LSST: Comprehensive NEO detection, characterization, and orbits
Zeljko Ivezic1 & R. Lynne Jones1
1University
of Washington
The Large Synoptic Survey Telescope (LSST) has Solar System mapping as one of its four key scientific design drivers, with emphasis on efficient Near-Earth Object (NEO) and Potentially Hazardous Asteroid
(PHA) detection, orbit determination, and characterization. The baseline design satisfies strong constraints on the cadence of observations mandated by PHAs, such as closely spaced pairs of observations to
link different detections and short exposures to avoid trailing losses. Due to frequent repeat visits LSST will effectively provide its own follow-up to derive orbits for detected moving objects. Detailed modeling of
LSST operations, incorporating real historical weather and seeing data from Cerro Pachon in Chile, the LSST site, shows that LSST could find 90% of the PHAs with diameters larger than 250 m LSST using its
baseline design cadence, and 75% of those greater than 140 m within ten years. However, simulations also show that LSST can reach the completeness of 90% of PHAs larger than 140m by optimizing observing
cadence and extending the survey lifetime to 12 years. In addition to detecting and determining orbits for these PHAs, LSST will also provide valuable data on their physical characteristics through accurate color
and variability measurements, which can be used to determine approximate taxonomical types, better size estimates by constraining albedos, rotation periods, and shape characteristics; thus constraining PHA
properties relevant for risk mitigation strategies
Detecting NEOs with LSST
LSST Moving Object Pipeline System (MOPS)
NEO Impact Hazard
LSST will detect approximately 100,000 NEOs over its
10 year survey lifetime. LSST’s typical r band limiting
magnitude of 24.5 enables detection of NEOs larger
than 140m in diameter out to distances of about 2.5 AU.
LSST could detect NEOs at solar elongations as small
as 45 degrees; although these observations would be at
high airmass, LSST would still be sensitive enough to
detect NEOS as small as 140m to be detected on
Venus-like orbits.
Discovering NEOs is the most challenging use-case for the
moving object pipeline system (MOPS), the software that
links individual detections of moving objects into identified
objects with orbits.
Each night, as images are obtained from the telescope,
catalogs of sources detected in ‘difference images’ are
created (‘DIASources’), then passed to MOPS along with
significant metadata about the images, previous associated
detections, and flags related to image processing.
At the end of each night, MOPS links the individual
DIASources from the night into ‘tracklets’ consisting of two
DIASources. To allow for cases where many images of the
same object are obtained on the same night, tracklets are
then merged. The tracklets typically span 15 to 90 minutes
of time and assume simple linear motion.
MOPS then links the tracklets into ‘tracks’ using the position
and velocity information from the tracks. Three nights of
tracklets are required to form a track; the goal is to allow a
30 night window for track generation. The tracks are fit with
a quadratic (or higher order) polynomial plus a topocentric
correction; tracks with high residuals are rejected
immediately.
Orbits are then fit to the remaining tracks; orbits with high
residuals are rejected. Orbital arcs are extended backward
in time by searching for additional previous tracklets
consistent with the orbit; as new observations are acquired,
additional detections are added to the orbit.
LSST will provide the orbits (including uncertainties) and
associated DIASources, including their positions, fluxes,
and shape measurements (and uncertainties) of all objects
in a database updated nightly.
More details about MOPS are available in the “Moving
Object Pipeline System Design” document at http://ls.st/ep1
In 2005 Congress directed NASA to implement a near-Earth object
survey that would catalogue 90% of NEOs larger than 140m by
2020. Simulations of LSST detection capabilities indicate that LSST
would discover 75% of the target population within ten years under
the baseline cadence.
These simulations were based on:
• Simulated pointing histories for LSST created by the Operations
Simulator (OpSim). The OpSim uses a high-fidelity model of the
telescope (slew speed, cable wraps, etc), real historical weather
and seeing data from Cerro Tololo and Cerro Pachon (the LSST
site), a model of the sky brightness similar to those available from
other observatories, and a set of “proposals” based on the actual
science goals that drive the observing cadence.
• PHA populations based on the known PHAs larger than 1km and
(simulated separately) a synthetic population provided by Al Harris
• Simulated observations of each of those model PHAs over the
lifetime of LSST; if the PHA was detected at a SNR>5, for at least
3 nights within a 30 night window with at least 2 observations
within a 90 minute window on each night, it was considered
“found”.
While under the baseline survey cadence, LSST would discover
75% of the PHAs larger than 140m within ten years, reaching the
Congressional goal of 90% would require a modified and extended
NEO-Optimized survey, dedicating 15% of survey time to higher
airmass searches near sun and along the northern ecliptic. This is
possible by extending the survey lifetime to 12 years.
