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A nearly pristine star from the Large Magellanic Cloud

Nature Astronomy (2026)Cite this article

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Abstract

The first stars formed out of pristine gas, causing them to be so massive that none are expected to have survived until today. If their direct descendants were sufficiently low-mass stars, such stars could exist today and would be recognizable by having the lowest metallicities (abundance of elements heavier than helium). Here we present the independent identification and detailed chemical analysis of the star SDSS J0715−7334, finding ultralow elemental abundances of both iron and carbon ([Fe/H] = −4.3, [C/Fe] < −0.2) and total metallicity Z < 7.8 × 10−7 (log Z/Z⊙ < −4.3). The star’s orbit indicates that it originates from the halo of the Large Magellanic Cloud. Its heavy element abundance pattern can be explained by a primordial supernova with an initial mass of 30 solar masses. This star is over ten times more chemically pristine than the most extreme high-redshift galaxies currently found by the James Webb Space Telescope. It is sufficiently metal-poor that current models of low-mass star formation require dust cooling to explain its existence.

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Fig. 1: J0715−7334 MIKE spectrum.
Fig. 2: Carbon and iron abundances of ultra-metal-poor stars.
Fig. 3: Kinematic properties.
Fig. 4: Population III supernova progenitor constraints.

Data availability

The BOSS spectrum of J0715−7334 (sdss_id 95803549) will become publicly available in SDSS Data Release 20, as will the background halo star sample of MINESweeper results. The individual line measurements, normalized MIKE spectrum, and literature star abundances and kinematics are available at https://doi.org/10.5281/zenodo.18483957 (ref. 198).

Code availability

Most codes used for analysis are publicly available on GitHub, including LESSPayne54, MOOG83,84,85, TSFitPy17, Turbospectrum88 and agama148. The exception is that M3DIS18 and the version of Multi3D used are not public yet, but a public release is planned.

