Modeling the Performance of the LSST in Surveying the Near-Earth Object Population

TL;DR

This paper simulates LSST's ability to detect near-Earth objects, showing it can discover over 60% of potentially hazardous asteroids larger than 140m within 10 years, especially when combining LSST with IR surveys.

Contribution

It provides a detailed survey simulation of LSST's NEO detection performance using current baseline cadence and models the combined effectiveness with IR platforms.

Findings

LSST can discover 62% of PHAs >140m with optimal tracklet linking.

Completeness drops to 58% with less effective detection cadence.

Combining LSST with IR surveys like NEOCam can achieve near-complete detection.

Abstract

We have performed a detailed survey simulation of the LSST performance with regards to near-Earth objects (NEOs) using the project's current baseline cadence. The survey shows that if the project is able to reliably generate linked sets of positions and times (a so-called "tracklet") using two detections of a given object per night and can link these tracklets into a track with a minimum of 3 tracklets covering more than a ~12 day length-of-arc, they would be able to discover 62% of the potentially hazardous asteroids (PHAs) larger than 140 m in its projected 10 year survey lifetime. This completeness would be reduced to 58% if the project is unable to implement a pipeline using the two detection cadence and has to adopt the four detection cadence more commonly used by existing NEO surveys. When including the estimated performance from the current operating surveys, assuming these would continue running until the start of LSST and perhaps beyond, the completeness fraction for PHAs larger than 140m would be 73% for the baseline cadence and 71% for the four detection cadence. This result is a lower than the estimate of Ivezic et al. (2007,2014); however it is comparable to that of Jones et al. (2016) who show completeness ~70$%. We also show that the traditional method of using absolute magnitude H < 22 mag as a proxy for the population with diameters larger than 140m results in completeness values that are too high by ~5%. Our simulation makes use of the most recent models of the physical and orbital properties of the NEO populations, as well as simulated cadences and telescope performance estimates provided by LSST. We further show that while neither LSST nor a space-based IR platform like NEOCam individually can complete the survey for 140m diameter NEOs, the combination of these systems can achieve that goal after a decade of observation.