Abstract
Brown dwarfs serve as ideal laboratories for studying the atmospheres of giant exoplanets on wide orbits, as the governing physical and chemical processes within them are nearly identical1,2. Understanding the formation of gas-giant planets is challenging, often involving the endeavour to link atmospheric abundance ratios, such as the carbon-to-oxygen (C/O) ratio, to formation scenarios3. However, the complexity of planet formation requires further tracers, as the unambiguous interpretation of the measured C/O ratio is fraught with complexity4. Isotope ratios, such as deuterium to hydrogen and 14N/15N, offer a promising avenue to gain further insight into this formation process, mirroring their use within the Solar System5,6,7. For exoplanets, only a handful of constraints on 12C/13C exist, pointing to the accretion of 13C-rich ice from beyond the CO iceline of the disks8,9. Here we report on the mid-infrared detection of the 14NH3 and 15NH3 isotopologues in the atmosphere of a cool brown dwarf with an effective temperature of 380 K in a spectrum taken with the Mid-Infrared Instrument (MIRI) of JWST. As expected, our results reveal a 14N/15N value consistent with star-like formation by gravitational collapse, demonstrating that this ratio can be accurately constrained. Because young stars and their planets should be more strongly enriched in the 15N isotope10, we expect that 15NH3 will be detectable in several cold, wide-separation exoplanets.
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Data availability
The JWST MIRI data presented in this paper are part of the JWST MIRI GTO programme (programme identifier (PID) 1189; PI T. Roellig). The JWST data will be publicly available in the Barbara A. Mikulski Archive for Space Telescopes (MAST; https://archive.stsci.edu/) after 28 July 2023 and can be found either using the programme identifier or using the https://doi.org/10.17909/as3s-x893. The HST WFC3 spectrum is available from https://cdsarc.cds.unistra.fr/viz-bin/cat/J/ApJ/920/20#/article.
Code availability
The code used in this publication to extract, reduce and analyse the data is as follows: the data-reduction pipeline of JWST can be found at https://jwst-pipeline.readthedocs.io/en/latest/; the atmospheric model codes used to fit the data can be found at https://www.exoclouds.com/ for the ARCiS code19 and at https://petitradtrans.readthedocs.io/en/latest/ for the petitRADTRANS code18. The simplified planet-formation model4 used to study 14N/15N as a function of accreted ice mass can be found at https://gitlab.com/mauricemolli/formation-inversion. The detailed setups of the open-source tools for the analyses presented here are described in the Methods section of this paper and can be made available to interested parties on request.
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Acknowledgements
This work is based (in part) on observations made with the NASA/ESA/CSA James Webb Space Telescope (JWST). The data were obtained from the Mikulski Archive for Space Telescopes (MAST) at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-03127 for the JWST. These observations are associated with programme 1189. The Mid-Infrared Instrument (MIRI) draws on the scientific and technical expertise of the following organizations: Ames Research Center, USA; Airbus Defence and Space, UK; CEA/IRFU, Saclay, France; Centre Spatial de Liège, Belgium; Consejo Superior de Investigaciones Científicas, Spain; Carl Zeiss Optronics, Germany; Chalmers University of Technology, Sweden; Danish Space Research Institute, Denmark; Dublin Institute for Advanced Studies, Ireland; European Space Agency, the Netherlands; ETCA, Belgium; ETH Zurich, Switzerland; Goddard Space Flight Center, USA; Institut d’Astrophysique Spatiale, France; Instituto Nacional de Técnica Aeroespacial, Spain; Institute for Astronomy, Edinburgh, UK; Jet Propulsion Laboratory, USA; Laboratoire d’Astrophysique de Marseille (LAM), France; Leiden University, the Netherlands; Lockheed Advanced Technology Center, USA; NOVA Opt-IR Group at Dwingeloo, the Netherlands; Northrop Grumman, USA; Max-Planck-Institut für Astronomie (MPIA), Heidelberg, Germany; Laboratoire d’Etudes Spatiales et d’Instrumentation en Astrophysique (LESIA), France; Paul Scherrer Institut, Switzerland; Raytheon Vision Systems, USA; RUAG Aerospace, Switzerland; Rutherford Appleton Laboratory (RAL Space), UK; Space Telescope Science Institute, USA; Toegepast Natuurwetenschappelijk Onderzoek (TNO-TPD), the Netherlands; UK Astronomy Technology Centre, UK; University College London, UK; University of Amsterdam, the Netherlands; University of Arizona, USA; University of Bern, Switzerland; University of Cardiff, UK; University of Cologne, Germany; University of Ghent, Belgium; University of Groningen, the Netherlands; University of Leicester, UK; KU Leuven, Belgium; University of Stockholm, Sweden; and Utah State University, USA. The following national and international funding agencies funded and supported the MIRI development: NASA; ESA; Belgian Science Policy Office (BELSPO); Centre Nationale d’Etudes Spatiales (CNES); Danish National Space Center; Deutsches Zentrum fur Luft und Raumfahrt (DLR); Enterprise Ireland; Ministerio de Economía y Competitividad; Netherlands Research School for Astronomy (NOVA); Netherlands Organisation for Scientific Research (NWO); Science and Technology Facilities Council; Swiss Space Office; Swedish National Space Agency; and UK Space Agency. D.B. and M.M.-C. are supported by Spanish MCIN/AEI/10.13039/501100011033 grant nos. PID2019-107061GB-C61 and MDM-2017-0737. C.C., A.B., P.