Age dating of an early Milky Way merger via asteroseismology of the naked-eye star ν Indi

Abstract

Over the course of its history, the Milky Way has ingested multiple smaller satellite galaxies1. Although these accreted stellar populations can be forensically identified as kinematically distinct structures within the Galaxy, it is difficult in general to date precisely the age at which any one merger occurred. Recent results have revealed a population of stars that were accreted via the collision of a dwarf galaxy, called Gaia–Enceladus1, leading to substantial pollution of the chemical and dynamical properties of the Milky Way. Here we identify the very bright, naked-eye star ν Indi as an indicator of the age of the early in situ population of the Galaxy. We combine asteroseismic, spectroscopic, astrometric and kinematic observations to show that this metal-poor, alpha-element-rich star was an indigenous member of the halo, and we measure its age to be \(11.0\pm 0.7\) (stat) \(\pm 0.8\) (sys) billion years. The star bears hallmarks consistent with having been kinematically heated by the Gaia–Enceladus collision. Its age implies that the earliest the merger could have begun was 11.6 and 13.2 billion years ago, at 68% and 95% confidence, respectively. Computations based on hierarchical cosmological models slightly reduce the above limits.

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Fig. 1: [Mg/Fe] versus [Fe/H] abundances of a large sample of Milky Way stars, from the APOGEE DR-14 spectroscopic survey data release8.
Fig. 2: Velocities of stars from APOGEE-DR14 having [Fe/H] values within uncertainties of the [Fe/H] value of \(\nu\) Indi.
Fig. 3: Contour plot of the distribution in eccentricity, \(e\), and maximum vertical excursion from the Galactic mid-plane, \({z}_{\max }\), for the same high-[Mg/Fe] (blue) and low-[Mg/Fe] (red) samples of stars as Fig. 2.
Fig. 4: Frequency–power spectrum of the TESS lightcurve of \(\nu\) Indi, showing a rich spectrum of solar-like oscillations. The ordinate is in power spectral density (PSD) units of parts per million squared per μHz.

Data availability

Raw TESS data are available from the MAST portal at https://archive.stsci.edu/access-mast-data. The TASOC lightcurve is available at https://tasoc.dk/. The TESS lightcurve and power spectrum is also available on request from the corresponding author. The high-resolution spectroscopic data are available at http://archive.eso.org/wdb/wdb/adp/phase3_spectral/form (HARPS \(\nu\) Indi), https://www.blancocuaresma.com/s/benchmarkstars (HARPS solar spectrum), and http://archive.eso.org/wdb/wdb/adp/phase3_spectral/form (FEROS). MARCS model atmospheres are available at http://marcs.astro.uu.se/. APOGEE Data Release 14 may be accessed via https://www.sdss.org/dr14/.

Code availability

The adopted asteroseismic modelling results were provided by the BeSPP code, which is available on request from A.M.S. (aldos@ice.csic.es). NLTE corrections were estimated using the interactive online tool at http://nlte.mpia.de. The computation of Kurucz models with ATLAS9 was performed using http://atmos.obspm.fr/index.php/documentation/7. Publicly available codes used to model the data include IRAF (http://ast.noao.edu/data/software), MOOG (https://www.as.utexas.edu/chris/moog.html), the MCMC code emcee (https://github.com/dfm/emcee), the peak-bagging codes DIAMONDS (https://github.com/EnricoCorsaro/DIAMONDS) and TAMCMC-C (https://github.com/OthmanB/TAMCMC-C), the stellar evolution code MESA (http://mesa.sourceforge.net/), and the stellar pulsation code GYRE (https://bitbucket.org/rhdtownsend/gyre/wiki/Home). Other codes used in the analysis—including frequency analysis tools—are available on reasonable request via the corresponding author.

References

  1. 1.

    Helmi, A. et al. The merger that led to the formation of the Milky Way as inner stellar halo and thick disk. Nature 563, 85–88 (2018).

  2. 2.

    Ricker, G. R. et al. Transiting Exoplanet Survey Satellite (TESS). In Space Telescopes and Instrumentation 2014: Optical, Infrared, and Millimeter Wave Vol. 9143 Proc. SPIE 914320 (2014).

  3. 3.

    Stassun, K. G. et al. The TESS input catalog and candidate target list. Astron. J. 156, 102 (2018).

