Leveraging planetary multiplicity to get better fits for exoplanet radii, in order to better understand the radius valley and planetary compositions.
One approach to probing planetary interiors is achieving higher precision of bulk planetary parameters, particularly planetary radius measurements. Precise radius measurements for transiting planets are difficult to obtain due to degeneracies between the transit depth, impact parameter, and limb-darkening coefficients. These degeneracies can be broken by considering multi-transiting planetary systems, since they share the same stellar radius and limb-darkening coefficients!
This photodynamical model is a pipeline that uses the exoplanet, lightkurve, and PyMC3 packages to fit Kepler systems for the density of the host star, impact parameters, limb-darkening coefficients, and planet-to-star radius ratios all simultaneously. An earlier iteration of this project was first initiated by Tom Wagg. Thank you to both my advisor Professor Eric Agol (University of Washington) for his guidance and to Tom!
First, use git to clone this repository where you'd like it on your local machine.
git clone https://github.com/gsuissa/improving-exoplanet-radii.git
cd improving-exoplanet-radii
Then, make sure you have the correct packages installed. Using conda:
conda env create --file environment.yml
It might take a while for conda to solve the environment. The file environment_exact.yml is also available for reference.
You can enter your new environment with:
conda activate improving-exoplanet-radii
Now you can explore the Jupyter notebooks! helpers/ contain the helper functions I made to help fit systems.