CONAN: The Swiss Army knife for exoplanet hunters - a Bayesian framework that simultaneously models transits, phase curves, and radial velocities to unlock alien world secrets

In the golden age of exoplanet discovery, astronomers are drowning in data from multiple instruments and observing modes. Each transit lightcurve, radial velocity measurement, and phase curve observation tells part of a planet’s story, but piecing together these heterogeneous datasets has been like solving a cosmic jigsaw puzzle with pieces from different boxes. Enter CONAN - not the barbarian, but the sophisticated Bayesian framework that’s taming this data deluge.

Developed at the Observatory of Geneva, CONAN excels at simultaneous modeling of diverse observational phenomena. It seamlessly handles photometric transits, occultations, and phase curves while incorporating complex effects like ellipsoidal variations and Doppler beaming. The framework supports multi-planet systems, transit timing variations (TTVs), and transmission spectroscopy analysis. What sets it apart is its flexible detrending arsenal - from polynomial baselines to multi-dimensional Gaussian processes and 2-D splines - ensuring that instrumental systematics don’t mask genuine planetary signals.

With Jupyter notebook examples spanning systems from WASP-127 to TOI-469, CONAN democratizes advanced exoplanet analysis for researchers worldwide. Whether you’re characterizing a puffy hot Jupiter’s atmospheric composition through transmission spectroscopy or unraveling the orbital dynamics of a multi-planet system, this open-source toolkit transforms months of custom coding into streamlined, reproducible science.

⭐ Stars: 6
💻 Language: Jupyter Notebook
🔗 Repository: titans-ge/CONAN