  4. 4.

    GaiaCollaboration et al. Gaia Data Release 2. Summary of the contents and survey properties. Astron. Astrophys. 616, A1 (2018).

  5. 5.

    Mayor, M. et al. Setting new standards with HARPS. Messenger 114, 20–24 (2003).

  6. 6.

    Kaufer, A. et al. Commissioning FEROS, the new high-resolution spectrograph at La Silla. Messenger 95, 8–12 (1999).

  7. 7.

    Bensby, T., Feltzing, S. & Oey, M. S. Exploring the Milky Way stellar disk. A detailed elemental abundance study of 714 F and G dwarf stars in the solar neighbourhood. Astron. Astrophys. 562, A71 (2014).

  8. 8.

    Majewski, S. R. et al. The Apache Point Observatory Galactic Evolution Experiment (APOGEE). Astron. J. 154, 94 (2017).

  9. 9.

    Hayes, C. R. et al. Disentangling the Galactic halo with APOGEE. I. Chemical and kinematical investigation of distinct metal-poor populations. Astrophys. J. 852, 49 (2018).

  10. 10.

    Mackereth, J. T. et al. The origin of accreted stellar halo populations in the Milky Way using APOGEE, Gaia, and the EAGLE simulations. Mon. Not. R. Astron. Soc. 482, 3426–3442 (2019).

  11. 11.

    Font, A. S. et al. Cosmological simulations of the formation of the stellar haloes around disc galaxies. Mon. Not. R. Astron. Soc. 416, 2802–2820 (2011).

  12. 12.

    McCarthy, I. G. et al. Global structure and kinematics of stellar haloes in cosmological hydrodynamic simulations. Mon. Not. R. Astron. Soc. 420, 2245–2262 (2012).

  13. 13.

    Tissera, P. B. et al. The central spheroids of Milky Way mass-sized galaxies. Mon. Not. R. Astron. Soc. 473, 1656–1666 (2018).

  14. 14.

    Schofield, M. et al. The asteroseismic target list for solar-like oscillators observed in 2 minute cadence with the transiting exoplanet survey satellite. Astrophys. J. Suppl. Ser. 241, 12 (2019).

  15. 15.

    Chaplin, W. J. & Miglio, A. Asteroseismology of solar-type and red-giant stars. Annu. Rev. Astron. Astrophys. 51, 353–392 (2013).

  16. 16.

    Bedding, T. R. et al. Gravity modes as a way to distinguish between hydrogen- and helium-burning red giant stars. Nature 471, 608–611 (2011).

  17. 17.

    Bedding, T. R. et al. Solar-like oscillations in the metal-poor subgiant V Indi: constraining the mass and age using asteroseismology. Astrophys. J. 647, 558–563 (2006).

  18. 18.

    Carrier, F. et al. Solar-like oscillations in the metal-poor subgiant \(\nu\) Indi. II. Acoustic spectrum and mode lifetime. Astron. Astrophys. 470, 1059–1063 (2007).

  19. 19.

    Høg, E. et al. The Tycho-2 catalogue of the 2.5 million brightest stars. Astron. Astrophys. 355, L27–L30 (2000).

  20. 20.

    Serenelli, A. et al. The first APOKASC catalog of Kepler dwarf and subgiant stars. Astrophys. J. Suppl. Ser. 233, 23 (2017).

  21. 21.

    Vincenzo, F. et al. The fall of a giant. Chemical evolution of Enceladus, alias the Gaia sausage. Mon. Not. R. Astron. Soc. 487, L47–L52 (2019).

  22. 22.

    Gallart, C. et al. Uncovering the birth of the Milky Way through accurate stellar ages with Gaia. Nat. Astron. 3, 932–939 (2019).

  23. 23.

    Velazquez, H. & White, S. D. M. Sinking satellites and the heating of galaxy discs. Mon. Not. R. Astron. Soc. 304, 254–270 (1999).

  24. 24.

    Blanco-Cuaresma, S., Soubiran, C., Jofré, P. & Heiter, U. The Gaia FGK benchmark stars. High resolution spectral library. Astron. Astrophys. 566, A98 (2014).

  25. 25.

    Tody, D. The IRAF Data Reduction and Analysis System. In Instrumentation in Astronomy VI (ed. Crawford, D. L.) Vol. 627 SPIE Conf. Ser. 733 (1986).

