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Title:
The Pan-STARRS Moving Object Pipeline
Authors:
Denneau, L., Jr.; Kubica, J.; Jedicke, R.
Publication:
Astronomical Data Analysis Software and Systems XVI ASP Conference Series, Vol. 376, proceedings of the conference held 15-18 October 2006 in Tucson, Arizona, USA. Edited by Richard A. Shaw, Frank Hill and David J. Bell., p.257
Publication Date:
10/2007
Origin:
ASP
Bibliographic Code:
2007ASPC..376..257D

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 ˜10^{12} 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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