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

Exoplanet Characterization with JWST Investigators: Exoplanet community Scientific Category: Exoplanets Scientific Keywords: Planet formation and evolution Planetary atmospheres Instruments: NIRSpec, MIRI, NIRCam Proprietary Period: 0-12 months Requested Allocation: 2600 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!

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.

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

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, …

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

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.

Eclipse Spectroscopy and Photometry IRS IRS MIPS State-of-the-art measurement of thermal emission from a hot jupiter. HD 189733 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 189733b 2 3 4 10 20 Swain et al., Astro2010 white paper

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.

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)

JWST Instrument Configurations eclipses transits 7 2 4 64 2 imaging 10 15 dispersers that redundantly cover 0.6-28 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

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.

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)

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.

Simulated MIRI Observations of HD 189733b Simulated MIRI spectrum. Three MRS settings, so three transits. Still HD 189733b. 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.

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.

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.

Thermal Emission versus Orbital Phase HD 189733 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

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 H2RG @ 1.05 µm Not JWST detector

50 Good Targets Today… Want 50 Best for JWST HD 149026 HD 189733 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, …

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.

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