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Signatures of strong magnetization and a metal-poor atmosphere for a Neptune-sized exoplanet

Nature Astronomy volume 6, pages 141–153 (2022)Cite this article

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Abstract

The magnetosphere of an exoplanet has yet to be unambiguously detected. Investigations of star–planet interaction and neutral atomic hydrogen absorption during transit to detect magnetic fields in hot Jupiters have been inconclusive, and interpretations of the transit absorption non-unique. In contrast, ionized species escaping a magnetized exoplanet, particularly from the polar caps, should populate the magnetosphere, allowing detection of different regions from the plasmasphere to the extended magnetotail and characterization of the magnetic field producing them. Here we report ultraviolet observations of HAT-P-11 b, a low-mass (0.08 MJ) exoplanet showing strong, phase-extended transit absorption of neutral hydrogen (maximum and tail transit depths of 32 ± 4% and 27 ± 4%) and singly ionized carbon (15 ± 4% and 12.5 ± 4%). We show that the atmosphere should have less than six times the solar metallicity (at 200 bar), and the exoplanet must also have an extended magnetotail (1.8–3.1 au). The HAT-P-11 b equatorial magnetic field strength should be about 1–5 G. Our panchromatic approach using ionized species to simultaneously derive metallicity and magnetic field strength can now constrain interior and dynamo models of exoplanets, with implications for formation and evolution scenarios.

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Fig. 1: Flowchart of the HAT-P-11 star–planet system (not to scale) and the corresponding modelling framework proposed in this study.
Fig. 2: HAT-P-11 b FUV transit absorption.
Fig. 3: Sensitivity of C ii model transit light curves versus the metallicity assumed in the deep atmosphere and the strength of the intrinsic magnetic field of the exoplanet.
Fig. 4: PIC high-resolution simulations (Δ ≈ 0.33 Rp) for one of the best fits of the magnetic field strength, B = 2.4 G.
Fig. 5: Flow streamlines over the density of C ii ions that originally started their trip from the north and south polar cap regions.

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Data Availability

The data that support the plots within this paper and other findings of this study are available from the corresponding author upon reasonable request. HST reduced data are available to the public through https://archive.stsci.edu/ using the dataset names shown in Supplementary Table 1. An ASCII version of the HAT-P-11 stellar spectrum shown in Extended Data Fig. 2b can be downloaded here: https://doi.org/10.48392/lbj-001.

Code Availability

All the codes used in this study have been employed in the past for published work and references are provided in the manuscript. Those references include enough detail to make the model predictions reproducible. The PIC code is an old version of the Tristan code that is available to the public though Github: https://github.com/ntoles/tristan-mp-pitp.

Change history

  • 23 December 2021

    In the version of this article initially published, in the second paragraph of the Conclusions section, the callout to Supplementary Discussion 6 should have been to Supplementary Discussion 7. The callout has been corrected in the article as of 23 December 2021.

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Acknowledgements

We are very grateful to the staff at the Space Telescope Science Institute, in particular to P. Royle, S. Penton, W. Januszewski and J. Debes, for their careful work in the scheduling of our observations and for various instrument insights. We also thank C. Carvalho at the Institut d’Astrophysique de Paris and T. Forrester at the Lunar & Planetary Laboratory for the setup and managing of various computing resources for this project. We thank V. Bourrier, D. Ehenreich and A. Lecavelier for helpful discussions about the analysis of the Lyα transit data. L.B.-J. and P.L. acknowledge support from the Centre National des Etudes Spatiales CNES (France) and the Centre National de la Recherche Scientifique (CNRS) under project PACES. All US co-authors acknowledge support from the Space Telescope Science Institute under the PanCET GO 14767 programme, and G.E.B., G.W.H. and T.K. were also funded under GO 14625. This work is based on observations with the National Aeronautics and Space Administration/European Space Agency HST, obtained at the Space Telescope Science Institute operated by AURA, Inc. This work is also based on observations with XMM-Newton.

