The Pan-STARRS Moving Object Processing System

TL;DR

The Pan-STARRS MOPS is a sophisticated software system capable of automatically discovering and identifying asteroids from survey data, achieving high efficiency and adaptability across different telescope configurations.

Contribution

This paper introduces MOPS, a new software system that automates asteroid detection and orbit determination with high efficiency, adaptable to various survey telescopes and capable of discovering unknown object populations.

Findings

Achieves >99.5% efficiency in orbit production from simulated asteroid populations.

Successfully detects populations of unknown objects like interstellar asteroids.

Maintains >99.5% detection efficiency on a single night, with some efficiency loss over multiple nights.

Abstract

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.