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Identification and properties of intense star-forming galaxies at redshifts z > 10

Nature Astronomy volume 7, pages 611–621 (2023)Cite this article

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Abstract

Surveys with the James Webb Space Telescope (JWST) have discovered candidate galaxies in the first 400 Myr of cosmic time. Preliminary indications have suggested these candidate galaxies may be more massive and abundant than previously thought. However, without confirmed distances, their inferred properties remain uncertain. Here we identify four galaxies located in the JWST Advanced Deep Extragalactic Survey Near-Infrared Camera imaging with photometric redshifts z of roughly 10–13. These galaxies include the first redshift z > 12 systems discovered with distances spectroscopically confirmed by JWST in a companion paper. Using stellar population modelling, we find the galaxies typically contain 100 million solar masses in stars, in stellar populations that are less than 100 million years old. The moderate star-formation rates and compact sizes suggest elevated star-formation rate surface densities, a key indicator of their formation pathways. Taken together, these measurements show that the first galaxies contributing to cosmic reionization formed rapidly and with intense internal radiation fields.

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Fig. 1: Distant galaxies selected and confirmed by the JWST JADES program.
Fig. 2: Precision photometry and spectral energy distribution (SED) modelling of JADES-GS-z12-0.
Fig. 3: Physical properties inferred from NIRCam imaging of distant, confirmed galaxies.

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Data availability

The data that support the findings of this study83 are available from a public online repository.

Code availability

The astropy58 and photutils84 software suites are publicly available. The Prospector code42 is publicly available, as is the forcepho photometric forward-modelling code.

References

  1. Robertson, B. Galaxy formation and reionization: key unknowns and expected breakthroughs with James Webb Space Telescope. Annu. Rev. Astron. Astrophys. 60, 121 (2022).

    Article  ADS  Google Scholar 

  2. Carnall, A. C. et al. A first look at the SMACS0723 JWST ERO: spectroscopic redshifts, stellar masses and star-formation histories. Mon. Not. Royal Astron. Soc.: Lett. 518, L45–L50 (2023).

    Article  ADS  Google Scholar 

  3. Brinchmann, J. J. High-z galaxies with JWST and local analogues—it is not only star formation. Preprint at https://arXiv.org/abs/2208.07467 (2022).

  4. Tacchella, S. et al. JWST NIRCam+NIRSpec: interstellar medium and stellar populations of young galaxies with rising star formation and evolving gas reservoirs. Preprint at https://arXiv.org/abs/2208.03281 (2022).

  5. Curti, M. et al. The chemical enrichment in the early Universe as probed by JWST via direct metallicity measurements at z ~ 8. Mon. Not. Royal Astron. Soc. 518, 425–438 (2022).

  6. Trussler, J. A. A. et al. Seeing sharper and deeper: JWST’s first glimpse of the photometric and spectroscopic properties of galaxies in the epoch of reionisation. Mon. Not. Royal Astron. Soc. https://doi.org/10.48550/arXiv.2207.14265 (2022).

  7. Morishita, T. & Stiavelli, M. Physical characterization of Early Galaxies in the Webb’s First Deep Field SMACS J0723.3-7323. Astrophys. J. https://arxiv.org/abs/2207.11671 (2022).

  8. Schaerer, D. et al. First look with JWST spectroscopy: z ~ 8 galaxies resemble local analogues. Astron. Astrophys. Lett. 665, L4 (2022).

    Article  ADS  Google Scholar 

  9. Endsley, R. et al. A JWST/NIRCam study of key contributors to reionization: star-forming and ionizing properties of UV-faint z ~ 7–8 galaxies. Preprint at https://arXiv.org/abs/2208.14999 (2022).

  10. Whitler, L. et al. On the ages of bright galaxies ~500 Myr after the Big Bang: insights into star formation activity at z > ~15 with JWST. Mon. Not. Royal Astron. Soc. 519, 157–171 (2022).

  11. Topping, M. et al. Searching for extremely blue UV continuum slopes at z = 7–11 in JWST/NIRCam imaging: implications for stellar metallicity and ionizing photon escape in early galaxies. Astrophys. J. 941, 153 (2022).

