No Arabic abstract
As the 3D spatial properties of exoplanet atmospheres are being observed in increasing detail by current and new generations of telescopes, the modelling of the 3D scattering effects of cloud forming atmospheres with inhomogeneous opacity structures becomes increasingly important to interpret observational data. We model the scattering and emission properties of a simulated cloud forming, inhomogeneous opacity, hot Jupiter atmosphere of HD 189733b. We compare our results to available HST and Spitzer data and quantify the effects of 3D multiple-scattering on observable properties of the atmosphere. We discuss potential observational properties of HD 189733b for the upcoming TESS and CHEOPS missions. We develop a Monte Carlo radiative transfer code and apply it to post-process output of our 3D radiative-hydrodynamic, cloud formation simulation of HD 189733b. We employ three variance reduction techniques; next event estimation, survival biasing and composite emission biasing to improve signal-to-noise of the output.For cloud particle scattering events, a log-normal area distribution is constructed from the 3D cloud formation RHD results and stochastically sampled in order to model the Rayleigh and Mie scattering behaviour of a mixture of grain sizes. Stellar photon packets incident on the eastern dayside hemisphere show predominantly Rayleigh, single-scattering behaviour, while multiple-scattering occurs on the western hemisphere. Combined scattered and thermal emitted light predictions are consistent with published HST and Spitzer secondary transit observations. Our model predictions are also consistent with geometric albedo constraints from optical wavelength ground based polarimetry and HST B-band measurements. We predict an apparent geometric albedo for HD 189733b of 0.205 and 0.229, in the TESS and CHEOPS photometric bands respectively.
High-resolution spectroscopy (R $ge$ 20,000) at near-infrared wavelengths can be used to investigate the composition, structure, and circulation patterns of exoplanet atmospheres. However, up to now it has been the exclusive dominion of the biggest telescope facilities on the ground, due to the large amount of photons necessary to measure a signal in high-dispersion spectra. Here we show that spectrographs with a novel design - in particular a large spectral range - can open exoplanet characterisation to smaller telescope facilities too. We aim to demonstrate the concept on a series of spectra of the exoplanet HD 189733 b taken at the Telescopio Nazionale Galileo with the near-infrared spectrograph GIANO during two transits of the planet. In contrast to absorption in the Earths atmosphere (telluric absorption), the planet transmission spectrum shifts in radial velocity during transit due to the changing orbital motion of the planet. This allows us to remove the telluric spectrum while preserving the signal of the exoplanet. The latter is then extracted by cross-correlating the residual spectra with template models of the planet atmosphere computed through line-by-line radiative transfer calculations, and containing molecular absorption lines from water and methane. By combining the signal of many thousands of planet molecular lines, we confirm the presence of water vapour in the atmosphere of HD 189733 b at the 5.5-$sigma$ level. This signal was measured only in the first of the two observing nights. By injecting and retrieving artificial signals, we show that the non-detection on the second night is likely due to an inferior quality of the data. The measured strength of the planet transmission spectrum is fully consistent with past CRIRES observations at the VLT, excluding a strong variability in the depth of molecular absorption lines.
The theory and numerical modelling of radiation processes and radiative transfer play a key role in astrophysics: they provide the link between the physical properties of an object and the radiation it emits. In the modern era of increasingly high-quality observational data and sophisticated physical theories, development and exploitation of a variety of approaches to the modelling of radiative transfer is needed. In this article, we focus on one remarkably versatile approach: Monte Carlo Radiative Transfer (MCRT). We describe the principles behind this approach, and highlight the relative ease with which they can (and have) been implemented for application to a range of astrophysical problems. All MCRT methods have in common a need to consider the adverse consequences of Monte Carlo noise in simulation results. We overview a range of methods used to suppress this noise and comment on their relative merits for a variety of applications. We conclude with a brief review of specific applications for which MCRT methods are currently popular and comment on the prospects for future developments.
