Download Discovery Process for Finding ARM Targets Using Pan

Discovery Process
for Finding ARM Candidate Targets
Using PanStarrs2 and New Atlas
Telescopes.
Eva Schunova, Robert Jedicke with
Peter Veres & Larry Denneau
Institute for Astronomy
University of Hawaii at Manoa
Target NEO 2 Conference
July 9, 2013
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Purpose
• ARM candidate target detection capability
with 100% NEO dedicated surveys
• PS2 survey
(2nd Panoramic Survey Telescope and Rapid Response System)
• ATLAS survey
(Asteroid Terrestrial-impact Last Alert System)
• 3 performance configurations assessed for both:
(underperformed: -0.5 mag, nominal, overperformed: +0.5 mag)
• Located in Hawaii
• Both in development stage
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Issues
• Annual discovery rates of NEOs by PS2 and ATLAS
• Follow-up with optical telescopes (IRTF) and radar
• ULTIMATE QUESTION: What is the total number of
available target candidates in the NEO population?
• REQUIRES:
– Reliable NEO model
– Accurate survey simulations
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NEO model
• Greenstreet et al. (2012)
• Based on Bottke et al. (2002) - finer resolution in (a, e, i)
• SFD of NEOs according to Brown et al. 2002
• Problem with small size NEO models:
– Discoveries are subject to huge selection effects
– Large non-gravitational effects (YORP, Yarkovsky )
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Synthetic ARM candidate targets
population
• 2.4 x 1011 NEOs generated
• 27 < H < 31
• 2m < D < 30m (albedo dependent)
• 5 dynamical criteria => Earth-like heliocentric orbits
• Survey simulation pre-selection: MOID < Δ(H)
• => 7.3 x 106 ARM candidate targets
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Only 0.003% of model NEOs pass
ARM target dynamical & size cuts
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ATLAS
Asteroid Terrestrial-impact Last Alert System
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Fully automatized => cheap
System operational in 2015
1-4 telescopes/ 2 sites
40 deg2 field-of-view
80,000 deg2/night
Scans most of the visible night sky 4x/night
Nominal Vlim=20.0
SELF FOLLOW UP
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PS2
2nd Panoramic Survey Telescope and
Rapid Response System
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7 deg2 field-of-view
~ 3,600 deg2/night
1/11th ATLAS coverage
Nominal Vlim = 22.0
Detects NEOs 2.5 x further away
Visits to the same bore site
separated by 3 nights.
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ATLAS nightly coverage
PS2 nightly coverage
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Survey simulations with MOPS
(Moving Object Processing System)
Generate NEOs
Fulfilling
ARM Target Criteria
Survey Simulation
(ATLAS-N, ATLAS-S, PS2)
Implement
Weather Losses
Implement fillfactor losses
Implement
trailing losses
Determine
IRTF and Radar
Recovery Availability
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Total synthetic ARM target discoveries
over 2 years with nominal systems
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Discrepancy
between simulations and real data
PS1 finds 8x more ARM candidates than predicted!
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Possible explanations
• Imperfect survey simulation
• Imperfect NEO model & Size-Frequency distribution
• Small NEOs more prone to non-gravitational effects
• Unknown dynamical process more efficient in transporting
small objects from MB to NEO region
• Temporary local NEO density enhancement
• (due to tidal disruption, collision, ...)
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Typical target follow-up window
IRTF
Arecibo radar
window
window
Little time for characterization after discovery!
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Typical discoveries of nominal systems
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ATLAS
PS2
>2 NEOs/month
Easier IRTF follow-up (30%)
Short window (~ 4 days)
All discoveries observable by radar
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>1 NEOs/month
Difficult for IRTF follow-up!! (10%)
Longer window (~12 days)
50% discoveries observable by radar
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Summary
• Observed discrepancy between predicted
discovery rates and PS1 data - 8 x more real
discoveries!
• ATLAS and PS2 surveys will discover dozens of
ARM candidates per year
• Windows for characterization are typically few
days (IRTF) and few weeks (radar)
• ATLAS has advantages over PS2 for ARM
candidate detection
• ATLAS: Vlim=20.5 - up to 70 ARM candidates/year
This work was supported by the NASA NEOO grant.
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Fill factor and trailing losses
Courtesy: Denneau et al. 2013
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Total synthetic ARM target discoveries over
2 years with over-performing systems
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Annual ARM candidate
detections for nominal systems
Collectively we will find XXX/year.
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