  12. Arellano-Cordova, K. Z. A first look at the abundance pattern—O/H, C/O, and Ne/O—in z > 7 galaxies with JWST/NIRSpec. Astrophys. J. 940, L3 (2022).

  13. Inayoshi, K. et al. A lower bound of star formation activity in ultra-high-redshift galaxies detected with JWST: implications for stellar populations and radiation sources. Astrophys. J. Lett. 938, 10 (2022).

    Article  ADS  Google Scholar 

  14. Ono, Y. et al. Morphologies of galaxies at z ≃ 9–17 uncovered by JWST/NIRCam imaging: cosmic size evolution and an identification of an extremely compact bright galaxy at z ~ 12. Preprint at https://arXiv.org/abs/2208.13582 (2022).

  15. Rodighiero, G. et al. JWST unveils heavily obscured (active and passive) sources up to z ~ 13. Mon. Not. Royal. Astron. Soc. Lett. 518, L19–L24 (2023).

  16. Harikane, Y. et al. A comprehensive study on galaxies at z ~ 9–17 found in the early JWST data: UV luminosity functions and cosmic star-formation history at the pre-reionization epoch. Astrophys. J. Suppl. Ser. 265, 5 (2023).

  17. Santini, P. et al. Early results from GLASS-JWST. XI: stellar masses and mass-to-light ratio of z > 7 galaxies. Astrophys. J. Lett. 942, L27 (2023).

  18. Leethochawalit, N. et al. Early results from GLASS-JWST. X: rest-frame UV-optical properties of galaxies at 7 < z < 9. Astrophys. J. Lett. 942, L26 (2023).

  19. Roberts-Borsani, G. et al. A shot in the Dark (Ages): a faint galaxy at z = 9.76 confirmed with JWST. Preprint at https://arXiv.org/abs/2210.15639 (2022).

  20. Pontoppidan, K. M. et al. The JWST early release observations. Astrophys. J. Lett. 936, 14 (2022).

    Article  ADS  Google Scholar 

  21. Finkelstein, S. et al. CEERS Key Paper I: an early look into the first 500 Myr of galaxy formation with JWST. Preprint at https://arXiv.org/abs/2211.05792 (2022).

  22. Treu, T. et al. The GLASS-JWST early release science program. I. Survey design and release plans. Astrophys. J. 935, 110 (2022).

    Article  ADS  Google Scholar 

  23. Castellano, M. et al. Early results from GLASS-JWST. III. Galaxy candidates at z ~ 9–15. Astrophys. J. Lett. 938, L15 (2022).

    Article  ADS  Google Scholar 

  24. Adams, N. J. et al. Discovery and properties of ultra-high redshift galaxies (9 < z < 12) in the JWST ERO SMACS 0723 field. Mon. Not. Royal Astron. Soc. 518, 4755 (2023).

  25. Finkelstein, S. L. et al. A long time ago in a galaxy far, far away: a candidate z ~ 12 galaxy in early JWST CEERS imaging. Astrophys. J. Lett. 940, L55 (2022).

  26. Naidu, R. P. et al. Two remarkably luminous galaxy candidates at z ≈ 10–12 revealed by JWST. Astrophys. J. Lett. 940, L14 (2022).

  27. Donnan, C. T. et al. The evolution of the galaxy UV luminosity function at redshifts z ~ 8–15 from deep JWST and ground-based near-infrared imaging. Mon. Not. Royal Astron. Soc. 518, 6011 (2023).

  28. Atek, H., et al. Revealing galaxy candidates out to z ~ 16 with JWST observations of the lensing cluster SMACS0723. Mon. Not. Royal Astron. Soc. 519, 1201 (2023).

  29. Labbe, I. et al. A population of red candidate massive galaxies ~600 Myr after the Big Bang, Nature (2023): https://doi.org/10.1038/s41586-023-05786-2

  30. Boylan-Kolchin, M. Stress testing ΛCDM with high-redshift galaxy candidates. Preprint at https://arXiv.org/abs/2208.01611 (2022).

  31. Lovell, C. C., et al. Extreme value statistics of the halo and stellar mass distributions at high redshift: are JWST results in tension with ΛCDM? Mon. Not. Royal Soc. 518, 2511 (2023).

