Abstract
The abundance of refractory elements in giant planets can provide key insights into their formation histories1. Owing to the low temperatures of the Solar System giants, refractory elements condense below the cloud deck, limiting sensing capabilities to only highly volatile elements2. Recently, ultra-hot giant exoplanets have allowed for some refractory elements to be measured, showing abundances broadly consistent with the solar nebula with titanium probably condensed out of the photosphere3,4. Here we report precise abundance constraints of 14 major refractory elements on the ultra-hot giant planet WASP-76b that show distinct deviations from proto-solar and a sharp onset in condensation temperature. In particular, we find nickel to be enriched, a possible sign of the accretion of the core of a differentiated object during the evolution of the planet. Elements with condensation temperatures below 1,550 K otherwise closely match those of the Sun5 before sharply transitioning to being strongly depleted above 1,550 K, which is well explained by nightside cold-trapping. We further unambiguously detect vanadium oxide on WASP-76b, a molecule long suggested to drive atmospheric thermal inversions6, and also observe a global east–west asymmetry7 in its absorption signals. Overall, our findings indicate that giant planets have a mostly stellar-like refractory elemental content and suggest that temperature sequences of hot Jupiter spectra can show abrupt transitions wherein a mineral species is either present or completely absent if a cold trap exists below its condensation temperature8.
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Data availability
The MAROON-X data used in this work are available at https://udemontreal-my.sharepoint.com/:f:/g/personal/stefan_pelletier_umontreal_ca/EkYThK-JMKFHlclyx7RnlIABySi6V60HuZC0c_9m6LfE6Q?e=vGErBT. The ESPRESSO data used to confirm the VO detection are publicly available on Dace (https://dace.unige.ch/dashboard/). Source data are provided with this paper.
Code availability
The MAROON-X reduction pipeline33 used by the instrument team to perform the data extraction is public software available from Gemini at https://github.com/GeminiDRSoftware/MAROONXDR. The atmospheric modelling and retrievals use SCARLET17,40, HELIOS-K44 (https://helios-k.readthedocs.io), FastChem58 (https://github.com/exoclime/FastChem), emcee64 (https://emcee.readthedocs.io/en/stable/) and corner.py88 (https://corner.readthedocs.io/en/latest/). The ESPRESSO data analysis was performed using Tayph66 (https://github.com/Hoeijmakers/tayph). The main analysis routines written for this work and using the astropy89,90, matplotlib91, numpy92, scipy93 and scikit-learn94 Python libraries are available at https://udemontreal-my.sharepoint.com/:f:/g/personal/stefan_pelletier_umontreal_ca/EmXMwsPp2JFCnckKJNWkf7ABrEomi5EqmadxK4Hofd7ItQ?e=73GbIp.
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Acknowledgements
This work is based on observations obtained at the international Gemini Observatory, a program of the National Science Foundation (NSF)’s NOIRLab, which is managed by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the NSF on behalf of the Gemini Observatory partnership: the NSF (USA), National Research Council (Canada), Agencia Nacional de Investigación y Desarrollo (Chile), Ministerio de Ciencia, Tecnología e Innovación (Argentina), Ministério da Ciência, Tecnologia, Inovações e Comunicações (Brazil), and Korea Astronomy and Space Science Institute (Republic of Korea).This work was enabled by observations made from the Gemini North telescope, located within the Maunakea Science Reserve and adjacent to the summit of Maunakea. We are grateful for the privilege of observing the Universe from a place that is unique in both its astronomical quality and its cultural significance. This research has made use of NASA’s Astrophysics Data System and the NASA Exoplanet Archive, which is operated by the California Institute of Technology, under contract with NASA within the Exoplanet Exploration Program. S.P. is supported by the Technologies for Exo-Planetary Science (TEPS) Natural Sciences and Engineering Research Council of Canada (NSERC) CREATE Trainee Program. B.B. acknowledges funding by the NSERC and the Fonds de Recherche du Québec – Nature et Technologies (FRQNT). M.A.-D. is supported by Tamkeen under the NYU Abu Dhabi Research Institute, United Arab Emirates grant CAP3. B.P. acknowledges partial financial support from the Fund of the Walter Gyllenberg Foundation. D.K., A.S. and J.L.B. acknowledge funding from the David and Lucile Packard Foundation, the Heising-Simons Foundation, the Gordon and Betty Moore Foundation, the Gemini Observatory, the NSF (award number 2108465) and NASA (grant numbers 80NSSC22K0117 and 80NSSC19K0293). F.D. thanks the CNRS/INSU Programme National de Planétologie (PNP) and Programme National de Physique Stellaire (PNPS) for funding support. B.K. acknowledges funding from the European Research Council under the European Union’s Horizon 2022 research and innovation programme (grant agreement no. 865624, GPRV). O.L. acknowledges financial support from the FRQNT (270853 and 303926), the NSERC, the Trottier Institute for Research on Exoplanets (iREx) and from the University of Montreal. A.C. acknowledges funding from the French ANR under contract number ANRCE310019 (SPlaSH). This work is supported by the French National Research Agency in the framework of the Investissements d’Avenir programme (ANR-15-IDEX-02), through the funding of the “Origin of Life” project of Grenoble-Alpes University.
