The Pan-STARRS M oving O bject P rocessing S ystem (& Science)

The Pan-STARRSMoving Object Processing System

(& Science)

Robert Jedicke(for the Pan-STARRS collaboration)

Institute for AstronomyUniversity of Hawaii2004 September 29

IMPACT

IMPACT

IMPACT

The Pan-STARRSMoving Object Processing System

(& Science)

Robert Jedicke(for the Pan-STARRS collaboration)

Institute for AstronomyUniversity of Hawaii2004 September 16

Robert Jedicke(for the Pan-STARRS collaboration)

Institute for AstronomyUniversity of Hawaii2004 September 16

The Pan-STARRSMoving Object Processing System

(& Science) (& Science)

Bigger Further Slower Dumber

Bigger Further Slower Dumber

DEFINITIONS

COMETS

ASTEROIDS

icier

dirtier

DEFINITIONSNear Earth Objects (NEO)

NEO ZONEPerihelion < 1.3AU

(about 130 million miles)

DEFINITIONSPotentially Hazardous Objects (PHO)

PHO ZONEMOID < 0.05 AU

(about 5 million miles)

PHO OrbitEarth Collision

at perihelion

Non-Collision ‘PHO’ Orbit

Not at Earth’sorbit at perihelion

1995 CR

DEFINITIONSDeath Plunge Objects (DPO)*

* Not an official acronym

Solar System Animation #3

Main Belt Objects

DEFINITIONS

TrojansTrojans

DEFINITIONSTrans-Neptunian Objects (TNO)

Comets

Long Period Comets

HalleyFamilyComets

Short PeriodComets

Centaurs

DEFINITIONS

Oort Cloud

3 light years

The Pan-STARRS Moving Object Processing System

(MOPS)

Selected PanSTARRS’s TopLevel Science Requirements

• MOPS shall create and maintain a data collection of detections and object parameters (e.g. orbit elements, absolute magnitudes) for >90\% of the PHOs that reach R=24 for 12 contiguous days during the course of Pan-STARRS operations.

• MOPS shall create and maintain a data collection (DC) of detections and object parameters (e.g. orbit elements, absolute magnitudes) for >90% of the members that reach R=24 12 contiguous days within each class of solar system object (Main Belt, Trojan, Centaur, TNO, Comet, etc, except NEO and PHO) during the course of Pan-STARRS operations.

Selected PanSTARRS’s TopLevel Science Requirements

• MOPS shall create and maintain a data collection of detections and object parameters (e.g. orbit elements, absolute magnitudes) for >90\% of the PHOs that reach R=24 for 12 contiguous days during the course of Pan-STARRS operations.

• MOPS shall create and maintain a data collection (DC) of detections and object parameters (e.g. orbit elements, absolute magnitudes) for >90% of the members that reach R=24 12 contiguous days within each class of solar system object (Main Belt, Trojan, Centaur, TNO, Comet, etc, except NEO and PHO) during the course of Pan-STARRS operations.

Why?

REASON #1

REASON #2

SPACEGUARD GOAL

SPACEGUARD GOAL

NASA NEO SDT

• 99% completion of PHOs with D>1km 90% reduction in residual

global impact risk• 90% completion of PHOs with D>300m

50% reduction in sub-global impact risk

Pan-STARRS & PHOs

• 99% completion of PHOs with D>1km 90% reduction in residual

global impact risk• 90% completion of PHOs with D>300m

50% reduction in sub-global impact risk

REASON #3

REASON #4

Existing Surveys

• 3-5 images/night

• Linear motion• Very low

false-positive rate

• 3-5 images/night

• Linear motion• Very low

false-positive rate

Existing Surveys – Step 1:Discovery & Identification

SpacewatchKitt Peak, AZ

LINEARWhite Sands, NM)

