Predictive learn and apply: MAVIS application-apply

Title: Predictive learn and apply: MAVIS application-apply
Creator: Cranney, Jesse; Zhang, Hao; Doucet, Nicolas; Rigaut, Francois; Gratadour, Damien; Korkiakoski, Visa; De Dona, Jose; Hong, Yuxi; Ltaief, Hatem; Keyes, David
Relation: SPIE Astronomical Telescopes + Instrumentation. Proceedings of Volume 11448, Adaptive Optics Systems VII (online 14-22 December, 2020)
Publisher Link: http://dx.doi.org/10.1117/12.2561914
Publisher: SPIE Press
Resource Type: conference paper
Date: 2020
Description: 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.
Subject: adaptive Optics; learn and apply; MAVIS; MCAO; POLC; pedictive control
Identifier: http://hdl.handle.net/1959.13/1443209
Identifier: uon:41916
Identifier: ISBN:9781510636835
Language: eng
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