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From Gaia to SIM-Lite: Terrestrial planet detection with μas astrometry

From Gaia to SIM-Lite: Terrestrial planet detection with μas astrometry. Mario G. Lattanzi (INAF-OATo) S. Casertano (STScI) A. Sozzetti (INAF-OATo). The NASA/JPL-studied mission SIM-Lite. SIM. Observing principle for highest astrometric precision. SIM-Lite. The astrometric assembly.

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From Gaia to SIM-Lite: Terrestrial planet detection with μas astrometry

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  1. From Gaia to SIM-Lite: Terrestrial planet detection with μas astrometry Mario G. Lattanzi (INAF-OATo) S. Casertano (STScI) A. Sozzetti (INAF-OATo)

  2. The NASA/JPL-studied mission SIM-Lite

  3. SIM Observing principle for highest astrometric precision

  4. SIM-Lite The astrometric assembly Flight segment

  5. The narrow angle observing scenario with a target star at the center of the field of regard and reference stars within a circle of 1 degree radius. The baseline orientation on a subsequent visit would be orthogonal to that shown here. Capable of 0.2-1 as single measurement errors (with a noise floor <0.1 as)

  6. Basic Facts for extrasolar planet search RVs = (Mp/Ms) RVp

  7. Gaia vs SIM-lite

  8. The NASA-requested double-blind test exercise for Earths detection and characterization in multi-planet systems • Four teams: planetary system models (5 groups), data simulation (1 group), data analysis (4 groups: UC Berkeley, San Francisco State, Princeton, JPL, STScI/OATo), and synthesis (1 group) • RV + SIM Lite astrometry: RV data evenly distributed over 15 yrs, 1 m/sec single visit accuracy; astrometry - 5 years uniform coverage at 0.4 micro-arcsec accuracy per single visit.

  9. Where are we “coming from”? • The Gaia mission experience • Large Double Blind Test campaign on more than 150,000 systems for detection and characterization of planets utilizing only astrometric observations from the ESA Gaia satellite (Casertano, Lattanzi, Sozzetti et al., AA, 2008). Different teams for systems simulation, fitting, and evaluation. Characterization “targeting” Jupiter-size “first” planets with periods just exceeding the mission operational time (6 yr compared to 5 yr). Multi-planets possible but difficult as precision & accuracy depend on mag (fixed observing time), uneven coverage geometry (scanning law), and/or color of parent star: best astrometry good to about 10 as, 10-20 times worse than SIM. • Hold primary responsibility for planet detection and characterization in Gaia’s DPAC consortium pipeline. • Earlier experience with SIM like data (Sozzetti et al, PASP, 2002 and 2003)

  10. What did we set out to do? • We want to understand if Earth-like planets (terrestrial mass and habitable-zone orbit) can be detected in multiple-planet systems, using SIM-Lite astrometry and ground-based RV observations. • A simulation campaign in double-blind mode was designed to answer this question.

  11. Period Search and Orbit Fitting Procedure • Iterative process, first RVs, then Astrometry, then combined solution • Iterative periodogram search (FAP < 0.01) on post-single-star fit residuals (astrometry only) and after successful removal of each component (P(F) < 0.01), T-I representation, global search on P,e,T ( ), L-M minimization, error estimates using full info from covariance matrix. Stop when calculated 2  20.99 [-> P(2 > 20.99 ) < 0.01], i.e. 1% significance level test.

  12. Notes on available code • IDL RV + Astrometry combined implementation derived from Gaia astrometry-only code. Slow, no time for improvements given very tight schedule and available manpower. • Iterations for multiple planets mostly manual. Needs more automatic tools. • FAP fixed.

  13. RV solution – System 13 – Batch 2

  14. RV solution – System 13 – Batch 2

  15. RV solution – System 13 – Batch 2

  16. ASTRO solution – System 13 – Batch 2

  17. ASTRO solution – System 13 – Batch 2

  18. ASTRO solution – System 13 – Batch 2 ( X-axis periodogram)

  19. ASTRO solution – System 13 – Batch 2 ( Y-axis periodogram)

  20. Lessons Learned (1) • We’re not ‘complete’ in the low S/N, high FAP regime • Typically systems are less ‘resolved’: higher 2 when high FAP components are missed, but also when all components are identified (-> need to get “more used” to multiple systems) Phase 1, all systems completeness = #detected / #detectable

  21. Lessons Learned (2) Phase 2, batch 2 (from McArthur)

  22. Lessons learned (3) • Failures modes • Part or entire sets of orbital parameters in astrometric solution of some difficult systems left unchanged when using “standard” adjustment procedure. (IDL Levenberg-Marquardt routine MRQMIN from Minpack. Behavior under investigation.) • Improvements in resulting 2 when using findings from other C teams as starting values.

  23. Conclusions (1/2) • Tremendous gain in going from the 10 as, Gaia, to the 1 as, or better, regime (SIM) especially for the multi-planet systems. • RVs essential in several cases (long periods) • Work with higher FAPs (increase the probability of false alarms when set size given  Take more chances!), but multiple & independent solver/fitting teams essential (confirmation of Gaia’s planets DBT experience)

  24. Conclusions (2/2) Would SIM see terrestrial planets? From what we have seen we can say that an astrometric mission like SIM-Lite is our best bet at finding terrestrial planets within the next 10 years in the immediate solar neighborhood!

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