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A high internal heat flux and large core in a warm Neptune exoplanet

Abstract

Interactions between exoplanetary atmospheres and internal properties have long been proposed to be drivers of the inflation mechanisms of gaseous planets and apparent atmospheric chemical disequilibrium conditions1. However, transmission spectra of exoplanets have been limited in their ability to observationally confirm these theories owing to the limited wavelength coverage of the Hubble Space Telescope (HST) and inferences of single molecules, mostly H2O (ref. 2). In this work, we present the panchromatic transmission spectrum of the approximately 750 K, low-density, Neptune-sized exoplanet WASP-107b using a combination of HST Wide Field Camera 3 (WFC3) and JWST Near-Infrared Camera (NIRCam) and Mid-Infrared Instrument (MIRI). From this spectrum, we detect spectroscopic features resulting from H2O (21σ), CH4 (5σ), CO (7σ), CO2 (29σ), SO2 (9σ) and NH3 (6σ). The presence of these molecules enables constraints on the atmospheric metal enrichment (M/H is 10–18× solar3), vertical mixing strength (log10Kzz = 8.4–9.0 cm2 s−1) and internal temperature (>345 K). The high internal temperature is suggestive of tidally driven inflation4 acting on a Neptune-like internal structure, which can naturally explain the large radius and low density of the planet. These findings suggest that eccentricity-driven tidal heating is a critical process governing atmospheric chemistry and interior-structure inferences for most of the cool (<1,000 K) super-Earth-to-Saturn-mass exoplanet population.

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Fig. 1: Spectroscopic and broadband NIRCam light curves of the transit of WASP-107b.
Fig. 2: Independent reductions of the transmission spectrum of WASP-107b.
Fig. 3: Interpretation of the transmission spectrum of WASP-107b.
Fig. 4: Inferred molecular volume mixing ratios from the transmission spectrum of WASP-107b.

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Data availability

The NIRCam data used in this paper are associated with JWST GTO programme 1185 (P.I. Greene; observations 8 and 9) and will be publicly available from the Mikulski Archive for Space Telescopes (MAST; https://mast.stsci.edu) at the end of their 1-year exclusive access period. The MIRI data used in this paper are from JWST GTO programme 1280 (P.I. Lagage; observation 1) and will also be publicly available on the MAST at the end of their proprietary period. Further intermediate results from this work are archived on Zenodo at https://doi.org/10.5281/zenodo.10780448 (ref. 46).

Code availability

We used the following codes to reduce and fit the JWST data: STScI’s JWST calibration pipeline44, Eureka!14, tshirt15, starry63, PyMC3 (ref. 66), numpy118, astropy119,120, scipy121 and matplotlib122.

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Acknowledgements

L.W. acknowledges support for this work provided by NASA through the NASA Hubble Fellowship grant #HST-HF2-51496.001-A awarded by the Space Telescope Science Institute (STScI), which is operated by the Association of Universities for Research in Astronomy, Inc., for NASA, under contract NAS5-26555. T.P.G. and T.J.B. acknowledge support from NASA JWST WBSs 411672.07.04.01.02 and 411672.07.05.05.03.02. P.M. acknowledges that this work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344. The document number is LLNL-JRNL-859050. M.R.L. acknowledges NASA XRP award 80NSSC19K0446 and STScI grant HST-AR-16139. M.R.L. and L.W. acknowledge Research Computing at Arizona State University for providing high-performance computing and storage resources that have substantially contributed to the research results reported in this manuscript. L.W. thanks M. Min for meaningful conversations. K.O. acknowledges support from JSPS KAKENHI grant number JP23K19072. M.M. acknowledges funding from NASA Goddard Spaceflight Center through NASA contract NAS5-02105. A.D. and P.-O.L. acknowledge funding support from CNES. We thank M. Rieke for allocating the NIRCam time for this programme.