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Acknowledgements

We acknowledge The College at University of Chicago for their support of undergraduate research that led to the identification of this star and supporting its analysis. This paper includes data gathered with the 6.5 meter Magellan Telescopes located at Las Campanas Observatory, Chile. We thank the staff at Las Campanas Observatory for their support making the observations possible. A.P.J. thanks A. Drlica-Wagner, H. Katz, J. Greene and D. Souto for useful discussions; and I. Roederer, I. Thompson and S. Shectman for a comparison spectrum of CD−38 245. We acknowledge support from the National Science Foundation under awards AST-2206264 (A.P.J., S.M.-T., Z.Z. and P.N.T.), AST-2338645 (K.C.S.) and DGE2139841 (W.C.). A.P.J. acknowledges the Alfred P. Sloan Research Fellowship and the University of Chicago’s Research Computing Center. M.B. is supported through the Lise Meitner grant from the Max Planck Society and through the European Research Council (ERC) under the European Unions Horizon 2020 research and innovation programme (grant agreement number 949173). M.H. and J.A.J. acknowledge support from NASA grant 80NSSC24K0637. C.F.P.L. acknowledges funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement number 852839) and the Agence Nationale de la Recherche (ANR project ANR-24-CPJ1-0160-01). W.C. acknowledges support from a Gruber Science Fellowship at Yale University. J.G.F.-T. acknowledges the support provided by ANID Fondecyt Regular No. 1260371, ANID Fondecyt Postdoc No. 3230001 (sponsoring researcher), the Joint Committee ESO-Government of Chile under the agreement 2023 ORP 062/2023 and the support of the Doctoral Program in Artificial Intelligence, DISC-UCN. This project has been supported by the LP2021-9 Lendület grant of the Hungarian Academy of Sciences. This work benefited from a workshop supported by the National Science Foundation under grant number OISE-1927130 (IReNA), the Kavli Institute for Cosmological Physics, and the University of Chicago Data Science Institute. Funding for the Sloan Digital Sky Survey V has been provided by the Alfred P. Sloan Foundation, the Heising-Simons Foundation, the National Science Foundation and the participating institutions. SDSS acknowledges support and resources from the Center for High-Performance Computing at the University of Utah. SDSS telescopes are located at Apache Point Observatory, funded by the Astrophysical Research Consortium and operated by New Mexico State University, and at Las Campanas Observatory, operated by the Carnegie Institution for Science. The SDSS website is www.sdss.org. SDSS is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS Collaboration, including the Carnegie Institution for Science, Chilean National Time Allocation Committee (CNTAC) ratified researchers, Caltech, the Gotham Participation Group, Harvard University, Heidelberg University, The Flatiron Institute, The Johns Hopkins University, L’Ecole polytechnique fédérale de Lausanne (EPFL), Leibniz-Institut für Astrophysik Potsdam (AIP), Max-Planck-Institut für Astronomie (MPIA Heidelberg), Max-Planck-Institut für Extraterrestrische Physik (MPE), Nanjing University, National Astronomical Observatories of China (NAOC), New Mexico State University, The Ohio State University, Pennsylvania State University, Smithsonian Astrophysical Observatory, Space Telescope Science Institute (STScI), the Stellar Astrophysics Participation Group, Universidad Nacional Autónoma de México, University of Arizona, University of Colorado Boulder, University of Illinois at Urbana-Champaign, University of Toronto, University of Utah, University of Virginia, Yale University, and Yunnan University. 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. Figure 3 uses a Gaia image by the Gaia Data Processing and Analysis Consortium (DPAC); A. Moitinho/A. F. Silva/M. Barros/C. Barata, University of Lisbon, Portugal; H. Savietto, Fork Research, Portugal. This paper includes data collected by the TESS mission. Funding for the TESS mission is provided by the NASA’s Science Mission Directorate. The national facility capability for SkyMapper has been funded through ARC LIEF grant LE130100104 from the Australian Research Council, awarded to the University of Sydney, the Australian National University, Swinburne University of Technology, the University of Queensland, the University of Western Australia, the University of Melbourne, Curtin University of Technology, Monash University and the Australian Astronomical Observatory. SkyMapper is owned and operated by The Australian National University’s Research School of Astronomy and Astrophysics. The survey data were processed and provided by the SkyMapper Team at ANU. The SkyMapper node of the All-Sky Virtual Observatory (ASVO) is hosted at the National Computational Infrastructure (NCI). Development and support of the SkyMapper node of the ASVO has been funded in part by Astronomy Australia Limited (AAL) and the Australian Government through the Commonwealth’s Education Investment Fund (EIF) and National Collaborative Research Infrastructure Strategy (NCRIS), particularly the National eResearch Collaboration Tools and Resources (NeCTAR) and the Australian National Data Service Projects (ANDS). This publication makes use of data products from the Two Micron All-Sky Survey, which is a joint project of the University of Massachusetts and the Infrared Processing and Analysis Center/California Institute of Technology, funded by the National Aeronautics and Space Administration and the National Science Foundation. This publication makes use of data products from the Wide-field Infrared Survey Explorer, which is a joint project of the University of California, Los Angeles, and the Jet Propulsion Laboratory/California Institute of Technology, funded by the National Aeronautics and Space Administration. This research has made use of the VizieR catalogue access tool, CDS, Strasbourg, France. The original description of the VizieR service was published in ref. 200. This research has made use of NASA’s Astrophysics Data System Bibliographic Services; the arXiv preprint server operated by Cornell University; and the SIMBAD databases hosted by the Strasbourg Astronomical Data Center.

Author information

Authors and Affiliations

  1. Department of Astronomy and Astrophysics, University of Chicago, Chicago, IL, USA

    Alexander P. Ji, Selenna Mejias-Torres, Zhongyuan Zhang, Hillary Diane Andales, Ha Do, Natalie M. Orrantia, Rithika Tudmilla, Pierre N. Thibodeaux & Guilherme Limberg

  2. Kavli Institute for Cosmological Physics, University of Chicago, Chicago, IL, USA

    Alexander P. Ji & Guilherme Limberg

  3. NSF-Simons AI Institute for the Sky (SkAI), Chicago, IL, USA

    Alexander P. Ji

  4. Center for Astrophysics ∣ Harvard & Smithsonian, Cambridge, MA, USA

    Vedant Chandra

  5. Max Planck Institute for Astronomy, Heidelberg, Germany

    Philipp Eitner & Maria Bergemann

  6. Heidelberg University, Heidelberg, Germany

    Philipp Eitner & Tadafumi Matsuno

  7. William H. Miller III Department of Physics and Astronomy, Johns Hopkins University, Baltimore, MD, USA

    Kevin C. Schlaufman

  8. Department of Physics and Astronomy, Vanderbilt University, Nashville, TN, USA

    Keivan G. Stassun

  9. Department of Astronomy and Center for Cosmology and AstroParticle Physics, The Ohio State University, Columbus, OH, USA