LONEOSFlagstaff, AZ

UHASMauna Kea, HI

NEAT/JPLHaleakala, Maui

NEAT/JPLPalomar, CA

CSS - NorthMt. Lemmon, AZ

CSS -SouthAustralia

• Links detections to known objects

• Identifies new objects

• Fits orbits to all objects with new detections

• Much more…

Existing Surveys – Step 2Linkage & Orbit Determination

• Links detections to known objects

• Identifies new objects

• Fits orbits to all objects with new detections

• Much more…

MPC

• Refine orbits• Calculate

impact probability

Existing Surveys – Step 3Impact Risk Assessment

• Refine orbits• Calculate

impact probability

• Fully integrated• Detection, attribution,

linking,orbit identification

• Orbit fitting• Parallel synthetic data

analysis Real-time efficiency/bias

• Fully integrated• Detection, attribution,

linking,orbit identification

• Orbit fitting• Parallel synthetic data

analysis Real-time efficiency/bias

Moving Object Processing System Telescopes

&Survey

ImageProcessing

PipelineMOPS Impact

Probability

Pan-STARRS

Moving Object Processing System

Moving Object Processing System

• MPC requires that reported detections be real forces Pan-STARRS to obtain 3 images/night reducing total sky coverage reducing total discoveries

• Difficult to control/monitor system efficiency introduce synthetic objects into data stream determine efficiency in real time monitor system performance in real time

• MPC requires that reported detections be real forces Pan-STARRS to obtain 3 images/night reducing total sky coverage reducing total discoveries

• Difficult to control/monitor system efficiency introduce synthetic objects into data stream determine efficiency in real time monitor system performance in real time

Moving Object Processing System

• 107 asteroids within range of PanSTARRS

• ~200 / deg2 @ V=24 @ on ecliptic

• 107 detections / month (20X current rates)

PanSTARRS Asteroid Surveying

• 107 asteroids within range of PanSTARRS

• ~200 / deg2 @ V=24 @ on ecliptic

• 107 detections / month (20X current rates)

Cumulative Observations

0

20,000,000

40,000,000

60,000,000

80,000,000

100,000,000

120,000,000

140,000,000

160,000,000

1995

1996

1997

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

PS1 Starts

• Every survey mode obtains at least twoimages at each location separated by a Transient Time Interval (15-30 minutes) serendipitous positions &

colours• Solar system survey re-visits each

location after 3-6 days obtain 3-4 nights/month ~12 day arc

Observing Cadence • Every survey mode obtains at least

twoimages at each location separated by a Transient Time Interval (15-30 minutes) serendipitous positions &

colours• Solar system survey re-visits each

location after 3-6 days obtain 3-4 nights/month ~12 day arc

• 2 detections/nightwith multi-night linking

•synthetic data

increased sky coverage push deeper into noise more objects

real-time system monitoring efficiency determination correction for selection effects

Moving Object Processing System

• 2 detections/nightwith multi-night linking

•synthetic data

increased sky coverage push deeper into noise more objects

real-time system monitoring efficiency determination correction for selection effects

Transient Detection (IPP)

+

+

+

Combined

4 Telescopes

Moving

Stationary

Static

Transients

Transient Types

Fast Asteroidal Object

Normal Asteroidal Object

Slow Asteroidal Object

Death Plunge Object

Supernovae/GRB

Cometary ObjectDifference

Linking Detections

Day 11 Field-of-view1500 real detections +1500 false detections

Linking Detections

Day 51 Field-of-view1500 real detections +1500 false detections

Linking Detections

Day 91 Field-of-view1500 real detections +1500 false detections

•Brute force (MPC) approach 100X Pan-STARRS computing power

• kd-tree (CMU) approach ~1/3 Pan-STARRS computer power

Linking Detections

•Brute force (MPC) approach 100X Pan-STARRS computing power

• kd-tree (CMU) approach ~1/3 Pan-STARRS computer power

• Must include– All major solar system perturbing bodies– Full error analysis

• Two available solutions– AstDys (Italy)– JPL (USA)

Orbit Determination

• Must include– All major solar system perturbing bodies– Full error analysis

• Two available solutions– AstDys (Italy)– JPL (USA)

Data Storage• Large by most astronomical standards• Small in comparison to Pan-STARRS (~1%)