  26. 26.

    Gustafsson, B. et al. A grid of MARCS model atmospheres for late-type stars. I. Methods and general properties. Astron. Astrophys. 486, 951–970 (2008).

  27. 27.

    Chen, Y. Q., Nissen, P. E., Zhao, G., Zhang, H. W. & Benoni, T. Chemical composition of 90 F and G disk dwarfs. Astron. Astrophys. Suppl. 141, 491–506 (2000).

  28. 28.

    Meléndez, J. et al. 18 Sco: a solar twin rich in refractory and neutron-capture elements. Implications for chemical tagging. Astrophys. J. 791, 14 (2014).

  29. 29.

    Reddy, B. E., Tomkin, J., Lambert, D. L. & Allende Prieto, C. The chemical compositions of Galactic disc F and G dwarfs. Mon. Not. R. Astron. Soc. 340, 304–340 (2003).

  30. 30.

    Asplund, M., Grevesse, N., Sauval, A. J. & Scott, P. The chemical composition of the Sun. Annu. Rev. Astron. Astrophys. 47, 481–522 (2009).

  31. 31.

    Morel, T. et al. Atmospheric parameters and chemical properties of red giants in the CoRoT asteroseismology fields. Astron. Astrophys. 564, A119 (2014).

  32. 32.

    Bruntt, H. et al. Accurate fundamental parameters for 23 bright solar-type stars. Mon. Not. R. Astron. Soc. 405, 1907–1923 (2010).

  33. 33.

    Morel, T. The chemical composition of α Centauri AB revisited. Astron. Astrophys. 615, A172 (2018).

  34. 34.

    Bergemann, M., Lind, K., Collet, R., Magic, Z. & Asplund, M. Non-LTE line formation of Fe in late-type stars — I. Standard stars with 1D and 3D model atmospheres. Mon. Not. R. Astron. Soc. 427, 27–49 (2012).

  35. 35.

    Bergemann, M. & Cescutti, G. Chromium: NLTE abundances in metal-poor stars and nucleosynthesis in the Galaxy. Astron. Astrophys. 522, A9 (2010).

  36. 36.

    Bergemann, M., Pickering, J. C. & Gehren, T. NLTE analysis of Co i/Co ii lines in spectra of cool stars with new laboratory hyperfine splitting constants. Mon. Not. R. Astron. Soc. 401, 1334–1346 (2010).

  37. 37.

    Bergemann, M. et al. Red supergiant stars as cosmic abundance probes. II. NLTE effects in J-band silicon lines. Astrophys. J. 764, 115 (2013).

  38. 38.

    Bergemann, M. et al. Non-local thermodynamic equilibrium stellar spectroscopy with 1D and 3D models. I. Methods and application to magnesium abundances in standard stars. Astrophys. J. 847, 15 (2017).

  39. 39.

    Bergemann, M. & Gehren, T. NLTE abundances of Mn in a sample of metal-poor stars. Astron. Astrophys. 492, 823–831 (2008).

  40. 40.

    Bergemann, M. et al. Observational constraints on the origin of the elements. I. 3D NLTE formation of Mn lines in late-type stars. Astron. Astrophys. 631, A80 (2019).

  41. 41.

    Noyes, R. W., Hartmann, L. W., Baliunas, S. L., Duncan, D. K. & Vaughan, A. H. Rotation, convection, and magnetic activity in lower main-sequence stars. Astrophys. J. 279, 763–777 (1984).

  42. 42.

    Henry, T. J., Soderblom, D. R., Donahue, R. A. & Baliunas, S. L. A survey of Ca II H and K chromospheric emission in southern solar-type stars. Astron. J. 111, 439 (1996).

  43. 43.

    Wright, J. T. Do we know of any Maunder minimum stars? Astron. J. 128, 1273 (2004).

  44. 44.

    Mamajek, E. E. & Hillenbrand, L. A. Improved age estimation for solar-type dwarfs using activity-rotation diagnostics. Astrophys. J. 687, 1264–1293 (2008).

  45. 45.

    Zasowski, G. et al. Target selection for the apache point observatory Galactic evolution experiment (APOGEE). Astron. J. 146, 81 (2013).

  46. 46.

