Generic data reduction for nulling interferometry package: the grip of a single data reduction package on all the nulling interferometers
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arXiv
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| Autori principali: | , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| author | Martinod, Marc-Antoine Defrère, Denis Laugier, Romain Ertel, Steve Absil, Olivier Norris, Barnaby Garreau, Germain Mennesson, Bertrand |
| author_facet | Martinod, Marc-Antoine Defrère, Denis Laugier, Romain Ertel, Steve Absil, Olivier Norris, Barnaby Garreau, Germain Mennesson, Bertrand |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_08802 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Generic data reduction for nulling interferometry package: the grip of a single data reduction package on all the nulling interferometers Martinod, Marc-Antoine Defrère, Denis Laugier, Romain Ertel, Steve Absil, Olivier Norris, Barnaby Garreau, Germain Mennesson, Bertrand Instrumentation and Methods for Astrophysics 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. |
| title | Generic data reduction for nulling interferometry package: the grip of a single data reduction package on all the nulling interferometers |
| topic | Instrumentation and Methods for Astrophysics |
| url | https://arxiv.org/abs/2407.08802 |