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Discovery Process for Finding ARM Candidate Targets

Using PanStarrs2 and New Atlas Telescopes.

Eva Schunova, Robert Jedicke with Peter Veres & Larry Denneau Institute for AstronomyUniversity of Hawaii at Manoa

Target NEO 2 ConferenceJuly 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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• 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 )

NEO model

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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

ATLASAsteroid Terrestrial-impact Last Alert System

• 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

• 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 fill-factor 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 windowIRTF Arecibo radar

Little time for characterization after discovery!

window

window

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Typical discoveries of nominal systems

ATLAS

• >2 NEOs/month• Easier IRTF follow-up (30%)• Short window (~ 4 days)• All discoveries observable by radar

PS2

• >1 NEOs/month• Difficult for IRTF follow-up!! (10%)• Longer window (~12 days)• 50% discoveries observable by radar

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This work was supported by the NASA NEOO grant.

• 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

Summary

FORHIRE

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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.