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Register a new userAtmospheric Retrieval for Super-Earths: Uniquely Constraining the Atmospheric Composition with Transmission Spectroscopy
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We present a retrieval method based on Bayesian analysis to infer the atmospheric compositions and surface or cloud-top pressures from transmission spectra of exoplanets with general compositions. In this study, we identify what can unambiguously be determined about the atmospheres of exoplanets from their transmission spectra by applying the retrieval method to synthetic observations of the super-Earth GJ 1214b. Our approach to infer constraints on atmospheric parameters is to compute their joint and marginal posterior probability distributions using the MCMC technique in a parallel tempering scheme. A new atmospheric parameterization is introduced that is applicable to general atmospheres in which the main constituent is not known a priori and clouds may be present. Our main finding is that a unique constraint of the mixing ratios of the absorbers and up to two spectrally inactive gases (such as N2 and primordial H2+He) is possible if the observations are sufficient to quantify both (1) the broadband transit depths in at least one absorption feature for each absorber and (2) the slope and strength of the molecular Rayleigh scattering signature. The surface or cloud-top pressure can be quantified if a surface or cloud deck is present. The mean molecular mass can be constrained from the Rayleigh slope or the shapes of absorption features, thus enabling to distinguish between cloudy hydrogen-rich atmospheres and high mean molecular mass atmospheres. We conclude, however, that without the signature of Rayleigh scattering--even with robustly detected infrared absorption features--there is no reliable way to tell if the absorber is the main constituent of the atmosphere or just a minor species with a mixing ratio of <0.1%. The retrieval method leads us to a conceptual picture of which details in transmission spectra are essential for unique characterizations of well-mixed atmospheres.
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WASP-121b is one of the most studied Ultra-hot Jupiters: many recent analyses of its atmosphere report interesting features at different wavelength ranges. In this paper we analyze one transit of WASP-121b acquired with the high-resolution spectrograph ESPRESSO at VLT in 1-telescope mode, and one partial transit taken during the commissioning of the instrument in 4-telescope mode. We investigate the anomalous in-transit radial velocity curve and study the transmission spectrum of the planet. By analysing the in-transit radial velocities we were able to infer the presence of the atmospheric Rossiter-McLaughlin effect. We measured the height of the planetary atmospheric layer that correlates with the stellar mask (mainly Fe) to be 1.052$pm$0.015 Rp and we also confirmed the blueshift of the planetary atmosphere. By examining the planetary absorption signal on the stellar cross-correlation functions we confirmed the presence of a temporal variation of its blueshift during transit, which could be investigated spectrum-by-spectrum. We detected significant absorption in the transmission spectrum for Na, H, K, Li, CaII, Mg, and we certified their planetary nature by using the 2D tomographic technique. Particularly remarkable is the detection of Li, with a line contrast of $sim$0.2% detected at the 6$sigma$ level. With the cross-correlation technique we confirmed the presence of FeI, FeII, CrI and VI. H$alpha$ and CaII are present up to very high altitudes in the atmosphere ($sim$1.44 Rp and $sim$2 Rp, respectively), and also extend beyond the transit-equivalent Roche lobe radius of the planet. These layers of the atmosphere have a large line broadening that is not compatible with being caused by the tidally-locked rotation of the planet alone, and could arise from vertical winds or high-altitude jets in the evaporating atmosphere.
This brief review focuses on methods and applications of modeling exoplanetary atmospheres. We discuss various kinds of state of the art self-consistent and retrieval models in 1D and multi-D with a focus on open questions and short- and long-term goals in the field. Expertise previously developed in modeling cool stellar atmospheres and in modeling solar system planetary atmospheres has proven valuable to the field, and will continue to do so. We described upcoming opportunities for making progress in our understanding of atmospheres, and close with what we see as the fields challenges.
The competition between the torques induced by solid and thermal tides drives the rotational dynamics of Venus-like planets and super-Earths orbiting in the habitable zone of low-mass stars. The tidal responses of the atmosphere and telluric core are related to their respective physical properties and strongly depend on the tidal frequency. The resulting torque determines the possible equilibrium states of the planets spin. We compute here an analytic expression for the total tidal torque exerted on a Venus-like planet. This expression is used to characterize the equilibrium rotation of the body. Close to the star, the solid tide dominates. Far from it, the thermal tide drives the rotational dynamics of the planet. The transition regime corresponds to the habitable zone, where prograde and retrograde equilibrium states appear. We demonstrate the strong impact of the atmospheric properties and of the rheology of the solid part on the rotational dynamics of Venus-like planets, highlighting the key role played by dissipative mechanisms in the stability of equilibrium configurations.
We explore the chemistry and observability of nitrogen dominated atmospheres for ultra-short-period super-Earths. We base the assumption, that super-Earths could have nitrogen filled atmospheres, on observations of 55 Cnc e that favour a scenario with a high-mean-molecular-weight atmosphere. We take Titans elemental budget as our starting point and using chemical kinetics compute a large range of possible compositions for a hot super-Earth. We use analytical temperature profiles and explore a parameter space spanning orders of magnitude in C/O & N/O ratios, while always keeping nitrogen the dominant component. We generate synthetic transmission and emission spectra and assess their potential observability with the future James Webb Space Telescope and ARIEL. Our results suggest that HCN is a strong indicator of a high C/O ratio, which is similar to what is found for H-dominated atmospheres. We find that these worlds are likely to possess C/O > 1.0, and that HCN, CN, CO should be the primary molecules to be searched for in thermal emission. For lower temperatures (T < 1500 K), we additionally find NH3 in high N/O ratio cases, and C2H4, CH4 in low N/O ratio cases to be strong absorbers. Depletion of hydrogen in such atmospheres would make CN, CO and NO exceptionally prominent molecules to look for in the 0.6 - 5.0 $mu$m range. Our models show that the upcoming JWST and ARIEL missions will be able to distinguish atmospheric compositions of ultra-short period super-Earths with unprecedented confidence.
Over the past decade, the study of extrasolar planets has evolved rapidly from plain detection and identification to comprehensive categorization and characterization of exoplanet systems and their atmospheres. Atmospheric retrieval, the inverse modeling technique used to determine an exoplanetary atmospheres temperature structure and composition from an observed spectrum, is both time-consuming and compute-intensive, requiring complex algorithms that compare thousands to millions of atmospheric models to the observational data to find the most probable values and associated uncertainties for each model parameter. For rocky, terrestrial planets, the retrieved atmospheric composition can give insight into the surface fluxes of gaseous species necessary to maintain the stability of that atmosphere, which may in turn provide insight into the geological and/or biological processes active on the planet. These atmospheres contain many molecules, some of them biosignatures, spectral fingerprints indicative of biological activity, which will become observable with the next generation of telescopes. Runtimes of traditional retrieval models scale with the number of model parameters, so as more molecular species are considered, runtimes can become prohibitively long. Recent advances in machine learning (ML) and computer vision offer new ways to reduce the time to perform a retrieval by orders of magnitude, given a sufficient data set to train with. Here we present an ML-based retrieval framework called Intelligent exoplaNet Atmospheric RetrievAl (INARA) that consists of a Bayesian deep learning model for retrieval and a data set of 3,000,000 synthetic rocky exoplanetary spectra generated using the NASA Planetary Spectrum Generator. Our work represents the first ML retrieval model for rocky, terrestrial exoplanets and the first synthetic data set of terrestrial spectra generated at this scale.
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