Layer-oriented Multiconjugate Adaptive Optics Research Articles

Operation of a layer-oriented multiconjugate adaptive optics system in the partial illumination regime

Multiconjugate adaptive optics (MCAO) promises uniform wide-field atmospheric correction. However, partial illumination of the layers at which the deformable mirrors are conjugated results in incomplete information about the full turbulence field. We report on a working solution to this difficulty for layer-oriented MCAO, including laboratory and on-sky demonstration with the LINC-NIRVANA instrument at the Large Binocular Telescope. This approach has proven to be simple and stable.

Solar GLAO and TAO: performance comparisons

Multi-conjugate adaptive optics (MCAO), consisting of several deformable mirrors (DMs), can significantly increase the adaptive optics (AO) correction field of view. Current MCAO can be realized by either star-oriented or layer-oriented approaches. For solar AO, ground-layer adaptive optics (GLAO) can be viewed as an extreme case of layer-oriented MCAO in which the DM is conjugated to the ground, while solar tomography adaptive optics (TAO) that we proposed recently can be viewed as star-oriented MCAO with only one DM. Solar GLAO and TAO use the same hardware as conventional solar AO, and therefore it will be important to see which method can deliver better performance. In this article, we compare the performance of solar GLAO and TAO by using end-to-end numerical simulation software. Numerical simulations of TAO and GLAO with different numbers of guide stars are conducted. Our results show that TAO and GLAO produce the same performance if the DM is conjugated to the ground, but TAO can only generate better performance when the DM is conjugated to the best height. This result has important application in existing one-DM solar AO systems.

层向多层共轭自适应光学系统的模拟

The adaptive optics (AO) system in which one turbulence layer is corrected has a good compensation performance only over small field of view. The technology of multi-conjugate adaptive optics (MCAO) can overcome the limitation. The elementary structure and working principle of layer oriented multi-conjugate adaptive optics (LOMCAO) system was presented. Simulation method of LOMCAO system was investigated, including how to generate dynamic turbulence wavefront data, wavefront reconstruction algorithm of pyramid wavefront sensor and close-loop modal control procedure of deformable mirror. Simulations for single layer-conjugate and two layer-conjugate AO systems were carried out. The simulation results show that LOMCAO system has better correction performance over a larger field of view than single-conjugate AO system due to the face that much more guide stars are used and two layer turbulence are compensated in LOMCAO system.

Calibrating the interaction matrix for the LINC-NIRVANA high layer wavefront sensor.

LINC-NIRVANA is a near-infrared Fizeau interferometric imager that will operate at the Large Binocular Telescope. In preparation for the commissioning of this instrument, we conducted experiments for calibrating the high-layer wavefront sensor of the layer-oriented multi-conjugate adaptive optics system. For calibrating the multi-pyramid wavefront sensor, four light sources were used to simulate guide stars. Using this setup, we developed the push-pull method for calibrating the interaction matrix. The benefits of this method over the traditional push-only method are quantified, and also the effects of varying the number of push-pull frames over which aberrations are averaged is reported. Finally, we discuss a method for measuring mis-conjugation between the deformable mirror and the wavefront sensor, and the proper positioning of the wavefront sensor detector with respect to the four pupil positions.

First laboratory results with the LINC-NIRVANA high layer wavefront sensor

In the field of adaptive optics, multi-conjugate adaptive optics (MCAO) can greatly increase the size of the corrected field of view (FoV) and also extend sky coverage. By applying layer oriented MCAO (LO-MCAO) [4], together with multiple guide stars (up to 20) and pyramid wavefront sensors [7], LINC-NIRVANA (L-N for short) [1] will provide two AO-corrected beams to a Fizeau interferometer to achieve 10 milliarcsecond angular resolution on the Large Binocular Telescope. This paper presents first laboratory results of the AO performance achieved with the high layer wavefront sensor (HWS). This sensor, together with its associated deformable mirror (a Xinetics-349), is being operated in one of the L-N laboratories. AO reference stars, spread across a 2 arc-minute FoV and with aberrations resulting from turbulence introduced at specific layers in the atmosphere, are simulated in this lab environment. This is achieved with the Multi-Atmosphere Phase screen and Stars (MAPS) [2] unit. From the wavefront data, the approximate residual wavefront error after correction has been calculated for different turbulent layer altitudes and wind speeds. Using a somewhat undersampled CCD, the FWHM of stars in the nearly 2 arc-minute FoV has also been measured. These test results demonstrate that the high layer wavefront sensor of LINC-NIRVANA will be able to achieve uniform AO correction across a large FoV.

Preconditioned conjugate gradient wave-front reconstructors for multiconjugate adaptive optics.

Multiconjugate adaptive optics (MCAO) systems with 10(4)-10(5) degrees of freedom have been proposed for future giant telescopes. Using standard matrix methods to compute, optimize, and implement wavefront control algorithms for these systems is impractical, since the number of calculations required to compute and apply the reconstruction matrix scales respectively with the cube and the square of the number of adaptive optics degrees of freedom. We develop scalable open-loop iterative sparse matrix implementations of minimum variance wave-front reconstruction for telescope diameters up to 32 m with more than 10(4) actuators. The basic approach is the preconditioned conjugate gradient method with an efficient preconditioner, whose block structure is defined by the atmospheric turbulent layers very much like the layer-oriented MCAO algorithms of current interest. Two cost-effective preconditioners are investigated: a multigrid solver and a simpler block symmetric Gauss-Seidel (BSGS) sweep. Both options require off-line sparse Cholesky factorizations of the diagonal blocks of the matrix system. The cost to precompute these factors scales approximately as the three-halves power of the number of estimated phase grid points per atmospheric layer, and their average update rate is typically of the order of 10(-2) Hz, i.e., 4-5 orders of magnitude lower than the typical 10(3) Hz temporal sampling rate. All other computations scale almost linearly with the total number of estimated phase grid points. We present numerical simulation results to illustrate algorithm convergence. Convergence rates of both preconditioners are similar, regardless of measurement noise level, indicating that the layer-oriented BSGS sweep is as effective as the more elaborated multiresolution preconditioner.