The Pan-STARRS moving object pipeline

被引：0
|
作者：
Denneau, Larry, Jr. [1 ]
Kubica, Jeremy [2 ]
Jedicke, Robert [1 ]
机构：
[1] Univ Hawaii, Inst Astron, 2680 Woodlawn Dr, Honolulu, HI 96822 USA
[2] Google Inc, Pittsburgh, PA USA
来源：
ASTRONOMICAL DATA ANALYSIS SOFTWARE AND SYSTEMS XVI | 2007年 / 376卷
基金：
美国国家科学基金会;
关键词：
D O I：
暂无
中图分类号：
P1 [天文学];
学科分类号：
0704 ;
摘要：
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 similar to 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.
引用
收藏
页码：257 / +
页数：2
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