The Large Synoptic Survey Telescope as a Near-Earth Object Discovery Machine
R. Lynne Jones, Colin T. Slater, Joachim Moeyens, Lori Allen, Tim, Axelrod, Kem Cook, \v{Z}eljko Ivezi\'c, Mario Juri\'c, Jonathan Myers, and, Catherine E. Petry

TL;DR
This paper evaluates LSST's capability to discover Near-Earth Objects and Potentially Hazardous Asteroids, demonstrating that strategic survey extensions can significantly improve detection rates and reduce undiscovered hazardous objects.
Contribution
It provides an empirical assessment of LSST's NEO detection potential and explores survey modifications to enhance discovery yields.
Findings
LSST can detect approximately 66% of PHAs brighter than H=22 with its baseline strategy.
Extending the survey by two years and increasing the search window raises PHA detection to 86%.
False detection rate in LSST image differencing is about 450 deg$^{-2}$.
Abstract
Using the most recent prototypes, design, and as-built system information, we test and quantify the capability of the Large Synoptic Survey Telescope (LSST) to discover Potentially Hazardous Asteroids (PHAs) and Near-Earth Objects (NEOs). We empirically estimate an expected upper limit to the false detection rate in LSST image differencing, using measurements on DECam data and prototype LSST software and find it to be about ~deg. We show that this rate is already tractable with current prototype of the LSST Moving Object Processing System (MOPS) by processing a 30-day simulation consistent with measured false detection rates. We proceed to evaluate the performance of the LSST baseline survey strategy for PHAs and NEOs using a high-fidelity simulated survey pointing history. We find that LSST alone, using its baseline survey strategy, will detect of the PHA and …
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Taxonomy
TopicsAstronomy and Astrophysical Research · Astronomical Observations and Instrumentation · Stellar, planetary, and galactic studies
