In this paper we speak about the double-axicon unit built for the CaNaPy instrument, the LGS-AO backbone of the ESA ALASCA TRL6 facility, to demonstrate Optical Feeder Links for Satellite Communications in 2023 using Laser Guide Star Adaptive Optics technologies. The ALASCA system will co-propagate a guidestar laser (λ = 589 nm) and an infrared laser (λ = 1075 nm), using the monostatic approach through the entire 1-m Optical Ground Station (OGS) at Teide Observatory, Canary Islands (Spain). Provisions have been made to use either the full aperture or a section of the OGS primary mirror. The OGS telescope secondary mirror would introduce 30% central vignetting losses on the uplink laser beams. In order to minimise the losses, a double-axicon module shapes the gaussian beam as an annulus, thus optimises the laser profile to match the telescope pupil and nulls the losses, achieving the most efficient coupling to the OGS telescope. We present the CaNaPy axicon module design and analysis for the 589-nm laser as well as the ALASCA axicon module design for the OFL; we describe the tests done and the gain achieved in power transmission when shaping the laser compared to propagating a conventional Gaussian beam through a telescope with a non-negligible central obstruction.
The Multi-conjugate Adaptive Optics RelaY (MAORY) is one of the key Adaptive Optics (AO) systems on the Extremely Large Telescope (ELT). MAORY aims to achieve a good wavefront correction over a large field of view, which involves a tomographic estimation of the 3D atmospheric wavefront disturbance. Mathematically, the reconstruction of turbulent layers in the atmosphere is severely ill-posed, hence, it limits the achievable reconstruction accuracy. Moreover, the reconstruction has to be performed in real-time at a few hundred to one thousand Hertz frame rates. In this talk we focus on the iterative Finite Element Wavelet Hybrid Algorithm (FEWHA). The key feature of FEWHA is a matrix-free representation of all underlying operators, which makes the algorithm fast and enables on the fly parameter updates. We show the performance of the algorithm regarding reconstruction quality and run-time for the MAORY instrument via numerical simulations.
The Multi-conjugate Adaptive Optics RelaY (MAORY) is one of the key adaptive optics (AO) systems on the European Southern Observatory’s Extremely Large Telescope. MAORY aims to achieve good wavefront correction over a large field of view, which involves a tomographic estimation of the three-dimensional atmospheric wavefront disturbance. Mathematically, the reconstruction of turbulent layers in the atmosphere is severely ill-posed, hence, limits the achievable reconstruction accuracy. Moreover, the reconstruction has to be performed in real time at a few hundred to one thousand hertz frame rates. Huge amounts of data have to be processed and thousands of actuators of the deformable mirrors have to be controlled by elaborated algorithms. Even with extensive parallelization and pipelining, direct solvers, such as the matrix vector multiplication method, are extremely demanding. Thus, research in recent years shifted into the direction of iterative methods. We focus on the iterative finite-element wavelet hybrid algorithm (FEWHA). The key feature of FEWHA is a matrix-free representation of all operators involved, which makes the algorithm fast and enables on-the-fly system updates whenever parameters at the telescope or in the atmosphere change. We provide a performance analysis of the method regarding quality and run-time for the MAORY instrument using the AO software package COMPASS.
The new generation of ground-based extremely large telescopes rely on adaptive optics (AO). Many AO systems require the reconstruction of the turbulence profile, which is called atmospheric tomography. Due to the growth of telescope sizes the computational load for this problem is increasing drastically. Thus, the collaboration of state-of-the-art real-time hardware with an efficient solver that take advantage of the available hardware resources is of great importance. In this talk, we look at an iterative approach called FEWHA and its adaption to perform best on real-time hardware. We conclude our talk with a comparison between FEWHA and the frequently used MVM within the framework of MAORY.
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