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| Main Authors: | , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2409.13126 |
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| _version_ | 1866910613885681664 |
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| author | Skaf, Nour Jensen-Clem, Rebecca Hunter, Aaron Guyon, Olivier Deo, Vincent Hinz, Phil Cetre, Sylvain Chambouleyron, Vincent Fowler, J. Sengupa, Aditya Salama, Maissa Males, Jared McEwen, Eden Douglas, Ewan S. Van Gorkom, Kyle Por, Emiel Lucas, Miles Ferreira, Florian Sevin, Arnaud Bowens-Rubin, Rachel Cranney, Jesse Calvin, Ben |
| author_facet | Skaf, Nour Jensen-Clem, Rebecca Hunter, Aaron Guyon, Olivier Deo, Vincent Hinz, Phil Cetre, Sylvain Chambouleyron, Vincent Fowler, J. Sengupa, Aditya Salama, Maissa Males, Jared McEwen, Eden Douglas, Ewan S. Van Gorkom, Kyle Por, Emiel Lucas, Miles Ferreira, Florian Sevin, Arnaud Bowens-Rubin, Rachel Cranney, Jesse Calvin, Ben |
| contents | Real-time control (RTC) is pivotal for any Adaptive Optics (AO) system, including high-contrast imaging of exoplanets and circumstellar environments. It is the brain of the AO system, and what wavefront sensing and control (WFS\&C) techniques need to work with to achieve unprecedented image quality and contrast, ultimately advancing our understanding of exoplanetary systems in the context of high contrast imaging (HCI). Developing WFS\&C algorithms first happens in simulation or a lab before deployment on-sky. The transition to on-sky testing is often challenging due to the different RTCs used. Sharing common RTC standards across labs and telescope instruments would considerably simplify this process. A data architecture based on the interprocess communication method known as shared memory is ideally suited for this purpose. The CACAO package, an example of RTC based on shared memory, was initially developed for the Subaru-SCExAO instrument and now deployed on several benches and instruments. This proceeding discusses the challenges, requirements, implementation strategies, and performance evaluations associated with integrating a shared memory-based RTC. The Santa Cruz Extreme AO Laboratory (SEAL) bench is a platform for WFS\&C development for large ground-based segmented telescopes. Currently, SEAL offers the user a non-real-time version of CACAO, a shared-memory based RTC package initially developed for the Subaru-SCExAO instrument, and now deployed on several benches and instruments. We show here the example of the SEAL RTC upgrade as a precursor to both RTC upgrade at the 3-m Shane telescopes at Lick Observatory (Shane-AO) and a future development platform for the Keck II AO. This paper is aimed at specialists in AO, astronomers, and WFS\&C scientists seeking a deeper introduction to the world of RTCs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_13126 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Real-time control and data standardization on various telescopes and benches Skaf, Nour Jensen-Clem, Rebecca Hunter, Aaron Guyon, Olivier Deo, Vincent Hinz, Phil Cetre, Sylvain Chambouleyron, Vincent Fowler, J. Sengupa, Aditya Salama, Maissa Males, Jared McEwen, Eden Douglas, Ewan S. Van Gorkom, Kyle Por, Emiel Lucas, Miles Ferreira, Florian Sevin, Arnaud Bowens-Rubin, Rachel Cranney, Jesse Calvin, Ben Instrumentation and Methods for Astrophysics Real-time control (RTC) is pivotal for any Adaptive Optics (AO) system, including high-contrast imaging of exoplanets and circumstellar environments. It is the brain of the AO system, and what wavefront sensing and control (WFS\&C) techniques need to work with to achieve unprecedented image quality and contrast, ultimately advancing our understanding of exoplanetary systems in the context of high contrast imaging (HCI). Developing WFS\&C algorithms first happens in simulation or a lab before deployment on-sky. The transition to on-sky testing is often challenging due to the different RTCs used. Sharing common RTC standards across labs and telescope instruments would considerably simplify this process. A data architecture based on the interprocess communication method known as shared memory is ideally suited for this purpose. The CACAO package, an example of RTC based on shared memory, was initially developed for the Subaru-SCExAO instrument and now deployed on several benches and instruments. This proceeding discusses the challenges, requirements, implementation strategies, and performance evaluations associated with integrating a shared memory-based RTC. The Santa Cruz Extreme AO Laboratory (SEAL) bench is a platform for WFS\&C development for large ground-based segmented telescopes. Currently, SEAL offers the user a non-real-time version of CACAO, a shared-memory based RTC package initially developed for the Subaru-SCExAO instrument, and now deployed on several benches and instruments. We show here the example of the SEAL RTC upgrade as a precursor to both RTC upgrade at the 3-m Shane telescopes at Lick Observatory (Shane-AO) and a future development platform for the Keck II AO. This paper is aimed at specialists in AO, astronomers, and WFS\&C scientists seeking a deeper introduction to the world of RTCs. |
| title | Real-time control and data standardization on various telescopes and benches |
| topic | Instrumentation and Methods for Astrophysics |
| url | https://arxiv.org/abs/2409.13126 |