The Pan-STARRS Moving Object Processing System

Abstract

We describe the Pan-STARRS Moving Object Processing System (MOPS), a modern\nsoftware package that produces automatic asteroid discoveries and\nidentifications from catalogs of transient detections from next-generation\nastronomical survey telescopes. MOPS achieves > 99.5% efficiency in producing\norbits from a synthetic but realistic population of asteroids whose\nmeasurements were simulated for a Pan-STARRS4-class telescope. Additionally,\nusing a non-physical grid population, we demonstrate that MOPS can detect\npopulations of currently unknown objects such as interstellar asteroids.\n MOPS has been adapted successfully to the prototype Pan-STARRS1 telescope\ndespite differences in expected false detection rates, fill-factor loss and\nrelatively sparse observing cadence compared to a hypothetical Pan-STARRS4\ntelescope and survey. MOPS remains >99.5% efficient at detecting objects on a\nsingle night but drops to 80% efficiency at producing orbits for objects\ndetected on multiple nights. This loss is primarily due to configurable MOPS\nprocessing limits that are not yet tuned for the Pan-STARRS1 mission.\n The core MOPS software package is the product of more than 15 person-years of\nsoftware development and incorporates countless additional years of effort in\nthird-party software to perform lower-level functions such as spatial searching\nor orbit determination. We describe the high-level design of MOPS and essential\nsubcomponents, the suitability of MOPS for other survey programs, and suggest a\nroad map for future MOPS development.\n