Predictive learn and apply: MAVIS application-apply

Jesse Cranney, Hao Zhang, Nicolas Doucet, François Rigaut, Damien Gratadour, Visa Korkiakoski, José De Doná, Yuxi Hong, Hatem Ltaief, David E. Keyes

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

The Learn and Apply tomographic reconstructor coupled with the pseudo open-loop control scheme shows promising results in simulation for multi-conjugate adaptive optics systems. We motivate, derive, and demonstrate the inclusion of a predictive step in the Learn and Apply tomographic reconstructor based on frozen-flow turbulence assumption. The addition of this predictive step provides an additional gain in performance, especially at larger wave-front sensor exposure periods, with no increase of online computational burden. We provide results using end-to-end numerical simulations for a multi-conjugate adaptive optics system for an 8m telescope based on the MAVIS system design.
Original languageEnglish (US)
Title of host publicationAdaptive Optics Systems VII
PublisherSPIE
ISBN (Print)9781510636835
DOIs
StatePublished - Dec 13 2020

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