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R. Jedicke, L. Denneau, T. Grav, J. Heasley (University of Hawaii), Jeremy Kubica (Carnegie Mellon University), Pan-STARRS Team
The Institute for Astronomy at the University of Hawaii is developing a large optical astronomical surveying system - the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS). The Moving Object Processing System (MOPS) client of the Pan-STARRS image processing pipeline is developing software to automatically discover and identify >90% of near-Earth objects (NEOs) 300m in diameter and >80% of other classes of asteroids and comets. In developing its software, MOPS has created a synthetic solar system model (SSM) with over 10 million objects whose distributions of orbital characteristics matches those expected for objects that Pan-STARRS will observe. MOPS verifies its correct operation by simulating the survey and subsequent discovery of synthetically generated objects. MOPS also employs novel techniques in handling the computationally difficult problem of linking large numbers of unknown asteroids in a field of detections.
We will describe the creation and verification of the Pan-STARRS MOPS SSM, demonstrate synthetic detections and observations by the MOPS, describe the MOPS asteroid linking techniques, describe accuracy and throughput of the entire MOPS system, and provide predictions regarding the numbers and kinds of objects, including as yet undiscovered "extreme objects", that the MOPS expects to find over its 10-year lifetime.
Pan-STARRS is funded under a grant from the U.S. Air Force.
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The author(s) of this abstract have provided an email address for comments about the abstract: jedicke@ifa.hawaii.edu
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Bulletin of the American Astronomical Society, 37 #4
© 2005. The American Astronomical Soceity.