Above: Size/Absolute Magnitude limits for NEOs
discovered at LSST’s typical limiting magnitude in r band,
as a function of both geocentric (left column) and
heliocentric (right column) distance, and at 60 degrees
solar elongation (top row) and opposition (bottom row).
Above: Histogram of apparent velocities for
various populations of solar system objects.
Above: Data flow through the LSST nightly
processing pipeline, including MOPS.
Early Warning Limits
Above: MOPS efficiently links DIASources into
tracklets, and tracklets into tracks, using kd-trees.
The available warning time is an important consideration for NEO impacts.
While warning time for each individual PHA obviously depends on its size and
orbit, typical warning time for 45m objects would be 1-3 months with LSST’s
faint limiting magnitudes and observing cadence. The plots at right show an
example of the available early warning time for a PHA. The top plot illustrates
the PHA orbit in a rotating heliocentric system; the magenta line shows the area
that LSST could detect a 140m object. The bottom plot shows the velocity vs
distance diagram for the same PHA; the red dots show positions in 1-day
intervals for which a 45m object would have V<24.5 (LSST’s faint limit) and the
blue dots indicate intervals with V<20. The warning time is 39 days with LSST;
however, note that LSST would also detect the PHA during three previous close
approaches.
NEO Characterization
Above: MOPS associates individual detections (DIASources) into
tracklets (2 DIASources), merges tracklets within a night where
possible, then links these tracklets into tracks, and finally orbits.
MOPS Simulations
Above: The ecliptic plane and the positions of NEAs
outside the orbit of Venus. This is an edited version of
Figure 3.5 from the 2010 NRC study “Defending Planet
Earth: Near-Earth Object Surveys and Hazard Mitigation
Strategies”, with additions of the LSST search region for
NEOs (the red lines). LSST can point to within 20 degrees
of the horizon; this allows observations to 45 degrees
solar elongation.
Simulations of MOPS performance have been run using a
test Solar System Model (the S3M; Grav et al., PASP 2011)
observed with the baseline LSST observing cadence
(realistically simulated using the LSST Operations
Simulator), and adding variable amounts of additional
‘noise’ detections. The results show that requiring 2
detections per night, with 3 nights of detections, is sufficient
for linking objects moving at main belt speeds and slower,
given anticipated LSST noise levels. Further development
is planned to improve MOPS performance for NEOs.
Left: Number of potential
impactors as a function of
size/impact
energy
(Harris; modified from the
2007 NASA NEO report).
Below:
LSST
NEA
detection
completeness
as a function of size, after
10 years (solid line) and
after 12 years of NEOemphasized
observing
(upper dashed line).
Above: MOPS identifies potential tracks by linking
tracklets following roughly quadratic motion; then
attempts to fit a higher-order polynomial plus a
topocentric correction to the DIASources. The top
panel of the plot above illustrates the sky motion of
an NEO over 20 nights (solid black line); the red dots
indicate hypothetical observations at 11pm and
midnight each night. The panels to the lower left
show the separate RA and Dec motions, including a
cubic fit, as a function of time. The panels to the
lower right show the residuals between the fit and the
actual motion; with a quadratic fit only, these
residuals can be 40” and larger. The topocentric
correction has not been included here, but is visible
in these residuals.
This second fitting step reduces the number of initial
quadratic-only tracks by approximately a factor of 50.
Orbit fitting reduces the number of tracks by
approximately another order of magnitude.
LSST will acquire multiple NEO observations in ugrizy (most relevant
being griz) filters, allowing generation of rough taxonomies for most
objects. In addition, these color classifications will improve the statistical
determination of the size distribution. Previous surveys have shown that
the albedo distribution of asteroids is bimodal, with one peak having a
mean albedo of 0.06 while the other peak has a mean of 0.20 in g or
about 0.25 in r or i, and that these peaks are correlated with color. Low
albedo MBAs are C-, D-, and P-types asteroids, while those MBAs with
higher albedos are S-, R-, V-, E-, and M-type asteroids. While this does
not permit firm determination of the albedo for a single object, it does
reduce the error on the overall size distribution by 30-50%.
Asteroid colors can be used
to determine a general
spectral type (left; Parker et
al. Icarus 2008); these
colors also map to albedo,
as
demonstrated
by
NEOWISE (right; Mainzer et
al. AJ 2012 – albedo in
visible to left, in IR to right)
Spacecraft Targets
By discovering 100,000’s of NEOs,
LSST will greatly improve the chances
of discovering a suitable, low-velocity,
nearby NEO to serve as a target for
future spacecraft missions.
Artist’s depiction of the DAWN spacecraft
orbiting Ceres (Credit: McREL)