  32. Ferrara, A., Pallotini, A. & Dayal, P. On the stunning abundance of super-early, massive galaxies revealed by JWST. Preprint at https://arXiv.org/abs/2208.00720 (2022).

  33. Williams, H., et al. Spectroscopy from Lyman alpha to [O III] 5007 of a triply imaged magnified galaxy at redshift z = 9.5. Preprint at https://arXiv.org/abs/2210.15699 (2022).

  34. Rieke, M. J., Kelly, D. & Horner, S. Overview of James Webb Space Telescope and NIRCam’s role. Proc. PIE 5904, 590401 (2005).

  35. Jakobsen, P. et al. The near-iInfrared spectrograph (NIRSpec) on the James Webb Space Telescope. I. Overview of the instrument and its capabilities. Astron. Astrophys. 661, 80 (2022).

    Article  Google Scholar 

  36. Illingworth, G., et al. The Hubble Legacy Fields (HLF-GOODS-S) v1.5 data products: combining 2442 orbits of GOODS-S/CDF-S region ACS and WFC3/IR images. Preprint at https://arXiv.org/abs/1606.00841 (2016).

  37. Curtis-Lake, E., et al., Spectroscopic confirmation of four metal-poor galaxies at z=10.3-13.2. Preprint at https://arXiv.org/abs/2212.04568

  38. Bouwens, R. J. et al. A candidate redshift z ~ 10 galaxy and rapid changes in that population at an age of 500 Myr. Nature 469, 504 (2011).

    Article  ADS  Google Scholar 

  39. Ellis, R. S. et al. The abundance of star-forming galaxies in the redshift range 8.5-12: new results from the 2012 Hubble Ultra Deep Field. Astrophys. J. Lett. 763, L7 (2013).

    Article  ADS  Google Scholar 

  40. Bouwens, R. J. et al. Evolution of the UV LF from z ~ 15 to z ~ 8 using new JWST NIRCam medium-band observations over the HUDF/XDF. Preprint at https://arXiv.org/abs/2211.02607 (2022).

  41. Sérsic, J. L. Atlas de Galaxias Australes (Observatorio Astronomico, 1968).

  42. Johnson, B. et al. Stellar population inference with Prospector. Astrophys. J. Supp. Ser. 254, 22 (2021).

    Article  ADS  Google Scholar 

  43. Wilkins, S. M., et al. First light and reionisation epoch simulations (FLARES) VII: the star formation and metal enrichment histories of galaxies in the early Universe. Mon. Not. Royal Astron. Soc. 518, 3935 (2023).

  44. Tacchella, S. et al. A redshift-independent efficiency model: star formation and stellar masses in dark matter halos at z>4. Astrophys. J. 868, 92 (2018).

    Article  ADS  Google Scholar 

  45. Harris, J. & Zaritsky, D. The star formation history of the small magellanic cloud. Astron. J. 127, 1531 (2004).

    Article  ADS  Google Scholar 

  46. Weinberg, D. H., Andrews, B. H. & Freudenburg, J. Equilibrium and sudden events in chemical evolution. Astrophys. J. 837, 183 (2017).

    Article  ADS  Google Scholar 

  47. Genzel, R. et al. A study of the gas-star formation relation over cosmic time. Mon. Not. R. Soc. 407, 2091 (2010).

    Article  ADS  Google Scholar 

  48. Izotov, Y. I. et al. Low-redshift Lyman continuum leaking galaxies with high [O III]/[O II] ratios. Mon. Not. R. Soc. 478, 4851 (2018).

    Article  ADS  Google Scholar 

  49. Shapley, A. E. et al. Q1549-C25: clean source of Lyman-continuum emission at z = 3.15. Astrophys. J. Lett. 826, 24 (2016).

    Article  ADS  Google Scholar 

  50. Sharma, M. et al. The brighter galaxies reionized the Universe. Mon. Not. R. Soc. L. 458, 94 (2016).

    Article  ADS  Google Scholar 

  51. Giavalisco, M. et al. The great observatories origins deep survey: initial results from optical and near-infrared imaging. Astrophys. J. 600, L93–L98 (2004).

