CONAN: A Python package for modeling lightcurve and radial velocity data of exoplanetary systems

TL;DR

CONAN is an open-source Python package that offers a unified Bayesian framework for analyzing various exoplanet datasets, including light curves and radial velocities, to derive system parameters.

Contribution

It introduces a comprehensive tool that simultaneously models multiple types of exoplanet data with flexible detrending options, enhancing analysis consistency.

Findings

Enables combined analysis of photometric and radial velocity data.

Supports flexible detrending methods like Gaussian Processes and splines.

Provides a unified Bayesian approach for exoplanet system characterization.

Abstract

We present CONAN (COde for exoplaNet ANalysis), an open-source Python package for comprehensive analyses of exoplanetary systems. It provides a unified Bayesian framework to simultaneously analyze diverse exoplanet datasets to derive global system parameters. CONAN allows to consistently model photometric transit light curves, occultations, phase curves, and radial velocity measurements, while detrending each dataset with any combination of parametric, sinusoidal, Gaussian Processes, and spline models.