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 Keyes

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Citations (Scopus)

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
Title of host publicationAdaptive Optics Systems VII
EditorsLaura Schreiber, Dirk Schmidt, Elise Vernet
PublisherSPIE
ISBN (Electronic)9781510636835
DOIs
Publication statusPublished - 2020
EventAdaptive Optics Systems VII 2020 - Virtual, Online, United States
Duration: 14 Dec 202022 Dec 2020

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume11448
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceAdaptive Optics Systems VII 2020
Country/TerritoryUnited States
CityVirtual, Online
Period14/12/2022/12/20

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