Reconstruction and control laws for multi-conjugate adaptive optics in astronomy

The optical resolution of ground-based astronomical telescopes is in principle limited by the atmospheric turbulence. Adaptive optics is a technique that enables high-resolution imaging from the ground by compensating in real-time for the phase perturbations introduced by atmospheric turbulence. One of the major limitations of single-conjugate adaptive optics (SCAO) is the fact that compensation is only attainable in a small field of view due to anisoplanatism. Multi-conjugate adaptive optics (MCAO) is a technique that was conceived to overcome this limitation. This is achieved by the use of several wavefront sensors (WFSs) to probe the atmospheric volume in different directions, and several deformable mirrors (DMs) optically conjugated at different altitudes to compensate for the phase perturbations introduced by the atmospheric volume. Spatial reconstruction in MCAO refers to the problem of estimating from the WFSs measurements the three-dimensional distribution of the atmospheric-turbulence phase perturbations. We present a review of the deterministic and the statistical estimation methods to solve the reconstruction problem in MCAO by describing the problem within the formalism of inverse problems. Then, we have used this formalism to study and fully characterize the propagation of the remaining error —also known as generalized aliasing— in MCAO. We have also studied the application of modal gain optimization in MCAO, and we have shown that the generalized aliasing in MCAO poses a shortcoming to the generalization of this control technique to MCAO. In the framework of the Multi-conjugate Adaptive optics Demonstrator (MAD) project, we have participated in the experimental validation of the MCAO concept in the laboratory. We present the high-flux optimization of the MAD system and a comparison of simulation and experimental results.

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