    Article  ADS  Google Scholar 

  52. Williams, C. C., et al. JEMS: A deep medium-band imaging survey in the Hubble Ultra-Deep Field with JWST NIRCam & NIRISS. Preprint at https://arXiv.org/abs/2301.09780 (2023).

  53. Boyer, M. L. et al. The JWST resolved stellar populations early releases science program. I. NIRCam flux calibration. Res. Not. Am. Astron. Soc. 6, 191 (2022).

    ADS  Google Scholar 

  54. Rigby, J. et al. Characterization of JWST science performance from commissioning. Preprint at https://arXiv.org/abs/2207.05632 (2022).

  55. Schlawin, E. et al. JWST noise floor. I. Random error sources in JWST NIRCam time series. Astron. J. 160, 231 (2020).

    Article  ADS  Google Scholar 

  56. Gaia Collaboration. Gaia Early Data Release 3. Summary of the contents and survey properties. Astron. Astrophys. 649, 1 (2021).

    Article  Google Scholar 

  57. Fruchter, A. S. & Hook, R. N. Drizzle: a method for the linear reconstruction of undersampled images. Pub. Astron. Soc. Pacif. 114, 144–152 (2002).

    Article  ADS  Google Scholar 

  58. Astropy Collaboration. The Astropy Project: sustaining and growing a community-oriented open-source project and the latest major release (v5.0) of the core package. Astrophys. J. 935, 167 (2022).

    Article  ADS  Google Scholar 

  59. Bertin, E. & Arnouts, S. SExtractor: software for source extraction. Astron. Astrophys. Supp. 117, 393–404 (1996).

    Article  ADS  Google Scholar 

  60. Kron, R. G. Photometry of a complete sample of faint galaxies. Astrophys. J. Supp. Ser. 43, 305–325 (1980).

    Article  ADS  Google Scholar 

  61. Krist, J. E., Hook, R. N. & Stoehr, F. 20 years of Hubble Space Telescope optical modeling using Tiny Tim. Proc. SPIE. 81270J (2011).

  62. Perrin, M. D. et al. Updated point spread function simulations for JWST with WebbPSF. Proc. SPIE. 9143, 91433X (2014).

  63. Hainline, K. N. et al. Simulating JWST/NIRCam color selection of high-redshift galaxies. Astrophys. J. 892, 125 (2020).

    Article  ADS  Google Scholar 

  64. Brammer, G. B., van Dokkum, P. G. & Coppi, P. EAZY: a fast, public photometric redshift code. Astrophys. J. 686, 1503–1513 (2008).

    Article  ADS  Google Scholar 

  65. Chevallard, J. & Charlot, S. Modelling and interpreting spectral energy distributions of galaxies with BEAGLE. Mon. Not. R. Astron. Soc. 462, 1415–1443 (2016).

    Article  ADS  Google Scholar 

  66. Neal, R. M. in Handbook of Markov Chain Monte Carlo (eds Brooks, S. et al.) 113–162 (Chapman & Hall/CRC, 2011).

  67. Tacchella, S. et al. On the stellar populations of galaxies at z ~ 9−11: the growth of metals and stellar mass at early times. Astrophys. J. 927, 170 (2022).

    Article  ADS  Google Scholar 

  68. Choi, J., Conroy, C. & Byler, N. The evolution and properties of rotating massive star populations. Astrophys. J. 838, 159 (2017).

    Article  ADS  Google Scholar 

  69. Chabrier, G. Galactic stellar and substellar initial mass function. Pub. Astron. Soc. Pac. 115, 763–795 (2003).

    Article  ADS  Google Scholar 

  70. Calzetti, D. et al. The dust content and opacity of actively star-forming galaxies. Astrophys. J. 533, 682–695 (2000).

    Article  ADS  Google Scholar 

  71. Ferland, G. et al. The 2013 release of Cloudy. Rev. Mex. Astron. Astro. 49, 137–163 (2013).

    ADS  Google Scholar 

  72. Byler, N. et al. Nebular continuum and line emission in stellar population synthesis models. Astrophys. J. 840, 44 (2017).

