1. Exoplanet Characterization with JWST Jeff Valenti (Space Telescope Science Institute)

2. Exoplanet Characterization with JWST
Investigators: Exoplanet community
Scientific Category: Exoplanets
Scientific Keywords:
Planet formation and evolution
Planetary atmospheres
Instruments: NIRSpec, MIRI, NIRCam
Proprietary Period: months
Requested Allocation: hours (6% of 5 years)
Talk structured like a proposal – scientific justification, state-of-the-art, need for JWST, feasibility, target sample.
Resolved planets are very interesting, but they were covered in detail yesterday.
Community discussion before cycle 1 to provide context for the TAC.
Obtain some non-proprietary data early to stimulate science.
DRAFT – please circulate!

3. Explore the diversity of planets
Key Questions
Explore the diversity of planets
Density, Composition, Stratospheres, Eccentricity, …
How do planets form/arrive so close to star?
Signatures of core-accretion processes
Migration and other dynamical processes
Processes that control planetary atmospheres
Cloud formation, non-equilibrium chemistry, etc.
Stellar irradiation
Origin of water
Top-level questions will still be with us when JWST launches.

4. Core-Accretion Scenario
Pollack et al. (1996, Icarus, 124, 62)
Phase III
Giant planet formation
via rapid gas accretion
Phase II
Envelope formation via
gradual gas accretion
Phase I
Core formation
via rapid accretion
of planetesimals
in “feeding zone”
Core + Envelope
This famous description of core-accretion is a proxy for the incredible theoretical work going on now.
Rapid core formation, cooling-limited gas accretion, runaway accretion.
Jupiter has smaller core, Phase II longer than disk lifetimes, ignores migration, …
Core Only
Isolation
Mass

5. Diverse Formation and Evolution
Low
Density
Exoplanet
Diversity
High
Density
Proxy for flood of observational constraints on models.
Planets are not a simple one-dimensional sequence.
Observables: planetary mass, radius, period, eccentricity, multiplicity, composition. Stellar mass, abundance, temperature, age
Initial disk properties. Chaos.
JWST will provide new observational constraints.
Core mass, composition,
migration, heating, …

6. Schematic of Transit and Eclipse Science
Planet thermal
emission appears
and disappears 10-3
Seager & Deming (2010, ARAA, 48, 631)
Cartoon of observational technique.
Transit
Learn about atmospheric
circulation from thermal
phase curves
Measure size of planet 10-2
See starlight transmitted
through planet atmosphere 10-4

7. Refine planet radius and hence planet density
Program Goals
Refine planet radius and hence planet density
Atmospheric composition: H, CH4, CO, CO2, H2O, …
Vertical temperature structure, effect of irradiation
Longitudinal temperature structure, heat distribution
Latitudinal temperature structure (grazing eclipses)
Measure small eccentricities transit/eclipse timing
Dependence on planet mass (Jupiter  super-Earth)
Constrain formation, evolution, and structure models
Sample stellar surface features (limb, spots, …)
Verify transits of terrestrial planets (e.g. Kepler)
Assess habitability?
Planetary exospheres?
List of JWST measurements.

8. Eclipse Spectroscopy and Photometry
IRS
IRS
MIPS
State-of-the-art measurement of thermal emission from a hot jupiter.
HD has most favorable contrast ratio.
Mid-IR from Spitzer. No more until JWST.
Near-IR with HST. R=40. Important species visible in models. Less clear in the data.
NICMOS
Model
HD b 2 3 4 10 20
Swain et al., Astro2010 white paper

