Asteroid color photometry with Gaia and synergies with other space - - PowerPoint PPT Presentation

Asteroid color photometry with Gaia and synergies with other space missions

Marco Delbo UNS-CNRS-Observatoire de la Cˆ

• te d’Azur

& Gaia DPAC Coordination Unit 4 (Solar System Objects) May 23, 2011 Pisa, Italy

Collaborators

Philippe Bendojya (UNS-CNRS-Observatoire de la Cˆ

• te d’Azur)

Antony Brown (Leiden Observatory, the Netherlands) Giorgia Busso (Leiden Observatory, the Netherlands) Alberto Cellino (INAF-Osservatorio Astronomico di Torino, Italy) Laurent Galluccio (UNS-CNRS-Observatoire de la Cˆ

• te d’Azur)

Julie Gayon-Markt (UNS-CNRS-Observatoire de la Cˆ

• te d’Azur)

Christophe Ordenovic (UNS-CNRS-Observatoire de la Cˆ

• te d’Azur)

Paola Sartoretti (Observatoire de Paris) Paolo Tanga (UNS-CNRS-Observatoire de la Cˆ

• te d’Azur)

Outline of the presentation

Introduction Asteroid spectral classes and mineralogy Modern CCD based asteroid spectroscopy and its limitations Asteroid spectral classification using Gaia The BP-RP photometers on board of Gaia Expected peformances of the BP-RP Data products for asteroid color photometry Asteroid spectral classification algorithm Unsupervised clustering algorithm for asteroid spectral classification Combination of Gaia photometry with AUXILIARY Data

Asteroid spectral types

Asteroids are assigned a type based on spectral shape. These types are thought to correspond to an asteroid’s surface composition. Bus and Binzel spectral types:

◮ C-group (carbonaceus) with a

featureless spectrum

◮ B-type (featureless and blue)

◮ S-group (stony) with silicate

absorption bands

◮ X-group of mostly metallic

• bjects including

enstatite-chondrite like spectra

0.8 0.85 0.9 0.95 1 1.05 1.1 1.15 1.2 0.4 0.45 0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 S-type X-type B-type C-type

Wavelength (microns) Reflec tance S B X C

from the SMASS web site, by R. Binzel and collaborators

Modern CCD based asteroid spectroscopy

Bus and Binzel 2002 DeMeo et al., 2009

◮ However, all spectra do not go shortwards 450nm. ◮ Most available data in the blue region (340-550nm) are very

poor in quality.

Sloan Digital Sky Survey (SDSS); Parker et al. (08) colors

SDSS: color photometry of more than 100,000 asteroids. Example from the SDSS Moving Object Catalog 4 (MOC4).

0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Reflectivity Wavelength (um) S-type

bands: u’:354, g’:477, r’:623, i’:763, z’:913 (mn) with a∗ = 0.89(g′ − r′) + 0.45(r′ − i′) − 0.57.

Asteroid spectral classes and mineralogy of the main belt

◮ Investigation of the

mineralogy of families.

◮ Comparison of spectra of

NEAs with those of families near the NEA source regions...

with the help of dynamical models; see e.g. De Leon et al. 2010; Campins et al. 2010; Jenniskens et al. 2010; Walsh et

• al. 2011; Gayon-Markt et al.

2011; etc..)

The photometers on the focal plane of Gaia

SM1-2 AF1 - 9 BP 420 mm 0.69° RP RVS

BAM BAM WFS WFS

0s 10.6 15.5 49.5 56.3 64.1 30.1 0s 5.8 10.7 44.7 51.5 59.3 25.3

sec sec FOV1 FOV2

1 pixel 60 x 180 mas 106 CCDs (4.5 x 2 kpix) = 1 Gpixel

disclaimer: in the Gaia community, BP-RP data is called color phometry; it is low resolution (R ∼ 20 − 90) slit-less spectroscopy, though.

The photometers: resolving power (R =

λ ∆λ)

R~70 R~20 R~90 R~70

◮ Sampling is such to have about 18

independent bands in the BP-RP domain (A. Brown, spring 2011)

◮ Sampling is 60 pixel per

photometer, signal is in general contained in 40 pixel per photometer.

◮ Telescope PSF FWHM is about 2

pixels AL (40/2∼20 independent bands) and 1 pixel AC.

◮ 80% of asteroid observations have

velocities ≤15 mas/s. Beacuse a CCD transit lasts 4 s → ≤1 pixel widening of the PSF: this is not too bad.

BP-RP response for point like sources

G=15 point source with different colors.

0.0 0.5 1.0 1.5 2.0 2.5 3.0 BP counts (10 3 photons) 40 30 20 10 sample 400 500 680 900 ! (nm) 0.0 0.5 1.0 1.5 2.0 2.5 3.0 RP counts (10 3 photons) 60 50 40 30 20 10 sample 640 700 800 9001000 ! (nm)

G2V star is the middle green curve.

Credits: Busso, G. & Brown, A. 2009

BP-RP SNR for an asteroid with G=17

2 4 6 8 10 12 14 300 400 500 600 700 800 900 1000 1100 SNR Wavelength (nm) BP RP

Photon Noise limited in general. So SNR=

• Nphotons

BP-RP SNR as function of magnitude (1 transit)

1 10 100 1000 10 12 14 16 18 20 SNR [400-1000] nm G magnitude Min SNR Peak SNR

◮ Minimum and Peak SNR in the range 400-1000 nm per

transit.

