Whipple Mission Simulations – Detectability and Parameter Extraction
Abstract:The Whipple mission will conduct a blind occultation survey to detect small solar system bodies beyond the orbit of Neptune extending to thousands of AU. Flux from a distant star occulted by an intervening body varies over time periods of tenths to a few seconds, depending on the distance to the object and its size. Other parameters that characterize the observed light curve include the impact parameter, angular size and magnitude of the monitored star, sampling rate, and relative velocity of the observer and the occulting body. Using an idealized light curve generator based on these parameters, and a model for the Whipple instrument and spacecraft (including the telescope PSF, photon shot noise, readout noise, detector non-uniformity; spacecraft jitter and stray light), we generate random instances of an observation. A chi-squared test that matches pre-computed templates to the simulated observation is used to determine best fit size and distance estimates, keeping the known star angular size, magnitude, cadence and relative velocity parameters fixed.
For objects characteristic of the Kuiper Belt (35-50 AU distant), the size of small objects (1–3 km in radius) is determined to better than ~15%, while distances are determined ~30%. Both size and distance estimates are slightly biased, with sizes slightly smaller and distances generally larger than the ideal values. For objects characteristic of the outer Oort Cloud (> 3,000 AU), the size of 10-20 km objects is determined to better than ~25% and the distances are determined to better than about 50%, with biases similar to what we find for KBOs.
These preliminary results demonstrate that the Whipple mission can observe and characterize the population of small bodies with sufficient accuracy to permit classification as belonging to the Kuiper Belt or Oort Cloud (inner and outer), and with a sufficient number of detections, comparison to model predictions for the numbers of objects and their size distributions.