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National Aeronautics and Space Administration Wesley A. Traub Jet Propulsion Laboratory, California Institute of Technology Advantages and Strategies for.

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Presentation on theme: "National Aeronautics and Space Administration Wesley A. Traub Jet Propulsion Laboratory, California Institute of Technology Advantages and Strategies for."— Presentation transcript:

1 National Aeronautics and Space Administration Wesley A. Traub Jet Propulsion Laboratory, California Institute of Technology Advantages and Strategies for Direct Imaging and Characterization of Exoplanets The Search for Life in the Universe Symposium STScI 4-7 May 2009

2 National Aeronautics and Space Administration Outline The Goals: Earths, Super-Earths, Search for Life Detection: Transits, RV, Astrometry, Imaging Characterization: Transit & Imaging Spectroscopy

3 National Aeronautics and Space Administration Earths, Super-Earths, & Jupiters

4 National Aeronautics and Space Administration Observed vs Expected Planets Ref.: (left) Extrasolar Planets Encyclopaedia (2009); (right) Multi-Planet Study (2009) Corot, Kepler, (TESS): How many Earths & Super-Earths?

5 National Aeronautics and Space Administration Jupiter at 10 pc Plot: Kasting et al 2009 (WP); Zodi: Kuchner 2009; vis: Karkoschka 2002; IR: Fortney 2009

6 National Aeronautics and Space Administration Delta-mag chart for all coronagraphs

7 National Aeronautics and Space Administration The Earth at 10 pc Plot: Kasting et al 2009 (WP). Zodi: Kuchner 2009.

8 National Aeronautics and Space Administration Detection by Transits

9 National Aeronautics and Space Administration Three Geometries Primary Transit Direct Imaging 9Traub Secondary Transit

10 National Aeronautics and Space Administration The Successes of Transits Ref.: (left) Extrasolar Planets Encyclopaedia (2009); (right) Multi-Planet Study (2009) Corot, Kepler, (TESS): how many Earths?

11 National Aeronautics and Space Administration Detection by RV and Astrometry

12 National Aeronautics and Space Administration Planet Hunter (Marcy) or SIM: Search for Earth-Like Planets HIP 1475 HIP 56997 HIP 67275 GAIA (70 µas) RV @ 1 m/s TPF-C (8 m) M2K2G2F2 Planets ~Tidally Locked Concentrate observing time (40% on a small number ~60 for SIM-Lite) over a 5 year mission. To achieve sensitivity to 1 Mearth @ (1 AU) scaled to the luminosity of the star

13 National Aeronautics and Space Administration

14 Astometric-RV Multi-Planet Study 5 input teams, 5 analysis teams Scoring CategoryPart 1Part 2 Completeness: Terrestrial18/20=90%37/43 = 86% Completeness: HZ13/13=100%21/22 = 95% Completeness: Terrestrial HZ9*/9=100%17**/18 = 94% Completeness: All planets51/54=94% 63/70 = 90% Reliability: Terrestrial25/27=93%38/39 = 97% Reliability: HZ16/16=100%20/20 = 100% Reliability: Terrestrial HZ12/12=100%16/16 = 100% Reliability: All planets64/67=96%66/68 = 97% - Analysts were asked to be aggressive in Part-1 and conservative in Part-2. - This is reflected in the denominators of the Completeness & Reliability sections. * All 9 T/HZ Part-1 detected planets were in multiple-planet systems. ** 10 of the 17 T/HZ Part-2 detected planets were in multiple-planet systems

15 National Aeronautics and Space Administration Detection by Imaging

16 National Aeronautics and Space Administration HST 2.4-mJWST 6.5-mATLAST 8-mATLAST 16-m Planets vs zodi: telescope size matters 1.5 m 2.4 m 4 m 10 m Ref.: (upper) M. Postman et al., ATLAST study; (lower) W. Cash et al., NWO study.

17 National Aeronautics and Space Administration Planned imaging study Analyze detection of planets, with expected noise Astrometric-RV study will be model Will include a range of visible imaging coronagraphs Will include zodi and scattered light Will be competitive

18 National Aeronautics and Space Administration Characterization by Transit Spectroscopy

19 National Aeronautics and Space Administration Transit successes Traub19 Transits have been very successful: Radius  density Brightness temperature Day-night temperature differences Temperature asymmetries Spectral features of Na, H 2 O, CH 4 … Question: can transits characterize Earth-like planets? I will focus on primary transits. (Secondary transits are another topic)

20 National Aeronautics and Space Administration Clouds Traub20 We assume that 60% of the Earth is covered by non-overlapping, opaque clouds: 24% at 1 km 24% at 6 km 12% at 12 km This mix produces spectra that match observations in the visible, near-infrared, and thermal infrared. We model this with 3 parallel spectra, weighted & summed.