    Zasowski, G. et al. Target selection for the SDSS-IV APOGEE-2 survey. Astron. J. 154, 198 (2017).

  47. 47.

    Bovy, J. galpy: a Python library for galactic dynamics. Astrophys. J. Suppl. Ser. 216, 29 (2015).

  48. 48.

    GravityCollaboration et al. Detection of the gravitational redshift in the orbit of the star S2 near the Galactic centre massive black hole. Astron. Astrophys. 615, L15 (2018).

  49. 49.

    Bennett, M. & Bovy, J. Vertical waves in the solar neighbourhood in Gaia DR2. Mon. Not. R. Astron. Soc. 482, 1417–1425 (2019).

  50. 50.

    Schönrich, R., Binney, J. & Dehnen, W. Local kinematics and the local standard of rest. Mon. Not. R. Astron. Soc. 403, 1829–1833 (2010).

  51. 51.

    Jenkins, J. M. et al. The TESS science processing operations center. In Software and Cyberinfrastructure for Astronomy IV Vol. 9913 Proc. SPIE 99133E (2016).

  52. 52.

    Lund, M. N., Handberg, R., Kjeldsen, H., Chaplin, W. J. & Christensen-Dalsgaard, J. Data preparation for asteroseismology with TESS. In European Physical Journal Web of Conferences Vol. 160, 01005 (2017).

  53. 53.

    Kjeldsen, H. et al. Solar-like oscillations in α Centauri B. Astrophys. J. 635, 1281–1290 (2005).

  54. 54.

    Bedding, T. R. et al. Solar-like oscillations in the G2 subgiant β hydri from dual-site observations. Astrophys. J. 663, 1315–1324 (2007).

  55. 55.

    Benomar, O., Appourchaux, T. & Baudin, F. The solar-like oscillations of HD 49933: a Bayesian approach. Astron. Astrophys. 506, 15–32 (2009).

  56. 56.

    Gaulme, P., Appourchaux, T. & Boumier, P. Mode width fitting with a simple Bayesian approach. Application to CoRoT targets HD 181420 and HD 49933. Astron. Astrophys. 506, 7–14 (2009).

  57. 57.

    Mosser, B. et al. Spin down of the core rotation in red giants. Astron. Astrophys. 548, A10 (2012).

  58. 58.

    Corsaro, E. & De Ridder, J. DIAMONDS: a new Bayesian nested sampling tool. Application to peak bagging of solar-like oscillations. Astron. Astrophys. 571, A71 (2014).

  59. 59.

    Corsaro, E., De Ridder, J. & García, R. A. Bayesian peak bagging analysis of 19 low-mass low-luminosity red giants observed with Kepler. Astron. Astrophys. 579, A83 (2015).

  60. 60.

    Vrard, M. et al. Helium signature in red giant oscillation patterns observed by Kepler. Astron. Astrophys. 579, A84 (2015).

  61. 61.

    Nielsen, M. B., Schunker, H., Gizon, L., Schou, J. & Ball, W. H. Limits on radial differential rotation in Sun-like stars from parametric fits to oscillation power spectra. Astron. Astrophys. 603, A6 (2017).

  62. 62.

    Roxburgh, I. W. Anomalies in the Kepler asteroseismic legacy project SATA. A re-analysis of 16 Cyg A and B, KIC 8379927 and 6 solar-like stars. Astron. Astrophys. 604, A42 (2017).

  63. 63.

    García Saravia Ortiz de Montellano, A., Hekker, S. & Themeßl, N. Automated asteroseismic peak detections. Mon. Not. R. Astron. Soc. 476, 1470–1496 (2018).

  64. 64.

    Benomar, O. et al. Asteroseismic detection of latitudinal differential rotation in 13 Sun-like stars. Science 361, 1231–1234 (2018).

  65. 65.

    Kallinger, T., Beck, P. G., Stello, D. & Garcia, R. A. Non-linear seismic scaling relations. Astron. Astrophys. 616, A104 (2018).

  66. 66.

    Davies, G. R. et al. Why should we correct reported pulsation frequencies for stellar line-of-sight Doppler velocity shifts? Mon. Not. R. Astron. Soc. 445, L94–L98 (2014).

  67. 67.

