Solar System science by Gaia observations Observatoire de la Cte - - PDF document

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Solar System science by Gaia observations Observatoire de la Cte - - PDF document

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Solar System science by Gaia observations Observatoire de la Cte dAzur P. Tanga Paolo Tanga Gaia and the Solar System Asteroids (~400.000 most known) Mainly Main Belt Asteroids (MBA) Several NEOs Other

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Paolo Tanga

Solar System science by Gaia observations

  • P. Tanga

Observatoire de la Côte d’Azur

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Paolo Tanga, Gaia Solar System Science – Pisa May 4-6 2011

Gaia and the Solar System…

  • Asteroids (~400.000 – most known)

– Mainly Main Belt Asteroids (MBA) – Several NEOs – Other populations (trojans, Centaurs,..)

  • Comets

– Primitive material from the outer Solar System

  • « Small » planetary satellites

– « regular » – « irregular » (retrograde orbits)

  • Gaia will probably NOT collect observations of « large » bodies

(>600 mas?)

– Main Planets, large satellites – A few largest asteroids

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Paolo Tanga, Gaia Solar System Science – Pisa May 4-6 2011

The scanning law

Sole

Spin axis Spin axis trajectory, 4 months 4 rotations/day Sun trajectory, 4 months

45°

Rotation axis movement

Scan path 4 days Spin axis trajectory 4 days

Scan path in 4 days

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Paolo Tanga, Gaia Solar System Science – Pisa May 4-6 2011

Observable region on the ecliptic

~ 60 detections/ 5 years for

Main Belt asteroids ~ 1 SSO object in the FOV every second around the ecliptic

  • Discovery space:

– Low elongations (~45-60°) – Inner Earth Objects (~unknown) – Other NEOs

unobservable unobservable

Sun Gaia

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Paolo Tanga, Gaia Solar System Science – Pisa May 4-6 2011

5

How many asteroids with Gaia?

  • Evolution of the number of entries H < Hlim

Gaia det ect ion limit Probable t ot al number

Nknown H <16 ~ 250 000 margin f or discovery H < 16 Nnew H <16 ~ 150 000

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Paolo Tanga, Gaia Solar System Science – Pisa May 4-6 2011

Gaia data for asteroids

  • Astrometric Field

– Main source of photometric and

astrometric data – Read-on window assigned on board around each source – Window is tracked during the transit – For most sources the signal is binned across scan Best accuracy in the « along scan » direction Across Scan uncertainty ~ window size

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Paolo Tanga, Gaia Solar System Science – Pisa May 4-6 2011

Windows on moving sources

  • Windows are allocated from ASM centroiding

– centroiding errors lead to offset in the window – transit velocity errors lead to a drift in the window

  • A moving object will also drift relative to the window

– the total effect depends on the window size and Val

SM Signal recorded AF1 AF2

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Paolo Tanga, Gaia Solar System Science – Pisa May 4-6 2011

Velocity distribution

  • simulation on 5,000 objects

–main-belt, NEOs

  • motion detectable
  • ver 1 transit

Val Vac σ ~ 7 mas/s σ ~ 12 mas/s

mas/s %

  • 40
  • 30
  • 20
  • 10

10 20 30 40 1 2 3 4 5 6 7 8

along-scan

mas/s %

  • 40
  • 30
  • 20
  • 10

10 20 30 40 1 2 3 4 5

across-scan

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Paolo Tanga, Gaia Solar System Science – Pisa May 4-6 2011

Solar elongations

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Paolo Tanga, Gaia Solar System Science – Pisa May 4-6 2011

St at ist ics on 20000 bright est obj ect s

Phase angles

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Paolo Tanga, Gaia Solar System Science – Pisa May 4-6 2011

Expected properties of Gaia data: summary

  • 1 linear signal per CCD column

– 2D data available in some cases – Loss of data due to motion

  • High accuracy in the along scan (AL) direction, poor accuracy

across-scan (AC)

– Resulting in strongly correlated ucertainties on single-epoch equatorial positions

  • 50-70 observations of a given Main Belt Asteroid over 5 years
  • Low elongations (~45°) accessible
  • Frequent subsequent observations in the two FOVs
  • parallax effect relative to Earth (observations from L2)
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Paolo Tanga, Gaia Solar System Science – Pisa May 4-6 2011

Science goals

  • Systematic survey down to 20 mag ~ 3x105 objects
  • Main belt
  • NEOs
  • Orbits : virtually all object observed - x30 better than now

higher resolution of dynamical families

  • Masses from close encounters ~ 100 masses expected
  • Diameter for over 1000 asteroids : shape, density
  • Binary asteroids
  • Photometric data in several bands : albedo, taxonomic classification
  • Light curves over 5 years : rotation, pole, shape
  • Space distribution vs. physical properties
  • Perihelion precession for 300 planets : GR tests
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Paolo Tanga, Gaia Solar System Science – Pisa May 4-6 2011

Astrometry orbit refinement

  • Orbit reconstruction from simulated data

– point sources & gravitational interaction – solar system perturbations > 102 better than current accuracy

Mouret et al. 2007

Density

  • +

10 -8

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Paolo Tanga, Gaia Solar System Science – Pisa May 4-6 2011

