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Register a new userEigenspectra: A Framework for Identifying Spectra from 3D Eclipse Mapping
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Planetary atmospheres are inherently 3D objects that can have strong gradients in latitude, longitude, and altitude. Secondary eclipse mapping is a powerful way to map the 3D distribution of the atmosphere, but the data can have large correlations and errors in the presence of photon and instrument noise. We develop a technique to mitigate the large uncertainties of eclipse maps by identifying a small number of dominant spectra to make them more tractable for individual analysis via atmospheric retrieval. We use the eigencurves method to infer a multi-wavelength map of a planet from spectroscopic secondary eclipse light curves. We then apply a clustering algorithm to the planet map to identify several regions with similar emergent spectra. We combine the similar spectra together to construct an eigenspectrum for each distinct region on the planetary map. We demonstrate how this approach could be used to isolate hot from cold regions and/or regions with different chemical compositions in observations of hot Jupiters with the James Webb Space Telescope (JWST). We find that our method struggles to identify sharp edges in maps with sudden discontinuities, but generally can be used as a first step before a more physically motivated modeling approach to determine the primary features observed on the planet.
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Planetary rotation rates and obliquities provide information regarding the history of planet formation, but have not yet been measured for evolved extrasolar planets. Here we investigate the theoretical and observational perspective of the Rossiter-McLauglin effect during secondary eclipse (RMse) ingress and egress for transiting exoplanets. Near secondary eclipse, when the planet passes behind the parent star, the star sequentially obscures light from the approaching and receding parts of the rotating planetary surface. The temporal block of light emerging from the approaching (blue-shifted) or receding (red-shifted) parts of the planet causes a temporal distortion in the planets spectral line profiles resulting in an anomaly in the planets radial velocity curve. We demonstrate that the shape and the ratio of the ingress-to-egress radial velocity amplitudes depends on the planetary rotational rate, axial tilt and impact factor (i.e. sky-projected planet spin-orbital alignment). In addition, line asymmetries originating from different layers in the atmosphere of the planet could provide information regarding zonal atmospheric winds and constraints on the hot spot shape for giant irradiated exoplanets. The effect is expected to be most-pronounced at near-infrared wavelengths, where the planet-to-star contrasts are large. We create synthetic near-infrared, high-dispersion spectroscopic data and demonstrate how the sky-projected spin axis orientation and equatorial velocity of the planet can be estimated. We conclude that the RMse effect could be a powerful method to measure exoplanet spins.
We highlight a physical effect that is often not considered that impacts the calculation of model spectra of planets at secondary eclipse, affecting both emission and reflection spectra. The radius of the emitting surface of the planet is not merely one value measured from a transit light curve, but is itself a function of wavelength, yet it is not directly measurable. At high precision, a similar effect is well-known in transit transmission spectroscopy but this related effect also impacts emission and reflection. As is well-appreciated, the photospheric radius can vary across $sim$4-8 atmospheric scale heights, depending on atmospheric opacity and spectral resolution. This effect leads to a decreased weighting in model calculations at wavelengths where atmospheric opacity is low, and one sees more deeply into the atmosphere, to a smaller radius. The overall effect serves to mute emission spectra features for atmospheres with no thermal inversion but to enhance features for atmospheres with a thermal inversion. While this effect can be ignored for current emph{Hubble} observations, it can lead to wavelength-dependent 10-20% changes in planet-to-star flux ratios in the infrared at $Rsim~200-1000$ (readily achievable for JWST) for low-gravity hot Jupiters, although values of 5% are more typical for the population. The effect is mostly controlled by the ratio of the atmospheric scale height to the planet radius, and can be important at any planetary temperature. Of known planets, the effect is largest for the cool super-puffs at very low surface gravity, where it can alter calculated flux ratios by over 100%. We discuss complexities of including this photospheric radius effect in 1D and 3D atmosphere models.
Atmospheric retrievals of exoplanetary transmission spectra provide important constraints on various properties such as chemical abundances, cloud/haze properties, and characteristic temperatures, at the day-night atmospheric terminator. To date, most spectra have been observed for giant exoplanets due to which retrievals typically assume H-rich atmospheres. However, recent observations of mini-Neptunes/super-Earths, and the promise of upcoming facilities including JWST, call for a new generation of retrievals that can address a wide range of atmospheric compositions and related complexities. Here we report Aurora, a next-generation atmospheric retrieval framework that builds upon state-of-the-art architectures and incorporates the following key advancements: a) a generalised compositional retrieval allowing for H-rich and H-poor atmospheres, b) a generalised prescription for inhomogeneous clouds/hazes, c) multiple Bayesian inference algorithms for high-dimensional retrievals, d) modular considerations for refraction, forward scattering, and Mie-scattering, and e) noise modeling functionalities. We demonstrate Aurora on current and/or synthetic observations of hot Jupiter HD209458b, mini-Neptune K218b, and rocky exoplanet TRAPPIST1d. Using current HD209458b spectra, we demonstrate the robustness of our framework and cloud/haze prescription against assumptions of H-rich/H-poor atmospheres, improving on previous treatments. Using real and synthetic spectra of K218b, we demonstrate the agnostic approach to confidently constrain its bulk atmospheric composition and obtain precise abundance estimates. For TRAPPIST1d, 10 JWST NIRSpec transits can enable identification of the main atmospheric component for cloud-free CO$_2$-rich and N$_2$-rich atmospheres, and abundance constraints on trace gases including initial indications of O$_3$ if present at enhanced levels ($sim$10-100x Earth levels).
Simultaneous Localization and Mapping (SLAM) has been considered as a solved problem thanks to the progress made in the past few years. However, the great majority of LiDAR-based SLAM algorithms are designed for a specific type of payload and therefore dont generalize across different platforms. In practice, this drawback causes the development, deployment and maintenance of an algorithm difficult. Consequently, our work focuses on improving the compatibility across different sensing payloads. Specifically, we extend the Cartographer SLAM library to handle different types of LiDAR including fixed or rotating, 2D or 3D LiDARs. By replacing the localization module of Cartographer and maintaining the sparse pose graph (SPG), the proposed framework can create high-quality 3D maps in real-time on different sensing payloads. Additionally, it brings the benefit of simplicity with only a few parameters need to be adjusted for each sensor type.
The high-contrast imaging technique is meant to provide insight into those planets orbiting several astronomical units from their host star. Space missions such as WFIRST, HabEx, and LUVOIR will measure reflected light spectra of cold gaseous and rocky planets. To interpret these observations we introduce ExoReL$^Re$ (Exoplanetary Reflected Light Retrieval), a novel Bayesian retrieval framework to retrieve cloud properties and atmospheric structures from exoplanetary reflected light spectra. As a unique feature, it assumes a vertically non-uniform volume mixing ratio profile of water and ammonia, and use it to construct cloud densities. In this way, clouds and molecular mixture ratios are consistent. We apply ExoReL$^Re$ on three test cases: two exoplanets ($upsilon$ And e and 47 Uma b) and Jupiter. We show that we are able to retrieve the concentration of methane in the atmosphere, and estimate the position of clouds when the S/N of the spectrum is higher than 15, in line with previous works. Moreover, we described the ability of our model of giving a chemical identity to clouds, and we discussed whether or not we can observe this difference in the planetary reflection spectrum. Finally, we demonstrate how it could be possible to retrieve molecular concentrations (water and ammonia in this work) below the clouds by linking the non-uniform volume mixing ratio profile to the cloud presence. This will help to constrain the concentration of water and ammonia unseen in direct measurements.
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