    Casagrande, L. & VandenBerg, D. A. Synthetic stellar photometry — II. Testing the bolometric flux scale and tables of bolometric corrections for the Hipparcos/Tycho, Pan-STARRS1, SkyMapper, and JWST systems. Mon. Not. R. Astron. Soc. 475, 5023–5040 (2018).

  68. 68.

    Stassun, K. G. & Torres, G. Eclipsing binaries as benchmarks for trigonometric parallaxes in the Gaia era. Astron. J. 152, 180 (2016).

  69. 69.

    Torres, G. et al. Improved spectroscopic parameters for transiting planet hosts. Astrophys. J. 757, 161 (2012).

  70. 70.

    Salaris, M., Chieffi, A. & Straniero, O. The alpha-enhanced isochrones and their impact on the FITS to the Galactic globular cluster system. Astrophys. J. 414, 580–600 (1993).

  71. 71.

    Rendle, B. M. et al. AIMS — a new tool for stellar parameter determinations using asteroseismic constraints. Mon. Not. R. Astron. Soc. 484, 771–786 (2019).

  72. 72.

    Ong, J. M. J. & Basu, S. Explaining deviations from the scaling relationship of the large frequency separation. Astrophys. J. 870, 41 (2019).

  73. 73.

    SilvaAguirre, V. et al. Standing on the shoulders of dwarfs: the Kepler asteroseismic LEGACY sample. II. Radii, masses, and ages. Astrophys. J. 835, 173 (2017).

  74. 74.

    Mosumgaard, J. R., Ball, W. H., SilvaAguirre, V., Weiss, A. & Christensen-Dalsgaard, J. Stellar models with calibrated convection and temperature stratification from 3D hydrodynamics simulations. Mon. Not. R. Astron. Soc. 478, 5650–5659 (2018).

  75. 75.

    Ball, W. H. & Gizon, L. Surface-effect corrections for oscillation frequencies of evolved stars. Astron. Astrophys. 600, A128 (2017).

  76. 76.

    Lebreton, Y. & Goupil, M. J. Asteroseismology for ‘à la carte’ stellar age-dating and weighing. Age and mass of the CoRoT exoplanet host HD 52265. Astron. Astrophys. 569, A21 (2014).

  77. 77.

    Yildiz, M., Çelik Orhan, Z. & Kayhan, C. Fundamental properties of Kepler and CoRoT targets. III. Tuning scaling relations using the first adiabatic exponent. Mon. Not. R. Astron. Soc. 462, 1577–1590 (2016).

  78. 78.

    Lacey, C. & Cole, S. Merger rates in hierarchical models of galaxy formation. Mon. Not. R. Astron. Soc. 262, 627–649 (1993).

  79. 79.

    Belokurov, V., Erkal, D., Evans, N. W., Koposov, S. E. & Deason, A. J. Co-formation of the disc and the stellar halo. Mon. Not. R. Astron. Soc. 478, 611–619 (2018).

  80. 80.

    Mo, H., van den Bosch, F. C. & White, S. Galaxy Formation and Evolution (Cambridge University Press, 2010).

  81. 81.

    Myeong, G. C., Vasiliev, E., Iorio, G., Evans, N. W. & Belokurov, V. Evidence for two early accretion events that built the Milky Way stellar halo. Mon. Not. R. Astron. Soc. 488, 1235–1247 (2019).

  82. 82.

    Correa, C. A., Wyithe, J. S. B., Schaye, J. & Duffy, A. R. The accretion history of dark matter haloes. I. The physical origin of the universal function. Mon. Not. R. Astron. Soc. 450, 1514–1520 (2015).

  83. 83.

    Correa, C. A., Wyithe, J. S. B., Schaye, J. & Duffy, A. R. The accretion history of dark matter haloes. II. The connections with the mass power spectrum and the density profile. Mon. Not. R. Astron. Soc. 450, 1521–1537 (2015).

  84. 84.

    Correa, C. A., Wyithe, J. S. B., Schaye, J. & Duffy, A. R. The accretion history of dark matter haloes. III. A physical model for the concentration-mass relation. Mon. Not. R. Astron. Soc. 452, 1217–1232 (2015).