    Article  ADS  Google Scholar 

  73. Leja, J. et al. How to measure galaxy star formation histories. II. Nonparametric models. Astrophys. J. 876, 3 (2019).

    Article  ADS  Google Scholar 

  74. Speagle, J. S. DYNESTY: a dynamic nested sampling package for estimating Bayesian posteriors and evidences. Mon. Not. R. Astron. Soc. 493, 3132–3158 (2020).

    Article  ADS  Google Scholar 

  75. Faucher-Giguère, C.-A. A model for the origin of bursty star formation in galaxies. Mon. Not. R. Astron. Soc. 473, 3717–3731 (2018).

    Article  ADS  Google Scholar 

  76. Tacchella, S., Forbes, J. C. & Caplar, N. Stochastic modelling of star-formation histories II: star-formation variability from molecular clouds and gas inflow. Mon. Not. R. Astron. Soc. 493, 698–725 (2020).

    Article  Google Scholar 

  77. Steidel, C. C. et al. Reconciling the stellar and nebular spectra of high-redshift galaxies. Astrophys. J. 826, 159 (2016).

    Article  ADS  Google Scholar 

  78. Ma, X. et al. No missing photons for reionization: moderate ionizing photon escape fractions from the FIRE-2 simulations. Mon. Not. R. Soc. 498, 2001–2017 (2020).

    Article  ADS  Google Scholar 

  79. Naidu, R. P. et al. Rapid reionization of the oligarchs: the case for massive, UV-bright, star-forming galaxies with high escape fractions. Astrophys. J. 892, 109 (2020).

    Article  ADS  Google Scholar 

  80. Calzetti, D., Kinney, A. L. & Storchi-Bergmann, T. Dust extinction of the stellar continua in starburst galaxies: the ultraviolet and optical extinction law. Astrophys. J. 429, 582–601 (1994).

    Article  ADS  Google Scholar 

  81. Whitler, L. et al. Star formation histories of UV-luminous galaxies at z ~ 6.8: implications for stellar mass assembly at early cosmic times. Mon. Not. R. Astron. Soc. 519, 151–171 (2023).

    Article  ADS  Google Scholar 

  82. Dressler, A. et al. Early results from GLASS-JWST. XVII: building the first galaxies—chapter 1. Star formation histories at 5 < z < 7. Preprint at https://arXiv.org/abs/2208.04292 (2022).

  83. Robertson, B. E., Tacchella, S., Johnson, B. D. & JADES Collaboration. JWST Advanced Deep Extragalactic Survey: thumbnail images of spectroscopically-confirmed galaxies at z > 10 (v.0.5.1). Zenodo https://doi.org/10.5281/zenodo.7460116 (2022).

  84. Bradley, L. et al. astropy/photutils:1.5.0. Zenodo https://doi.org/10.5281/zenodo.6825092 (2022).

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Acknowledgements

B.E.R., B.D.J., D.J.E., M.R., E.E., G.R., C.N.A.W., M.F. and F.S. acknowledge support from the JWST/NIRCam Science Team contract to the University of Arizona, NAS5-02015. L.W. acknowledges support from the National Science Foundation Graduate Research Fellowship under grant no. DGE-2137419. D.J.E. is further supported as a Simons Investigator. S. Albert acknowledges support from the JWST Mid-Infrared Instrument Science Team Lead, grant no. 80NSSC18K0555, from NASA Goddard Space Flight Center to the University of Arizona. R.H. was funded by the Johns Hopkins University, Institute for Data Intensive Engineering and Science. G.R. acknowledges support from grant no. 80NSSC22K1293. S. Arribas acknowledges support from the research project no. PID2021-127718NB-I00 of the Spanish Ministry of Science and Innovation/State Agency of Research (MICIN/AEI). N.B. and P.J. acknowledge support from the Cosmic Dawn Center (DAWN), funded by the Danish National Research Foundation under grant no. 140. A.J.B., A.J.C., J.C., I.E.B.W. and A.S. 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). S.Carniari acknowledges support by European Union’s HE ERC Starting grant no. 101040227 – WINGS. E.C.-L. acknowledges support of an Science and Technology Facilities Council (STFC) Webb Fellowship (grant no. ST/W001438/1). M.C., F.D.E., T.J.L., R.M., J.W. and L.S. acknowledge support by the STFC, ERC Advanced grant no. 695671 ‘QUENCH’. R.M. is further supported by a research professorship from the Royal Society. J.W. is further supported by the Fondation MERAC. R.S. acknowledges support from a STFC Ernest Rutherford Fellowship (grant no. ST/S004831/1). H.Ü. gratefully acknowledges support by the Isaac Newton Trust and by the Kavli Foundation through a Newton-Kavli Junior Fellowship. S.B. acknowledges support from the Natural Sciences and Engineering Research Council of Canada. 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.E.H. acknowledges support from the National Science Foundation Graduate Research Fellowship Program under grant no. DGE-1746060. This research made use of the lux supercomputer at UC Santa Cruz, funded by NSF MRI grant no. AST 1828315 (B.E.R.).

