CRA Seminar

Abstract:

A number of ongoing surveys, such as Pan-STARRS, the Catalina Sky Survey, OSSOS, and NEOWISE, as well as planned surveys such as ZTF, LSST, and NEOCam, are designed to pursue goals ranging from constraining models of planet formation, through finding evidence of additional planets in our solar system, to fulfilling the US Congressional mandate to discover 90% of the potential hazardous asteroids with diameters exceeding 140m.

The typical asteroid search strategy is based on identifying `tracklets’, a sequence of two or more observations that are taken over a time span that is short enough that it is likely that the detections correspond to the same moving object, and a long enough to distinguish solar system objects from stationary background sources. A primary goal is to obtain enough tracklets for each object that the corresponding orbit is accurately determined. By design, most objects are naturally re-observed in the course of these surveys. However, which observations correspond to which object must still be identified before the orbits of those objects can be determined. This is known as the `linking problem.’

The best current solution to the linking problem, the Pan-STARRS Moving Object Processing System (MOPS), employs a sophisticated variation of the brute force approach, bringing groups of three tracklets together to be tested with orbit fitting. The computational load of MOPS scales as $\mathcal{O}(N_t^3)$, where $N_t$ is the number of tracklets.

We present a novel approach, heliocentric linking and clustering, that scales as $\mathcal{O}(N_t \log N_t)$. We use this approach to identify thousands of new objects within the Minor Planet Center’s “Isolated Tracklet File”. Finally, we discuss the implications of our results for ongoing and future surveys.