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Spectroscopic confirmation of four metal-poor galaxies at z = 10.3–13.2

Nature Astronomy volume 7, pages 622–632 (2023)Cite this article

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Abstract

Finding and characterizing the first galaxies that illuminated the early universe at cosmic dawn is pivotal to understand the physical conditions and the processes that led to the formation of the first stars. In the first few months of operations, imaging from the James Webb Space Telescope (JWST) has been used to identify tens of candidates of galaxies at redshift (z) greater than 10, less than 450 million years after the Big Bang. However, none of such candidates has yet been confirmed spectroscopically, leaving open the possibility that they are actually low-redshift interlopers. Here we present spectroscopic confirmation and analysis of four galaxies unambiguously detected at redshift 10.3 ≤ z ≤ 13.2, previously selected from JWST Near Infrared Camera imaging. The spectra reveal that these primeval galaxies are metal poor, have masses on the order of about 107–108 solar masses and young ages. The damping wings that shape the continuum close to the Lyman edge provide constraints on the neutral hydrogen fraction of the intergalactic medium from normal star-forming galaxies. These findings demonstrate the rapid emergence of the first generations of galaxies at cosmic dawn.

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Fig. 1: Spectra of the four z > 10 galaxies targeted for the first deep spectroscopic pointing of the JADES survey.
Fig. 2: UV slope versus magnitude for the four z > 10 galaxies.
Fig. 3: Spectral break fit region and the derived constraints on neutral hydrogen in the IGM for JADES-GS-z11-0.

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Data availability

The data that support the findings of this study are available from the corresponding authors upon reasonable request.

Code availability

BEAGLE is available via a Docker image (distributed through docker hub) upon request at https:/iap.fr/beagle.

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Acknowledgements

For the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising from this submission. E.C.-L. acknowledges support of an STFC Webb Fellowship (ST/W001438/1). S. Carniani acknowledges support by European Union’s HE ERC Starting Grant No. 101040227 - WINGS. M.C., F.D.E., T.J.L., R.M., J.W. and L.S. acknowledge support by the Science and Technology Facilities Council (STFC), ERC Advanced Grant 695671 ‘QUENCH’. R.M. is further supported by a research professorship from the Royal Society. J.W. is further supported by the Fondation MERAC. H.Ü. gratefully acknowledges support by the Isaac Newton Trust and by the Kavli Foundation through a Newton-Kavli Junior Fellowship. N.B. and P.J. acknowledge support from the Cosmic Dawn Center (DAWN), funded by the Danish National Research Foundation under grant no.140. R.S. acknowledges support from a STFC Ernest Rutherford Fellowship (ST/S004831/1). A.B., A.C., J.C., I.E.B.W., A.S. and G.C.J. acknowledge funding from the ‘FirstGalaxies’ Advanced Grant from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 789056). B.R., B.D.J., D.J.E., M.R., E.E., C.N.A.W. and F.S. acknowledge support from the JWST/NIRCam Science Team contract to the University of Arizona, NAS5-02015. D.J.E. is further supported as a Simons Investigator. R. Bowler acknowledges support from an STFC Ernest Rutherford Fellowship (grant number ST/T003596/1). R.E.H. acknowledges support from the National Science Foundation Graduate Research Fellowship Program under Grant No. DGE-1746060. S.A., B.R.d.P. and M.P. acknowledge support from the research project PID2021-127718NB-I00 of the Spanish Ministry of Science and Innovation/State Agency of Research (MICIN/AEI). M.P. is further supported by the Programa Atracción de Talento de la Comunidad de Madrid via grant 2018-T2/TIC-11715. L.W. acknowledges support from the National Science Foundation Graduate Research Fellowship under Grant No. DGE-2137419. K.B. is supported in part by the Australian Research Council Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D), through project number CE170100013. R.H. was funded by the Johns Hopkins University, Institute for Data Intensive Engineering and Science (IDIES). This research made use of the lux supercomputer at UC Santa Cruz, funded by NSF MRI grant AST 1828315. Acknowledgement for getting assigned a protected node for the DEEP BagPipes runs: “This study made use of the Prospero high performance computing facility at Liverpool John Moores University.”

Author information

Author notes

  1. These authors contributed equally: Emma Curtis-Lake, Stefano Carniani.

Authors and Affiliations

  1. Centre for Astrophysics Research, Department of Physics, Astronomy and Mathematics, University of Hertfordshire, Hatfield, UK

    Emma Curtis-Lake

  2. Scuola Normale Superiore, Pisa, Italy

    Stefano Carniani

  3. Department of Physics, University of Oxford, Oxford, UK

    Alex Cameron, Andrew Bunker, Jacopo Chevallard, Gareth C. Jones, Aayush Saxena & Imaan E. B. Wallace

  4. Sorbonne Université, CNRS, UMR 7095, Institut d’Astrophysique de Paris, Paris, France

    Stephane Charlot

  5. Cosmic Dawn Center (DAWN), Copenhagen, Denmark

    Peter Jakobsen & Nina Bonaventura

  6. Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark

    Peter Jakobsen & Nina Bonaventura

  7. Kavli Institute for Cosmology, University of Cambridge, Cambridge, UK

    Roberto Maiolino, Joris Witstok, Mirko Curti, Francesco D’Eugenio, Tobias J. Looser, Hannah Übler, Sandro Tacchella & Lester Sandles

