GRIP: a generic data reduction package for nulling interferometry

Nulling interferometry is a powerful observing technique to study exoplanets and circumstellar dust at separations too small for direct imaging with single-dish telescopes. With recent photonic developments and the near-future ground-based instrumental projects, it bears the potential to detect young giant planets near the snow lines of their host stars. The observable quantity of a nulling interferometer is called the null depth, and its precise measurement and calibration remain challenging against instrument and atmospheric noise. Null self-calibration is a method aiming to model the statistical distribution of the nulled signal. It has proven to be more sensitive and accurate than average-based data reduction methods in nulling interferometry. The variety of existing and upcoming nullers raises the issue of consistency of the calibration process, the structure of the data, and the ability to reduce archived data in the long term. It has also led to many different implementations of the null self-calibration method. We introduce GRIP: the first open-source toolbox to reduce nulling data with enhanced statistical self-calibration methods from any nulling interferometric instrument within a single and consistent framework. Astrophysical results show good consistency with two published Guided-Light Interferometric Nulling Technology and Large Binocular Telescope Interferometer datasets and confirm nulling precision down to a few 10−4.