اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدExoplanet atmospheres with EChO: spectral retrievals using EChOSim
105
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
We demonstrate the effectiveness of the Exoplanet Characterisation Observatory mission concept for constraining the atmospheric properties of hot and warm gas giants and super Earths. Synthetic primary and secondary transit spectra for a range of planets are passed through EChOSim (Waldmann & Pascale 2014) to obtain the expected level of noise for different observational scenarios; these are then used as inputs for the NEMESIS atmospheric retrieval code and the retrieved atmospheric properties (temperature structure, composition and cloud properties) compared with the known input values, following the method of Barstow et al. (2013a). To correctly retrieve the temperature structure and composition of the atmosphere to within 2 {sigma}, we find that we require: a single transit or eclipse of a hot Jupiter orbiting a sun-like (G2) star at 35 pc to constrain the terminator and dayside atmospheres; 20 transits or eclipses of a warm Jupiter orbiting a similar star; 10 transits/eclipses of a hot Neptune orbiting an M dwarf at 6 pc; and 30 transits or eclipses of a GJ1214b-like planet.
قيم البحث
اقرأ أيضاً
A dedicated mission to investigate exoplanetary atmospheres represents a major milestone in our quest to understand our place in the universe by placing our Solar System in context and by addressing the suitability of planets for the presence of life
. EChO -the Exoplanet Characterisation Observatory- is a mission concept specifically geared for this purpose. EChO will provide simultaneous, multi-wavelength spectroscopic observations on a stable platform that will allow very long exposures. EChO will build on observations by Hubble, Spitzer and groundbased telescopes, which discovered the first molecules and atoms in exoplanetary atmospheres. EChO will simultaneously observe a broad enough spectral region -from the visible to the mid-IR- to constrain from one single spectrum the temperature structure of the atmosphere and the abundances of the major molecular species. The spectral range and resolution are tailored to separate bands belonging to up to 30 molecules to retrieve the composition and temperature structure of planetary atmospheres. The target list for EChO includes planets ranging from Jupiter-sized with equilibrium temperatures Teq up to 2000 K, to those of a few Earth masses, with Teq ~300 K. We have baselined a dispersive spectrograph design covering continuously the 0.4-16 micron spectral range in 6 channels (1 in the VIS, 5 in the IR), which allows the spectral resolution to be adapted from several tens to several hundreds, depending on the target brightness. The instrument will be mounted behind a 1.5 m class telescope, passively cooled to 50 K, with the instrument structure and optics passively cooled to ~45 K. EChO will be placed in a grand halo orbit around L2. We have also undertaken a first-order cost and development plan analysis and find that EChO is easily compatible with the ESA M-class mission framework.
Future space-based direct imaging missions will perform low-resolution (R$<$100) optical (0.3-1~$mu$m) spectroscopy of planets, thus enabling reflected spectroscopy of cool giants. Reflected light spectroscopy is encoded with rich information about t
he scattering and absorbing properties of planet atmospheres. Given the diversity of clouds and hazes expected in exoplanets, it is imperative we solidify the methodology to accurately and precisely retrieve these scattering and absorbing properties that are agnostic to cloud species. In particular, we focus on determining how different cloud parameterizations affect resultant inferences of both cloud and atmospheric composition. We simulate mock observations of the reflected spectra from three top priority direct imaging cool giant targets with different effective temperatures, ranging from 135 K to 533 K. We perform retrievals of cloud structure and molecular abundances on these three planets using four different parameterizations, each with increasing levels of cloud complexity. We find that the retrieved atmospheric and scattering properties strongly depend on the choice of cloud parameterization. For example, parameterizations that are too simplistic tend to overestimate the abundances. Overall, we are unable to retrieve precise/accurate gravity beyond $pm$50%. Lastly, we find that even low SNR=5, low R=40 reflected light spectroscopy gives cursory zeroth order insights into cloud deck position relative to molecular and Rayleigh optical depth level.