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Acknowledgements

This paper includes data collected by the TESS mission, which are publicly available from the Mikulski Archive for Space Telescopes (MAST). Resources supporting this work were provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center for the production of the SPOC data products. W.J.C. acknowledges support from the UK Science and Technology Facilities Council (STFC) and UK Space Agency. Funding for the Stellar Astrophysics Centre is provided by The Danish National Research Foundation (grant agreement number DNRF106). This research was partially conducted during the Exostar19 programme at the Kavli Institute for Theoretical Physics at UC Santa Barbara, which was supported in part by the National Science Foundation under grant number NSF PHY-1748958. A.M., J.T.M., F.V. and J.M. acknowledge support from the ERC Consolidator Grant funding scheme (project ASTEROCHRONOMETRY, grant agreement number 772293). F.V. acknowledges the support of a Fellowship from the Center for Cosmology and AstroParticle Physics at The Ohio State University. W.H.B. and M.B.N. acknowledge support from the UK Space Agency. K.J.B. is supported by the National Science Foundation under award AST-1903828. M.B.N. acknowledges partial support from the NYU Abu Dhabi Center for Space Science under grant number G1502. A.M.S. is partially supported by the Spanish Government (ESP2017-82674-R) and Generalitat de Catalunya (2017-SGR-1131). T.M. acknowledges financial support from Belspo for contract PRODEX PLATO. H.K. acknowledges support from the European Social Fund via the Lithuanian Science Council grant number 09.3.3-LMT-K-712-01-0103. S.B. acknowledges support from NSF grant AST-1514676 and NASA grant 80NSSC19K0374. V.S.A. acknowledges support from the Independent Research Fund Denmark (research grant 7027-00096B). D.H. acknowledges support by the National Aeronautics and Space Administration (80NSSC18K1585, 80NSSC19K0379) awarded through the TESS Guest Investigator Program and by the National Science Foundation (AST-1717000). T.S.M. acknowledges support from a visiting fellowship at the Max Planck Institute for Solar System Research. Computational resources were provided through XSEDE allocation TG-AST090107. D.L.B. acknowledges support from NASA under grant NNX16AB76G. T.L.C. acknowledges support from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement number 792848 (PULSATION). This work was supported by FCT/MCTES through national funds (PIDDAC) by means of grant UID/FIS/04434/2019. K.J.B., S.H., J.S.K. and N.T. are supported by the European Research Council under the European Community’s Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement number 338251 (StellarAges). E.C. is funded by the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement number 664931. L.G.-C. acknowledges support from the MINECO FPI-SO doctoral research project SEV-2015-0548-17-2 and predoctoral contract BES-2017-082610. P.G. is supported by the German space agency (Deutsches Zentrum für Luft- und Raumfahrt) under PLATO data grant 50OO1501. R.K. acknowledges support from the UK Science and Technology Facilities Council (STFC), under consolidated grant ST/L000733/1. M.S.L. is supported by the Carlsberg Foundation (grant agreement number CF17-076). Z.C.O., S.O. and M.Y. acknowledge support from the Scientific and Technological Research Council of Turkey (TÜBİTAK:118F352). S.M. acknowledges support from the Spanish ministry through the Ramon y Cajal fellowship number RYC-2015-17697. T.S.R. acknowledges financial support from Premiale 2015 MITiC (PI B. Garilli). R.Sz. acknowledges the support from NKFIH grant project No. K-115709, and the Lendület program of the Hungarian Academy of Science (project number 2018-7/2019). J.T. acknowledges support was provided by NASA through the NASA Hubble Fellowship grant number 51424 awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., for NASA, under contract NAS5-26555. This work was supported by FEDER through COMPETE2020 (POCI-01-0145-FEDER-030389. A.M.B. acknowledges funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 749962 (project THOT). A.M. and P.R. acknowledge the support of the Government of India, Department of Atomic Energy, under Project No. 12-R&D-TFR-6.04-0600. K.J.B. is an NSF Astronomy and Astrophysics Postdoctoral Fellow and DIRAC Fellow.