500 TerraBytes

• Inject synthetic objects into MOPS parallel to real data analysis monitor system efficiency for correcting

observational selection effects monitor system performance to flag unusual

behavior

Synthetic Data

• Inject synthetic objects into MOPS parallel to real data analysis monitor system efficiency for correcting

observational selection effects monitor system performance to flag unusual

behavior

• Synthetic model matches real distributions all asteroid and comet types realistic orbit and size distribution realistic shape, rotation periods, pole

orientations + ‘unusual’ orbits e.g. hyperbolic interstellar,

retrograde main belt, distant Earths

Synthetic Data

• Synthetic model matches real distributions all asteroid and comet types realistic orbit and size distribution realistic shape, rotation periods, pole

orientations + ‘unusual’ orbits e.g. hyperbolic interstellar,

retrograde main belt, distant Earths

MOPS: Known Object Attribution

MOPS: Synthetic Detection & Noise Generation

MOPS: Orbit Determination & Attribution Loop

MOPS: Linking New Detections

The Pan-STARRS

Solar System Survey & Science

Solar System Survey Locations

Evening Sweet Spot Morning Sweet SpotOpposition

19:00 HST 00:00 HST 05:00 HST

• Tens of thousands of NEOs Size-frequency

distribution Orbit distribution Source fitting Genetic families?

Pan-STARRS & NEOs/PHOs

• Tens of thousands of NEOs Size-frequency

distribution Orbit distribution Source fitting Genetic families?

• Pan-STARRS will find as many objects in one lunation as have been identified since the discovery of Ceres in 1801

Pan-STARRS & the Main Belt

• 10,000,000 MB objects in ten years Size-frequency distribution Orbit distribution New small asteroid families Asteroid/comet transition objects Asteroid collisions Pole Orientations Rotation Rates Shapes

• 10,000,000 MB objects in ten years Size-frequency distribution Orbit distribution New small asteroid families Asteroid/comet transition objects Asteroid collisions Pole Orientations Rotation Rates Shapes

Pan-STARRS & the Main Belt

Trojans of all giant planets L4 & L5 swarm statistics Genetic families SFD through rollover at H~11

Pan-STARRS & Trojan Asteroids

0

1

2

3

4

5

6

1 2 3 4

Series1

Series2Known

Pan-STARRS

Jupiter Saturn Uranus Neptune1

10

100

1,000

10,000

100,000

1,000,000

Jewitt 2003, ‘Project Pan-STARRS and the Outer Solar System,’ EMP

Trojans of all giant planets L4 & L5 swarm statistics Genetic families SFD through rollover at H~11

Pan-STARRS & Comets• Pan-STARRS will find ~10X as many

comets per year as all existing surveys

• 1,000’s of comets in ten years operation Dormant detections at large distance Size-frequency distribution Orbit distribution

• INTERSTELLAR ! ! !

• Pan-STARRS will find ~10X as many comets per year as all existing surveys

• 1,000’s of comets in ten years operation Dormant detections at large distance Size-frequency distribution Orbit distribution

• INTERSTELLAR ! ! !

• Comet designation problem

• New Proposal Comet Jedicke-XXX X=(0-9,a-z,A-Z) (base 62) allows for ~240,000

comets

P/Jedicke 1996A1

Pan-STARRS & Comets

Pan-STARRS & TNOs

• ~20,000 TNOs Inclination distribution Size-frequency distribution Orbit distribution / dynamical

structure More Plutos? ~100 wide binaries

• ~20,000 TNOs Inclination distribution Size-frequency distribution Orbit distribution / dynamical

structure More Plutos? ~100 wide binaries

Pan-STARRS & Distant Planets

Jewitt 2003, ‘Project Pan-STARRS and the Outer Solar System,’ EMP

New Plutos320AU New Earths

620AU (50AU)New Neptunes1230AU (130AU)

New Jupiters2140AU (340AU)

Pan-STARRS Minor Planet Summary

0

1

2

3

4

5

6

7

8

1 2 3 4 5 6 7 8 9 10

Series1

Series2

Series3

1

10,000,000

1,000,000

100,000

10,000

1,000

100

10

KnownPS 1 YearPS 10 Years

NEO / PHOM

ain BeltJovian TrojansOther TrojansCentaursCom

etsTNOs

Wide TNO Binaries

Companions

Interstellar Visitors

PS1 - 2006PS4 - 2008Coming soon to an island near you.

Pan-STARRS Problem:

Pan-STARRS plans on using a very wide ‘Solar System’ G filter but is required to reach R=24. Assuming that the R-filter transmission is 100% in the range [R1,R2] and 0% outside that range and that the G-filter has similar performance in the range [G1,G2] where G1<R1 and G2>R2, what is the ratio of the required exposure times in the two filters to reach R=24 in the AB magnitude system?Assuming that Vega is a black-body, what is the answer in the Johnson system?Make other reasonable assumptions as necessary