Author information

Authors and Affiliations

  1. Institut d’Astrophysique de Paris, Sorbonne Universités, UPMC & CNRS, Paris, France

    Lotfi Ben-Jaffel

  2. Lunar and Planetary Laboratory, University of Arizona, Tucson, AZ, USA

    Lotfi Ben-Jaffel & Gilda E. Ballester

  3. Zentrum für Astronomie und Astrophysik, Technische Universität Berlin, Berlin, Germany

    Antonio García Muñoz

  4. AIM, CEA, CNRS, Université Paris-Saclay, Université de Paris, Gif-sur-Yvette, France

    Antonio García Muñoz

  5. Groupe de Spectroscopie Moléculaire et Atmosphérique, Université de Reims, Champagne-Ardenne, France

    Panayotis Lavvas

  6. Department of Earth & Planetary Sciences, John Hopkins University, Baltimore, MD, USA

    David K. Sing

  7. Department of Physics & Astronomy, John Hopkins University, Baltimore, MD, USA

    David K. Sing

  8. Centro de Astrobiología (CSIC-INTA), ESAC, Madrid, Spain

    Jorge Sanz-Forcada

  9. Lowell Center for Space Science and Technology, University of Massachusetts, Lowell, MA, USA

    Ofer Cohen

  10. NASA Jet Propulsion Laboratory, Pasadena, CA, USA

    Tiffany Kataria

  11. Center of Excellence in Information Systems, Tennessee State University, Nashville, TN, USA

    Gregory W. Henry

  12. DTU Space, National Space Institute, Technical University of Denmark, Kongens Lyngby, Denmark

    Lars Buchhave

  13. Kavli Institute for Astrophysics and Space Research, Massachusetts Institute of Technology, Cambridge, MA, USA

    Thomas Mikal-Evans

  14. School of Physics, University of Bristol, HH Wills Physics Laboratory, Bristol, UK

    Hannah R. Wakeford

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

    Mercedes López-Morales

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  1. Lotfi Ben-Jaffel
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  2. Gilda E. Ballester
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Contributions

L.B.-J. led the data analysis with contributions from G.E.B and identified the problem and solution for the current COS pipeline derivation of errors. He defined and planned over time the 3D PIC magnetospheric simulations and the post-processing of the large set of plasma data that enabled the reported analysis. He also defined the H i interactions with protons. He defined the final strategy and reasoning to disentangle the different parameters of the problem and get the different results summarized in Table 1. He used a Parker model for the stellar wind definition. He also derived a simplified model regarding the magnetic field strength and internal heat of the planet. He prepared the final draft with contributions from G.E.B. in particular and other co-authors as described below. G.E.B. initiated the multifaceted far-UV approach to the study of HAT-P-11 b in heavy metals versus H i, and, with L.B.-J. and A.G.M., led the definition and implementation of the cascading modelling scheme and its implementation by other co-investigators under both HST programmes and other related work. She led and conducted the HST far-UV observations and closely interacted with L.B.-J. on most aspects of the work, in particular with in-depth discussions of the general magnetospheric science including the need to resolve the effects of metallicity versus field strength from signatures in the data. She worked on several aspects of the publication including writing some sections. A.G.M. also provided the photochemistry hydro code modelling and contributed to the data interpretation and paper writing. He wrote the ‘Upper-atmosphere aeronomy’ section in the Methods. P.L. provided the lower-atmosphere chemistry code modelling and contributed to the data interpretation and paper writing. He wrote the ‘Lower-middle atmosphere’ section in the Methods. D.K.S. contributed to the implementation of the HST observing programme, 1D lower atmospheric modelling, interpretation and contributed to writing the ‘Deep-lower atmosphere’ section in the Methods and the paper in general. J.S.-F. was responsible for the X-ray observations obtained for this project. He analysed the X-ray data, modelled the XUV emission and conducted its interpretation with discussion with G.E.B and L.B.-J. He wrote the ‘Stellar XUV spectrum reconstruction’ section in the Methods with contributions from L.B.-J. and G.E.B. O.C. applied his MHD code and solar and stellar wind expertise to model HAT-P-11 b. He wrote the ‘Stellar wind plasma and interplanetary magnetic field conditions at the orbital position of the exoplanet’ section in the Methods with contributions from L.B.-J. T.K. provided the 3D GCM models and contributed to writing the ‘Deep-lower atmosphere’ section in the Methods. G.W.H. obtained the optical monitoring of the star activity that was used in two PanCET publications and contributed to the paper writing. L.B., T.M.-E. and H.R.W. contributed to the paper writing. M.L.-M. contributed to the obtention of the HST time and the preparation of the HST observations to collect the data presented in the manuscript. She contributed to the paper writing. All authors contributed at different levels to the definition of the PanCET concept that is applied here.

Corresponding author

Correspondence to Lotfi Ben-Jaffel.

