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تسجيل مستخدم جديدMulti-orbital-phase and multi-band characterization of exoplanetary atmospheres with reflected light spectra
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Direct imaging of widely separated exoplanets from space will obtain their reflected light spectra and measure atmospheric properties. Previous calculations have shown that a change in the orbital phase would cause a spectral signal, but whether this signal may be used to characterize the atmosphere has not been shown. We simulate starshade-enabled observations of the planet 47 Uma b, using the to-date most realistic simulator SISTER to estimate the uncertainties due to residual starlight, solar glint, and exozodiacal light. We then use the Bayesian retrieval algorithm ExoReL$^Re$ to determine the constraints on the atmospheric properties from observations using a Roman- or HabEx-like telescope, comparing the strategies to observe at multiple orbital phases or in multiple wavelength bands. With a $sim20%$ bandwidth in 600 - 800 nm on a Roman-like telescope, the retrieval finds a degenerate scenario with a lower gas abundance and a deeper or absent cloud than the truth. Repeating the observation at a different orbital phase or at a second $20%$ wavelength band in 800 - 1000 nm, with the same integration time and thus degraded S/N, would effectively eliminate this degenerate solution. Single observation with a HabEx-like telescope would yield high-precision constraints on the gas abundances and cloud properties, without the degenerate scenario. These results are also generally applicable to high-contrast spectroscopy with a coronagraph with a similar wavelength coverage and S/N, and can help design the wavelength bandwidth and the observation plan of exoplanet direct imaging experiments in the future.
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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 roc
ky 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.
Recent work has shown that sulfur hazes may arise in the atmospheres of some giant exoplanets due to the photolysis of H$_{2}$S. We investigate the impact such a haze would have on an exoplanets geometric albedo spectrum and how it may affect the dir
ect imaging results of WFIRST, a planned NASA space telescope. For temperate (250 K $<$ T$_{rm eq}$ $<$ 700 K) Jupiter--mass planets, photochemical destruction of H$_{2}$S results in the production of $sim$1 ppmv of seight between 100 and 0.1 mbar, which, if cool enough, will condense to form a haze. Nominal haze masses are found to drastically alter a planets geometric albedo spectrum: whereas a clear atmosphere is dark at wavelengths between 0.5 and 1 $mu$m due to molecular absorption, the addition of a sulfur haze boosts the albedo there to $sim$0.7 due to scattering. Strong absorption by the haze shortward of 0.4 $mu$m results in albedos $<$0.1, in contrast to the high albedos produced by Rayleigh scattering in a clear atmosphere. As a result, the color of the planet shifts from blue to orange. The existence of a sulfur haze masks the molecular signatures of methane and water, thereby complicating the characterization of atmospheric composition. Detection of such a haze by WFIRST is possible, though discriminating between a sulfur haze and any other highly reflective, high altitude scatterer will require observations shortward of 0.4 $mu$m, which is currently beyond WFIRSTs design.
We derive efficient, closed form, differentiable, and numerically stable solutions for the flux measured from a spherical planet or moon seen in reflected light, either in or out of occultation. Our expressions apply to the computation of scattered l
ight phase curves of exoplanets, secondary eclipse light curves in the optical, or future measurements of planet-moon and planet-planet occultations, as well as to photometry of solar system bodies. We derive our solutions for Lambertian bodies illuminated by a point source, but extend them to model illumination sources of finite angular size and rough surfaces with phase-dependent scattering. Our algorithm is implemented in Python within the open-source starry mapping framework and is designed with efficient gradient-based inference in mind. The algorithm is 4-5 orders of magnitude faster than direct numerical evaluation methods and about 10 orders of magnitude more precise. We show how the techniques developed here may one day lead to the construction of two-dimensional maps of terrestrial planet surfaces, potentially enabling the detection of continents and oceans on exoplanets in the habitable zone.
Computing and using opacities is a key part of modeling and interpreting data of exoplanetary atmospheres. Since the underlying spectroscopic line lists are constantly expanding and currently include up to ~ 10^10 - 10^11 transition lines, the opacit
y calculator codes need to become more powerful. Here we present major upgrades to the HELIOS-K GPU-accelerated opacity calculator and describe the necessary steps to process large line lists within a reasonable amount of time. Besides performance improvements, we include more capabilities and present a toolbox for handling different atomic and molecular data sets: from downloading and pre-processing the data to performing the opacity calculations in a user-friendly way. HELIOS-K supports line lists from ExoMol, HITRAN, HITEMP, NIST, Kurucz and VALD3. By matching the resolution of 0.1 cm^-1 and cutting length of 25 cm^-1 used by the ExoCross code for timing performance (251 seconds excluding data read-in time), HELIOS-K can process the ExoMol BT2 water line list in 12.5 seconds. Using a resolution of 0.01 cm^-1, it takes 45 seconds - equivalent to about 10^7 lines per second. As a wavenumber resolution of 0.01 cm^-1 suffices for most exoplanetary atmosphere spectroscopic calculations, we adopt this resolution in calculating opacity functions for several hundred atomic and molecular species, and make them freely available on the open-access DACE database. For the opacity calculations of the database, we use a cutting length of 100 cm^-1 for molecules and no cutting length for atoms. Our opacities are available for downloading from https://dace.unige.ch/opacityDatabase and may be visualized using https://dace.unige.ch/opacity.
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Christiane Helling (Centre for Exoplanet Science
, University of Stn Andrews
, St Andrews
2020
Today, we know ~4330 exoplanets orbiting their host stars in ~3200 planetary systems. The diversity of these exoplanets is large, and none of the known exoplanets is a twin to any of the solar system planets, nor is any of the known extrasolar planet
ary systems a twin of the solar system. Such diversity on many scales and structural levels requires fundamental theoretical approaches. Large efforts are underway to develop individual aspects of exoplanet sciences, like exoplanet atmospheres, cloud formation, disk chemistry, planet system dynamics, mantle convection, mass loss of planetary atmospheres. The following challenges need to be addressed in tandem with observational efforts. They provide the opportunity to progress our understanding of exoplanets and their atmospheres by exploring our models as virtual laboratories to fill gaps in observational data from different instruments and missions, and taken at different instances of times: Challenge a) Building complex models based on theoretical rigour that aim to understand the interactions of atmospheric processes, to treat cloud formation and its feedback onto the gas-phase chemistry and the energy budget of the planetary atmosphere moving away from solar-system inspired parameterisations. Challenge b) Enabling cloud modelling based on fundamental physio-chemical insights in order to be applicable to the large and unexplored chemical, radiative and thermodynamical parameter range of exoplanets in the universe. Challenge b) will be explored in this chapter of the book ExoFrontiers.
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