A1 Journal article (refereed), original research

Wavelet methods in multi-conjugate adaptive optics

Open Access publication

Publication Details

Authors: Helin Tapio, Yudytskiy Mykhaylo

Publisher: IOP Publishing: Hybrid Open Access

Publication year: 2013

Language: English

Related journal or series: Inverse Problems

Journal name in source: Inverse Problems

Volume number: 29

Issue number: 8

ISSN: 0266-5611

eISSN: 1361-6420

JUFO level of this publication: 2

Digital Object Identifier (DOI): http://dx.doi.org/10.1088/0266-5611/29/8/085003

Permanent website address: https://api.elsevier.com/content/abstract/scopus_id/84881399744

Open Access: Open Access publication

Location of the parallel saved publication: https://arxiv.org/abs/1302.3734


The next generation ground-based telescopes rely heavily on adaptive
optics for overcoming the limitation of atmospheric turbulence. In the
future adaptive optics modalities, like multi-conjugate adaptive optics
(MCAO), atmospheric tomography is the major mathematical and
computational challenge. In this severely ill-posed problem, a fast and
stable reconstruction algorithm is needed that can take into account
many real-life phenomena of telescope imaging. We introduce a novel
reconstruction method for the atmospheric tomography problem and
demonstrate its performance and flexibility in the context of MCAO. Our
method is based on using locality properties of compactly supported
wavelets, both in the spatial and frequency domains. The reconstruction
in the atmospheric tomography problem is obtained by solving the
Bayesian MAP estimator with a conjugate-gradient-based algorithm. An
accelerated algorithm with preconditioning is also introduced. Numerical
performance is demonstrated on the official end-to-end simulation tool
OCTOPUS of European Southern Observatory.

Last updated on 2020-28-09 at 13:15