Larry Denneau, Robert Jedicke, Tommy Grav, Mikael Granvik, Jeremy Kubica, Andrea Milani, Peter Veres, Richard Wainscoat, Daniel Chang, Francesco Pierfederici, N. Kaiser, K. C. Chambers, J. N. Heasley, Eugene. A. Magnier, P. A. Price, Jonathan Myers, Jan Kleyna, Henry Hsieh, Davide Farnocchia, Chris Waters, W. H. Sweeney, Denver Green, Bryce Bolin, W. S. Burgett, J. S. Morgan, John L. Tonry, K. W. Hodapp, Serge Chastel, Steve Chesley, Alan Fitzsimmons, Matthew Holman, Tim Spahr, David Tholen, Gareth V. Williams, Shinsuke Abe, J. D. Armstrong, Terry H. Bressi, Robert Holmes, Tim Lister, Robert S. McMillan, Marco Micheli, Eileen V. Ryan, William H. Ryan, James V. Scotti
We describe the Pan-STARRS Moving Object Processing System (MOPS), a modern software package that produces automatic asteroid discoveries and identifications from catalogs of transient detections from next-generation astronomical survey telescopes. MOPS achieves > 99.5% efficiency in producing orbits from a synthetic but realistic population of asteroids whose measurements were simulated for a Pan-STARRS4-class telescope. Additionally, using a non-physical grid population, we demonstrate that MOPS can detect populations of currently unknown objects such as interstellar asteroids. MOPS has been adapted successfully to the prototype Pan-STARRS1 telescope despite differences in expected false detection rates, fill-factor loss and relatively sparse observing cadence compared to a hypothetical Pan-STARRS4 telescope and survey. MOPS remains >99.5% efficient at detecting objects on a single night but drops to 80% efficiency at producing orbits for objects detected on multiple nights. This loss is primarily due to configurable MOPS processing limits that are not yet tuned for the Pan-STARRS1 mission. The core MOPS software package is the product of more than 15 person-years of software development and incorporates countless additional years of effort in third-party software to perform lower-level functions such as spatial searching or orbit determination. We describe the high-level design of MOPS and essential subcomponents, the suitability of MOPS for other survey programs, and suggest a road map for future MOPS development.
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http://arxiv.org/abs/1302.7281
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