Author information

W.J.C. led the project, with help from A.M.S., A.M., S.B. and W.H.B. W.J.C., H.K., W.H.B., H.M.A., T.R.B., R.A.G., D.H., K.J.B., D.L.B., O.B., L.B., T.L.C., E.C., L.G.-C., G.R.D., Y.P.E., P.G., H.G., O.J.H., A.H., S.H., R.H., A.J., R.K., J.S.K., T.K., M.S.L., S.M., B.M., A.M.B., M.B.N., I.W.R., H.S., R.S., N.T., A.E.L.T., M.V. and T.M.W. worked on extracting mode parameters from the TESS data. R.H. and M.N.L. oversaw production of the TESS lightcurves for the asteroseismic analysis. A.M.S., A.M., S.B., W.H.B., A.S., K.V., J.R.M., V.S.A., A.M., P.R., Y.B., J.O., P.B., M.B., K.J.B., D.B., Z.C.O., M.P.D.M., Z.G., S.H., J.M., S.O., B.M.R., T.S.R., D.S., J.T., W.E.v.R., A.W. and M.Y. worked on modelling \(\nu\) Indi. T.M. performed the spectroscopic analysis of the archival HARPS and FEROS data on \(\nu\) Indi. M.B. assessed the impact of NLTE on the spectroscopic analysis. R.E. performed the chromospheric activity analysis of \(\nu\) Indi. J.T.M. performed the kinematics analysis and comparison of the chemistry of \(\nu\) Indi with samples of Milky Way stars, and F.V. computed the theoretical prior based on hierarchical cosmological models of structure formation. D.H., K.G.S. and B.S. provided estimates of the luminosity of \(\nu\) Indi. J.C.-D., H.K., W.J.C., T.R.B., S.D.K. and S.B. are key architects of TASC (members of its board), while G.R.R., J.M.J., D.W.L., R.K.V. and J.N.W. are key architects of the TESS Mission. W.J.C., D.H., T.A., A.M.S., O.C., R.A.G. and T.S.M. oversaw the TASC working groups on solar-like oscillators and, with M.S. and T.L.C., oversaw the selection of short-cadence targets for asteroseismic studies of solar-like oscillators with TESS, which included ensuring \(\nu\) Indi was included on the list (and hence received the TESS short-cadence data needed to make this study possible). All authors have contributed to the interpretation of the data and the results, and to discussion and comments on the paper.

Correspondence to William J. Chaplin.

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Extended data

Extended Data Fig. 1 An échelle diagram showing the observed frequencies (in grey) and the best-fitting model frequencies (coloured symbols).

The diagram was made by dividing the spectrum into segments of length equal to the average frequency separation \(\Delta \nu\) between consecutive overtones, which were then stacked in ascending order, so one plots \(\nu\) versus (\(\nu\) mod \(\Delta \nu\)). The \(l=0\) (radial) modes are plotted with square symbols, the \(l=1\) (dipole) modes are plotted with circular symbols, and the \(l=2\) (quadrupole) modes are plotted with triangular symbols. Symbol sizes reflect the relative visibilities of the different modes, with a suitable correction included to reflect the impact of mixing on the mode inertia. All model frequencies are plotted, irrespective of whether we were able to report a reliable observed frequency for them.

Extended Data Fig. 2 Inference on the epoch of the Gaia–Enceladus merger.

The dashed black line shows the measured cumulative posterior on \(\nu\) Indi. The dot-dashed black line is the estimated cumulative prior probability for the merger assuming a virial mass of the Gaia–Enceladus dark-matter halo of \({M}_{{\rm{Enc}}}=1\times 1{0}^{10}\ {{\rm{M}}}_{\odot }\). The solid black line shows the cumulative probability for the merger, dependent on the estimated age of \(\nu\) Indi and the assumed 2-Gyr-wide merger duration; while the solid red line shows the cumulative probability for the merger also taking into account the merger prior (different in each panel, since this depends on \({M}_{{\rm{Enc}}}\)).

Extended Data Fig. 3 As for Extended Data Fig. 2, but now assuming a virial mass of the Gaia–Enceladus dark-matter halo of 1 × 1011 M.

We note the measured cumulative posterior on \(\nu\) Indi (dashed black line) and the cumulative probability for the merger (dependent on the estimated age of \(\nu\) Indi and the assumed 2-Gyr-wide merger duration; black line) are the same as in Extended Data Fig. 2.

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Chaplin, W.J., Serenelli, A.M., Miglio, A. et al. Age dating of an early Milky Way merger via asteroseismology of the naked-eye star ν Indi. Nat Astron (2020). https://doi.org/10.1038/s41550-019-0975-9

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