Epivascular microstructures, a potential biomarker for retinal diseases, are investigated in the living human retina using adaptive optics optical coherence tomography (AO-OCT). The AO correction is driven by a four-sided pyramid wavefront sensor with a loop bandwidth of 30 Hz. In order to achieve a stable placement of the focus of the imaging beam in the desired retinal layer, a new concept for focus shifting is introduced which uses an in vivo calibration routine that is performed pre-imaging in each subject. The capability of the instrument is demonstrated by visualizing hyporeflective microstructures situated along the retinal vasculature with single volume AO-OCT images recorded at an extended 4° x 4° field of view.
We present a novel type of nonlinear reconstructor for all Fourier-type wavefront sensors like the Pyramid Wavefront Sensor. Different to interaction matrix approaches which critically degrade image quality due to approximation errors in nonlinear regimes, the new wavefront estimation algorithm has been designed to be robust in such frameworks. It works by employing an iterative technique to circumvent the major drawbacks associated with linear methods. A significant advantage to this approach is that the developed nonlinear algorithm is a generalised wavefront reconstruction method meaning that the reconstructor is directly applicable to any Fourier-type WFS.
Pyramid wavefront sensors are planned to be a part of many instruments that are currently under development for the extremely large telescopes (ELT). The unprecedented scales of the upcoming ELT-era instruments are inevitably connected with serious challenges for wavefront reconstruction and control algorithms. Apart from the huge number of correcting elements to be controlled in real-time, real-life features such as the segmentation of the telescope pupil, the low wind effect, the nonlinearity of the pyramid sensor, and the noncommon path aberrations will have a significantly larger impact on the imaging quality in the ELT framework than they ever had before. We summarize various kinds of wavefront reconstruction algorithms for the pyramid wavefront sensor. Based on several forward models, different algorithms were developed in the last decades for linear and nonlinear wavefront correction. The core ideas of the algorithms are presented, and a detailed comparison of the presented methods with respect to underlying pyramid sensor models, computational complexities, and reconstruction qualities is given. In addition, we review the existing and possible solutions for the above-named real-life phenomena. At the same time, directions for further investigations are sketched.
The generation of Extremely Large Telescopes (ELTs) with mirror diameters up to 40 m has thick secondary mirror support structures (also known as spider legs), which cause difficulties in the wavefront reconstruction process. These spider legs create areas where the information of the phase is disconnected on the wavefront sensor detector, leading to pupil fragmentation and a loss of data on selected subapertures. The effects on wavefront reconstruction are differential pistons between segmented areas, leading to poor wavefront reconstruction. The resulting errors make the majority of existing control algorithms unfeasible for telescope systems having spider legs incorporated. A solution, named the split approach, is presented, which suggests to separate reconstruction of segment piston modes from the rest of the wavefront. Further, two methods are introduced for the direct reconstruction of the segment pistons. Due to the separate handling of the piston offsets on the segments, the split approach makes any of the existing phase reconstruction algorithms developed for nonsegmented pupils suitable for wavefront control in the presence of telescope spiders. We present end-to-end simulation results showing accurate, stable, and extremely fast wavefront reconstruction for the first light instrument mid-infrared ELT imager and spectograph of the ELT that is currently under construction.
MICADO will enable the ELT to perform diffraction limited near-infrared observations at first light. The instrument’s capabilities focus on imaging (including astrometric and high contrast) as well as single object spectroscopy. This contribution looks at how requirements from the observing modes have driven the instrument design and functionality. Using examples from specific science cases, and making use of the data simulation tool, an outline is presented of what we can expect the instrument to achieve.
The new generation of ground-based telescopes relies on real-time adaptive optics systems to compensate for atmospheric perturbations arising during the imaging process. Pyramid wavefront sensors are planned to be part of many instruments currently under development for ELT-sized telescopes. The high number of correcting elements to be controlled in real-time and the segmented pupils of the ELTs lead to unprecedented challenges posed to the control algorithms. Based on various (approximate) models, several algorithms were developed in the last decades for linear and non-linear wavefront correction from pyramid sensor data. Among those, we emphasize interaction-matrix-based approaches, Fourier domain methods, iterative algorithms, and algorithms based on the inversion of the Finite Hilbert transform. We briefly present the core ideas of the algorithms and provide the necessary theoretical background like, e.g., the Fourier domain filters, or the direct inversion formulas. We give a detailed comparison of the presented methods with respect to underlying pyramid sensor models, the computational complexities, and reconstruction qualities. The performance of our algorithms is demonstrated in the context of an XAO system on the EPICS instrument and a SCAO system on the METIS instrument on the ELT. In the simulations, realistic features as the ELT spiders and the hexagonal M4 geometry are partially taken into account.
In the design of the future generation ELTs the support structures for the secondary mirror (also known as spiders) lead to a piston on each of the pupil segments created by the spiders, known as ”island effect”. In this talk we focus on fast and stable reconstruction methods to cope with the island effect. We present and compare wavefront reconstruction algorithms and highlight their performance in a METIS- like AO system. We focus on FEWHA (Finite Element-Wavelet Hybrid Algorithm), Poke Matrix Inversion using a set of predefined DM influence functions and new methods for a direct segment piston estimation in combination with the P-CuReD (Preprocessed Cumulative Reconstructor with Domain decomposition). The results are backed up by Octopus (the full AO end-to-end simulator from ESO) simulations highlighting stable Strehl ratios for our simulation setting.
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