Patterns in Skewness from Monte Carlo Simulations of Stellar Occultations of Saturn’s Rings

The Ultraviolet Imaging Spectrograph High-Speed Photometer (UVIS HSP) aboard the Cassini spacecraft gathered stellar occultation data from stars as they were occulted by Saturn’s rings over a range of viewing geometries. In an effort to better understand the nature of Saturn’s Rings, we created a model of a simplified representation of a ring segment. The model assumes spherical particles, and a top-down viewing geometry of the ring plane. We perform numerous Monte Carlo simulations to mimic stellar occultations of the rings, while changing different variables, such as the particle radius (R), ring optical depth (tau), and the star brightness (I0). We introduce features such as small gaps, or ‘ghosts’, and clumps into our simulations to represent similar features detected in the ring system. Ghost and clump sizes range from one to several times the size of an individual integration area which is typically a few hundred square meters in the UVIS occultations. We calculate the skewness (S) of the simulated occultation light curves. We find that skewness as a function of optical depth increases with both increasing R and I0. When ghosts are introduced, S(tau) increases dramatically when the fraction of ghosts is very small, then steadily decreases as we increase the amount of ghosts. Similarly, when clumps are introduced, S(tau) decreases by a large amount when the fraction of clumps is very small, then continues to increase as the number of clumps in the simulation increases. Skewness is a sensitive metric to identify rare outliers in occultation data. We also find that skewness peaks when the scale of the ghost matches the resolution of the data. Thus, analysis of skewness of data with different resolutions and binned by different amounts can be used to probe the size distribution of ghosts.