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Authors and Affiliations

Authors

Contributions

L.W. led the modelling analysis effort, performed the atmospheric modelling using free retrievals and 1D-RCPE models, contributed to the theoretical analysis/interpretation of the observations, led the cross-validation analysis and led the writing of the manuscript. T.J.B. contributed the fiducial Eureka! analyses of the NIRCam and MIRI observations, verified the observing parameters of the NIRCam observations and contributed to the text. T.G.B. contributed the Pegasus analyses of the HST and NIRCam observations, verified the observing parameters of the NIRCam observations, performed the SED fitting and radius estimation, performed the tidal heating analysis and contributed to the text. M.R.L. performed the 1D-RCPE simulations, wrote the introductory text and methods and helped sculpt the direction of the manuscript. K.O. provided comments on the manuscript and helped with interpreting the NH3 detection. J.J.F. contributed to the planet structure models, contributed to the interpretation of the internal temperature of the planet and contributed to the text. E.S. simulated the planet and retrievals before launch, help planned the observation specifications, carried out the tshirt reduction and light-curve fitting and contributed to the text. T.P.G. selected the planet for observation, designed the observational programme, directed some of the analysis and commented on the manuscript. E.R. provided feedback on the modelling interpretation and provided comments on the manuscript. P.M. contributed the cross-validation analysis and to the text. V.P. provided feedback throughout the project and helped with the vertical mixing discussion. Y.T. contributed to the planet structure models. M.M. contributed to deriving the orbital parameters of the planet and feedback on the text. I.E., S.M., L.S.W. and K.E.A. provided useful discussions throughout the manuscript process. P.-O.L. designed the MIRI observational programme and provided its data. A.D. contributed to the MIRI data analysis.

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Correspondence to Luis Welbanks.

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Extended data figures and tables

Extended Data Fig. 1 The 390-Hz noise signal of MIRI/LRS visualized.

a, The background pixel values for part of the second integration of the MIRI/LRS observations of WASP-107b are shown by black points, whereas our fitted 390-Hz noise signal is shown with a red line. b, The Lomb–Scargle periodogram of the pixels in the second group of the second integration before the 390-Hz noise-removal and GLBS steps are applied are shown in red and the periodogram after these two steps are applied is shown in black. The three harmonics used in our cleaning procedure (1st, 2nd and 4th) are indicated with pale blue vertical lines and the skipped 3rd harmonic is shown with a pale orange vertical line. The clear impact of the 390-Hz noise-removal and GLBS steps is seen in the eliminated spikes in the Lomb–Scargle periodogram.

Extended Data Fig. 2 Comparison of different NIRCam reductions and limb-darkening choices.

a, The NIRCam F322W2 and F444W transmission spectra as reduced by the Eureka!, Pegasus and tshirt pipelines are shown in different colours after being smoothed by a four-point-wide boxcar filter. Both the Eureka! and Pegasus reductions fixed limb-darkening coefficients to ATLAS model predictions, whereas tshirt freely fit quadratic coefficients. At wavelengths longer than about 2.9 μm, the F322W2 spectrum of tshirt consistently falls below the spectra of Eureka! and Pegasus; this difference is caused by a combination of tshirt’s ROEBA method (which results in a roughly constant offset across F322W2) and tshirt’s free limb darkening (which results in a small slope across F322W2). b, A similar plot, demonstrating the minimal impacts of varying limb-darkening choices on our final spectra produced by Eureka!.

Extended Data Fig. 3 A demonstration of the underestimation of error bars in the MIRI/LRS observations of L168-9b and the impact of the 390-Hz noise-removal step.

The median fitted transit depth uncertainties decrease with increasing spectral bin width, as would be expected for white noise (blue symbols). Meanwhile, the standard deviation of the L168-9b transmission spectrum is around two times the expected noise level in the spectrally unbinned data. The ratio of the standard deviation of the spectrum to the median fitted uncertainty decreases with increasing bin size, with the exception of a peak around 0.25 μm.