21 National Aeronautics and Space Administration Ray-by-ray spectra, visible & near-infrared 21 Short wavelength range of transmission spectrum. Note: - strong O3 bands at 0.3 & 0.6 um, - weak H2O bands in visible, - strong Rayleigh in blue, -low transmission below 10 km. At Paris molecule/exoplanet meeting, Enric Palle et al. showed a similar spectrum from a lunar eclipse, but with additional dimer features. Ref.: Kaltenegger & Traub 2009

22 National Aeronautics and Space Administration Transit Geometry z T( z, ) h is the effective height of an opaque atmosphere: h( ) = ∫ (1-T) dz So R( ) = R 0 + h( ) Note: The scale height is H ~ 1/R0 i.e., smaller for Super-Earths. 22

23 National Aeronautics and Space Administration Visible & near-infrared segment 23 Ref.: Kaltenegger & Traub 2009

24 National Aeronautics and Space Administration Bottom line: 1-transit SNRs for the nearest star Ref.: Kaltenegger & Traub 2009 Most likely transits will be at 10-20 pc, so 100 times fainter, & 10 times smaller SNR where SNR = N 1/2 (total)*2hR p /R 2 s

25 National Aeronautics and Space Administration Characterization by Imaging Spectroscopy

26 National Aeronautics and Space Administration Visible and Far-infrared Earth Spectra Refs.: (left) Woolf et al. 2002; (right) Kaltenegger et al. 2007, and Christensen & Pearl 1997

27 National Aeronautics and Space Administration DRM for 8-m telescope What characterization is possible with an 8-m telescope? 2 Design Reference Mission studies (Brown/Postman 2009; Stapelfeldt 2009) Parameters: wavelength = 760 nm (O2) SNR in continuum = 10 Spectral resolution = 70 Number of visits = 1 or several IWA = 3 or 2.1 lambda/D max integration time = 500,000 sec (6 days) read noise = 2 electrons dark noise = 0.001 elec/sec max exposure = 3600 sec number of zodis = 3 or 3 plus 10^-10 bkgd efficiencies = 0.29 or 0.08 PSF sharpness = 0.025 or 0.040 Earth contrast = 10^-10 coronagraph = band-limited Lyot (= VNC) & external Ref.: M. Postman et al. 2009, ATLAST study.

28 National Aeronautics and Space Administration DRM results: star counts An 8-m internal coronagraph could examine 100 star systems, 3 times each, in 5 years, using only 20% of the total observing time. Or, an 8-m telescope with external occulter could examine 85 systems. Ref.: M. Postman et al. 2009, ATLAST study.

29 National Aeronautics and Space Administration Spectroscopy inputs Spectral features listed in Des Marais et al 2002: species = O2, H2O, O3, vegetation, Rayleigh wavelength FWHM depth curves of growth cloud-free Earth Variability of features: spectral features: Traub & Turnbull, 2005 broad-band albedo: Seager 2004 Integral field spectrometer: resolution element = 760nm/70 = 11 nm Zodi background: Kuchner model 2009 Ref.: M. Postman et al. 2009, ATLAST study.

30 National Aeronautics and Space Administration Molecular column MassIR fluxIR colorVis flux Vis & IR spectra Eff temp. RadiusAlbedo Greenhouse warming Density of planet Surface gravity Surface & cloud reflectances Surface pressure Scale height of atmos. Lapse rate of atmos. Surface Temp. TPF-C TPF-C & TPF-ITPF-I SIM measured derived Type of planet Likelihood of plate tectonics & atmos retention Presence of H 2 O Cumulus, cirrus, ice, rock, sand, water implied Habitability of an Earth-like Planet

31 National Aeronautics and Space Administration Species SNRs & abundance uncertainties Ref.: M. Postman et al. 2009, ATLAST study.

32 National Aeronautics and Space Administration Visible spectra Near-IR spectra Infrared spectra Vegetation variation TPF-CTPF-ITPF-C derived implied Water, oxygen, carbon dioxide variations Cloud variation Surface spectrum variation Temperature variations Mass of atmosphere observed Orbital eccentricity Cloud height variations Large-scale weather patterns Obliquity Thermal time const of atmos Continents, oceans, ice areas SeasonsLength of day SIM Variability On An Earth-like Planet

33 National Aeronautics and Space Administration Summary of 8-m Spectroscopic Characterization We can detect signs of life (H2O, O2, O3, vegetation) on an Earth-twin with 6 days of integration around ~72 stars. We can detect variations of brightness, telling us about rotation, continents/oceans, and weather. We can push deeper with longer integrations.

34 National Aeronautics and Space Administration Overall Summary Detection: Transits will tell us the distribution function of Earths/Jupiters, but not the addresses of the nearest Earths & Super-Earths. Astrometry & RV can tell us the addresses of the nearest Earths. Zodi: We need to measure the zodi around nearby stars. Characterization: Transits will not characterize Earths or Super-Earths, unless we are very lucky. Direct optical imaging, with a large telescope, is needed to characterize nearby Earths, and to search for signs of life on them.

35 National Aeronautics and Space Administration Thank you!

36 National Aeronautics and Space Administration 36Traub Visible Earthshine Spectrum Validation Observed Earthshine, reflected from dark side of moon. Ref. Woolf, Smith, Traub, & Jucks, ApJ 574, p.430, 2002 Rayleigh Ozone O 3 Chlorophyll 720 nm edge Oxygen O 2 Water H 2 O Marked features show habitability & signs of life

37 National Aeronautics and Space Administration 37Traub Near-IR Earthshine Validation Ref.: Turnbull et al., ApJ, June 2006 Integrated- Earth spectrum Individual gas species All features show habitability & signs of life: H 2 O, O 2, CO 2, CH 4, cirrus, cumulus

38 National Aeronautics and Space Administration 38Traub Far-infrared spectrum of Earth: validation Integrated light of Earth, seen by TES enroute to Mars. CO 2, O 3, H 2 O dominate. CH 4, N 2 O ~hidden by 6-micron water. H2O CO2 O3 H2O T T T


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