1. Early science on exoplanets with Gaia A. Mora 1, L.M. Sarro 2, S. Els 3, R. Kohley 1 1 ESA-ESAC Gaia SOC. Madrid. Spain 2 UNED. Artificial Intelligence Department. Madrid. Spain 3 Gaia DPAC Project Office. Madrid. Spain 2010-05-20. GREAT Exoplanets Kick-off meeting. Osservatorio Astronomico di Torino

2. 1. Introduction

3. Exoplanets: thousands candidates ► Thousands of Jupiter sized planets with a ~ 1 AU ► 5 years survey for high precision parameters ► Uncertainties for large period exoplanets  Low precision for periods larger than mission lifetime Casertano et al. (2008)

4. Hypothesis: 1.5 yr early release ► The astrometric solution (AGIS) needs 1.5+ years of data to provide parallaxes ► End of mission: best astrometric precision  G2V: σ π < 7 μas (V<10), 24 μas (V=15), 300 μas (V=20) ► Planet detection: individual measurements  Bright limit (G<11), σ AL,1CCD ~ 50 μas, σ AC,1CCD ~ 250μas ► Number of transits on the Gaia field of view  They can be predicted (scanning law)  ~80, end of mission (5 years)  ~24, hypothetical early realease (1.5 years)

5. AL & AC single CCD precision de Bruijne (2009)

6. Gaia scanning law

7. 2. Radial velocity candidates inclination

8. RV candidates inclination ► Radial velocity (RV) technique  Hundreds of exoplanet candidates ► Inclination ( sin i ) determination is difficult ► HST FGS provides narrow field mas astrometry  Inclinations for ~6 RV candidates Benedict et al. (2010) Benedict et al. (2002)

9. RV candidates selection ► Combination of RV and Gaia early data  Minimum sampling: half a period (P ≤ 3 yr)  1 Transit bright limit (G<11) average precision: ► σ AL,1transit ~ 17 μas, σ AC,1transit ~ 84 μas  ~24 data points (one per transit)  Astrometric signature ► α = (M P / M  ) (a P / 1AU) (pc / d) arcsec ► α ≥ 3 σ AL,1transit = 51 μas  Gaia brightness bright end limit: G ≥ 6 ► ~50 suitable candidates. Inclination known for two

10. Orbital element determination ► Orbital element determination is a complex non-linear problem ► Simulations needed  To learn what extra knowledge can be gained  Arbitrary thresholds used. Number of suitable candidates can be very different ► RV data coeval with Gaia probably needed  Simulations  better telescope time allocation

11. 3. Early candidates radial velocity follow-up

12. Exoplanets: 1.5 year survey ► Will planets be detected?  Biased, order of magnitude estimation: 40% of 5 yr ~3000 objects ► Lots of planetary systems ► Many false detections ► Low period planets only ► Low precision parameters ► Break degeneracies  RV Casertano et al. 2008 ~40%

13. RV follow-up of early candidates ► RV confirmation of candidates  false detections ► Planetary systems parameters  Break degeneracies and high precision parameters  RV monitoring during many periods required ► Plenty of telescope time needed !!  Dedicated telescopes/instruments? ► Simulations  observations optimization  Number and time of RV measurements  Upcoming astrometric data has to be considered

14. 4. Stellar activity: impact on astrometry

15. Stellar activity: starspots ► Starspots in active stars can be very large ► They leave astrometric signatures  ~10 μAU (LC V), ~500 μAU (LC III), ~10000 μAU (LC I) Strassmeier (2009)

16. Stellar activity: impact Eriksson & Lindegren (2007)

17. Stellar activity: impact ► Some estimations available  e.g. Eriksson & Lindegren (2007), Makarov et al. (2009) ► Exoplanet detection by Gaia not affected  Astrometric jitter << 1 M J planet signature  But predictions must be confirmed ► Impact on Gaia astrometry of giant stars ?? ► Impact on future missions (e.g. SIM Lite) ?? ► Test: Simultaneous astrometry + Doppler imaging

18. Stellar activity: Doppler imaging ► Line shape is altered by starspots ► Surface temperature map reconstruction ► High resolution spectra  λ / Δλ ~ 100,000  SNR ~ 300 ► Photometric data useful ► Observations during a period  astrometric signature estimation Strassmeier (2006)

19. Stellar activity: observations ► Empirical determination of astrometric signature  ~50-100 μas for nearby giants  Gaia and VLTI/PRIMA ► Simultaneous Astrometry and Doppler imaging ► Astrometry with Gaia  Scanning law  prediction of focal plane transits  Plenty of ground-based telescope time needed ► e.g. 10 transits x 10 observations = 100 spectra per star ► Astrometry with VLTI/PRIMA  Less telescope time needed, e.g. 10 spectra / rotation  Bright nearby reference star required. Distance ~ 20”

20. Stellar activity: statistical analysis ► The astrometric signature σ pos depends on the stellar magnitude variability σ m ► Gaia will provide millimag light curves ► Knowledge on a single object is limited, but statistical analysis could be feasible ► Trends with mass and evolutionary status

21. 5. Summary Early science activities

22. Early science: activities ► Simulations  Inclination angle for RV candidates  Candidate selection for RV follow-up ► Observations  RV: coeval data for existing RV candidates  RV: early astrometry planets monitoring  Gaia + Doppler imaging of active stars  PRIMA + Doppler imaging of active stars  Stellar activity: statistical analysis