Wavelet methods in multi-conjugate adaptive optics
Tapio Helin, Mykhaylo Yudytskiy · 2016
ABSTRACT. The next generation ground–based telescopes rely heavily on adap-tive optics for overcoming the limitation of atmospheric turbulence. In the future adaptive optics modalities, like multi–conjugate adaptive optics (MCAO), at-mospheric 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 imag-ing. We introduce a novel reconstruction method for the atmospheric tomog-raphy problem and demonstrate its performance and flexibility in the context of MCAO. Our method is based on using locality properties of compactly sup-ported wavelets, both in the spatial and frequency domain. 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 Ob-servatory. 1.