λp = 30 βp = 60 b/a = 0.7 c/a = 0.5 P = 7h.527 φ0 = 0.4

Simulated Gaia photometry

Δ(mag) wrt first observation

Orbit of 39 Laetitia

  • A. Cellino, P. Tanga, M. Delbo
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Paolo Tanga, Gaia Solar System Science – Pisa May 4-6 2011

Photometry Shapes

  • Asteroid’s magnitude function of:

– shape, rotation period, direction of spin axis

  • Direct problem:

– model of light curves for different shapes and rotation

  • Inverse problem:

– find the rotation parameters from photometric data – strongly non linear

  • Choice for Gaia:

– Three-axial ellipsoids

Animat ion: M. Delbo

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Paolo Tanga, Gaia Solar System Science – Pisa May 4-6 2011

Size of the asteroids

  • Direct

Direct size determination for over 1000 asteroids

  • Good quality sizes for D>40km
  • Object’s size at different epochs
  • verall shape
  • Binarity

Signals f or dif f erent source diamet er

unresolved θ ~ 100 mas θ ~ 300 mas

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Paolo Tanga, Gaia Solar System Science – Pisa May 4-6 2011

RP/BP Taxonomic classification

  • Taxonomy classifies asteroids on the basis of visible

Taxonomy classifies asteroids on the basis of visible and near near-

  • IR

IR reflectance spectroscopy reflectance spectroscopy

– – Based on ~1000 objects today Based on ~1000 objects today

  • Gaia special features:

Gaia special features:

– – High solar elongation High solar elongation – – Blue spectrum coverage Blue spectrum coverage – – Several Several “ “bands bands” ”

  • Preliminary investigation on

Preliminary investigation on earth earth-

  • based observations

based observations

  • Limitations

Limitations

– – … …no albedo no albedo ambiguity E,M,P ambiguity E,M,P… …

  • automatic classifier developed

automatic classifier developed for Gaia for Gaia

  • Gaia taxonomy

Gaia taxonomy

Normalised ref lect ance

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Paolo Tanga, Gaia Solar System Science – Pisa May 4-6 2011

How much is / will be known

Property today Gaia

astrometry ~ 0"5 0"005 rotation periods 3000 ~100,000 shapes, poles ~200 ~100,000 spectral type ~ 1800 ~200,000 masses, σ < 60% ~ 40 150 size , σ < 10% ~ 500 1000 satellites ~ 20 (MBA) ?

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Paolo Tanga, Gaia Solar System Science – Pisa May 4-6 2011

Processing of SSO data

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Paolo Tanga, Gaia Solar System Science – Pisa May 4-6 2011

The DPAC

SSO

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Paolo Tanga, Gaia Solar System Science – Pisa May 4-6 2011

SSOs in the Gaia DPAC

  • Coordination Unit 4

– manager : D. Pourbaix; deputy: P. Tanga – Implementation of software in the Data Processing Center – ~ 20 european astronomers working on SSOs

Two pipelines for SSO:

  • Short-term (daily) processing

– Working on 24h of data – Fast processing for identifying anomalous/unknown asteroids Triggering of alerts

  • Long term processing

– Best accuracy – Complex object model (shapes, motion,…), best astrometric solution, all effects taken into account – Aims: intermediate final data releases

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Paolo Tanga, Gaia Solar System Science – Pisa May 4-6 2011

Daily pipeline scheme for SSOs

IDT Initial Data Treatment Initial Filter based on object motion during the focal plane crossing Comparison to ephemeris

  • f known objects

Linking of observations

  • ver ~48 hours

into « bundles » Preliminary short-arc orbit Identification certain? YES STOP Candidate « new » SSO

CU 4

NO SSO database IDT Initial Data Treatment

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Paolo Tanga, Gaia Solar System Science – Pisa May 4-6 2011

Gaia Follow-Up-Network for SSO

  • Validation of SSO nature of the «new» objects

– Ground based recovery can discriminate « false » and « true » SSO – Reliability verification of the daily processing chain

  • Recovery of the highest possible number of

– New objects, discovered by Gaia – Objects with « poor » orbits ( ambiguous identification)

  • Improve orbit accuracy

– a single ground-based detection can “collapse” the uncertainty of an

  • rbit
  • Advantages

– contamination of data sent to Minor Planet Center during the early mission operations is avoided – the science impact of the mission is maximized

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Paolo Tanga, Gaia Solar System Science – Pisa May 4-6 2011

Long-term processing

IDT Initial Data Treatment Comparison to ephemeris

  • f known objects

Linking of all available

  • bservations for each
  • bject into « threads »

CU 4

SSO database Physical properties Global parameters Accurate

  • rbits

Mission outcome

  • No external data sources used for DPAC processing

– probably for validation purposes only

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Paolo Tanga, Gaia Solar System Science – Pisa May 4-6 2011

Possible actions triggered by the Gaia output

  • Further data exploitation

– Computation of proper elements, new dynamical family classifications – Deeper analysis of anomalous sources (suspect binaries, comets…)

  • Obtention of new data

– TNO/asteroid occultations – Complementary observations:

  • Spectra
  • Photometry
  • Astrometry (candidates for mass / Yarkovsky determination)
  • Exploitation by associating data of other surveys:

– Pan-STARRS, LSST, Spitzer & WISE …

This is the reason why we are in Pisa now!

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Paolo Tanga, Gaia Solar System Science – Pisa May 4-6 2011

The End…