    Madeline Howell & Jennifer A. Johnson

  10. Department of Astronomy, University of Florida, Gainesville, FL, USA

    Jamie Tayar

  11. School of Physics & Astronomy, Monash University, Clayton, Victoria, Australia

    Andrew R. Casey & Riley Thai

  12. Center for Computational Astrophysics, Flatiron Institute, New York, NY, USA

    Andrew R. Casey

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

    Joleen K. Carlberg

  14. Department of Astronomy, Yale University, New Haven, CT, USA

    William Cerny

  15. Núcleo UCN en Arqueología Galáctica - Inst. de Astronomía, Universidad Católica del Norte, Antofagasta, Chile

    José G. Fernández-Trincado

  16. Departamento de Ingeniería de Sistemas y Computación, Universidad Católica del Norte, Antofagasta, Chile

    José G. Fernández-Trincado

  17. Department of Astronomy, The University of Texas at Austin, Austin, TX, USA

    Keith Hawkins

  18. The Observatories of the Carnegie Institution for Science, Pasadena, CA, USA

    Juna A. Kollmeier

  19. LIRA, Observatoire de Paris, Université PSL, Sorbonne Université, Université Paris Cité, CY Cergy Paris Université, CNRS, Meudon, France

    Chervin F. P. Laporte

  20. Institut de Ci‘encies del Cosmos (ICCUB), Universitat de Barcelona, Barcelona, Spain

    Chervin F. P. Laporte

  21. Institut d’Estudis Espacials de Catalunya (IEEC), Barcelona, Spain

    Chervin F. P. Laporte

  22. Kavli IPMU (WPI), UTIAS, The University of Tokyo, Kashiwa, Chiba, Japan

    Chervin F. P. Laporte

  23. ELTE Eötvös Loránd University, Gothard Astrophysical Observatory, Szombathely, Hungary

    Szabolcs Mészáros

  24. MTA-ELTE Lendület ‘Momentum’ Milky Way Research Group, Szombathely, Hungary

    Szabolcs Mészáros

  25. HUN-REN CSFK, Konkoly Observatory; Eötvös Loránd University, Institute of Physics and Astronomy, Budapest, Hungary

    Szabolcs Mészáros

  26. Department of Astronomy, University of Illinois at Urbana-Champaign, Urbana, IL, USA

    Sean Morrison

  27. Department of Physics, Montana State University, Bozeman, MT, USA

    David L. Nidever

  28. Center for Astrophysics and Space Astronomy, University of Colorado, Boulder, CO, USA

    Guy S. Stringfellow

  29. Department of Astronomy & Astrophysics, The Pennsylvania State University, University Park, PA, USA

    Donald P. Schneider

  30. The Institute for Gravitation for and the Cosmos, The Pennsylvania State University, University Park, PA, USA

    Donald P. Schneider

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  1. Alexander P. Ji
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  2. Vedant Chandra
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Contributions

A.P.J. led the conceptualization, MIKE observations, stellar parameter and chemical abundance analysis, population III analysis, writing, and interpretation. V.C. led the BOSS and kinematic analysis and contributed to writing and interpretation. S.M.-T. led the NLTE abundance analysis. Z.Z. led the literature compilation and total metallicity calculations, and contributed to the population III analysis and interpretation. S.M.-T. and Z.Z. contributed to the BOSS target selection. P.E. computed the 3D models and led the 3D LTE carbon analysis. K.C.S. led the distance determinations and contributed to stellar parameters, writing and interpretation. H.D.A., H.D., N.M.O., R.T. and P.N.T. contributed to the MIKE observations and the stellar parameter, chemical abundance, kinematic analysis and interpretation. K.G.S. contributed to the stellar parameter analysis, writing and interpretation. M.H. led the asteroseismology analysis. J.T. contributed to the carbon evolutionary corrections. M.B. contributed to the 3D and NLTE analyses. A.R.C. and J.A.J. contributed to the stellar parameter analysis. All authors contributed to the paper, interpretation, SDSS-V infrastructure and/or the SDSS-V high-resolution follow-up programme.

Corresponding author

Correspondence to Alexander P. Ji.

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Extended data

Extended Data Fig. 1 Profile likelihood for CH upper limit.