Author information

Author notes

  1. These authors contributed equally: B. E. Robertson, S. Tacchella.

Authors and Affiliations

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

    B. E. Robertson & K. A. Suess

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

    S. Tacchella, M. Curti, F. D’Eugenio, T. J. Looser, R. Maiolino, H. Übler, J. Witstok & L. Sandles

  3. Cavendish Laboratory, University of Cambridge, Cambridge, UK

    S. Tacchella, M. Curti, F. D’Eugenio, T. J. Looser, R. Maiolino, H. Übler, J. Witstok & L. Sandles

  4. Center for Astrophysics, Harvard and Smithsonian, Cambridge, MA, USA

    B. D. Johnson & D. J. Eisenstein

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

    K. Hainline, L. Whitler, M. Rieke, D. P. Stark, S. Alberts, E. Egami, G. Rieke, I. Shivaei, C. N. A. Willmer, Z. Chen, M. Florian, J. M. Helton, R. E. Hviding, Z. Ji, J. Lyu, F. Sun & M. Topping

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

    R. Endsley

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

    A. Dressler

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

    R. Hausen

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

    C. C. Williams

  10. Centre for Astrobiology (CAB), CSIC–INTA, Torrejón de Ardoz, Madrid, Spain

    S. Arribas

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

    N. Bonaventura & P. Jakobsen

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

    N. Bonaventura & P. Jakobsen

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

    A. Bunker, A. J. Cameron, J. Chevallard, A. Saxena & I. E. B. Wallace

  14. Scuola Normale Superiore, Pisa, Italy

    S. Carniani

  15. Institute for Astrophysics of Paris, Sorbonne University, CNRS, UMR7095, Paris, France

    S. Charlot

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

    E. Curtis-Lake

  17. Space Telescope Science Institute, European Space Agency, Baltimore, MD, USA

    N. Lützgendorf & T. Rawle

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

    R. Maiolino & A. Saxena

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

    M. V. Maseda

  20. Max-Planck Institute for Astronomy, Heidelberg, Germany

    H.-W. Rix & A. de Graaff

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

    R. Smit

  22. NRC Herzberg, Victoria, British Columbia, Canada

    C. Willott

  23. Department of Physics and Astronomy, University of Manitoba, Winnipeg, Manitoba, Canada

    S. Baum

  24. European Space Agency, ESA/ESTEC, Noordwijk, the Netherlands

    R. Bhatawdekar

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

    K. Boyett

  26. ARC Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D), Parkville, Victoria, Australia

    K. Boyett

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

    N. Kumari

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

    E. Nelson

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

    K. A. Suess

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  1. B. E. Robertson
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Contributions

