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Register a new userToward the Analysis of JWST Exoplanet Spectra: the effective temperature in the context of direct imaging
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The current sparse wavelength range coverage of exoplanet direct imaging observations, and the fact that models are defined using a finite wavelength range, lead both to uncertainties on effective temperature determination.We study these effects using black-bodies and atmospheric models and we detail how to infer this parameter. Through highlighting the key wavelength coverage that allows for a more accurate representation of the effective temperature, our analysis can be used to mitigate or manage extra uncertainties being added in the analysis from the models. We find that the wavelength range coverage will soon no longer be a problem. An effective temperature computed by integrating the spectroscopic observations of the James Webb Space Telescope (JWST) will give uncertainties similar to, or better than, the current state-of-the-art, which is to fit models to data. Accurately calculating the effective temperature will help to improve current modelling approaches. Obtaining an independent and precise estimation of this crucial parameter will help the benchmarking process to identify the best practice to model exoplanet atmospheres.
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Given the forthcoming launch of the James Webb Space Telescope (JWST) which will allow observ- ing exoplanet atmospheres with unprecedented signal-over-noise ratio, spectral coverage and spatial resolution, the uncertainties in the atmosphere modelling used to interpret the data need to be as- sessed. As the first step, we compare three independent 1D radiative-convective models: ATMO, Exo-REM and petitCODE. We identify differences in physical and chemical processes taken into ac- count thanks to a benchmark protocol we developed. We study the impact of these differences on the analysis of observable spectra. We show the importance of selecting carefully relevant molecular linelists to compute the atmospheric opacity. Indeed, differences between spectra calculated with Hitran and ExoMol exceed the expected uncertainties of future JWST observations. We also show the limitation in the precision of the models due to uncertainties on alkali and molecule lineshape, which induce spectral effects also larger than the expected JWST uncertainties. We compare two chemical models, Exo-REM and Venot Chemical Code, which do not lead to significant differences in the emission or transmission spectra. We discuss the observational consequences of using equilibrium or out-of- equilibrium chemistry and the major impact of phosphine, detectable with the JWST.Each of the models has benefited from the benchmarking activity and has been updated. The protocol developed in this paper and the online results can constitute a test case for other models.
This whitepaper discusses the diversity of exoplanets that could be detected by future observations, so that comparative exoplanetology can be performed in the upcoming era of large space-based flagship missions. The primary focus will be on characterizing Earth-like worlds around Sun-like stars. However, we will also be able to characterize companion planets in the system simultaneously. This will not only provide a contextual picture with regards to our Solar system, but also presents a unique opportunity to observe size dependent planetary atmospheres at different orbital distances. We propose a preliminary scheme based on chemical behavior of gases and condensates in a planets atmosphere that classifies them with respect to planetary radius and incident stellar flux.
Further advances in exoplanet detection and characterisation require sampling a diverse population of extrasolar planets. One technique to detect these distant worlds is through the direct detection of their thermal emission. The so-called direct imaging technique, is suitable for observing young planets far from their star. These are very low signal-to-noise-ratio (SNR) measurements and limited ground truth hinders the use of supervised learning approaches. In this paper, we combine deep generative and discriminative models to bypass the issues arising when directly training on real data. We use a Generative Adversarial Network to obtain a suitable dataset for training Convolutional Neural Network classifiers to detect and locate planets across a wide range of SNRs. Tested on artificial data, our detectors exhibit good predictive performance and robustness across SNRs. To demonstrate the limits of the detectors, we provide maps of the precision and recall of the model per pixel of the input image. On real data, the models can re-confirm bright source detections.
We present results of deep direct imaging of the radial velocity (RV) planet-host star 14 Her (=GJ 614, HD 145675), obtained in the lprime ~band with the Clio-2 camera and the MMT adaptive optics system. This star has one confirmed planet and an unconfirmed outer companion, suggested by residuals in the RV data. The orbital parameters of the unconfirmed object are not well constrained since many mass/semimajor axis configurations can fit the available data. The star has been directly imaged several times, but none of the campaigns has ruled out sub-stellar companions. With about 2.5 hrs of integration, we rule out at 5$sigma$ confidence $gtrsim$ 18 mj ~companions beyond about 25 AU, based on the cite{baraffe} COND mass-luminosity models. Combining our detection limits with fits to the RV data and analytic dynamical analysis, we constrain the orbital parameters of 14 Her c to be: $3 lesssim m/$mj ~$lesssim 42$, $7 lesssim a/$AU $lesssim 25$, and $e lesssim 0.5$. A wealth of information can be obtained from RV/direct imaging overlap, especially with deep imaging as this work shows. The collaboration between RV and direct imaging will become more important in the coming years as the phase space probed by each technique converges. Future studies involving RV/imaging overlap should be sure to consider the effects of a potential planets projected separation, as quoting limits assuming face-on orientation will be misleading.
In the last decade, about a dozen giant exoplanets have been directly imaged in the IR as companions to young stars. With photometry and spectroscopy of these planets in hand from new extreme coronagraphic instruments such as SPHERE at VLT and GPI at Gemini, we are beginning to characterize and classify the atmospheres of these objects. Initially, it was assumed that young planets would be similar to field brown dwarfs, more massive objects that nonetheless share similar effective temperatures and compositions. Surprisingly, young planets appear considerably redder than field brown dwarfs, likely a result of their low surface gravities and indicating much different atmospheric structures. Preliminarily, young free-floating planets appear to be as or more variable than field brown dwarfs, due to rotational modulation of inhomogeneous surface features. Eventually, such inhomogeneity will allow the top of atmosphere structure of these objects to be mapped via Doppler imaging on extremely large telescopes. Direct imaging spectroscopy of giant exoplanets now is a prelude for the study of habitable zone planets. Eventual direct imaging spectroscopy of a large sample of habitable zone planets with future telescopes such as LUVOIR will be necessary to identify multiple biosignatures and establish habitability for Earth-mass exoplanets in the habitable zones of nearby stars.
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