Deep learning algorithms are growing in popularity in the field of exoplanetary science due to their ability to model highly non-linear relations and solve interesting problems in a data-driven manner. Several works have attempted to perform fast ret
rievals of atmospheric parameters with the use of machine learning algorithms like deep neural networks (DNNs). Yet, despite their high predictive power, DNNs are also infamous for being black boxes. It is their apparent lack of explainability that makes the astrophysics community reluctant to adopt them. What are their predictions based on? How confident should we be in them? When are they wrong and how wrong can they be? In this work, we present a number of general evaluation methodologies that can be applied to any trained model and answer questions like these. In particular, we train three different popular DNN architectures to retrieve atmospheric parameters from exoplanet spectra and show that all three achieve good predictive performance. We then present an extensive analysis of the predictions of DNNs, which can inform us - among other things - of the credibility limits for atmospheric parameters for a given instrument and model. Finally, we perform a perturbation-based sensitivity analysis to identify to which features of the spectrum the outcome of the retrieval is most sensitive. We conclude that for different molecules, the wavelength ranges to which the DNNs predictions are most sensitive, indeed coincide with their characteristic absorption regions. The methodologies presented in this work help to improve the evaluation of DNNs and to grant interpretability to their predictions.
We present a publicly available library of model atmospheres with radiative-convective equilibrium Pressure-Temperature ($P$-$T$) profiles fully consistent with equilibrium chemical abundances, and the corresponding emission and transmission spectrum
with R$sim$5000 at 0.2 $mu$m decreasing to R$sim$35 at 30 $mu$m, for 89 hot Jupiter exoplanets, for four re-circulation factors, six metallicities and six C/O ratios. We find the choice of condensation process (local/rainout) alters the $P$-$T$ profile and thereby the spectrum substantially, potentially detectable by JWST. We find H$^-$ opacity can contribute to form a strong temperature inversion in ultra-hot Jupiters for C/O ratios $geq$ 1 and can make transmission spectra features flat in the optical, alongside altering the entire emission spectra. We highlight how adopting different model choices such as thermal ionisation, opacities, line-wing profiles and the methodology of varying the C/O ratio, effects the $P$-$T$ structure and the spectrum. We show the role of Fe opacity to form primary/secondary inversion in the atmosphere. We use WASP-17b and WASP-121b as test cases to demonstrate the effect of grid parameters across their full range, while highlighting some important findings, concerning the overall atmospheric structure, chemical transition regimes and their observables. Finally, we apply this library to the current transmission and emission spectra observations of WASP-121b, which shows H$_2$O and tentative evidence for VO at the limb, and H$_2$O emission feature indicative of inversion on the dayside, with very low energy redistribution, thereby demonstrating the applicability of library for planning and interpreting observations of transmission and emission spectrum.
New observing capabilities coming online over the next few years will provide opportunities for characterization of exoplanet atmospheres. However, clouds/hazes could be present in the atmospheres of many exoplanets, muting the amplitude of spectral
features. We use laboratory simulations to explore photochemical haze formation in H2-rich exoplanet atmospheres at 800 K with metallicity either 100 and 1000 times solar. We find that haze particles are produced in both simulated atmospheres with small particle size (20 to 140 nm) and relative low production rate (2.4 x 10-5 to 9.7 x 10-5 mg cm-3 h-1), but the particle size and production rate is dependent on the initial gas mixtures and the energy sources used in the simulation experiments. The gas phase mass spectra show that complex chemical processes happen in these atmospheres and generate new gas products that can further react to form larger molecules and solid haze particles. Two H2-rich atmospheres with similar C/O ratios (~0.5) yield different haze particles size, haze production rate, and gas products, suggesting both the elemental abundances and their bonding environments in an atmosphere can significantly affect the photochemistry. There is no methane (CH4) in our initial gas mixtures, although CH4 is often believed to be required to generate organic hazes. However, haze production rates from our experiments with different initial gas mixtures indicate that CH4 is neither required to generate organic hazes nor necessary to promote the organic haze formation. The variety and relative yield of the gas products indicate that CO and N2 enrich chemical reactions in H2-rich atmospheres.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
