Hands-on Session: Detection and Spectroscopic Characterization of Transiting Exoplanets with the James Webb Space Telescope

Transcription

1 Hands-on Session: Detection and Spectroscopic Characterization of Transiting Exoplanets with the James Webb Space Telescope Nikole K. Lewis JWST Project Scientist Space Telescope Science Institute

2 Why Transiting Extrasolar Planets? See cyclical variations in brightness of planet Secondary Eclipse See thermal radiation and reflected light from planet disappear and reappear Figure Credit: S. Seager Transit See radiation from star transmitted through the planet s atmosphere Currently more than 3000 confirmed transiting extrasolar planets!

3 Transits Na K H 2 O Sing et al. (2016) WASP-17b 65 WASP-39b 60 2 Rp 2 R ~ 0.01% to 1% Rp R 2 H Relative altitude in scale heights z(λ)/h eq HD209458b WASP-19b HAT-P-1b WASP-31b WASP-12b HAT-P-12b Probes Pressures mbar Near Planetary Limb HD189733b WASP-6b Wavelength (µm)

4 In the Era of Webb. The Astrophysical Journal, 817:17 (22pp), 2016 January 20 Greene et al. Figure 4. Final simulated transmission spectra of the transmission models shown in Figure 2. The Tr ( Rp, R * ) 2 spectra are for a single transit with equal time on the star alone for each of the four instrument modes (Table 4). Spectra have been been binned to resolution R 100 (hot Jupiter, warm Neptune, warm sub-neptune; see Section 4.2) as used for all retrievals or R = 35 (cool super-earth) for display purposes only. The simulated spectra include a noise instance and are presented as colored curves. The black error bars denote 1σ of noise composed of random and systematic components. Dashed lines show the wavelength range boundaries of the chosen NIRISS, NIRCam, and MIRI instrument modes. The data used to create this figure are available. Greene et al. (2016)

5 In the Era of Webb. The Astrophysical Journal, 817:17 (22pp), 2016 January 20 Greene et al. Figure 6. Retrieved and derived quantities of the hot Jupiter planet. Retrieved volume mixing ratios are shown for each molecular species. Marginalized posterior histogram shadings are color-coded by instrument mode and therefore wavelengths of spectra used for retrievals. Priors are indicated by blue horizontal dashed lines for the retrieved molecules. The resulting distributions for the derived quantities log(c/o) and [Fe/H] from the gas priors are more complex distribution functions (shown in blue). True values are indicated by vertical dashed black lines for all quantities. Greene et al. (2016)

6 The Near Infrared Imager and Slitless Spectrograph Single Object Slitless Spectroscopy mode: NIRISS SOSS 8 6 Relative Intensity (%) Spatial Axis (Pixels) Beichman et al. (2015)

7 The participants in this hands-on exercise will complete a three-step process to detect and characterize the planet in their JWST NIRISS SOSS data 1. Work with high-level data products from the JWST pipeline to find the planetary transit as a function of wavelength. 2. Use MCMC-based fitting tools to measure changes in the planetary radius with wavelength to find the planetary spectrum from 0.6 to 2.5 microns. 3. Determine the atmospheric composition of the planet using spectroscopic retrieval tools.

8 Work with high-level data products from the JWST pipeline to find the planetary transit as a function of wavelength.

9 Use MCMC-based fitting tools to measure changes in the planetary radius with wavelength to find the planetary spectrum from 0.6 to 2.5 microns. batman: BAsic Transit Model calculation in Python Laura Kreidberg, Kreidberg (2015)

10 Determine the atmospheric composition of the planet using spectroscopic retrieval tools. Atmospheric Composition Constraints

11 Goals of Transit Hands-on Session Get participants familiar with the types of data products that will be produced by JWST pipeline and delivered to MAST archive. Help participants understand the basics of transit data and how to extract a planetary spectrum given spectroscopic time-series observations. Guide participants through a robust process for determining exoplanet atmospheric composition. Introduce participants to python, which will be the language in which all JWST pipeline modules, tools, etc. will be built. Questions?