Possible Evidence for the Presence of Volatiles on the Warm Super-Earth TOI-270 b
The Astronomical Journal 170:4 (2025)
Abstract:
The search for atmospheres on rocky exoplanets is a crucial step in understanding the processes driving atmosphere formation, retention, and loss. Past studies have revealed the existence of planets interior to the radius valley with densities lower than would be expected for pure-rock compositions, indicative of the presence of large volatile inventories, which could facilitate atmosphere retention. Here, we present an analysis of the JWST/NIRSpec G395H transmission spectrum of the warm ( Teq,AB=0=569 K) super-Earth TOI-270 b (Rp = 1.306 R⊕), captured alongside the transit of TOI-270 d. The JWST white light-curve transit depth updates TOI-270 b’s density to ρp = 3.7 ± 0.5 g cm−3, inconsistent at 4.4σ with an Earth-like composition. Instead, the planet is best explained by a nonzero, percent-level water mass fraction, possibly residing on the surface or stored within the interior. The JWST transmission spectrum shows possible spectroscopic evidence for the presence of this water as part of an atmosphere on TOI-270 b, favoring an H2O-rich steam atmosphere model over a flat spectrum ( lnB=0.3–3.2 , inconclusive to moderate), with the exact significance depending on whether an offset parameter between the NIRSpec detectors is included. We leverage the transit of the twice-larger TOI-270 d crossing the stellar disk almost simultaneously to rule out the alternative hypothesis that the transit light source effect could have caused the water feature in TOI-270 b’s observed transmission spectrum. Planetary evolution modeling furthermore shows that TOI-270 b could sustain a significant atmosphere on gigayear timescales, despite its high stellar irradiation, if it formed with a large initial volatile inventory.A carbon-rich atmosphere on a windy pulsar planet
(2025)
Assessing Robustness and Bias in 1D Retrievals of 3D Global Circulation Models at High Spectral Resolution: A WASP-76 b Simulation Case Study in Emission
The Astrophysical Journal American Astronomical Society 990:2 (2025) 106
Abstract:
High-resolution spectroscopy (HRS) of exoplanet atmospheres has successfully detected many chemical species and is quickly moving toward detailed characterization of the chemical abundances and dynamics. HRS is highly sensitive to the line shape and position; thus, it can detect three-dimensional (3D) effects such as winds, rotation, and spatial variation of atmospheric conditions. At the same time, retrieval frameworks are increasingly deployed to constrain chemical abundances, pressure–temperature (P–T) structures, orbital parameters, and rotational broadening. To explore the multidimensional parameter space, we need computationally fast models, which are consequently mostly one-dimensional (1D). However, this approach risks introducing interpretation bias since the planet’s true nature is 3D. We investigate the robustness of this methodology at high spectral resolution by running 1D retrievals on simulated observations in emission within an observational framework using 3D global circulation models of the quintessential HJ WASP-76 b. We find that the retrieval broadly recovers conditions present in the atmosphere, but that the retrieved P–T and chemical profiles are not a homogeneous average of all spatial and phase-dependent information. Instead, they are most sensitive to spatial regions with large thermal gradients, which do not necessarily coincide with the strongest emitting regions. Our results further suggest that the choice of parameterization for the P–T and chemical profiles, as well as Doppler offsets among opacity sources, impact the retrieval results. These factors should be carefully considered in future retrieval analyses.Machine learning spectral clustering techniques: Application to Jovian clouds from Juno/JIRAM and JWST/NIRSpec
Astronomy & Astrophysics EDP Sciences 701 (2025) a247
Abstract:
We present a new method, based on a joint application of a principal component analysis (PCA) and Gaussian mixture models (GMM), to automatically find similar groups of spectra in a collection. We applied the method (condensed in the public code chopper.py ) to archival Jupiter spectral data in the 2–5 µm range collected by NASA Juno/JIRAM in its first perijove passage (August 2016) and to mosaics of the great red spot (GRS) acquired by JWST/NIRSpec (July 2022). Using JIRAM data analyzed in previous work, we show that using a PCA+GMM clustering can increase the efficiency of the retrieval stage without any loss of accuracy in terms of the retrieved parameters. We show that a PCA+GMM approach is able to automatically identify spectra of known regions of interest (e.g., belts, zones, GRS) belonging to different clusters. The application of the method to the NIRSpec data leads to detection of substructures inside the GRS, which appears to be composed of an outer halo characterized by low reflectivity and an inner brighter main oval. By applying these techniques to JIRAM data, we were able to identify the same substructure. We remark that these new structures have not been seen before at visible wavelengths. In both cases, the spectra belonging to the inner oval have solar and thermal signals comparable to those belonging to the halo, but they present broadened 2.73 µm solar-reflected peaks. Performing forward simulations with the NEMESIS radiative transfer suite, we propose that the broadening may be caused by differences in the vertical extension of the main cloud layer. This finding is consistent with recent 3D fluid dynamics simulations.Strict Limits on Potential Secondary Atmospheres on the Temperate Rocky Exo-Earth TRAPPIST-1 d
The Astrophysical Journal American Astronomical Society 989:2 (2025) 181