  8. Cavendish Laboratory - Astrophysics Group, University of Cambridge, Cambridge, UK

    Roberto Maiolino, Joris Witstok, Mirko Curti, Francesco D’Eugenio, Tobias J. Looser, Hannah Übler, Sandro Tacchella & Lester Sandles

  9. Department of Physics and Astronomy, University College London, London, UK

    Roberto Maiolino & Aayush Saxena

  10. Astrophysics Research Institute, Liverpool John Moores University, Liverpool, UK

    Renske Smit

  11. NRC Herzberg, Victoria, British Columbia, Canada

    Chris Willott

  12. European Space Agency, European Space Astronomy Centre, Madrid, Spain

    Pierre Ferruit

  13. Centro de Astrobiología (CAB), CSIC–INTA, Madrid, Spain

    Santiago Arribas, Bruno Rodríguez del Pino & Michele Perna

  14. Leiden Observatory, Leiden University, Leiden, The Netherlands

    Marijn Franx

  15. ATG Europe for the European Space Agency, ESTEC, Noordwijk, The Netherlands

    Giovanna Giardino

  16. European Space Agency (ESA), ESA Office, STScI, Baltimore, MD, USA

    Nora Lützgendorf, Tim Rawle & Marco Sirianni

  17. Department of Astronomy, University of Wisconsin-Madison, Madison, WI, USA

    Michael V. Maseda

  18. Max-Planck-Institut für Astronomie, Heidelberg, Germany

    Hans-Walter Rix & Anna de Graaff

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

    Alan Dressler

  20. Steward Observatory University of Arizona, Tucson, AZ, USA

    Eiichi Egami, Kevin Hainline, Marcia Rieke, Irene Shivaei, Daniel P. Stark, Christopher N. A. Willmer, Zuyi Chen, Jakob M. Helton, Raphael E. Hviding, Jianwei Lyu, Fengwu Sun, Michael W. Topping & Lily Whitler

  21. Center for Astrophysics, Harvard & Smithsonian, Cambridge, MA, USA

    Daniel J. Eisenstein & Benjamin D. Johnson

  22. Department of Astronomy, University of Texas, Austin, TX, USA

    Ryan Endsley

  23. Department of Physics and Astronomy, The Johns Hopkins University, Baltimore, MD, USA

    Ryan Hausen

  24. Department of Astronomy and Astrophysics University of California, Santa Cruz, CA, USA

    Brant Robertson & Katherine A. Suess

  25. NSF’s National Optical-Infrared Astronomy Research Laboratory, Tucson, AZ, USA

    Christina C. Williams

  26. European Space Agency, ESA/ESTEC, Noordwijk, NL, The Netherlands

    Rachana Bhatawdekar

  27. Jodrell Bank Centre for Astrophysics, Department of Physics and Astronomy, School of Natural Sciences, The University of Manchester, Manchester, UK

    Rebecca Bowler

  28. School of Physics, University of Melbourne, Parkville, Victoria, Australia

    Kristan Boyett

  29. ARC Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D), Canberra, Australian Capital Territory, Australia

    Kristan Boyett

  30. AURA for European Space Agency, Space Telescope Science Institute, Baltimore, MD, USA

    Nimisha Kumari

  31. Department for Astrophysical and Planetary Science, University of Colorado, Boulder, CO, USA

    Erica Nelson

  32. Kavli Institute for Particle Astrophysics and Cosmology and Department of Physics, Stanford University, Stanford, CA, USA

    Katherine A. Suess

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  1. Emma Curtis-Lake
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Contributions

E.C.-L. and S. Carniani led the writing of this paper. M.R., C.N.A.W., E.E., F.S., K.H. and C.C.W. contributed to the design, construction and commissioning of NIRCam. A.B., A.D., C.N.A.W., C.W., D.J.E., H.-W.R., M.R., M.F., P.F., P.J., R.M. and S.A. contributed to the design of the JADES survey. B.R., S.T., B.D.J., C.N.A.W., D.J.E., I.S., M.R., R.E. and Z.C. contributed to the JADES imaging data reduction. R.H. and B.R. contributed to the JADES imaging data visualization. B.D.J., S.T., A.D., D.P.S., L.W., M.W.T. and R.E. contributed the modelling of galaxy photometry. K.H., J.M.H., J.L., L.W., R.E. and R.E.H. contributed the photometric redshift determination and target selection. B.D.J., E.N., K.A.S. and Z.C. contributed to the JADES imaging morphological analysis. B.R., C.N.A.W., C.C.W., K.H. and M.R. contributed to the JADES pre-flight imaging data challenges. S. Carniani, M.C., J.W., P.F., G.G., S.A. and B.R.d.P. contributed to the NIRSpec data reduction and to the development of the NIRSpec pipeline. P.J., N.B. and S.A. contributed to the design and optimization of the MSA configurations. A.C., A.B., C.N.A.W., E.C.-L., H.Ü, R. Bowler and K.B. contributed to the selection, prioritization and visual inspection of the targets. S. Charlot, J.C., E.C.-L., R.M., J.W., R.S., F.D.E., M.V.M., M.C., A.d.G., G.C.J., A.S., I.E.B.W. and L.S. contributed to analysis of the spectroscopic data, including redshift determination and spectral modelling. P.J., P.F., M.S., T.R., G.G., N.L., N.K., M.P., R. Bhatawdekar and B.R.d.P. contributed to the design, construction and commissioning of NIRSpec. F.D.E., T.J.L., M.V.M., M.C., B.R.d.P., R.M., S.A. contributed to the development of the tools for the spectroscopic data analysis, visualization and fitting. C.W. contributed to the design of the spectroscopic observations and MSA configurations. B.R., C.W., D.J.E., D.P.S., M.R., N.L. and R.M. serve as the JADES Steering Committee.