Left: the two spectral orders being fit with a 7th degree polynomial, the data is fit well. A red model is plotted indicating the 3σ upper limit, masked regions shown in grey. Center top: Stitched and normalized spectrum (black line, with 3σ pixel uncertainties shown as dashed black lines) compared to the best-fit (effectively no-carbon) spectrum (blue line) and the 3σ upper limit (red line). The data and blue lines are normalized to 1, while the red 3σ model is normalized to the dashed red 3σ continuum line. The dashed red line is not exactly at 1, because the continuum is redetermined at every value of A(C), resulting in a more conservative upper limit when compared to a fixed continuum by about 0.2 dex. We apply an extra +0.2 dex correction to the final results, as the 3D model’s stellar parameters are not identical to our adopted parameters (see text). Center bottom: error-normalized residual for the best fit model (blue) and the 3σ upper limit (red). The per-pixel value is shown as a thin line, while the thick line is smoothed over 2 pixels. The red line is above the blue line where the CH features are. Note this is an approximation for visualization: the calculation is done on each order independently, not on the stitched spectrum. Right: χ2 as a function of A(C). The blue point marks our minimum χ2 value. The 3σ upper limit, corresponding to 99.9% confidence or Δχ2 = 10.273 for 1 degree of freedom, is marked as a red point.

Extended Data Fig. 2 Profile Likelihood for NH upper limit.

Top Left: the full spectral order containing the NH band. The black line is smoothed by a Gaussian with 5 pixel FWHM, and the blue box indicates a wavelength region where there is a clear deviation from the echelle order shape. Bottom Left: the exact range being fit. The continuum (dashed lines) is modeled as a 2nd degree polynomial, which fits the data well. A blue model is plotted indicating the best fit, and a red model is plotted indicating the 3σ upper limit. Center top: Normalized spectrum (black line, with 1σ pixel uncertainties shown as black dashed lines) compared to the best-fit model (blue line) and the 3σ upper limit (red line). The data and blue lines are normalized to 1, while the red 3σ model is normalized to the dashed red 3σ continuum line. Center bottom: Smoothed visualization of the data. The best-fit model and 1σ uncertainties are shown in solid blue line/shaded region, while the model with no nitrogen is shown as a dotted blue line. Right: χ2 as a function of A(N). The blue point marks the best-fit nitrogen value, A(N) = 4.10+0.18-0.25. The 3σ upper limit is A(N) <4.56 and marked as a red point.

Extended Data Fig. 3 Energy and angular momentum in a static potential.

Top: Specific energy and angular momentum. J0715-7334 is shown as a large red star. Black points show a literature sample (see Literature Data Sample section in text). Large blue circles indicate the LMC and SMC. Colored points highlight eight notable metal-poor stars with 68% confidence uncertainties. The same stars are shown in the Main Text in Fig. 2. The shaded grey background is metal-poor stars from the SDSS-V halo program, computed in a static Milky Way gravitational potential (see Methods). J0715-7334 joins LMC-11926 as originating from the LMC. Bottom: Galactocentric specific angular momentum in the Lz-Lx plane, in which stars associated with the Magellanic Clouds have a distinctive signature52. All halo stars from SDSS-V are shown, along with known ultra-metal-poor stars from the literature with 68% confidence uncertainties. Magellanic Stellar Stream members proposed by Chandra et al.52 are shown, along with the selection box used to identify Magellanic Debris. J0715-7334 has kinematics that strongly associate it with the Clouds.

Extended Data Fig. 4 Distance to LMC over time for different orbit integration samples.

The thick red line shows the median orbit. The same orbit is shown in the Main Text in Fig. 3. The other lines are color-coded by the future fate of J0715-7334: orange lines show orbits that will be unbound to the Milky Way, while blue lines show orbits that will remain bound to the Milky Way.

Extended Data Fig. 5 1D LTE abundances of SDSS J0715-7334 for different elements, compared to literature stars.

Grey boxplots indicate the minimum, maximum, median, and 25-75 percentile [X/H] range for the literature stars in 1D LTE, where carbon has evolutionary corrections. Colored points highlight the 1D LTE analyses of SMSS J0313-670810 and J1029+17297. A horizontal red line is drawn at the [Fe/H] value for J0715-7334.

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Ji, A.P., Chandra, V., Mejias-Torres, S. et al. A nearly pristine star from the Large Magellanic Cloud. Nat Astron (2026). https://doi.org/10.1038/s41550-026-02816-7

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