Other
Scientific paper
Sep 2008
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2008dps....40.3210j&link_type=abstract
American Astronomical Society, DPS meeting #40, #32.10; Bulletin of the American Astronomical Society, Vol. 40, p.453
Other
Scientific paper
The Large Synoptic Survey Telescope (LSST) will provide a unique tool to study moving objects throughout the solar system, creating massive catalogs of Near Earth Objects (NEOs), asteroids, Trojans, TransNeptunian Objects (TNOs), comets, planetary satellites and other rare, yet-undiscovered populations, with well-measured orbits and high quality, multi-color photometry, accurate to 0.005 magnitudes for the brightest objects. In the baseline LSST observing plan, back-to-back 15-second images reach a limiting magnitude as faint as r=24.7 in each 9.6 square degree visit, twice per night; a total of approximately 15,000 square degrees of the sky will be imaged in multiple filters every 3 nights.
The catalogs will include more than 80\% of the potentially hazardous asteroids larger than 140m in diameter, millions of main-belt asteroids and perhaps 20,000 Trans-Neptunian Objects. Objects with diameters as small as 100m in the Main Belt and <100km in the Kuiper Belt can be detected in individual images. Specialized deep drilling observing sequences will detect KBOs down to 10s of kilometers in diameter.
Derivation of proper elements for main belt and Trojan asteroids will allow ever more resolution of asteroid families and their size-frequency distribution.
By obtaining multi-color ugrizy data for a substantial fraction of objects, relationships between color and dynamical history can be established. This will also enable taxonomic classification of asteroids, provide further links between diverse populations such as irregular satellites and TNOs or planetary Trojans, and enable estimates of asteroid diameter with rms uncertainty of 30%.
By obtaining high-quality photometric measurements, rotation periods and phase curves will be measured for large fractions of each population, leading to new insight on physical characteristics. Photometric variability information, together with sparse lightcurve inversion, will allow spin state and shape estimation for up to two orders of magnitude more objects than presently known.
Chesley Steven R.
Connolly Andrew J.
Harris Alan W.
Ivezic Zeljko
Jones Robert L.
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