fig. 4: Comparison of the Li abundances between the HeWD–RGB merger model prediction and the stars in our sample.

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Data availability

The data that support the plots within this paper and other findings of this study are available from the corresponding authors upon reasonable request. Souce data are provided with this paper for Figs. 1–3. The LAMOST DR7 data are available for registered users at http://dr7.lamost.org. The stellar evolution tracks and isochrones data of PARSEC are available at https://people.sissa.it/sbressan/CAF09_V1.2S_M36_LT.

Code availability

The codes that support the plots within this paper and other findings of this study are available from the corresponding authors upon reasonable request. The stellar evolution code MESA used to compute the HeWD–RGB merger is available at http://mesa.sourceforge.net. The code SPECTRUM used to compute the stellar templates for deriving the Li abundance for the low-resolution sample is available at http://www.appstate.edu/~grayro/spectrum/spectrum.html. The codes used to calculate the luminosity and surface gravity from the Gaia parallax are available at https://github.com/YutaoZhou/2020Na_codes. The codes involved in the plots are based on AstroLib, Coyote Library, Matplotlib, Pandas, NumPy and Astropy.

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Acknowledgements

This research is supported by the National Key R&D Program of China (grant no. 2019YFA0405502), the National Natural Science Foundation of China (grant nos. 11988101, 11833006, 11833002, 11890694, 11973052, 11973042, 11603037 and 11973049), and the Strategic Priority Research Program of the Chinese Academy of Sciences (CAS) (grant no. XDB34020205). We acknowledge support by the International Partnership Program of the CAS (grant no. 114A32KYSB20160049). H.-L.Y. acknowledges support from the Youth Innovation Promotion Association of the CAS (grant no. 2019060). T.M. is supported by a Grant-in-Aid for Fellows of the Japan Society for the Promotion of Science (JSPS) (grant no. 18J11326). K.P. acknowledges support from a Mt. Cuba Astronomical Foundation grant. This work is partially based on data collected at the Subaru telescope, which is operated by the National Astronomical Observatory of Japan, and was supported by a JSPS–CAS joint research programme. We acknowledge support from the staff at the Lijiang 2.4 m and 1.8 m telescopes, and support from the Telescope Access Program for accessing the Automated Planet Finder telescope. We acknowledge support from the Cultivation Project for LAMOST Scientific Payoff and Research Achievement of CAMS-CAS, and support from the Astronomical Big Data Joint Research Center, which is co-funded by the National Astronomical Observatories of the CAS and the Alibaba Cloud. The Guoshoujing telescope (LAMOST) is a National Major Scientific Project built by the CAS. Funding for the project has been provided by the National Development and Reform Commission. LAMOST is operated and managed by the National Astronomical Observatories of the CAS. We acknowledge the use of Gaia, APOGEE and Gaia-ESO data, and of the VizieR catalogue access tool. We also thank J.-J. Mao and X.-T. Fu for discussions.

Author information

Author notes

  1. These authors contributed equally: Hong-Liang Yan, Yu-Tao Zhou.

Authors and Affiliations

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

    Hong-Liang Yan, Yu-Tao Zhou, Qi Gao, Jian-Rong Shi, Gang Zhao, Xiao-Dong Xu, Haining Li, Ya-Qian Wu, Yu-Juan Liu, Jing-Kun Zhao & Xi-Long Liang

  2. Department of Astronomy, School of Physics, Peking University, Beijing, China

    Yu-Tao Zhou

  3. Kavli Institute for Astronomy and Astrophysics, Peking University, Beijing, China

    Yu-Tao Zhou

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

    Xianfei Zhang, Yaguang Li, Meng-Qi Jin, Shao-Lan Bi & Jian-Ning Fu

  5. Sydney Institute for Astronomy (SIfA), School of Physics, University of Sydney, Sydney, NSW, Australia

    Yaguang Li

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

    Yaguang Li

  7. School of Astronomy and Space Science, University of Chinese Academy of Sciences, Beijing, China

    Qi Gao, Jian-Rong Shi, Gang Zhao & Xi-Long Liang

  8. National Astronomical Observatory of Japan, Tokyo, Japan

    Wako Aoki & Tadafumi Matsuno

  9. Department of Astronomical Science, School of Physical Sciences, The Graduate University for Advanced Studies (SOKENDAI), Tokyo, Japan

    Wako Aoki & Tadafumi Matsuno

  10. Kapteyn Astronomical Institute, University of Groningen, Groningen, The Netherlands

    Tadafumi Matsuno

  11. Yunnan Astronomical Observatory, Chinese Academy of Sciences, Kunming, China

    Yan Li

  12. LESIA, Observatoire de Paris, Université PSL, CNRS, Sorbonne Université, Université de Paris, Meudon, France

    Benoit Mosser

  13. Apache Point Observatory, New Mexico State University, Sunspot, NM, USA

    Kaike Pan

  14. The Open University of Japan, Chiba, Japan

    Takuma Suda

  15. Research Center for the Early Universe, University of Tokyo, Tokyo, Japan

    Takuma Suda

Authors
  1. Hong-Liang Yan
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  2. Yu-Tao Zhou
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Contributions

H.-L.Y., J.-R.S. and G.Z. proposed and designed this study. H.-L.Y., Y.-T.Z. and J.-R.S. led the data analysis with contributions from Q.G., W.A., T.M., X.-D.X., H.L., and Y.-J.L., X.Z., Yan Li, S.-L.B. and T.S. contributed to the model calculations and discussions. Yaguang Li, Y.-Q.W., M.-Q.J., B.M. and J.-N.F. performed the asteroseismology analysis and derived the evolutionary phases. W.A., H.L. and K.P. carried out the high-resolution spectroscopic observations. J.-K.Z. and X.-L.L. performed the statistical calculation and tests. All of the authors discussed the results and contributed to the writing of the manuscript.

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Correspondence to Jian-Rong Shi or Gang Zhao.

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Extended data

Extended Data Fig. 1 The distributions of mass and [N/Fe] for the Li-rich stars and Li-normal stars.

The gray histogram indicate the Li-normal RGB stars or RC star (as noted in each panel) of which the evolutionary phases identified by Hon et al. 201728, the masses are from Yu et al. 201867, and the [N/Fe] are from ASPCAP33. The bin size is as same as Fig. 3.

Extended Data Fig. 2 The mass versus [N/Fe] in our sample.

Martig et al. (2016) mapped the correlations46 of stellar masses with ASPCAP [N/Fe] using machine learning. Their ‘predicted’ masses of the common sources in our sample are plotted as the grey dots. The red and blue dots are Li-rich RC and RGB stars in our sample, respectively. The region marked with light blue is the most clumped mass range predicted by the HeWD-RGB merger model. For the predicted mass range of 0.8-1.8 M⊙ by the HeWD-RGB model, a fraction of stars indeed show much larger [N/Fe] (also see Fig. 3) compared to other RC stars within this mass range, but there seems no evident correlation between stars with high-mass and stars with high-[N/Fe].

Supplementary information

Supplementary Information

Supplementary Figs. 1–4 and Tables 1–3.

Source data

Source Data Fig. 1

The data that support the plots of Fig. 1.

Source Data Fig. 2

The data that support the plots of Fig. 2.

Source Data Fig. 3

The data that support the plots of Fig. 3.

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Yan, HL., Zhou, YT., Zhang, X. et al. Most lithium-rich low-mass evolved stars revealed as red clump stars by asteroseismology and spectroscopy. Nat Astron 5, 86–93 (2021). https://doi.org/10.1038/s41550-020-01217-8

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