Rotational Light-curve Recovery and Predictions of the LSST Yield of Hildas

Abstract The Hilda population occupies the stable 3:2 mean-motion resonance of Jupiter and provides a window into solar system evolution, including collisional processes. The National Science Foundation and Department of Energy Vera C. Rubin Observatory will conduct the 10 yr Legacy Survey of Space and Time (LSST). We present a simulation of Rubin’s discovery of Hildas with the Sorcha survey simulator and the recovery of their light curves. We constructed a synthetic Hilda population model that includes distributions of orbital properties, sizes, collisional families, and colors. We applied three distinct populations of sinusoidal light curves to this same orbit–size–color model: (1) a Gaussian kernel density estimate fit to rotational periods and amplitudes from the Lightcurve Database (LCDB), (2) a superfast rotator population, and (3) a superslow rotator population. Over the 10 yr simulated survey, we predict LSST will discover ∼33,400 Hildas, a fivefold increase over the known population. Using a multiband Lomb–Scargle Periodogram via Astropy we confidently recover ∼45.96% of Hildas in our LCDB-based population, higher than typical in observational searches. This suggests our light-curve population model may differ from the intrinsic population. We find strong biases in light-curve amplitude, with recovery efficiency dropping sharply below 0.1 magnitudes, while biases from rotational period are comparatively weak aside from cadence-related features such as LSST’s ∼36 minute revisit cadence. Our recovery efficiency is likely overestimated due to our assumption of constant sinusoidal light curves, which correspond to optimal pole orientations. These results are the first test of light-curve recovery from simulated LSST observations.