Adaptive optics real-time control with the compute and control for adaptive optics (Cacao) software framework
Name:
Adaptive_optics_real_time_control_with_the_compute_and_control_for_adaptive_optics__CACAO__software_framework.pdf
Size:
2.606Mb
Format:
PDF
Description:
Accepted manuscript
Type
Conference PaperAuthors
Guyon, OlivierSevin, Arnaud
Ferreira, Florian
Ltaief, Hatem

Males, Jared
Deo, Vincent
Gratadour, Damien
Cetre, Sylvain
Martinache, Frantz
Lozi, Julien
Vievard, Sebastien
Fruitwala, Neelay
Bos, Steven
Skaf, Nour
KAUST Department
Extreme Computing Research CenterComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Date
2020-12-13Permanent link to this record
http://hdl.handle.net/10754/667666
Metadata
Show full item recordAbstract
The Compute and control for adaptive optics (Cacao) is an open source software package providing a flexible framework for deploying real-time adaptive optics control. Cacao leverages CPU and GPU computational resources to meet the demands of modern AO systems with thousands of degrees of freedom running at kHz speed or faster. Cacao adopts a modular approach, where individual processes operate over a standardized data stream stucture. Advanced control loops integrating multiple sensors and DMs are built by assembling multiple such processes. High-level constructs are provided for sensor fusion, where multiple sensors can drive a single physical DM. The common data stream format is at the heart of Cacao, holding data content in shared memory and timing information as semaphores. Cacao is currently in operation on the general-purpose Subaru AO188 system, the SCExAO and MagAOX extreme-AO instruments. Its data stream format has been adopted at Keck, within the COMPASS AO simulation tool, and in the COSMIC modular RTC platform. We describe Cacao's software architecture and toolset, and provide simple examples for users to build a real-time control loop. Advanced features are discussed, including on-sky results and experience with predictive control and sensor fusion. Future development plans will include leveraging machine learning algorithms for real-time PSF calibration and more optimal AO control, for which early on-sky demonstration will be presented.Citation
Guyon, O., Sevin, A., Ferreira, F., Ltaief, H., Males, J. R., Deo, V., … Skaf, N. (2020). Adaptive optics real-time control with the compute and control for adaptive optics (Cacao) software framework. Adaptive Optics Systems VII. doi:10.1117/12.2562822Sponsors
Developers of the Cacao software package receive funding from the National Science Foundation (MagAO-X project), the Japanese Society for the Promotion of Science (SCExAO project), the Japanese NINS Astrobiology Center, and the European Union (project Green Flash). LDFC development at SCExAO is supported by the NASA Strategic Astrophysics Technology (SAT) Program grant 80NSSC19K0121. Development of advanced wavefront control algorithms with Cacao is supported by NASA grant 80NSSC19K0336. The development of SCExAO was supported by the Japan Society for the Promotion of Science (Grant-in-Aid for Research #23340051, #26220704, #23103002, #19H00703 & #19H00695), the Astrobiology Center of the National Institutes of Natural Sciences, Japan, the Mt Cuba Foundation and the director’s contingency fund at Subaru Telescope. The authors wish to recognize and acknowledge the very significant cultural role and reverence that the summit of Maunakea has always had within the indigenous Hawaiian community. We are very fortunate to have the opportunity to conduct observations from this mountain.Publisher
SPIE-Intl Soc Optical EngConference/Event name
Adaptive Optics Systems VII 2020ISBN
9781510636835ae974a485f413a2113503eed53cd6c53
10.1117/12.2562822