9. GJ 1214b Transit Spectrum from the Ground
Bean et al. (2010, Nature, 468, 669)
VLT/FORS2
Why JWST? Because work from the ground is possible, but limited in diagnostic power and sensitivity.
CCD spectroscopy of planet very interesting planet discovered by Mearth.
The transmission spectrum of GJ 1214b compared to models Theoretical predictions of the transmission spectrum for GJ 1214b6 are shown for atmospheres with a solar composition (i.e., hydrogen-dominated; orange line and squares), a 100% water vapor composition (blue line and triangles), and a mixed composition of 70% water vapor and 30% molecular hydrogen by mass (green line and stars). The points for the models give the expected values for the transmission spectrum in each of the spectrophotometric channels. All of the features in the model spectra arise from variations in the water vapor opacity, with the exception of the feature at 890 nm that is due to methane absorption. The measurements and their uncertainties (black circles) were esti- mated by fitting the spectrophotometric data using five Markov chains with 2.5 x 105 steps. The uncertainties, which are valid for the relative values only, are the 1 σ confidence intervals of the resulting posterior distributions, and are consistent with the estimates we obtained from a residual permutation bootstrap analysis. The uncertainty in the absolute level is 0.11 R⊕, and is due mainly to the uncertainty in the host star mass. The data are consistent with the model for the water vapor atmosphere (χ2 = 5.6 for 10 degrees of freedom) and inconsistent with the model for the solar com- position model at 4.9 σ confidence (χ2 = 47.3). The predictions for a solar composition atmosphere with CH4 removed due to photodissociation (not shown) are equally discrepant with the data. The mixed water vapor and molecular hydrogen atmosphere model contains the most hydrogen pos- sible to still be within 1 σ (χ2 = 11.5) of the measurements. The data are furthermore consistent with a hydrogen-dominated atmosphere with optically thick clouds or hazes located above a height of 200 mbar (not shown). We obtain similar results when comparing the models to measurements obtained using smaller or larger channel sizes.

10. HD 189733b Thermal Emission from the Ground
NLTE
CH4 ?
Near-IR is possible from the ground, but limited in diagnostic power and sensitivity.
Controversy about apparent emission line.
Very difficult to measure water bands from the ground.
High-resolution should help, but current facilities are limited.
Swain et al. (2010, Nature, 463, 637)

11. JWST Instrument Configurations
eclipses
transits 7 2 4 64 2
imaging 10
15 dispersers that redundantly cover microns at four different resolutions.
assume one disperser per transit (no switching)
decide which gratings are best scientifically. prioritize wavelengths.
test which mode yields best precision, e.g. binned high resolution may be better than low resolution 33

12. Spectrum of a Planet Host
ETC simulation of brightest transiting planet host in the IR.
Saturates NIRSpec below 3 microns. Eclipse observation is possible.
Up-the-ramp sequence: reset-read-read yields duty cycle of 33%.
S/N per extracted pixel is 270 in 2.7 seconds. Detector will be programmed to repeat without pause.

13. Timeline of a Transit Observation
Light curve for one wavelength point in extracted spectrum.
Each point is one 2.7 sec integration ramp. There are 5500 integrations in this 4 hour visit.
Wall clock time is 5 hours, which is cost to observatory/TAC/observer.
Note pause due to event-driven operations and stabilization time.
Assume no grating change during observation to maintain thermal and electrical stability.
Different settings mean different transits.
0.9 second effective integration time with 2.7 second cadence (reset, read, read).
1400 integrations in 21 minutes between 2nd and 3rd contact
2400 integrations in 36 minutes pre-transit and post-transit
S/N=200 per extracted pixel in 1 integration.
S/N=6000 in ratio spectrum = transit / (pre+post)

14. Thermal Emission from a Hot Jupiter
Emission spectrum for the planet. Black points are simulated NIRSpec data (every 5 pixels binned).
Noise completely dominated by the now-subtracted host star spectrum.
Colored curves are models with different vertical opacity profiles in the atmosphere and longitudinal heat transfer efficiencies.
Vastly overconstrained. Will be trivial to detect flaws in the models.
Better resolved line profiles will allow detection of other species, constrain vertical temperature profile, etc.

