Asteroid Discovery and Characterization with the Large Synoptic Survey Telescope (LSST)

TL;DR

The LSST will revolutionize asteroid discovery and characterization by detecting over 5 million objects, providing detailed data on their properties, and significantly expanding our understanding of small bodies in the Solar System.

Contribution

This paper outlines the LSST's capabilities and survey strategy for asteroid detection, highlighting its potential to vastly increase known small body populations and provide detailed physical characterization.

Findings

LSST will discover over 5 million asteroids in ten years.

The survey will provide multiple observations per object, enabling detailed physical analysis.

Automated software will efficiently process data for asteroid detection and characterization.

Abstract

The Large Synoptic Survey Telescope (LSST) will be a ground-based, optical, all-sky, rapid cadence survey project with tremendous potential for discovering and characterizing asteroids. With LSST's large 6.5m diameter primary mirror, a wide 9.6 square degree field of view 3.2 Gigapixel camera, and rapid observational cadence, LSST will discover more than 5 million asteroids over its ten year survey lifetime. With a single visit limiting magnitude of 24.5 in r-band, LSST will be able to detect asteroids in the Main Belt down to sub-kilometer sizes. The current strawman for the LSST survey strategy is to obtain two visits (each visit being a pair of back-to-back 15s exposures) per field, separated by about 30 minutes, covering the entire visible sky every 3-4 days throughout the observing season, for ten years. The catalogs generated by LSST will increase the known number of small bodies in the Solar System by a factor of 10-100 times, among all populations. The median number of observations for Main Belt asteroids will be on the order of 200-300, with Near Earth Objects receiving a median of 90 observations. These observations will be spread among ugrizy bandpasses, providing photometric colors and allowing sparse lightcurve inversion to determine rotation periods, spin axes, and shape information. These catalogs will be created using automated detection software, the LSST Moving Object Processing System (MOPS), that will take advantage of the carefully characterized LSST optical system, cosmetically clean camera, and recent improvements in difference imaging. Tests with the prototype MOPS software indicate that linking detections (and thus discovery) will be possible at LSST depths with our working model for the survey strategy, but evaluation of MOPS and improvements in the survey strategy will continue. All data products and software created by LSST will be publicly available.