sara seager - lecture1 - mit
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Trent Schindler
Trent Schindler
Sara Seager Massachusetts Institute of
Technology
Exoplanet Atmospheres: From Discovery to Characterization
and Beyond
Known Planets 1995
Based on data compiled by J. Schneider
Known Planets 1996
Based on data compiled by J. Schneider
Known Planets 2000
Based on data compiled by J. Schneider
Known Planets 2005
Based on data compiled by J. Schneider
Known Planets 2010
Based on data compiled by J. Schneider
Exoplanet Atmospheres Discovery Characterization
Beyond
Transiting Planet Science
Primary Eclipse Measure size of planet See star’s radiation transmitted through the planet atmosphere
Secondary Eclipse See planet thermal radiation disappear and reappear
Learn about atmospheric circulation from thermal phase curves
10-2
10-4
10-3
Courtesy Josh Winn
See Seager and Mallen-Ornelas 2003
Identification of Atoms and Molecules
H2O and CH4 in transmission from HST Swain et al. (2008) See also Grillmair et al. 2008.
HD 189733b Na, H2O, CH4 , CO2, CO, hazes
HD 209458b Na, H2O, CH4, CO, CO2, H Ly α
Day-Night Temperature Variation
NASA/ESA/G. Bacon Spitzer Space Telescope
Day-Night Temperature Variation
HD 189733
HD 189733b Knutson et al. 2007
HAT-P-7b Borucki et al. 2009
Thermal Phase Curves
HD 189733
HD 189733b Knutson et al. 2007
Hottest regions are shifted away from the substellar point are interpreted as advection by a prograde superrotating equatorial jet.
No model yet explains or predicts the westward-shifted cold spot
Variability
Madhusudhan and Seager, 2009
Data from: Swain et al. 2008, Charbonneau et al. 2008, Grillmair et al. 2008
Variability: CO2
From VPL website
10-18
10-18
10-21
10-21
10-21
A Comment on Data
Courtesy F. Pont
Data from Pont et al. 2008, Swain et al. 2008 Tinetti et al. 2007, Beaulieu et al. 2008, 2009, Desert et al. 2009. Figure courtesy Pont.
Disagreement in the literature in Spitzer data is gradually being resolved over time, due to understanding different approaches to systematics’ removal.
Tran
sit R
adiu
s (R
p/R*)
8 5 2 1 0.6 Wavelength (µm)
Identification of molecules Day-night temperature gradients Variability at 2-σ level Atmospheric escape Hot Jupiters are dark
Summary of Atmosphere Highlights
There is real data on exoplanet atmospheres. It may be limited, but many people are modeling the data
Exoplanet Atmospheres Discovery Characterization
Highlights Model Constraints
Beyond
Exoplanet Atmosphere Models
+
Get a recipe
Fit the data
Vary ingredients
=
Everything other than g and F*
Exoplanet atmosphere modeling is like cooking – S. Aigrain
Exoplanet Atmosphere Models
Previously unanswered questions • What is the “best-fit” model? • How is the best-fit quantified? • Is the “best-fit” model unique? • If the best-fit is not unique, what are the allowed ranges of
model parameters?
Charbonneau et al. 2008 Grillmair et al. 2008 Swain et al. 2008
Hot Jupiter Radiative Transfer
• Stellar irradiation • Intrinsic energy source
Boundary Conditions
Chemical Equilibrium
• Day-night redistribution: • Unknown opacity: • Composition ( ) + clouds, etc.
Model Free Parameters • No longer “self consistent” models • Computation time and convergence • Just a few models are run
Caveats
1D, plane parallel, LTE
€
dIλdτλ
= Iλ − Sλ
κλ Jλ − Sλ( )0
∞
∫ dλ = 0
dTdz
= −γ −1γ
µgkB
dPdz
= −ρg
P =ρkBT
µ
A Temperature and Abundance Retrieval Technique
Run millions of models to constrain T and abundances Madhusudhan and Seager, 2009 N. Madhusudhan PhD 2009
Atmosphere Temperature Profiles
HD 189733
Madhusudhan and Seager 2009
Grillmair et al. 2008 Charbonneau et al. 2008 Deming et al. 2006 Swain et al. 2008
Madhusudhan and Seager 2009
Result #1 Variability
Variability: True uncertainty in the data? Then no useful limits on molecular abundances Or the atmospheres are variable both in the energy redistribution state and in the concentrations of molecular abundances
Result #2 Quantitative Abundances
HD 189733 b Madhusudhuan and Seager 2009
Spitzer/IRAC
Result #2 Quantitative Abundances
HD 189733 b Madhusudhuan and Seager 2009
Spitzer/IRAC + HST/NICMOS
Result #3 Challenge to Thermal Inversion
Evidence for thermal inversion difficult to assess for most exoplanets, assuming 2 σ data uncertainties and/or a range of molecular abundances Madhusudhan and Seager, submitted to ApJ
Result #4 Lack of CH4 on the Hot Neptune GJ 436b
Stevenson et al. Nature 2010 Madhusudhan and Seager, submitted to ApJ
We have moved beyond discovery to characterization several robust observational highlights a quantitative tool for atmospheres
Atmosphere Summary
Exoplanet Atmospheres Discovery Characterization Beyond
de Mooij & Snellen 2009
Ground-Based Advances • Very Hot Jupiter secondary eclipses • Directly imaged Jupiters • Search for transiting super Earths
β Pictoris: New Planet
A composite image of the planet from 2003 and 2009 and the disk. Lagrange et al., Science 2010 (today)
The M Star Opportunity
Semi-Major Axis
Sun
K2
M6
Probability = 1/200 P = 365 days Transit depth = 10-4
Probability = 1/140 P = 177 days Transit depth = 1.25 x10-4
Probability = 1/50 P = 13 days Transit depth = 0.001 Tidally-locked
John E. Kauffman used with permission
Radiative transfer
Atmospheric Composition
Chemical equilibrium/disequilibrium
Photochemistry
Atmospheric escape
Atmospheric circulation
Connection with observations
Clouds
JWST = TPF?
Lecture #3 Wed. June 23
Earth’s Spectrum
Turnbull et al. 2007
Pearl and Christensen 1997
Lecture #3 Wed. June 23
• Discovery – Hundreds of exoplanets are known – Atmosphere measurements for over dozens
• Characterization – A few robust observational highlights show that exoplanet
atmospheres are being studied in detail – Models are required to solidify interpretation
• Beyond – Direct imaging of hot young planets – The M star opportunity: searching for super Earths orbiting close to low-mass stars and planned characteriztiaon with JWST
Summary
Trent Schindler
Trent Schindler
Seager & Deming, Annual Reviews of Astronomy and Astrophysics, 09/2010
Madhusudhan and Seager ApJ, 2009
Seager, “Exoplanet Atmospheres: Physical Processes” 2010, Princeton University Press
References