| Téléchargement | - Voir la version finale : Mitigating the nonlinearities in a pyramid wavefront sensor (PDF, 8.8 Mio)
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| DOI | Trouver le DOI : https://doi.org/10.1117/1.JATIS.9.4.049005 |
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| Auteur | Rechercher : Archinuk, Finn1; Rechercher : Hafeez, Rehan1; Rechercher : Fabbro, Sébastien1; Rechercher : Teimoorinia, Hossen1; Rechercher : Véran, Jean-Pierre1 |
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| Affiliation | - Conseil national de recherches du Canada. Herzberg en astronomie et en astrophysique
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| Format | Texte, Article |
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| Sujet | adaptive optics; machine learning; wavefront reconstruction; astronomy; wavefront errors; wavefront sensors; wavefronts; education and training; data modeling |
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| Résumé | For natural guide star adaptive optics (AO) systems, pyramid wavefront sensors (PWFSs) can provide a significant increase in sensitivity over the traditional Shack–Hartmann but at the cost of a reduced linear range. When using a linear reconstructor, nonlinearities result in wavefront estimation errors, which can have a significant impact on the image quality delivered by the AO system. We simulate a wavefront passing through a PWFS under varying observing conditions to explore the possibility of using a nonlinear machine learning model to estimate wavefront errors and compare with a linear reconstruction. We find significant potential improvements in delivered image quality even with computationally simple models, underscoring the need for further investigation of this approach. |
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| Date de publication | 2023-12-28 |
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| Maison d’édition | SPIE |
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| Dans | |
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| Langue | anglais |
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| Publications évaluées par des pairs | Oui |
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| Exporter la notice | Exporter en format RIS |
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| Signaler une correction | Signaler une correction (s'ouvre dans un nouvel onglet) |
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| Identificateur de l’enregistrement | c25bbc1b-8ba3-49c3-a7bc-06fbaf0eee1f |
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| Enregistrement créé | 2024-05-02 |
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| Enregistrement modifié | 2024-05-02 |
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