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

doi:10.1117/12.2561914

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 proceeding › Conference contribution

12 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 language	English (US)
Title of host publication	Adaptive Optics Systems VII
Publisher	SPIE
ISBN (Print)	9781510636835
DOIs	https://doi.org/10.1117/12.2561914
State	Published - Dec 13 2020

Bibliographical note

KAUST Repository Item: Exported on 2021-02-23

Access to Document

10.1117/12.2561914

https://repository.kaust.edu.sa/bitstream/10754/667543/1/114482L.pdf

Cite this

@inproceedings{b340ee5d4f514ca8aba7880c781c62df,

title = "Predictive learn and apply: MAVIS application-apply",

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.",

author = "Jesse Cranney and Hao Zhang and Nicolas Doucet and Fran{\c c}ois Rigaut and Damien Gratadour and Visa Korkiakoski and {De Don{\'a}}, Jos{\'e} and Yuxi Hong and Hatem Ltaief and Keyes, {David E.}",

note = "KAUST Repository Item: Exported on 2021-02-23",

year = "2020",

month = dec,

day = "13",

doi = "10.1117/12.2561914",

language = "English (US)",

isbn = "9781510636835",

booktitle = "Adaptive Optics Systems VII",

publisher = "SPIE",

}

TY - GEN

T1 - Predictive learn and apply: MAVIS application-apply

AU - Cranney, Jesse

AU - Zhang, Hao

AU - Doucet, Nicolas

AU - Rigaut, François

AU - Gratadour, Damien

AU - Korkiakoski, Visa

AU - De Doná, José

AU - Hong, Yuxi

AU - Ltaief, Hatem

AU - Keyes, David E.

N1 - KAUST Repository Item: Exported on 2021-02-23

PY - 2020/12/13

Y1 - 2020/12/13

N2 - 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.

AB - 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.

UR - http://hdl.handle.net/10754/667543

UR - https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11448/2561914/Predictive-learn-and-apply-MAVIS-application---apply/10.1117/12.2561914.full

UR - http://www.scopus.com/inward/record.url?scp=85100010237&partnerID=8YFLogxK

U2 - 10.1117/12.2561914

DO - 10.1117/12.2561914

M3 - Conference contribution

SN - 9781510636835

BT - Adaptive Optics Systems VII

PB - SPIE

ER -

Predictive learn and apply: MAVIS application-apply

Abstract

Bibliographical note

Access to Document

Other files and links

Fingerprint

Cite this