15. Simulated MIRI Observations of HD 189733b
Simulated MIRI spectrum. Three MRS settings, so three transits. Still HD b.
Binning factor in blue at top. Increase binning factor at long wavelengths where planet is faint.
S/N in red per bin. Excellent! Need higher resolution models and better line data.
Planet is fainter than in NIR, but stellar noise is down too. Contrast ratio still improving.

16. GJ 1214 Sample observing sequence for a fainter M dwarf.
Still filling the pixel wells for efficiency (reset+9 reads = 80% efficiency) and cosmic ray ID.

17. Transit Spectrum of Habitable “Ocean Planet”
Now we move on to terrestrial, but not yet Earth-like planets, looking only at absorption during planetary transit.
Blue curve is a model from Ehrenreich et al. (2006) for an Earth-sized “ocean planet” transiting an M3V.
The small radius of the M dwarf, relative to G dwarfs, increases the depth of transit features.
The water vapor features have a depth of 50 parts per million, comparable to the slit loss variations we calculated earlier.
I’ve picked J=8, which is faint enough that such a transiting planet should exist, if eta_Earth is anything near unity.
Discovering small planets that transit M dwarfs is another matter.
The simulation assumes 10 transits observations, covering 0.7 hours before and after each 1.4 hour transit.

18. Thermal Emission versus Orbital Phase
HD b
1210 K
Peak temperature
precedes eclipse
by 16±6˚
970 K
0.979 transit depth
Knutson et al. (2007, Nature, 447, 183)
Famous plot directly showing longitudinal temperature profile.
Expensive to monitor a planet for 1-2 days, but will probably happen if long-term stability is adequate
Spitzer, 8 µm, 33 hours

19. Photometric Precision as Target Drifts
Sum of 5x1 pixels
Single
Pixel
Response profile vs. scan position of five adjacent pixels located along the y-direction for 1050 nm light. The scan is performed through the center of the five pixels. The response of each individual pixel (filled circles) is displayed along with the combined response (filled squares) of the five pixels. The rms fluctuation of the combined response from 20 to 70 mm is 1.02%.
Precise test of photometric precision in the lab requires proper calibration of nonlinearity, intra-pixel capacitance, etc.
Barron et al. (2007, PASP, 119, 466)
Charge Diffusion µm
Not JWST detector

20. 50 Good Targets Today… Want 50 Best for JWSTHD
149026 HD RV
Elektra
TESS
GJ 1214
Bright transiting exoplanets as of this morning, according to my favorite exoplanets.org web site.
Need 50 targets to study planet properties vs. mass, semi-major axis, stellar temperature, etc.
Have good targets, but better ones are waiting to be found.
Kepler
CoRot
HAT, WASP, XO, …

21. Transit Study of Cool Atmospheres
NIRCam
Transit
S/N
Transit Depth
(%)
Planet
Radius (RJ)
Orbit
Period
(d) a
(AU)
Star Mag (R)
Star Rad
(Rsun)
Star Teff
(K)
Teq
73.7
0. 74
1.13
17.86
0.141
11.35
1.32
6419
868
62.4
0. 64
0.75
125.6
0.499
12.39
0.94
5638
344
46.5
0. 47
22.3
0.165
12.20
1.66
6090
851
39.7
0. 40
0.91
75.1
0.4
11.71
1.44
6987
586
30.7
0. 31
0.59
9.43
0.089
11.58
1.065
5533
844
14.0
0. 14
0.62
90.5
0.42
534
Good targets from Kepler… better ones coming!
Extracted from Bill Borucki’s presentation on Monday. Data from Tome Greene.

22. Strawman Survey Program
Goal
Targets
Visits
Hours
Assess strategies 1+ 20
100
Jupiter Eclipse Survey 50 2
500
Jupiter Transit Survey 10
Cool Atmospheres
Neptune Atmospheres
1000
Super-Earth Atmospheres 40
400
Phase curves, Weather, … …
Assumes an average of 5 hours / visit