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S.P., B.B. and L.P. conceived the project. S.P. wrote the original MAROON-X observing proposal and the manuscript and carried out the analysis of the MAROON-X data, with B.B. and H.J.H. providing guidance. M.A.-D. performed the accretion modelling portion of the analysis. B.P. independently analysed the ESPRESSO data to confirm the VO detection. D.K., A.S., J.L.B. and J.S. assisted with the observational setup, carried out the observations and performed the MAROON-X data extraction. F.D., B.K., T.H. and A.C. acquired and contributed extra data for the project. L.B. implemented the FastChem equilibrium chemistry code in the modelling framework. A.Y.K., O.L. and N.C.-B. contributed to the stellar contamination detrending algorithm. All co-authors provided comments and suggestions about the manuscript.
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Extended data figures and tables
Extended Data Fig. 1 Data detrending steps and noise model.
a, A single MAROON-X spectral order for the 5.3-h transit time series obtained on 12 September 2020. b, After continuum alignment. c, With the median out-of-transit spectrum divided out. d, Post-removal of stellar and telluric contaminants using PCA, with ten principal components removed in this case. e, The noise model used for an example exposure. The reduction steps take care of removing all telluric and stellar lines, as well as the continuum, whereas the noise model serves to downweigh regions of the spectrum that are noisier. The end product of the data reduction (d) contains the planetary trace buried in noise and serves as the input for the later cross-correlation and retrieval analyses.
Extended Data Fig. 2 Cross-sections of prominent metals, ions and molecules.
Values are computed for a temperature of 2,500 K and include 10−4 bar pressure broadening where applicable. Atoms with only a single valence electron (Li, Na, K, Ca+ and Ba+) have few very strong lines, whereas most other metals tend to be composed of ‘line forests’ on top of a low continuum. Molecules also have forests of spectral lines, but on top of distinct absorption bands. Meanwhile, H− acts as a flat source of continuum opacity in this wavelength range, similar to a grey cloud deck. The product of the cross-section and volume-mixing ratio of a species in the atmosphere of WASP-76b determines how detectable it is.
Extended Data Fig. 3 Cross-correlation results for species not detected in the atmosphere of WASP-76b.
Same as Fig. 1 but for species of interest that were notably not detected. Particularly noticeable is the absence of Ti, TiO, Sc and AlO, which MAROON-X should be able to easily detect. Other non-detections are less surprising, as they either have few strong lines in the MAROON-X bandpass (Al) or are not expected to be particularly abundant from chemical-equilibrium predictions (Ti+, V+, CrH).
Extended Data Fig. 4 Independent confirmation of the VO detection on WASP-76b.
a, The VO detection with MAROON-X (490–920 nm, R = 85,000, three transits). b, The VO detection with ESPRESSO (380–790 nm, R = 140,000, two transits7). The ESPRESSO analysis was done with an independent framework13, using an independent model template, on a separate dataset, and also shows a clear VO signal slightly offset to the expected location (black cross) that is consistent with the MAROON-X data. Differences in the overall detection strength and shape are because of MAROON-X having a lower resolution but a redder wavelength coverage, and three instead of two transits. The presence of a VO signal in both the MAROON-X and ESPRESSO transit datasets provides a high degree of confidence as to the robustness of the signal.