Extended Data Fig. 4 A comparison of different reductions of the WASP-107b MIRI/LRS spectra.

a, A demonstration of the impact of the 390-Hz noise-removal and GLBS steps on our reduction of the WASP-107b MIRI/LRS data. For wavelengths >10 μm, the GLBS step slightly reduces the final transmission, while also turning off the 390-Hz noise-removal step seems to have no further impact at any wavelength. Error bars show 1σ uncertainties. b, A comparison of our fiducial reduction with the three reductions presented in ref. 16, with 1σ uncertainties. Although there are some differences between the four different reductions, the overall shape of the transmission spectrum is robust to differences in reduction choices. c, The per-point differences between different pairs of reductions, which are summarized with a histogram in panel d. With the exception of a single TEATRO point, our reduction agrees with the European Consortium’s three reductions at 3σ. However, there is some structure to the differences between our reduction and those of the European Consortium, with our reduction giving larger transit depths on average than the European Consortium’s from around 8–10 μm.

Extended Data Fig. 5 Illustration of the effects of the key physical processes on the atmospheric structure and resultant spectra.

Panels a and b show the impact of disequilibrium chemical processes (vertical mixing and photochemistry) relative to thermochemical equilibrium. Panels c and d show the influence of changing internal temperature. Panels e and f show the impact of changing eddy diffusion strength. We only show the vertical abundance profiles (panels a, c and e) for observable gases that are influenced by these effects (for instance, water is not shown as it not affected). The observed transit spectrum is shown with grey points with 1σ error bars in panels b, d and f.

Extended Data Fig. 6 Effect of self-consistent microphysical eddysed clouds on the spectrum.

Panel a shows the condensate vertical distributions for the major condensate species. The cloud bases, in which the condensates first forms, all occur at or below the 100-mbar level, with the silicate clouds forming at or below the 1-bar level. Panel b shows the resulting spectrum (with 1σ error bars), as well as the contribution from each cloud species.

Extended Data Fig. 7 Comparison of retrieved pressure–temperature structure.

The retrieved vertical temperature structures (median, 1σ and 2σ) from the free retrieval (Aurora, blue) and the 1D-RCPE model (red) are generally in good agreement within their 68% confidence intervals. The dotted line shows the equilibrium temperature of the planet. The observations generally examine pressures lower than about 100 mbar and as low as about several 10−5 bar. We include in black the Tint = 200 K profile from Extended Data Fig. 5 as an example of lower internal temperatures.

Extended Data Fig. 8 The detection of NH3 in the transmission spectrum of WASP-107b is driven by NIRCAM F322W2 observations.

The data are colour-coded by the point-wise difference in expected log posterior predictive density between the reference 1D-RCPE model and the model without NH3 absorption. The best-fit 1D-RCPE model (R = 300) is shown in grey. Redder data points (larger positive Δelpd score) are better explained by the reference model including NH3 absorption. Although points with positive Δelpd are present throughout the entire transmission spectrum, indicating that NH3 improves the model performance at all wavelengths, the highest scoring points are localized at roughly 3 μm, at which strong NH3 absorption is visible. The purple-shaded regions show areas in which the cross-section of NH3 contributes to 50% or more of the cross-sections detected in WASP-107b, and with visually prominent features. Three data points in the MIRI observations (7.017, 7.318 and 7.468 μm) are not included in the analysis because their associated Pareto k value exceeded 0.7. Data points are shown with 1σ error bars.

Extended Data Table 1 1D-RCPE retrieved atmospheric properties
Extended Data Table 2 Free retrieval retrieved atmospheric properties

Supplementary information

Supplementary Figures

Two supplementary figures showing figures equivalent to Figs. 3 and 4 from the main text but for the Aurora free retrieval

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Welbanks, L., Bell, T.J., Beatty, T.G. et al. A high internal heat flux and large core in a warm Neptune exoplanet. Nature 630, 836–840 (2024). https://doi.org/10.1038/s41586-024-07514-w

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