Current observational data of exoplanets are providing increasing detail of their 3D atmospheric structures. As characterisation efforts expand in scope, the need to develop consistent 3D radiative-transfer methods becomes more pertinent as the complex atmospheric properties of exoplanets are required to be modelled together consistently. We aim to compare the transmission and emission spectra results of a 3D Monte Carlo Radiative Transfer (MCRT) model to contemporary radiative-transfer suites. We perform several benchmarking tests of a MCRT code, Cloudy Monte Carlo Radiative Transfer (CMCRT), to transmission and emission spectra model output. We add flexibility to the model through the use of k-distribution tables as input opacities. We present a hybrid MCRT and ray tracing methodology for the calculation of transmission spectra with a multiple scattering component. CMCRT compares well to the transmission spectra benchmarks at the 10s of ppm level. Emission spectra benchmarks are consistent to within 10% of the 1D models. We suggest that differences in the benchmark results are likely caused by geometric effects between plane-parallel and spherical models. In a practical application, we post-process a cloudy 3DHD 189733b GCM model and compare to available observational data. Our results suggest the core methodology and algorithms of CMCRT produce consistent results to contemporary radiative transfer suites. 3D MCRT methods are highly suitable for detailed post-processing of cloudy and non-cloudy 1D and 3D exoplanet atmosphere simulations in instances where atmospheric inhomogeneities, significant limb effects/geometry or multiple scattering components are important considerations.
Clouds and hazes are commonplace in the atmospheres of solar system planets and are likely ubiquitous in the atmospheres of extrasolar planets as well. Clouds affect every aspect of a planetary atmosphere, from the transport of radiation, to atmospheric chemistry, to dynamics and they influence - if not control - aspects such as surface temperature and habitability. In this review we aim to provide an introduction to the role and properties of clouds in exoplanetary atmospheres. We consider the role clouds play in influencing the spectra of planets as well as their habitability and detectability. We briefly summarize how clouds are treated in terrestrial climate models and consider the far simpler approaches that have been taken so far to model exoplanet clouds, the evidence for which we also review. Since clouds play a major role in the atmospheres of certain classes of brown dwarfs we briefly discuss brown dwarf cloud modeling as well. We also review how the scattering and extinction efficiencies of cloud particles may be approximated in certain limiting cases of small and large particles in order to facilitate physical understanding. Since clouds play such important roles in planetary atmospheres, cloud modeling may well prove to be the limiting factor in our ability to interpret future observations of extrasolar planets.
Multi-wavelength transit and secondary-eclipse light-curve observations are some of the most powerful techniques to probe the thermo-chemical properties of exoplanets. Although the large planet-to-star brightness contrast and few available spectral bands produce data with low signal-to-noise ratios, a Bayesian approach can robustly reveal what constraints we can set, without over-interpreting the data. Here I performed an end-to-end analysis of transiting exoplanet data. I analyzed space-telescope data for three planets to characterize their atmospheres and refine their orbits, investigated correlated noise estimators, and contributed to the development of the respective data-analysis pipelines. Chapters 2 and 3 describe the Photometry for Orbits, Eclipses and Transits (POET) pipeline to model Spitzer Space Telescope light curves, applied to secondary-eclipse observations of the Jupiter-sized planets WASP-8b and TrES-1. Chapter 4 studies commonly used correlated-noise estimators for exoplanet light-curve modeling, time averaging, residual permutations, and wavelet likelihood, and assesses their applicability and limitations to estimate parameters uncertainties. Chapter 5 describes the open-source Bayesian Atmospheric Radiative Transfer (BART) code to characterize exoplanet atmospheres. BART combines a thermochemical-equilibrium code, a one-dimensional line-by-line radiative-transfer code, and the Multi-core Markov-chain Monte Carlo statistical module to constrains the atmospheric temperature and chemical-abundance profiles of exoplanets. I applied the BART code to the Hubble and Spitzer Space Telescope transit observations of the Neptune-sized planet HAT-P-11b. BART finds an atmosphere enhanced in heavy elements, constraining the water abundance to ~100 times that of the solar abundance.