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

doi:10.1117/12.2561914

13 December 2020 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

Author Affiliations +

Proceedings Volume 11448, Adaptive Optics Systems VII; 114482L (2020) https://doi.org/10.1117/12.2561914
Event: SPIE Astronomical Telescopes + Instrumentation, 2020, Online Only

Conference Poster

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.

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Jesse Cranney, Hao Zhang, Nicolas Doucet, François Rigaut, Damien Gratadour, Visa Korkiakoski, José De Doná, Yuxi Hong, Hatem Ltaief, and David Keyes "Predictive learn and apply: MAVIS application - apply", Proc. SPIE 11448, Adaptive Optics Systems VII, 114482L (13 December 2020); https://doi.org/10.1117/12.2561914

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