/WJs

Warm Jupiters population inference

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Hot Jupiters internal luminosity population inference

Hot Jupiters population inference based on coupling the observed properties of hot Jupiters to theoretical interior structure models.

This framework was developed and implemented for the paper Evidence of Three Mechanisms Explaining the Radius Anomaly of Hot Jupiters by Paula Sarkis et al. and submitted to A&A. The paper is being reviewed and available upon request.

About the code

The main goal of this code is to infer the internal luminosity of hot Jupiters based on coupling observations to theoretical models. We developed a hierarchical Bayesian model that allows us to make inferences on the population of hot Jupiters within a probabilistic framework. This framework also allows us to account for the uncertainties on the observed parameters.

The framework is divided into two parts:

1- Lower Level of the hierarchical model: Infers the internal luminosity of a single planet.

2- Upper Level of the hierarchical model: Inference at the population level

Repo Content

Code

The lower level of the probabilistic model is implemented in single.py and the upper level in population.py.

Data

data contains all the required data sets to run the code.

  • interpFn_*: previously interpolated functions of the theoretical models
  • all_planets-ascii.txt: the database used in our study
  • sys_HD_209458: an example of a dataset in order to run the SinglePlanetModel
  • *_chains.csv: population posterior samples for the different relations MLR, HEET, Tint-Teq, and Prcb-Teq using both priors.

Examples

All examples are applied to HD_209458.

single_planet_demo.ipynb: demonstrates how to use the code to infer the internal luminosity distribution of HD_209458.

single_planet_choice_of_prior.ipynb: shows how to use different priors for the internal luminosity at the lower level and its effect on the inference.

population_posterior_plots.ipynb: example code to reproduce some of the figures from the paper.

Dependencies