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Extended data

Extended Data Fig. 1 Lyman alpha model fit.

One of our best models fit (B = 2.4 G, 2.35 x solar metallicity) compared to HAT-P-11b Lya line profiles observed at selected phases of the transit event (HST visit 1 & 2 averaged). We show the out-of-transit Lya line profile (average of orbit 1 of the two visits, black), in-transit observed line profile (red), and model best fit for the selected phase (cyan). Error bars represent the 1σ statistical uncertainties. a, HST orbit 5. b, HST orbit 4. c, HST orbit 3 (see Fig. 2 main draft for details).

Extended Data Fig. 2 Stellar spectrum.

a, Reconstruction of the intrinsic profile (solid line) of the Lya line of HAT-P-11 using observations (histogram) and best fit model with an ISM [H I] ~ 4 ×1018 cm-2 (dashed). b, HAT-P-11 full spectrum reconstructed at 1 AU from the star. The spectrum, in the range 1-54997 Å, is used as an input for all theoretical models developed in this comprehensive study. An ascii file of the spectrum is provided online.

Extended Data Fig. 3 Light curves variability.

Transit light curves of HAT-P-11 versus time variability. a, Integrated flux of C II 133.45 nm (red) and C II 133.57 nm lines (black, scaled by the two lines’ mean flux ratio ~1.41) versus time measured from the transit central time Tc. For clarity, dates of observations are only shown for the first HST orbit (time from mid-transit = -0.375), the other exposures being separated by a multiple of the HST orbit (1.5 h). b, Normalized flux of FUV chromosphere lines. We notice a flare event during the fifth HST orbit of the transit observed on December 21 2016 (blue) in the SI III and Si IV lines, an activity that is not visible in the C II lines. An extended but weaker activity also appears at most orbital phases during the May 21 2017 transit (olive) for the Si III and Si IV lines but not for the C II lines.

Extended Data Fig. 4 HST COS Error.

HD 209458 exposure lb4m05knq obtained with COS G130M on Oct. 2, 2009 (Ballester & Ben-Jaffel, 2015)38. The stellar C II 1335 Å doublet spectrum (black) is compared to the statistical errors derived with the old (olive, e.g., CALCOS 2.14.4 or 2.18.5) and new (red, CALCOS 3.1.8) calibration pipelines. With the new pipeline errors (red), any detection of a transit absorption would be impossible. The new and highly inflated pipeline errors would also render the basic shape of the FUV spectrum of HD 209458 unmeasurable while other FUV dataset for this sunlike star are available (e.g., with HST STIS/G140L, STIS/Echelle data).

Extended Data Fig. 5 Middle and upper atmosphere models.

a, Atmospheric thermal structure (black lines) and eddy mixing (blue lines) for the atmosphere of HAT-P-11 b, under different assumptions of metallicity. The thermal profile is consistent with the conditions at lower atmosphere (section I) and upper atmosphere (section III). b, Model of species mole fraction distribution in the lower-middle atmosphere of HAT-P-11 b under the assumption of solar metallicity and thermal structure shown in a. c, Model of species distribution in the upper atmosphere of HAT-P-11 b based on mixing ratios displayed on a & b. d, Temperature and velocity distributions corresponding to upper atmosphere shown in c.

Extended Data Fig. 6 Plasma gyroradii.

2D distribution of gyroradius of individual species in the noon-midnight plane. a, Planetary protons. b, Planetary C II. c, Stellar wind protons. For electrons (not shown), the gyroradius should be mi/me=100 smaller. For the three plasma sources and for electrons, those scales are well resolved in our simulation, which allows us to properly describe charge separation and kinetic acceleration of species that are needed in the present study (see Supplementary Discussion X & ‘Plasmasphere and magnetosphere’ in the Methods for more details).

Extended Data Fig. 7 MHD coronal model.

Temperature distribution in the exoplanet’s orbital plane extracted from MHD 3D model simulation of HAT-P-11 wind (see ‘Stellar wind plasma and interplanetary magnetic field conditions at the orbital position of the exoplanet’ in the Methods for more details).

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Supplementary discussion and Tables 1–3.

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Ben-Jaffel, L., Ballester, G.E., Muñoz, A.G. et al. Signatures of strong magnetization and a metal-poor atmosphere for a Neptune-sized exoplanet. Nat Astron 6, 141–153 (2022). https://doi.org/10.1038/s41550-021-01505-x

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