# Juliet: a versatile modelling tool for transiting and non-transiting exoplanetary systems

## TL;DR

juliet is a comprehensive software tool designed for analyzing transiting and non-transiting exoplanetary systems, integrating multiple data types and models with Bayesian methods for thorough parameter estimation and model comparison.

## Contribution

It introduces a versatile, publicly available tool that combines transit, radial-velocity, and Gaussian Process modeling with nested sampling for exoplanet system analysis.

## Key findings

- Supports simultaneous multi-instrument data analysis
- Enables fitting of shared hyperparameters in Gaussian Processes
- Provides scalable multi-threaded computation

## Abstract

Here we present juliet, a versatile tool for the analysis of transits, radial-velocities, or both. juliet is built over many available tools for the modelling of transits, radial-velocities and stochastic processes (here modelled as Gaussian Processes; GPs) in order to deliver a tool/wrapper which can be used for the analysis of transit photometry and radial-velocity measurements from multiple instruments at the same time, using nested sampling algorithms which allows it to not only perform a thorough sampling of the parameter space, but also to perform model comparison via bayesian evidences. In addition, juliet allows to fit transiting and non-transiting multi-planetary systems, and to fit GPs which might share hyperparameters between the photometry and radial-velocities simultaneously (e.g., stellar rotation periods), which might be useful for disentangling stellar activity in radial-velocity measurements. Nested Sampling, Importance Nested Sampling and Dynamic Nested Sampling is performed with publicly available codes which in turn give juliet multi-threading options, allowing it to scale the computing time of complicated multi-dimensional problems. We make juliet publicly available via GitHub.