Corresponding authors

Correspondence to Emma Curtis-Lake or Stefano Carniani.

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Extended data

Extended Data Fig. 1 Model Balmer break strength.

Balmer break amplitude plotted against age for single stellar populations with metallicities 0.01Z⊙, 0.1Z⊙, 0.2Z⊙, and Z⊙ (as indicated), according to the models described in Section 3. The break is defined as the ratio of the flux fλ integrated over the rest-frame 3751–4198Å wavelength range to that in the rest-frame 3145–3563 Å wavelength range. The peak at early ages for all metallicities arises from the onset or red supergiant stars, and that around 6 × 108 yr from bright asymptotic-giant-branch stars.

Extended Data Fig. 2 BEAGLE fits to GS-z10-0, GS-z11-0 and GS-z12-0.

The results of full spectral fitting to JADES-GS-z10-0 (top left), JADES-GS-z11-0 (top right) and JADES-GS-z12-0 (bottom) with BEAGLE. We fit models to spectra extracted over the full shutter aperture to minimise the wavelength-dependent losses due to varying point spread function (PSF). The triangle plot shows the 2D (off-diagonal) and 1D (along the main diagonal) posterior probability distributions on stellar mass (M), metallicity (Z), maximum age of stars (t) and the effective dust attenuation optical depth in the V-band (τˆv) which are all derived from the beagle fits. We also include the model constraints on the star formation rate (Ψ), UV slope (β) and ionizing photon emissivity (ξion), which are derived parameters of the model. The dark, medium and light blue contours show the extents of the 1, 2 and 3σ credible regions of the posterior probability, respectively. The inset panel shows the observed spectrum and 1σ standard errors per pixel in red and light red respectively, and the median and 1σ range in fitted model spectra in blue. We fit with a constant star formation history (more details in the text and Methods section 3).

Extended Data Fig. 3 BEAGLE fit to GS-z13-0.

As for Extended Data Fig. 2, but for BEAGLE fits to JADES-GS-z13-0. The bottom right panel shows the observed photometry and associated as blue diamonds and associated 1σ s.d. error bars while the coral shaded regions show the model photometry in the same bands. Since this galaxy is very close to the edge of the shutter, we use an extraction over 3 pixels to maximize the S/N. Then to account for wavelength-dependent slit losses we simultaneously fit the spectrum and NIRCam photometry.

Extended Data Fig. 4 Alternative balmer break fits to the spectra.

The fitted spectra if we force the observed spectral break to be interpreted as a Balmer break rather than a Lyman break. We see that the fits fail to reproduce the blue slopes red-ward of the spectral break, and in the cases of JADES-GS-z10-0 and JADES-GS-z11-0, flux in the fitted models blue-ward of the break is notably higher than the observed flux. Combined with the limits placed in Methods section 2 (and presented in Table 1), these fits show that the observed spectra are inconsistent with being Balmer breaks. The panels show the observed spectrum and 1σ standard error per pixel in red and light red respectively, and the median and 1σ range in fitted model spectra in blue.

Extended Data Fig. 5 Alternative redshift solution to GS-z13-0.

The left panel shows the measured NIRCam photometry and associated 1σ s.d. error bars for JADES-GS-z13-0 as blue diamonds and lines, respectively. The coral violin shaded regions show the underlying model values. The black line shows the maximum a posteriori probability solution with strong emission lines due to active-galactic-nuclei narrow-line emission. The right panel shows a zoom of the intermediate redshift solution fitted to the photometry.

Extended Data Fig. 6 Higher-redshift damping-wing fit to GS-z13-0.

As for Fig. 3 but showing a fit to the damping wing using a different definition of ‘best fit’ to fix the physical parameters of the galaxy spectrum which pushes the constraints to a higher-redshift solution.

Extended Data Table 1 Emission-line limiting fluxes
Full size table
Extended Data Table. 2 BEAGLE parameters
Full size table
Extended Data Table 3 Exploring different parameter constraints with BEAGLE
Full size table

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Curtis-Lake, E., Carniani, S., Cameron, A. et al. Spectroscopic confirmation of four metal-poor galaxies at z = 10.3–13.2. Nat Astron 7, 622–632 (2023). https://doi.org/10.1038/s41550-023-01918-w

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