◮ Best fit to min SNR: SNR=17631 × 10−0.201317∗G

Average SNR for BP-RP at the end of mission

◮ The large majority of asteroids

(main belt) are observed at least 60 times [Mignard, F. 2001 (SAGFM09)]

◮ The SNR of the accumulated

(avarage spectrum) is 8 times larger

10 100 1000 10000 10 12 14 16 18 20 SNR [400-1000] nm G magnitude Min SNR Peak SNR

Minimum SNR at the end of the mission assuming 50 transit/asteroid

For asteroids with G=19-20 spectral classification will be difficult. Solution:?!: Spectral binning.

Spectral Shape Coefficients: 8-colors asteroid survey

◮ Spectral Shape Coefficients (SSCs;

4 for BP and 4 for RP; 8 colors for each source) are calculated by IDT (Initial Data Treatment).

◮ SSCs calculated also by PhotPipe

and refined at every cycle.

◮ Potentially very interesting for

performing an 8-colors asteroid survey.

20 40 60 80 100 120 140 160 300 400 500 600 700 800 900 1000 1100 Signal (e-/transit) Wavelength (nm) BP RP BP-SSC RP-SSC

Example of SSC values calculated for a BP-RP signal of a G=20 asteroid (solar-like spectrum).

Data products for asteroid color photometry

◮ The spectral energy distribution (SED) is obtained from

accumulated BP-RP data.

◮ Average SEDs is produced (1 per asteroid). ◮ Epoch SEDs is also produced where possible (for SNR≥20 per

transit ∼G≤15).

◮ Smearing due to proper motion is taken into account.

◮ Asteroid reflectivity is calculated from the SED.

◮ BP and RP SEDs are combined into one SED. ◮ The SED is divided by the solar spectrum and the results

normalized at 0.55 microns.

◮ The asteroid reflectivity is used to determine the asteroid

spectral class.

◮ Unsupervised clustering algorithm. ◮ Comparison with other classifications (e.g. Bus & Binzel).

Clustering method based on Minimal Spanning Tree (MST)

Galluccio et al. (2008 ) Method for partitioning a set V of N data points (V ∈ RL) into K non-overlapping clusters with:

◮ the inter-cluster variance is maximized; ◮ the intra-cluster variance is minimized.

Example of MST in R2

!!"# ! !"# !!"# !!"$ !!"% !!"& !!"' ! !"' !"& !"% !"$ !"#

Identification of the number of clusters:

◮ The lenght of the edge at each addition of

a vertex of the MST is recorded.

◮ Then by identifying valleys in this curve,

we can estimate the number and positions

• f high density regions of points → i.e.

the clusters.

! #! '!! '#! &!! &#! %!! %#! $!! ! !"!!# !"!' !"!'# !"!& !"!&#

Test of the classification algorithm

◮ Spectra of asteroids belonging to all spectral classes were

• btained at the Telescopio Nazionale Galileo (TNG) under

Gaia-like observing geometry. PI Paolo Tanga; Data analysis in progress.

photo credits: P. Tanga

◮ See next talk by Julie Gayon-Markt.

Removal of spectral classification degeneracies

There are some well known degeneracies in the mineralogical interpretation of asteroid spectral classes. For instance, asteroids (46) Hestia, (55) Pandora, and (317) Roxane have very similar spectra.

0.2 0.4 0.6 0.8 1 1.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Normalized Reflectance Wavelength (um) (55) Pandora - M-type (46) Hestia - P-type (317) Roxane - E-type

But asteroids (46) Hestia, (55) Pandora, and (317) Roxane have different albedos.

0.2 0.4 0.6 0.8 1 1.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Reflectance Normalized to the albedo Wavelength (um) (55) Pandora - M-type (46) Hestia - P-type (317) Roxane - E-type

Albedo + spectra → removal of spectral class degeneracies.

Asteroid spectral classification (Gaia + WISE data)

◮ NASA WISE has observed 100,000 asteroids in the thermal IR. ◮ Albedos will be obtained from WISE data. ◮ First data (IR images) already released. ◮ Albedo + spectra → removal of spectral class degeneracies. ◮ Albedo and spectra can be classified using our non supervised

classification algorithm.

ExploreNEOs with Warm Spitzer: PI D. Trilling (NAU)

Albedos from Warm Spitzer

0.5 1.0 1.5 2.0 2.5 3.0 a (AU) 0.0 0.2 0.4 0.6 0.8 1.0 e

Albedo (%)

5 10 15 20 25 30

Conclusions

DPAC products (from Gaia observations only):

◮ Gaia will obtain R ∼ 20 − 90 visible spectra of asteroids. ◮ Average spectra (reflectancies) will be published. ◮ Epoch spectra for the brighter asteroids. ◮ Spectral classes of asteroids will be also published.

Gaia + Auxiliary data (e.g. WISE albedos):

◮ Albedo from WISE or Spitzer will allow spectral classes

degeneracies to be removed → mineralogical map of the main belt.