-O.L., R.G. and A.C. acknowledge funding support from CNES. P.P. thanks the Swiss National Science Foundation (SNSF) for financial support under grant number 200020_200399. N.W. acknowledges funding from NSF award 1909776 and NASA XRP award 80NSSC22K0142. O.A., I.A., B.V. and P.R. thank the European Space Agency (ESA) and the Belgian Science Policy Office (BELSPO) for their support in the framework of the PRODEX Programme. L.D. acknowledges funding from the KU Leuven Interdisciplinary Grant (IDN/19/028), the European Union H2020-MSCA-ITN-2019 under grant no. 860470 (CHAMELEON) and the FWO research grant G086217N. I.K. acknowledges support from grant TOP-1 614.001.751 from the Dutch Research Council (NWO). O.K. acknowledges support from the Federal Ministry of Economy and Energy (BMWi) through the German Space Agency (DLR). J.P. acknowledges financial support from the UK Science and Technology Facilities Council and the UK Space Agency. G.O. acknowledges support from the Swedish National Space Board and the Knut and Alice Wallenberg Foundation. P.T. acknowledges support by the European Research Council (ERC) under grant agreement ATMO 757858. F.A.M. has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 860470. L.C. acknowledges support by grant PIB2021-127718NB-100 from the Spanish Ministry of Science and Innovation/State Agency of Research MCIN/AEI/10.13039/501100011033. E.F.v.D. acknowledges support from A-ERC grant 101019751 MOLDISK. T.R. acknowledges support from the ERC 743029 EASY. G.Ö. acknowledges support from SNSA. T.H. acknowledges support from the ERC under the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 832428-Origins. We thank the MIRI instrument team and the many others who contributed to the success of the JWST.
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All authors played a substantial role in one or more of the following: designing and building the MIRI, development of the original proposal, management of the project, definition of the target list and observation plan, analysis of the data, theoretical modelling and preparation of this paper. Some specific contributions are listed as follows. P.-O.L. is PI of the JWST MIRI GTO European consortium programme dedicated to JWST observations of exoplanet atmospheres. D.B., P.M. and P.P. provided overall programme leadership and management of the WISE J1828 working group. P.-O.L., T.H., R.W., (co-lead of the JWST MIRI GTO European consortium), D.B. and M.Mu. made notable contributions to the design of the observational programme and contributed to the setting of the observing parameters. P.P., I.A. and M.S. reduced the data. P.T. generated theoretical model grids for comparison with the data. P.M., M.Mi. and N.W. fitted the generated spectrum with retrieval models and M.V. also contributed. F.A.M. applied the radiative-convective equilibrium retrieval to the spectrum. D.B., P.M. and P.P. led the writing of the manuscript. P.-O.L. and L.D. made notable contributions to the writing of this paper. Further contributions were provided by M.M.-C. and L.D. P.B., A.B., J.B., C.C., A.C., N.C., R.G., A.G., A.M.G., S.K., F.L., D.R., P.R., S.S. and I.W. contributed to instrument construction, the programme design and/or the data analysis. P.M., P.P. and D.B. generated the figures for this paper. G.W. is PI of the JWST MIRI instrument, P.-O.L., T.H., M.G., B.V., L.C., E.F.v.D., T.R. and G.Ö. are co-PIs and L.D., R.W., O.A., I.K., O.K., J.P., G.O. and D.B. are co-investigators of the JWST MIRI instrument.
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Extended data figures and tables
Extended Data Fig. 1 The spectrum of WISE J1828 and the best-fit model.
We show the MIRI/MRS spectrum of WISE J1828 (black solid lines) and the best-fit model of the regularized P–T retrieval of petitRADTRANS (red line). Residuals (models − observed spectrum) are shown in the bottom panel. pRT-reg and ARCiS-reg stand for the regularized P–T retrieval of petitRADTRANS and ARCiS, respectively.
Extended Data Fig. 2 Model inferences on the various P–T profiles derived for WISE J1828.
The individual panels always highlight the constraint from one given model, whereas the results of the other models are shown in the background. pRT-reg and ARCiS-reg stand for the regularized P–T retrievals, whereas pRT-free and ARCiS-free stand for the unregularized P–T retrievals of petitRADTRANS and ARCiS, respectively. The contribution functions of the HST and MIRI observations, constrained from the best-fit pRT-reg model, are shown as dotted and dashed lines, respectively. The condensation curve for water (at solar metallicity) is shown as a blue dash-dotted curve, indicating that, although neglected in our models, water clouds could affect the spectrum in a modest away.
Extended Data Fig. 3 One-dimensional projection of the posterior distributions of the WISE J1828 retrievals.
Values correspond to key atmospheric quantities shown in Extended Data Table 1. pRT-reg and ARCiS-reg stand for the regularized P–T retrievals, whereas pRT-free and ARCiS-free stand for the unregularized P–T retrievals of petitRADTRANS and ARCiS, respectively.
Extended Data Fig. 4 Evolution of the planetary 14N/15N as a function of the mass accreted in solids (rock and ice).
This computation assumes a planet that forms outside the NH3 iceline but inside the N2 iceline. The dotted black line denotes the value expected for pure NH3 ice.
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Barrado, D., Mollière, P., Patapis, P. et al. 15NH3 in the atmosphere of a cool brown dwarf. Nature 624, 263–266 (2023). https://doi.org/10.1038/s41586-023-06813-y
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DOI: https://doi.org/10.1038/s41586-023-06813-y
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