Extended Data Fig. 5 Retrieved constraints on the atmospheric and orbital properties of WASP-76b obtained from three MAROON-X transits.
a, Corner plot of the marginalized posterior distributions for the abundance of included species, cloud-top pressure Pc (in bar), scaling parameter α, temperature of different atmospheric layers, Keplerian velocity Kp and systemic velocity Vsys. The shaded regions respectively depict the 39.3%, 86.5%, and 98.9% confidence intervals. b, The sum of the volume-mixing ratio of individual metals, ions and molecules included in the model. The equivalent sums for solar and stellar compositions (dashed lines) are also shown for comparison, with WASP-76b being consistent with slightly (+0.28 dex) super-stellar. c, The resulting vertical temperature structure from the ten temperature points (T0–T9, black dots), showing the presence of a stratosphere.
Extended Data Fig. 6 Chemical-equilibrium predictions of the atmospheric composition of WASP-76b.
a, The retrieved temperature–pressure profile and cloud-top continuum pressure. b, Chemical-equilibrium-abundance predictions58 for a wide range of elements given the retrieved temperature–pressure structure (a) and assuming a stellar atmospheric composition18. Measured abundances for WASP-76b at the estimated investigated altitudes are also shown for comparison. Most refractory species (for example, Fe, Mg, Ni, Mn and Cr) are not expected to be substantially ionized below the microbar level and are relatively well approximated by a constant-with-altitude volume-mixing-ratio model. With the exception of V and Ti, most elements are only expected to be bound in molecular form in trace amounts. Alkali metals, calcium and barium all ionize more readily and have deep spectral features and, thus, are expected to be substantially ionized at the lower pressures analysed. Error bars and shaded regions represent 1σ uncertainties.
Extended Data Fig. 7 Comparison of results from different retrieval prescriptions.
a, Retrieved abundance ratios given different model parameterizations. b, Inferred temperature profile for each associated retrieval prescription. The three retrievals use separate combinations of the VALD52, Kurucz53 and NIST54 opacities and fitted free17, Guillot70 and isothermal temperature–pressure profiles. Despite using differing temperature-structure prescriptions and opacities, the recovered abundance ratios in all three retrievals are consistent within uncertainties. However, assuming an isothermal or Guillot profile can overconstrain the temperature structure. Error bars represent 1σ uncertainties. Shaded regions represent 1σ and 2σ contours.
Extended Data Fig. 8 Accretion toy model exploring the scenario of WASP-76b accreting a body with a Mercury-like composition.
a, The change in enrichment of elemental-abundance ratios relative to proto-solar as a function of the accreted mass (V/Fe and Ba/Fe behave similarly to Mn/Fe and are not shown for clarity). In this example, the accreted body has a core-mass fraction of 1.95, a mantle composition matching that of the surface of Mercury84 and a core composition of 15% Ni and predominantly Fe as the rest83. The horizontal blue line denotes a proto-solar composition and the vertical dashed lines show the masses of Mercury, Mars and Venus for reference. If too small a body is accreted (≤0.1 M⊕) onto the initial 284 M⊕ of WASP-76b, the composition does not change greatly from proto-solar. If too large a body is accreted (≥3 M⊕), the overall composition begins to change too exceptionally. Although all abundance ratios require different masses to be perfectly matched under this assumed enrichment material composition, the overall best fit occurs if a large object between roughly the size of Mars and Venus is added to WASP-76b. b, A comparison between the data and the toy model assuming an accreted mass of 0.5 M⊕, in which the data points except Mn/Fe are reasonably well matched. All error bars denote 1σ uncertainties.
Extended Data Fig. 9 Rest-frame absorption signals of individual species on WASP-76b.
Shown in each panel are the cross-correlation trails for the species combined in Fig. 3b. Despite their wide range in condensation temperature, most species have a similar ‘kinked’ absorption trail as Fe (dotted white line), probably indicating that condensation is not the sole culprit for the asymmetric signature. One notable exception is ionized calcium, which does not show such an asymmetry, probably because of Ca+ triplet having an absorption depth consistent with analysing an escaping atmosphere18.
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Pelletier, S., Benneke, B., Ali-Dib, M. et al. Vanadium oxide and a sharp onset of cold-trapping on a giant exoplanet. Nature 619, 491–494 (2023). https://doi.org/10.1038/s41586-023-06134-0
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DOI: https://doi.org/10.1038/s41586-023-06134-0
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