Planetary surfaces

Abstract:

One of the long-term goals of exoplanet science is the atmospheric characterization of dozens of small exoplanets in order to understand their diversity and search for habitable worlds and potential biosignatures. Achieving this goal requires a space mission of sufficient scale. We seek to quantify the exoplanet detection performance of a space-based mid-infrared nulling interferometer that measures the thermal emission of exoplanets. For this, we have developed an instrument simulator that considers all major astrophysical noise sources and coupled it with Monte Carlo simulations of a synthetic exoplanet population around main-sequence stars within 20 pc. This allows us to quantify the number (and types) of exoplanets that our mission concept could detect over a certain time period. Two different scenarios to distribute the observing time among the stellar targets are discussed and different apertures sizes and wavelength ranges are considered. Within a 2.5-year initial search phase, an interferometer consisting of four 2 m apertures covering a wavelength range between 4 and 18.5 $\mu$m could detect up to ~550 exoplanets with radii between 0.5 and 6 R$_\oplus$ with an integrated SNR$\ge$7. At least ~160 of the detected exoplanets have radii $\le$1.5 R$_\oplus$. Depending on the observing scenario, ~25-45 rocky exoplanets (objects with radii between 0.5 and 1.5 $_{\oplus}$) orbiting within the empirical habitable zone (eHZ) of their host stars are among the detections. With four times 3.5 m aperture size, the total number of detections can increase to up to ~770, including ~60-80 rocky, eHZ planets. With four times 1 m aperture size, the maximum detection yield is ~315 exoplanets, including $\le$20 rocky, eHZ planets. In terms of predicted detection yield, such a mission can compete with large single-aperture reflected light missions. (abridged)

Abstract:

An accurate description of how visible light scatters from the lunar surface enables 1) constraints to be placed on the physical and compositional properties of the surface, using a photometric model such as the Hapke BRDF model, which has nine free parameters related to compositional and physical properties, and 2) more realistic scattering function inputs to be set within thermal models. Until a recent study by Foote et al. in 2010, lunar visible light scattering functions had been theoretically derived using limited laboratory measurements. Within thermal models, unrealistic scattering functions may be partly responsible for modelled temperature discrepancies of up to ~15-50 K (dependent on location)—when compared to remote sensing data from Diviner, onboard the Lunar Reconnaissance Orbiter—in regions such as polar craters, where light scattering due to surface topography dominates heat transfer. In this project, a laboratory goniometer setup was developed, which was used to measure a suite of visible light scattering functions for Apollo 11 (10084) and Apollo 16 (68810) lunar regolith samples across a wider range of viewing angles than has previously been measured. These samples were characterized in terms of their surface roughness and porosity profiles, and this enabled two of the free parameters within the Hapke BRDF model to be constrained. By fitting the model to the dataset, Hapke parameters could be deduced for the two representative (mare and highlands) regolith samples, and further constraints could be placed on the ‘practical’ size-scale of the model’s slope angle parameter. Thus, the dataset enabled Diviner’s visible-wavelength off-nadir data to be interpreted in a novel way, due to the reduction of free terms within the model. This led to surface roughness and compositional deductions (via the Hapke parameters h_s, b and θ ̅) for seven Diviner targets. Finally, the dataset was used to set more realistic scattering functions within the Oxford 3D Thermal Model, and it was demonstrated that this 1) could affect modelled high-latitude lunar surface temperature profiles by up to ~30 K—as compared to using previously assumed scattering functions—and 2) could increase the minimum depth at which water ice is predicted to be stable in the lunar subsurface by up to ~0.8 m. Hence, this dataset may help to constrain the possible distribution of water ice on the lunar surface, and this may be crucial for future lunar exploration missions such as Luna-27 and Artemis.