B.E.R., S.T. and B.D.J. led the writing of this paper. M.R., C.N.A.W., E.E., F.S., G.R., K.H., C.C.W. P.F., and M.F. contributed to the design, construction and commissioning of NIRCam. B.E.R., S.T., B.D.J., C.N.A.W., D.J.E., I.S., M.R., R.E., S.Alberts and Z.C. contributed to the JADES imaging data reduction. R.H. and B.E.R. contributed to the JADES imaging data visualization. B.D.J., S.T., A.D., D.P.S., L.W., M.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., Z.C. and Z.J. contributed to the JADES imaging morphological analysis. B.E.R., C.N.A.W., C.C.W., K.H. and M.R. contributed to the JADES preflight imaging data challenges. S.Carniani, M.C., J.W. and S.Arribas contributed to the NIRSpec data reduction and to the development of the NIRSpec pipeline. P.J., N.B. and S.Arribas contributed to the design and optimization of the MSA configurations. A.J.C., A.B., E.C.-L., H.U., K.B., R. B., I. W. and C.N.A.W. 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., A.S. and L.S. contributed to analysis of the spectroscopic data, including redshift determination and spectral modelling. P.J., P.F., M.S., T.R., N.L. and N.K. contributed to the design, construction and commissioning of NIRSpec. F.D.E., T.J.L., M.V.M., M.C., R.M. and S.Arribas 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. A.B., A.D., C.N.A.W., C.W., D.J.E., H.-W.R., M.R., P.F., P.J., R.M., S.Albert and S.Arribas contributed to the design of the JADES survey. S.B. commented on a draft of this paper. B.E.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 B. E. Robertson or S. Tacchella.

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Extended data

Extended Data Fig. 1 Inferred spatial profiles.

The marginalized and joint posterior distribution for the Sérsic index and half-light radius from forcepho fitting to the individual exposures of each galaxy (a-d). We only infer an upper limit on the sizes of JADES-GS-z10-0 (d) and JADES-GS-z13-0 (a).

Extended Data Fig. 2 Spectral energy distribution (SED) modelling of all four z>10 galaxies (panels a-d).

The observational data used in the SED fitting is shown in the top panels. The mean and 1σ s.d. uncertainties of the flux in detected filters are plotted as blue circles, while the 5σ s.d. upper limits are indicated as bars with an arrow pointing down. Horizontal error bars indicate the approximate wavelength range of each filter. The red line with the shaded region around it shows the best-fitting SED with 1σ s.d. marginalized credibility interval, fit to N=8, 6, 12, and 9 detections in panels a), b), c), and d), respectively. The orange boxes mark the posterior fluxes in the different filters. The bottom panels show the χ values for each filter and the total χ2 value is given.

Extended Data Fig. 3 Inferred posterior distributions for galaxy JADES-GS-z13-0 (zspec=13.20).

This corner figure (panel a) shows the posterior distribution of some of the key quantities that we infer from our SED modelling, including the stellar mass, specific SFR, stellar age (half-mass time), dust attenuation in the rest-frame V-band, the ratio of the attenuation in the rest-frame UV to the V-band (probing the slope of the attenuation law), escape fraction and stellar metallicity. The priors are indicated on the marginalized distributions as solid black lines. The inset on the top right (panel b) shows the posterior of the star-formation history (SFH). This galaxy is consistent with an increasing SFH and a young age, though older stellar populations of up to a 100 Myr cannot be ruled out. The SED of this galaxy is consistent with both a lower stellar metallicity solution (together with a low escape fraction and a steeper attenuation law) and higher metallicity solution (together with a higher escape fraction and a shallower attenuation law).

Extended Data Fig. 4 Inferred posterior distributions for galaxy JADES-GS-z12-0 (zspec=12.63).

The figure follows the same layout as Extended Data Fig. 3. The SFH of this galaxy is consistent with being constant. Although young ages are preferred, there is a significant tail to older ages, leading to a median of the posterior age distribution of 50 Myr.

Extended Data Fig. 5 Inferred posterior distributions for galaxy JADES-GS-z11-0 (zspec=11.58).

The figure follows the same layout as Extended Data Fig. 3. The SED of this galaxy implies a significant older component with a decreasing SFH, leading to an age consistent with as high as 100 Myr.

Extended Data Fig. 6 Inferred posterior distributions for galaxy JADES-GS-z10-0 (zspec=10.38).

The figure follows the same layout as Extended Data Fig. 3. The galaxy, similar to JADES-GS-z13-0, shows a bimodal distribution in the escape fraction.

Extended Data Table 1 forcepho and Aperture Photometry
Full size table

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Robertson, B.E., Tacchella, S., Johnson, B.D. et al. Identification and properties of intense star-forming galaxies at redshifts z > 10. Nat Astron 7, 611–621 (2023). https://doi.org/10.1038/s41550-023-01921-1

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