Presentation + Paper
28 August 2024 Generic data reduction for nulling interferometry package: the grip of a single data reduction package on all the nulling interferometers
Author Affiliations +
Abstract
Nulling interferometry is a powerful observing technique to reach exoplanets and circumstellar dust at separations too small for direct imaging with single-dish telescopes and too large for indirect methods. With near-future instrumentation, it bears the potential to detect young, hot planets near the snow lines of their host stars. A future space mission could detect and characterize a large number of rocky, habitable-zone planets around nearby stars at thermal-infrared wavelengths. The null self-calibration is a method aiming at modelling 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. This statistical approach opens the possibility of designing a GPU-based Python package to reduce the data from any of these instruments, by simply providing the data and a simulator of the instrument. GRIP is a toolbox to reduce nulling and interferometric data based on the statistical self-calibration method. In this article, we present the main features of GRIP as well as applications on real data.
Conference Presentation
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Marc-Antoine Martinod, Denis Defrère, Romain Laugier, Steve Ertel, Olivier Absil, Barnaby Norris, Germain Garreau, and Bertrand Mennesson "Generic data reduction for nulling interferometry package: the grip of a single data reduction package on all the nulling interferometers", Proc. SPIE 13095, Optical and Infrared Interferometry and Imaging IX, 130951A (28 August 2024); https://doi.org/10.1117/12.3017506
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KEYWORDS
Nulling interferometry

Calibration

Equipment

Histograms

Monte Carlo methods

Device simulation

Stars

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