A Computationally Efficient Wavefront Reconstructor for Simulations of Multi-Conjugate Adaptive Optics on Giant Telescopes
Brent L. Ellerbroek
Gemini Observatory, 670 N. A'ohoku Pl., Hilo, HI 96720
L. Gilles
Michigan Technical University, Dept. of Electrical and Computer Engineering, Houghton, MI 49931-1295
C. R. Vogel
Montana State University, Dept. of Mathematical Sciences, Bozeman, MT 59717-2400
Abstract.
Multi-conjugate adaptive optical (MCAO) systems with from 104 to 105 degrees of freedom have been proposed for future giant telescopes. Using standard matrix methods to compute, optimize, and implement wavefront reconstruction algorithms for these systems is impractical, since the number of calculations required to compute (apply) the reconstruction matrix scales as the cube (square) of the number of AO degrees of freedom. Significant improvements in computational efficiency are possible by exploiting the sparse and/or periodic structure of the calculations. In this paper, we review recent progress in developing an iterative sparse matrix implementation of minimum variance wavefront reconstruction for MCAO. The basic method is preconditioned conjugate gradients, using a multigrid preconditioner incorporating a layer-oriented, iterative smoothing operator. We outline the tilt-removed LGS wavefront measurements and auxiliary full aperture tip/tilt measurements from natural guide stars. Performance predictions for sample natural guide star (NGS) and LGS MCAO systems on 8 and 16 meter class telescopes are also presented.
Keywords: Adaptive optics, wavefront reconstruction, extremely large telescopes