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| Paper: |
The Pan-STARRS Moving Object Pipeline |
| Volume: |
376, Astronomical Data Analysis Software and Systems XVI |
| Page: |
257 |
| Authors: |
Denneau,, L. Jr.; Kubica, J.; Jedicke, R. |
| Abstract: |
The Moving Object Processing System (MOPS) team of the University of Hawaii’s Pan-STARRS telescope is developing software to automatically discover and identify >90% of near-Earth objects (NEOs) larger than 300 m, and >80% of other classes of asteroids and comets. MOPS relies on new, efficient, multiple-hypothesis KD-tree and variable-tree search algorithms to search the ~ 1012 detection pairs that are expected per night. Candidate intra- and inter-night associations of detections are evaluated for consistency with a real solar system object, and orbits are computed. We describe the basic operation of the MOPS pipeline, identify pipeline processing steps that are candidates for multiple-hypothesis spatial searches, describe our implementation of those algorithms, and provide preliminary results for MOPS. |
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